development of food grade colloidal system for …
TRANSCRIPT
DEVELOPMENT OF FOOD GRADE COLLOIDAL SYSTEM
FOR DELIVERY OF VITAMIN A AND D
TAHIR MEHMOOD
07-arid-163
Department of Food Technology
Faculty of Crop and Food Sciences
Pir Mehr Ali Shah
Arid Agriculture University Rawalpindi
Pakistan
2018
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DEVELOPMENT OF FOOD GRADE COLLOIDAL SYSTEM
FOR DELIVERY OF VITAMIN A AND D
by
TAHIR MEHMOOD
(07-arid-163)
A thesis submitted in the partial fulfillment of
the requirements for the degree of
Doctor of Philosophy
in
Food Technology
Department of Food Technology
Faculty of Crop and Food Sciences
Pir Mehr Ali Shah
Arid Agriculture University Rawalpindi,
Pakistan
2018
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DEDICATION
This Humble Effort is Solely Dedicated
to the Uplifted hands
of my
Parents, brother and sister
Who urged me to work hard
and to achieve my goals.
The Hands Ever Praying for Me
These Hands may never fall down
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CONTENTS
Page
List of Tables xi
List of Figures xv
Acknowledgments xix
ABSTRACT xxi
1 INTRODUCTION 1
2 REVIEW OF LITERATURE 5
2.1 FORMULATIONS OF NANOEMULSIONS 5
2.1.1 Oil Phase 5
2.1.2 Aqueous Phase 6
2.1.3 Stabilizers 6
2.1.3.1 Emulsifier 7
2.1.3.2 Texture modifiers 9
2.2 NANOEMULSIONS PREPARATION 10
2.2.1 High-Pressure Homogenizer 11
2.2.2 Ultrasonic Homogenizer 12
2.3 DESIGNING OF FUNCTIONAL NANOEMULSIONS 14
2.3.1 Composition of Particle 14
2.3.2 Concentration of Particle 15
2.3.3 Particle Dimensions 16
2.3.4 Interfacial Properties 18
2.3.5 The Physical State of Particle 19
2.4 DROPLET BREAKUP IN NANOEMULSIONS 19
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2.5 ADVANTAGES OF NANOEMULSIONS 21
2.5.1 Antimicrobial Activity 21
2.5.2 Lipophilic Components Encapsulation 22
2.5.3 Control Delivery and Increased Bioavailability of Lipophilic
Components
23
2.5.4 Improved Stability of Nanoemulsions 24
2.5.5 Modification of Texture 25
2.6 BIOLOGICAL FATE OF NANOEMULSIONS 26
2.7 APPLICATION OF THE NANOEMULSIONS IN FOOD
PRODUCTS
28
2.8 POTENTIAL TOXICITY OF NANOEMULSIONS 30
2.8.1 Bioactive Compounds with Increased Bioavailability which
are Toxic at Higher Level
31
2.8.2 Direct Absorption of Smaller Droplets 31
2.8.3 Disturbance in Normal Gastrointestinal Functions 32
2.8.4 Effect of Composition 33
3 MATERIALS AND METHODS 35
3.1 COLLECTION OF MATERIALS 35
3.2 CHARACTERIZATION OF COMPONENTS 35
3.3 NANOEMULSIONS PREPARATION 35
3.4 PARTICLE SIZE ANALYSIS 36
3.5 OPTIMIZATION OF PREPARATION CONDITIONS 36
3.5.1 p-Anisidine Value 40
3.5.2 Beta Carotene Retention 41
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3.6 OPTIMIZATION OF PREPARATION CONDITIONS FOR
VITAMIN D NANOEMULSIONS
42
3.6.1 Droplet Growth Ratio (DGR) 45
3.6.2 Vitamin D2 Retention 46
3.7 CHARACTERIZATION OF NANOEMULSIONS 46
3.7.1 Storage Stability 46
3.7.2 Turbidity Measurement 47
3.8 FACTORS AFFECTING SELECTIVE PARAMETERS 47
3.8.1 Effect of pH 47
3.8.2 Effect of Ionic Strength Variation 47
3.8.3 Thermal Stability 47
3.8.4 Physical Stability 48
3.9 ANIMAL STUDIES 48
3.9.1 In Vivo Toxicity for Vitamin A 48
3.9.2 In Vivo Toxicity for Vitamin D 49
3.9.3 Nuclear Abnormalities Analysis 50
3.9.4 Comet Assay 50
3.9.4.1 Procedure for staining 51
3.9.4.2 Slides Scoring 52
3.10 DEVELOPMENT OF BETA CAROTENE AND VITAMIN
D FORTIFIED BEVERAGES
52
3.10.1 Viscosity 52
3.10.2 °Brix 53
3.10.3 Sensory Evaluation 53
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3.11 STATISTICAL ANALYSIS 53
4 RESULTS AND DISCUSSION 54
4.1 CHARACTERIZATION OF COMPONENTS 54
4.2 OPTIMIZATION OF NANOEMULSIONS 56
4.2.1 Fitting the Model 56
4.2.2 Effect of Independent Variables on Response Variables 58
4.2.2.1 Droplet size 58
4.2.2.2 p-Anisidine value 63
4.2.2.3 β-Carotene retention 64
4.2.3 Optimization of Independent Variables 65
4.2.4 Verification of RSM Model 66
4.3 OPTIMIZATION OF VITAMIN D NANOEMULSIONS 66
4.3.1 Fitting the Model 66
4.3.2 Effects of Independent Variables on Responses 70
4.3.2.1 Droplet size 70
4.3.2.2 Droplet growth ratio 72
4.3.2.3 Vitamin D retention 76
4.3.3 Optimization of Emulsifying Conditions for Vitamin D
Nanoemulsions
77
4.3.4 Verifications of the Model 78
4.4 CHARACTERIZATION OF THE BETA CAROTENE
AND VITAMIN D NANOEMULSION
79
4.4.1 Droplet Growth Ratio and Storage Stability 79
4.4.2 p-Anisidine Value 87
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4.4.3 Turbidity 91
4.5 EFFECT OF ENVIRONMENTAL CONDITION ON BETA
CAROTENE AND VITAMIN D NANOEMULSIONS
93
4.5.1 Effect of pH 95
4.5.2 Effect of Ionic Strength 98
4.5.3 Effect of Temperature 100
4.5.4 Physical Stability (Freeze-Thaw Cycle) 105
4.6 TOXICOLOGICAL STUDIES FOR BETA CAROTENE
AND VITAMIN D NANOEMULSIONS
107
4.6.1 Body Weight 109
4.6.2 Nuclear Abnormalities Analysis 113
4.6.2.1 Bi-nuclear assay 113
4.6.2.2 Multi-nuclear assay 115
4.6.3 Comet Assay 120
4.6.3.1 Tail length 120
4.6.3.2 Tail DNA 126
4.6.3.3 Olive moment 128
4.10 PREPARATION OF FORTIFIED BEVERAGE 133
SUMMARY 136
RECOMMENDATIONS 138
LITERATURE CITED 139
APPENDICES 161
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LIST OF TABLES
Table No.
