bioconversion of sugarcane bagasse and soybean …

BIOCONVERSION OF SUGARCANE BAGASSE AND

SOYBEAN HULLS FOR THE PRODUCTION OF A

GENERIC MICROBIAL FEEDSTOCK

A thesis submitted to The University of Manchester

for the degree of Doctor of Philosophy

in the Faculty of Engineering and Physical Sciences

2015

CHEN-WEI CHANG

Satake Centre for Grain Process Engineering

School of Chemical Engineering and Analytical Science

The University of Manchester, UK

Table of contents

i

Table of contents

List of tables ................................................................................................... vii

List of figures ................................................................................................... ix

List of abbreviations and acronyms ................................................................ xix

Abstract ......................................................................................................... xx

Declaration ................................................................................................... xxi

Copyright statement .................................................................................... xxii

Acknowledgements ..................................................................................... xxiii

CHAPTER 1 Introduction................................................................................ 1

Background .............................................................................................. 1

Structure of the thesis ............................................................................. 4

CHAPTER 2 Literature review ........................................................................ 5

The need for bioeconomy development ................................................. 5

The biorefinery concept .......................................................................... 5

Lignocellulosic feedstocks ....................................................................... 7

2.3.1 Sugarcane bagasse .......................................................................... 12

2.3.2 Soybean hulls ................................................................................... 14

Pretreatment of lignocellulosic materials ............................................. 15

2.4.1 Physical pretreatment ..................................................................... 18

2.4.2 Chemical pretreatment ................................................................... 18

2.4.3 Physico-Chemical pretreatment ...................................................... 19

2.4.4 Biological pretreatment .................................................................. 20

Solid state fermentation........................................................................ 21

2.5.1 Fungal growth in SSF ....................................................................... 22

2.5.2 Lignocellulose feedstock ................................................................. 24

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ii

2.5.3 Biomass estimation in SSF ............................................................... 26

2.5.3.1 Metabolic activities of biomass ............................................... 26

2.5.3.2 Dielectric properties of cells .................................................... 26

2.5.3.3 Biomass components ............................................................... 28

2.5.4 Fermentation conditions ................................................................. 29

2.5.4.1 Effect of nutrition ..................................................................... 29

2.5.4.2 Effect of particle size and porosity........................................... 29

2.5.4.3 Effect of temperature .............................................................. 31

2.5.4.4 Effect of moisture content and water activity ......................... 32

2.5.4.5 Effect of pH .............................................................................. 34

2.5.4.6 Effect of aeration ..................................................................... 34

2.5.5 Reactor ............................................................................................ 35

2.5.6 Mathematical models of SSF ........................................................... 38

2.5.7 Application of SSF ............................................................................ 39

Enzymatic hydrolysis of lignocellulose .................................................. 41

Microbial feedstock production ............................................................ 44

2.7.1 Reducing sugars production from lignocellulose ............................ 44

2.7.2 The nutrient-rich microbial feedstock production .......................... 48

2.7.2.1 Process description .................................................................. 48

2.7.2.2 Fungal autolysis ........................................................................ 49

CHAPTER 3 Objectives and research programme.......................................... 52

Introduction ........................................................................................... 52

Proposed bioprocess concept ............................................................... 53

Research objectives ............................................................................... 55

3.3.1 Growth and adaptation of T. longibrachiatum ............................... 55

3.3.2 Sequential hydrolysis of fermented solids ...................................... 55

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iii

3.3.3 Bioreactor Studies ........................................................................... 56

3.3.4 Ethanol production from bagasse derived feedstock ..................... 56

CHAPTER 4 Materials and methods ............................................................. 57

Introduction ........................................................................................... 57

Materials and microorganisms .............................................................. 57

4.2.1 Sugarcane Bagasse and Soybean Hull ............................................. 57

4.2.2 Microorganisms and inoculum preparation .................................... 58

4.2.2.1 Microorganism used in solid state fermentation .................... 58

4.2.2.2 Microorganism used for ethanol fermentation ....................... 60

Reactor systems .................................................................................... 60

4.3.1 Petri dish .......................................................................................... 60

4.3.2 Circular tray bioreactor ................................................................... 60

4.3.3 Multi-layer tray bioreactor .............................................................. 62

4.3.4 Packed-bed bioreactor .................................................................... 63

4.3.5 Enzyme hydrolysis and fungal autolysis system .............................. 64

4.3.6 Ethanol fermentation system .......................................................... 64

Analytical methods ................................................................................ 65

4.4.1 Fungal spore count .......................................................................... 65

4.4.2 Analysis of the moisture content of materials ................................ 66

4.4.3 Properties of solid substrate ........................................................... 67

4.4.4 Scanning electron microscope (SEM) .............................................. 69

4.4.5 Thermogravimetric Analysis (TGA) .................................................. 69

4.4.6 Analysis of glucose .......................................................................... 70

4.4.7 Total reducing sugars ...................................................................... 70

4.4.8 Composition analysis of solid substrate .......................................... 72

4.4.9 Free amino nitrogen ........................................................................ 74

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iv

4.4.10 Inorganic Phosphorous (IP) ............................................................. 77

4.4.11 pH .................................................................................................... 79

4.4.12 Enzyme activity ................................................................................ 79

4.4.12.1 Cellulase activity ...................................................................... 79

4.4.12.2 Xylanase activity ....................................................................... 82

4.4.12.3 Beta-glucosidase activity.......................................................... 84

4.4.13 Ethanol ............................................................................................ 86

CHAPTER 5 Production of a generic feedstock: solid-state fermentation ...... 87

Introduction ........................................................................................... 87

The characteristics of the substrates .................................................... 88

5.2.1 Chemical composition ..................................................................... 88

5.2.2 Bed Porosity .................................................................................... 89

5.2.3 Water evaporation .......................................................................... 91

Effect of washing procedure on sugarcane bagasse ............................. 95

Effect of particle size on sugarcane bagasse ......................................... 97

Influence of nitrogen supplement on SSF ........................................... 100

Effect of mixed substrates on SSF ....................................................... 106

Effect of environmental humidity on SSF (in petri dishes) ................ 114

Effect of incubation time on sequential enzyme hydrolysis ............... 122

Summary ............................................................................................. 125

CHAPTER 6 Production of a generic feedstock: subsequent hydrolysis ....... 126

Introduction ......................................................................................... 126

Solid to liquid ratio effect .................................................................... 127

Temperature and pH effect ................................................................. 131

The effect of microbial inhibitor on further hydrolysis ...................... 134

Fungal autolysis ................................................................................... 137

Table of contents

v

Kinetics of further hydrolysis............................................................... 139

Characterisation of optimal reaction temperature and pH of the crude

enzymes from SSF............................................................................................ 142

Summary .............................................................................................. 144

CHAPTER 7 Production of a generic feedstock: bioreactor studies .............. 146

Introduction ......................................................................................... 146

Bioreactor studies ............................................................................... 146

7.2.1 Multi-layer tray bioreactor studies ............................................... 147

7.2.2 Packed-bed bioreactor studies ...................................................... 153

7.2.2.1 Profile of fermentation .......................................................... 153

7.2.2.2 Water and energy balance in the packed-bed bioreactor ..... 159

7.2.2.2.1 Water balance ................................................................... 161

7.2.2.2.2 Energy balance .................................................................. 163

7.2.2.2.3 Model validation ................................................................ 166

Growth kinetics in SSF systems ........................................................... 169

7.3.1 Glucosamine production ............................................................... 170

7.3.2 The respiratory gas model ............................................................. 177

Characteristics of fermented solids during SSF ................................... 184

7.4.1 Microscopic observation ............................................................... 184

7.4.2 Thermogravimetric analysis .......................................................... 189

Summary .............................................................................................. 192

CHAPTER 8 Evaluation of the generic feedstock .......................................... 193

Introduction ......................................................................................... 193

Ethanol fermentation .......................................................................... 193

Material balance for Ethanol production using generic microbial

feedstock ......................................................................................................... 199

Table of contents

vi

Summary ............................................................................................. 201

CHAPTER 9 Conclusions and recommendations ......................................... 202

Conclusions .......................................................................................... 202

Recommendations for further work ................................................... 206

References ................................................................................................... 208

Word count: 55,651

List of tables

vii

List of tables

Table 2.1 Chemical composition of common lignocellulosic residues and wastes 9

Table 2.2 List of fungal species used in the biological pretreatment of

lignocellulosic materials ........................................................................................ 20

Table 2.3 Advantage and disadvantage of SSF (Robinson et al., 2001) ............... 24

Table 2.4 Commercial cellulases produced by companies and their sources ...... 40

Table 2.5 Total reducing sugars from bagasse after different pretreatments and

enzymatic hydrolysis ............................................................................................. 46

Table 4.1 List of ingredients of DNS reagent ......................................................... 71

Table 5.1 Composition of sugarcane bagasse and soybean hull on dry basis ..... 88

Table 5.2 Bed porosity of Sugarcane bagasse and Soybean hull particles........... 90

Table 5.3 Values of effective diffusivity obtained for different particle sizes of

sugarcane bagasse and soybean hull .................................................................... 93

Table 5.4 C/N ratio of mixed-substrates culture medium .................................. 101

Table 5.5 Composition of mixed-substrates culture medium ............................. 107

Table 5.6 Values of effective diffusivities obtained with different environmental

humidities on solid state fermentation ............................................................... 118

Table 5.7 Celluloytic enzyme activities produced by T. longibrachiatum ........... 124

Table 6.1 Broth composition after 48 h of fungal autolysis ................................ 139

Table 6.2 kinetic model of further hydrolysis ..................................................... 141

Table 6.3 Characteristics of hydrolytic enzymes from T. longibrachiatum grown

on sugarcane bagasse and soybean hull ............................................................. 144

Table 7.1 Results of analysis featuring differences with different trays after 120 h

of fermentation ................................................................................................... 152

List of tables

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Table 7.2 Results of further hydrolysis featuring differences with different trays

after 120 h of fermentation ................................................................................ 153

Table 7.3 Results of further hydrolysis featuring differences with different levels

after 120 h of fermentation ................................................................................ 159

Table 8.1 Ethanol fermentations of S. cerevisiae on different media ................ 195

Table 8.2 Ethanol yield and media consumption of fermentation using S.

cerevisiae ............................................................................................................. 195

Table 8.3 Ethanol yields for different lignocellulosic materials pretreatment ... 198

Table 9.1 Operating parameters for operation in the production of ethanol from

sugarcane bagasse and soybean hulls ................................................................ 205

List of figures

ix

List of figures

Figure 2.1 A schematic of biorefinery processes .................................................... 6

Figure 2.2 Structure of lignocellulosic biomass ....................................................... 9

Figure 2.3 Structure of cellulose (A) β -(1-4) glycosidic bonds (B)Schematic

structure of fibre .................................................................................................. 10

Figure 2.4 A sugarcane plant ................................................................................. 13

Figure 2.5 Solid wastes generated in cane sugar production ............................... 14

Figure 2.6 A schematic of the conversion of lignocellulosic biomass to chemicals

............................................................................................................................... 15

Figure 2.7 Schematic of goals of pretreatment on lignocellulosic materials ........ 16

Figure 2.8 Schematic of some micro-scale processes that occur during solid-state

fermentation ......................................................................................................... 23

Figure 2.9 Number of papers and year of publication containing the term “solid

state fermentation + lignocellulose” ..................................................................... 25

Figure 2.10 Effect of particle size and shape on the bed porosity ........................ 30

Figure 2.11 Physical meaning of the porosity (void fraction) and bed packing

density ................................................................................................................... 31

Figure 2.12 Isotherms of solids used in solid-state fermentation (- - -) Desorption

isotherm of autoclaved wheat grains at 35°C; (-) Isotherm of corn at 20°C (lower

curve), 35°C (middle curve) and 50°C (upper curve) ............................................. 34

Figure 2.13 Basic design features of the diverse solid-state fermentation

bioreactors. ........................................................................................................... 36

Figure 2.14 The marcoscale and microscale process happened within an SSF

bioreactor. ............................................................................................................. 38

List of figures

x

Figure 2.15 Flow diagram of polysaccharides and the hydrolytic enzymes used to

cleave them into shorter polymers and simple sugars ......................................... 42

Figure 2.16 Processes scheme of fermentable sugars production from

lignocellulose ......................................................................................................... 45

Figure 2.17 Schematic diagram of a sugar production based on the biological

pretreatment of lignocellulose.............................................................................. 47

Figure 2.18 Overview of fungi autolysis ................................................................ 50

Figure 3.1 Proposed process for a generic microbial feedstock production from

lignocellulose ......................................................................................................... 54

Figure 4.1 Appearance of (a) sugarcane bagasse and (b) soybean hull ................ 58

Figure 4.2 Trichoderma Longibrachiatum on PDA medium agar plate ................ 59

Figure 4.3 Left: A circular tray bioreactor. Right: A perspective view of bioreactor

............................................................................................................................... 61

Figure 4.4 A diagram of the system developed for on-line automated monitoring

of solid state fermentation (1) Regulated pressure air inlet; (2) 0.2 µm filter (3)

humidifier; (4) air distributor; (5) Circular tray fermenters; (6) Silica gel tube (7)

Gas analyser. ......................................................................................................... 61

Figure 4.5 Left: A multi-layer trays bioreactor. Right: A perspective view of

bioreactor .............................................................................................................. 62

Figure 4.6 Schematic diagram of the multi-layer tray bioreactor system (1)

Compressed air, (2) air flow meter, (3) 0.2 µm air filter, (4) humidifier, (5) water

bath at 30°C, (6) incubator at 30°C, (7) multi-layer circular bioreactor, (8) silica

gel, (9) thermocouples type K, (10) temperature data logger, (11) gas analyser,

(12) computer ........................................................................................................ 63

List of figures

xi

Figure 4.7 Schematic diagram of the 1.5 L packed-bed bioreactor system (1)

Compressed air, (2) air flow meter, (3) 0.2 µm air filter, (4) humidifier, (5) water

bath at 30°C, (6) relative humidity data logger, (7) incubator at 30°C, (8) packed-

bed bioreactor, (9) thermocouples type K, (10) temperature data logger, (11)

silica gel, (12) gas analyser, (13) computer ........................................................... 64

Figure 4.8 Spores counting on haemocytometer .................................................. 66

Figure 4.9 Spores of Trichoderma Longibrachiatum on Haemocytometer grid

(magnification 100X) ............................................................................................. 66

Figure 4.10 Porosity ............................................................................................... 68

Figure 4.11 A standard calibration curve for reducing sugar concentration

(maltose)................................................................................................................ 72

Figure 4.12 A standard calibration curve for free amino nitrogen (FAN)

concentration ........................................................................................................ 77

Figure 4.13 A standard calibration curve for inorganic phosphorous (IP)

concentration ........................................................................................................ 78

Figure 4.14 A standard calibration curve for glucose concentration .................... 81

Figure 4.15 Calculation of FPU from a plot of enzyme dilution vs glucose

concentration ........................................................................................................ 82

Figure 4.16 A standard curve for measuring xylose concentration ...................... 84

Figure 5.1 Sugarcane bagasse at different particle sizes under a USB microscope,

2X magnification (a) 2-1.4 mm (b) 1.4-0.85 mm (c) 0.85-0.5 mm (d) 0.5-0.21 mm

............................................................................................................................... 91

Figure 5.2 The drying curve of sugarcane bagasse and soybean hull ................... 92

List of figures

xii

Figure 5.3 SSF using Trichoderma longibrachiatum on (a) washed and (b) non-

washed sugarcane bagasse after 5 days ............................................................... 96

Figure 5.4 Effect of washing process on nutrients production via solid state

fermentation and subsequent hydrolysis ............................................................. 97

Figure 5.5 Images of fungi growth on different particle sizes of sugarcane bagasse

with soybean hull (2X magnification, USB Microscope) ....................................... 98

Figure 5.6 Effect of particle size on nutrients production via solid state

fermentation and subsequent hydrolysis ............................................................. 99

Figure 5.7 SSF using Trichoderma longibrachiatum on different amount of

nitrogen supplement on sugarcane bagasse after 5 days .................................. 102

Figure 5.8 Dry weight loss of 5 days solid state fermentation with different

amount of nitrogen supplement ......................................................................... 103

Figure 5.9 Effect of different amounts of nitrogen supplement on sugar

production via solid state fermentation (SSF) or sequential bioprocessing (SSF +

hydrolysis). Error bars indicate ranges between duplicate samples. ................. 104

Figure 5.10 Average saccharification yield in subsequent hydrolysis (SSF +

hydrolysis) with different proportion of nitrogen added. Letters a b c and d

represent significantly different (p<0.05) groups of data ................................... 105

Figure 5.11 Effect of different amounts of nitrogen supplement on FAN

production via solid state fermentation (SSF) or solid state fermentation plus

sequential bioprocessing (SSF + hydrolysis) ........................................................ 106

Figure 5.12 Growth of Trichoderma longibrachiatum on different mixed substrate

ratios (a) 1:0, SB:SH (b) 8:2, SB:SH (c) 6:4, SB:SH (d) 5:5, SB:SH (e) 2:8, SB:SH (f)

0:1, SB:SH. ........................................................................................................... 108

List of figures

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Figure 5.13 Growth of Trichoderma longibrachiatum on mixed substrates at a

ratio of 6:4 (SB:SH) .............................................................................................. 109

Figure 5.14 Dry weight loss of the solids after 5 days fermentation with different

mixed substrate ratios ......................................................................................... 110

Figure 5.15 Effect of mixed substrates ratio on sugar production via solid state

fermentation (SSF) or sequential bioprocessing (SSF + hydrolysis) .................... 111

Figure 5.16 Average sugar yield in subsequent hydrolysis after 5 days of growth

on substrate consisting of mixtures of sugarcane bagasse and soybean hull with

different carbon/nitrogen ratios. Different letters represent groups with

significant differences (p<0.05) ........................................................................... 112

Figure 5.17 Effect of mixed substrate ratios on FAN production via solid state

fermentation (SSF) or sequential bioprocessing (SSF + hydrolysis) .................... 113

Figure 5.18 Water balance in a solid state fermentation using petri dish system

............................................................................................................................. 115

Figure 5.19 The moisture ratio of non-fermented solids under different

environmental relative humidity (35 and 75%) .................................................. 116

Figure 5.20 The moisture ratio of solid state fermentation under different

environmental relative humidity (35 and 75%) .................................................. 117

Figure 5.21 Effect of the relative humidity on SSF after 3 days (a) 75% (b) 35%

showing top (left) and bottom (right) views ....................................................... 120

Figure 5.22 Effect of the relative humidity on SSF after 5 days (a) 75% (b) 35% 121

Figure 5.23 Effect of environmental humidity level on sugar and FAN production

via sequential bioprocessing (SSF + hydrolysis) .................................................. 122

List of figures

xiv

Figure 5.24 Effect of SSF incubation time on Sugar and FAN production via

sequential bioprocessing (SSF + hydrolysis) ........................................................ 124

Figure 6.1 Post-fermentation hydrolysis of bagasse at different solid loadings (2,

4, 6, 8, 10 and 12 g) into 100 mL citric buffer solution ....................................... 128

Figure 6.2 Effect of substrate concentration on sugar production in subsequent

hydrolysis of fermented bagasse/SBH solids ...................................................... 129

Figure 6.3 Effect of substrate concentration on FAN production in subsequent

hydrolysis of fermented bagasse/SBH solids ...................................................... 130

Figure 6.4 Effect of temperature and pH on sugar production during 48h further

hydrolysis after solid state fermentation ............................................................ 133

Figure 6.5 Effect of temperature and pH on FAN production during further


Figure 6.6 possible fungal growth during enzymatic hydrolysis and autolysis at

40°C, pH 6 ............................................................................................................ 134

Figure 6.7 Effect of microbial inhibitor on sugar production during further


Figure 6.8 Effect of microbial inhibitor on FAN production during further


Figure 6.9 Cytoplasm degradation during the autolysis/hyrolysis of fermented

solids at 50°C, pH 4.8 ........................................................................................... 138

Figure 6.10 Profiles of further hydrolysis of the fermented solids at 50°C. The

solid lines are generated by equation 6-1 to predict the production of reducing

sugar, FAN and IP ................................................................................................ 140

List of figures

xv

Figure 6.11 Lignocellulose degradation after 48 h autolysis/hydrolysis of

fermented solids at 50°C, pH 4.8 citric buffer ..................................................... 141

Figure 6.12 Effect of pH at 50°C on crude enzymes activity ............................... 143

Figure 6.13 Effect of temperature at pH 4.8 on crude enzymes activity ............ 143

Figure 7.1 Multi-layer tray bioreactor ................................................................. 147

Figure 7.2 Temperature profile at the different trays of the multi-tray bioreactor

during fermentation ............................................................................................ 149

Figure 7.3 Respiratory profile of the OUR and CER during solid state fermentation

in the multi-layer tray bioreactor ........................................................................ 150

Figure 7.4 Respiratory quotient (RQ) profile during solid state fermentation in the

multi-layer tray bioreactor .................................................................................. 151

Figure 7.5 Packed-bed reactor placed in the incubator ...................................... 155

Figure 7.6 Temperature profile at different positions in the packed-bed

bioreactor during fermentation .......................................................................... 156

Figure 7.7 Respiratory profile of the OUR and CER during solid state fermentation

in the packed-bed bioreactor .............................................................................. 157

Figure 7.8 Respiratory quotient (RQ) profile during the solid state fermentation in

the packed-bed bioreactor .................................................................................. 158

Figure 7.9 Comparison between predicted (line) and experimental (symbol) dry

weight change in the packed-bed bioreactor during the course of fermentation

............................................................................................................................. 167

Figure 7.10 Comparison between predicted (line) and experimental (symbol)

average water content of bed during the course of fermentation..................... 168

List of figures

xvi

Figure 7.11 Comparison between predicted (dotted line) and experimental (solid

line) average bed temperature during the course of fermentation ................... 168

Figure 7.12 Time course of solid state fermentation by T. longibrachiatum, using

a circular tray bioreactor system ........................................................................ 171

Figure 7.13 Experimental (symbols) and predicted (line) for glucosamine

(biomass concentration) during 7 days solid state fermentation As shown in

Figure 7-13, the logistic equation predicted the fungal biomass fairly accurately,

with a short lag phase during the first 24 h, an exponential growth phase that last

until 120 h of incubation and a deceleration growth phase. Maximum specific

growth rates (μm) depend on the particular SSF system, substrate type and

microorganism used. The μm and Xm for T. longibrachiatum cultivated in the

Circular tray bioreactor system here were calculated to be 0.023 h-1 and 0.088

g/g substrate, respectively (Equation 7-24). A wide range of maximum specific

growth rates has been reported, from 0.027 h-1 (Santos et al., 2003) to 0.05 h-1

(Membrillo et al., 2011) using sugarcane bagasse as substrate for solid state

fermentation. This indicates that the utilisations of recalcitrant lignocellulose like

sugarcane bagasse as a carbon source is slower than other agricultural wastes,

for example, wheat bran, where 0.15 h-1 was obtained for Trichoderma reesei

(Smits et al., 1998). .............................................................................................. 173

Figure 7.14 Correlation between total carbohydrate loss and biomass generation

(glucosamine) during 7 days solid state fermentation ....................................... 174

Figure 7.15 Experimental (Symbols) and predicted (line) total carbohydrate

consumption during 7 days solid state fermentation ......................................... 175

List of figures

xvii

Figure 7.16 Correlation between total carbohydrate loss and dry matter weight

loss during 7 days solid state fermentation ........................................................ 176

Figure 7.17 Correlation between dry matter weight loss and cumulative CO2

evolution .............................................................................................................. 177

Figure 7.18 Profile for T. longibrachiatum growth during 7days solid state

fermentation (a) Accumulated CO2 and CO2 evolution rate (b) biomass growth

(glucosamine) ...................................................................................................... 179

Figure 7.19 Profile of T. longibrachiatum growth, as glucosamine concentration

(symbols) and simulation (line) during 7days solid state fermentation using

circular tray bioreactor ........................................................................................ 181


(symbols) and simulation (line) during 5 days solid state fermentation using

multi-layer tray bioreactor .................................................................................. 182


(symbols) and simulation (line) during 5 days solid state fermentation using

packed-bed bioreactor ........................................................................................ 183

Figure 7.22 Change in biomass distribution during a static SSF process with a

fungus. (a) Growth to cover the particle surface during the early stages of the

fermentation, shown with an overhead view of the particle surface. (b)

Development of aerial and penetrative hyphae during the late phase of the

fermentation, shown with a side view of a cut through two particles. (adapted

from (Mitchell et al., 2006) ................................................................................. 185

List of figures

xviii

Figure 7.23 Fermented solids of T. longibrachiatum after 5 days fermentation

using a multi-tray bioreactor with moist air aeration (a) fungal cake (b) aerial

hyphae intermeshed above the surface ............................................................. 186

Figure 7.24 SEM image of a sugarcane bagasse structure, showing rigid and

highly ordered fibrils ........................................................................................... 187

Figure 7.25 SEM image of mixed sugarcane bagasse and soybean hull after 120 h

of fermentation covered by hyphae of Trichoderma longibrachiatum .............. 188

Figure 7.26 SEM image of mixed sugarcane bagasse and soybean hull after 120 h

of fermentation covered by spores of Trichoderma longibrachiatum ............... 189

Figure 7.27 TG and DTG analysis of (a) untreated substrates (b) treated

substrates ............................................................................................................ 191

Figure 8.1 Material balance for the SSF-based process showing the lignocellulose

(600 g of sugarcane bagasse and 400 g of soybean hull) to ethanol conversion

yield. Calculations were based on the average ethanol yield (0.31 g/g total

reducing sugar consumed) for fermentation using hydrolysate. The ratio of SSF

solids to water was 4% (w/w) in the simultaneous hydrolysis and fungal autolysis

to produce a suitable generic microbial feedstock for ethanol fermentation. .. 199

List of abbreviations and acronym

xix

List of abbreviations and acronyms

μm micrometre(s)

µL microliter(s)

aw water activity

C/N ratio carbon to nitrogen ratio

CER carbon dioxide evolution rate

DNS 3,5-dinitrosalicylic acid

DTG derivative thermogravimetric analysis

FAN free amino nitrogen

FPU filter paper unit

g gram(s)

h hour(s)

IP inorganic phosphorus

kg kilogram(s)

L litre(s)

LAP laboratory analytical procedure

mg milligram(s)

mL millilitre(s)

mm millimetre(s)

mm2 square millimetre(s)

mm3 cubic millimetre(s)

OUR oxygen uptake rate

rpm round per minute

RQ respiratory quotient

SB sugarcane bagasse

SCGPE Satake Centre for Grain Process Engineering

SEM scanning electron microscope

SH soybean hull

SmF submerged fermentation

List of abbreviations and acronym

xx

SSF solid-state fermentation

U enzyme activity unit

USB universal serial bus

USD United states dollar(s)

v/v volume by volume

w/w weight by weight

X magnification factor

YD yeast extract solution supplemented with glucose

YDX yeast extract solution supplemented with glucose and xylose

Abstract The University of Manchester

xx

Bioconversion of sugarcane bagasse and soybean hulls for the production of a generic microbial feedstock

Abstract Lignocellulose, mostly from agricultural and forestry resources, is a potential renewable material for sustainable development of biorefineries. From previous studies, reducing sugar production through biological pretreatment involves two steps: solid-state fermentation (SSF) for delignification, followed by enzymatic hydrolysis by adding celluloytic enzymes (cellulase and xylanase etc.). In the process described in this thesis, the necessary enzymes are produced in-situ and the hydrolysis proceeds directly after the solid-state fermentation. Enzyme hydrolysis releases free amino nitrogen (FAN), reducing sugar and many other potential nutrients from the fermented materials. This method additionally avoids the need for removal of inhibitors compared with conventional chemical pretreatment processes. A range of solid-state fermentations were carried out to investigate the effect of washing procedure, particle size and nitrogen supplement on Trichoderma longibrachiatum growth. From these preliminary studies it was concluded that nitrogen supplementation is a crucial factor to improve significantly the fungi growth and production of feedstock using sugarcane bagasse as raw material. In order to evaluate the influence of environmental humidity on petri dish experiments, moist environments were investigated, with over 75% relative humidity to limit water evaporation from solid-state fermentation. The results showed that moist environments gave approximately 1.85 times the reducing sugar yield than dry environments. The process of simultaneous enzymatic hydrolysis of substrates and fungal autolysis were also studied. The degree of hydrolysis was affected by initial fermented solid to liquid ratio, temperature and pH range. The optimal conditions for subsequent hydrolysis of fermented solids were determined. The optimal solid to liquid ratio, 4% (w/w), temperature 50°C and pH 7 were established. The highest final reducing sugar, 8.9 g/L and FAN, 560 mg/L, were measured after 48 h. The fungal autolysis was identified by image analysis as well as by the consumption of nutrient and the release of free amino nitrogen and phosphorous. Solid state fermentation in a multi-layer tray bioreactor and a packed-bed bioreactor were also developed, with moist air supply for oxygen provision and heat removal. Fermented solids in the multi-layer bioreactor led to the highest subsequent hydrolysis yield on reducing sugar, FAN and Inorganic Phosphorous (IP), 222.85 mg/g, 11.56 mg/g and 19.9 mg/g, respectively. These series of fermentation experiments illustrate the feasibility for the application of consolidated bioprocessing, through simultaneous pretreatment and enzyme production as a more economic and environment-friendly process compared with those reported for chemical pretreatment followed by commercial enzyme process. A growth kinetic model regarding both growth and respiration is also proposed. Ethanol production was studied using the generic feedstock produced from sugarcane bagasse and soybean hulls. Total ethanol yield reached 0.31 mg g-1 (61.4% of theoretical yield) after 30 h of submerged fermentation. The result of subsequent fermentation has already shown the potential of the generic microbial feedstock to be used to produce varied products depending on the microorganism utilised. Chen-Wei Chang PhD Thesis June 2015

Declaration

xxi

Declaration

No portion of the work referred to in the thesis has been submitted in support of

an application for another degree or qualification of this or any other university or

other institute of learning.

Copyright statement

xxii

Copyright statement

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Acknowledgements

xxiii

Acknowledgements

I would like to show my gratitude to these following people who helped me

through my time in my PhD research.

Firstly I would like to profoundly thank my supervisor Professor Colin Webb for his

help and support throughout this research over the last few years. I have learned

not only professional knowledge, but also the most important thing, the way of

thinking from him. I also appreciate the time he spent with me during my thesis

proofreading.

I would like to thanks examiners Dr Apostolis Koutinas and Dr James Winterburn

for their suggestions. I would also like to thank members of the Satake Centre for

Grain Process Engineering for their helps, insightful comments and feedbacks

during my study. Many thanks to my colleagues (Musaalbakri Abdul Manan and

Stavros Michalios) for their assistant during my PhD research.

Finally I would like to thank my family for their mentally support and encouragement

and also to my wife, Shuyu.

Chapter 1 Introduction

1

CHAPTER 1 Introduction

Background For more than a century, industrialised society has relied on fossilised organic

materials such as coal, gas and oil as feedstocks for transportation fuels and

commodity chemicals. The extensive depletion of fossil fuels is causing global

concerns, such as greenhouse gas emissions, destruction of natural habitats and

other environmental catastrophes. Furthermore, short term price volatility has

“heightened apprehension to the future of global energy security” (Hahn-Hägerdal

et al., 2006). This has led to a growing interest in the application of the biorefinery

concept to replace fossil sources.

Biorefining is the sustainable processing of biomass into a spectrum of marketable

products and energy (FitzPatrick et al., 2010). Among several sources of biomass

residues that can be employed in energy generation, sugarcane bagasse is one of

the most used in the world. Sugarcane bagasse is the residue produced by cane

sugar mills after juice is extracted from the cane. It is a fibrous lignocellulosic

material, which is easily combusted. Most of this bagasse, 75%, is used as fuel for

power generation or as raw material for low-value products such as mulch or

ceiling tiles. The remaining 25% is considered as solid waste and is dumped to

landfill (Dawson and Boopathy, 2008). Similarly, Soybean hull, the main by-

product of the soybean processing industry, is also a lignocellulosic material but

containing only a small proportion of lignin when compared to sugarcane bagasse.

(Gnanasambandam and Proctor, 1999; Hickert et al., 2014). Due to their low cost

and relatively large abundance, sugarcane bagasse and soybean hull are potential

alternative sources to satisfy the demands of biorefinery development.

Bioconversion of biomass into products usually requires milder process conditions

and less conversion steps than petroleum-derived synthesis routes. These

features can lead to cheaper equipment costs and easier process safety


2

management. Lignocellulosic biomass, the most abundant organic material on

Earth, typically consists of three major constituents: cellulose, hemicellulose, and

lignin. Unfortunately, the crystallinity of cellulose, hydrophobicity of lignin, and

encapsulation of cellulose by the lignin-hemicellulose matrix are three major

factors that make bioconversion of lignocellulosic material particularly difficult

(Moraïs et al., 2012). In order to overcome this natural recalcitrance, a series of

deconstruction processes is necessary. Currently, conversion of lignocellulose to

chemicals (ethanol, butanol, succinic acid and PHB etc.) is usually approached in

three steps (1) pretreatment to breakdown the complex structure and open the

crystalline structure of cellulose, (2) hydrolysis with enzymes to reduce cellulose

to glucose and (3) fermentation of glucose to chemicals (Sun and Cheng, 2002).

However, the commercial utilisation of low-cost lignocellulosic materials is yet to

be successfully exploited and needs further innovations to overcome the still high

energy costs and the use of environmentally unfriendly pretreatment processes

(Kamm and Kamm, 2004; Koutinas et al., 2004).

Microbial pretreatment has recently received attention as an alternative to the

prevalent physicochemical pretreatment processes due to its potential

advantages of lower environmental impact, process simplification and reduced

energy (Shi et al., 2008). However, not all microorganisms have the capacity of

degrading cellulose, hemicellulose and lignin directly and efficiently into

metabolites of interests. The filamentous fungi from Trichoderma, Aspergillus,

Phlebia and Pleurotus genera are some of the microorganisms that have been used

to deconstruct these materials directly (Shi et al., 2008; Wang et al., 2002).

Solid-state fermentation (SSF) is a process whereby an insoluble substrate is

fermented with sufficient moisture, but without free water. This system can

present many advantages over submerged fermentation (SmF), including high

volumetric productivity, relatively higher concentration of the products, less

effluent generation, requirement for simple fermentation equipment, etc

(Camassola and Dillon, 2007; Pandey and Larroche, 2008). The SSF process closely

resembles the natural habitat of filamentous fungi. This environment could allow


3

them to effectively colonise and penetrate the solid substrate via hyphae

development (Pandey et al., 2000; Tengerdy and Szakacs, 2003).

(Webb and Wang, 1997) developed a process based on submerged fungal

bioconversion for the production of a nutrient-rich fermentation feedstock from

wheat. The process minimised the number of conversion steps, avoiding

unnecessary separation, using in-situ enzymes and preventing loss of nutrients. In

the Satake centre for Grain Processing Engineering at The University of

Manchester, various fermentation feedstocks, produced using variations of this

approach, have been demonstrated to be feasible media for bioproduction of a

wide spectrum of fine chemicals including lactic acid, ethanol,

polyhydroxybutyrate (PHB) and succinic acid (Arifeen et al., 2009; Botella et al.,

2009; Dorado et al., 2009; Du et al., 2008a; Koutinas et al., 2007b; Wang et al.,

2002). It could be possible to use the same approach to develop generic feedstocks

from lignocellulosic materials.

Several strategies by combined physical/chemical and microbial treatment, using

either commercial enzymes or on-site enzymes complex, have been shown that

recalcitrant lignocellulose can be used as raw materials for fermentative sugars

(Bak et al., 2009; Pirota et al., 2014; Shi et al., 2009). However to make the

conversion of lignocellulose into ethanol more economically feasible and

environment friendly, it is necessary to minimise chemicals utilisation and the

generation of unnecessary effluent streams. In this thesis a study of the

development of simultaneous in-situ enzymes production and deconstruction of

lignocellulosic substrates by solid state fermentation is presented. Application of

further hydrolysis of whole fermented solids, containing the in-situ enzymes and

mycelium, for the production of generic fermentation feedstocks is also

investigated.


4

Structure of the thesis Further to this introductory Chapter a review of the relevant literature is

presented in Chapter 2. The discussion of the literature is separated into several

topics; background information on biorefineries, pretreatment strategies for

lignocellulose, solid state fermentation and generic microbial feedstocks. The

objectives and the experimental plan for this project are given in Chapter 3.

The methods and materials used in all experimental work reported are described

in Chapter 4. Experimental results are then presented and discussed in four results

Chapters. The first of these reports on the production of nutrient-rich solution by

means of solid state fermentation followed by hydrolysis. Preliminary studies of

the influence on hydrolysis yield including different substrate treatments (washing

and particle size) and some operational studies (C/N ratio, mixed ratio substrates,

environmental humidity and incubation days) are given in Chapter 5. In chapter 6,

the growth kinetics of T. longibrachiatum in a bioreactor are presented. The

mathematical models used for the growth kinetics were based on metabolic

measurements; due to difficulty of fungal growth evaluation in solid state

fermentation. Different studies carried out in further hydrolysis and fungal

autolysis, including different operation factors (loading ratio, pH, temperature and

inhibitor addition) and fungal autolysis are reported in Chapter 7. Finally, in

Chapter 8, the generic microbial feedstock produced using sequential

bioprocessing was evaluated for ethanol production. Conclusions are presented in

Chapter 9 along with suggestions for future work.

Chapter 2 Literature review

5

CHAPTER 2 Literature review

The need for bioeconomy development Since the industrial revolution, the utilisation of fossil reserves has led to the

development of a global economy and has had a profound influence on world

society. Fossil feedstocks are used in manufacturing a wide variety of consumer

products and commodities, such as plastics, pharmaceuticals and agrichemicals.

Fossil materials additionally serve as feedstocks for electricity generation to

industrial and domestic markets and liquid fuels production for the transport

sector. These fossil resources are not infinite in the world, often come from

politically unstable regions and new resource discoveries are increasingly located

in difficult-to-reach places. Issues relating to energy security and independence

will become increasingly important to future energy, chemical and pharmaceutical

markets in every country (Jenkins, 2008). In addition to the significant problems

associated with security and renewability of these resources, their continued use

results in massive release of greenhouse gases and other pollutants that drive

global climate change. Over the past decade, UK policy has given bioenergy an

increasingly important role, especially for decarbonising the energy utilisation and

production system in cost–effective ways. UK legislation mandates a 35%

reduction of carbon emissions by 2020 and 80% cut in carbon emissions by 2050,

compared with 1990 levels, according to the 2008 Climate Change Act (UK

Government, 2008). Therefore, the replacement of oil with biomass as raw

material for fuel and chemical production is a significant driving force for the

development of biorefinery complexes. These will lead a very sizeable transition

in terms of technology, market design, consumer behaviour and, in all likelihood,

unprecedented economic development, resulting in a so called ‘bioeconomy’

(Bennett, 2012; Welfle et al., 2014).

The biorefinery concept Ethanol and Chemicals production from lignocellulosic wastes has the potential to

significantly improve sustainability of biofuels for transport by avoiding food


6

competition with crops and utilizing wastes from agricultural industry. However,

high production costs remain the bottleneck for large-scale development of this

pathway. The biorefinery could significantly reduce production costs of plant-

based chemicals and facilitate their substitution into existing markets. This

concept embraces a wide range of technologies able to separate biomass

resources (wood, grasses, corn, etc.) into their building blocks (carbohydrates,

proteins, triglycerides, etc.) which can be converted to value-added products,

biofuels and chemicals. According to a definition by IEA Bioenergy Task 42, a

biorefinery involves the "sustainable processing of biomass into a spectrum of

marketable products and energy." This means that a biorefinery can be a concept,

a facility, a process, a plant, or even a cluster of facilities, that integrates biomass

conversion processes and equipment to produce transportation biofuels, power,

chemicals and fibres from biomass. In essence, the biorefinery is analogous to

today’s oil-refinery, which produces multiple fuels and products from fossil fuel

(Cherubini, 2010). Figure 2.1 shows this analogy in terms of the range of products

which can be derived from petroleum and some of their counterparts from a

potential biorefinery.