Page
3.1 Independent variables for optimization of preparation
conditions for β- Carotene nanoemulsion
38
3.2 Different combinations of independent variables for
application of RSM design for optimization of β- Carotene
nanoemulsions
39
3.3 Different combinations of independent variables for
application of RSM design for optimization of vitamin D
nanoemulsions
43
3.4 Different combinations of independent variables for
application of RSM design for optimization of vitamin D
nanoemulsions
44
4.1 Physicochemical properties of different components of beta
carotene and vitamin D nanoemulsions
55
4.2 Effect of independent variables on responses for β-carotene
nanoemulsions
56
4.3 Regression coefficients for beta carotene nanoemulsions 58
4.4 Optimum preparation conditions and response value for β-
carotene nanoemulsions
68
4.5 Effect of independent variable on responses for optimization
of vitamin D nanoemulsions
69
4.6 Regression coefficients values for vitamin D nanoemulsions 71
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4.7 Optimum preparation conditions for vitamin D
nanoemulsions
80
4.8 ANOVA for droplet growth ratio of beta carotene
nanoemulsions
81
4.9 ANOVA for droplet growth ratio of vitamin D
nanoemulsions
83
4.10 ANOVA for storage stability of beta carotene nanoemulsions 84
4.11 ANOVA for storage stability of vitamin D nanoemulsions 86
4.12 ANOVA for p-Anisidine value of beta carotene
nanoemulsions
88
4.13 ANOVA for p-Anisidine value of vitamin D nanoemulsions 90
4.14 ANOVA for turbidity value of beta carotene nanoemulsions 92
4.15 ANOVA for turbidity value of vitamin D nanoemulsions 94
4.16 ANOVA for pH stability of beta carotene nanoemulsions 96
4.17 ANOVA for pH stability of vitamin D nanoemulsions 97
4.18 ANOVA for stability of beta carotene nanoemulsions against
ionic strength
99
4.19 ANOVA for stability of vitamin D nanoemulsions against
ionic strength
101
4.20 ANOVA for stability of beta carotene nanoemulsions against
higher temperature
103
4.21 ANOVA for stability of vitamin D nanoemulsions against
higher temperature
104
4.22 ANOVA for physical stability of β-carotene nanoemulsions 106
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against freeze-thaw cycle
4.23 ANOVA for physical stability of vitamin D nanoemulsions
against freeze-thaw cycle
108
4.24 ANOVA for effect of beta carotene nanoemulsions on
weight
110
4.25 ANOVA for effect of different treatments of vitamin D
nanoemulsions on the weight of mice
112
4.26 ANOVA for bi-nuclear assay against different treatments of
beta carotene nanoemulsions
114
4.27 ANOVA for effect of different treatments of vitamin D
nanoemulsions on bi-nuclear assay
116
4.28 ANOVA for multi-nuclear assay of different treatment of
beta carotene nanoemulsions
118
4.29 Analysis of variance for effect of different treatments of
vitamin D nanoemulsions on multi-nuclear assay
119
4.30 ANOVA for effect of beta carotene nanoemulsions on tail
length
122
4.31 ANOVA for effect of different treatments of vitamin D
nanoemulsions on tail length
125
4.32 ANOVA for effect of different treatments of beta carotene
nanoemulsions on tail DNA
127
4.33 ANOVA for effect of different treatments of vitamin D
nanoemulsions on tail DNA
129
4.34 ANOVA for effect of different treatments of beta carotene 130
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nanoemulsions on olive moment
4.35 ANOVA for effect of different treatments of vitamin D
nanoemulsions on olive moment
132
4.36 Physicochemical properties of beta carotene and vitamin D
fortified beverages
134
4.37 Sensory Evaluation of beta carotene and vitamin D fortified
beverages
134
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LIST OF FIGURES
Figure No. Page
4.1 (A) Particle size distribution of β-carotene
nanoemulsions (B) Visual appearance of β-carotene
nanoemulsions
61
4.2 3D graphic surface optimization of (A) droplet size (nm)
versus surfactant concentration (%) and homogenization
time (Min.) (B) droplet size (nm) versus oil content (%)
and surfactant concentration (%) (C) p-Anisidine value
versus surfactant concentration (%) and homogenization
time (Min.) (D) p-Anisidine value versus oil content (%)
and surfactant concentration (%) (E) β-carotene
retention (%) versus surfactant concentration (%) and
homogenization time (Min.) (F) β-carotene retention
(%) versus oil content (%) and surfactant concentration
(%).
62
4.3 (A) Particle size distribution of vitamin D
nanoemulsions (B) Visual appearance of vitamin D
nanoemulsions
73
4.4 3D graphic surface optimization of (A) droplet size (nm)
versus S/O ratio and homogenization time (Min.) (B)
droplet size (nm) versus disperse phase volume (%) and
S/O ratio (C) Droplet growth ratio versus S/O ratio and
homogenization time (Min.) (D) Droplet growth ratio
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versus disperse phase volume (%) and S/O ratio (E)
Vitamin D retention (%) versus S/O ratio and
homogenization time (Min.) (F) Vitamin D retention
(%) versus disperse phase volume (%) and S/O ratio
4.5 Change in droplet growth ratio of beta carotene
nanoemulsions during one month storage
81
4.6 Effect of time and temperature on storage stability of
beta carotene nanoemulsions
83
4.7 Change in droplet growth ratio of vitamin D
nanoemulsions during one month storage
84
4.8 Effect of time and temperature on storage stability of
vitamin D nanoemulsions
86
4.9 Change in p-Anisidine value of beta carotene
nanoemulsions during storage
88
4.10 Change in p-Anisidine value of vitamin D
nanoemulsions during storage
90
4.11 Effect of time and temperature on turbidity 92
4.12 Effect of time and temperature on turbidity value of
vitamin D nanoemulsions during storage
94
4.13 Effect of pH on the stability of beta carotene
nanoemulsions
96
4.14 Effect of pH on the stability of vitamin D
nanoemulsions
97
4.15 Effect of ionic strength on the stability of beta carotene 99
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nanoemulsions
4.16 Effect of ionic strength on the stability of vitamin D
nanoemulsions
101
4.17 Stability of beta carotene nanoemulsions against higher
temperature
103
4.18 Stability of vitamin D nanoemulsions against higher
temperature
104
4.19 Physical stability of beta carotene nanoemulsions
against freeze-thaw cycle
106
4.20 Physical stability of vitamin D nanoemulsions against
freeze-thaw cycle
108
4.21 Effect of different treatments of beta carotene
nanoemulsions on the weight of mice
110
4.22 Effect of different treatments of vitamin D
nanoemulsions on the weight of mice
112
4.23 Effect of different treatments of beta carotene
nanoemulsions on the frequency of bi-nuclear cells
114
4.24 Effect of different treatments of vitamin D
nanoemulsions on the frequency of bi-nuclear cells
116
4.25 Effect of different treatments of beta carotene
nanoemulsions on multi-nuclear cells frequency
118
4.26 Effect of treatments of vitamin D nanoemulsions on the
frequency of multi-nuclear cells
119
4.27 Effect of beta carotene nanoemulsions on tail length 121
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4.28 Effect of different treatments of vitamin D
nanoemulsions on tail length in comet assay
122
4.29 Comet Assay Results for beta carotene nanoemulsions
(A) Group A (B) Group E
124
4.30 Comet Assay Results for vitamin D nanoemulsions (A)
Group A (B) Group E
125
4.31 Effect of beta carotene nanoemulsions on tail DNA 127
4.32 Effect of different treatments of vitamin D
nanoemulsions on tail DNA in comet assay
129
4.33 Effect of beta carotene nanoemulsions on olive moment 130
4.34 Effect of vitamin D nanoemulsions on olive moment 132
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ACKNOWLEGEMENTS
All kinds of appreciation and thanks are for Almighty Allah, the
beneficent, the merciful, Who is entire source of wisdom, knowledge and knows
better the mysteries and secrets of universe; who granted me the patience and
persistence to carry out my research study to the end. All respects are for the Holy
Prophet Muhammad (PBUH) who is, forever, a light of guidance of the entire
humanity.
I feel extremely privileged in taking this opportunity to express my
profound gratitude and sense of devotion to my worthy Supervisor Dr. Anwaar
Ahmed, Associate Professor Department of Food Technology, Pir Mehr Ali Shah
Arid Agriculture University, Rawalpindi. It was only because of his inspiring
guidance, cogent and thought provoking suggestions, consistent encouragement,
sympathetic attitude and dynamic supervision during the entire research work that I
could prepare this manuscript.
I am grateful to Prof. Dr. Asif Ahmad, Directior, Institute of Food and
Nutritional Sciences, for his valuable guidance and support at every stage of this
work. His cooperation and assistance made this research paper a worthwhile effort.
His enthusiasm and energy in the field of science is admirable. He has always been
willing to spare time and encourage me when needed.
I also owe debt of gratitude to Dr. Mansoor Abdullah, Faculty of
Veterinary and Animal Sciences, Pir Mehr Ali Shah Arid Agriculture University
Rawalpindi, for his kind behavior and valuable suggestions while completing this
work. Cordial and humble thanks are for Dr. Muhammad Sheeraz Ahmad, for
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his technical and constructive guidance during my research work.
I am highly obliged for indecorous, indemonstrable and endearment
guidance and support of Dr. Zaheer Ahmad, Assistant Professor, Department of
Home and Health Sciences, AIOU, Islamabad, Professor Dr. Sara Qaisar from
NCP and Dr. Abida Raza from NORI Hospital for their sympathetic attitude and
dynamic supervision during the entire research work that I could prepare this
manuscript.
I would like to record my special acknowledgments and sincerest thanks to
all my friends especially Abdul Waheed, Faheem Ilyas, Abdul Wakeel, Muhammad
Imran Yamin, Muhammad Kaleem, Muhammad Ali and Kashif Rafique for their
generous help and cooperation during my research work. Before I close, I would
like to acknowledge the efforts, the patience, the sacrifices rendered by my parents
in growing me up in a way that made it possible for me to achieve the present level.
No words can really express the feeling that I have for my beloved parents, brother
and sister. May Allah give them a long and happy life (Ameen).
TAHIR MEHMOOD
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ABSTRACT
Nutritional deficiency of vitamin A and D is causing a lot of problems in the world.