Figure 2.1 A schematic of biorefinery processes Adapted from (Colin Webb, 1994)


7

Biorefineries combine established technologies, developed from various fields

such as material science, chemical engineering, biology and chemistry to pre-treat

raw materials, hydrolyse the substrate to fractionate industrial intermediates and

eventually to manufacture the final products (Sharma et al., 2011).

There are many chemicals that can be currently derived from biomass. In 2004,

the US Department of Energy (DOE) identified a list of the top 12 most attractive

candidates to focus research efforts in future years. The twelve building blocks can

be subsequently converted to a number of valued-added bio-based chemicals or

materials. These included several organic acids (succinic, itaconic, levulinic, and

fumaric acids), amino acids (glutamic acid) and polyols/sugars (glycerol, sorbitol,

etc.), indicated as sugar-based building blocks (Lin et al., 2011; Werpy and

Petersen, 2004). Bozell et al. (2010) presented an updated evaluation of potential

chemicals and put new candidates (ethanol and Lactic acid) into the list. There will

be two-part pathways for chemicals production from raw materials through the

intermediates, or building blocks. The first part is the transformation of sugars to

the building blocks. The second part is the conversion of the building blocks to

secondary chemicals or families of derivatives. In general, biological

transformations account for the majority of routes from plant feedstocks to

building blocks, but chemical transformations predominate in the conversion of

building blocks to molecular derivatives and intermediates. Each route will have

to overcome a range of technological issues before it can become a commercial

reality, including the flexibility to use different types of feedstocks, the efficient

use of feedstocks, and the successful scaling-up from pilot- to large-scale plants

(Azapagic, 2014). In addition to technological issues, integrated biorefineries face

a number of sustainability challenges (environmental, economic, and social) that

must be considered on a life-cycle basis.

Lignocellulosic feedstocks For large-scale biological production of fuel or chemicals, there is a need to use

cheaper and more accessible substrates, improved fermentation efficiency and


8

more sustainable process operations for product recovery and water recycle.

Feedstocks generally contribute most to production cost. On a conventional plant,

for example, corn starch accounts for up to 79% of the overall ABE (acetone,

butanol, ethanol) production cost while energy for operations including distillation,

contributes 14% to the overall cost (Green, 2011). The production cost of the plant

largely depends upon the price of feedstock and is extremely sensitive to any price

fluctuation. Therefore, transition towards cheaper and non-edible feedstocks such

as corn cob, corn stover, sugarcane bagasse, wheat straw and municipal solid

waste, offer the biggest opportunity for cost reduction and food chain security.

Also, use of lignocellulosic and waste material might be more sustainable, offering

a low carbon footprint and decreased greenhouse gas emissions. However,

successful implementation of these strategies comes with multiple technical,

engineering, and biological challenges. Utilisation of lignocellulosic biomass is

limited by the close association and complex bonding that exists among these

components. In order to exploit sugarcane bagasse for its efficient conversion

from carbohydrates into the desired products, it is important to understand the

composition, structure and interaction of these cell wall components.

The resistance to decomposition of plant biomass is often referred to as

“recalcitrance”, a term that has become popular in the field of lignocellulosic

materials conversion technology. This property of plant material, not only

prevents deconstruction by structural arrangement, but also retards enzymatic

hydrolysis through some cell wall components. Lignocellulose is the primary

building block of plant cell walls. Plant biomass is mainly composed of three groups

of polymers: cellulose, hemicellulose, and lignin, along with smaller amounts of

pectin, protein, extractives (soluble non-structural materials such as sugars,

nitrogenous material, chlorophyll, and waxes), and ash (Jørgensen et al., 2007a).

This is shown structurally in Figure 2.2., the composition of these constituents, as

shown in Table 2.1, varies from one plant type to another. For example, hardwood

has greater amounts of cellulose, whereas wheat straw and leaves have more

hemicelluloses (Jørgensen et al., 2007a). The basic structures, organization, and


9

interactions between these molecules largely determine the physical and chemical

characteristics of the overall plant.

Figure 2.2 Structure of lignocellulosic biomass (Rubin, 2008)

Table 2.1 Chemical composition of common lignocellulosic residues and wastes

(Cardona et al., 2010; Sun and Cheng, 2002)

Lignocellulosic materials

Cellulose (%) Hemicellulose (%) Lignin (%)

Hardwood 40-55 24-40 18-25

Softwood 45-50 25-35 25-35

Corn cobs 45 35 15

Wheat straw 30 50 15

Switch grass 45 31 12

Nut shells 25-30 25-30 30-40

Solid cattle manure 1.5-4.7 1.4-3.3 2.7-5.7

Sugarcane bagasse 33-45 24-35 20-30


10

Cellulose

Cellulose often exists in the form of microfibres (formed by ordered polymer

chains that contain tightly packed, crystalline regions) embedded within a matrix

of hemicellulose and lignin. Covalent bonds between lignin and the carbohydrates

have been suggested to consist of benzyl esters, benzyl ethers and phenyl

glycosides. Cellulose is a linear polysaccharide that consists of glucose units linked

together by β-(1-4) glycosidic bonds (Figure 2.3). This polysaccharide is

widespread in nature, in fact, it is the most abundant organic molecule on earth

and occurs in both primitive and highly evolved plants. Chain length varies

between 100 and 14,000 residues. Cellulose chains form numerous intra- and

intermolecular hydrogen bonds, which account for the formation of rigid,

insoluble microfibres. The chains are oriented in parallel and form highly ordered,

crystalline microfibre domains interspersed by more disordered, amorphous

regions.

Figure 2.3 Structure of cellulose (A) β -(1-4) glycosidic bonds (B)Schematic structure of fibre (Béguin and Aubert, 2006)


11

Hemicellulose

Unlike cellulose, which is a particular polymer, there are several different types of

hemicellulose. These include xylan, glucuronoxylan, arabinoxylan, glucomannan,

and xyloglucan, all of which have branches with short lateral chains consisting of

different sugars. These polysaccharides contain many different sugar monomers

such as pentoses (xylose, rhamnose, and arabinose), a few hexoses (glucose,

mannose, and galactose), and uronic acids (Kuhad et al., 1997) although they are

predominantly composed of pentose sugars. The hemicellulose polymers

surround and associate with the cellulose by means of hydrogen bonds in the cell

walls. In contrast to cellulose, the polymers present in hemicelluloses are easily

hydrolysable under mildly acidic conditions. These polymers do not aggregate,

even when they co-crystallise with cellulose chains (Jung et al., 1993).

Lignin

Lignin is the third most abundant natural polymer present in nature after cellulose

and hemicelluloses. It is a complex, large molecular structure containing cross-

linked polymers of phenolic monomers, bringing structural support,

impermeability, and resistance against microbial attack. The major barrier for

utilization of lignocellulosic biomass is the complete separation of lignin from

carbohydrates in the complexes which shield cellulose from enzymatic hydrolysis

and fermentation. The enzymatic digestibility of the biomass for production of bio-

products and biofuels depends mainly on its lignin content (Liu and Wyman, 2003).

Furthermore, lignin is also very rigid, therefore responsible for the rigidity of wood

cells. In general, herbaceous plants such as grasses have the lowest contents of

lignin, whereas softwoods have the highest lignin contents (Table 2.1). Three

phenyl propionic alcohols exist as monomers of lignin: coniferyl alcohol (guaiacyl

propanol), coumaryl alcohol (p-hydroxyphenyl propanol), and sinapyl alcohol

(syringyl alcohol) (Figure 2.2). Alkyl−aryl and aryl−aryl ether bonds link these

phenolic monomers together (Buranov and Mazza, 2008; Kumar et al., 2009).


12

2.3.1 Sugarcane bagasse

Sugarcane is one of the largest crop in the world. In 2010, FAO (Food and

Agriculture Organization) estimated that it was cultivated on about 23.8 million

hectares, in more than 90 countries, with a worldwide harvest of 1.69 billion

tonnes. Brazil is the largest producer of sugar cane in the world. The next five

major producers, in decreasing amounts of production, are India, China, Thailand,

Pakistan and Mexico. The world demand for sugar is the primary driver of

sugarcane agriculture. For sugar industry using sugarcane as raw material, waste

management is one of the biggest problems to solve. Bagasse is the residue

obtained when sugarcane is crushed to extract juice used for sugar and ethanol

production. In general, 280 kg of humid bagasse is produced from 1 tonne of

sugarcane. According to the information from Food and Agriculture Organization

of the United Nations (FAO) in 2010, there are 4.73 thousand million tonnes of

bagasse in the world. Therefore, the conversion of sugarcane bagasse into value-

added products may have sustainable economic and strategic benefits (Chandel

et al., 2012).

The sugarcane plant is shown in Figure 2.4. It is composed by leaves, stem and

straw. The sugarcane stem is the material removed before the milling of cane to

obtain a juice which is subsequently used for sugar industry (sucrose) or ethanol

production. The residue, sugarcane bagasse, is coming from the stem after

extraction of juice. Instead of creating air pollution by burning it in the open

agricultural field, however, some other potential uses of the bagasse include: (1)

fuel for combustion to supply energy; (2) raw material to char, oil or gas by

pyrolysis; (3) feedstock for paper production; (4) substrate for microbial growth to

produce chemicals. (Canilha et al., 2012).


13

Figure 2.4 A sugarcane plant (Canilha et al., 2012)

Figure 2.5 illustrates the process and the major solid waste streams produced in

sugar juice manufacturing. These include sugarcane trash, bagasse, pressed mud

and fly ash. The characteristics of these wastes are summarised below.

1. Sugarcane trash: this is the tops and leaves of sugarcane that are obtained

upon sugarcane harvesting and approximately consist of cellulose (40%),

hemicellulose (25%) and lignin (18-20%). About 0.09 to 0.11 tonne trash is

generated per tonne of sugarcane harvested(Singh et al., 2008).

2. Sugarcane bagasse: this is the fibrous residue obtained from juice

extraction step. About 0.25-0.3 tonnes bagasse is generated per tonne of

sugarcane (Pessoa et al., 1997). There are residual sugars in the bagasse,

and it needs to be washed before pulverisation as fuel for electricity

generation or other use.

3. Pressed mud: the solid residue obtained after sugarcane juice clarification

process. This is a complex product with crude wax (5-14%), crude protein

(5-15%), sugar (5-15%) and other compounds such as SiO2 (4-10%), CaO (1-

4%) and MgO (1.5%). Around 0.03 tonne per tonne sugarcane could be


14

generated during the sugar production (Yadav and Solomon, 2006).

4. Fly ash: this is the waste generated when the bagasse is used as fuel for

electricity generation. It contains lots of silica and other metal oxides.

Around 0.005 tonnes fly ash is produced per tonne of sugarcane

(Balakrishnan and Batra, 2011; Umamaheswaran and Batra, 2008).

5.

Figure 2.5 Solid wastes generated in cane sugar production (Balakrishnan and Batra, 2011)

2.3.2 Soybean hulls

Soybean hulls (SH) are an agricultural residue produced during processing of

soybeans. The hard shell or hull of the soybean is removed mechanically and

accounts for about 5–8% of the 95 million tons per year soybean crop in the United

States (Mielenz et al., 2009). The major components include 40–45% cellulose, 30–

35% hemicellulose, 9–12% protein, and only around 3–4% lignin (Zhang and Hu,

2012). Considered a waste by-product from the production of soy oil, soybean

meal, and other high-protein products, soybean hulls are typically sold as

compressed pellets or fed to cattle. Recently researchers have tried to produce

ethanol, lipids and peroxidases from soybean hulls through different types of

process (Mielenz et al., 2009; Montgomery, 2004; Zhang and Hu, 2012). Due to its

low content of lignin and high cellulose content, it can be a good resource for the

production of cellulolytic enzymes in SSF (Brijwani et al., 2010).


15

Pretreatment of lignocellulosic materials Lignocellulosic materials could be used as more accessible fermentation

feedstocks after an effective pretreatment process. Commodities and fuel

production from lignocellulosic materials comprises the following main steps:

pretreatment, enzymatic digestibility of cellulose and hemicelluloses, sugar

fermentation (Figure 2.6). In this process, the task of hydrolysing lignocellulose to

fermentable monosaccharides is still a technical challenge since the cellulose

hydrolysis is barred by physical-chemical and structural factors. Owing to these

characteristics of lignocellulosic biomass, pretreatment is an essential step to

obtain potentially fermentative sugars in the hydrolysis process.

Figure 2.6 A schematic of the conversion of lignocellulosic biomass to chemicals

The major purpose of the pretreatment is to alter the structure of lignocellulose,

separate lignin and hemicellulose from cellulose, increase the porosity of the

substrate and decrease the material’s crystallinity (Figure 2.7). An efficient

pretreatment must set free the highly crystalline structure of cellulose and extend

the amorphous areas for enzyme digestibility. The removal of lignin is also

essential. A decrease of one-third in the lignin content of hardwood or two-thirds

in that of softwood increases the digestibility of these materials to 60%. Apart

from being considered a decisive step in the fermentation to chemicals and

biofuels, pretreatment also plays a crucial role in the economics of the process. As


16

a matter of fact, it has been described as the most expensive unit cost in the

lignocellulose to fuels conversion based on biological processing (Kumar et al.,

2009; Mosier et al., 2005).

?

Degrading enzymes

Degrading enzymes

Figure 2.7 Schematic of goals of pretreatment on lignocellulosic materials

Adapted from (Mosier et al., 2005)

The factors influencing the hydrolysis of cellulose include accessible surface area

of the substrates, fibre crystallinity, and content of lignin and hemicelluloses.

Conventionally, structural features have been divided into two groups and

classified as physical and chemical factors. Since the above structural features are

closely associated, which means that the change in one structural feature could

also lead to change in the other factors (Zhu et al., 2008).

Some recent studies have shown that accessible surface area is a vital factor that

influences biomass hydrolysis (Chandra et al., 2009, 2008; Rollin et al., 2011).

Accessibility of substrate to cellulase enzymes will always increase after breaking

the linkage between lignocellulose components and disrupting the orderly

hydrogen bonds in the cellulose fibres. It is broadly accepted that highly crystalline

cellulose is less accessible to cellulase attack than amorphous; therefore,

crystallinity obstructs the efficiency of enzyme contact with cellulose (Zhu et al.,

2008). Once lignocellulosic materials were pretreated, decrease in crystallinity was

accompanied by the change of other substrate properties such as particle size


17

reduction, lignin and hemicelluloses removal or increase in available surface area.

However, some pretreatments will increase crystallinity of the cellulose fraction.

This fact has been interpreted to be due to the removal or reduction of more easily

hydrolysed amorphous cellulose. Some researchers suggested that the effect of

reduced crystallinity on the enzymatic digestibility rate might be a consequence of

increased surface area or decreased particle size. However, further reduction of

particle size below 40-mesh (0.42 mm) did not increase the hydrolysis rate (Chang

et al., 1997).

Research has shown that biomass digestibility is enhanced with increasing lignin

removal, although the extent of delignification required to enhance hydrolysis

may differ between biomass species. The presence of lignin restricts the swelling

of cellulose, thus limits the accessible surface area of the cellulose available to the

enzymes. Swelling of cellulose, leading to an increase of accessible surface area, is

required to achieve efficient cellulose digestibility (Kumar et al., 2012).

Removal of hemicelluloses will also increase the surface area and pore volume of

the substrate and therefore increase the accessibility of cellulose. And at least 50%

of hemicelluloses should be removed to significantly enhance cellulose

digestibility (Zhu et al., 2008).

There are several fundamental requirements of pretreatment methods as follows:

(1) low cost of the chemicals treatment for pretreatment; (2) Minimal by-product

waste production; (3) Increase saccharification conversion in enzyme hydrolysis;

(4) low enzyme loading of treated lignocellulose materials. Based on these above

requirements there are different techniques developed and employed for

lignocellulose pretreatment including; (1) Physical; (2) physicochemical; (3)

chemical and (4) biological process. The effects and benefits to all these methods

will be discussed in the following sections.


18

2.4.1 Physical pretreatment

The main purpose of physical pretreatment is to reduce the particle size of the raw

material and to decrease cellulose crystallinity. This can be achieved by chipping,

grinding and milling. In the case of bagasse, it is firstly chipped to around 10 mm

particle size. Milling and grinding then reduces particle size down to around 1 mm

or less (Sun and Cheng, 2002). Millett et al. (1976) showed that vibratory ball

milling was more effective than ordinary ball milling in decreasing cellulose

crystallinity, though this was for spruce and aspen chips. They also found that this

improved the digestibility of the biomass. Actually, a size reduction of

lignocellulosic materials is a significant step in lignocellulosic biorefinery. Because

of the characteristics of non-compact materials, it causes the rising of transport

cost and increasing the storage space. Therefore, no matter which pretreatment

methods be applied for the feedstock, once harvesting from the factory or farm,

physical pretreatment usually be used firstly in the lignocellulosic processing.

2.4.2 Chemical pretreatment

Ozone can be used to degrade lignin and hemicellulose in many lignocellulose, for

example, wheat straw (Ben-Ghedalia and Miron, 2004), bagasse, peanut, green

hay and sawdust (Neely, 1984; Vidal and Molinier, 1988). In general, the

degradation was mainly focused on lignin and holocellulose was only slightly

affected. (Vidal and Molinier, 1988) presented that the rate of enzymatic

hydrolysis increased by 5 times, following large amounts of lignin removal (60%)

from wheat straw in ozone pretreatment.

Concentrated acids (H2SO4 and HCl) have also been used to deconstruct

lignocellulose in many processes. However, due to the characteristics of

concentrated acids, for example, reactive, corrosive and other hazardous features,

which makes the pretreatment process costly (Kumar et al., 2009; Sun and Cheng,

2002). Alkaline peroxide process is one of promising pretreatment to provide the

effective delignification and decrystallisation of cellulose. The hydrogen peroxide

in alkaline solutions will react readily with lignin to produce water soluble, low


19

molecular weight oxidation products. The role of H2O2-derived radicals in the

oxidative reaction is to depolymerise lignin by attacking lignin side chains and

transform the macro-compounds into a number of small compounds (Gould, 1985;

Selig et al., 2009).

In the organic solvent pretreatment process, the lignin and hemicellulose bonds

embedded in the cellular fibres are broken through the addition of organic solvent

and inorganic acid catalysts (H2SO4 or HCl) mixture. The common used solvents

including methanol, ethanol, acetone, ethylene glycol, triethylene glycol, and

tetrahydrofurfuryl alcohol are being used to depolymerise lignin and

hemicellulose (Chum et al., 1988; Thring et al., 1990).

A negative effect of the chemical pretreatment is microbial inhibitor production

following by chemical reaction on lignocellulose. This effect may causes the low

efficiency of subsequent enzyme hydrolysis and microbial fermentation.

2.4.3 Physico-Chemical pretreatment

Steam explosion is was invented and developed as a biomass pretreatment

method (Mason, 1926). In this process, biomass are fed in the reactor, then heated

with saturated steam at a temperature of 160–260°C and a pressure of 4.8 MPa

for about 2 to 10 min. Once the reaction is done, the biomass are then discharged

through the restricted pipe and explode at atmospheric pressure into a receiving

tank. The sudden pressure release is to make plant cellular bundles loose and

cause a better accessible opportunity for enzymatic hydrolysis (Sun and Cheng,

2002).

Ammonia fibre explosion (AFEX), is conducted with biomass with liquid ammonia

at high temperature (120°C) for several minutes to an hour in pressured reactor,

and then the pressure is released. This action causes disruption to the

lignocellulose network, benefiting hydrolysis. A significant increase in the

fermentation rate of various herbaceous materials was reported. However, this


20

ammonia work is not a very efficient method for high lignin content of

lignocellulose like hardwoods and nut shells (Kumar et al., 2009; Mes-Hartree et

al., 1988).

2.4.4 Biological pretreatment

All the above mentioned pretreatment methods which are harsh and cost/energy

intensive and may cause the environment problem. On the contrary, a biological

pretreatment process is mild, energy-saving and environment friendly. A fungal

treatment has been applied to upgrade the lignocellulose to supply paper and

livestock industries for decades. Because of the sustainable and environmental

consideration in the developing biorefinery, this pretreatment method has

received attention to increase the conversion of lignocellulose in biofuel research.

Most of biological treatments mainly employ brown, white and soft-rot fungi

which degrade lignin and hemicelluloses and very little of cellulose (Saritha et al.,

2011; Singh et al., 2008). Generally speaking, a conventional biological

pretreatment involves microorganisms such as white-rot fungi that are used to

degrade lignin and solubilize hemicellulose through solid state fermentation. Table

2.2 is the list of fugal species used for biological pretreatment.

Table 2.2 List of fungal species used in the biological pretreatment of lignocellulosic materials

Type of fugus Fugal species

White rot Phanerochaete chrysosporium

Pleurotus ostreatus

Cyathus stercoreus

Penicillium sp.

Brown rot Aspergillus niger

Fomitopsis palustris

Gloeophyllum trabeum

Soft rot Trichoderma reesei


21

The fungus degrades the complicated polymers such as cellulose, hemicellulose,

lignin, starch and pectin through enzymes from hyphae, and convert these

marcomolecules into assimilable simple molecules ((glucose, xylose and phenolic

compound etc.) for cell growth. The most commonly used fermentation process is

submerged fermentation (SmF) due to familiarity of this techniques (Robinson et

al., 2001). However, a number of studies have shown that solid-state fermentation

provides higher ligninolytic and celluloytic enzymes productivity than submerged

fermentation. Further discussion of solid-state fermentation will be given in next

section.

Solid state fermentation There are many different definitions of solid-state fermentation (SSF) mentioned

in the literatures. (Mitchell et al., 2006) described SSF involves the growth of

microorganisms on moist solid particles, where the void spaces between particles

contain a continuous gas phase and absence of free flowing water. In the SSF

process, agricultural residues and food waste are always be used as substrates. The

main source of nutrients typically comes from within the particle of substrate,

although there are some cases in which additional nutrients provided by extra

supplements. In the last 20 years, a growing interest in SSF has been shown by a

significant increase in numbers of publication on this topic.

The solid-state fermentation (SSF) creates the natural environment for cell growth

such as composting and ensiling. In industrial applications this natural process can

be utilised in a controlled way to produce a desired product (Couto and Sanromán,

2006). Many types of microorganisms, mainly yeast and fungi and few bacteria,

being used in SSF for producing diverse products.

SSF has been widely used for a long periods in the human history. A lot of examples

in the food application, such as cheese, fish preservation, alcoholic beverages and

vinegar have existed for hundred years (Krishna, 2005). Since the emergence of

submerged fermentation technology to produce antibiotics such as penicillin on a


22

large scale, the progress of solid-state fermentation research slowed down after

1940 (Hölker and Lenz, 2005; Singhania et al., 2009). However, SSF have attracted

a renewed attention recently from researchers due to several advantages over the

liquid (submerged) fermentation, for example, solid waste management and high

value products production.

2.5.1 Fungal growth in SSF

Many types of microorganisms (bacteria, yeast and fungi) can be cultivated in SSF

for diverse products production. In SSF system, bacterial and yeast grow by

adhering to the surface of the substrate particles whereas filamentous fungi are

able to penetrate through their vegetable growth-based hyphae into the solid for

nutrient uptake (Gowthaman et al., 1993; Weber and Pitt, 2001). Bacteria are

mainly involved in composting, ensiling and other food process. Yeast can be

applied in alcohol and other food or animal feed production (Saucedo-Castaneda

et al., 1992). However, filamentous fungi play an important role of microorganisms

used in SSF application due to their unique morphological characteristics. The

hyphal development gives a major advantage to filamentous fungi over unicellular

microorganisms to colonise and penetrate the solid substrate in search for

nutrients (Raimbault, 1998).

A clear understanding of fungal morphology and growth is limited by the complex

orientation of the mycelium with the substrate types, substrate heterogeneity and

the lack of techniques for the direct estimation of viable biomass (Gowthaman et

al., 2001). The pattern of growth of filamentous fungi in submerged culture is

generally not the same as in solid-state culture. Fungal cultures adopt different

growth patterns when cultivated in liquid and solid medium. It is evident that the

culture conditions (medium formulation, pH, oxygen and inoculum size) can

influence fungal growth and morphology (Koutinas et al., 2003; Wang and Webb,

1995). Under Submerged fermentation (SmF), they are exposed to hydrodynamic

forces such as turbulence or agitation, while in solid state fermentation (SSF)

fungal growth is restricted to the solid matrix. In liquid environment, fungi grows


23

as pellets or free mycelia, depending on the genotype of the strain and culture

conditions (Papagianni et al., 1999). In solid-state culture, the growth is by

extension of hyphae to eventually cover the entire surface of the static solid

substrate and a penetration of the substrate. The aerial hyphae which occur only

in SSF are mainly responsible for oxygen uptake (te Biesebeke et al., 2002). A

detailed illustration of some of the micro-scale processes that occur during solid

state fermentation is presented in Figure 2.8. All these and many other

phenomena such as microbial growth and death rates, transfer between the inter-

particle regions, and destruction of the polysaccharide due to the growth, can

strongly influence process performance during solid state cultivation.

Figure 2.8 Schematic of some micro-scale processes that occur during solid-state fermentation (Hölker and Lenz, 2005)

SSF resembles the natural habitat of microorganism, therefore, provides preferred

environment for microorganisms to produce useful products. On the contrary, SmF

would be violated to their natural habitat, especially for filamentous fungi

(Singhania et al., 2009). Table 2.3 shows the advantage and disadvantage of solid-

state fermentation.


24

Table 2.3 Advantage and disadvantage of SSF (Robinson et al., 2001)

Advantages Disadvantages

higher yields in a shorter time period Problems in scale-up

better oxygen circulation Difficult control of process parameters

(pH, heat, nutrient conditions, etc.)

it is simpler with lower energy requirements

it resembles the natural habit for filamentous fungi

higher impurity product, increasing recovery product costs

less effort in downstream processing

Although a lot of bio-based compounds production are still dominated by SmF

process, there has been an increasing interest on the application of the SSF

technique since this method has been shown more efficient and sustainable than

SmF (Martins et al., 2011). SSF technique offers many new process for chemicals

production since it can utilises agricultural residues as feedstock directly. Also, SSF

products obtained are relatively concentrated, which could be easily recovered

and purified than products obtained from SmF processes. Pinto et al. (2012)

reported that fungal pretreatment using solid state fermentation allowed a higher

saccharification yield than liquid medium.

2.5.2 Lignocellulose feedstock

The increasing interest in the issue of bioresource utilisation in the last ten years,

and a recent literature survey has been reflected about this trend. Figure 2.9

illustrates the evolution of the number of scientific publications found using term

‘solid-state fermentation + lignocellulose” in Scopus database. As the graph shown,

the number of publications grows dramatically since 2005. Due to the increase of

oil price, causing the research of bioenergy and bioresource raised at that time.

All solid substrates have a common feature, generally insoluble in water and are

made of macromolecules (i.e. cellulose, hemicellulose, pectin, lignin, starch and


25

other polysaccharides) (Krishna, 2005; Raimbault, 1998). These macromolecules

may provide a function as an inert matrix within which the nutrients are adsorbed.

Not all substrates are digested equally easily. For example, the lignocellulosic

substrate (i.e. wheat straw, rice straw, sugarcane bagasse, corncob) are more

difficult to digest than starches (Hoogschagen et al., 2001).

Figure 2.9 Number of papers and year of publication containing the term “solid state fermentation + lignocellulose”

In addition to its chemical properties, the physical characteristics of the substrate

(i.e. particle size, particle shape, porosity, consistency) may affect nutrient

utilisation in a solid-state fermentation. Particle size and shape appear to be the

most significant factors that influence the substrate consumption (Manpreet et al.,

2005; Pandey, 1992). The ratio of the surface area to the volume of the particle,

which relate to the particle size and shape. And this factor could affect the depth

of hyphae penetration in a static bed of solids. The more details about particle size

effect will be discussed in section 2.5.4 below.

0

5

10

15

20

25

Nu

mb

er o

f P

ub

licat

ion

usi

ng

term

solid

sta

te f

erm

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atio

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lign

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Year of Publication


26

2.5.3 Biomass estimation in SSF

The biomass concentration is a crucial parameter in kinetic studies for

characterizing microbial growth. In a solid-state cultivation, the biomass is difficult

to measure directly as it is difficult to separate the mycelium from the fermenting

substrate. Several indirect measurement techniques have been applied to

estimate biomass in solid-state fermentations. These indirect measurement

methods are based on the content of certain cell components such as protein,

ergosterol, nucleic acid, chitin and biological activity such as respiration (Bellon-

Maurel et al., 2003; de Carvalho et al., 2006; Koutinas et al., 2003; Ooijkaas et al.,

1998) and the dielectric properties of cells (Kaminski et al., 2000; Markx and Davey,

1999; Patel and Markx, 2008).

2.5.3.1 Metabolic activities of biomass

A respiration process releases energy for use in cell growth. And oxygen

consumption and carbon dioxide evolution happened can be observed in aerobic

microorganisms. These metabolic activities are therefore growth associated and

can be used for the estimation of cell growth (de Carvalho et al., 2006; Medeiros

et al., 2001; Raimbault, 1998). Therefore, on-line measurement of carbon dioxide

and oxygen in the exit gas from SSF allows real time data on the physiological

proliferation of cells to be monitored. It is convenient to provide a good indication

of diverse bio-reaction and has possible application to the scale-up (Machado et

al., 2004).

2.5.3.2 Dielectric properties of cells

The dielectric properties of cells have been widely studied for bioprocess

monitoring since the huge requirement of on-line biomass measurement.

Impedance method is a clear reflection of viable live cell rather than the total cell

umbers in bioreactor (Carvell and Dowd, 2006). Kaminski et al. (2000) showed that

the capacitance method can give useful information on fungal growth in SSF

system, however, the sensitivity was limited and failed to response early stage of


27

fermentation. It may be the reasons that the biomass monitor probe is designed

for submerged fermentation and did not reflect efficiently in a static,

heterogeneous solid state fermentation.


28

2.5.3.3 Biomass components

Several compounds of the biomass are stable and account for a specific proportion

to the biomass. All these components can be used to estimate biomass

concentration and are reviewed in this section.

Protein and nitrogen content

Protein is a readily measured cellular components for biomass estimation.

Determination of soluble protein has been applied to estimate the growth of

Aspergillus niger during solid state fermentation (Favela-Torres et al., 1998).

However, there could be an interference problem happened with a substrate rich

in protein (Bellon-Maurel et al., 2003).

Ergoesterol

Ergosterol is the predominant sterol in fungal cell membrane. In solid cultures,

contents of ergosterol and glucosamine are generally correlated against mycelium

of biomass (de Carvalho et al., 2006; Raimbault, 1998). Nevertheless, in some case,

the content of ergosterol of microorganism could varied, depending on the culture

conditions, and not be an reliable method to biomass estimation (Nout et al.,

1987).

Nucleic acids

The biomass concentration was estimated by DNA measurement during solid-

state fermentation using Aspergillus oryzae (Bajracharya and Mudgett, 1980).

However, the DNA contents in substrates may interfere the exact DNA content of

biomass. Therefore, it is not reliable if the substrate contains detectible nucleic

acids.

Glucosamine

Chitin (poly-N-acetylglucosamine), a polymer of glucosamine, is an essential

component of fungal cell walls. Hydrolysis of chitin produces glucosamine that can

be measured and correlated to the biomass content. Glucosamine measurement


29

is widely claimed to be a good indicator for fungal growth. The disadvantage of

this method is that chitin content of mycelium varies with age, interference with

glucosamine present in the substrate (Bellon-Maurel et al., 2003; Raimbault, 1998).

2.5.4 Fermentation conditions

The culture conditions significantly influence microorganisms on solid-state

fermentation. Several factors will be discussed in the following sections.

2.5.4.1 Effect of nutrition

Among the cultivation parameters, the carbon/nitrogen (C/N) ratio is one of the

most important factors to balance biomass and metabolites production. The

excess or lack of nitrogen content in the substrate may be a limiting factor for

fungus growth (Mantovani et al., 2007). Carbon to nitrogen ratios in the cultivation

substrate vary for different fungi species. Usually, C/N ratios in microbial cells is

8:1 to 12:1, In the growth of microorganism, 50% of the carbon for energy

consumption, 50% of the carbon composes the cells. Thus, an ideal C/N ratio in

growth medium is 16:1 to 24:1 to make sure that there is enough nutrient for

utilisation (Chen, 2014). It is worth to notice that the complexity of substrate

structure, depending on various lignocellulose, could influence the fungal growth.

Therefore, the utilisation efficiency of fungi could be different when using the

same strain with the similar C/N ratio of different lignocellulosic materials.

2.5.4.2 Effect of particle size and porosity

For particle size, the reason for this might be the attributed to substrate shape in

different scale of particle size. The substrate size and shape will affect the

attachment and accessibility of microorganisms. The larger size of particle might

provide the greater depth of the nutrients within the particle. This situation will

give a challenge to hyphae penetration and fungal growth. However, for different

particle size of sugarcane bagasse, it always consists of irregular sized particles and

different shaped substrates (Figure 2.10). Once the irregularly size particles, then

smaller one might tend to pack the inter-particle void space between larger


30

spheres and block the open pore for enzyme accessibility (Figure 2.10b). It may be

the reason that the enzyme production does not correlate with the various particle

size of mix-substrates.

Figure 2.10 Effect of particle size and shape on the bed porosity

(Mitchell et al., 2006)

Porosity of an SSF bed does not remain constant throughout SSF processes and

this could be addressed to biomass grow, degradation of solid substrate, swelling

or shrinking phenomena and water content variability in the solid bed (Karimi et

al., 2014). Comparing two beds of different particle sizes but the same porosity

(void fraction), it will be not easy to force air through the bed of smaller particles,

leading to the pressure drop. Nevertheless, the passing air may go through routes

in a bed of bigger particles which is called the channelling effect. Hence, it is

important to decide the suitable particle size of substrate for the large-scale

bioreactor. Porosity (void fraction) is a measure of the void spaces in a material.

The packing of substrate bed will influence the proportion and continuity of the

inter-particle spaces, providing oxygen replenishment and heat removal during

fermentation. Gas transfer is strongly affected by the porosity (Figure 2.11), size

and shape of substrates used in solid-state fermentation. A better understanding

of the physical properties of the particle is important for further research in

process analysis.


31

Figure 2.11 Physical meaning of the porosity (void fraction) and bed packing density (Mitchell et al., 2006)

2.5.4.3 Effect of temperature

The heat released during SSF is directly proportional to the fungal growth, spore

germination and product formation in the process due to heat energy would be

produced from cells during respiration (Saucedo-Castañeda et al., 1990). The

released heat can reach up to 3000 kcal from 1 kg of digested substrate, causing a

radial gradient of 5°C/cm at the centre of the reactor (Bellon-Maurel et al., 2003).

Insufficient heat removal inevitably leads to a rise in bed temperature of solid

state fermentation. Low water content and poor conductivity of porous solid

substrates promote the heat accumulation in the SSF system.

A number of cooling methods have been applied for heat dissipation. For example,

intermittent agitation, circulation of water through a jacket, low depth of bed

substrate. Alternatively, spraying water directly onto the fermenting solids

coupled with forced aeration or mixing can also be helpful. Forced aeration may

remove more than 80% of heat produced (Manpreet et al., 2005), but high

aeration rates may cause a loss of moisture and a reduced water activity of the

substrate. Dry air is more effective for cooling (evaporative cooling) but humidified

air is generally used to minimize water loss. Some water loss occurs even if


32

saturated air is used (Raghavarao et al., 2003).

The common incubation temperature for the growth of fungi such as A. niger

(Delille et al., 2004), A. oryzae (Wang et al., 2010), Trichoerma sp., Penicillium sp.

and Graphium sp. (Delille et al., 2004) is taken to be 30°C. For Trichoderma

longibrachiatum, several studies showed that operation temperature is set as 30°C

for SSF experiments(Guerra et al., 2006; Kovacs et al., 2004). Mohd et al. (2011)

also reported that the most favourable temperature for growth and sporulation

of Trichoderma longibrachiatum was found in between 25–30°C.

2.5.4.4 Effect of moisture content and water activity

The definition of Solid-state fermentation has already shown, there should not

contain free water in the system. However, as with other living organism, water is

a vital role to support lives. High moisture content may reduce substrate porosity

and mass transfer of oxygen. While low moisture content results in a reduced

accessibility of nutrients to the fungus (Pandey, 2003). Generally, fungi could

survive in a wide range between 30-75% (w/w). In contrast, bacterial culture

requires more than 70% (w/w) moisture in the substrate (Gautam et al., 2002;

Pandey and Larroche, 2008; Pérez-Guerra et al., 2003). Previous studies reported

the ability of Trichoderma longibrachiatum to produce xylanase with a range of 45

to 70% (Azin et al., 2007; Ridder et al., 1999).

The optimum moisture content was only 40% for the cultivation of Aspergillus

niger on rice, whereas on coffee pulp the content was 80%, which demonstrates

the uncertainty of moisture content chosen for predicting cell growth in different

medium. It is now generally accepted that the water requirements of

microorganisms should be defined in terms of the water activity (aw) rather than

the water content of the solid substrates (Raimbault, 1998). The water activity is

the ratio of the vapour pressure of water in a system to the vapour pressure of

pure water at the same temperature. Fungi and yeasts can grow at a relatively low

water activity in the range of 0.6-0.9. In contrast, bacteria require higher water


33

activity values for growth (Manpreet et al., 2005; Raimbault, 1998). Several

evidences showed that the water activity of the substrates is a key factor in solid

state fermentation. First of all, cell growth is dependent on the water activity of

the substrates. Secondly, the difference of water activity between solid phase and

gas phase will reach equilibrium through evaporation effect. In other words,

Water migrates from the high aw area to low aw area. The amount of water which

is available for microbial growth depends on the ability of the other components

in a material to immobilise water. The physical adsorbed water is closely

associated with and relatively difficult to remove from specific materials.

Therefore the water activity cannot be calculated from the moisture content

directly, it must be measured independently. Figure 2.12 shows that typical

isotherms of different solid materials used in solid-state fermentation. For each

particular solids it will be essential to measure isotherms individually. Nagel et al.

(2001) and Calçada (1998) fitted the equation 2-1 and 2-2, respectively, to present

the isotherm of wheat and corn as a function of its water content respectively.

𝑎𝑤𝑠 = −2.917 +3.919

1+(𝑊 0.0344)⁄ −1.861 (Wheat) Equation 2-1

𝑎𝑤𝑠 = (1 − exp(−𝑊(1.275−0.0029𝑇𝑠 exp(2.9 + 0.004𝑇𝑠)))1 0.32⁄ (Corn)

Equation 2-2


34

Figure 2.12 Isotherms of solids used in solid-state fermentation (- - -) Desorption isotherm of autoclaved wheat grains at 35°C; (-) Isotherm of corn at 20°C (lower curve), 35°C (middle curve) and 50°C (upper curve) Adapted from (Calçada, 1998; Mitchell et al., 2006; Nagel et al., 2001a)

2.5.4.5 Effect of pH

Filamentous fungi have good growth over a wide range of pH (2 - 9) with an

optimal range of 3.8 to 6.0 (Gowthaman et al., 2001). For solid substrate

cultivation, pH control during the fermentation is extremely difficult as free water

is absent and cannot easily monitored by any instruments (Manpreet et al., 2005;

Saucedo-Castaneda et al., 1992). Also, it is not practical to add acid or alkali to the

medium to adjust the pH during the fermentation due to the lack of mixing and

possibility of changing moisture content. To minimise pH variation, buffers can be

used, for instance, urea as a nitrogen source and Mandel's medium as mineral salts

source, relieving the difficulties in controlling and maintaining pH during

fermentation (Saucedo-Castaneda et al., 1992).

2.5.4.6 Effect of aeration

Aeration is a significant parameter in SSF because of oxygen consumption in the

aerobic bioprocess as well as heat and mass transport in a heterogeneous


35

environment (Pandey and Larroche, 2008). Because there is no free water and

steady mixing in SSF process, oxygen transfer is limited to the liquid film of the

solid surface and stagnant. Although all concentrations (oxygen and temperature)

are uniform at the beginning of fermentation, the oxygen and temperature

gradient will develop as the fermentation progresses due to mass transfer

resistances (Gowthaman et al., 1993). In order to perform efficient solid-state

fermentation, these gradients must be minimised. Aeration could provide four

beneficial functions for SSF, namely (1) to maintain aerobic conditions, (2) to

remove CO2 from solid bed, (3) to manage the temperature of bed and (4) to

maintain the moisture level of bed (Krishna, 2005; Raimbault, 1998). It must be

emphasized, however, unsaturated air supply to solid state fermentation could

lead to intensive evaporation happened, causing water loss of fermenting solids

and inhibit fungal growth.

2.5.5 Reactor

A solid-state fermentation bioreactor is designed to provide the desired

environment for the fermentation, where biological reactions carry out converting

the raw materials into products. According to Mitchell et al., (2000) there are four

main types of reactor on the basis of how they are mixed and aerated (Figure 2.13).

This classification covers the most common bioreactor types used in solid state

fermentation. These are the tray bioreactor, the packed-bed bioreactor, the

rotating drum bioreactor, and the mechanically mixed bioreactor. These are

briefly explained in the following sections.

Tray bioreactor

A tray bioreactor typically comprises a large number of individual flat trays,

stacked one above the other with a gap. Aeration air with control of humidity and

temperature is forced into the chamber and circulates around the surfaces of trays.

Individual trays are made of wood, metal or bamboo. They have shallow depth (2

to 4 cm) and perforated bottoms to increase the accessibility to oxygen and heat

dissipation (Gowthaman et al., 2001; Krishna, 2005; Mitchell et al., 2006).


36

Figure 2.13 Basic design features of the diverse solid-state fermentation bioreactors. Adapted from (Mitchell et al., 2006)

Packed-bed bioreactor

A Packed-bed bioreactor in which the solid is generally packed into cylindrical

column and air is blown in the base plate from the bottom to provide oxygen and

cool the bed (Mitchell et al., 2000). For commercial implementation of solid state

fermentation, packed-bed bioreactors have the advantage of simple features,

larger capacity and better aeration control than tray bioreactor. Moreover, It is

easy to connect a trickle bed extractor to column reactor for product recovery

after the fermentation (Gowthaman et al., 2001; Krishna, 2005). However, it has

been reported that temperature and steep gas occur in this type of bioreactor,

even though the saturated air was supplied to alleviate this problems. Thus, Lu et

al. (1998) proposed the multi-layer packed-bed reactor to improve the mass

transfer and heat dissipation and reduce the risk of channelling happened in the

traditional packed bed bioreactor.

Rotating drum bioreactor

A rotating drum bioreactor in which the bed is continuously mixed or mixed

periodically with a specific frequency (Mitchell et al., 2006). They typically are


37

horizontal or inclined cylinders which allow the mixing by rotation of the partially

filled solid bed. The drum is rotated slowly to gently mix the substrate around 1-

15 rpm. The tumbling reaction could reduce the heterogeneity of solid substrate

and heat accumulation during fermentation (Gowthaman et al., 2001). However,

the solid particles tend to agglomerate over a period of time in this type of

bioreactor and also the rotational action could damage shear sensitive mycelium

of fungal cells (Gowthaman et al., 2001).


38

2.5.6 Mathematical models of SSF

In solid-state fermentation, macroscale and microscale sub-models can be

thought in the development of mathematical models. The heat and mass transfer

across the bed as a whole and between the headspace and the bioreactor wall are

described in the macroscale sub-model (Figure 2.14). In contrast, the microscale

sub-model describes the growth kinetics of the microorganism and how these

kinetics depend on various mechanisms that occur at the scale of individual

substrates (Viccini et al., 2001).

Figure 2.14 The marcoscale and microscale process happened within an SSF bioreactor (Viccini et al., 2001).

Because of the complicated transport phenomenon within SSF bioreactors, the

majority of bioreactor models only have simple empirical kinetic sub-models

(Mitchell et al., 2003). Different significant gradients (gas, moisture and


39

temperature concentration) happened within a packed-bed bioreactor can be

measured during fermentation. Therefore, the balance equations in SSF

bioreactors are required to use partial differential equations, which need more

computational effort than ordinary differential equations to represent the

balances of systems. Thus, once the system could provide efficient mixing and

good heat dissipation at the marcoscale, it could be considerably simplifying the

balance equations and allowing the assumption that whole substrates are

subjected to identical external conditions (Mitchell et al., 2004).

The microscale phenomena included in the growth kinetic model comprise: the

growth rate of the microorganism depends on the environmental conditions such

as pH, nutrient concentrations, temperature, and water activity; intra-particle

processes such as hydrolysis of polymers and the diffusion of enzymes and

hydrolysis products (Viccini et al., 2001). Further discussion on the kinetic of fungal

growth is included in Chapter 7, where different techniques based on dry weight,

glucosamine and metabolic measurements are analysed and studied. The balance

equations of packed-bed bioreactor will be also investigated.

2.5.7 Application of SSF

A solid culture fermentation has been widely used especially in East Asia for

traditional food fermentation, ethanol production by Koji process, mould-ripened

cheese, and composting process (Kim et al., 1985). Nowadays, numerous products

such as enzymes, organic acids, biogas, compost, antibiotics, surfactants,

fermented foods are produced by SSF techniques (Manpreet et al., 2005; Robinson

et al., 2001).

Since in this research, SSF would be conducted using Trichoderma longibrachiatum,

only the SSF application involving Trichoderma species are reported. The potential

of Trichoderma species as lignocellulose-degrading microorganisms was

recognized in the early 1960s (Selby and Maitland, 1967). Trichoderma species are

frequently found growing in moist soil and on other substrates, such as wood and


40

bark. In addition, they are well known for its ability to produce certain extracellular

enzymes and are already used for production of a variety of extracellular enzymes

and metabolites, such as cellulase, hemicellulase, beta-glucosidase, proteins at an

industrial scale.

Nowadays, filamentous fungi are the major producer for commercial cellulases

production. Cellulolytic fungi belonging to the genera Trichoderma (T. viride,

T. longibrachiatum, T. reesei) have been considered the most powerful and

productive destroyers of crystalline cellulose (Gusakov, 2011; Merino and Cherry,

2007). Commercial cellulase preparations based on several Trichoderma species

are produced on an industrial scale by many companies worldwide (Table 2.4). The

demand for cellulases is consistently on the rise because of its various applications

such as textile detergent, bioenergy and paper industries. However, commercial

enzymes are still predominantly produced by submerged fermentations instead of

solid state fermentations due to several challenges (Waites et al., 2009).

Table 2.4 Commercial cellulases produced by companies and their sources

(Singhania et al., 2010)

Enzyme samples Supplier Source

Cellubrix (Celluclast) Novozymes, Denmark T. longibrachiatum and A. niger

Novozymes 188 Novozymes A. niger

Cellulase 2000L Rhodia-Danisco (Vinay, France) T. longibrachiatum/T. reesei

Rohament CL Rohm-AB Enzymes (Rajamaki, Finland) T. longibrachiatum/T. reesei

Viscostar 150L Dyadic (Jupiter, USA) T. longibrachiatum/T. reesei

Multifect CL Genencor Intl. (S. San Francisco, CA) T. reesei

Bio-feed beta L Novozymes T. longibrachiatum/T. reesei

Energex L Novozymes T. longibrachiatum/T. reesei

Ultraflo L Novozymes T. longibrachiatum/T. reesei

Viscozyme L Novozymes T. longibrachiatum/T. reesei

Cellulyve 50L Lyven (Colombelles, France) T. longibrachiatum/T. reesei

GC 440 Genencor-Danisco (Rochester, USA) T. longibrachiatum/T. reesei

GC 880 Genencor T. longibrachiatum/T. reesei

Spezyme CP Genencor T. longibrachiatum/T. reesei

GC 220 Genencor T. longibrachiatum/T. Reesei

Accelerase®1500 Genencor T. Reesei

Cellulase AP30K Amano Enzyme A. niger

Cellulase TRL Solvay Enzymes (Elkhart, IN) T. reesei/T. Longibrachiatum

Econase CE Alko-EDC (New York, NY) T. reesei/T. Longibrachiatum

Cellulase TAP106 Amano Enzyme (Troy, VA) T. viride

Biocellulase TRI Quest Intl. (Sarasota, FL) T. reesei/T. Longibrachiatum

Biocellulase A Quest Intl. A. niger

Ultra-low microbial (ULM) Iogen (Ottawa, Canada) T. reesei/T. Longibrachiatum


41

Several industrial important enzymes produced under SSF using Trichoderma

species have been extensively studied. For example, (Brijwani et al., 2010) co-

cultivated T.reesei and A. oryzae to produce cellulase enzymes in the SSF using

soybean hull and bran as a nutrient medium. Numerous studies cultivated T.

longibrachiatum to produce cellulase and xylanase in SSF using wheat straw,

wheat bran, and sugarcane straw as the solid substrate (Azin et al., 2007; Guerra

et al., 2006; Kovacs et al., 2004; Ridder et al., 1999). As can be seen above, fungi

in the genus Trichoderma have an ability to produce cellulolytic enzymes on a

broad spectrum of substrates, especially in lignocellulosic materials. This feature

leads to an extension of the study aiming to utilize agricultural residues to produce

on-site enzymes and lignocellulose deconstruction simultaneously which is

reported in this thesis.

Enzymatic hydrolysis of lignocellulose A wide range of agricultural wastes include protein, carbohydrates, and fibre in

significant amounts, making it an ideal substrate to produce value-added products.

However, many microorganism prefer to use monosaccharide (glucose, xylose etc.)

instead of polysaccharide. Therefore, hydrolysis of these natural polymer

(cellulose, hemicellulose) to produce sugars after pretreatment process is

important and critical step for biorefinery.

Today, the major strategy used for lignocellulosic ethanol production comprises

three main steps: (1) pretreatment process (2) enzymatic hydrolysis and (3)

ethanol fermentation. The enzymatic hydrolysis contributes significantly to the

production cost of cellulosic ethanol, and hence the improvement in the enzyme

digestibility efficiency is a prerequisite. As shown in Figure 2.15, a lot of nutrient

materials for growth of microorganisms could be used once these long chain

polymer be degraded. To utilise the lignocellulosic materials completely, different

enzymes need to be required to hydrolyse for specific polysaccharides and

oligosaccharides. However, high cost of commercial enzyme cause obstacle to use

diverse enzyme to obtain abundant nutrient solution. The key method to solve the


42

problem is to produce in-situ enzyme complex from natural materials using fungi

instead of using commercial enzyme.

Figure 2.15 Flow diagram of polysaccharides and the hydrolytic enzymes used to cleave them into shorter polymers and simple sugars (Schuster and Chinn, 2013)

The use of insoluble and highly heterogeneous substrate poses several challenges

in conversion to fermentable sugars. For example, hydrolysis at high solids

concentrations can lead to the problem of product inhibition and insufficient

mixing, which results in lower performance of enzyme digestibility. The presence

of lignin, which shields the cellulose chain and interferes or adsorbs the enzyme

complex, causes non-productive binding. In addition, the enzyme activities may be

decreased as time goes on due to denaturation. There may also be other, as

unidentified, reasons for decreased conversion (Kristensen et al., 2009; Puri et al.,

2013).

At the end of enzyme hydrolysis, high fermentable sugar concentrations are

preferable for the subsequent fermentation. This will increase the product titres

and facilitate the efficiency of downstream processing, particular in product

recovery. However, the heterogeneity and structure of lignocellulosic materials,


43

high viscosity of substrates, is an important factor to limit efficient mixing using

high solid substrates. The viscosity of slurries increases dramatically over a certain

level (typically 20% of solids ratio), and appear the linearity of the solids effect

with increasing loading. One alternative strategy to overcome is the fed-batch

substrate addition, which reduced the initial viscosity to allow well mixing

(Puri et al., 2013).


44

Microbial feedstock production It is widely accepted that the finite resource we currently use as feedstock for the

production of chemicals and energy will have been consumed and chemical

processing will be obliged to turn to bioprocessing gradually to achieve sustainable

development. However, whatever other factors influence the choice, the real

driving force for the adoption of new process is the relative production cost

associated with obtaining materials and processing compared with traditional

process. Also, the cost of microbial medium is one of the major obstruction facing

the successful transition from hydrocarbon-based to sugar-based chemical and

fuel production (Koutinas et al., 2004; Lynd et al., 1999; Webb and Wang, 1997).

2.7.1 Reducing sugars production from lignocellulose

The most common source of carbon for fermentation is fermentable sugar (usually

as glucose, xylose or sucrose). For fermentation medium preparation, hydrolysing

lignocellulose to fermentable monosaccharides efficiently is a major task. Overall,

typical sugar production from lignocellulose includes several steps: biomass

pretreatment, detoxification of liquid fraction and cellulose hydrolysis

(Figure 2.16). As mentioned before in section 2.4, the typical principle of

pretreatment is to hydrolyse hemicellulose, lignin into solution and remains

cellulose unaltered in the solid residue and can be further processed to produce

glucose. Acid or steam pretreatment conducted at a high temperature is one of

the most effective ways due to high glucose yield after enzyme hydrolysis. The

severe conditions, however, lead to microbial inhibitors generation from

monosaccharides such as furfural and hydroxymethyfurfural (HMF) (Cardona et al.,

2010). Also, alkaline pretreatment can induces the inhibitors produced, the costly

detoxification processes are necessary to remove these inhibitory byproducts (Bak

et al., 2009; Sun and Cheng, 2002).


45

Pretreatment

Detoxification

Cellulosehydrolysis

Acid treatment Akaline treatment Thermal treatment Ionic liquid treatment Organsolv treatment Biological treatment

Neutralisation Overliming Adsorption Ion exchange resin Organsolv treatment Electrodyalisis

Acid hydrolysis Enzymatic hydrolysis Microbial cultivation

Xylose-rich solution

Glucose-rich solution

Lignocellulose

Liqu

id f

ract

ion

Soli

d f

ract

ion

Figure 2.16 Processes scheme of fermentable sugars production from lignocellulose

Steam pretreatment followed by enzymatic hydrolysis of wheat straw achieved

244 mg/g raw material of sugar yield (Zabihi et al., 2010). Guragain et al. (2011)

reported 223 mg/g raw material could be obtained when dilute acid pretreatment

(1% H2SO4, v/v) was employed on the wheat straw. Acid pretreatment (10% H2SO4,

w/w) at 121°C for 20 min followed by enzymatic hydrolysis resulted in 590 mg/g

raw material of sugar yield from sugarcane bagasse (Giese et al., 2013). Zhao et al.

(2009) also discussed alkali–peracetic acid pretreatment of sugarcane bagasse at

121 °C for 2 h followed by 120 h of enzymatic hydrolysis reached 92.04% of

reducing sugars yield from raw sugarcane bagasse.

Unlike severe reaction occurred by chemicals, fungi pretreatment has superior

selectivity towards chemical bonds between lignin and polysaccharides and loosen

the lignocellulose structure without inhibitors formation. Figure 2.17 shows the

configuration of two different biological pretreatment strategies for

lignocellulose-based sugar production employed in the latest research. In the

strategy I, white-rot fungi have been introduced to disrupt complex cell wall,

particularly lignin degradation, in order to expose polysaccharides for further

hydrolysis. Solid fraction from biological pretreatment or chemical hydrolysis


46

followed by fungal pretreatment contains the cellulose and hemicellulose which is

later hydrolysed. On the other hand, liquid fraction contains lignin, fungal cells and

other metabolites such as enzymes after pretreated substrates was loss during

washing. Shi et al. (2009) presented that pretreatment of cotton stalk with P.

chrysosporium followed by enzyme digestibility led to 55.6 mg/g raw materials of

sugar yield. It was also reported that the enzymatic hydrolysis of sugarcane

bagasse that had been treated with C. caperata and P. florida were 1.5 and 2.36

times greater, respectively, than that of untreated sugarcane bagasse (Deswal et

al., 2014). In the different pretreatment strategies, the reducing sugars released

from chemical pretreatment were comparatively higher than the biological

treatment (Table 2.5).

Table 2.5 Total reducing sugars from bagasse after different pretreatments and enzymatic hydrolysis

Pretreatment Saccharification yield

(g/g pretreated bagasse) Reference

Sulfuric acid treatment 0.59 Giese et al., 2013

Alkali-peracetic treatment 0.92 Zhao et al., 2009 Microwave-acid treatment 0.83 Binod et al., 2012 Fungal treatment (P. florida) 0.3 Deswal et al., 2014 Fungal treatment (C. caperata) 0.19 Deswal et al., 2014


47

Biological pretreatment or Combined chemical

pretreatment and biological pretreatment

Enzymatichydrolysis

Lignin Mycelium and fungal cells Metabolites Nutrients (FAN, IP, etc.)

Sugar-rich solutions

Lignocellulose

Liqu

id f

ract

ion

Solid

frac

tio

n

Wastes

CommercialEnzymes / On-site enzyme

production from SSF or SmF

Enzymatic hydrolysis

Sugar-rich solutionsLignocellulose

Strategy I

Strategy II

Biological pretreatment or Combined chemical

pretreatment and biological pretreatment

Solid fraction

Figure 2.17 Schematic diagram of a sugar production based on the biological

pretreatment of lignocellulose

Another strategy is to use the whole fermented medium, containing the enzymes,

mycelium and the solid residues for the subsequent saccharification to avoid

filtration steps and unnecessary effluent streams. A similar process has been

reported, the whole solid state fermentation (SSF) of sugarcane bagasse using T.

reesei for the further hydrolysis (Pirota et al., 2013). Pensupa et al. (2013)

demonstrated the use of whole SSF cultivated medium of acid-treated wheat

straw for the further digestibility using in-situ enzymes. In addition to SSF, whole

submerged fermentation (SmF) broth of T. reesei has been used for the hydrolysis

of spruce and corn cob (Kovács et al., 2009; Liming and Xueliang, 2004).

However, it should not be negligible to consider all the nutrients required to

support the majority of microorganisms and so, in principle, require little

supplementation of nitrogen, phosphorous, etc. The majority of researches on

ethanol production or other products through fermentation have used media

containing complex microbial growth supplement, like yeast extract, beef extract

or other nutrient broth, to accomplish high ethanol yield (Asachi et al., 2011). This


48

kind of nutrient regeneration has been applied in the industry for many years. For

example, yeast are disrupted by exogenous (hydrolysis) or endogenous (autolysis)

enzymes to produce a nutrient-rich medium (Koutinas et al., 2005). It is, however,

not realistic for industrial ethanol production because of the cost of the

supplement. The cost for microbial bioconversion media can account for 30% to

50% of the total production cost in the commodity sector. (Hofvendahl and Hahn–

Hägerdal, 2000; Makkar and Cameotra, 2002; Rodrigues et al., 2006). As a

consequence, there is a tendency towards not only alternative source of carbon

but also other nutrients supplements for fermentation in recent years.

2.7.2 The nutrient-rich microbial feedstock production

Research in the Satake Centre for Grain Process Engineering (SCGPE) has been

focused on the development of a cost-competitive and sustainable wheat-based

feedstock for microbial fermentations. Further details will be discussed in the

following sections.

2.7.2.1 Process description

An efficient production and utilisation of enzymes (e.g. cellulose, xylanase,

β-glucosidase) can affect the lignocellulose-based bioprocessing development.

Fungal fermentations using agricultural wastes (e.g. sugarcane bagasse, soybean

hull) can produce the majority of celluloytic enzymes. Not all microorganisms like

fungi have the capability of degrading cellulose, hemicellulose, or lignin directly

and efficiently into metabolites of interests. Fungi can grow towards nutrient

sources and penetrate into solid substrates by their hyphae. Enzyme are

synthesised inside the cell and then secreted outside the cell, where their function

is to break down complex macromolecules (e.g. starch, protein, cellulose,

hemicellulose, lignin) into smaller units (e.g. glucose, xylose, amino acids) to be

absorbed by the cell for growth and assimilation.

At the Satake Centre for Grain Process Engineering (SCGPE), researchers have

published a wide range of biorefining strategies based on fungal fermentation for

the fuels, platform chemicals, and biodegradable plastics production. Cereal crops


49

or rapeseed meal were enzymatically converted into a generic fermentation

feedstock, enriched in amino acids, peptides and various micro-nutrients, using

crude enzymes produced via solid state fermentation by a fungal strain such as

Aspergillus oryzae and Aspergillus awamori. The above studies showed that on-

site fungal fermentations could provide not only enzymes for the hydrolysis of

starch, cellulose or hemicellulose, but also a nutrient-rich solution from the further

hydrolysis of fermented residues (Du et al., 2008b; Koutinas et al., 2007a, 2004;

Wang et al., 2010). Such solids remain lots of fungal cells and undigested polymers

after fungal fermentation. Under autolytic conditions, it can induce the secretion

of lytic enzymes by fungi, which will deconstruct remaining fungal fermented

media components and cellular components. Not only Aspergillus species could

be employed in this nutrient generation process, but also other fungi such as

Mucor indicus and Grifola frondosa (Asachi and Karimi, 2013; Xu et al., 2012). In

addition, the process of nutrient regeneration has been industrially applied in the

case of yeast for a long time, which are broken down by endogenous (autolysis) or

exogenous (hydrolysis) enzymes to generate nutrient-rich solutions (Koutinas et

al., 2005, 2004). The above concept could be employed in lignocellulose-based

process, producing not only sugars but also nutrients (amino acids, peptide,

nucleotides, phosphorous and vitamins) as compared to current industrial

practices for pure sugar production through different strategies from

lignocellulosic materials.

2.7.2.2 Fungal autolysis

Cell autolysis is a natural degradation process, which starts after the exhaustion of

external nutrient supply and reserve substances. This triggers the disintegration of

cellular components by the endogenous enzymes contained in cells providing a

“self digestion” process for the cell. Autolysis is a natural part of filamentous fungal

bioprocesses, and its onset can be advanced or retarded by both intrinsic and

extrinsic factors (Figure 2.18).


50

Enzymatic reaction upon fungal cell components may lead either from the attack

of enzymes released by other microorganisms or from the action of autolytic

enzymatic complexes originated in the protoplasm of fungal hyphae. Although the

activation and regulation of autolytic hydrolases is complex, the major groups may

be categorised into the basis of the specific substrate degraded, that is, proteases,

glucanases, chitinases and phosphatases (Perez-Leblic et al., 1982; Santamaria and

Reyes, 1988; White et al., 2002). Like other metabolic reaction mechanisms, fungal

autolysis generally relies on the synergistic action of those enzymes that can

deconstruct building blocks (e.g. protein, glucan and chitin) of fungal cell wall.

These enzymes are de-repressed and tend to reach maximal levels under

conditions of extrinsic factors (limiting glucose or nitrogen, physical stress) or

intrinsic factors (cell aging stage, hyphal differentiation).

Figure 2.18 Overview of fungi autolysis (White et al., 2002)


51

Little is known about the effects of reactive oxygen in the filamentous fungi. Thus,

investigations about the relationship between oxidative stress and fungal autolysis

could be relevant to submerged fungal bioprocesses. This significance is due to the

supply of high dissolved oxygen concentrations for most fungal growths at the

industrial scale production (White et al., 2002). In 2010, Wang et al. showed that

fermented materials were transferred to another vessel for further hydrolysis at

the end of solid-state fermentation. Biological reaction in the process of hydrolysis

might include not only enzymatic hydrolysis of materials but also the autolysis of

fungi cells. The oxygen limited environment could lead the autolysis of strict

aerobic fungi in a submerged environment (Wang et al., 2010).

Chapter 3 Objective and research programme

52

CHAPTER 3

Objectives and research programme

Introduction In the previous chapter it was pointed out that lignocellulosic residues do not

currently compete with food demands and can therefore provide a low cost

feedstock for production of commodity chemicals and fuels, offering economic

and environmental advantages. The aim of the project described in this thesis was

to demonstrate the feasibility of utilising lignocellulosic residues to produce value-

added products through sequential bioprocessing. As part of this goal, the project

was focused on the development of a novel strategy for the production of generic

fermentation feedstocks based on solid state fermentation (SSF) bioprocessing

using sugarcane bagasse and soybean hull.

The following section 3.2 is basically a description of the research idea based on

the original research plan, following an analysis of the lignocellulosic biorefinery

process and numerous researches on grain-based generic fermentation feedstock

production in the Satake Centre for Grain Process Engineering (SCGPE). The origin

of the proposed research idea came from the modification of typical lignocellulose

pretreatment process, advantageous features of solid state fermentation and the

production of the generic feedstock from wheat grains and rapeseed meals. The

resultant study focused primarily on the development of a process for the

production of a generic microbial feedstock. This was based on hydrolysis and

fungal autolysis as a nutrient production method using fermented solids from solid

state fermentation of Trichoderma longibrachiatum on agricultural residues.


53

Proposed bioprocess concept In conventional processing for lignocellulose, the pretreatment process involves

either physical, chemical or physico-chemical treatment. These are either energy

intensive or produce large effluent discharge problems. The use of a biological

treatment instead of other methods could reduce considerably the energy

consumption and effluent release of the process.

Attempts at bioprocessing involving submerged fermentation (SmF) using

filamentous fungi have suffered from viscosity problems and poor mass transfer

due to difficulty in controlling the fungal morphology during fermentation and

lignocellulose suspension in liquid medium (Lan et al., 2013). The inherent

advantage of solid state fermentation is that it provides growth conditions that

are similar to the environment to which filamentous fungi are naturally adapted.

Higher enzyme concentrations could be achieved because of better interaction

between the microorganism and the substrate in SSF.

This novel process concept is represented schematically in Figure 3.1. The

proposed process includes two key steps. In the first, a SSF with the fungus

Trichoderma longibrachiatum using sugarcane bagasse and soybean hull, is used

to simultaneously secrete cellulolytic enzymes and deconstruct recalcitrant

lignocellulose. This consolidated fungal fermentation not only eliminates the

expensive pretreatment stage but also provides abundant enzymes (cellulase,

beta-glucosidase, xylanse etc.) for further hydrolysis. At the end of the SSF, the

whole fermented solids, containing the enzymes, fungal mycelium and residual

substrate, are transferred and blended in sterile distilled water to cut the

mycelium and make the suspension homogeneous. The suspension is then stored

at higher temperature and oxygen-limited conditions to elevate enzyme activities

in the mash for hydrolysing the remaining substrates to produce sugars, free

amino nitrogen (FAN), inorganic phosphorous (IP) and other nutrients. The

purpose of using high temperature for hydrolysis is, not only to prevent fungi

growth, but also to achieve optimal enzyme activities for hydrolysis of the


54

lignocellulose. Previous studies have shown that the growth of bacterial

contaminants was also effectively prevented at temperatures above 50 °C in

hydrolysis of fermented rapeseed meal (Wang et al., 2010). On the other hand,

oxygen-limited conditions could trigger fungal autolysis and release nutrients by

degrading cell walls to give the generic microbial feedstock more nutrients (sugars,

FAN, IP etc.) rather than sugar solution only. Fungal cell wall disruption and

macromolecules hydrolysis, therefore, lead to the production of a nutrient-rich

solution containing amino acids, peptides, nucleotides, phosphorous and vitamins

as well as other trace elements.

Figure 3.1 Proposed process for a generic microbial feedstock production from lignocellulose

The further fermentation step is carried out using the microbial feedstocks

obtained from the above proposed process. For example, submerged

Fermentation with yeast was used to test the suitability of the microbial

feedstocks for the production of the ethanol (reported in chapter 8).


55

Research objectives In order to establish a process for the biological pretreatment of sugarcane

bagasse, four major objectives were identified. The first was to grow the fungus

on the substrate. Secondly, testing the enzymes produced during growth for the

ability to further hydrolyse the substrate was key to the process. The third and

fourth objectives were then to carry out trials in bioreactors and to use the

resultant medium for a subsequent fermentation process. Each objective

is described in more details in the following sections.

3.3.1 Growth and adaptation of T. longibrachiatum

The early part of the project was focused on acquiring knowledge about the fungi

growth on lignocellulosic material as carbon source. Trichoderma longibrachiatum

cultivation in varied conditions, particle size, C/N ratio, different proportions of

substrates, incubation time and environment moisture level, were investigated.

After solid state fermentation (SSF), the whole fermented solids were transfer to

sequential hydrolysis stage. The principal components in the nutrient medium

obtained from the solid state fermentation followed by further hydrolysis are

reducing sugars and free amino nitrogen (FAN). These total reducing sugars and

FAN were to be used as indicators to evaluate the performance of the bioprocess.

The objectives of these experiments were to identify a set of improved conditions

for the growth of T. longibrachiatum on sugarcane bagasse and soybean hull and

their effects on nutrients production.

3.3.2 Sequential hydrolysis of fermented solids

The aim of this part of the study was to investigate the optimum hydrolysis

conditions (solid loading ratio, temperature, pH, microbial inhibitor addition) for

efficient microbial feedstocks production from fermented solids of

T. longibrachiatum. Investigations of kinetics on further hydrolysis and fungal

autolysis help to understand the hydrolysis profile for further application.

Moreover, the characteristics of cellulase, xylanase and beta-glucosidase were


56

investigated by means of determination of physico-chemical parameters

e.g. optimal temperature and pH.

3.3.3 Bioreactor Studies

This experimental stage involved studies of microbial feedstocks production

through solid state fermentation (SSF) in a single-layer tray bioreactor, a multi-

layer tray bioreactor and a packed-bed bioreactor. To study the growth kinetics of

the microorganisms in SSF, biomass content measurement, substrate

concentration and other process parameters are required. Because separating

filamentous fungi from solid substrates is difficult, indirect measurements such as

carbon dioxide, oxygen and glucosamine were employed to examine

quantitatively the fungal growth, substrate consumption kinetics in solid state

fermentation.

3.3.4 Ethanol production from bagasse derived feedstock

To produce ethanol, S. cerevisiae was used in the nutrient-rich medium produced

from sugarcane bagasse and soybean hull. Nutrient utilisation (sugars, FAN and

Inorganic phosphorous) as well as ethanol production were observed then

compared with that from glucose-based media (glucose and yeast extract). A mass

balance of overall ethanol production using feedstock derived from sugarcane

bagasse and soybean hull was presented. A preliminary consideration of economic

feasibility, based on the results of the study, provided a further objective.

Chapter 4 Materials and methods

57

CHAPTER 4 Materials and methods

Introduction The experimental methods in all practical work described in this thesis are

presented in this chapter, including fermentation methodology and product

analysis. Analytical methods are also given and theoretical information presented

where appropriate. Research results from experiments are presented in Chapters

5, 6, 7 and 8, where brief summaries of the relevant experimental methods are

also given.

Materials and microorganisms

4.2.1 Sugarcane Bagasse and Soybean Hull

Sugarcane bagasse was provided by Dr. R.F. Chang, Taiwan, packaged in vacuum-

packed bags to maintain freshness (Figure 4.1). To adjust the different particle

sizes for experiments, sugarcane bagasse was ground using a kitchen blender then

passed through three different sieves (1.4 mm, 0.85 mm and 0.5 mm) and the

fractions were stored in air-tight plastic containers until used.

Soybean hull was obtained from Cargill Plc, Liverpool, United Kingdom (Figure 4.1).

It was also ground using a kitchen blender then passed through a 2 mm sieve to

remove other debris and stored at room temperature in an air-tight plastic

container. After adjustment to the desired moisture content and mixed substrates,

the conditioned substrates were sterilised at 120°C in the autoclave for 20 min.

Prior to carrying out chemical analysis, both substrates were ground with a small

hammer mill (Glen Creston, DFH48) fitted with a 0.8 mm sieve for 3 times for

accurate sampling.


58

Figure 4.1 Appearance of (a) sugarcane bagasse and (b) soybean hull

4.2.2 Microorganisms and inoculum preparation

4.2.2.1 Microorganism used in solid state fermentation

Many microorganisms are known to produce different type of lignocellulolytic

enzymes. Among them, Trichoderma spp. are widely known as a lignocellulose

decomposer since they are filamentous and have the ability to produce prolific

spores and abundant lignocellulolytic enzymes which can invade substrates

quickly. In this PhD thesis, Trichoderma Longibrachiatum was used because of the

ability to generate high levels of both cellulolytic and xylanolytic enzymes. The

fungus, Trichoderma Longibrachiatum, obtained from the fermentation

engineering laboratory of the School of Chemical Engineering and Analytical

Science, Faculty of Engineering and Physical Science, University of Manchester, UK

was used throughout this study for solid state fermentation.

The spores were purified in order to ensure that the inocula used throughout the

research study were initiated, each time, from a single spore. First of all, a small

amount of the spore suspension (0.5 mL) obtained from previous culture was

spread on the surface of the 50 mL PDA medium (15 g/L agar, 20 g/L dextrose, and

4 g/L of potato extract) in 250 mL Erlenmeyer flasks, and the inoculated flasks were

incubated at 30°C for 7 days. Several glass beads (4-mm diameter) and 50 mL of

sterile 0.1% (v/v) Tween 80 were added to the flasks to extract and form a stock

spore suspension after gentle shaking. Monospore isolation was performed by


59

serially diluting the fungal spore suspension from 101 to 109. A 10 μL aliquot of

each serially diluted spore suspension was plated onto solid PDA medium and

incubated at 30°C for 7 days (Figure 4.2). Then an isolated colony was selected

from the Petri dish and transferred onto slopes of the same sporulation medium

in test tubes for spore formation and incubated for another 7 days at 30°C. After

this incubation period the slopes were transferred and stored at 4°C.

Figure 4.2 Trichoderma Longibrachiatum on PDA medium agar plate

(Growth of colony after 7 days at 30°C).

In these studies, untreated sugarcane bagasse and soybean hull, were used for

growing T. longibrachiatum. The ratio of sugarcane bagasse and soybean hull were

adjusted according to the purpose of experiments. For each set of preliminary

experiments in Petri dishes (chapter 5 and 6), a total weight of 4 g (dry weight) of

the mixed substrates were used by. All samples were put into 250 mL flasks and

sterilized at 121°C for 20 min. The substrates were allowed to cool to room

temperature before inoculating with T. longibrachiatum and moistened with an

amount of sterilized mineral salt medium (CaCl2‧2H2O: 0.5g/L; KH2PO4: 3g/L;

MgSO4: 0.5g/L) to obtain the desired moisture content. The spores were harvested

from the slope with 10 mL of sterile 0.1% (v/v) Tween 80. 1 mL of the spore

suspension (106 spores/mL) was inoculated and mixed into the substrate. Then

whole inoculated samples were transferred to petri dishes. All petri dishes were


60

incubated at 30°C for 5 days, and samples were taken to measure total reducing

sugar, free amino nitrogen (FAN), moisture content, weight loss and enzyme

activity (cellulase, xylanase and beta-glucosidase).

4.2.2.2 Microorganism used for ethanol fermentation

Yeast fermentations were carried out using Saccharomyces cerevisiae ATCC 22602

for the production of ethanol. Yeast cells were cultivated in standard YDX medium

(5 g/L yeast extract, 10 g/L xylose, and 5 g/L glucose) for inoculum preparation.

Reactor systems

4.3.1 Petri dish

Petri dishes of 10 cm of diameter and 1 cm height were used during the project to

carry out several preliminary experiments. These simple reactor systems which

have some similarities with tray bioreactors were filled with the inoculated

substrates and were placed in an incubator at 30°C where the cultivation was

carried out statically. Individual petri dishes, from a parallel set, were sacrificed for

analysis as required.

4.3.2 Circular tray bioreactor

Circular tray bioreactors were used as an extension to the simple petri dish system.

One of these is shown in Figure 4.3, and consisted of a single circular perforated

tray with 10.0 cm diameter. The bioreactors were made of polycarbonate and

were autoclave compatible. The system (Figure 4.4) was used to determine the

kinetic parameters for the fungal growth and the consumption of substrate. Due

to their similarity, five circular tray bioreactors could be operated in parallel, and

like petri dishes, one could be sacrificed per day for analysis (e.g. at specific time

24, 72, 96, 120, 168 h). The bioreactors were connected to humidifier and gas

distributor and fermented in the incubator at 30°C. The airflow of air supply was

maintained at 0.6 L/min per gram of substrate for each bioreactor. The outlet gas

was passed through a filter and silica gel tube to reduce the humidity and


61

impurities of exhaust gases before entering to a gas analyser (FerMac 368,

Electrolab, UK) to sample on-line CO2 and O2 data.

Figure 4.3 Left: A circular tray bioreactor. Right: A perspective view of bioreactor

Figure 4.4 A diagram of the system developed for on-line automated monitoring of solid state fermentation (1) Regulated pressure air inlet; (2) 0.2 µm filter (3) humidifier; (4) air distributor; (5) Circular tray fermenters; (6) Silica gel tube (7) Gas analyser.


62

4.3.3 Multi-layer tray bioreactor

As shown in Figure 4.5, the multi-layer tray bioreactor contained three sieve trays

with 10.0 cm diameter and 5.0 cm height, which were tightly stacked one over

another, and a bottom tray that was closed. This bottom tray, with the same

diameter and 3.5 cm height, acted as an air distributor. The forced air passed from

the bottom to the top tray by continuous aeration. The stacked trays were sealed

in such a manner that prevented air exchange from the outside to the inside

environment and vice versa. The bioreactor, adapted from a set of laboratory

sieves, was constructed from stainless steel and aluminium. The mesh bases, with

specific aperture sizes (500 and 600 μm) allowed uniform distribution of air, as

well as supporting the solid particles on the tray.

Figure 4.5 Left: A multi-layer trays bioreactor. Right: A perspective view of bioreactor

A schematic diagram of the multi-layer tray bioreactor system is shown in Figure

4.6. The compressed air entered the system at 0.6 L/min·g and was sterilised using

an air filter. Sterilized thermocouples were positioned at all three trays to record

the bed temperature using a multichannel temperature data logger (Microlab II,


63

Aglicon, UK). The outlet gas was passed through a filter and silica gel tube to

reduce the humidity and impurities of exhaust gases before entering to a gas

analyser (FerMac 368, Electrolab, UK) to sample on-line CO2 and O2 data.

Figure 4.6 Schematic diagram of the multi-layer tray bioreactor system (1) Compressed air, (2) air flow meter, (3) 0.2 µm air filter, (4) humidifier, (5) water bath at 30°C, (6) incubator at 30°C, (7) multi-layer circular bioreactor, (8) silica gel,

(9) thermocouples type K, (10) temperature data logger, (11) gas analyser, (12) computer

4.3.4 Packed-bed bioreactor

The generic microbial feedstocks production using T. longibrachiatum was

implemented in a 1.5 L packed bed bioreactor. After the inoculation, the

substrates were transferred to the sterilised reactor (1.5 h at 121°C), which was

set up as shown in Figure 4.7.