It is estimated that about one billion people worldwide are either vitamin D
deficient or have insufficient vitamin D intake. In Pakistan about 85% of both
pregnant and non-pregnant mothers have been found vitamin D deficient. Apart
from this, 5.7 million children below 5 years of age and 42.5 % women were
identified as vitamin A deficient in Pakistan. Being food fortification or
supplementation a best approach, the food manufacturers are interested in
fortifying their products with vitamin A and D. As both vitamins are restricted to
fats and oils due to their non-solubility in water. Nanoemulsions are ideal solution
to address this problem because this technique enhances the solubility, kinetic
stability, bio efficacy and bioavailability of encapsulated material due to their
smaller size. The purpose of present study was to fortify beverages with
nanoemulsions of vitamin A and D. The nanoemulsions were prepared by using
food grade surfactants (Tween 80 and soya lecithin), deionized water and vegetable
oil (olive and canola oil). Preparation conditions for beta carotene and vitamin D
nanoemulsions were optimized using response surface methodology. These
nanoemulsions were further characterized against different physico-chemical
parameters. In vivo study was carried out on animal model to investigate the safety
of nanoemulsions. The nanoemulsions based delivery system was used to fortify
the beverages with these vitamins. The results manifested that, ideal optimum
preparation conditions for beta carotene nanoemulsions were 6.07% surfactant,
4.19 minutes homogenization time and 6.50% oil contents. For vitamin D
nanoemulsions, optimum preparation conditions were 4.82 minutes
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homogenization time, 0.67 surfactant to oil ratio (S/O) and 7% disperse phase
volume. During two months of storage studies, these nanoemulsions remained
stable against phase separation and creaming. Moreover, droplet size of
nanoemulsions stored at 4 °C slowly increased as compared to nanoemulsions
stored at 25 °C. Additionally, p-Anisidine value of the vegetable oil (canola and
olive oil) incorporated into nanoemulsions were significantly lower as compared to
free vegetable oil. These nanoemulsions were stable against droplet aggregation
and phase separation over a wide range of pH (2-8), salt concentration (50-400
mM) and temperature (30-80°C). During toxicity study, bi-nuclear assay, multi-
nuclear assay and comet assay did not showed any toxic effect of nanoemulsions
on animal models. During last part of study, vitamin beta carotene and vitamin D
fortified model beverages was developed successfully. Hence, nanoemulsions
based delivery system can be used for fortification of aqueous products with fat
soluble vitamins and other nutraceutical compounds.
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Chapter 1
INTRODUCTION
The food industry is interested in the development of colloidal-based
delivery system which incorporates lipophilic compounds into food and beverages.
These colloidal systems vary in their physicochemical properties, stability and
composition, due to which these differ in functional performance (Mcclements et
al., 2007; Rao and Mcclements, 2011). There are numerous commercial
applications in the food industry where lipophilic compounds (such as flavors,
bioactive lipids, antioxidants, antimicrobials and nutraceuticals) are needed to be
incorporated into the aqueous phase (Given, 2009; Ziani et al., 2012). The most
convenient way to achieve the objective is colloidal- based delivery system i.e.
emulsions, nanoemulsions and microemulsions. It is seen that nanoemulsions are
an ideal colloidal system for the incorporation of lipophilic components into
aqueous media because of their solubility, kinetic stability, bioefficacy and
bioavailability attributed to their smaller size (Ozturk et al., 2014).
Nanoemulsions are kinetically stable system with mean radii of < 100 nm.
These have smaller particle size as compared to light wavelength, due to which
nanemulsions are appeared as transparent or slightly turbid (Mcclements, 2011).
Hence, nanoemulsions can be incorporated into food products where transparent
look is desirable e.g. fortified beverages and water. Furthermore, emulsions have
greater stability against droplet aggregation and sedimentation as compared to
conventional emulsions due to their smaller droplet size (Mcclements and Rao,
2011).
Nanoemulsions can be produced by using high energy (high-pressure
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homogenization, sonication and microfluidization) and low energy (phase inversion
and spontaneous emulsification) methods. During high energy method, intense
disruptive forces are generated to mechanically break the disperse phase into
smaller droplets which can be dispersed into continuous phase. High energy
methods are desirable in food industry for preparation of nanoemulsions by using
low surfactant to oil ratio as compared to low energy methods (Ozturk et al., 2014).
Hence, high energy methods are widely used for the preparation of nanoemulsions.
Low energy methods are not desirable for food industry because it is not possible
to use natural emulsifier (polysaccharides and proteins) for nanoemulsions
preparation in low energy approaches. Additionally, higher amount of synthetic
surfactant is used in low energy methods which is not desirable for food industry
(Mcclements and Rao, 2011).
β- carotene is a member of carotenoid family which is mainly found in
fruits and vegetables. It provides a substantial proportion of vitamin A in human
diet because of retinol precursor with higher conversion rate (Naves and Moreno,
1998). β- carotene is also useful in the prevention of numerous diseases such as
heart diseases, cataracts and cancer (Aherne et al., 2010). Furthermore, it is also
used in food industry as a colorant and antioxidant (Hou et al., 2012). So, food
industry is interested in its incorporation into food products to cater above-
mentioned benefits. But, their incorporation into beverages and various other foods
is challenging due to their poor water solubility, instability in heat, oxygen and
light and appearance in crystalline state at ambient temperature (Mattea et al.,
2009). Consequently, β- carotene are dissolved in oil or any suitable medium in oil
in water emulsions before their incorporation into aqueous food products (Qian et
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al., 2012b). Stability of beta carotene in oil in water depends on the composition of
emulsion and environmental conditions like heat, surfactant, light, food systems,
singlet oxygen and antioxidant addition (Hou et al., 2010). The most convenient
way to incorporate β- carotene into food products is nanoemulsions based colloidal
system which ensures higher stability, solubility and bioavailability due to smaller
particle size.
Vitamin D is a fat-soluble vitamin and it is produced from 7-
dehydrocholesterol when the skin of our body is exposed to sunlight. It plays an
important role in the development of cartilage, teeth and bone (Cranney et al.,
2008). It is also useful in the prevention of numerous diseases such as heart
diseases, immune diseases and cancer (Haham et al., 2012). Vitamin D possesses
two different active forms: cholecalciferol (vitamin D3) and ergocalciferol (vitamin
D2). Cholecalciferol is synthesized in our skin after exposure of sunlight as well as
ergocalciferol is naturally available in foods in small quantity (Guttoff et al., 2015).
The deficiency of vitamin D is worldwide and it is estimated that about one billion
people on the globe are vitamin D deficient or their consumption of vitamin D is
insufficient (Haham et al., 2012). This deficiency of vitamin D can be easily
addressed by fortifying food products with vitamin D. But, its fortification is
challenging due to poor solubility, bioavailability and chemical degradation under
different environmental conditions (Tsiaras and Weinstock, 2011). The
encapsulation of vitamin D in nanoemulsion-based delivery system is best solution
which exhibit it more solubility, stability and bioavailability.