The reactor consisted of a sterilisable glass cylinder of 8 cm diameter and 30 cm

height, closed at both ends with stainless-steel plates. The bottom plate had a port

for air inlet (0.6 L/min·g) and the top plate had a port for the exhaust gas. Three

temperature probes (thermocouples type K) at 5.5, 13.8, and 21.9 cm from the

bottom and two sampling points at 6.4 and 17.4 from the bottom were located

through the glass cylinder. The reactor was placed into an incubator at 30°C


64

instead of using the water jacket. Sterilized thermocouples were used to record

the bed temperature using a multichannel temperature data logger (Microlab II,

Aglicon, UK). The outlet gas was passed through a filter and silica gel tube to

reduce the humidity and impurities of exhaust gases before entering to a gas

analyser (FerMac 368, Electrolab, UK) to sample on-line CO2 and O2 data.

Figure 4.7 Schematic diagram of the 1.5 L packed-bed bioreactor system (1) Compressed air, (2) air flow meter, (3) 0.2 µm air filter, (4) humidifier, (5) water bath at 30°C, (6) relative humidity data logger, (7) incubator at 30°C, (8) packed-

bed bioreactor, (9) thermocouples type K, (10) temperature data logger, (11) silica gel, (12) gas analyser, (13) computer

4.3.5 Enzyme hydrolysis and fungal autolysis system

At the end of solid state fermentations, the contents of petri dishes, bioreactors

or flasks were suspended in sterilised solution (citric buffer or water). The

suspension was stored in 500 mL Duran bottles under oxygen-limited condition at

specific temperature (40 to 60°C), 160 rpm for 48 hours to elevate the enzyme

activities in the solids for hydrolysing the remaining components.

4.3.6 Ethanol fermentation system

The strain Saccharomyces cerevisiae was used for ethanol production experiments.

Fermentation experiments were performed in Erlenmeyer flasks (250 mL)

containing 100 mL of hydrolysates without any supplement, at 32°C for 30 hours.


65

Analytical methods

4.4.1 Fungal spore count

The concentration of the spore suspension was measured using a

haemocytometer (Figure 4.8 and 4.9). The suspension should be dilute enough so

that the spores do not overlap each other on the grid of the haemocytometer and

should be uniformly distributed as it is assumed that the total volume in the

chamber represents a random sample. To prepare the haemocytometer, the

mirror-like polished surface is carefully cleaned with lens paper and 75% ethanol.

The spore suspension is introduced onto the surface using a Pasteur pipette (about

200 µL). The cover slip is then placed over the counting surface. The

haemocytometer is then placed on the microscope stage and the counting grid is

brought into focus at low magnification (100X) and then followed with higher

magnification at 400X. The spores are counted in selected squares so that the total

count is around 100 spores or so (number of spores needed for a statistically

significant count). The main divisions separate the grid into 9 large squares. Each

square has a surface area of 1.0 mm2. The depth of the chamber is 0.1 mm. Each

square of the haemocytometer with the cover slip in place represents a total

volume of 0.1 mm3. The subsequent spore concentration per mL can therefore be

determined (Figure 4.8). If there are less than 50, or more than 200 spores per

large square, the procedure is repeated by using an appropriate dilution factor.

The subsequent spore concentration per mL and the total number of spores is

determined using the following equation.

Number of Spores per mL = [the average count per square] x [dilution factor] x 104

Equation 4-1

Total spores number = spores per mL x the original volume of spores stock

suspension from which spores sample was removed.


66

The volume of suspension needed for the inoculation of the solid was calculated

for each experiment to reach a concentration of around 1 x 106 spores/g solid

substrate.

Figure 4.8 Spores counting on haemocytometer

Figure 4.9 Spores of Trichoderma Longibrachiatum on Haemocytometer grid (magnification 100X)

4.4.2 Analysis of the moisture content of materials

Moisture content of the samples was determined by weight loss after heating to

constant weight at 95°C. After being dried in the oven for 24 hours, the samples

were cooled in desiccators for 30 min before being weighed.


67

Moisture content was calculated as follows:

M(d.b)=(Wi−Wf)

(Wf−Wd)× 100 Equation 4-2

Where:

M(d.b): Moisture content in dry basis (g water/g dry solid) (on a dry solid basis)

Wi: Total weight of the dish with the materials before drying (g)

Wf : Total weight of the dish with the materials after drying (g)

Wd: Weight of the dish (g)

4.4.3 Properties of solid substrate

Following the procedure described by (The GLOBE program, 2002), the bulk

density, particle density and porosity of sugarcane bagasse and soybean hull were

measured using the soil particle density protocol. Density is measured as mass per

unit volume. Solid substrate density depends on the chemical composition and

structure of the solid substrate. Density of any materials (solid substrate) can be

divided into two categories: (1) bulk density and (2) particle density. Bulk density

refers to the volume of the solid portion of the solid substrate particles along with

the spaces where the air and water exist. In contrast, particle density is only

concerned with solid substrate particles and the pore spaces occupied within the

solid substrate. Bulk density is used along with particle density to calculate

porosity. Porosity is defined as the ratio of the volume of voids to the total volume

(void + solid) (Figure 4.10).


68

Figure 4.10 Porosity

Adapted from (The GLOBE program, 2002)

Bulk density

Solid substrates (sugarcane bagasse and soybean hulls) were oven dried at 50°C

for 24h, then poured into a measuring cylinder of known volume (50.0 mL) and

weighed to determine the bulk density. Bulk density of solid particles was

calculated using Equation 4-3.

Bulkdensity(𝜌𝑏) =𝑚𝑎𝑠𝑠𝑜𝑓𝑑𝑟𝑦𝑠𝑜𝑙𝑖𝑑𝑠𝑢𝑠𝑏𝑡𝑟𝑎𝑡𝑒(𝑔)

𝑡𝑜𝑡𝑎𝑙𝑣𝑜𝑙𝑢𝑚𝑒𝑜𝑓𝑠𝑜𝑙𝑖𝑑𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒𝑎𝑛𝑑𝑎𝑖𝑟(𝑚𝐿) Equation 4-3

Particle density

1. The weight of an empty 100.0 mL volumetric flask without a cap was

measured.

2. Approximately 5.0 g of dried solid substrate (50°C for 24h) was weighed

and placed in the volumetric flask using a funnel or a spatula.

3. The weight of the volumetric flask containing the solid substrate was

measured at different moisture contents.

4. About 50 mL distilled water was added to the solid substrate in the

volumetric flask.


69

5. The solid substrate/water mixture was brought to a gentle boil by placing

the volumetric flask on a hot plate. The flask was gently swirled for 10

seconds once every minute to keep the solid substrate/water mixture from

foaming over. The boiling process was continued for 10 min to remove air

bubbles.

6. The volumetric flask was removed from the heating plate and the mixture

was allowed to cool.

7. Once the volumetric flask has cooled, the flask was capped and let to sit

for 24 h.

8. After 24 h, the cap was removed and the flask filled with distilled water, so

that the bottom of the meniscus is at the 100 mL line.

9. The 100 mL solid substrate/water mixture was weighed in the volumetric

flask.

10. The weight values were recorded in the appropriate columns of the

spreadsheet for further data analysis.

11. Particle density was calculated using equation 4.4

Particledensity(𝜌𝑝) =𝑚𝑎𝑠𝑠𝑜𝑓𝑑𝑟𝑦𝑠𝑜𝑙𝑖𝑑𝑠𝑢𝑠𝑏𝑡𝑟𝑎𝑡𝑒(𝑔)

𝑉𝑜𝑙𝑢𝑚𝑒𝑜𝑓𝑠𝑜𝑙𝑖𝑑𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒𝑜𝑛𝑙𝑦(𝑚𝐿) Equation 4-4

4.4.4 Scanning electron microscope (SEM)

Individual solid substrates were taken during fungal fermentation and observed

using a scanning electron microscope (SEM, TESCAN VEGA) in low vacuum mode.

4.4.5 Thermogravimetric Analysis (TGA)

A computerised TA Instruments Q5000 TGA thermogravimetry analyser was

employed in a gas flow of 10 mL/min following the ASTM E1131-03 standard

method.


70

4.4.6 Analysis of glucose

Glucose concentration of liquid samples was analysed using an Analox GL6

analyser. Either two or three readings were taken for each sample. The apparatus

mixes a fixed volume of sample with a reagent that contains glucose oxidase. The

glucose is oxidised to gluconic acid and the reduction of oxygen in the reagent is

measured by an oxygen sensor. The total amount of glucose in the sample is

proportional to the oxygen consumed during the oxidation of glucose. The

analyser can analyse glucose concentrations up to 4.5 g/L. Thus, samples with

glucose concentration above 4.5 g/L were diluted with distilled water and

reanalysed.

4.4.7 Total reducing sugars

Total reducing sugars concentration in the solution was measured by using the

DNS method proposed by Miller (1959) using a spectrophotometer.

The principle involves the determination of total reducing sugars based on the

colour reaction between the reducing sugars and 3,5-dinitrosalicyclic acid. The

reaction yield can be measured as absorbency of the sample at 540 nm using

spectrophotometer. The procedure for sample preparation, analysis and

calculation of total reducing sugars is given in detail below:

Preparation of DNS reagent:

1. Weigh accurately the following chemicals in order (Table 4.1), heat directly on

a heating and stir plate using constant stirring to dissolve. Do not boil the

solution.

2. Make up to 1000 mL with adding distilled water. The reagent should be

dissolved and mixed well. Keep this reagent in an amber bottle at room

temperature.


71

Table 4.1 List of ingredients of DNS reagent

Distilled water 800 mL

3,5-dinitrosalicyclic acid 10.6 g

(C7H4N2O7 ; MW: 228.1; Sigma-Aldrich)

Sodium hydroxide 19.8 g

(NaOH; MW: 40; Fluka)

Sodium sulphite anhydrous 8.3 g

(NaSO3; MW: 126.04; Fluka)

Phenol 2.0 g

(C6H5OH; MW: 94.11; Fluka)

Potassium sodium tartrate 306.0 g

(KNaC4H4O6．4H2O; MW: 282.1; Sigma-Aldrich)

Preparation of standard solution: 0.1 g maltose (C12H22O11 .H2O; MW: 360.3; Fisher Scientific) is weighted accurately

and dissolved in 100.0 mL deionised water in a volumetric flask for 0.1% (w/v)

standard solution. A series of dilutions of the maltose solution is made for

concentrations ranging from 0 to 1.0 mg/mL.

Standard curve:

A series of dilutions of maltose solution corresponding to concentrations ranging

from 0 to 1.0 mg/mL was made in test tubes. In a separate test tube, 0.5 mL

deionised water was used as a blank. For the rest of the procedure, the steps

explained above (under procedure) are followed. The total reducing sugars in

culture filtrate were quantified according to equation 4.5 and the standard curve

of maltose (Figure 4.11), which was linear for maltose concentrations ranging from

0 to 1.0 mg/mL.

The reducing sugar (mg/mL) = A540×D

m Equation 4-5


72

Where:

A540: absorbance of the test sample

m: the slope of maltose standard solution

D: dilution factor of the sample

Figure 4.11 A standard calibration curve for reducing sugar concentration (maltose)

4.4.8 Composition analysis of solid substrate

The solids were analysed for carbohydrate, acid-insoluble lignin and ash content

following the National Renewable Energy Laboratory (NREL) standard protocols

LAP-2, LAP-3 and LAP-5, respectively (NREL, 2005). Part of analytic procedures was

modified by (Ververis et al., 2007).

Procedure for the determination of carbohydrates and lignin in biomass

A. Preparation of sample analysis 1. Weigh 300.0 ±10.0 mg of the sample or QA standard into serum bottle, 100 mL.

2. Add 3.00 ±0.01 mL (or 4.92 ±0.01g) of 72% sulfuric acid to each serum bottle.

Use a glass stir rod to mix for one minute.

y = 0.8569x + 0.0367R² = 0.9727

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

0.0 0.2 0.4 0.6 0.8 1.0 1.2

Ab

sorb

ance

(5

40

nm

)

Maltose concentration (mg/mL)


73

3. Place the bottle on a water bath set at 30 ±3°C and incubate the sample for 60

minutes. Using the stirring rod, stir the sample every five to ten minutes

without removing the sample from the bath. Stirring is essential to ensure even

acid to particle contact and uniform hydrolysis.

4. Upon completion of the 60 minute hydrolysis, remove the bottles from the

water bath. Dilute the acid to a 4% concentration by adding 84 mL distilled

water using automatic burette (dilution can also be done by adding 84 g of

purified water using a balance). Mix the sample by inverting the bottle several

times to eliminate phase separation between high and low concentration acid

layers.

5. Place the bottles in an autoclave for one hour at 121°C.

B. Analyse the sample for acid-insoluble lignin

1. Vacuum filter the autoclaved hydrolysis solution through one of the previously

weighed filtering crucibles.

2. Transfer an aliquot, approximately 50 mL, into a sample storage bottle. This

sample will be used to determine acid soluble lignin as well as carbohydrates.

(If the hydrolysis liquid must be stored, it should be stored in a cold room for a

maximum of two weeks.)

3. Use distilled water to quantitatively transfer all remaining solids out of the

serum bottle into the filtering crucible. Rinse the solids with a minimum of 50

mL fresh distilled water. (hot distilled water may be used in place of room

temperature water to decrease the filtration time.)

4. Dry the crucible and acid insoluble residue at 105°C until a constant weight is

achieved, usually a minimum of four hours.

5. Remove the sample from the oven and cool in a desiccator. Record the weight

of the crucible and dry residue (W1).

6. Place the crucible and residue in the muffle furnace at 575°C for 24 hours.

7. Weigh the crucible and ash and record the weight (W2).

8. Calculate lignin content using equation 4.6.

Lignin (%) = W1−W2

ovendryweight Equation 4-6


74

C. Analyse the sample for carbohydrates

1. Using the hydrolysis liquid, transfer an approximately 20 mL aliquot of each

liquor to a 50 mL Erlenmeyer flask.

2. Use calcium carbonate to neutralize each sample to pH 5-6. [Add calcium

carbonate slowly after reaching a pH of 4. After reaching pH 5-6, stop calcium

carbonate addition, allow the sample to settle.

3. Use Glucose analyser and DNS method to measure the content of glucose and

reducing sugar.

4. Calculate cellulose and hemicellulose contents using equation 4.7 and 4.8

respectively.

The cellulose content (%, w/w) = (0.9/0.96)× C1 × (V/M) × α × 100 Equation 4-7

Where:

0.9 is the coefficient that results from the molecular weight ratio of the polymer

and the monomer hexose. The saccharification yield was taken as 0.96. C1 is the

glucose concentration (g/L), V the total volume of sugar solution (L), M the dry

weight of the algal biomass sample (g) and α is the dilution factor of the sample.

The hemicellulose content (%, w/w)= (0.88/0.93)× (C2-C1) × (V/M) × α × 100

Equation 4-8

Where:

0.88 is the coefficient that results from the molecular weight ratio of the polymer

and the monomer pentose. 0.93 is the saccharification yield of xylan to xylose, C2

is the determined reducing sugars concentration (g/L) from the DNS method. C1

as the glucose concentration (g/L), V the total volume of sugar solution (L), M the

dry weight of the algal biomass sample (g) and α is the dilution factor of the sample.

4.4.9 Free amino nitrogen

Free amino nitrogen (FAN) is the amount of individual amino acids and small

peptides which can be utilised by microorganisms, especially in yeast, for cell


75

growth and proliferation. FAN concentration was measured by using the ninhydrin

colorimetric method as outlined by the European Brewery Convention (Lie, 1973)

with modifications by (Wang, 1999). The method based on the colour reaction

between ninhydrin and amino acids at pH 6.7, gives an estimate of amino

acids, ammonia and in addition the terminal alpha-amino nitrogen groups of

peptides and proteins.

Ninhydrin colour reagent:

Weigh accurately 49.71g di-sodium hydrogen phosphate dehydrate (HNa2PO4．

2H2O; MW: 177.99); 60.00 g potassium dihydrogen orthophosphate (KH2PO4; MW:

136.09); 5.00 g ninhydrin spectrophotometric grade (C9H6O4; MW: 178.14) and

3.00 g fructose (C6H12O6; MW: 180.16) and dissolve in 750 mL distilled water. The

solution is brought to exactly 1 litre in a volumetric flask and pH adjusted between

6.6 – 6.8 by the addition of acid or alkali. Keep in amber glass bottle at 4°C in a

refrigerator.

Dilution reagent:

Weigh accurately 2.00 g potassium iodate (KIO3; MW: 214) and dissolve in 616 mL

distilled water. The solution is brought to exactly 1 litre in volumetric flask by the

addition of 384 mL absolute ethanol (CH3CH2OH; MW: 46.04). Keep at 4°C in a

refrigerator.

Glycine stock solution:

Weigh accurately 0.005 mg glycine (C2H5NO2 ; MW: 75.07) and dissolve in distilled

water in a 100 mL volumetric flask to give an accurate concentration of 50 mg/L.

Keep the solution at 4°C in a refrigerator.

Glycine standard solution:

Make a series of dilutions for glycine concentration ranging from 0 – 50 mg/L.


76

FAN analysis procedure:

1. Sample preparation:

Whenever necessary, the samples were diluted with distilled water. Usually a

dilution factor from 10 to 50 is sufficient. 1.0 mL of diluted sample was

introduced into 2 test tubes (duplicate trials) and then procedure of FAN

analysis was followed.

2. Blank:

A volume of 1.0 mL of distilled water was introduced into 2 test tubes

(duplicate) and then the procedure of FAN analysis was followed.

3. Standard preparation:

A volume of 1.0 mL of glycine standard solution was introduced into 2 tests

tubes (duplicate) and then the procedure of FAN analysis was followed.

4. Analysis:

0.5 mL of colour reagent was added to all test tubes prepared as 1 (sample),

2 (blank) and 3 (standard). The test tubes were sealed to prevent evaporation

and placed in a boiling water bath for exactly 16 min. The tubes were cooled

to room temperature in a water bath. To each tube, 2.5 mL of dilution reagent

was added and the tubes mixed thoroughly on a vortex mixer. Absorbance

was read for each sample at 570 nm against the reagent blank and the value

was expressed as unit absorbance 570 nm (A570). The colour formed should

be measured within 30 min. The FAN concentration in culture filtrate was

quantified according to the standard curve of FAN (Figure 4.12) which was

linear for glycine concentration ranging from 0 to 50.0 mg/L.

The concentrations of FAN in the samples were calculated using equation 4.9:

FAN (mg/L) = 𝐴570

m× 2 × 𝐷 Equation 4-9

Where:


m: the slope of glycine standard solution


77

2: amount of free amino nitrogen in the glycine standard solution (mg/L)


Figure 4.12 A standard calibration curve for free amino nitrogen (FAN) concentration

4.4.10 Inorganic Phosphorous (IP)

The principle of this method is the reaction of ammonium molybdate in an acidic

environment with vanadate and orthophosphate to form

molybdovanadophosphoric acid. Phosphate will readily react with ammonium

molybdate in the presence of suitable reducing agents to form a blue coloured

complex, the intensity of which is directly proportional to the concentration of

phosphate in the solution.

Solution A:

1% (w/v) ammonium vanadate (NH4VO3; MW: 116.98) in 2 N nitric acid (HNO3;

MW: 63.01): Weigh accurately 1.0 g NH4VO3 and dissolved 100 mL 2 N nitric acid.

y = 0.0373x + 0.0262R² = 0.9932

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

0 10 20 30 40 50 60

Ab

sorb

ance

(5

70

mm

)

FAN concentration (mg/L)


78

Solution B:

10% (w/v) ammonium molybdate ([ΝΗ4]6Μo7Ο24.4Η2Ο; MW: 1235.8): Weigh

accurately 10 g [ΝΗ4]6Μο7Ο24.4Η2Ο and dissolve in 100 mL distilled water.

Phosphorus standard solution:

0.5% (w/v) di-potassium hydrogen phosphate (KH2PO4; MW: 178.18): Weigh

accurately 0.1 g di-potassium hydrogen phosphate and dissolve with 100 mL

deionised water in volumetric flaks. Make a series of dilutions for di-potassium

hydrogen phosphate concentration ranging from 0 to 1 mg/mL. A standard curve

of inorganic phosphorous concentration is shown in Figure 4.13.

Figure 4.13 A standard calibration curve for inorganic phosphorous (IP) concentration

IP analysis procedure:

Phosphorus content determination was carried out using the

Vanadomolybdophosphoric acid colorimetric method using the following

procedures:

1. Place 0.5 mL sample from above procedures into glass test tube

2. Add 0.5 mL of solution A and then followed by 1.0 mL solution B

y = 0.4653x - 0.0347R² = 0.9903

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0 0.2 0.4 0.6 0.8 1 1.2

Ab

sorb

ance

(4

70

mm

)

Phosphorous concentration (mg/mL)


79

3. After allowing exactly 20 minutes at room temperature, the colour was fully

developed; the absorbency was measured with a spectrophotometer at

470 nm against distilled water as a blank.

4. Phosphorus concentration was calculated using equation 4,10 based on the

standard curve obtained using di-potassium hydrogen phosphate as a

known phosphorus materials.

The inorganic phosphorous (mg/mL) = A470×D

m Equation 4-10

Where:


m: the slope of phosphorous standard solution


4.4.11 pH

The pH of citric buffer preparation and solution after the hydrolysis process were

directly measured using a pH meter (HANNA Instruments HI 221, UK).

4.4.12 Enzyme activity

4.4.12.1 Cellulase activity

Filter paper cellulase activity was measured using International Union of Pure and

Applied Chemistry (IUPAC) guidelines. The procedures were designed to measure

cellulase activity in terms of “filter paper units” (FPU) per millilitre (mL) of original

(undiluted) enzyme solution. The value of 2.0 mg of reducing sugar as glucose from

50 mg of Whatman No.1 filter paper (4% conversion) in 60 minutes has been used

as the intercept for calculating filter paper cellulase units (FPU) by IUPAC. (Ghose,

1987) mentioned that the FPU is defined only at this extent of conversion (4%) due

to a nonlinear function between reducing sugar yield and the quantity of enzyme

in the assay mixture.


80

Analysis procedures:

1. Preparation of substrate:

The substrate is a 50.0 mg Whatman No. 1 filter paper strip (1.0 x 6.0 cm). A

rolled filter paper strip was placed into each glass test tube. 1.0 mL of 0.05 M

sodium citrate buffer, pH 4.8 was added to every test tube. Filter paper should

be submerged and saturated inside the buffer. The tubes were incubated at

50 °C in a water bath for about 10 min to maintain a constant temperature in

the substrate solution.

2. Preparation of glucose standard solution:

A working stock solution of anhydrous glucose (C6H12O6; MW: 180.16; Fisher

Scientific) (10.0 mg/mL) was made up. A series of dilutions were made up for

glucose concentration ranging from 0 to 10.0 mg/mL. Glucose standard tubes

should be prepared by adding 0.5 mL of each glucose dilution to 1.0 mL

sodium citrate buffer. Reagent blank, enzyme control, substrate control and

glucose standards were incubated along with the enzyme assay tubes at 50°C

and the procedure was completed by adding 3.0 mL of DNS reagents. The

tubes were mixed on a vortex mixer before analysing in the

spectrophotometer.

3. Colour development:

All tubes were boiled for exactly 15 min in boiling water. After boiling, the

tubes were cooled in a cold water bath. Tubes were kept until all the pulps

were cooled down to room temperature. 0.2 mL of colour-developed reaction

mixture was pipetted and 2.5 mL distilled water was added in a

spectrophotometer cuvette.

The absorbance for each sample was measured at 540 nm against the reagent

blank using the spectrophotometer. Using the glucose standard curve (Figure

4.14), the amount of glucose released for each of the samples was determined

after subtraction of values obtained for the enzyme control and substrate control.

The concentration of enzyme, which would have released exactly 2.0 mg of

glucose, was estimated by means of a plot of glucose liberated against the enzyme

concentration (enzyme dilution).


81

Enzyme concentrations for samples = 1/dilution

(e.g. 1/2 and 1/5)

The term “enzyme concentration” is defined as the proportion of the original

enzyme solution present in each enzyme dilution (i.e., the number of mL of the

original solution present in each mL of the dilution). This is calculated using

equation 4.11:

2𝑚𝑔𝑔𝑙𝑢𝑐𝑜𝑠𝑒 0.1806𝑚𝑔 ∙ (𝑔𝑔𝑙𝑢𝑐𝑜𝑠𝑒 ∙ 𝜇𝑚𝑜𝑙𝑒)−1⁄

0.5𝑚𝐿𝑒𝑛𝑧𝑦𝑚𝑒 × 60𝑚𝑖𝑛

= 0.37𝜇𝑚𝑜𝑙𝑒 ∙ 𝑚𝑖𝑛−1 ∙ 𝑚𝐿−1

Equation 4-11

Where, 0.37: The numerator in the equation is derived from the factor for

converting the 2.0 mg of "glucose equivalent" generated in the assay to mmoles

of glucose (2.0/0.18016). The denominator is the volume of the enzyme being

tested that is used in the assay (0.5 mL) and from the incubation time (60 minutes)

required for generation of the reducing equivalents.

Figure 4.14 A standard calibration curve for glucose concentration

y = 0.0965x + 0.0178R² = 0.986

0

0.2

0.4

0.6

0.8

1

1.2

0 2 4 6 8 10 12

Ab

sorb

ance

(5

40

nm

)

Glucose concentration (mg/mL)


82

Determination of the concentration of enzyme that would have released exactly

2.0 mg of glucose was carried out by plotting the concentration of glucose

liberated against enzyme concentration as shown in Figure 4.15. Cellulase activity

is then determined using equation 4.12.

Figure 4.15 Calculation of FPU from a plot of enzyme dilution vs glucose concentration

Cellulase(𝐹𝑃𝑈 𝑚𝐿⁄ ) =0.37𝜇𝑚𝑜𝑙𝑒∙𝑚𝑖𝑛−1∙𝑚𝐿−1

𝑒𝑛𝑧𝑦𝑚𝑒𝑐𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛𝑡𝑜𝑟𝑒𝑙𝑎𝑠𝑒2.0𝑚𝑔𝑔𝑙𝑢𝑐𝑜𝑠𝑒 Equation 4-12

4.4.12.2 Xylanase activity

Determination of xylanase activity was conducted according to the method

developed by Bailey et al. (1992). The assay is based on the release of reducing

sugars from 1% (w/v) xylan (Sigma-Aldrich) solution prepared in 0.05 M citrate

buffer pH 5.4 by 3,5-dinitrosalycylic acid method (DNS method, Miller, 1959) at

50°C. The xylanase activity was expressed throughout this work in units of U/g

material measured on dry basis. One unit of xylanase activity was defined as the

amount of enzyme producing 1 μmole xylose equivalents per minute under assay

conditions. The procedures of xylanase determination were conducted as follows:


83

1% (w/v) substrate suspension of xylan in 0.05 M citrate buffer, pH 5.4 was

prepared. The suspension was heated at temperature 60 – 70°C until dissolution.

The solution should not be boiled. 10.0 mL of the substrate solution was incubated

at 50°C, for 10 min to maintain a constant temperature in the substrate solution.

5.0 mL of appropriate diluted enzyme supernatant was added. At specific times (0,

5 min), 0.5 mL of reaction mixture was collected for the measurement of xylose

and therefore the degree of substrate hydrolysis. The enzyme reaction in the

sample was stopped immediately by adding 1.0 mL of DNS reagent. The solutions

were mixed well and the tubes were placed in a boiling water bath for 10 – 15 min.

These were then cooled under running tap water. 9.0 mL of deionised water was

added to each of the test tubes and the tubes were mixed on a vortex mixer.

The absorbance for each sample was measured at 540 nm against the reagent

blank using a spectrophotometer. A blank solution was also prepared using 1.0 mL

distilled water, 0.5 mL of diluted enzymatic extract solution, and 1.0 mL DNS by

following procedures explained above. Using the xylose (C5H10O5; MW: 150.13;

Sigma-Aldrich) standard curve (100 – 1,000 μg/mL) the amount of xylose released

for each samples was determined.

Xylose standard curve:

A working stock solution of D(+)-xylose (C5H10O5; MW: 150.13; Sigma-Aldrich) at

1,000.0 μg/mL was made up. A series of dilutions are made from the working stock

within the range 200 to 1,000 μg/mL. In a separate test tube, 0.5 mL of deionised

water was used as a blank. Further steps were carried out following the procedure

explained above. The xylose concentration was quantified according to standard

curve of xylose, which was linear for xylose concentration ranging from 200 to

1,000 μg/mL (Figure 4.16).


84

Figure 4.16 A standard curve for measuring xylose concentration

Enzyme activity was calculated from the slope of xylose standard curve and the

slope of xylose release from the enzyme reaction test (equation 4.13). Data

obtained from enzyme reaction trials provided absorbance value (540 nm) against

reaction time (5 min) and the slope was obtained.

Xylanase(𝑈 𝑚𝐿⁄ ) =𝑆𝑙𝑜𝑝𝑒𝐼𝐼

𝑆𝑙𝑜𝑝𝑒𝐼×

1𝜇𝑚𝑜𝑙𝑒

150.03𝜇𝑔×

𝑡𝑜𝑡𝑎𝑙𝑣𝑜𝑙𝑢𝑚𝑒𝑜𝑓𝑟𝑒𝑎𝑐𝑡𝑖𝑜𝑛𝑚𝑖𝑥𝑡𝑢𝑟𝑒(𝑚𝐿)

𝑒𝑛𝑧𝑦𝑚𝑒𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛𝑣𝑜𝑙𝑢𝑚𝑒𝑖𝑛𝑎𝑠𝑠𝑎𝑦(𝑚𝐿)

Equation 4-13

Where:

Slope I =𝐴540

𝑥𝑦𝑙𝑜𝑠𝑒𝑐𝑜𝑛𝑐𝑒𝑛𝑡𝑟𝑎𝑡𝑖𝑜𝑛(𝜇𝑔

𝑚𝐿⁄ ) (From xylose standard curve, Figure 4.16)

Slope II = 𝐴540

5(𝑚𝑖𝑛) (From enzyme reaction test)

Total volume reaction = 15.0 mL

Enzyme volume = 5.0 mL

4.4.12.3 Beta-glucosidase activity

β-glucosidase hydrolyzes carbohydrates by acting on terminal, non-reducing β (1-

4)-linked D-glucose residues with the release of D-glucose. β-glucosidases are

required by organisms for the consumption of cellulose. In this assay, β-

y = 0.0006x + 0.0749R² = 0.9644

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0 200 400 600 800 1000 1200

Ab

sorb

ance

(5

40

nm

)

Xylose concentration (µg/mL)


85

glucosidase activity is determined by a reaction in which β-glucosidase hydrolyzes

p-nitrophenyl- β-D-glucopyranoside resulting in the formation of p-nitrophenol, a

colorimetric (405 nm) product, proportional to the β-glucosidase activity present.

Solution A:

20 mM PNPG solution: Weigh 603mg p-nitrophenyl-β-D-glucopyranoside (PNPG)

and dissolved in 100 mL distilled water. (Stable for two weeks if stored at 0-5°C)

Solution B:

0.2M Na2CO3 solution: Weigh 21.2 g Na2CO3 and dissolved in 1,000 mL distilled

water.

Analysis procedures:

1. Prepare the following reaction mixture in two test tubes and equilibrate at

37°C for about 5 min. 1.0 mL of 0.1M of acetate buffer (pH 5.0) and 0.5 mL

of PNPG solution (solution A) for sample test. 1.0 mL of 0.1M of acetate

buffer (pH 5.0) and 0.5 mL of distilled water for blank.

2. Add 0.5 mL of the enzyme solution into both test tubes and mix.

3. After exactly 15 min at 37°C, add 2.0 mL of Na2CO3 solution (solution B) into

both test tubes to stop the reaction and measure the optical density at 400

nm against water using spectrometer.

Activity can be obtained by using equation 4-14:

β − glucosidase(𝑈 𝑚𝐿) =𝐴400×𝑡𝑜𝑡𝑎𝑙𝑣𝑜𝑙𝑢𝑚𝑒×𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛𝑓𝑎𝑐𝑡𝑜𝑟

18.1×𝑡×𝑟𝑒𝑎𝑐𝑡𝑖𝑜𝑛𝑡𝑖𝑚𝑒×𝑠𝑎𝑚𝑝𝑙𝑒𝑣𝑜𝑙𝑢𝑚𝑒⁄ Equation 4-14

Where:

Total volume: 4.0 mL

Sample volume: 0.5 mL

18.1: Millimolar extinction coefficient of p-nitrophenol under the assay condition

(cm2/micromole)


86

Reaction time: 15 min

4.4.13 Ethanol

Ethanol concentration was measured directly using an Analox GL6 analyser

(Analox, England).

Chapter 5 Production of a generic feedstock: solid-state fermentation

87

CHAPTER 5

Production of a generic feedstock:

solid-state fermentation

Introduction In the consolidated bioprocess, the solid material plays an important role as

physical support and nutrient supply. Consequently, the characteristics of the raw

material (chemical composition and physical properties such as bulk density,

particle density, porosity and water evaporation) will influence the microorganism

growth. A good knowledge of material characteristics could greatly help the

selection of substrates, as well as design and optimisation of the solid state

fermentation.

The ability of Trichoderma spp. to produce secondary metabolites, especially

cellulase and xylanase, is well known. However, the evaluation of performance in

this project is the production of nutrients (sugars, nitrogen and other minerals)

through the consolidated bioprocess rather than enzyme secretion from

fermentation. Trichoderma longibrachiatum has not been previously studied for

this consolidated process. First, a technique for studying a sequential bioprocess

using lignocellulose had to be developed. This was then used to collect data and

optimise conditions for further bioreactor application.

Several different experimental conditions reported for Trichoderma species in SSF

influence enzyme yield and deconstruction of lignocellulose, including particle size

of substrate, C/N ratio of substrate, and moisture content of substrate. Other

factors that affect Fungi growth during SSF include temperature, aeration and

incubation time. The study reported in this chapter was therefore aimed at

identifying suitable conditions for growth and nutrients production with a focus


88

on the sugar and FAN. All results obtained were used as fundamental knowledge

for growing T. longibrachiatum in subsequent experiments.

The characteristics of the substrates

5.2.1 Chemical composition

The chemical composition of sugarcane bagasse and soybean hull is presented in

Table 5.1. Half of the chemical composition of sugarcane bagasse and soybean hull

is cellulose and hemicelluloses. Notably lignin content is quite different between

sugarcane bagasse (17.8) and soybean hull (8.4), causing the fungal growth to a

certain extent.

Table 5.1 Composition of sugarcane bagasse and soybean hull on dry basis

Type Cellulose Hemicellulose Lignin Protein* Others

Sugarcane

bagasse

30.9% 31.9% 17.8% 2.5% 16.9%

Soybean

hull

31.1% 21.9% 8.4% 11.9% 26.7%

*Protein content of sugarcane bagasse and soybean were obtained from references (Jenkins et al., 1998; Ontario minister of agriculture, food and rural affairs, 2011)

An important factor in solid-state fermentation is the ratio between carbon and

nitrogen (C/N). The ratio of C/N is most vital for a specific process to obtain desired

products. Sugarcane bagasse has higher cellulosic composition which is ideal for

good growth of fungal cultures and enzyme production. However, its low protein

content (2.5%) and high lignin concentration limit its efficiency of bioconversion

to produce value-added products (El-Sayed et al., 1994). Brijwani et al., (2010)

showed that the protein content of soybean hull (11.9%) is not as high as wheat

bran (16.29%). However, Soybean hull is still a good source of nitrogen compared

with sugarcane bagasse. Mixtures of sugarcane bagasse and soybean hull can,


89

potentially, improve C/N to present ideal conditions for fungal growth and enzyme

production and this is explored below.

5.2.2 Bed Porosity

As has been defined, SSF involves a discrete solid phase in which microorganisms

grow on the surface of moist particles as well as inside and between them. The

space between particles is occupied by a continuous gas phase. And the size, shape,

and porosity of substrates could affect the gas phase in the SSF. Availability of

spaces between particles ensures the accessibility of oxygen for enzyme

production in aerobic fungal growth (Brijwani and Vadlani, 2011).

In order to assess the likely importance of particle size and type on bed porosity,

measurements were made of bulk density and particle density and these were

then used to calculate bed porosity for a range of different particle sizes of

sugarcane bagasse as well as for soy bean hull particles. The results, presented in

Table 5.2, show that there is a substantial difference in the porosity, estimated at

dry basis, for different particle sizes of sugarcane bagasse compared with soybean

hull (<2 mm). For sugarcane bagasse, with the increase of particle size, the porosity

raises gradually from 84.2% to 92.9%. The higher value of porosity means the more

open space available between substrate particles. Notably, the maximum

difference of bed porosity between soybean hull (<2 mm) and sugarcane bagasse

(2-1.4 mm) was close to 18%. These results match those observed in earlier studies

that porosity varies depending on several factors such as fibre bonds, moisture,

particle size and aggregation.


90

Table 5.2 Bed porosity of Sugarcane bagasse and Soybean hull particles

Type Bulk Density (g/mL)

Particle Density (g/mL)

Porosity (%)

Sugarcane bagasse (2-1.4 mm)

0.05 0.704 92.9

Sugarcane bagasse (1.4mm-0.85 mm)

0.049 0.6 91.8


0.058 0.401 85.5


0.059 0.375 84.2

Soybean hull (< 2 mm)

0.435 1.787 75.6

Figure 5.1 shows photographs of sugarcane bagasse under a microscope at 50X

magnification. For the biggest size of sugarcane bagasse (2-1.4 mm), various

particle shapes are shown in Figure 5.1a. Because of the irregularly size particles,

particles could not pack the inter-particle void space and block the open pore for

air or water accessibility. Therefore, the void spaces between particles are larger

than for other particle sizes. As for the smallest one (0.5-0.21 mm), the quality and

shape of particles is more homogeneous (Figure 5-1d), causing the amount of

open space to reduce. The findings of the current study are consistent with those

of (Manickam and Suresh, 2011) who showed that the porosity is decreasing with

decreasing particle size for corn pitch.


91

Figure 5.1 Sugarcane bagasse at different particle sizes under a USB microscope, 2X magnification (a) 2-1.4 mm (b) 1.4-0.85 mm (c) 0.85-0.5 mm (d) 0.5-0.21 mm

5.2.3 Water evaporation

The water evaporation rate of substrates is related to the efficiency of Solid-state

fermentation, especially for the issue of heat and mass transfer during

bioprocessing. One of the major barriers is the difficulty in controlling the water

content and temperature of the bed in large-scale bioreactors.

For investigating evaporation characteristics of sugarcane bagasse and soybean

hull, it could be useful to use dimensionless moisture ratio (MR) to represent

evaporation behaviour.

MR=(M-Me)

(Mo-Me) Equation 5-1

Where M is the moisture content of the product, Mo is the initial moisture content

of the product and Me is the equilibrium moisture content.


92

The values of Me are relatively small compared to M and Mo for long drying times

and accordingly one can write:

MR=M

M0 Equation 5-2

The non-fermented sugarcane bagasse and soybean hull were dried at 30°C in an

oven, adopting thin-layer thickness of about 10 mm. The initial moisture content

of samples was about 0.75g water per g of dry matter. All samples were put in

petri dishes without lids. Using the moisture ratio to generalize the change of

moisture content is the most common method in drying process. As shown in

Figure 5.2, the moisture ratio versus drying time for sugarcane bagasse and

soybean hull at 30°C. According to the results obtained, the effect of various

particle size of sugarcane bagasse does not cause significant difference of water

evaporation.

Figure 5.2 The drying curve of sugarcane bagasse and soybean hull

The limitation of mass transport by diffusion plays an important role in solid state

fermentation especially when the substrate has a porous structure. Mass transfer

inside the substrate particle is limited to diffusion and because of consumption of

nutrients by the microorganisms, concentration gradients will go up within the

0

0.2

0.4

0.6

0.8

1

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

Mo

istu

re r

atio

(M

R)

Time (hr)

bagasse (2-1.4mm)

bagasse (1.4-0.85mm)

bagasse (0.85-0.5mm)

soybean hull


93

substrate. Therefore, understanding this characteristic of the substrate is one of

the crucial factors for the design of solid state fermentation. It has been accepted

that the drying characteristics of biological products in the falling rate period can

be described by using Fick's diffusion equation. Crank (1975) used various regularly

shaped bodies such as rectangular, cylindrical and spherical products, and the

form of Equation 5-3 to apply on particles with slab geometry, as is the case of the

sugarcane bagasse and soybean hull, by assuming uniform initial moisture

distribution (Crank, 1975; M.A. Mazutti et al., 2010).

MR =8

𝜋2∑

1

(2𝑛+1)2∞(𝜋=0) 𝑒𝑥𝑝 (−

(2𝑛+1)2𝜋2𝐷𝑒𝑓𝑓𝑡

4𝐿02 ) Equation 5-3

where Deff is the effective diffusivity (m2 s−1), L0 is the half thickness of slab (m). For

long drying periods, Equation 5-3 can be simplified to retain only the first term of

the series and re-writing to a logarithmic form as follows:

ln(MR) = ln(8

π2) −

π2Defft

4L02 Equation 5-4

Diffusivities are determined by plotting drying data in terms of ln(MR) versus time

in Equation 5-4, providing a straight line with the slope given by:

slope = −π2Deff

4L02 Equation 5-5

Table 5.3 Values of effective diffusivity obtained for different particle sizes of sugarcane bagasse and soybean hull

Sample Effective Diffusivity (m2s-1)

2-1.4 mm of sugarcane bagasse 6.36 x 10-11

1.4-0.85 mm of sugarcane bagasse 6.82 x 10-11

0.85-0.5 mm of sugarcane bagasse 6.59 x 10-11

Soybean hull (<2mm) 5.21 x 10-11


94

The values of effective diffusivity (Deff) of sugarcane bagasse with various particle

size and soybean hull are presented in Table 5-3. The effective diffusivities for

sugarcane bagasse ranged from 6.82 x 10-11 to 6.36 x 10-11 m2s-1, whereas for

soybean hull the value was 5.21 x 10-11. The effective diffusivities of sugarcane

bagasse were, on average, 1.26 times higher than those found for soybean hull. A

possible explanation for this might be that the diffusion rate is proportional to the

porosity of the solids (Table 5.3), and as the drying process takes place the

structure hinders diffusion, diminishing the values of Deff.


95

Effect of washing procedure on sugarcane bagasse

Sucrose is the prime constituent of sugarcane juice. Also, a variety of other

carbohydrates is found in mixed juice. (Walford, 1996) reported that the most

common consist of the monosaccharides glucose and fructose (3-6%), and the

dissacharides, sucrose (81-87%). Oligosaccharides and polysaccharides (0.2-0.8%)

may be present depending on the age of the cane when harvested and

deterioration during delays. In sugar processing, the first step is to shred

sugarcane to prepared cane. The cane juice is then extracted from the prepared

cane and collected through a series of solid-liquid separation processes. The

residue left after crushing is called ‘bagasse’. Sugarcane bagasse is the fibrous

material still containing a significant amount of sugar. In sugar processing plant,

there are five more crushing stages to extract the remaining sugar from bagasse

and the remained residue in the last extraction stage is called ‘final bagasse’

(Tewari and Malik, 2007). Since the bagasse in the experiments reported in this

thesis was collected from a traditional market, the sugarcane was extracted

through a simple sugarcane extruder. It was necessary, therefore, to explore the

influence of the remaining sugar in the bagasse on the solid state fermentation.

Several researches showed that microorganisms are able to use sucrose from

sugarcane bagasse during solid state fermentation (Kumar et al., 2003; Marcio A.

Mazutti et al., 2010). This study was carried out to investigate the influence of

washing the sugarcane bagasse on the sugar and FAN yield obtained from

sequential solid state fermentation (SSF) and hydrolysis.

The solids (sugarcane bagasse) were either used as non-washed or washed with

distilled water before inoculation of solid state fermentation. The amount of

distilled water used in the washing process was about 1 L per 25 g bagasse (dry

basis). The wash liquid was stored at 4°C for further analysis within 3 days.


96

After being autoclaved at 121°C for 20 min, 4 g of non-washed and washed

sugarcane bagasse were then distributed into each of two 9 cm petri dishes and

incubated at 30°C for 120 h. The default culture condition was 65 % moisture

content using sterile mineral salt water, 10% (w/w) of yeast extract supplemented,

106 spores per gram substrate, and 7-day spores if it was not indicated specially.

At the end of solid state fermentation the contents of all Petri dishes were

suspended in pH 4.8 citric buffer. The suspension was stored in sealed Duran

bottles to elevate enzyme activities in the fermented substrate for hydrolysing the

remaining sugarcane bagasse components. All experiments were carried out with

agitation using a shaking incubator at 50°C, 160 rpm for 48 h.

From Figure 5.3a, it was noticed that there was nearly no growth of T.

longibrachiatum on washed sugarcane bagasse. Careful visual observation

showed that there were some mycelia formed on the substrate surface, which

means that T. longibrachiatum did grow on it, but with a slow rate. However, when

non-washed sugarcane bagasse was used for substrate (Figure 5.3b), the growth

was slightly improved.

Figure 5.3 SSF using Trichoderma longibrachiatum on (a) washed and (b) non-washed sugarcane bagasse after 5 days

The composition analysis of the resulting wash waters showed that reducing

sugars, sucrose and FAN were 0.04, 0.14 and 0.01 g per g of bagasse, respectively.

Of the nutrient compounds monitored, sucrose is retained in the highest


97

concentration. This means that a large fraction of fermentable sugars remained in

the sugarcane bagasse that could be fed to the solid state fermentation.

It is clear that non-washed sugarcane bagasse led to a higher sugar and FAN yield

after sequential bioprocessing (Figure 5.4). Data for non-washed process are

almost twice as high as those for washed process. A possible explanation for this

result might be that abundant fermentable sugars were washed from sugarcane

bagasse before inoculation, resulting in insufficient nutrients and poor microbial

growth. These findings may help us to understand the effect of remaining sugars

in the bagasse on our sequential bioprocess. A reasonable approach for further

experiments is to choose non-washed bagasse to ensure enough sugars and

nitrogen for fungal growth.

Figure 5.4 Effect of washing process on nutrients production via solid state fermentation and subsequent hydrolysis

Effect of particle size on sugarcane bagasse Particle size of the substrate is related to substrate characteristics and system

capacity to interchange with microbial growth and heat and mass transfer during

SSF. Smaller particle size could provide larger surface area for microbial growth

and it is also beneficial for heat transfer and exchange of oxygen and carbon

0

50

100

150

200

250

300

0

1

2

3

4

5

6

7

washed non-washed

FAN

(m

g/L)

Red

uci

ng

suga

r (g

/L)

Reducing sugar

FAN


98

dioxide between the air and solid matrix. However, too small particles may lead to

substrate agglomeration, which may interfere with microorganism respiration and

then result in poor cell growth (Pandey et al., 2000; Xin and Geng, 2010).

Three different particle sizes of sugarcane bagasse were carried out following the

method described in section 5.3. Figure 5.5 shows the characteristic development

of T. longibrachiatum under different particle sizes of substrates. The spores are

spread on the surface and inside the solid matrix, and hyphae forms a microscopic

network (mycelium) inside the substrate. Varying the growth condition, similar

patterns of morphological development are observed in Figure 5.5. However, the

smaller particles may result in agglomeration, causing the void space to decrease.

Therefore, the development of fungal growth would be a little different from the

others. As shown in the figure, the aerial hyphae intermeshed on the surface of

the substrate densely.

Figure 5.5 Images of fungi growth on different particle sizes of sugarcane bagasse with soybean hull (2X magnification, USB Microscope)


99

Figure 5.6 Effect of particle size on nutrients production via solid state fermentation and subsequent hydrolysis

Figure 5.6 shows sugar and FAN production from sugarcane bagasse using T.

longibrachiatum under the sequential bioprocessing conditions described. When

sequential bioprocesses were carried out with different particle sizes of bagasse,

particle size of 1.4-0.85 mm supported maximal reducing sugar and FAN (9.4 g/L

and 670.7 mg/L). Generally, the particle size not only significantly affects the water

holding capacity of the substrate, but also influences the diffusion of nutrients and

the exogenous metabolic products to and from the microorganisms. According to

the result reported in section 5.2.2, the porosity of over 1.4 mm particle size (92.9)

is quite similar with the one of 1.4-0.85 mm (91.8). However, larger particle sizes

could present less surface area than smaller one. And it could affect the fungal

growth or enzyme production. In this case, sugarcane bagasse with 1.4-0.85 mm

particle size possibly provided sufficient surface area and aeration to T.

longibrachiatum for growth and enzyme production resulting in increased sugar

production.

0

100

200

300

400

500

600

700

800

0

2

4

6

8

10

12

2-1.4mm 1.4-0.85mm 0.85-0.5mm

FAN

(m

g/L)

Red

uci

ng

suga

r (g

/L)

Reducing sugar

FAN


100

Influence of nitrogen supplement on SSF For fungi of the genus Trichoderma, better results of enzyme production in SSF

have been obtained with organic nitrogen sources, such as peptone, yeast extract

or corn-steep liquid, than with inorganic compounds, such as ammonium sulfate

or ammonium nitrate, as the sole nitrogen (Sun et al., 2010).

In the current project, the sugarcane bagasse contains 62.8% of total

carbohydrates and 0.4% of total nitrogen. The abundant amount of carbohydrates

in bagasse could be desirable for filamentous fungi utilisation. The smaller amount

of total nitrogen, 0.4%, on the other hand could not provide a sufficient source of

nitrogen to promote the fungal growth and facilitate enzyme production. A high

C/N ratio could mean that the nitrogen will be consumed before carbon is utilised.

In contrast, a low C/N ratio may provide excess nitrogen which tends to become

toxic to some microorganisms (Mital, 1997). Therefore, it is necessary to know

what level of C/N ratio could benefit nutrients production through T.

longibrachiatum. The effect of different amounts of nitrogen source on sugar and

FAN production was tested by yeast extract (Table 5.4). All of the experiments

were carried out in an incubator at 30°C for 120h for SSF and then transferred to

50°C for 48h for subsequent hydrolysis.

Carbon to nitrogen ratio (C/N) is a ratio of the mass of carbon to the mass of

nitrogen in a substance. In section 5.5, the carbon content and nitrogen content

in the sugarcane bagasse and yeast extract were based on referred data (Holwerda

et al., 2012; Kruesi et al., 2013).


101

Table 5.4 C/N ratio of mixed-substrates culture medium

Nitrogen added (%, w/w) C/N ratio (g g-1)a

0 107.2

1.5 80.9

4.5 54.3

7.5 40.8

10.5 32.7

15 25.2

a Ratio between carbon in sugarcane bagasse and supplemented nitrogen

It was observed that different amount of yeast extract supplemented has a direct

effect on the growth of T. longibrachiatum on sugarcane bagasse (Figure 5.7).

Fungi did not grow well in the fermentation with nitrogen added below 7.5% (w/w).

It is known that the C/N ratio is one of the most important factors to balance

biomass and products production. The excess or lack of nitrogen content in the

substrate may inhibit fungal growth and is presumably the reason to hinder

enzyme production (Mantovani et al., 2007). In the solid state fermentative

process, even minor variations in the C/N ratios may result in quite distinct

responses from the biological system, since the local concentrations are greatly

superior to those of the submerged fermentation (Bertolin et al., 2003). Figure 5.7

shows that a green surface area appeared in plates where the yeast extract

supplemented is above 7.5% (w/w). In addition, droplets of condensed water were

observed on the internal surface of lids where prolific fungal growth was observed.


102

Figure 5.7 SSF using Trichoderma longibrachiatum on different amount of nitrogen supplement on sugarcane bagasse after 5 days

Figure 5.8 shows that reduction in the dry weight of the substrate is directly

related to the consumption of the nutrients by the extent of fungal growth. Dry

weight loss is increasing in fermentations with nitrogen added contents between

0% and 15% (w/w). The highest dry weight loss (25% of initial dry weight) was

observed in the fermentation carried out using 15% of nitrogen supplement. The

dry weight loss seems be associated with the fungal growth from visual

observation (see Figure 5.7). However, it is worth mentioning that separation of

fungal mycelium from the solid particles of the substrate was practically

impossible, and therefore quantitative analysis of biomass from the remaining dry

fermented substance is very difficult.


103

Figure 5.8 Dry weight loss of 5 days solid state fermentation with different amount of nitrogen supplement

The effect of different amounts of nitrogen added on sugar and FAN production is

presented in Figures 5.9 to 5.11. Enzyme production and substrate utilisation are

associated with fungal growth. Hydrolytic enzymes such as cellulase, xylanase,

beta-glucosidase and protease, which are secreted by the mycelium, diffuse to the

solid matrix and degrade macromolecules into smaller units for taking up

surrounding nutrients. In this study, though, cellulase, xylanase, beta-glucosidase

and protease production were not examined directly, but reducing sugar and FAN,

the products of the hydrolysis reactions, were measured. The results shown in

figures are the average values of duplicate samples.

The reducing sugar released after 120 h fermentation as a consequence of the

hydrolysis of substrate (cellulose and hemicellulose) during solid state

fermentation, provides available carbon source for fungi consumption. Figure 5.9

shows that no yeast extract supplement had the highest reducing sugar yield (35.8

mg/g substrate) after solid-state fermentation. However, substrates with high

sugar content may inhibit the microbial growth during SSF, resulting in low system

productivity.

0

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30

0 1.5 4.5 7.5 10.5 15

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mat

ter

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t lo

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(% o

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Nitrogen supplemented (%, w/w)


104

Figure 5.9 Effect of different amounts of nitrogen supplement on sugar production via solid state fermentation (SSF) or sequential bioprocessing (SSF + hydrolysis). Error bars indicate ranges between duplicate samples.

Subsequent hydrolysis of whole fermented substrates could provide partially

deconstructed materials and abundant in-situ enzyme complex, which further

reduce operating cost and nourish the hydrolysate with sugar, FAN and trace

elements. Figure 5.9 shows that 10.5% of yeast extract supplement had the

highest reducing sugar yield (120.9 mg/g substrate) after sequential bioprocessing

(SSF + hydrolysis), followed by the 15% nitrogen supplement (89.6 mg/g substrate).

The lowest sugar production was SSF with 4.5% of yeast extract supplement.

There is little apparent difference between the first three trials (0% to 4.5%) about

the effect of nitrogen addition on the sugar production of sequential bioprocessing

from Figure 5.9. To verify this observation, the analysis of variance (ANOVA) was

used to test the basic difference between the groups in this experiment. The

results of reducing sugar released during the hydrolysis of fermented solids

presented four significantly (p<0.05) different groups (a to d) as a function of

nitrogen supplemented (Figure 5.10). The maximum sugar yield was obtained on

the medium with 10.5% of yeast extract added (C/N = 32.7), 85.7 mg/g substrate.

It is interesting to note that sugar production of hydrolysis after SSF with a range

of nitrogen supplemented from 0 to 4.5% (C/N from 107.2 to 54.3) was constant,

0

20

40

60

80

100

120

140

0 1.5 4.5 7.5 10.5 15

Re

du

cin

g su

gar

(mg/

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bst

rate

)

Nitrogen supplement (%, w/w)

SSF

SSF + hydrolysis


105

with no significant difference. Clearly, the sugars production and fungal growth

were strongly related to a low C/N ratio that resulted in better productivity and

biomass. The high ratio between carbon and nitrogen content in the medium led

to a low consumption of substrates and a decrease in the sugars production.

Figure 5.10 Average saccharification yield in subsequent hydrolysis (SSF + hydrolysis) with different proportion of nitrogen added. Letters a b c and d represent significantly different (p<0.05) groups of data

The production of FAN after 5 days of fermentation was also investigated (Figure

5.11). The positive effect of increasing nitrogen supplement was observed,

growing from 0.6 mg/g substrate obtained for no nitrogen supplement condition

to 7.5mg/g substrate (15% added yeast extract). Protease activity is associated

with FAN hydrolysis from protein, and It was found that the profile of protease

activity was very similar to that of fungal growth (Wang et al., 2005). From Figure

5.7, it can be clearly seen that FAN production could be related to visual

observation of solid state fermentation.

During the subsequent hydrolysis period, not only the enzymatic hydrolysis

reaction happened, but also the autolysis of the fungal cells occurred under an

oxygen limited condition. Many enzymes such as protease, phosphatase,

0

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90

0 2 4 6 8 10 12 14 16

Suga

r yi

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)

Nitrogen supplement (%, w/w)

c

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a

b


106

glucanase and chitinase are degrading fungal cell walls, cytoplasmic materials and

remaining protein of fermented solids. This process could release intracellular

nutrients (amino acid, peptide, phosphorous and vitamins etc.) and break down

protein remaining in fermented lignocellulose, to the hydrolysate. FAN production

after SSF and hydrolysis is presented in Figure 5.11. In SSF with nitrogen

supplemented from 7.5% to 15% (C/N ratios from 40.8 to 25.2), total FAN

production after sequential bioprocessing (SSF + hydrolysis) were higher than the

others. However, FAN yields in the subsequent hydrolysis in all trials were similar

from 1.31 mg/g to 6.83 mg/g, with no significant (p< 0.05) difference. Results from

this study suggest that the production of sugars and FAN are highly dependent on

C/N ratios.

Figure 5.11 Effect of different amounts of nitrogen supplement on FAN production via solid state fermentation (SSF) or solid state fermentation plus sequential bioprocessing (SSF + hydrolysis)

Effect of mixed substrates on SSF The composition of the cultivation medium is a key parameter in optimising SSF

processes since nutritional factors such as the carbon source, and the levels of

nitrogen and trace minerals, can influence the metabolites enzymes and spore

production. Despite the potential to produce value-added products through solid

state fermentation, supplementing with organic nitrogen sources can be costly. It

0

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14

0 1.5 4.5 7.5 10.5 15

FAN

(m

g/g

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SSF

SSF + hydrolysis


107

is not an economical process for chemicals production. In this work, soybean hull

was used as alternative nitrogen supplement for solid state fermentation. Soybean

hulls are by-products from soybean processing, being considered as waste due to

anti-nutritional protein as the low-quality animal feed supplements (Zhang and Hu,

2012). However, with its low content of lignin and sufficient nitrogen content for

microorganisms, soybean hull can be a good choice for medium formulation.

As shown in Table 5.5, sugarcane bagasse (SB) and soybean hull (SH) were used in

varied SB:SH ratios (1:0, 8:2, 6:4, 5:5, 2:8 0:1) for solid state fermentation using T.

longibrachiatum. Carbon to nitrogen ratio is a ratio of the mass of carbon to the

mass of nitrogen in a substance. The carbon content and nitrogen content in the

substrates (sugarcane bagasse and soybean hull) were based on referred data

(Kruesi et al., 2013; Ontario minister of agriculture, 2011).

Table 5.5 Composition of mixed-substrates culture medium

Medium C/N Ratio Composition

A 107.2 100% SB (1:0, SB:SH)

B 63.4 80% SB + 20% SH (8:2, SB:SH)

C 44.9 60% SB + 40% SH (6:4, SB:SH)

D 39.2 50% SB + 50% SH (5:5, SB:SH)

E 28.3 20% SB + 80% SH (2:8, SB:SH)

F 23.8 100% SH (0:1, SB:SH)

The preliminary experiment was incubated at 30°C for 5 days for understanding

the effect of different mixed substrates on SSF at the beginning of the study. From

Figure 5.12, it is noticed that there was nearly no growth of Trichoderma

longibrachiatum (Figure 5.12a). However, when 80% of the sugarcane bagasse

was mixed with 20% of soybean hulls (Figure 5.12b), the growth was slightly


108

improved. The centre area of mixed-substrate could be seen covered by the green

coloured fungus with spreading mycelia in the case of 60% bagasse and 40% hulls

(Figure 5.12c). There was good growth in parts of the plate with 50% bagasse with

50% hulls (Figure 5.12d). When only 20% bagasse was used for the substrate

(Figure 5.12e), abundant growth of mycelia and spores could be seen around the

substrate. The growth then got poorer as the proportion of bagasse to hulls got

smaller. In the last experiment, 100% soybean hulls (Figure 5.12f), careful visual

observation showed that there were some mycelia formed on the substrate, which

means that Trichoderma longibrachiatum did grow on the substrate. Nevertheless,

no spores could be seen in this case.

Figure 5.12 Growth of Trichoderma longibrachiatum on different mixed substrate ratios (a) 1:0, SB:SH (b) 8:2, SB:SH (c) 6:4, SB:SH (d) 5:5, SB:SH (e) 2:8, SB:SH (f) 0:1, SB:SH.

It was observed that some mixed substrates, for example, medium c (6:4, SB:SH)

shrank considerably during the fermentation. Also, it was observed that the

fermented solids inside the petri dish had formed a complete cake through the

extension of the fungal hyphae (Figure 5.13). Due to the extent of growth and cake


109

formation, it was not easy to get representative samples to measure composition

of fermented substrate and enzyme activities from heterogeneous medium,

especially under time course experiment using the same bioreactor.

Figure 5.13 Growth of Trichoderma longibrachiatum on mixed substrates at a ratio of 6:4 (SB:SH)

Cultivation media were consumed for the metabolism of the fungus, and cell

formation during solid state fermentation. Consequently, the highest dry weight

loss should take place in the fermentation with highest cellular metabolic activity.

The dry matter weight loss during each fermentation is presented in Figure 5.14.


110

Figure 5.14 Dry weight loss of the solids after 5 days fermentation with different mixed substrate ratios

As can be seen in Figure 5.14, the highest reduction in the dry weight was observed

in the fermentation with mixed substrate at a ratio of 5:5 (SB:SH). In this study,

ratios of 1:0, 8:2, and 6:4 (SB:SH) show increasing dry weight loss with increasing

soybean hull addition. Thereafter, the reduction of dry weight between 6:4 to 0:1

(SB:SH) was quite similar. The trend of weight reduction is similar to previous

experiments with supplemented nitrogen, which showed increased dry weight

loss with decreasing C/N ratio.

The major goal of implementing solid state fermentation using agricultural wastes,

in this study, was to produce sugars and FAN as a potential generic fermentation

feedstock. In this set of experiments, the effect of mixed substrate ratio on

nutrients production was investigated. Reducing sugars were measured after the

120 h of solid state fermentation and solid state fermentation with subsequent

hydrolysis, respectively. The experiments were carried out with mixed substrate

ratio between 1:0 to 0:1 (SB:SH) and results are presented in Figure 5.15.

0

5

10

15

20

25

30

35

1:0 8:2 6:4 5:5 2:8 0:1

Dry

mat

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(% o

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Substrate ratio (SB:SH)


111

Figure 5.15 Effect of mixed substrates ratio on sugar production via solid state fermentation (SSF) or sequential bioprocessing (SSF + hydrolysis)

As can be seen from Figure 5.15, an equal mixture of substrates 5:5 (SB:SH) ratio

gives the best result after 120 h of solid state fermentation, 202 mg/g of sugar

productivity. Using further hydrolysis at 50°C for 48 h, more sugars were released

from the substrate by enzymes already attached to cellulose and hemicellulose.

The mixed substrate ratio of medium directly affects sugar production after

sequential bioprocessing (SSF + hydrolysis). Sugar yields raised with increasing

soybean hull supplemented up to 50% (w/w) of addition, and decrease thereafter.

The highest sugar production, 197.4 mg/g substrate, was obtained in the

fermentation carried out at mixed ratio of 6:4 (SB:SH).

The carbon to nitrogen (C/N) ratio is always used as a measure of nutrient balance

in the fermentation process. Also, It is known that C/N ratio of substrates is a

critical factor that determines microbial growth, and metabolite formation in solid

state fermentations (Mantovani et al., 2007; Sun et al., 2010). According to Table

5.5, varied mixed-substrate trials can be presented in specific carbon to nitrogen

(C/N) ratios. Figure 5.16 presents five significantly (p<0.05) different groups (a to

e) of sugar yield during further hydrolysis with different C/N ratios. The highest

sugar production, 187.4 mg/g substrate, was obtained in the fermentation carried

0

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100

150

200

1:0 8:2 6:4 5:5 2:8 0:1

Red

uci

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suga

r (m

g/g

sub

stra

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SSF

SSF + hydrolysis


112

out at mixed ratio of 6:4 (SB:SH). It is worthwhile to note that in substrate

formulations with C/N ratio ranging from 44.9 to 39.2 (SB: SH from 6:4 to 5:5),

sugar production was similar, with no significant (p<0.05) difference. There was a

low sugar production in the substrate with C/N ratios lower than 39.2. In the

medium with C/N ratio of 23.8 (100% of soybean hull) there was significant

(p<0.05) reduction of sugar yield when compared to the substrate with C/N ratio

of 28.3 (20% of sugarcane bagasse and 80% of soybean hull). The above results

suggest appropriate medium could provide prolific fungal growth and sufficient

enzymes to break down the tough lignocellulosic structure, leading to efficient

subsequent hydrolysis of fermented solids.

Figure 5.16 Average sugar yield in subsequent hydrolysis after 5 days of growth on substrate consisting of mixtures of sugarcane bagasse and soybean hull with different carbon/nitrogen ratios. Different letters represent groups with significant differences (p<0.05)

FAN production during various processes with different mixed substrate ratios was

compared as shown in Figure 5.17: solid state fermentation (SSF) and solid state

fermentation followed by subsequent hydrolysis (SSF + hydrolysis). During the

solid state fermentation, FAN production was low (below 2.5 mg/g substrate) with

soybean hull supplements from 0% to 80%. Interestingly, the FAN yield was

0

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180

200

0 20 40 60 80 100 120

Suga

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a

b

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e


113

markedly increased to 7 times using soybean hull only as substrate and reached

the maximum value of 18 mg/g substrate. It is likely that the high protein content

in soybean hull (11.9%) compared with sugarcane bagasse (2.5%), stimulates

higher protease activity production. As a result, a high level of FAN content was

observed in the case of fermentation using soybean hull only.

Figure 5.17 Effect of mixed substrate ratios on FAN production via solid state fermentation (SSF) or sequential bioprocessing (SSF + hydrolysis)

FAN production after sequential bioprocessing (SSF and hydrolysis) is affected

significantly by the ratio of sugarcane bagasse to soybean hull as shown in Figure

5.17. FAN concentration was greatly increased when the soybean hull was added

to the medium. With increased addition of soybean hull to the medium, FAN

reached the highest level (28.2 mg/g) when soybean hull was used alone. As

mentioned before, during the subsequent hydrolysis of fermented solids, not only

the enzymatic hydrolysis reaction happened, but also the autolysis of the fungal

cells occurred under an oxygen limited condition. Two sources to be converted to

FAN after the hydrolysis stage could contribute to (1) remaining substrate protein

and (2) fungal cells. In these experiments, insufficient remaining protein for

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35

40

1:0 8:2 6:4 5:5 2:8 0:1

FAN

(m

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SSF + hydrolysis


114

subsequent hydrolysis could be the reason for low FAN content (ranging from 0%

to 50% of soybean hull supplemented), caused by microbial consumption and low

protein provided during solid state fermentation.

Effect of environmental humidity on SSF (in petri dishes)

Smits et al. (1999) explicitly describes the water balance of solid-state

fermentation, which consists of three important processes (1) metabolic water

production by the microorganism (2) evaporation of water (3) diffusion of water

vapour in the fermentation bed (Figure 5.18). Even though simulations with the

model suggested that the diffusion of water was not important for a tray

bioreactor incubated in a 98% relative humidity headspace, it might become

important if the tray were incubated within a drier atmosphere (e.g. lower

humidity). This might be done to promote an evaporative cooling effect, although

such a strategy would quickly lead to drying out of the fermentation bed (Mitchell

et al., 2003; Smits et al., 1999). Evaporation effect is a major concern in the

moisture control of solid-state fermentation, especially in bioreactors. It is

important to keep consistency of operating factors such as moisture content from

laboratory scale to large scale production. However, far too little attention has

been paid to environmental humidity influence (humidity of incubator) on solid-

state fermentation using petri dishes.


115

Figure 5.18 Water balance in a solid state fermentation using petri dish system

Evaporation is the process by which liquid is vaporised from a surface into a

gaseous phase that is not saturated with the evaporating substance. Mitchell et al.

(2006) mentioned that the degree of evaporation depends on the saturation of

the air. If the air entering the bed is not saturated with water, it will promote

evaporation and dry out the bed, eventually decreasing the water activity to

values unfavourable for growth. Saturated air should therefore be supplied for air

inlet, so that the evaporation effect can be minimised. The same phenomenon

could be happening in the small-scale fermentation system (petri dish).

Petri dishes (9 cm diameter) containing 5 g of non-fermented mixed solid medium

substrates (6:4, SB:SH) were tested with different environmental relative humidity

(35% and 75%) at 30°C. The initial moisture content of solids was 65% (w/w, db).

All samples were put in the petri dishes and covered with lids without inoculating.

Using the moisture ratio to generalise the change of moisture content is the most

common method in the drying trial. Results for the test are shown in Figure 5.19.

Clearly, with a low environmental humidity (35%), the evaporation rate from the

non-fermented solids was higher than when the surroundings were more humid.


116

According to the results obtained, the effect of environmental humidity on solids

in the petri dish did cause significant difference in water evaporation. The

moisture ratio observed for the non-fermented substrate under 35% of

environmental relative humidity after 7 days was around 0.29, while for the higher

relative humidity (75%) during the same period a value of around 0.71 was

reached. This is due to the higher moisture difference between the outside

environment and the head space within the petri dish, which provides the driving

force for the evaporation.

Figure 5.19 The moisture ratio of non-fermented solids under different

environmental relative humidity (35 and 75%)

In order to understand the effect of relative humidity on growth, the different

levels were tested (35% and 75%, relative humidity) with inoculated substrates.

The relative humidity of incubator can be regulated by placing an open container

filled with sterilised water at the bottom of the incubator. The environmental

relative humidity could achieved and maintained 75% within 2 hours in the

incubator at 30°C. On the contrary, the relative humidity of incubator was only

35% without providing sterilised water in the container. To make sure the

consistency of the relative humidity level, the portable humidity sensor was used

to monitor the variation during the solid-state fermentation.

0

0.1

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117

The required amount of spore suspension was poured into disposable Petri dishes

(9 cm diameter) and the solid fermentation was started by adding 5 g of the

sterilized mixed solid substrate (6:4, SB:SH). The pH was not controlled and the

plates were incubated under static conditions at 30°C. Plates from different

cultivation conditions were withdrawn for analysis at the desired intervals. The

initial moisture content of all substrates was adjusted to 65% (w/w). Results are

shown in Figure 5.20.

Figure 5.20 The moisture ratio of solid state fermentation under different environmental relative humidity (35 and 75%)

The decrease of moisture ratio for both conditions is quite similar during the first

2 days of incubation, where there appears to be a balance between water

production (via metabolism) and water loss (via evaporation). However, the

moisture ratio reduction for the low humidity case (35%) after 3 days is much

faster than that for the higher one (75%). The moisture ratio experimentally

obtained for the incubator with high humidity was still around 0.93 after 7 days,

while for the incubator with low humidity the value had fallen to around 0.47.

Clearly, in the high humidity case, there is a good balance between production and

loss. As in the non-fermented substrates test, Inspection of Figure 5.20 shows a

0

0.2

0.4

0.6

0.8

1

1.2

0 1 2 3 4 5 6 7

Mo

istu

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35% 75%


118

significant difference between high and low humidity environments for solid state

fermentation using petri dishes.

The values of effective diffusivities (Deff) of fermented and non-fermented

substrates for the two humidity environments are presented in Table 5.6. As

expected, the values of Deff increased with increasing moisture difference between

environment and system (petri dish). It shows that the non-fermented substrate

of environment with low humidity affords higher values of Deff, about 2.87 times,

than that with high humidity. Furthermore, conducting solid state fermentation at

the same condition for moisture ratio resulted in a raise of about 15 times in Deff

values. The above results mean that the metabolic water production during

fermentation leads to effective diffusivities for the fermented solids that are

apparently lower than those for non-fermented solids.

Table 5.6 Values of effective diffusivities obtained with different environmental humidities on solid state fermentation

Sample Effective Diffusivity (m2s-1)

Non-fermented, 35% 1.278 x 10-11

Non-fermented, 75% 4.45 x 10-12

Fermented, 35% 9.02 x 10-12

Fermented, 75% 5.86 x 10-13

For mass and heat transport during heating process, external and internal

transport phenomena can be distinguished. External transport occurs from the

particle surface to the surrounding air and internal transport from the inner to the

outer layer of the particle. The difference of water concentration between the gas

and the solid phase, and the bulk of the air is the driving force for mass transfer

(Sun, 2007). When the water concentration gradient is increased in the gas phase

between system (petri dish) and environment (incubator), the moisture content

of substrate can reduce dramatically due to evaporation of the existing water in

the solids through metabolic heat evolution. It is worthwhile to note that the use

of high relative humidity does not prevent evaporation from occurring within the


119

bed, but it does minimize evaporation compared to the use of unsaturated air. The

reason could be attributed to the metabolic water production during solid state

fermentation, which can maintain the desired level of moisture content when the

minor evaporation effect occurs under small water concentration difference

between system and environment.

As can be seen in Figure 5.21a, which shows petri dishes from above and below,

the fungi development during 3 days of fermentation with high relative humidity

(75%) occurs on both top and bottom surfaces. In addition, droplets of condensed

water were observed on the internal surface of the lid. The low concentration

gradient between environment (incubator) and system (petri dish) could leave

abundant water vapour inside the petri dish, leading to condensation when it

reached the lid. However, in the other experiment with lower relative humidity

(35%) lower growth was observed, with very poor growth on the bottom surface

(Figure 5.21b).


120

Figure 5.21 Effect of the relative humidity on SSF after 3 days (a) 75% (b) 35% showing top (left) and bottom (right) views

After 5 days of fermentation it could be seen that fungal growth favoured the high

relative humidity environment (Figure 5.22). It was noticed that the entire surface

of the substrate was covered with spores and mycelium in the fermentation with

higher relative humidity (75%). In contrast, the lower relative humidity case (35%)

showed much less growth on the same mixed substrate. Despite having been

inoculated over entire petri dish, Figure 5.22b shows two quite distinct areas on

the surface of the substrate; a green surface covered by the prolific fungal growth

in the centre of the substrate (area 1); and poor development in the outer region

of the medium (area 2). The moisture content of the centre area was measured at

56%, whereas the outer region was only 19%. The moisture content of substrate

in the centre was therefore almost 3 times greater than that found for the outer


121

region. This visual observation supports the phenomenon observed in Figure 5.20,

where the high moisture gradient between petri dish and incubator led to

increased moisture content reduction of substrate during solid state fermentation.

Figure 5.22 Effect of the relative humidity on SSF after 5 days (a) 75% (b) 35%

Further hydrolysis of fermented solids should be also investigated to understand

the effect of humidity level on sequential bioprocessing (SSF and in-situ enzyme

hydrolysis). Figure 5.23 indicates that the sugar yield was enhanced by increasing

environmental humidity level from 35% to 75%, and maximum reducing sugar

production yield of 263.1 mg/g substrate was obtained when the relative humidity

level was 75%. It is acknowledged that the water activity (aw) of the substrate is a

key factor affecting microbial activity and enzyme production, an optimal moisture

level has to be maintained during solid state fermentation (Molaverdi et al., 2013).

Strong evaporation effect and mass transfer work synergistically to promote water

vapour diffusion from substrate, leading to low moisture level of the substrate

(Figure 5.22b) to reduce fungal growth, enzyme activity and substrate

deconstruction. However, there is no significant difference between low humidity

level and high humidity level on FAN production, 13.4 mg/g substrate and 13.8

mg/g substrate, respectively. This is probably due to the same limited nitrogen

source supplied (SB:SH, 6:4) of the substrate for sequential bioprocessing.


122

Figure 5.23 Effect of environmental humidity level on sugar and FAN production via sequential bioprocessing (SSF + hydrolysis)

In summary, relative humidity is one of the most important aspects of fungi

growth in petri dishes as it has a direct influence on evaporation. A low relative

humidity increases evaporation rate from the moist fermented medium.

Depending on the process, the results obtained in a preliminary test indicated the

necessity of a better control of the medium moisture content by maintaining a

high humidity content of the incubation environment. This measure could provide

similar and more reliable results for comparison with larger scale experiments.

Effect of incubation time on sequential enzyme hydrolysis

During solid state fermentation, enzyme activities and deconstruction level of

substrate are affected by the growth of the microorganism. Therefore, it is crucial

to monitor nutrients production to find the optimal time to terminate the

fermentation to have a proper enzyme complex and accessible substrate for

0

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16

18

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Re

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The relative humidity of Incubator

Reducing sugar

FAN


123

further hydrolysis. Based on the outcomes of the pervious experiments, the size

of sugarcane bagasse was adjusted to 1.4-0.85 mm and mixed with soybean hull

in the ratio of 6:4 (SB:SH). Initial moisture content of substrate was set to 65%

(w/w), the relative humidity in the incubator was fixed to 75% and the

fermentations were carried out at 30°C. The time interval chosen for sampling was

every 24 hours.

After 1 day of solid state fermentation, further hydrolysis yielded only 5.6 mg

reducing sugar/g solid and 3.9 mg FAN/g solid (Figure 5.24). After 5 days of

incubation, the reducing sugars and FAN, after subsequent hydrolysis, were 226.3

mg/g and 7.7 mg/g respectively. Beyond 5 days of solid state fermentation, sugar

yield started to decrease and further incubation times were markedly affected. It

is believed that sugar production was considered to be associated with cellulase,

beta-glucosidase and hemicellulase activity that degraded cellulose and

hemicellulose remaining after SSF. The decreasing pattern, however, suggests that

the synergistic effect of lignocellulosic enzymes might reach highest level during 5

days of fermentation and thus hit the highest point of further hydrolysis

performance. As for FAN production, it was a result of the activity of both

extracellular protease released during the fermentation and intracellular protease

from autolysis (Wang et al., 2010). FAN production rose gradually until 5 days of

SSF and then reached a plateau around 7.8 mg/g substrate. This is probably due

to the limited nitrogen content of the substrate and the inhibition of enzymes by

the product.


124

Figure 5.24 Effect of SSF incubation time on Sugar and FAN production via sequential bioprocessing (SSF + hydrolysis)

A further experiment was carried out to show the celluloytic enzyme activities

produced from Trichoderma longibrachiatum in SSF system (Table 5.7). Since

sequential bioprocessing development is our priority, further investigation in the

coming chapters focuses on the generic feedstock production rather than

optimisation of enzyme production.