Presently, a few studies have been carried out on the food grade
nanoemulsions and their potential applications in beverage and food industry. This
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research was designed to test the hypothesis that food grade colloidal system is a
successful technique for vitamin A and D delivery. This hypothesis was tested
through preparation and characterization of colloidal system (food grade
nanoemulsions). Later on, application of colloidal based delivery system in
beverages. The main objectives of the present study are:
Preparation of food grade nanoemulsion and incorporation of vitamin A and D
as active ingredient.
Characterization of these nanoemulsions for different physicochemical
parameters under different environmental conditions.
Investigation of the safety of these nanoemulsions.
Application of colloidal-based delivery system in beverage and subsequently
characterization of these beverages against different quality parameters.
5
Chapter 2
REVIEW OF LITERATURE
Nanoemulsions are those emulsions which consist of very small droplet size
having diameter in the range of 20-200 nm (Mason et al., 2006). Due to the smaller
particle size, they have many advantages as compared to conventional emulsion
when applied in different food products. Their particle size is smaller as compared
with light wavelength, so these appeared as transparent or slightly turbid (Tadros et
al., 2004). This smaller particle size makes them stable to droplet aggregation and
sedimentation as compared to macroemulsions (Wooster et al., 2008).
Nanoemulsion based colloidal delivery system increases the bioavailability of
encapsulated material. Hence, it can be used to improve the bioavailability of
nutraceutical compounds (Acosta, 2009).
2.1 FORMULATIONS OF NANOEMULSIONS
Nanoemulsions consist of three main components i.e. emulsifier, oil and
water. However, water and oil phase may contain many other compounds and
mixed surfactants. The concentration and characteristics of these components have
major influence on the functional properties of nanoemulsions.
2.1.1 Oil Phase
The oil phase of nanoemulsions is made up of non-polar compounds, which
includes monoglycerides, diglycerides, triglycerides, free fatty acids (FFA),
mineral oils, flavors oils, essential oils, waxes, fat substitutes, fat-soluble vitamins
and various bioactive compounds (Mcclements and Rao, 2011). The preparation,
stability and other properties of nanoemulsions depend on the physicochemical
properties of lipid phase e.g. interfacial tension, solubility in water, polarity,
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density, viscosity, refractive index, chemical stability and phase behavior (Anton
and Vandamme, 2009). Preparation of nanoemulsion from triglycerols is desirable
in food industry due to their abundance, low cost and their nutritional and
functional properties e.g. sunflower oil, safflower oil, olive oil, corn oil and fish oil
(Mcclements and Rao, 2011).
2.1.2 Aqueous Phase
The aqueous phase of nanoemulsions primarily consists of water but
sometimes it may carry other polar compounds such as alcohols, proteins,
carbohydrates, polyols and minerals. The composition and concentration of polar
compounds determine the physicochemical properties of aqueous phase such as
refractive index, polarity, interfacial tension, ionic strength and phase behavior
(Mcclements and Rao, 2011). The ionic strength and pH of aqueous phase has
major influence on electrostatic interaction of lipid droplets. Viscosity enhancers
are added to aqueous phase before homogenization to reduce the oil droplet size by
increasing disruptive shear stress in homogenizer (Qian and Mcclements, 2011).
Apart from this, additions of viscosity enhancer into nanoemulsions change their
stability by slowing droplet collisions and gravitational separation. Additionally,
lipid oxidation can be prevented in nanoemulsions by addition of anti-oxidants in
aqueous phase (Mcclements and Decker, 2000). So, we can control functional
properties, stability and formation of nanoemulsions by controlling the composition
of its aqueous phase.
2.1.3 Stabilizers
Nanoemulsions are kinetically stable but thermodynamically unstable
system. Hence, appropriate amount of surfactant is required to stabilize aqueous
7
and lipid phase (Wooster et al., 2008). Emulsifiers facilitate smaller droplet
formation during homogenization and stabilize droplets against droplet aggregation
after homogenization. Different stabilizers (such as ripening inhibitors, texture
modifier and weighting agent) are intentionally added into nanoemulsions to
prevent Ostwald ripening, gravitational separation and droplet aggregation
(Mcclements and Rao, 2011).
2.1.3.1 Emulsifier
Emulsifiers are added in nanoemulsions to prevent the separation of
aqueous and oily phase. Emulsifiers are those surface active molecules which are
adsorbed on the surface of droplet to facilitate disruption of droplets and protect
them from droplet aggregation (Kralova and Sjöblom, 2009). Molecular structure
of surfactant comprises of lipophilic and hydrophilic parts. Hydrophilic part has
affinity for hydrophilic media such as water, while hydrophobic part has affinity
for hydrophobic media such as oil. Hydrophilic-lipophilic balance is good indicator
of emulsifier affinity for aqueous and oily phase. Emulsifier with more than 10
HLB (Hydrophilic-lipophilic balance) number has greater affinity for hydrophilic
groups while those with lower than 10 HLB number have affinity for lipophilic
compounds (Kralova and Sjöblom, 2009). Emulsifier helps in droplet disruption
during homogenization by lowering the interfacial tension. The concentration of
emulsifiers plays an important role in the development of nanoemulsions because
of their larger surface area. Hence, greater surfactant concentration is required to
cover larger surface area as compared to conventional emulsions. Previous studies
reported that the size of oil droplet significantly reduced with the increase in
surfactant concentration in both low and high energy homogenization methods
8
(Qian and Mcclements, 2011; Rao and Mcclements, 2011). Choice of emulsifier
selected for nanoemulsions preparation varies according to characteristic of oily
phase. Generally, protein and smaller molecular based surfactants are preferred in
the preparation of food-grade nanoemulsions due to their ability to adsorb at the
interface of oil and water (Bos and Van Vliet, 2001). Proteins produce larger
droplets as compared to surfactant because these are slowly adsorbed at interface
during homogenization and are less effective for interfacial tension reduction
(Stang et al., 1994).