Table 5.7 Celluloytic enzyme activities produced by T. longibrachiatum

Sources of enzymes Enzyme activities1

Exoglucanase Beta-glucosidase Xylanase

FPU/g U/g U/g

DEPOL 686L 24.9 144.5 382.4

1 enzymes production from Trichoderma longibrachiatum under 5 days of solid-state fermentation using mixed-substrates (SB:SH, 6:4)

0

1

2

3

4

5

6

7

8

9

10

0

50

100

150

200

250

300

1 2 3 4 5 6 7

FAN

(m

g/g

sub

stra

te)

Re

du

cin

g su

gar

(mg/

g su

bst

rate

)

Incubation time of SSF (day)

Reducing sugar

FAN


125

Summary

The main objectives of the experiments reported in this chapter were to check the

feasibility of sugarcane bagasse and soybean hull for the growth of Trichoderma

longibrachiatum and subsequent hydrolysis. The influence of operational factors

for solid state fermentation and environmental variables on this system for sugar

and FAN production were also investigated. Preliminary studies of Trichoderma

longibrachiatum in mixed-substrates demonstrated its capability to produce a

generic microbial feedstock. This indicates that sequential bioprocessing could be

a competitive choice for microbial culture medium production (sugar, FAN and

other minerals) and a suitable alternative to traditional sugar production from

lignocellulose.

Chapter 6 Production of a generic feedstock: subsequent hydrolysis

126

CHAPTER 6


subsequent hydrolysis

Introduction Enzymatic hydrolysis efficiency has a great influence on the overall lignocellulose

bioconversion process and thus has been recognised as one of the bottlenecks in

lignocellulose biorefinery development during the past two decades. Besides the

technical challenge of enzyme hydrolysis, the cost of enzyme is another issue to

be solved. It is evident from the literature that enzymatic hydrolysis accounts for

up to around 66% of the cost on lignocellulose-based bioethanol (Du et al., 2014).

Currently, no report on direct utilisation of raw lignocellulose for microbial

feedstock using solid state fermentation and subsequent in-situ enzyme hydrolysis

with fungal autolysis is available. In chapter 5, the technical feasibility of utilising

the sugarcane bagasse and soybean hull as raw material for generic microbial

feedstock has been demonstrated through preliminary trials. The focus of this

chapter is the investigation of operation factors on the subsequent hydrolysis with

fungal autolysis of fermented solids. The effect of solid loading and reaction

conditions (temperature, pH, as well as inhibitor addition) on hydrolysis was

closely studied and enzyme activities were explored under different pH and

temperature. Additionally, specific attention was given to fungal autolysis in the

submerged cultivation in order to verify that fungal autolysis occurred in the

oxygen-limited environment.


127

Solid to liquid ratio effect Unlike starch hydrolysis, being an insoluble and highly heterogeneous substrate,

lignocellulosic materials pose several challenges in conversion to fermentable

sugars (Kristensen et al., 2009). Increasing a solid loading in hydrolysis is one of

the most important challenges to make biofuels production more economical due

to the reduction of water usage and ethanol distillation cost (López-Linares et al.,

2014; Modenbach and Nokes, 2013). In most of the lignocellulose-based ethanol

production, the final ethanol titer should be above 4% (v/v), which is the minimum

for economic feasibility (Huang et al., 2011; Jørgensen et al., 2007b; Wingren et

al., 2003). To reach an ethanol concentration higher than 4%, a promising

approach is to increase substrate concentrations up to 20% (w/w) during enzyme

hydrolysis. However, High solids concentrations would lead to larger levels of end-

product inhibition (Andrić et al., 2010), limitation of enzyme diffusion (Lee and Fan,

1982; Wang et al., 2011) and viscosity increase, as well as stirring and mixing

limitations (López-Linares et al., 2014). To reduce these negative effects and

facilitate lignocellulose conversion, different strategies such as fed-batch mode or

diverse pretreatment process have been proposed for subsequent hydrolysis at

high substrate concentrations.

In this study, fermented solids need to be prepared for further hydrolysis. The 10

g of mixed substrates (6:4, sugarcane bagasse: soybean hull) for each solid state

fermentation were prepared. The substrate and mineral salt solution were then

autoclaved at 121 ° C for 20 min. After the substrates had cooled to room

temperature, they were moistened with the mineral salt solution, subsequently

inoculated with T. longibrachiatum spore suspension and mixed with the substrate

thoroughly to reach a concentration of 1x106 spores/g substrate and final

moisture of 65% (g water per 100 g wet substrate). The solid state fermentations

using petri dishes under 75% of environmental humidity condition were carried

out for 5 days. After 5 days of fermentation, enzymatic hydrolysis and fungal

autolysis were carried out at pH 4.8 using 0.05 M sodium citrate buffer and 50°C

in an incubator shaker at 160 rpm for 48 h under oxygen-limited condition. The


128

experiments were carried out in 500 mL Duran bottles containing a total dry mass

of 10 g fermented solids. Considering the type of hydrolysis step used in our study,

approximately 12-15% of insoluble solids represent the upper limit at which

lignocellulose can be mixed effectively in stirred-tank reactors (Hodge et al., 2009).

Therefore, different fermented solids loading at 2%, 4%, 6%, 8%, 10% and 12%

(w/w) were investigated in the further hydrolysis experiments after solid state

fermentation. All experiments were conducted in duplicate.

As shown in Figure 6.1, the amount of free liquid water decreased as the solid

loading increased (2 to 12%, w/w). Further increase of the bagasse concentration

was attempted, however, the bagasse powder is so bulky and puffy that complete

wetting in solution could not be achieved. Thus, 12% was considered as the highest

loading ratio for the hydrolysis experiment at lab scale. The material with 12%

loading initially appeared as only slightly moist and very little free water could be

observed in the bottle. The materials with lower solid loading (2 to 8%, w/w) were

transformed into a paste-like matter after around 20 h. However, materials with

initial 12% (w/w) were still dense and had a clay-like appearance. It is well known

that end-product inhibition plays an important role in enzymatic hydrolysis and

particularly cellulase, beta-glucosidase and cellobiohydrolase (Xiao et al., 2004).

Figure 6.1 Post-fermentation hydrolysis of bagasse at different solid loadings (2, 4, 6, 8, 10 and 12 g) into 100 mL citric buffer solution


129

During the hydrolysis step, the yield of sugar production gradually decreased (33

to 11%) as the solids concentration increased, the sugar yield was reduced to

almost one third at 12% (w/w) of solid loading compared with that at 2% (Figure

6.2). On the other hand, sugar concentration increased (6.5 to 13.14 g/L) as solid

loading decreased. For free amino nitrogen (FAN) production, both yield and

concentration decreased with increasing solid loading (Figure 6.3).

The process used in this experiment is quite distinct from previous lignocellulose

hydrolysis studies, though they have quite similar hydrolysis kinetics. In this

research, instead of additional commercial or crude enzymes, the in-situ enzymes

were transferred with fermented solids and used for further hydrolysis.

Furthermore, secreted enzymes have probably already attached to the surface of

the substrate (cellulose, hemicellulose) as the mycelium penetrated into the

bundle of lignocellulosic fibres during the solid state fermentation. Once

fermented, these are transferred directly to the hydrolysis step where, unlike with

the use commercial enzymes, they are already absorbed into the substrate.

Figure 6.2 Effect of substrate concentration on sugar production in subsequent hydrolysis of fermented bagasse/SBH solids

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

3

5

7

9

11

13

15

0.02 0.04 0.06 0.08 0.1 0.12

Yiel

d (

g/g

pre

trea

ted

su

bst

rate

s)

Red

uci

ng

suga

r (g

/L)

Solid loading ratio in enzyme hydrolysis (g/g)

Reducing sugar

Yield


130

Figure 6.3 Effect of substrate concentration on FAN production in subsequent hydrolysis of fermented bagasse/SBH solids

The results confirm that the in-situ enzymes enable saccharification of

lignocellulosic materials at 12% (w/w) of solid concentration, and probably even

higher. However, the general trend appears to be a significant decrease in

conversion yield of sugar with increasing solid content. The reduced efficiency at

higher solid loadings appears to be a general effect as previous studies

investigating the relationship between solids concentration and conversions

showed a similar effect. Since the problem of enzyme diffusion is minimised in the

process proposed in this thesis, part of the reason for the decreased yield might

be end-product inhibition, which intensifies as the substrate concentration

increases (Jørgensen et al., 2007b). Unlike sugar production, the decreasing FAN

concentration with increasing loading could be attributed to the ineffective mixing,

which is a crucial factor influencing the hydrolysis efficiency. Further and more

specific testing in the stirred reactor would be required to clarify the limitation of

solid loading in subsequent hydrolysis. Because different types of analysis (sugars,

FAN, moisture content and composition analysis) need to be carried out within

limited raw materials (sugarcane bagasse), the 4% solids loading was chosen

instead of the higher solids loading in the next experiments.

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

100

150

200

250

300

0.02 0.04 0.06 0.08 0.1 0.12

Yiel

d (

g/g

pre

trea

ted

su

bst

rate

)

FAN

(m

g/L)

Solid loading ratio in enzyme hydrolysis (g/g)

FAN

Yield


131

Temperature and pH effect A lot of reported studies on enzymatic hydrolysis of cellulose or lignocelluloses

using commercial Trichoderma reesei cellulase were conducted at pH 4.8 with

temperature near 50°C, and it was found that activity would be maximised within

a pH range between 4.8 to 5.0 and decrease out of this range (Lan et al., 2013).

However, the optimal range could be slightly different between varied

lignocellulose and pure cellulose. One of the reasons for the above difference is

the amount of existing lignin in lignocellulose to show a surface hydrophobic

property and cause nonspecific binding to the cellulase or other enzymes

(Mansfield et al., 1999). The pH value can influence substrate surface charge

through surface functional groups to change hydrophobicity of the surface. Also,

the pH-induced lignin surface charge may also affect electrostatic interactions

between enzymes and lignin. This surface charge variation can lead to various

effects on hydrophobic/hydrophilic and perhaps electrostatic interactions

between cellulase and lignin in reducing cellulase non-productive binding to lignin

and therefore enhancing saccharification among different substrates. The enzyme

activity could be adversely affected by temperature through protein denaturation

and adsorption (Lan et al., 2013; Seiji Nakagame et al., 2011). Moreover, crude

multi-enzyme solution from the specific microorganism could present different

behaviour rather than single enzyme shown in previous research. To explore the

effect of pH and temperature on enzyme hydrolysis using in-situ multi-enzymes

could provide further knowledge to optimise the process design.

The fermented solids for further hydrolysis were prepared following the

procedure in section 5.8. The objective of the present work was to investigate the

effect of pH (4-8.5) and temperature (40-60°C) on enzymatic hydrolysis using the

in-situ enzymes with whole fermented media of Trichoderma longibrachiatum

cultivated on substrates.

The optimum temperature and pH for subsequent hydrolysis and autolysis were

determined by conducting experiments at 40, 50, 60°C from pH 4 to pH 8.5.


132

Reaction temperature was controlled at three levels in order to investigate the

possible growth of contaminants and fungal growth. The maximum sugar

concentration of hydrolysis (9.1 g/L) was achieved at 50°C, pH 6 (Figure 6.4). The

large yield at 50°C, pH 6 could be attributed to the fact that this temperature and

pH combination is close to the optimum one for these multi-enzymes (e.g.

cellulase, xylanase and beta-glucosidase). Overall, the enzymatic hydrolysis below

60°C could achieve better sugar production in the experiments. By comparing the

results presented in Figure 6.4 and Figure 6.5 for the experiments measured for

FAN concentration, the profile is slightly different. The FAN production increases

gradually from pH 4 to pH 6 at different temperature levels except in the 50°C trial.

It can be observed that the FAN production hit the peak at a pH value of pH 7 then

declined at pH 8.5. These results differ from previous study that showed the pH

effect (3-6.5) did not considerably affect the degree of fungal autolysis

(Koutinas et al., 2005). A possible explanation for this might be that the specific

characteristics were of multi-enzymes presented from a different fungus (i.e. T.

longibrachiatum). The fungal mycelium autolysis and hydrolysis requires the

synergism of many enzymes because of the complexities of cell walls and

substrates. Each of the enzymes secreted from different microorganisms catalyses

a specific reaction in a particular pH range. Another possible reason for this is that

the substrate used for hydrolysis and autolysis could affect the efficiency of

enzyme-binding in varied pH environments (Lan et al., 2013).


133

Figure 6.4 Effect of temperature and pH on sugar production during 48h further hydrolysis after solid state fermentation

Figure 6.5 Effect of temperature and pH on FAN production during further hydrolysis after solid state fermentation

Growth of contaminants never occurred in any experiments implemented at

temperatures above 50°C. However, fungal re-growth could happen at 40°C during

enzyme hydrolysis and fungal autolysis under oxygen-limited conditions. Figure

6.6 shows that at 40°C some white specks formed in the hydrolysate after 48 h.

0

1

2

3

4

5

6

7

8

9

10

3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

Red

uci

ng

suga

r (g

/L)

Reaction pH

40℃

50℃

60℃

0

100

200

300

400

500

600

3.5 4 4.5 5 5.5 6 6.5 7 7.5 8 8.5 9

FAN

(m

g/L)

Reaction pH

40℃

50℃

60℃


134

This may be attributed to insufficient environment stress during the fungal

autolysis, so the fungi kept growing and formed mycelia in the nutrient solution.

Many fungi can grow in submerged fermentation in different forms ranging from

dispersed filaments to pellets, depending on culture conditions and the strain of

organism used. Different pellets could be observed from loosely packed hyphae,

forming ‘‘fluffy’’ pellets, to tightly packed, compact, dense pellets (Ferreira et al.,

2009; Papagianni, 2004).

Figure 6.6 possible fungal growth during enzymatic hydrolysis and autolysis at 40°C, pH 6

The effect of microbial inhibitor on further hydrolysis

The implementation of enzyme hydrolysis with fungal autolysis above 50°C under

oxygen-limited environment is very crucial in the process developed during this

project. Not only did it accelerate enzyme activities to produce sugars, nitrogen

and other nutrients, it also inhibited fungal growth and destroyed the mycelium

through the action of its own enzymes (autolysis). However, because no

sterilisation was carried out when the fermented solids were transferred to the

further hydrolysis steps, there is a risk of contamination in the subsequent

hydrolysis under particular conditions. Numerous studies have used sodium azide


135

to prevent microbial growth during enzyme hydrolysis of lignocellulose (Kuo and

Lee, 2009; Mussatto et al., 2008). Because the influence of microbial inhibitor on

further hydrolysis is unknown, especially in the oxygen-limited condition, it is

necessary to test microbial addition effect on further hydrolysis. In the present

study, the effect of microbial inhibitor addition was investigated under the same

hydrolysis procedure as mention in section 6.1. The solid loading was 4% (w/w) at

50°C, 160 rpm under oxygen-limited condition in citric buffers at two pH values

(4.8 and 6) and sterilised tap water (6.5), respectively.

Figure 6.7 and 6.8 show that the sugar and FAN hydrolysis profile varied under the

different conditions used. It is immediately apparent that the overall sugar

production is more or less the same between the hydrolysis with sodium azide

addition and those without addition (Figure 6.7). The sugar concentration rose

steadily without sodium azide addition from pH 4.8 to pH 6, and achieved highest

while using sterilised water. The above results demonstrate that the further

hydrolysis at 50°C under oxygen-limited condition could suppress microbial

activity effectively.

Figure 6.7 Effect of microbial inhibitor on sugar production during further hydrolysis after solid state fermentation

0

1

2

3

4

5

6

7

8

9

pH 4.8 pH 6 Sterilised water (pH 6.5)

Re

du

cin

g su

gar

(g/L

)

without addition

sodium azide addition


136

Figure 6.8 Effect of microbial inhibitor on FAN production during further hydrolysis after solid state fermentation

The influence of sodium azide addition on FAN production after 48 h of further

hydrolysis is shown in Figure 6.8. In general, subsequent hydrolysis with the

addition of sodium azide were higher than without sodium azide. Both conditions

could achieve the highest FAN concentration in pH 6. It is interesting to note that

sodium azide is one of the non-specific autolysis inducers to inhibit cytochrome

oxidase and ATPase to trigger autolysis reaction (Chung et al., 2009). This could be

the reason that hydrolysis with sodium azide could reach higher FAN

concentration in some specific conditions but more or less the same sugar

concentration compared to the trials without sodium azide addition. However,

sodium azide may affect some microorganisms such as Saccharomyces cerevisiae

and Candida albicans (Fales, 1953; Rikhvanov et al., 2002). This effect must be

considered when the hydrolysate is used for subsequent fermentations. The

results shown in this section indicate the possibility of sterilised tap water used in

hydrolysis to substitute citric buffer to reduce production cost.

0

50

100

150

200

250

300

350

400

450

pH 4.8 pH 6 Sterilised water (pH 6.5)

FAN

(m

g/L)

without addition

sodium azide addition


137

Fungal autolysis Fungal autolysis is the natural process of self-digestion of aged hyphal cultures,

happening as a result of hydrolyase activity, leading to disruption of organelles and

cell wall structure to release cytoplasmic proteins and vacuolation (White et al.,

2002). Numerous previous studies have been carried out on the susceptibility to

autolysis and lysis of fungal cell walls. For example. In many bioprocesses fungi

may be exposed to either nutrient limitation or physical stress leading to

morphological and/or physiological changes (Lahoz et al., 1986; Pollack et al.,

2008). Environmental stress induced changes may cause damage in some

bioprocesses such as penicillin production (Harvey et al., 1998). But for some

processes, the autolysis could significantly benefit outputs through rational

process integration. A series of studies in the SCGPE has demonstrated that fungal

autolysis can yield beneficial results, for example, nutrient supplements

production from fermented residues (Dorado et al., 2009; Du et al., 2008a;

Koutinas et al., 2005; Wang et al., 2010).

Microscopic observations showed that cell walls were difficult to solubilise

completely and break down at temperatures between 50 and 60°C. There are

similarities between the results presented in the present study and those

described by Koutinas et al. (2005). Figure 6.9 shows the degradation of released

cytoplasm and some of them can be observed around the hyphae. Overall, the

damage to cell wall structure was limited because autolysis could continue for over

30 days once the environmental stress was imposed (Lahoz et al., 1986). The

reported results about the resistance of fungal cell walls could be consistent with

the observation of partial degradation in the first two days of the autolysis process.


138

Figure 6.9 Cytoplasm degradation during the autolysis/hyrolysis of fermented solids at 50°C, pH 4.8

In this study, solid state fermented solids were used as substrate for further

hydrolysis to produce generic microbial feedstock. However, it is not easy to

confirm that the autolysis occurred from data since cellulose and hemicellulose

were hydrolysed by in-situ enzymes simultaneously to increase sugar and FAN

concentration. Therefore, a fungal autolysis test should be examined by the simple

sugars used to rule out the contribution of enzymatic hydrolysis. In this

experiment, Submerged fermentation of T. longibrachiatum (10 g/L glucose, 5 g/L

yeast extract, pH 6 citric buffer) was carried out at 30°C, 160 rpm for 120 h. At the

end of fermentation, the whole medium was transferred to the Duran bottle and

the temperature increased to 50°C, 160 rpm for 48 h, causing fungal autolysis

under environmental stress (high temperature and oxygen-limited condition).

The fungal autolysis trial was tested in an oxygen-limited environment using the

remaining glucose of a submerged fermentation as carbon source. Under


139

environmental stress condition reducing sugar (glucose) remained unchanged

after 48 h of autolysis (Table 6.1). Meanwhile, FAN concentration increased from

4.7 mg/L up to 13.2 mg/L at the end of reaction. The fungal autolysis was increased

from the results obtained in the early solid state experiment (Figure 6-9). A direct

comparison between the microscopic study of fungal autolysis and nutrient

measurements confirmed that the environmental stress does limit fungal activity

during further hydrolysis.

Table 6.1 Broth composition after 48 h of fungal autolysis

Reducing sugar (g/L) FAN (mg/L)

0 h 1.93 4.7

48 h 1.94 13.2

Kinetics of further hydrolysis The hydrolysis kinetics of fermented substrates with in-situ enzyme complex was

studied. When a suspension of 4% (w/w) fermented solids was transferred at 50°C,

pH 4.8 citric buffer and the production of reducing sugars, FAN (free amino

nitrogen) and IP (inorganic phosphorous) was initiated (Figure 6.10). At the

beginning of further hydrolysis, the mixture contained 25 mg reducing sugar/g

solid, 1.03 mg FAN/g solid and 2.1 mg IP/g solid. At the end of the experiment,

reducing sugars, FAN and IP were 112.48 mg/g, 7.51 mg/g and 9.61 mg/g

respectively. Figure 6.10 shows the production of these nutrient components

during the further hydrolysis and fungal autolysis. The concentration of reducing

sugar rose sharply during the first 10 h then reached the plateau until the end of

reaction. This was probably due to the product inhibition and the enzyme activity

decrease with time, leading to a decrease in hydrolysis efficiency. As for FAN and

IP production, it was a result of protease enzyme and autolytic enzyme activity

that digested fungal cell walls and little nitrogen remained after solid state

fermentation (Koutinas et al., 2005; Wang et al., 2010).


140

Figure 6.10 Profiles of further hydrolysis of the fermented solids at 50°C. The solid lines are generated by equation 6-1 to predict the production of reducing sugar, FAN and IP

Simultaneous hydrolysis and fungal autolysis involve many undefined enzymatic

hydrolysis reactions. The deconstructed cellulose, hemicellulose and remaining

protein from fermented solids were hydrolysed by various in-situ enzymes

secreted during the solid state fermentation. Meanwhile, disintegration of cellular

components occurred in the cytoplasm and cell wall (McIntyre et al., 2000). In

order to predict the production of reducing sugar, FAN and IP, an equation

proposed by Koutinas et al. (2003) was used (Equation 6-1).

𝑋𝑖 = 𝑋𝑖∞(1 − 𝑒−𝑘𝑖𝑡) Equation 6-1

Where 𝑋𝑖is the instantaneous concentration of component i (mg/g solid); 𝑋𝑖∞is

the equilibrium concentration of component i (mg/g solid); ki is the first-order

reaction constant (h-1); and t is the reaction time (h).

The application of nonlinear regression software (Origin 8.0) was used to fit

equation 6-1 to the reducing sugar, FAN and IP production profiles of further

hydrolysis at 50°C and generated the empirical constants and regression

coefficients (Table 6.2).

0

1

2

3

4

5

6

7

8

9

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50

FAN

an

d IP

pro

ud

ctio

n (

mg/

g, d

b)

Tota

l red

uci

ng

suga

rs p

rou

dct

ion

(m

g/g,

db

)

Reaction time (h)

sugar

FAN

IP


141

Table 6.2 kinetic model of further hydrolysis

model R2

Reducing sugar Xs=88.87 (1-e-0.209t) 0.95

FAN XFAN=6.03 (1-e-0.224t) 0.96

IP XIP=7.653 (1-e-0.411t) 0.99

The remaining lignocellulose after fungal autolysis and hydrolysis are shown in

Figure 6.11. The fibres consisted of undigested cellulose and lignin to support the

whole structure. Because of the liberation of cellulose and hemicellulose, a large

number of lignocellulose fragments are shown and seemed clearly hollowed out.

Figure 6.11 Lignocellulose degradation after 48 h autolysis/hydrolysis of fermented solids at 50°C, pH 4.8 citric buffer


142

Characterisation of optimal reaction temperature and pH of the crude enzymes from SSF

Several hydrolytic enzymes were produced by T. longibrachiatum during solid

state fermentation of sugarcane bagasse with soybean hull. The complete

degradation of lignocellulose to sugars or oligosaccharides required synergistic

reaction between different enzymes, therefore the characterisation of each or co-

related enzymes was crucial to determine the hydrolysis yield (Ang et al., 2013).

The aim of this work was to characterise cellulase, beta-glucosidase and xylanase

produced by T. longibrachiatum culture under solid state fermentation. Optimal

pH and reaction temperature of the crude enzyme were determined (Figure 6.12

and 6.13).

In order to determine the optimal reaction pH of crude enzymes, assays were

carried out at various pH levels from 4 to 7 and the results are shown in Figure

6.12. The cellulase exhibited high activity in the range 4.8 - 6 with optimum activity

at pH 4.8 which is the same as that suggested for cellulase activity assay (Wood

and Bhat, 1988). The optimum pH for xylanase activity was at pH 5.4, and over

75% of the peak activity was displayed between pH 4 and 7. As for the beta-

glucosidase, the maximal enzyme activity was obtained at pH 4.8, indicating it was

the optimal condition for cellobiose hydrolysis in this system. Different pH stability

was observed for cellulase (maximum stability at pH 4.8), beta-glucosidase

(maximum stability at pH 4.8) and xylanase (maximum stability at pH 5.4).

Crude enzymes assay was conducted at different temperatures as indicated in

Figure 6.13 from 30 - 80°C with 10°C increment at pH 4.8 in order to determine

the optimal reaction temperature. Optimum temperature of crude cellulase for

hydrolysis of cellulose was found to be 50°C which showed good similarity with

other reported assay protocols (Saleh et al., 2014; Wood and Bhat, 1988). The

optimum temperature of beta-glucosidase and xylanase was 60°C which agreed

with other previous reports (Ang et al., 2013; D and M, 1994). Further increasing


143

temperature greatly reduced the enzyme activity most likely because of enzyme

denaturation.

Figure 6.12 Effect of pH at 50°C on crude enzymes activity

Figure 6.13 Effect of temperature at pH 4.8 on crude enzymes activity

All hydrolytic enzymes presented an optimal pH between 4.8 and 5.4, while the

optimum temperature was 50°C for cellulase and 60°C for the other enzymes

0

20

40

60

80

100

4 4.8 5.4 6 7

Rel

ativ

e ac

tivi

ty (

%)

pH

cellulase

Beta-gulcosidase

Xylanase

0

20

40

60

80

100

30 40 50 60 70 80

Rel

ativ

e ac

tivi

ty (

%)

Temperature (C)

cellulase

Beta-gulcosidase

Xylanase


144

(Table 6.3). The optimal conditions (temperature and pH) of crude enzymes

studied is not surprisingly slight different to those of subsequent hydrolysis of

fermented solids. The reason is due to complex polymers and several enzymes

involved in the complicated hydrolysis.

Table 6.3 Characteristics of hydrolytic enzymes from T. longibrachiatum grown on sugarcane bagasse and soybean hull

Characteristic Cellulase beta-glucosidase Xylanase

50°C

Optimum pH 4.8 4.8 5.4

Enzyme activity 0.67 (FPU/mL) 1.85 (U/mL) 2.61 (U/mL)

pH 4.8

Optimum Temp. (°C) 50 60 60

Enzyme activity 0.68 (FPU/mL) 1.49 (U/mL) 3.95 (U/mL)

Summary A range of different operational variables for further hydrolysis of fermented

residues, following solid state fermentation, were examined and reported in this

chapter. The Solid loading in subsequent hydrolysis was shown to be a key

consideration. Higher loading ratio decreased both sugar and FAN productivity,

and left more unhydrolysed residues. The study of solid loading effect on the

further hydrolysis in Duran bottle suggested that less than 8% (w/w) is an

appropriate choice for sugar and FAN production.

Further researches in subsequent hydrolysis have identified the effect of

temperature and pH on sugar and FAN production. It has been found that 50°C

and pH 7 results in higher reducing sugar and FAN concentration. Moreover,

addition of microbial inhibitor was also studied to provide the effect on further


145

hydrolysis. It was found that the further hydrolysis at 50°C under oxygen-limited

condition suppresses microbial activity effectively. The study of fungal cell

morphology illustrated that T. longibrachiatum release the cytoplasm during

fungal autolysis. Model equations have been used to predict the final reducing

sugars, FAN and inorganic phosphorous concentration after 48 h hydrolysis. The

regression coefficients for all the equations were above 0.95 which is very

reasonable for empirical models. The profile of crude enzymes from solid state

fermentation at the optimum temperature and pH were also evaluated.

Chapter 7 Production of a generic feedstock: bioreactor studies

146

CHAPTER 7


bioreactor studies

Introduction The main goal of this project was the development of generic microbial feedstocks

through sequential bioprocessing (solid state fermentation and further hydrolysis)

using renewable agricultural wastes. Results reported in chapter 5 have

demonstrated the potential of sequential bioprocessing to produce sugar and FAN

for microbial feedstocks using a simple petri dish system.

Unlike submerged fermentation, for SSF (solid state fermentation) there are no

broad general theory or models for scale-up, designing and optimising the

operation of large-scale bioreactors (Mitchell et al., 2006). Essentially, it is

necessary to develop mathematical models based on the important phenomena

for bioreactor development. In this chapter, the growth profile of T.

longibrachiatum in a multi-layer tray bioreactor and a packed-bed bioreactor is

explored. The use of different models to describe the fungal growth based on off-

line measurement (glucosamine) and on-line measurement (respiratory gas) from

bioreactor systems is also discussed. Finally, energy and water balance

information for the packed bed bioreactor is explored and discussed.

Bioreactor studies In view of the promising results with solid-state fermentation in static

lignocellulose beds in petri dishes, attempts were made to scale up this

fermentation in bioreactors. Two systems were investigated; multi-layer tray

bioreactor and packed-bed bioreactor.


147

7.2.1 Multi-layer tray bioreactor studies

There are several types of popular and common bioreactor used in solid state

fermentation, including packed bed, tray, rotating drum and aerated agitated bed.

Tray bioreactors and packed-bed bioreactors could provide static environment if

the microorganism is sensitive to mixing. In tray bioreactors, heat removal is

limited to the tray surfaces due to non-forced aeration. Therefore, bed heights

within trays are restricted to a few centimetres, leading to relatively small

amounts of substrate that can be fermented. This heat problem can be overcome

by forced aeration in the packed-bed bioreactor, but it is still difficult to prevent

an increase in the bed temperature between the air inlet and the air outlet

because of unidirectional air flow (Fanaei and Vaziri, 2009; Mitchell et al., 2010).

A design for minimizing axial temperature gradients in packed-bed bioreactors is

proposed by the work of Lu et al (1998). The strategy to deal with the heat problem

is to divide the bed into layers, creating a “multi-layer packed-bed bioreactor”

concept, which is similar to that represented in Figure 7.1 from the current work.

The headspace in every stacked tray led to improved heat and mass transfer in

comparison with a bioreactor in which the same total amount of substrate was

placed on a single perforated base plate.

Figure 7.1 Multi-layer tray bioreactor


148

Preliminary studies using a three-layer tray bioreactor was implemented in order

to study T. longibrachiatum growth and subsequent hydrolysis. In this experiment,

the mixed substrates (6:4, sugarcane bagasse: soybean hull) for each tray were

prepared as follows: 10g of mixed substrates were moistened with mineral salt

solution to achieve the required initial moisture content of approximately 62 - 63%

(g water per 100 g wet substrate). The substrate was then autoclaved at 121°C for

20 min. After substrates had cooled to room temperature, the substrates were

inoculated with T. longibrachiatum spore suspension and mixed with the substrate

thoroughly to reach a concentration of 1x106 spores/g substrate and final

moisture of 65%. The inoculated substrates were transferred to the three separate

trays of the sterilised bioreactor and aerated from the bottom of the reactor at 0.6

L/min using humidified air.

The characteristics of the multi-layer tray reactor were the same as described in

Chapter 4. At the end of the fermentation, three samples were taken from each

one of the three trays. One of the samples was then used for the further hydrolysis

adding sterilised tap water (pH 6.5) (described in section 6.4) and the other sample

was used for the analysis of the moisture content and glucosamine content as

described in chapter 4.

In solid state fermentation, spatial heterogeneity of the fermenting substrate

always leads to the problem of the heat dissipation. The effect of overheating in

the particulate substrate, especially in the middle section of the bed, is causing by

heat evolved from microorganism metabolism (Saucedo-Castañeda et al., 1990).

The temperature of the fermenting substrate bed is very crucial in SSF. High

temperatures affect spore germination, growth, metabolite production and

sporulation (Gowthaman et al., 1993). A large quantity of metabolic heat evolved

(3200 kcal/kg dry matter), which is directly related to the metabolic activities of

the microorganisms and the depth of the substrate (Lonsane et al., 1985;

Rajagopalan and Modak, 1994).


149

Figure 7.2 depicts the temperature profiles obtained as functions of time for each

tray in the multi-layer tray bioreactor. In all trays, the temperature during the first

15 h was relatively low, consistent with the lag phase of fermentation. During this

period, heat removal by forced aeration generally balances for metabolic heat

evolution. Temperature rise started considerably after 15 h and reached its peak

around 27-28 h. The rise in temperature with time was quite sharp in the middle

tray compared to the others. A temperature of 33.3°C was measured at the middle

tray after 27 h of incubation. This result may be explained by the fact that the heat

removal at the two ends of the multi-stacked tray bioreactor was more efficient

because of the increased surface area available. For the bottom tray, it is the

nearest to the air inlet, which reduces temperature by the moist air. And the top

tray is closest to the gas headspace to removal heat by evaporation cooling effect.

The findings of the current study are consistent with those of other studies and

showed that the middle level of the bioreactor had a much greater temperature

rise compared to the top and bottom levels (Brijwani et al., 2011). In all

fermentations, after the metabolic peak activity, the temperature declined as

growth entered the stationary phase and heat removal by aeration exceeded the

rate of heat production by metabolism. Temperature declined more rapidly after

the peak in beds that had attained a higher temperature during the peak.

Figure 7.2 Temperature profile at the different trays of the multi-tray bioreactor during fermentation

26

27

28

29

30

31

32

33

34

0 20 40 60 80 100 120

Tem

per

atu

re (

°C)

Time (h)

bottom

middle

top


150

Figure 7.3 shows the pattern of Oxygen uptake rate (OUR) and Carbon dioxide

evolution rate (CER) during the same cultivation period of 120 h in the multi-layer

tray bioreactor. It can be observed that OUR and CER rise sharply in the first 20h

of fermentation. CER showed an upward trend during 20 to 50 h and reached a

peak of 0.177 mg/h/g substrate at around 43 h. After this peak, CER dropped

sharply and stayed constant near 0.02 mg/h/g substrate until the end of the

fermentation. However, OUR reached a plateau after 20 h, hit the highest point

(1.35 mg/h/g substrate) at 50 h of incubation and remained stable until 75 h.

Figure 7.3 Respiratory profile of the OUR and CER during solid state fermentation in the multi-layer tray bioreactor

The respiratory quotient (RQ):

RQ = CO2 evolved / O2 consumed Equation 7-1

The RQ can be used to determine which foods are being used as an energy source.

Respiration of carbohydrate gives an RQ of 1.0 during aerobic condition. An RQ

value of more than 1.0 indicates that anaerobic respiration is taking place. In the

respiratory analysis of solid state fermentation, drastic changes can be always

observed for the respiratory quotient which commonly changes with the growth

phase. The maximum respiratory quotient (RQ, i.e., CER/OUR) reached 1.24 at 11

h and then dropped to below 0.2 after 20 h until the end of fermentation (Figure

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

0 20 40 60 80 100 120

CER

( m

g/h

*g s

ub

stra

te)

OU

R (

mg/

h*g

su

bst

rate

)

Time (h)

OUR

CER


151

7.4). The decrease in RQ showed that the oxygen and substrate were utilised by

the microorganism not only for biomass growth and CO2 evolution, but for

metabolite production (Medeiros et al., 2001). The measurement of either carbon

dioxide evolution or oxygen consumption is most powerful when coupled with the

use of a correlation model. The correlation models provide a tool for biomass

estimation since continuous on-line measurements can be achieved. Another

benefit of monitoring effluent air is to ensure optimal substrate oxidation by the

respiratory quotient (Raimbault, 1998). The above mentioned information could

help to establish and incorporate and automated feedback control system for a

solid state fermentation bioreactor.

Figure 7.4 Respiratory quotient (RQ) profile during solid state fermentation in the multi-layer tray bioreactor

The result of the various dry weight loss, final moisture content and glucosamine

concentration with depth after solid state fermentation are listed in Table 7.1. The

dry matter weight loss at the middle tray was significantly different from the top

and bottom trays. Similarly, glucosamine level at the middle tray was also smaller

than the top and bottom trays. However, the final moisture contents of fermented

solids of middle and top trays were more or less the same, and the bottom tray of

the bioreactor gained higher moisture content (73.85%) compared to initial

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 20 40 60 80 100 120

Res

pir

ato

ry q

uo

tien

t (R

Q)

Time (h)


152

moisture content (65%). It can be noticed that the base tray received higher

moisture than the others since it is closest to the air distributor. Humidified air

could provide sufficient moisture to more than compensate the water loss from

the substrate during fermentation. It could be observed from Table 7.1 that dry

weight loss was correlated with biomass concentration. When a high dry weight

loss was obtained, the glucosamine was also high. Several studies have confirmed

that the biomass in solid state fermentation can be estimated by determining the

dry matter weight loss (Terebiznik and Pilosof, 1999; Weng and Sun, 2006).

Table 7.1 Results of analysis featuring differences with different trays after 120 h of fermentation

Dry weight

loss (%) Final moisture

content (%) Glucosamine (g/g

substrate)

Bottom 13.07 73.85 0.012

Middle 8.79 64.46 0.0074

Top 21.03 65.87 0.0105

The bottom and top trays had similar reducing sugar, FAN and Phosphorous yield

after 48 h of further hydrolysis (Table 7.2). The subsequent hydrolysis on

fermented solids from middle tray resulted in a lower reducing sugar, FAN and

phosphorous yield. This was possibly due to the deficiency in deconstruction level

of lignocellulose and low enzyme activities secreted during the solid state

fermentation. Dry matter weight loss, for example, is one of the indexes to show

the condition of microorganism growth and metabolite production in solid state

fermentation (Smits et al., 1996). Hence the results of nutrients solution could be

observed with the same trend in dry weight loss from the different trays of the

bioreactor. The further hydrolysis from the bottom and the top level reached quite

similar yield as reducing sugar and FAN production using petri dish (chapter 5),

226.3 mg/g and 7.7 mg/g, respectively. This means that the multi-layer tray

bioreactor could be a possible choice to scale up for solid state fermentation.


153

Table 7.2 Results of further hydrolysis featuring differences with different trays after 120 h of fermentation

Reducing sugar yield

(mg/g substrate)

FAN yield

(mg/g substrate) Phosphorous yield (mg/g substrate)

Bottom 222.85 11.56 19.19

Middle 115.30 9.28 15.76

Top 216.75 10.24 17.58

7.2.2 Packed-bed bioreactor studies

Preliminary studies of sugar and FAN production in the petri dish fermentations

have illustrated that the ratio of substrates and environmental humidity in

lignocellulose based fermentation feedstock play very important roles in the solid

state fermentation. Hence, the study of sugar and FAN production in a controlled

bioreactor is required. Though various types of bioreactors can be used for solid

state fermentation, the packed-bed reactor was chosen for this work due to its

simplicity and low energy consumption (Lonsane et al., 1985; Mitchell et al., 2006).

Physical and biological characteristics of the fermentation using the packed bed

bioreactor were studied during this work.

7.2.2.1 Profile of fermentation

Packed-bed bioreactors have often been used in SSF for different chemical and

enzyme production. They consist of a column with a perforated base associated

with forced aeration and can be fitted with a jacket for the circulation of water to

control the temperature during fermentation. Forced aeration results in not only

supply of fresh oxygen and moist air but also a removal of carbon dioxide and heat

from the bed (Shojaosadati and Babaeipour, 2002).


154

Like previous experiments in the multi-layer tray bioreactor, preliminary studies

using the packed-bed bioreactor were carried out in order to study T.

longibrachiatum growth and further hydrolysis. In this experiment, the mixed

substrates (6:4, sugarcane bagasse: soybean hull) were prepared as follows: 60g

of mixed substrates were moistened with mineral salt solution to achieve the

required initial moisture content of approximately 62 - 63% (g water per 100 g wet

substrate). The substrate was then autoclaved at 121°C for 20 min.

After substrates had cooled to room temperature, they were inoculated with

T. longibrachiatum spore suspension and mixed with the substrate thoroughly to

reach a concentration of 1x106 spores/g substrate and final moisture of 65%. The

inoculated substrates were transferred to the three trays of the sterilised

bioreactor and aerated from the bottom of the reactor at 1.2 L/min using

humidified air. The schematic diagram of the packed-bed bioreactor system is

shown in Figure 4.7.

The characteristics of the reactor were the same as described in Chapter 4

(sterilisable glass cylinder, 8 cm diameter, 30 cm height, three temperature probes

at 5.5, 13.8, and 21.9 cm from the bottom and two sampling points at 6.4 and 17.4

from the bottom). The bottom plate had a port for air inlet and the top plate had

a port for the exhaust gas. The reactor was placed in an incubator at 30°C (Figure

7.5) instead of using the water jacket. Sterilized thermocouples were used to

record the bed temperature using a multichannel temperature data logger

(Microlab II, Aglicon, UK). The outlet gas was passed through a filter and silica gel

tube to reduce the humidity and impurities of exhaust gases before entering to a

gas analyser to sample on-line CO2 and O2 data.


155

Figure 7.5 Packed-bed reactor placed in the incubator

Figure 7.6 presents the temperature profile measured as a function of bed height

during 120 h of fermentation. The temperature gradient increased along the

bioreactor height, and the middle bed temperature reached 7°C higher than the

inlet air temperature at the maximum gradient after 22 h of fermentation. The

bottom level of the bed reached a peak of 37.2°C, and the top level 37.5°C at 22 h.

After the highest point, temperature declined in all levels of the bed then

remained stable until the end of the fermentation. The low temperature at the

both ends of the bed was presumably because of convective heat dissipation by

evaporative cooling from the top and moist inlet air from the bottom. The result

seems to be consistent with other research which found the similar trend in the

packed-bed bioreactor (Botella, 2007; Brijwani et al., 2011).

High temperatures can be deleterious to the microorganism and, consequently,

decrease enzyme production and lignocellulose deconstruction owing to cell

death. Other studies also reported higher temperature gradient effect in the

different type of fermentation processes (Marcio A. Mazutti et al., 2010). Despite


156

the higher temperature occurring in the outlet gas of the bioreactor, the moisture

content in the fermented solids was kept more or less constant until the end of

the fermentation. The details are discussed in the next section.

Figure 7.6 Temperature profile at different positions in the packed-bed bioreactor during fermentation

As shown in Figure 7.7, during the first 11 h of SSF, the oxygen uptake rate (OUR)

was below 0.2 mg/h/g substrate while the carbon dioxide evolution (CER) was

below 0.1 mg/h/g substrate, which indicates that fungal growth was in the lag

phase period. After 11 h of incubation, there was a simultaneous rapid increase to

the maximum value of OUR at 33 h of 1.3 mg O2/kg-dry substrate per hour and

CER at 26 h of 0.83 mg CO2/kg-dry substrate per hour, respectively. The gradual

decrease of O2 consumption and CO2 evolution after this peak may indicate the

beginning of stationary phase with respect to fungal growth. The similar result

could be found from other researchers, reported as an increase in OUR around 24

h of fermentation and a marked decrease at 72 h (Ikasari and Mitchell, 1998).

Moreover, it is interesting to note that the temperature decreased at the same

period as the CO2 stayed constant, indicating the relationship between fungal

27

29

31

33

35

37

39

41

0 20 40 60 80 100 120

Tem

per

atu

re(°

C)

Time (h)

top

middle

bottom


157

growth and temperature. A similar effect was also observed in the previous

research regarding packed bed bioreactors (Lu et al., 1998).

Figure 7.7 Respiratory profile of the OUR and CER during solid state fermentation in the packed-bed bioreactor

Respiratory quotient (RQ) provides information related to endogenous or

respiratory metabolism of microorganism, substrate oxidation level and culture

conditions (Volke-Sepúlveda et al., 2003). As shown in Figure 7.8, RQ hit the peak

sharply during the first 6 h of incubation (1.25). Afterward, the decline in RQ

corresponded to the beginning of the exponential growth phase of T.

longibrachiatum by consuming substrate and oxygen. However, RQ increased back

to another peak (1.17) after 52 h of fermentation. This behaviour occurred

probably because heat accumulation leading to the oxidative metabolism of the

fungi decreases, consequently decreasing the consumption of oxygen without

altering the CO2 evolution. Overall, the average value of RQ (0.68) during

fermentation is still below the criteria of aerobic respiration of 1.0.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 20 40 60 80 100 120

CER

(mg/

h/g

su

bst

rate

)

OU

R (

mg/

h/g

su

bst

rate

)

Time (h)

OUR CER


158

Figure 7.8 Respiratory quotient (RQ) profile during the solid state fermentation in the packed-bed bioreactor

The whole fermented solids were divided into two levels, lower (11 cm from the

base) and upper (the solids above 11 cm). At the end of the fermentation, three

samples were taken from each one of the two levels. One of the samples was then

used for the further hydrolysis adding sterilised tap water (pH 6.5) (described in

section 6.4) and the other sample was used for the analysis of the moisture

content and glucosamine content as described in chapter 4.

It is apparently clear that the upper level of fermented solids could achieve higher

reducing sugar, FAN and phosphorous yield during further hydrolysis (Table 7.3).

The results match those observed in earlier studies of multi-layer tray bioreactor,

higher nutrients content could be obtained from the bottom portion. It seems

possible that these results are due to the progress of fermentation, shrinkage of

substrate bed occurs and voidage also decreases, further obstructing heat transfer

among the particles. Under these circumstances, temperature and gaseous

concentration gradients build in the SSF. These gradients may lead to channelling

of the air supply and influence productivity in terms of biomass growth and

metabolite production (Gowthaman et al., 1993; Lu et al., 1998). Then, these lower

0

0.2

0.4

0.6

0.8

1

1.2

1.4

0 20 40 60 80 100 120

Res

pir

ato

ry q

uo

tien

t (R

Q)

Time (h)


159

enzyme activities and incompletely decomposed solids will result in lower sugar,

FAN and other nutrient yields.

Table 7.3 Results of further hydrolysis featuring differences with different levels after 120 h of fermentation

Reducing sugar yield

(mg/g substrate)

FAN yield

(mg/g substrate)

Phosphorous yield

(mg/g substrate)

lower 145.21 8.06 13.24

upper 184.50 8.42 15.76

7.2.2.2 Water and energy balance in the packed-bed bioreactor

Many studies claimed that solid state fermentation has lots of advantages over

submerged fermentation for the certain metabolite production, for instance,

higher production yield (product per volume) obtained and lower operation cost

(Khanahmadi et al., 2004). In spite of these examples, the commercial application

of SSF has been limited, mainly due to the problems associated with scale-up. The

main problem associated with scale-up is the removal of heat evolved by the

metabolic activities of the microorganisms (Nagel et al., 2001a, 2001b; Sargantanis

et al., 1993). The deleterious effects of high temperature could influence spore

germination, cell growth and metabolite production (Saucedo-Castaneda et al.,

1992). It thus becomes important to remove heat from the fermenting substrates.

This can be achieved in several ways such as forced aeration, water circulation

through a jacket surrounding the bioreactor, stirring of the solids, evaporation

cooling and water addition. Because of these issues, model development could

provide insights into how the various phenomena within the fermentation process

can influence control system strategies and guide the design and operation of

bioreactors (Mitchell et al., 2003).

The control strategies for a complex bioprocess such as SSF require a

representative mathematical model instead of an empirical model to deal with the


160

nonlinear behaviour. Lekanda and Pérez-Correa (2004) have indicated that in

experimental measurement based control strategies that have significant noise

due to substrate heterogeneity, it is crucial to take into account the transport

phenomena in order to establish accurate process models (Silveira et al., 2014).

The equations describe the change of water content and bed temperature of

packed-bed bioreactor using measurements of input and output data.

Process variables could be classified as (Peña y Lillo et al., 2001):

Measured input variables: F,Hgi, Tgi.

Measured output variables: %CO2, Hgo, Tgo.

Measured state variables: Ms (only at the beginning and end of fermentation),

Tb, Ta, Xw.

Predicted state variables: 𝑇�̂�, �̂�w.

Derived variables: CER, Rw, Qg,∆𝐻𝑟, Qwall, W, Cs.

Measured variables were sampled on-line every 30 min: inlet air flow rate (F), inlet

and outlet air temperatures (Tgi, Tgo); inlet and outlet air relative humidity (Hgi, Hgo);

exhaust air CO2 concentration (%CO2), ambient temperature (Ta), and bed

temperature (Tb). Total dry mass (MS) was measured at the beginning and at the

end of the fermentation. Bed water content (Xw) was measured from the sample

taken manually at the specific time: 0, 24, 96, and 120 h. �̂�𝑏, �̂�w was the predicted

bed temperature and bed water content, respectively. The derived variables: the

CO2 evolution (CER), the metabolic water generation (RW), the heat removed

through the gas (Qg), the heat of reaction (∆𝐻𝑟), the heat loss from the walls of

the reactor (Qwall), the evaporation rate (W) and the total heat capacity of the bed

(Cs).

The main assumptions considered in the development of the model were:

The temperature and concentration within the solid phase are homogenous

due to forced aeration.


161

The physical properties of the fermenting solids are independent of

temperature

The reactor wall is considered high heat capacity and high thermal conductivity.

The gas phase is pseudo-stationary (no accumulation in the gas phase).

7.2.2.2.1 Water balance

The change of water content in the fermenting bed (Xw) depended on the

generation of metabolic water production (Rw) and water evaporation rate (W) as

follows:

𝑑𝑋𝑤

𝑑𝑡= 𝑅𝑤 −𝑊 [g𝐻2𝑜 ∙ ℎ

−1 ∙ g𝑀𝑠−1] Equation 7-2

with

Xw = water content of bed [g𝐻2𝑜 ∙ g𝑀𝑠−1 ]

RW = metabolic water production [g𝐻2𝑜 ∙ ℎ−1 ∙ g𝑀𝑠

−1]

W = water evaporation rate [g𝐻2𝑜 ∙ ℎ−1 ∙ g𝑀𝑠

−1]

Metabolic water

The metabolic water generation is expressed on a dry mass basis by a correlation

between the CO2 evolution and a conversion factor (kw) (Lekanda and Pérez-

Correa, 2004).

𝑅𝑤 =𝑘𝑤∙𝐶𝐸𝑅

𝑀𝑠 [g𝐻2𝑜 ∙ ℎ


In which

CER = carbon dioxide evolution rate [g𝑐𝑜2 ∙ ℎ−1]

M s = tota l dry matter mass [ g ]

Kw = 0.41, conversion factor, theoretical combustion of glucose [g𝐻2𝑜 ∙ g𝑐𝑜2−1]

presents a ratio of water production and CO2 evolution

(Peña y Lillo et al., 2001)


162

Evaporation

The evaporation rate (W), estimated on a dry mass basis, is expressed by:

𝑊 =𝐹(𝑌𝑔𝑜−𝑌𝑔𝑖)

𝑀𝑠 [g𝐻2𝑜 ∙ ℎ


with

F = dry air f low rate [g𝑑𝑟𝑦𝑎𝑖𝑟 ∙ ℎ−1 ]

Ygo = specific humidity of the outlet air [ g𝐻2𝑜 ∙ g𝑑𝑟𝑦𝑎𝑖𝑟−1]

Ygi = specific humidity of the inlet air [ g𝐻2𝑜 ∙ g𝑑𝑟𝑦𝑎𝑖𝑟−1]

where Ygo and Ygi are the specific humidities of outlet and inlet air, respectively.

These are calculated from thermodynamic relationships as follows (Himmelblau

and Riggs, 2012) :

𝑌𝑔𝑜 =18𝑃𝑣𝑜

29(𝑃𝑎𝑡𝑚−𝑃𝑣𝑜)=

18𝐻𝑔𝑜𝑃𝑣𝑜

29(100𝑃𝑎𝑡𝑚−𝐻𝑔𝑜𝑃𝑣𝑜) [g𝐻2𝑜 ∙ g𝑑𝑟𝑦𝑎𝑖𝑟

−1] Equation 7-5

𝑌𝑔𝑖 =18𝑃𝑣𝑖

29(𝑃𝑎𝑡𝑚−𝑃𝑣𝑖)=

18𝐻𝑔𝑖𝑃𝑣𝑖

29(100𝑃𝑎𝑡𝑚−𝐻𝑔𝑖𝑃𝑣𝑖) [g𝐻2𝑜 ∙ g𝑑𝑟𝑦𝑎𝑖𝑟

−1] Equation 7-6

with

Hgo = outlet air relative humidity [%]

Hgi = inlet air relative humidity [%]

Pvo = the vapour pressure of the outlet air [mmHg]

Pvi = the vapour pressure of the inlet air [mmHg]

Patm = 760, atmospheric pressure [mmHg]

The vapour pressures of the outlet and inlet air (Pvo and Pvi) are given by their

Antoine equations (Amenaghawon and Aisien, 2012):

𝑃𝑣𝑜 = 𝑒(18.3−(3816.4/(𝑇𝑔𝑜−46.1))) Equation 7-7

𝑃𝑣𝑖 = 𝑒(18.3−(3816.4/(𝑇𝑔𝑖−46.1))) Equation 7-8

where Tgo and Tgi are the temperature (K) of outlet and inlet air, respectively.


163

Dry mass degradation

Dry matter loss is expressed by a linear relationship between the consumption

coefficient obtained empirically (kg) from Figure 6-20 and the CO2 evolution rate

(CER) (Lekanda and Pérez-Correa, 2004; Nagel et al., 2001b).

𝑑𝑀𝑆

𝑑𝑡= −𝑘𝑔 ∙ 𝐶𝐸𝑅 Equation 7-9

kg = 15.57, conversion factor between the dry matter loss [g𝑀𝑠∙ g𝑐𝑜2

−1]

and the CO2 evolution ( empirical data from equation 7-25)

7.2.2.2.2 Energy balance

The expression of the trend of the average bed temperature was obtained through

the energy balance (Figueroa-Montero et al., 2011; Lekanda and Pérez-Correa,

2004; Peña y Lillo et al., 2001).

𝑑𝑇𝑏

𝑑𝑡∙ 𝐶𝑠 ∙ 𝑘𝑒𝑥𝑝 = (𝑄𝐹𝑊 + ∆𝐻𝑟 − 𝑄𝑔 + QO2 − QCO2 − 𝑄𝑤𝑎𝑙𝑙) [W]

Equation 7-10

with

Tb = average temperature of the bed (port 1, 2 and 3) [°C]

Cs = the total heat capacity of the bed [J ∙ °C−1]

𝑘𝑒𝑥𝑝 = experimental parameter accounting for bed heterogeneity

QFW = the energy contribution of added water [J ∙ h−1]

∆𝐻𝑟 = t h e h eat o f r ea ct ion [J ∙ h−1]

Qg = the heat removed by the gas [J ∙ h−1]

Qwall = heat loss from the reactor wall [J ∙ h−1]


164

Heat capacity of the control volume

The total heat capacity of the system (Cs) includes the solid and liquid portion of

cultivation medium, as well as the glass wall of the bioreactor.

𝐶𝑠 = 𝑀𝑠 ∙ 𝐶𝑝𝑠+ 𝑀𝑠 ∙ 𝑋𝑤 ∙ 𝐶𝑝𝑤+ 𝑀𝑔𝑙𝑎𝑠𝑠 ∙ 𝐶𝑝𝑔𝑙𝑎𝑠𝑠 [J ∙ °C−1]

Equation 7-11

with

M s = t o t a l d r y m a s s [ g ]

𝐶𝑝𝑠= 1.5, solid media specific heat [J ∙ g−1 ∙ °C−1]

Xw = water content of bed [g𝐻2𝑜 ∙ g𝑀𝑠−1 ]

𝐶𝑝𝑤= 4.187, water specific heat [J ∙ g𝐻2𝑜−1 ∙ °C−1]

Mglass =4460, the glass mass of the bioreactor [g]

𝐶𝑝𝑔𝑙𝑎𝑠𝑠 = 0.753, glass specific heat [J ∙ g−1 ∙ °C−1]

Contribution of added water

The energy contribution of the added water to the system through the inlet

moist air.

𝑄𝐹𝑊 = 𝐹 ∙ 𝑌𝑔𝑜 ∙ 𝐶𝑝𝑤 ∙ (𝑇𝑖 − 𝑇𝑏) [W] Equation 7-12

with

F = dry air f low rate [g𝑑𝑟𝑦𝑎𝑖𝑟 ∙ ℎ−1 ]

Ygo = specific humidity of the outlet air [ g𝐻2𝑜 ∙ g𝑑𝑟𝑦𝑎𝑖𝑟−1]

𝐶𝑝𝑤= 4.187, water specific heat [J ∙ g𝐻2𝑜−1 ∙ °C−1]

T i = temperature of inlet gas [°C]

Tb = average temperature of the bed (port 1, 2 and 3) [°C]

The heat of reaction

Metabolic heat generation could be related to the CO2 evolution. Several

researchers have demonstrated that the heat of reaction could be derived from

the CO2 evolution rate (CER) under aerobic conditions of fermentation (Nagel et

al., 2001a, 2001b; Peña y Lillo et al., 2001).


165

∆𝐻𝑟 = −𝑌𝑞 𝑐𝑜2⁄ ∙ 𝐶𝐸𝑅 [W] Equation 7-13

with

𝑌𝑞 𝑐𝑜2⁄ = 7023305.08, heat of reaction for aerobic metabolism [J ∙ g𝑐𝑜2−1]

(Lekanda and Pérez-Correa, 2004)

CER = carbon dioxide evolution rate [g𝑐𝑜2 ∙ ℎ−1]

Heat removed by the gas

The heat removed by the gas (Qg) is made up of evaporation loss (Qevap) and

forced convection between the bed and the airflow (Qconv).

Qg = Qevap+ Qconv [W] Equation 7-14

Qevap = 𝐹 ∙ 𝜆𝑤(𝑌𝑔𝑜 − 𝑌𝑔𝑖) [W] Equation 7-15

where 𝜆𝑤 is 2432, the latent heat of evaporation [J ∙ g𝐻2𝑜−1].

Qconv = 𝐹 ∙ [𝐶𝑝𝑎(𝑇𝑔𝑜 − 𝑇𝑔𝑖) + 𝐶𝑝𝑣(𝑌𝑔𝑜𝑇𝑔𝑜 − 𝑌𝑔𝑖𝑇𝑔𝑖)

−𝐶𝑝𝑣𝑇𝑏(𝑇𝑔𝑜 − 𝑇𝑔𝑖)] [W]

Equation 7-16

with

𝐶𝑝𝑎= 1.004, dry air specific heat [J ∙ g−1 ∙ °C−1]

𝐶𝑝𝑣= 1.867, water vapour specific heat at 30°C [J ∙ g−1 ∙ °C−1]

Sensible heats associated with respiratory gases (QO2 andQCO2) would also be

considered.

QO2 = 𝑂𝑈𝑅 ∙ 𝐶𝑝,𝑂2(𝑇𝑔𝑖 − 𝑇𝑏) [W] Equation 7-17

QCO2 = 𝐶𝐸𝑅 ∙ 𝐶𝑝,𝐶𝑂2(𝑇𝑔𝑜 − 𝑇𝑏) [W] Equation 7-18

with

𝐶𝑝,𝑂2= 0.8432, oxygen specific heat [J ∙ g𝑜2−1 ∙ °C−1]

𝐶𝑝,𝐶𝑂2= 0.9174, carbon dioxide specific heat [J ∙ g𝑐𝑜2−1 ∙ °C−1]


166

Heat loss through the walls of the bioreactor

The amount of heat that is removed through the wall is calculated from:

𝑄𝑤𝑎𝑙𝑙 =𝑘𝑚 ∙ 𝐴 ∙ (𝑇𝑏 − 𝑇𝑤𝑎𝑙𝑙) [W] Equation 7-19

with

km = 1.4, heat transfer coefficient of the wall [W ∙ (𝑚2 ∙ °C)−1]

A= heat transfer area of the reactor [m2]

Twall = average temperature of the wall [°C]

7.2.2.2.3 Model validation

Samples were taken during fermentation instead of measuring the whole

fermenting bed content in the end. Validation of the developed model was

investigated by comparing its estimations with the results of fermentation carried

out in the packed-bed bioreactor in this study (Figure 7.9 to 7.11). The predictions

of the model agree well with the measured values except some visible deviations

as fermentation time progressed. In all cases the model slightly under-predicts

total dry weight change, the water content of the bed and the average

temperature of the bed. Simulation of the dry matter loss fits the real data with

an acceptable discrepancy (Figure 7.9). The deviation found could be explained by

the variation of the conversion factor (kg) between the dry matter consumption

and the CO2 evolution. And this parameter used in this study was obtained from

the experiments in Circular tray fermenters instead of the packed-bed bioreactor.

Over the whole period of the fermentation process, the water balance model

showed a good fit to measured data of water content in the bed (Figure 7.10).

Some variance was observed between predicted and experimental values, but

they were not very remarkable. This deviation could be the value of kw used in our

study, using a simple relationship between glucose and CO2 instead of complex

carbohydrate and CO2. Predicted temperature of bed followed the trend of

qualitatively experimental results (Figure 7.11). This is apparently as a


167

consequence of an under-estimation of the heat release rate, which in turn may

result from the heat capacity of the control volume and value of 𝑌𝑞 𝑐𝑜2⁄ in

metabolic heat production. Heat capacity of control volume could be influenced

by the discrepancy between theoretical and experimental dry weight loss, while

𝑌𝑞 𝑐𝑜2⁄ could vary with different conditions and needs to be calibrated (Peña y Lillo

et al., 2001). Also, the measured data shown was the average value of

temperature in different positions of the packed-bed bioreactor and could be a

factor to cause the deviation of model accuracy. Alternatively, a different stage of

fermentation should be modelled and additional terms should be incorporated to

fit data well, however, this might make the model overcomplicated.

Figure 7.9 Comparison between predicted (line) and experimental (symbol) dry weight change in the packed-bed bioreactor during the course of fermentation

10

20

30

40

50

60

70

80

0 20 40 60 80 100 120

Dry

mat

ter

mas

s (g

)

Time (h)


168

Figure 7.10 Comparison between predicted (line) and experimental (symbol) average water content of bed during the course of fermentation

Figure 7.11 Comparison between predicted (dotted line) and experimental (solid line) average bed temperature during the course of fermentation

0.5

1

1.5

2

2.5

3

0 20 40 60 80 100 120

Wat

er c

on

ten

t o

f th

e b

ed (

g/g

)

Time (h)

25

27

29

31

33

35

37

39

41

0 20 40 60 80 100 120

Tem

per

atu

re( ℃

)

Time (hr)


169

Growth kinetics in SSF systems Knowledge of the growth during fungal fermentation is crucial in sequential

bioprocessing including solid state fermentation and further hydrolysis. In the case

study of this project, though, the biomass is not the final product. Also, it is

generally considered difficult to measure fungal growth in SSF due to the

adherence of the fungus on the heterogeneous and insoluble solid particles.

Because the fungal biomass cannot be separated easily from the fermenting

substrate, and because of the intimate interactions between microorganism and

the solids, it is not possible to obtain a homogeneous sample of biomass during

the fermentation. Kinetic models provide the basic knowledge needed in the

design and optimisation of fermentation processes. To accomplish a solid state

fermentation process based on lignocellulosic biorefinery, fungal cell

measurement throughout the fermentation is highly desirable. Since the use of a

direct measurement method such as the dry weight method (including the cells

and the solid particles) is impractical, the use of an indirect measurement could

be an alternative (Gretty K. Villena, 2011; Koutinas et al., 2003). Indirect

estimation methods can be mainly categorised into two groups as follows:

1. Off-line indirect measurement: The estimation of biomass components

could be determined either within the cell suspended in the cytoplasm,

such as DNA and RNA, or constituent materials of the cell walls, such as

ergosterol, glucosamine or chitin. Unfortunately, the content of all of these

components within the biomass cell can vary with culture conditions and

with the age of the mycelium. And most of components such as DNA, RNA,

glucosamine and chitin, could be measured in both, the fungal cells and the

substrate (Koutinas et al., 2003; Mitchell et al., 2006).

2. On-line indirect measurement: This method relies on detecting metabolic

activities of the biomass. Of these, CO2 evolution rate (CER) and O2

consumption rate (OUR) are most important. Production of CO2 and O2

consumption take place due to fungal growth and maintenance. Thus,


170

automatic on-line analysis of exit gases from SSF allows real time

information on the physiological state of the cultures to be correlated with

cell concentration (Koutinas et al., 2003; Machado et al., 2004).

In the following sections a model for Trichoderma longibrachiatum growth in SSF

is adapted to provide comprehensive information on the kinetics using, firstly, off-

line measurements of glucosamine, and secondly,. metabolic data from

respiratory analysis to determine carbon dioxide evolution rate (CER).

During experiments, both glucosamine and CER were monitored. The CO2

evolution and O2 consumption by cultures were measured continually using a gas

analyser. At specific times (24, 72, 96, 120, 168 h) the bioreactors were also taken

off to analyse biomass concentration, dry weight loss and substrate composition.

Cell concentration was obtained by the glucosamine method and total

carbohydrate of the substrates was determined by the Anthrone method. Each

analysis was conducted in duplicate. A schematic diagram of the bioreactor system

is shown in Figure 4.4.

7.3.1 Glucosamine production

As mentioned above, the time course of solid state fermentation by T.

longibrachiatum was monitored along with the dry matter weight loss of solids,

the total carbohydrate of substrates and the glucosamine concentration. At the

beginning of the fermentation (0-24 h), only 3.86% of the dry matter weight was

lost. During 24-120 h of incubation, rapid increase of dry matter weight loss to

20.71% occurred, attaining 26.76% after 168 h fermentation (Figure 7.12).

Generally speaking, the more carbohydrate is consumed, the more the

microorganism grows, and the more the dry matter weight loss (Weng and Sun,

2006). Only a little total carbohydrate was utilised during the first 72 h

fermentation, 4.74% of total carbohydrate loss. Thereafter (72-120 h), large

amounts (15.5%) of total carbohydrate consumption occurred. The total

carbohydrate utilisation reached 19.91% by the end of fermentation. Figure 7.12


171

shows a short lag phase of biomass growth during the first 24h, followed by

exponential growth until 120 h, where the stationary growth phase began.

Figure 7.12 Time course of solid state fermentation by T. longibrachiatum, using a circular tray bioreactor system

Based on the data collected for glucosamine concentration during the 7-day solid

state fermentation, a series of mathematical models were developed to describe

the correlation between total carbohydrate consumption and carbon dioxide

evolution. Linear, exponential, logistic, and deceleration models have been

reported in various SSF systems. Among these, the logistic equation is most

commonly used due to its relatively simple form and good fit to around 75% of the

literature growth profiles obtained in SSF (Viccini et al., 2001). The model

describes growth in microbial population depending on maximum biomass density,

specific growth rate, and time as described in equation 7-20.

𝑑𝑋

𝑑𝑡= 𝜇𝑚 (1 −

𝑋

𝑋𝑚)𝑋 Equation 7-20

where μm is the maximum specific growth rate (h-1) and Xm is the maximal

biomass concentration reached when dX/dt = 0 for X>0. This equation does not

consider the biomass death.

0

10

20

30

40

50

60

70

80

90

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

0.011

0.012

0 24 48 72 96 120 144 168

Tota

l car

bo

hyd

rate

(%

, w/w

)D

ry m

atte

r w

eigh

t lo

ss (

%, w

/w)

Glu

cosa

min

e (g

/g s

ub

stra

te)

Time (h)

Glucosamine

Dry matter weight loss

Total carbohydrate


172

Integration used for performing model fitting and parameter estimation in this

study, is presented by equation 7-21.

𝑋 =𝑋𝑚

1+((𝑋𝑚𝑋0

)−1)𝑒−𝜇𝑚𝑡

Equation 7-21

whereX0 is the initial biomass concentration at t=0.

In general, the carbon source, oxygen consumption rates, and CO2 evolution rates

can be described with the linear growth model of Pirt (Gelmi et al., 2002; Lareo et

al., 2006; Ooijkaas et al., 2000).

−𝑑𝑆

𝑑𝑡=

1

𝑌𝑋 𝑆⁄

𝑑𝑋

𝑑𝑡+𝑚𝑆𝑋 Equation 7-22

where S is the carbohydrate fraction (g/g substrate), Yx/s is the yield of the biomass

(g biomass/g total carbohydrate) and ms is the specific maintenance rate (g of total

carbohydrate/g of biomass·h). The second term of the equation, maintenance,

refers to the energy required for cell’s survival or preservation of a certain state,

which are not directly related to cell division (Bailey, 1986; Lareo et al., 2006).

Using the boundary condition at t0=0, X=X0, S=S0, Equation 7-22 can be integrated

to giving the following Equation 7-23 (Zhu et al., 2014).

𝑆(𝑡) = 𝑆0 − (1

𝑌𝑋 𝑆⁄) ∙ (𝑋(𝑡) − 𝑋0) − 𝑚𝑠 ∙

𝑋𝑚

𝜇𝑚∙ ln(1 −

𝑋0∙(1−𝑒𝜇𝑚∙𝑡)

𝑋𝑚)

Equation 7-23

The model has been successfully used to simulate growth in the reactor in the

experiment. Assuming a constant ratio of glucosamine to cell mass (i.e. X can be

represented directly by the measured glucosamine) and using MATLAB

(MathWorks), the differential equations described above were solved and fitted

to the data using nonlinear least squares. Figure 7.13 depicts the glucosamine level

(biomass concentration) obtained during circular tray bioreactor fermentations

and the estimated growth derived using the Equation 7-21. This shows a very good

fit between measurements and the logistic model (R2=0.99) as follows:


173

𝐺(𝑋) =0.011

1+1.971𝑒−0.022𝑡 Equation 7-24

Where G(X) is the glucosamine concentration

Assuming a constant value of glucosamine to cell mass ratio of 0.12 (Raimbault,

1998), equation 7-24 becomes, in terms of actual biomass:

𝑋 =0.088

1+1.95𝑒−0.023𝑡 Equation 7-25

Figure 7.13 Experimental (symbols) and predicted (line) for glucosamine

(biomass concentration) during 7 days solid state fermentation

As shown in Figure 7-13, the logistic equation predicted the fungal biomass fairly

accurately, with a short lag phase during the first 24 h, an exponential growth

phase that last until 120 h of incubation and a deceleration growth phase.

Maximum specific growth rates ( μm ) depend on the particular SSF system,

substrate type and microorganism used. The μm and Xm for T. longibrachiatum

cultivated in the Circular tray bioreactor system here were calculated to be 0.023

h-1 and 0.088 g/g substrate, respectively (Equation 7-24).

A wide range of maximum specific growth rates has been reported, from

0.027 h-1 (Santos et al., 2003) to 0.05 h-1 (Membrillo et al., 2011) using sugarcane

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0.009

0.01

0.011

0 20 40 60 80 100 120 140 160 180

Glu

cosa

min

e (g

/g s

ub

stra

te)

Time (h)


174

bagasse as substrate for solid state fermentation. This indicates that the

utilisations of recalcitrant lignocellulose like sugarcane bagasse as a carbon source

is slower than other agricultural wastes, for example, wheat bran, where 0.15 h-1

was obtained for Trichoderma reesei (Smits et al., 1998).

Figure 7.14 shows the relation between the carbohydrate content and biomass

generation. It can be seen that the carbohydrate content is inversely proportional

to biomass production. The carbohydrate content of substrate was consumed

slowly while biomass generation was only 0.0009 g/g substrate during the initial

24 h. A plateau phase occurred when fungal biomass entered the log phase

(0.0009 to 0.0051 g/g substrate) from 24-96 h. Considering the heterogeneous

nature of the lignocellulosic feedstock, T. longibrachiatum may have to shift its

substrate utilisation between lignin and carbohydrate (cellulose and hemicellulose)

after depleting a fraction of the easily-accessible cellulose and hemicellulose

during early stage (Shi et al., 2012). Thereafter the total carbohydrate content

declined distinctly from 0.57 to 0.48 g/g substrate with gradual increase of

biomass concentration (0.0051 to 0.0065 g/g substrate).

Figure 7.14 Correlation between total carbohydrate loss and biomass generation (glucosamine) during 7 days solid state fermentation

0.4

0.45

0.5

0.55

0.6

0.65

0 0.001 0.002 0.003 0.004 0.005 0.006 0.007

Tota

l car

bo

hyd

rate

(g/

g su

bst

rate

)

Glucosamine (g/g substrate)


175

Total carbohydrate (cellulose and hemicellulose) served as the main carbon and

energy sources for supporting T. longibrachiatum growth. The estimated

parameters (μm and Xm) by nonlinear regression of equation 7-21 were used into

equation 7-23 to calculate the yield of the biomass (Yx/s) and the specific

maintenance rate (ms). Results presented in Figure 7.15 showed that the model

proposed from equation 7-23 in this research could predict carbohydrate

consumption well (R2=0.93). The estimated coefficient for total carbohydrate used

for cell growth (Yx/s) reached 0.19 (g biomass/g total carbohydrate) while the

maintenance coefficient (ms) is 0.12 (g total carbohydrate/g biomass*h). The value

of Yx/s was higher than those reported by Zhu et al. (2014) at 0.16 (g biomass/g

total carbohydrate) estimated for the solid-state fermentation using rice straw.

The reduction of carbohydrate content occurred slowly during the initial stage of

fermentation. The reason might be attributed to complex carbohydrate polymer

(cellulose and hemicellulose) and lignin interconnected by a great variety of

linkages which need to be broken down by a series of biochemical enzyme

reactions. Therefore, it takes time to secrete enzymes from fungi during the

beginning of fermentation (Crestini et al., 1998). The total carbohydrate trajectory

in Figure 7.15 agrees with that found by Padma and Singhal (2010).

Figure 7.15 Experimental (Symbols) and predicted (line) total carbohydrate consumption during 7 days solid state fermentation

0.002

0.102

0.202

0.302

0.402

0.502

0.602

0.702

0 20 40 60 80 100 120 140 160 180

Tota

l car

bo

hyd

rate

(g/

g su

bst

rate

)

Time (h)


176

Base on measured data, a straight line was found between dry matter weight loss

and biomass concentration during fermentation. The linear fit was X (glucosamine

concentration, g/g substrate) = 0.0046 + 0.0253D (dry weight loss, g/g substrate),

and R2 for this equation is 0.89. This result suggested that fungal growth seems to

be dry matter weight loss related. Moreover, dry matter weight loss increased

with the decline of total carbohydrate content during solid state fermentation.

Total carbohydrate loss was positively correlated with dry matter weight loss

during solid state fermentation (Figure 7.16). These results show that the dry

weight may indicate the change of the component of fermentation solids such as

carbohydrate content and provide a tool in order to validate the result of the

estimation method. At the end of fermentation, the total carbohydrate loss

reached to 19.92% and the dry matter weight loss is 26.76%. This means that

6.84% of dry weight loss in total could be contributed by nitrogen and lignin

consumption after 168 h cultivation.

Figure 7.16 Correlation between total carbohydrate loss and dry matter weight loss during 7 days solid state fermentation

A correlation existed between the dry matter weight loss and the cumulative CO2

evolution during 7 days of fermentation as shown in Figure 7.17. The mean

relationship can be described by Equation 7-26.

y = 0.7015xR² = 0.9465

0

5

10

15

20

25

0 5 10 15 20 25 30

Tota

l car

bo

hyd

rate

loss

(%

)

Dry weight loss (%)


177

∆𝐶𝑂2 = 0.0642 ∙ ∆𝐷𝑊+0.0008 (R2=0.89) Equation 7-26

where ∆𝐶𝑂2 is the amount of CO2 evolved (g/g initial dry substrate), and ∆𝐷𝑊 is

the amount of dry matter weight loss (g/g initial dry substrate). Several studies

showed a similar trajectory for Trichoderma species growth in the solid state

fermentation (Flodman and Noureddini, 2013; Smits et al., 1998, 1996). And the

all correlation coefficients of determination (R2) for the fit were from 0.87 to 0.89.

According to previous studies and the above experiment results, the

measurement of CO2 evolution is a potential way to model the fungal growth

during fermentation.

Figure 7.17 Correlation between dry matter weight loss and cumulative CO2 evolution

7.3.2 The respiratory gas model

Another alternative method to estimate biomass growth during solid state

fermentation is the use of CO2 evolution and O2 consumption. On-line analysis of

CO2 and O2 in the exhaust gases allows real time information of the physiological

state of the microorganisms to be collected. On-line derived variables such as CO2

y = 0.0642x + 0.0008R² = 0.897

0

0.002

0.004

0.006

0.008

0.01

0.012

0.014

0.016

0.018

0.02

0 0.05 0.1 0.15 0.2 0.25 0.3

CO

2 e

volu

tio

n (

g/g

sub

stra

te)

Dry matter weight loss (g/g substrate)


178

evolution rate (CER), O2 uptake rate (OUR) and the respiratory (RQ) could be used

to estimate the specific biomass growth rate on-line and assess the bioreactor

performance (Machado et al., 2004; Mitchell et al., 2006; Ooijkaas et al., 1998;

Rodriguez-Leon et al., 2008).

Figure 7.18a presents the time course of carbon dioxide evolution rate (CER) and

cumulative CO2 during fermentation using the circular tray bioreactors. A lag

phase in respiration was observed within the first 16 h of fermentation. The CO2

evolution was too low to be measured in this period. This might be due to an

adaptation of the microorganisms to the medium and to spore germination (de

Carvalho et al., 2006). After 16 h of fermentation, the CER increased dramatically

when biomass generation took place. The highest value of CER was detected at 27

h (0.27 mg/h·g). After this point, the exponential growth phase is suddenly

stopped when the oxygen uptake rate (OUR) dropped slightly from 1.9 to 1.5

mg/g·h and the highest temperature was reached (32.4°C). This means that fungal

cells were influenced by the temperature and oxygen level effect in the bioreactor.

The constant value of CER could be explained by the fact that the fungal cells

maintain a constant metabolic activity to utilise the remaining substrates.

Comparing the biomass growth and the accumulated CO2 evolution curve in Figure

7.18, it can be observed the similar trajectory from lag phase, exponential growth

phase and stationary phase during the fermentation. The profile of total CO2

evolution increased, corresponding to the beginning of the exponential growth

phase. After 113 h of cultivation, the beginning of the stationary phase as the total

CO2 evolution became flatter. The correlation coefficients (R2=0.99) confirmed a

close relationship between the total amount of CO2 evolved and cell growth during

solid state fermentation. This result indicated that the metabolic data can be used

to estimate indirectly the fungal growth through respiratory gas.

With the respirometric data, the maximum specific growth rate (μm) may also be

determined from the slope of the natural logarithm of the accumulated gases (CO2

and O2) (Gelmi et al., 2000; Machado et al., 2004). However, it is difficult to choose


179

the exact time interval of exponential growth phase, leading to a variation of the

maximum specific growth rate estimated easily.

Figure 7.18 Profile for T. longibrachiatum growth during 7days solid state fermentation (a) Accumulated CO2 and CO2 evolution rate (b) biomass growth (glucosamine)

The system simultaneously analyses both CO2 and O2 concentrations. In this

project, the choice of CO2 concentration, instead of O2, was due to the higher

sensitivity of the near infrared sensor. Considering that a CO2 evolution rates

which indicates biomass formation kinetics by combining growth associated and

0

0.05

0.1

0.15

0.2

0.25

0.3

0

2

4

6

8

10

12

14

16

18

0 20 40 60 80 100 120 140 160 180

CER

(mg/

h*g

)

Cu

mu

lati

ve C

O2

(mg/

g)

Time (h)(a)

cumulative CO2

CER

4

5

6

7

8

9

10

11

0 20 40 60 80 100 120 140 160 180

Glu

cosa

min

e (m

g/g

sub

stra

te)

Time (h)(b)


180

non-growth associated kinetics, thus, the following equation can written for CO2

evolution:

𝐶𝐸𝑅 =𝑑𝐶𝑂2

𝑑𝑡=

1

𝑌𝑋 𝐶𝑂2⁄

𝑑𝑋

𝑑𝑡+𝑚𝐶𝑂2𝑋 Equation 7-27

where CER is the carbon dioxide evolution rate (g of CO2/g of substrate·h), 𝑌𝑋 𝐶𝑂2⁄ is

the yield coefficient of cells with respect to CO2 (g of biomass/g of CO2) and 𝑚𝐶𝑂2is

the maintenance coefficient (g of CO2/g of biomass·h).