Electrical characteristic can be used to classify emulsifiers among different
groups which include anionic (negative), zwitterionic (both negative and positive),
cationic (positive) on non-ionic (neutral). Electrical properties on emulsifiers have
significant effect on preparation, functional properties and stability of food-grade
nanoemulsions (Mcclements, 2011). Examples of anionic surfactants are sodium
lauryl sulfate (SLS), diacetyl tartaric acid esters of monoglycerides (DATEM) and
sodium stearoyl lactylate (SSL) (Wooster et al., 2008). Examples of non-ionic
surfactants are esters of sucrose such as sucrose monopalmitate, Tweens and Brij.
Nonionic surfactant did not charge oily droplets but they may charge oil droplets if
they contain impurities or preferential adsorption of water ions. Mostly non-ionic
surfactant is used for the preparation of food grade nanoemulsion due to ease of
nanoemulsion preparation in low energy and high energy methods, lower toxicity
and lack of irritation e.g. Tweens (Chiu, 2006; Henry et al., 2009; Jafari et al.,
2007). Food industry rarely used cationic surfactant except for lauric alginate due
to stronger antimicrobial properties (Ziani et al., 2012). Another group of
surfactant is zwitterion which contains two or more ionizable groups having
9
opposite charge on the same molecule. Zwitterionic surfactants include protein and
lecithin (Hoeller et al., 2009). Apart from preparation and stability, surfactant plays
an important role in loading and protection of active ingredients. Furthermore,
some surfactants such as lauric arginate (LAE) or SDS have antimicrobial activity
in addition to stabilization of nanoemulsions (Ziani et al., 2011).
2.1.3.2 Texture modifiers
Hydrocolloids are commonly used in aqueous solutions based food
formulations due to their gelling and thickening properties (Saha and Bhattacharya,
2010). They are commonly used in nanoemulsions for texture modification or
stability improvement against gravitational separation. Modified rheological
properties change the mouth-feel, texture and retard movement of droplets
(Mcclements, 2011). Polysaccharides with hydrated and extended structures are
commonly used for texture modification due to their ability for gel formation and
thickening of solution. Amphiphilic based polysaccharides are widely used as
emulsifiers which include pectins, modified alginates, modified starches, modified
celluloses, cellulose derivatives or galactomannans and gum arabic (Dickinson,
2009). Polysaccharides may negatively affect the stability of nanoemulsions due to
depletion flocculation or bridging. Hydrocolloids may form multilayers by
interacting with already absorbed molecules (Dickinson, 2003). Hence, due to these
properties, hydrocolloids are commonly used in nanoemulsions based delivery
system for different food products. The bioactivity, as well as digestibility of the
compound encapsulated into nanoemulsions depends on the nature of biopolymers.
Additionally, hydrocolloids may affect the gastrointestinal fate of nanoemulsions
which lead to change in the nutritional properties of encapsulated materials
10
(Gidley, 2013).
2.2 NANOEMULSIONS PREPARATION
Nanoemulsions can be prepared by using different methods but we can
broadly categorize them into low and high energy methods on the basis of
underlying principles (Acosta, 2009; Anton and Vandamme, 2009; Leong et al.,
2009; Tadros et al., 2004). In high energy methods, mechanical devices are used
which generate disruptive force that disrupts and intermingle the aqueous and oil
phase into smaller droplets e.g. sonication, microfluidizer and high-pressure
homogenizers. These are mostly preferred in the food industry because we can
prepare nanoemulsions from different materials by using these methods (Gutiérrez
et al., 2008; Leong et al., 2009; Velikov and Pelan, 2008; Wooster et al., 2008). In
low energy methods, tiny oil droplets are formed spontaneously by altering the
environmental conditions and composition of oil-water-surfactant system e.g.
phase inversion and spontaneous emulsification methods (Bouchemal et al., 2004;
Freitas et al., 2005; Tadros et al., 2004). There are number of advantages which are
associated with high energy approaches as compared to low energy approaches
which include use of natural emulsifier, lower concentration of emulsifiers, large-
scale production and widely utilized equipment.
When two immiscible liquids are mixed together, they have tendency to
gain thermodynamically stable – oily layer on the top of water layer (Mcclements,
2011). Hence, mechanical stress is required to disrupt and mix lipid and aqueous
phases. Interfacial free energy (∆G1) is equal to increase in contact area between
the oil and water phases (∆A) multiplied by the interfacial tension of
nanoemulsions (γ): ∆G1 = γ∆A (Walstra, 1993). Interfacial free energy positively
11
changes with the decrease in oil droplets, because contact area increase after
homogenization, and therefore it oppose nanoemulsions formation. Hence, more
energy is required to break down droplets into smaller ones. Surfactants decrease
the interfacial tension of the system. As a result of this, lower energy is required to
break the droplets into smaller ones (Mcclements and Rao, 2011). Apart from this,
enough surfactant should be present in emulsifying chamber to cover newly formed
droplets and prevent the process of coalescence. Mostly, high- pressure
homogenizer and sonicator are used for the preparation of nanoemulsions due to
their capability for generation of higher energy densities.
2.2.1 High-Pressure Homogenizer
High-pressure homogenizer is commonly used in food industry for preparation
of emulsions and nanoemulsions due to their scaling up possibility and versatility.
There are many types of high-pressure homogenizer, but few of them are able to
break the droplets up to nanometer range. Most commonly used high- pressure
homogenizers are microfluidizers and high-pressure valve homogenizer.
Most widely used method for conventional emulsion preparation is high-
pressure valve homogenizer. This method can be used for the preparation of
nanoemulsions by pumping coarse emulsion through narrow valve which is located
at the end of chamber (Mcclements and Rao, 2011). Operating pressure, geometry
of homogenizer and number of passes has remarkable effect on the droplet size
distribution of nanoemulsions. With the increase in value of pressure or number of
cycles, nanoemulsions with smaller droplet size were produced (Donsì et al.,
2011b).