Equation 7-27 allows the estimation of the quantity of biomass that exists at a

particular time of the fermentation from the data of evolved CO2 by finite

determination of this evolution at particular time intervals. Equation 7-28 can be

integrated to obtain:

∫𝑑𝐶𝑂2

𝑑𝑡𝑑𝑡

𝑡=𝑛

𝑡=0= ∫

1

𝑌𝑋 𝐶𝑂2⁄

𝑡=𝑛

𝑡=0𝑑𝑡 +∫ 𝑚𝐶𝑂2𝑋𝑑𝑡

𝑡=𝑛

𝑡=0 Equation 7-28

Term ∫𝑑𝐶𝑂2

𝑑𝑡

𝑡=𝑛

𝑡=0 in equation 7-28 indicates that evolved CO2 in time t=n can be

evaluated from the relation between the carbon dioxide evolution (CER) and time.

Applying the Trapeze rule to the numerical integration of each term in the

expression, the following equation was obtained:

𝑋𝑛=(𝑌𝑋 𝐶𝑂2⁄ ∆𝑡(

1

2((

𝑑𝐶𝑂2𝑑𝑡

)𝑡=0

+(𝑑𝐶𝑂2𝑑𝑡

)𝑡=𝑛

)+∑ (𝑑𝐶𝑂2𝑑𝑡

)𝑡=𝑖

𝑖=𝑛−1𝑖=1 )+(1−

𝑎

2)𝑋0−𝑎∑ 𝑋𝑖

𝑖=𝑛−1𝑖=1 )

(1−𝑎

2)

where 𝑎 = 𝑚𝐶𝑂2𝑌𝑋 𝐶𝑂2⁄ ∆𝑡 Equation 7-29

To determine the carbon dioxide evolution ( 𝑌𝑋 𝐶𝑂2⁄ ) and biomass maintenance

coefficient (𝑚𝐶𝑂2), equation 7-27 can be rearranged to give:

𝐶𝐸𝑅

𝑋=

1

𝑋

𝑑𝑋

𝑑𝑡

1

𝑌𝑋 𝐶𝑂2⁄+𝑚𝐶𝑂2 Equation 7-30

The 𝑌𝑋 𝐶𝑂2⁄ and 𝑚𝐶𝑂2 can be estimated by linear regression through the plot of Y-

axis (𝐶𝐸𝑅

𝑋) versus X-axis (

1

𝑋

𝑑𝑋

𝑑𝑡). From the above calculation, bioprocess parameters


181

such as yield coefficient based on the carbon dioxide evolution (𝑌𝑋 𝐶𝑂2⁄ ), 0.071 g

biomass/g CO2, and biomass maintenance coefficient (𝑚𝐶𝑂2), 0.0092 g of CO2/g of

biomass·h, were determined. Figure 7.19 shows the estimated biomass and

measured one during the fermentation. It can be seen that the simulation could

fit the fungal growth during the first 120 h of fermentation. Towards the end of

fermentation the model estimated a bit higher growth than that measured.

Several studies have identified that accumulated CO2 evolution increases with

time. Therefore, a possible explanation for this might be that towards the end of

fermentation, the CO2 is more related to cell maintenance than to cell growth. In

general, therefore, it seems that fungal growth can be reliably assessed by

evaluating the CO2 evolved during the fermentation.

Figure 7.19 Profile of T. longibrachiatum growth, as glucosamine concentration (symbols) and simulation (line) during 7days solid state fermentation using circular tray bioreactor

The same approach used for the circular tray experiments was adopted to obtain

growth profile during fermentation in the multi-layer tray bioreactor and 1.5 L

packed bed reactor for the production of the microbial feedstock. Figure 7.20 to

7.21 show the estimated biomass kinetics based on the CO2 evolution for multi-

layer bioreactor and packed-bed bioreactor, respectively. The data fit the model

0.02

0.025

0.03

0.035

0.04

0.045

0.05

0.055

0.06

0 20 40 60 80 100 120 140 160 180

bio

mas

s (g

)

Time (h)


182

satisfactorily in both bioreactor systems. The linear regression using equation 7-

30 is applied to calculate carbon dioxide evolution (𝑌𝑋 𝐶𝑂2⁄ ), 0.8 g biomass/g CO2,

and biomass maintenance coefficient (𝑚𝐶𝑂2), 0.001 g of CO2/g of biomass·h, in

multi-layer bioreactor system. And in packed-bed bioreactor system, carbon

dioxide evolution (𝑌𝑋 𝐶𝑂2⁄ ), 0.19 g biomass/g CO2, and biomass maintenance

coefficient ( 𝑚𝐶𝑂2 ), 0.001 g of CO2/g of biomass·h, were determined.

The 𝑌𝑋 𝐶𝑂2⁄ and 𝑚𝐶𝑂2 values obtained from three different fermenters using

equation 7-30 were lower than those reported by Lareo et al. (2006) for C.

minitans (𝑌𝑋 𝐶𝑂2⁄ = 0.98, 𝑚𝐶𝑂2=0.0058). However, the biomass profile obtained

describes the experimental biomass production reasonably well (Figure 7.19 to

7.21).

Figure 7.20 Profile of T. longibrachiatum growth, as glucosamine concentration (symbols) and simulation (line) during 5 days solid state fermentation using multi-layer tray bioreactor

0

0.05

0.1

0.15

0.2

0.25

0.3

0 20 40 60 80 100 120

Bio

mas

s (g

)

Time (h)


183

Figure 7.21 Profile of T. longibrachiatum growth, as glucosamine concentration (symbols) and simulation (line) during 5 days solid state fermentation using packed-bed bioreactor

The experimental cell growth profile in the packed-bed bioreactor was strongly

correlated to the prediction of the model compared to that obtained in the multi-

layer bioreactor. There are several possible explanations for this result. One might

be the lack of adequate sampling data from the multi-layer bioreactor. Due to the

design of multi-layer bioreactor, it is impractical to take samples during the

fermentation, leading the error of estimated yield coefficient and maintenance

coefficient. Another reason for this is that the metabolic information (CO2 and O2)

of multi-layer tray bioreactor is the sum amount from biomass growth in three

different layers. Therefore, varied fungal growth profile could not be easy to

describe by the model using the total respiratory data.

Indirect methods to measure fungal growth like CO2 evolution may be useful in

solid-state fermentation by applying mathematical model. However, the

estimation of biomass through CO2 requires 𝑌𝑋 𝐶𝑂2⁄ and 𝑚𝐶𝑂2, which is strongly

dependent on specific growing conditions and fermentation systems. Therefore,

individual investigations for different fermentation conditions are necessary to

identify case-specific kinetic parameters.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0 20 40 60 80 100 120

Bio

mas

s (g

)

Time (h)


184

Characteristics of fermented solids during SSF Understanding changes in the structure of lignocellulose during solid state

fermentation could provide more valuable insights into the nature of this complex

bioprocessing. Microscopic observation, both optical and scanning electron

microscopy (SEM), can be a useful way to see changes in the substrates and fungal

growth in solid state fermentation. Moreover, thermogravimetric (TG) and

differential thermogravimetric (DTG) analysis of fermented substrates can also

provide information about the thermal decomposition profiles of lignocellulosic

components.

7.4.1 Microscopic observation

A fungal growth typically begins with the mixing of a spore inoculum with

substrate particles. Each particle initially has some spores attached to it. The

spores take around 10 hours to germinate while the substrate bed is under the

optimal conditions (water activity, temperature and pH etc.). As shown in Figure

7.22a, once each spore germinates, a germ tube extends away from the spore and

branches to give daughter hyphae, which extend and further branch to give an

expanding micro-colony. The original extension of the germ tube is fuelled by

reserves in the spores, but the continued expansion and growth depends on

nutrients from the substrate. Hyphae from near micro-colonies meet one another,

which cause interactions (Mitchell et al., 2006). During the growth period some

hyphae will also extend above the surface (aerial hyphae), and others will have

penetrated into the substrate (Figure 7.22b).


185

Figure 7.22 Change in biomass distribution during a static SSF process with a fungus. (a) Growth to cover the particle surface during the early stages of the fermentation, shown with an overhead view of the particle surface. (b) Development of aerial and penetrative hyphae during the late phase of the fermentation, shown with a side view of a cut through two particles. (adapted from (Mitchell et al., 2006)

Sampling is difficult throughout SSF experiments and it is not easy to take

homogeneous samples from the bioreactor during fermentation. Therefore, to

observe fully the fungal morphology in the bioreactor is almost impossible during

solid state fermentation., In the experiments reported here, when the bioreactor

was disassembled at the end of the fermentation, it was observed that fungal

growth was almost uniform throughout the solids and formed a “cake” as shown

in Figure 7.23a. In Figure 7-23b it can be clearly seen that aerial hyphae from

different micro-colonies meet and intermesh as suggested by Mitchell et al.,

(2006). Since the moist air supplies sufficient water to avoid drying by evaporation

during fermentation, the whole cake seems to be colonised and there is not the

suboptimal growth at the top of the substrate that is often associated with dry

systems. The experiment showed that lignocellulosic waste could be fermented

successfully in a bioreactor without mixing when moist air is supplied.


186

Figure 7.23 Fermented solids of T. longibrachiatum after 5 days fermentation using a multi-tray bioreactor with moist air aeration (a) fungal cake (b) aerial hyphae intermeshed above the surface

The untreated sugarcane bagasse exhibited rigid and highly ordered fibrils in the

SEM image (Figure 7.24). The ability of the fungus (Trichoderma longibrachiatum)

to penetrate into the fibres can be appreciated in the micrographs taken using the

SEM (Figure 7.25 and 7.26) which show high growth in the sugarcane bagasse. The

spores were distributed over the surface of the fibres, and the hyphae clearly form

a microscopic network (mycelium) inside the substrate, through which the

nutrients are absorbed. After solid-state fermentation, the fibres can be seen to

be partly degraded and separated by mycelium, creating a larger accessible

0.5 cm


187

surface area to facilitate subsequent enzymatic hydrolysis. Unfortunately, it was

not possible to remove the fungi in order to take pictures of samples before and

after fungal pretreatment, so these effects could not be compared.

Figure 7.24 SEM image of a sugarcane bagasse structure, showing rigid and highly ordered fibrils


188

Figure 7.25 SEM image of mixed sugarcane bagasse and soybean hull after 120 h of fermentation covered by hyphae of Trichoderma longibrachiatum


189

Figure 7.26 SEM image of mixed sugarcane bagasse and soybean hull after 120 h of fermentation covered by spores of Trichoderma longibrachiatum

7.4.2 Thermogravimetric analysis

The thermogravimetric (TG) and derivative thermogravimetric (DTG) analysis of

the raw materials (sugarcane bagasse and soybean hull) and fungal pretreated

materials are shown in Figure 7.27. In general, the thermal decomposition of these

fibres consists of four stages: stage 1 – moisture evaporation; stage 2 –

decomposition of lignocellulosic components of hemicelluloses; stage 3 –

decomposition of cellulose and lastly; stage 4 – decomposition of lignin (Ishak et

al., 2012; Yang et al., 2007). Stage 1 ranges from 45 to 150°C. With temperature


190

increase, hemicellulose starts its decomposition (stage 2) easily, between 220 and

315°C. Cellulose pyrolysis (stage 3) is focused at a higher temperature range (315–

400°C) with the maximum weight loss rate. Lignin is the most difficult to

decompose (stage 4). It decomposes slowly in the range from 300°C to 500°C

(Zhang et al., 2014).

Since all samples were dried prior to the TGA, the weight loss before stage one

was ignored. From the TGA distributions, it can be seen that the difference among

the materials is insignificant. With further examination upon the DTG curves, the

distribution of the raw materials is characterized by a multiple-peak distribution.

The first and the second peaks, developing at 236 and 365°C, respectively,

represent the thermal degradations of hemicellulose and cellulose in the

substrates. Once the materials undergo fungi pretreatment, the first peak

disappears, suggesting that hemicellulose has been removed to a great extent. The

DTG curves also revealed that the impact of the pretreatment on cellulose is

slightly varied in the second peak. According to the thermogravimetric analysis of

samples, the pyrolysis profile of fungi treated sugarcane bagasse and soybean hull

shifted to lower temperatures and with weaker major peaks. This result indicates

that the fungal pretreatment improved the efficiency of pyrolysis by reducing the

demand for a high thermal degradation temperature.


191

Figure 7.27 TG and DTG analysis of (a) untreated substrates (b) treated substrates

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0

10

20

30

40

50

60

70

80

90

100

75 175 275 375 475 575

DTG

(-d

m/d

t)

We

igh

t (%

)

Temperature (℃ )

TGA

DTG

Cellulose

0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

0

10

20

30

40

50

60

70

80

90

100

75 175 275 375 475 575

DTG

(-d

m/d

t)

We

igh

t (%

)

Temperature ( ℃)

TGA

DTG

Cellulose

(b)

Hemicellulose

(a)


192

Summary The object of the study reported in this chapter was the development of a

consolidated bioprocess using solid-state bioreactors to produce a generic

microbial feedstock. Experiments were conducted using two different types of

bioreactor (multi-layer tray bioreactor and packed-bed bioreactor). Results from

experiments confirmed that the upper layer of packed-bed bioreactors and

bottom tray of multi-layer tray bioreactor can have better sugar and FAN

production through subsequent hydrolysis. For the packed-bed bioreactor, an

equation based on material and energy balances was proposed for predicting and

simulating average bed temperature and average water content of the bed. A

microbial growth model based on metabolic data has been proposed for the

estimation of fungal growth in the solid-state fermentation. Yield of fungal cells

based on CO2 evolution and maintenance coefficients were estimated from

fermentation. This method can help to estimate and monitor cell growth during

fermentation from the on-line indirect measurement.

Several methods were also used to analysis the chemical and physical change of

substrates during fermentation. The SEM images showed the hyphae granule

penetration and the variation of substrate structure. Thermogravimetric analysis

also demonstrated that significant hemicellulose degradation occurred during the

solid-state fermentation.

Chapter 8 Evaluation of the generic feedstock

193

CHAPTER 8

Evaluation of the generic feedstock

Introduction The feasibility of a generic feedstock obtained from sugarcane bagasse and

soybean hull by the process developed in this project was evaluated. The

application of these media as the sole nutrient source for the production of

ethanol has been carried out. Based on the results reported in chapter 5 and in

this chapter, a mass balance for ethanol production from raw materials and a

preliminary economic assessment were conducted and are presented in section

8.3 and 8.4.

Ethanol fermentation Many lignocellulosic materials have been tested for developing large-scale ethanol

production during the past two decades. These processes provide several

desirable features: a secure source of energy supply, limited conflict with land use

for food production, and reduction of fossil fuel demand (Margeot et al., 2009). In

order to test the potential of the environment-friendly process developed in this

project, a number of experiments were carried out using the generic feedstock

produced by sequential bioprocessing for ethanol production.

Yeast strain, Saccharomyces cerevisiae was cultivated on slant of YDX medium

(yeast extract: 5 g/L, glucose: 5 g/L and xylose: 10 g/L) for pentose adaption. To

prepare inoculum the yeast were culture in 100 mL of YDX medium in 250 mL

flasks at 30°C on a 160 rpm shaker for 30 h. After being washed twice with sterile

distilled water to remove nutrient residuals, yeast cells harvested from 50 mL of

broth by centrifugation at 4000 rpm for 5 min were concentrated in to 4 mL. The

100 mL of hydrolysate were inoculated with 4 mL of a suspension of S. cerevisiae

giving a concentration of around 106 cell/mL. Ethanol fermentations were carried


194

out anaerobically at 32°C, 180 rpm in 250 mL Duran bottles fitted with “swan-neck”

caps to allow release of fermentation gases. As YD media, fermentations of

solutions containing 15 g/L glucose and 10 g/L yeast extract were performed. After

the fermentation, samples were taken for sugar, FAN and ethanol analysis and

results are shown in Table 8.1 and 8.2. The theoretical ethanol production could

be calculated from the reducing sugar, assuming that the theoretical ethanol yield

for fermentation is 0.511 g per g of reducing sugars (Wongwatanapaiboon et al.,

2012). The percentage of theoretical maximum ethanol yield was calculated by

equation 8-1.

%𝑜𝑓𝑡ℎ𝑒𝑜𝑟𝑒𝑡𝑖𝑐𝑎𝑙maximum𝑒𝑡ℎ𝑎𝑛𝑜𝑙𝑦𝑖𝑒𝑙𝑑

=𝑔𝑜𝑓𝑒𝑡ℎ𝑎𝑛𝑜𝑙𝑜𝑏𝑡𝑎𝑖𝑛𝑒𝑑

𝑔𝑜𝑓𝑟𝑒𝑑𝑢𝑐𝑖𝑛𝑔𝑠𝑢𝑔𝑎𝑟𝑠𝑐𝑜𝑛𝑠𝑢𝑚𝑒𝑑×0.511× 100

Equation 8-1

The hydrolysate resulting from the hydrolysis and autolysis of fermented

substrates for mixed substrates (sugarcane bagasse and soybean hull, 6:4) was

used as the feedstock for ethanol fermentation. The composition of the

hydrolysates and that of the YD media, as well as the corresponding ethanol

concentration, are presented in Table 8.1. The initial fermentation broth contains

2.53 g/L of glucose, 7.42 g/L of xylose and 1.01 g/L of arabinose. Hemicelluloses

contain most of the pentose sugars (xylose, arabinose mannose, galactose and

rhamnose), and occasionally small amounts of hexose sugar (glucose) as well. In

contrast, cellulose contains only anhydrous glucose. Through the sequential

bioprocess in this project. The abundant sugars come from the hemicellulose

instead of cellulose. Large amounts of hemicellulose sugars, making up over half

of the total reducing sugars, were produced after hydrolysis. After an anaerobic

incubation time of 30 h, the ethanol concentration of 3.14 g/L was obtained. Table

8.2 shows that ethanol yield based on consumed total sugars was 0.31 g/g (61.4%

of theoretical ethanol maximum), as 69% of total sugars, 62.6% of pentose sugar

and 100% of glucose were consumed respectively. It is not surprising that all

glucose was exhausted and about 37% of the pentose remained in the broth. The


195

naturally occurring Saccharomyces yeasts that are currently used by industry lack

the ability to utilise xylose because of the absence of genes required for

assimilation of these molecules (Hector et al., 2011). The yeast does not have the

ability of fermenting pentose sugars efficiently even though it was cultured and

adapted in high xylose content medium.

Table 8.1 Ethanol fermentations of S. cerevisiae on different media

Initial composition final composition

medium total reducing sugar (g/L)

glucose (g/L)

FAN (mg/L)

IP (g/L)

total reducing sugar (g/L)

glucose (g/L)

FAN (mg/L)

IP (g/L)

Ethanol (g/L)

hydrolysate 14.51 2.53 424.7 0.81 4.48 0.00 142.17 0.39 3.14

YD mediaa 15 15 492.2 0.84 1.95 1.95 231.4 0.28 6.02 a YD media used as 15 g/L glucose and 10 g/L yeast extract.

Table 8.2 Ethanol yield and media consumption of fermentation using S. cerevisiae

consumption ratio % Production

medium total reducing sugar (%)

glucose (%) FAN (%)

IP (%) total reducing sugars to

ethanol yield (g/g)

Hydrolysate 69.13 100.00 66.52 51.74 0.31

YD media 87 87 52.99 66.67 0.46

Sugarcane bagasse has been considered to be a feasible raw material for ethanol

production due its relative low lignin content and large amount of by-product from

sugarcane processing industry. (Carrasco et al., 2010) presented that ethanol

fermentation using SO2-catalyzed steam pretreated bagasse could reach ethanol

yields with respect to consumed sugars up to 0.48 g/g (Table 8-3) and 0.16 g/g dry

sugarcane bagasse. Many studies have demonstrated that chemical pretreatment

could facilitate the yield of sugar and production and then increase the ethanol

yield. Nevertheless, the generation of inhibitory compounds, waste effluent

disposal, and detoxification procedure during these processes hinder their


196

subsequent utilisation, increase production cost and create the environment

impact for ethanol production (López-Abelairas et al., 2013). In contrast, the

pretreatment of these materials with microorganisms provided an attractive

environmentally friendly alternative to traditional treatments.

Shi et al. (2009) reported that enzymatic hydrolysis and fermentation of fungi-

treated cotton stalk using P. chrysosporium. However, the ethanol yield only

ranged between 0.004 and 0.027 g/g dry cotton stalk after 48 h of fermentation.

In another biological pretreatment process, static submerged fermentation of

corn fibre using P. chrysosporium was found to result in the ethanol yield of

0.017g/g dry corn fibre after 144h of simultaneous saccharification and

fermentation (Shrestha et al., 2008). As shown in Table 8.3, the ethanol yield in

our study (0.06 g/g sugarcane bagasse) was similar or higher to that achieved in

fermentation using fungi-pretreated raw lignocellulosic materials, which is

consistent with the reports on ethanol yield, below 0.1 g/g dry lignocellulose, using

biological pretreatment process (Bak et al., 2009; López-Abelairas et al., 2013; Shi

et al., 2009; Shrestha et al., 2008). Unlike glucose-rich hydrolysate from chemical

pretreatment process, higher pentose content (mainly xylose) in the hydrolysate

was produced through biological pretreatment process. This could be due to the

fact that large amounts of hemicellulose remaining after fungi fermentation,

further enzyme hydrolysis could release large amount of hemicellulose sugars into

the hydrolysate. However, the native S. cerevisiae lacks the ability to utilise xylose

efficiently to ethanol, leading to lower ethanol yield compared with chemical

pretreatment-based strategies. The alternative yeast or bacterial species that can

co-ferment pentose will further enhance ethanol yield.

The highest sugarcane bagasse to ethanol conversion yield (0.04 g/g) achieved in

this study may seem lower than chemical pretreated process achieved yields (0.16

g/g) but it should be taken into consideration that it also contains the

carbohydrates consumed for enzymes production and recalcitrant lignocellulose

deconstruction. In most conventional cellulosic bioethanol production, enzymes


197

are purchased from specialised manufacturers that use fungal (Trichoderma)

species or bacterial fermentation on media of agricultural product. Such

fermentation are similar to the fungal fermentation applied in our process that

provided crude enzyme complex rather than individual enzyme.

Moreover, on-site enzyme production can help bioethanol producers

avoid downstream processing, adding stabilisation agents, warehousing

and shipping of huge quantities of enzymes to eliminate between 30 and 50%

of the total enzyme production cost (Brooks and Tchelet, 2014).


198

Table 8.3 Ethanol yields for different lignocellulosic materials pretreatment

substrate Pretreatment Enzyme microorganism Ethanol Ethanol yield reference

Concentration (g/L)

volumetric productivity (g/L/h)

g/g consumed total sugars

g/g untreated substrate

sugarcane bagasse

steam explosion

Commercial enzymes

recombinant S. cerevisiae

11.5 0.48 0.35 0.16 Martin et al., 2002

sugarcane bagasse

acid hydrolysis with H2SO4

Commercial enzymes

P.tannophilus DWO6

19 0.53 0.34 0.1 Cheng et al., 2008

sugarcane bagasse

Ionic liquid (NMMO)

Commercial enzymes

Zymomonas mobilis

14.5 0.3 0.44a 0.15 Kuo et al., 2009

sugarcane bagasse

chemical pretreatment

Commercial enzymes

S. cerevisiae 6.5 0.14 0.33 -- Hernández-Salas et al., 2009

sugarcane bagasse

ball milling Commercial enzymes

recombinant S. cerevisiae

17.8 0.37 0.42 -- da Silva et al., 2010

sugarcane bagasse

SO2-steam pretreatment

Commercial enzymes

S. cerevisiae TMB3400

4.5 0.23 0.48 -- Carrasco et al., 2010

sugarcane bagasse

alkaine pretreatment

Commercial enzymes

K. marxianus 24.6 0.34 0.4 -- Lin et al., 2013

corn fibre SO2

pretreatment with fungi treatment

In-situ enzymes

S. cerevisiae -- -- -- 0.017 Shrestha et al., 2008

wheat straw

biological pretreatment

Commercial enzymes

S. cerevisiae 16 0.27 0.48 0.097 López-Abelairas et al., 2013

Rice straw biological pretreatment

Commercial enzymes

S. cerevisiae D5A

9.5 0.4 0.32 0.09 Bak et al., 2009

cotton stalk


Commercial enzymes

S. cerevisiae -- -- 0.21 0.027 Shi et al., 2009

sugarcane bagasse, wheat bran

steam explosion with fungi treatment

In-situ enzymes

S. cerevisiae CAT-1

42.9 0.59 0.42 -- Pirota et al., 2014

sugarcane bagasse, soybean hull


In-situ enzymes

S. cerevisiae 3.14 0.105 0.31 0.041 This study

a the conversion of glucose to ethanol


199

Material balance for Ethanol production using generic microbial feedstock

Figure 8.1 presents the material balance of SSF-based biorefinery strategy

proposed in this study from lignocellulose to ethanol. The mass balance for

bioconversion was calculated based on results shown in Chapter 7, whereas the

results obtained from section 8.2 were used for calculation of the mass balance

for ethanol fermentation. The overall production yield achieved in this process

was 0.041 g ethanol per gram initial mixed lignocellulosic substrates. Although this

is still much lower than the theoretical maximum of 0.35 g/g (based on the total

carbohydrate content in the mixed substrate used in this study), it is distinctly

higher than the yield achieved via biological treatment-based strategy using

lignocellulose (Table 8.3).

SSF(T. longibrachiatum)

Hydrolysis & fungal

autolysis19.76 L

Mixed substrate

1.0 kg (d.b.)

Water1.8 L

Hydrolysate19.76 L

(14.5 g/L total reducing sugar)(0.42 g/L FAN)

(0.81 g/L IP)

Ethanol fermentation

19.76 L

Water17.96 L

1000 g dry mass309.58 g Cellulose

301.42 g Hemicellulose611 g total carbohydrate

791.4 g dry mass182.02 g Cellulose

205.21 g Hemicellulose387.23 g total carbohydrate 40.21 g glucose

151.29 g pentose 191.5 g total reducing sugar

Ethanol 41 g

Solid residues648.9 g

KH2PO4

5.4 g

MgSO4

0.9 g

CaCl2‧2H2O0.9 g

Figure 8.1 Material balance for the SSF-based process showing the lignocellulose

(600 g of sugarcane bagasse and 400 g of soybean hull) to ethanol conversion yield.

Calculations were based on the average ethanol yield (0.31 g/g total reducing

sugar consumed) for fermentation using hydrolysate. The ratio of SSF solids to

water was 4% (w/w) in the simultaneous hydrolysis and fungal autolysis to

produce a suitable generic microbial feedstock for ethanol fermentation.

The Solid material remained after solid-state fermentation (pretreatment) was

791.4g, which indicates that around 21% of the raw materials was consumed.

Large amounts of hexosan fraction (41.2%) were utilised, whereas, pentosane

fraction (68%) were remained in the pretreated solids. In order to obtain a


200

nutrient-rich microbial feedstocks, the pretreated solids was subjected to in-situ

enzyme hydrolysis and fungal autolysis. Sugar yields were calculated based on the

pretreated stream using the following equations. The equations are simplified by

stating the ratio of the molecular weights of glucose to cellulose (180/162) as

(1/0.9) and xylose to hemicellulose (150/132) as (1/0.88).

𝐺𝑙𝑢𝑐𝑜𝑠𝑒𝑦𝑖𝑒𝑙𝑑(%) =𝑔𝑜𝑓𝑔𝑙𝑢𝑐𝑜𝑠𝑒𝑜𝑏𝑡𝑎𝑖𝑛𝑒𝑑

(𝑔𝑜𝑓𝑐𝑒𝑙𝑙𝑢𝑙𝑜𝑠𝑒𝑖𝑛𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒𝑠/0.9)× 100 Equation 8-2

𝑋𝑦𝑙𝑜𝑠𝑒𝑦𝑖𝑒𝑙𝑑(%) =𝑔𝑜𝑓𝑥𝑦𝑙𝑜𝑠𝑒𝑜𝑏𝑡𝑎𝑖𝑛𝑒𝑑

(𝑔𝑜𝑓ℎ𝑒𝑚𝑖𝑐𝑒𝑙𝑙𝑢𝑙𝑜𝑠𝑒𝑖𝑛𝑠𝑢𝑏𝑠𝑡𝑟𝑎𝑡𝑒𝑠/0.88)× 100 Equation 8-3

After the hydrolysis of fermented solids, the xylose yields reached 64.9%. In

comparison, only 19.8% glucose yield was achieved in the hydrolysis of fermented

residues. However, this hydrolysate provides not only sugars but also nutrients

(amino acids, peptide, nucleotides, phosphorous and vitamins) as compared to

current industrial practices for pure sugar production through different strategies

from lignocellulosic materials. As mentioned in section 8.2, the native S. cerevisiae

is not capable of utilising pentose sugars efficiently, leading to about 59 g of

pentose remaining after 30 h of ethanol fermentation. A variety of other

microorganisms such as Pichia stipites, P. tannophilus and C. shehatae are able to

utilise pentose sugars by a reduction/oxidation pathway reaction under different

cultivation conditions from lignocellulose hydrolysates (Kuhad et al., 2011). Lin et

al., (2012) reported that ethanol yield from rice straw hydrolysate (23 g/L xylose

and 2.3 g/L glucose) was approximately 0.44 g per gram of consumed total sugars.

It could be possible to increase ethanol yield using the alternative yeast to achieve

higher conversion from raw lignocellulosic materials in this study.


201

Summary The feasible use of generic feedstock derived from sugarcane bagasse and

soybean hull as an alternative to commercial carbon and nitrogen sources was

explored and presented in this chapter. The ethanol yield of S. cerevisiae in

lignocellulose-derived media was compared to that in standard YD media. It was

found that YD media helped cells to produce higher ethanol yield (46%) than

lignocellulose-derived media (31%) from sugars during the 30 h of fermentation.

However, the ethanol yield from lignocellulose was higher than other researches

using biological pretreatment process. A mass balance for the ethanol production

from lignocellulose was also demonstrated in this chapter.

Chapter 9 Conclusions and recommendations

202

CHAPTER 9

Conclusions and recommendations

Conclusions In this project, sugarcane bagasse and soybean hulls were used as raw materials

for the production of a generic microbial feedstock. The results from a series of

fermentation experiments, measurement of metabolic activities, microbial

kinetics and process simulation yielded useful information regarding

bioconversion of complex lignocellulose. The knowledge obtained from these

experiments was used in the design of a novel consolidated bioprocess using

lignocellulosic materials.

A study of the growth of fungi (Trichoderma longibrachiatum) in solid media and

subsequent in-situ hydrolysis for nutrients production, reducing sugars and free

amino nitrogen (FAN), was presented in Chapter 5. It was concluded that

sugarcane bagasse is suitable for the growth of T. longibrachiatum. However, the

selection of washing procedure, particle size and C/N ratio for the solid state

fermentation using sugarcane bagasse is necessary. The washing effect of

sugarcane bagasse has been investigated during this project. Studies with washing

procedure show that non-washing process retains sucrose content (14%, w/w) in

sugarcane bagasse and improves fungal growth, sugar and FAN production. The

trials also showed 1.4-0.85 mm of sugarcane bagasse as a suitable range of particle

size to facilitate the nutrients production yield.

The effect of C/N ratios (between 107.2 and 25.2) on the fungal growth was

studied. In this experiment, fixed amount of sugarcane bagasse and peptone from

(0% to 15%, w/w) were added. The results suggested that a C/N ratio of 32.7 is the

optimal condition for Sugar and FAN production. A one-way analysis of variance

was applied and confirmed to this result. In order to implement biorefinery

concept, soybean hull was chosen to replace nitrogen-rich commercial products


203

as a nitrogen supplement. It was also found that the optimal proportion of mixed

substrates was 60% (w/w) sugarcane bagasse with 40% (w/w) soybean hulls.

Increasing the soybean hulls proportion beyond this was found to affect sugar

yield negatively due to inappropriate C/N ratio. During the evaporation studies,

the significance of environmental humidity cannot be ignored on solid state

fermentation using petri dish system. Therefore, high environmental humidity of

incubator was necessary when the solid-state fermentation was carried out. A high

sugars yield, 226.3 mg/g of substrate, can be achieved after the 5 days of solid

state fermentation and subsequent hydrolysis.

In Chapter 6 the effect of solid ratio, temperature, pH and microbial inhibitor on

subsequent hydrolysis was also investigated. Direct comparison of the nutrients

production measured in various solid ratios (from 2% to 12%, w/w) of hydrolysis.

The results demonstrated that the high sugar yield in 2% (w/w) was 0.33 (g/g of

pretreated materials) and high FAN yield in 4% (w/w) was 0.006 (g/g of pretreated

materials). However, the total nutrients production yield was lower in high solid

ratio (12%, w/w) hydrolysis for sugar and FAN, 0.11 (g/g of pretreated materials)

and 0.0015 (g/g of pretreated materials) respectively. The same optimal

temperature (50°C) was found for reducing sugar and FAN production. And the

optimum pH value for reducing sugar and FAN production were obtained at 6 and

7, respectively. However, the effect of pH was insignificant between 6 and 7 during

FAN production. In the trials of microbial inhibitor effect, results showed that the

addition of microbial inhibitor did not affect the hydrolysis significantly in the

oxygen-limited environment. In order to predict the production of nutrients, an

equation developed in this project was used and tested. A satisfactory fit was

obtained on reducing sugar, FAN and Inorganic phosphorous (IP), with regression

coefficients of 0.95, 0.96 and 0.99, respectively.

In Chapter 7, three different types of bioreactor; multi-layer tray type, packed-bed

type and circular tray type were investigated for microbial feedstock production

and kinetic study. The multi-layer tray bioreactor experiments demonstrated that

the bottom layer can provide a best subsequent hydrolysis yield on reducing sugar,


204

FAN and IP, 222.85 mg/g, 11.56 mg/g and 19.19 mg/g, respectively. However, it

should be noted that the subsequent hydrolysis from the top layer was also very

good (reducing sugar = 216.75 mg/g, FAN = 10.24 mg/g and IP = 17.58 mg/g). The

fermented solids from middle layer, on the other hand, could only provide lower

hydrolysis yield. This suggested that the sufficient fungal growth could provide

subsequent hydrolysis performance (Table 7-1). Fermentation experiments also

were carried out in packed-bed bioreactor, the hydrolysis trial performed better

in terms of sugar, FAN and IP yield from the upper proportion of bed, 184.5 mg/g,

8.42 mg/g and 15.76 mg/g, respectively compared to the lower one. During the

solid-state fermentation, on-line measurements (carbon dioxide evolution) have

shown the potential to estimate fungal growth by comparing the experimental

results using glucosamine method. The small difference between prediction and

experimental data provides confidence in this approach.

Evaluation of generic microbial feedstock from solid-state fermentation and

subsequent hydrolysis was performed in Chapter 8. The results confirmed that

native Saccharomyces cerevisiae can utilise the generic feedstock for ethanol

production. The highest ethanol yield achieved was 0.31 g per g of total reducing

sugar (61.4% of theoretical yield) using lignocellulose-based hydrolysate,

compared to 0.46 of standard medium (15 g/L glucose and 10 g/L yeast extract).

Based on these above findings, the operating conditions for every unit operation

involved in this process are summarised in Table 9.1.


205

Table 9.1 Operating parameters for operation in the production of ethanol from sugarcane bagasse and soybean hulls

Unit operation Parameter Value

Solid-state fermentation Fermentation time 120 h Temperature 30°C Initial moisture content 65% Inoculum size 1x106 spores/g substrate Aeration rate 0.6 L/min

Hydrolysis of fermented solids Reaction time 48 h

Reaction temperature 50°C Agitation speed 160 rpm Initial solid loading 4% (w/w) pH 6.5 (sterilised tap water)

Ethanol fermentation Fermentation time 30 h Temperature 32°C Agitation speed 180 rpm pH 6

A complete mass balance of the bioconversion process from sugarcane bagasse

and soybean hulls to a generic microbial feedstock was described. Chapter 8 also

presented preliminary economic studies of a generic microbial feedstock

production.

The results presented here show that microbial feedstock production through

sequential bioprocess from lignocellulose is possible, however further

investigation is necessary for industrial application of this environmental friendly

process. One of the most challenge is to improve the lignin degradation rather

than consume cellulose and hemicellulose during solid-state fermentation. Non-

cellulose utilizing white rot species could be used to degrade lignin prior to the

cultivation of cellulase-producing microorganisms. If the obstruction (lignin) could

be removed, then cellulase-producing fungi could secrete enzymes directly to

shorten the fermentation period and minimise loss of cellulose and hemicellulose.

In this bioprocess, residual lignin after hydrolysis could be used as raw materials to

produce electricity and heat through a combined heat and power (CHP) system.

Besides, the lignin can be further processed and modified to produce adhesives due


206

to the phenolic structures and compositions. To fully utilise every by-products and

resources to produce a spectrum of products is the goal of biorefinery development.

Recommendations for further work There are several potential parts of the study presented in this thesis which it

would be interesting to explore further in future studies. Specific

recommendations are listed below.

Improvement of fungal pretreatment process

The hydrolysis yield after the simultaneous fungal pretreatment and enzyme

production process has been demonstrated but was lower compared to other

chemical pretreatment process. The low productivity was probably due to lignin

levels in the substrates being too high, hindering in-situ enzyme attack effectively.

It is for this reason that further study of the lignin degradation effect during fungal

pretreatment is strongly recommended.

Enhancement of hydrolysis of fermented solids

The further in-situ hydrolysis is important and crucial stages in a generic microbial

feedstock, and knowledge of enzyme hydrolysis and fungal autolysis is essential.

As a result of the combined effects of the degree of deconstruction of substrate,

in-situ enzyme adsorption, mixing of high solid concentration and environmental

stress on fungi, sugar and FAN yield cannot be increased efficiently. Therefore,

further study of each of these factor is desirable.

Solid-state bioreactor

Although satisfactory nutrient concentrations were obtained through this

consolidated bioprocessing, the ineffective heat removal during fermentation

causes increased bed temperature beyond the optimum. Therefore, future studies


207

should focus on solid-state bioreactor design and temperature control of solid bed

to increase fungal growth, leading to high hydrolysis performance.

On-line measurement of solid-state fermentation

The technique of on-line measurement in solid-state fermentation is clearly

limited due to difficulty of cell counting. Although an attempt has been made in

this thesis by respiratory methods to study fungal growth, the environmental

factors could affect measurement such as bioreactor type, air circulation and

anaerobic condition. Therefore, a more detailed and accurate method is required.

Study of the possibility of using the generic feedstock for other

chemicals production

The feasibility of the generic microbial feedstock derived from sugarcane bagasse

and soybean hulls was demonstrated in this project. This sustainable process can

be used as a model to develop other chemicals such as Polyhydroxybutyrate (PHB),

lactic acid and butanol. Also, the value-added products can be produced from the

lignin remaining in the solid waste generated in this process to reduce production

cost.

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208

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