Microfluidizer is quite similar to high-pressure valve homogenizer, but their
12
disruption chamber differs in design. Just like high-pressure valve homogenizer,
coarse emulsions are passed through interaction chamber in microfluidizer, but the
interaction chamber is divided into two flow channels. As a result of this, intense
disruptive forces are generated when fast-moving streams of nanoemulsions strike
with each other’s which result in disruption of droplets having larger size into
smaller size (Mahdi Jafari et al., 2006). Channels of microfluidizers are available in
different shapes but Y- shaped channels are most widely used in pharmaceutical
and food industry for the preparation of nanoemulsions. The droplet size of
nanoemulsions can be reduced in microfluidizer through increasing the number of
cycle or increase in operating pressure, but over processing promote droplet
coalescence which results in larger droplet size (Salvia-Trujillo et al., 2013).
During high-pressure homogenization, temperature of the emulsifying chamber
significantly increases, which should be taken into account when dealing with heat-
sensitive material. The temperature can be controlled by installing cooling coils
outside the treatment chamber. Several previous studies reported the degradation of
active material due to increase in temperature in high-pressure homogenization
(Donsì et al., 2012; Shukat and Relkin, 2011). Hence, temperature of high-pressure
homogenization chamber must be controlled when designing nanoemulsions based
delivery system for heat sensitive materials.
2.2.2 Ultrasonic Homogenizer
High-intensity ultrasonic waves (>20kHz frequency) are utilized in ultrasonic
homogenizer to breakdown aqueous and lipid phases into smaller droplets.
Sonication is used in liquid products for inactivation of microbes, extraction and
emulsification (Vilkhu et al., 2008). Ultrasonic homogenizer reduces the size of
13
droplets through cavitation effect. This cavitation effect is generated through
pressure fluctuation within fluid which results in compression and cyclical growth
of air bubbles in the fluid. After reaching a critical size, these air bubbles become
unstable and collapse violently which result in generation of turbulence, high shear
forces and hot spots in cavitation zone. Due to these effects, oil droplet breaks into
smaller droplets, leading to nanoemulsion development (Soria and Villamiel,
2010).
The main variables which affect the droplet size during ultrasonic
homogenization are intensity and treatment time. With the increase in residence
time and intensity of ultrasonic waves, droplet size of nanoemulsions significantly
reduced (Salvia-Trujillo et al., 2013). Ultrasonic homogenizers are available in
batch and continuous design. In continuous sonication, broader range of particle-
size distribution was observed as compared to batch type design. Reduction in
droplet is independent of design but overpressure increases the process efficiency
(Leong et al., 2009).
Several drawbacks are also associated with the preparation of nanoemulsion
through ultrasonic homogenizer. Firstly, high shear rate and hot spots generated as
a result of bubble disruption increase the temperature of emulsifying chamber (up
to 80 °C) which leads to degradation of heat-sensitive compounds which are
present in emulsions. Additionally, cavitation effect can cause oxidation or
hydrolysis of triglycerides which leads to lipid degradation due to the formation of
reactive species (Chemat et al., 2004). Furthermore, it is also possible that particle
from sonication probe may release in form of metal ions into products (Freitas et
al., 2006).
14
2.3 DESIGNING OF FUNCTIONAL NANOEMULSIONS
The properties of nanoemulsion particles ultimately affect the bulk of
functional and physicochemical properties of nanoemulsions containing food
products e.g., release characteristics, digestibility, rheology, stability and optical
properties. Important characteristics of droplets which control the functional
properties of nanoemulsions are highlighted in this section.
2.3.1 Composition of Particle
The properties of nanoemulsions particles can be controlled by careful
selection of processing operations and ingredients. Droplets of O/W nanoemulsions
comprises of surface active material containing shell and lipophilic core
(Mcclements, 2011). The lipophilic core can be created using a variety of
ingredients (non-polar) which include free fatty acids, monoacylglycerols,
diacylglycerols, triacylglycerols, waxes, fat-soluble vitamins, essential oils, fat
substitutes, flavor oils essential oils, nutraceutical compounds (such as Co-enzyme
Q, curcumin, phytosterols and carotenoids). All of these ingredients have different
physico-chemical properties, including melting behavior, viscosities, refractive
index and densities, which significantly affect the overall functional properties of
nanoemulsions (Mehmood, 2015). Shell of nanoemulsion droplets can be created
using different surface active ingredients (food grade) which include phospholipids,
surfactants, polysaccharides, proteins, solid particles and mineral oils. The
selections of these ingredients have critical impact on the properties of
nanoemulsion particles, including release characteristics, physical stability, and
digestibility and release characteristics (Mcclements and Rao, 2011).
The thickness of shell is much smaller in conventional emulsions as compared
15
to core radius while in case of nanoemulsions, shell thickness is approximately
equal to core radius. Hence, shell also exerts pronounced effect on the composition
of particles (Mason et al., 2006). Furthermore, particle composition also depends
on size which has numerous practical utilizations. First, particle size has impact on
the properties of particles, including permeability, refractive index and densities
which change the stability (such as creaming rate, optical properties and release
characteristics) and physicochemical properties of nanoemulsions. Second, the
loading capacity of nanoemulsion particles decrease because these have less
fraction of lipophilic core as compared to conventional emulsions. Third, size
dependence of particle composition may affect the accuracy of particle size
measurement data obtained from different techniques such as dynamic light
scattering, spectro-turbidity and laser diffraction (Mcclements et al., 2007). The
mathematical models used by different instruments for the calculation of particle
size distribution using measurable physical property such as pattern of light-
scattering assumed that nanoemulsion droplets have well-defined physical
properties (i.e. densities and refractive index) and homogenous sphere. As a result
of this, there may be error in reported results of particle size distribution because
nanoemulsions droplets comprise of core-shell structure rather than homogenous
spheres.
2.3.2 Concentration of Particle
Generally, concentration of particles in colloidal dispersions are expressed as
mass, number, or total system mass or per unit volume of particles (Mcclements
and Rao, 2011). In conventional emulsions, particle concentrations of O/W
emulsions are reported in term of oil volume per unit emulsion volume. In case of
16
nanoemulsions, particle concentration is pure disperse phase because effective
volume comprised of sum of core and shell volume fractions. Due to this, there is a
remarkable difference in functional and physicochemical properties of
nanoemulsions (e.g. stability and rheology) as compared to conventional emulsions
(Mason et al., 2006; Tadros et al., 2004).
During the preparation of nanoemulsions, particle concentration is controlled
by controlling disperse and continuous phase. However, after the preparation of
nanoemulsions, particle concentration can be controlled through concentration
(such as centrifugation, filtration, evaporation or gravitational separation) or
dilution (addition of continuous phase) methods. The concentration of
nanoemulsions using these methods is much difficult than conventional emulsions
due to very smaller droplet size. The droplet size of nanoemulsions can be changed
by the addition of emulsifier or altering the conditions of the solution which effect
electrostatic interactions (e.g. by changing ionic strength or pH) (Mcclements et al.,
2007).
2.3.3 Particle Dimensions
Particle dimension is an important characteristic of nanoemulsions due to their
effect on rheological characteristics, optical properties, release characteristics and
biological fate. The particle dimensions are usually reported as particle size
distribution which represents the classes of particle fractions with discrete size
(Mehmood et al., 2017). Particle size distribution is usually reported in tabulated
form or graph of concentration of particles (e.g., number or volume percentage)
versus size of particles (e.g., radius or diameter). Central tendency of distribution
(such as mean or median) and distribution width (such as polydispersity index or
17
standard deviation) can be used for convenient representation of particle size
distribution.
Particle size distribution of nanoemulsions can be controlled by changing
system composition as well as preparation conditions. For example, in low energy
methods, particle size of nanoemulsions depend on different factors, including
composition of systems (e.g. ionic strength, type of surfactant and surfactant-oil-
water ratio) and environmental conditions (e.g. stirring speed and temperature-time
history) (Anton and Vandamme, 2009). In high energy approaches, nanoemulsions
droplet size depends on duration and intensity of energy input, relative viscosities
of continuous and disperse phases, interfacial tension, as well as nature and
concentration of surfactants (Jafari et al., 2007; Mahdi Jafari et al., 2006). Smaller
droplet of nanoemulsions can be produced by the intensity as well as duration of
homogenization, controlling viscosity ratio and using higher concentration of
surfactants (Schubert and Engel, 2004; Wooster et al., 2008). After the preparation
of nanoemulsions, stabilization of nanoparticles is mandatory to avoid and
undesirable change in particle dimensions during their utilization or storage.
The droplet size of nanoemulsions can be measured through dynamic light
scattering techniques. These techniques are based on measurement of translational
diffusion coefficient of droplets determined by analyzing the interaction between a
laser beam and nanoemulsions (Leung et al., 2006). Hydrodynamic diameter can be
calculated using Stokes-Einstein equation: (DH = kT/6πηD). Where DH represent
hydrodynamic diameter, k represent Boltzmann’s constant, D is coefficient of
translational diffusion, η indicate viscosity and T is absolute temperature. The two
most commonly used translational diffusion coefficient based methods are photon
18
correlation spectroscopy and doppler shift spectroscopy (Kaszuba et al., 2008).
2.3.4 Interfacial Properties
Interfacial characteristics of particles can be controlled in order to design
nanoemulsions with desirable functional attributes (Mason et al., 2006). Important
interfacial properties of particles which have pronounced effect on the functional
properties of nanoemulsions are rheology, interfacial permeability, environmental
responsiveness and interactions. Some surface active material creates interfacial
layer which is rigid and closely packed. Hence, it prevents the diffusion of other
components such as mineral oils, lipids and enzymes. On the other end, some
surface active molecule can be used to prepare interfacial layer with dynamic and
open structure which allow the passage of other molecules. In principle, selectively
permeable interfacial layers can be designed by careful selection of surface active
molecules (Mcclements et al., 2007).
Interaction of nanoemulsions particles with other surfaces and particles can be
prevented by controlling particle charge. For example, negatively charged particle
tends to stick with positively charged droplets and vice versa. Hydrophilic polymer
such as polyethylene glycol can be attached to particles for surface modification
which change their stealth character in human body (Howard et al., 2008). Particles
which are hydrophilic in nature are less susceptible to removal by natural defense
which increase particle residence time in systemic circulation. Surface active
polymers with non-polar characteristics (thermal or surface denatured globular
protein) can be used to increase the hydrophobicity of particle surface (Hashida et
al., 2005).
In nanoemulsions, interfacial properties of nanoemulsions can be controlled
19
using a particular type of emulsifiers, such as particular protein, surfactant,
polysaccharide or phospholipids. For example, fluid-like thin layers can be formed
using smaller molecule surfactants, thick fluid like layers can be formed using
biopolymers and thin elastic type layer can be formed using globular protein (soy
or whey protein) (Dickinson, 2003; Dickinson, 2009). Interfacial characteristics can
also be controlled using a combination of emulsifiers instead of using a single
emulsifier. Finally, another method for alteration of the interfacial characteristic is
the deposition of charged biopolymers successive layers on oil droplets containing
opposite charge to create nanolaminated coating having different environmental
responsiveness, charge or thickness (Guzey and Mcclements, 2006; Johnston et al.,
2006).
2.3.5 The Physical State of Particle
Usually, nanoemulsions are formulated using liquid oils, but these can be
prepared using lipids which are partially or fully crystallize at final temperature of
their usage (Weiss et al., 2008). During this situation, liquid state of lipid phase is
used during nanoemulsion preparation i.e., temperature should be more than lipid
melting point. After preparation, oil droplets of nanoemulsions are crystallized by
cooling them below their melting temperature (Mehmood et al., 2017; Wissing et
al., 2004). This approach can be used for the preparation of nanostructured lipid
carriers or solid lipid nanoparticles. These are nanoemulsions with partly or fully
solidify oil phase (Mller et al., 2004).
2.4 DROPLET BREAKUP IN NANOEMULSIONS
In general, shearing processes are used for the preparation of nanoemulsions
(Walstra, 1993). The droplet size of nanoemulsion depends on the two processes
20
which are occurred in homogenizer i.e. break-up of droplets and re-coalescence of
droplets (Jafari et al., 2008). The mechanical devices which have capacity to
generate intense disruptive forces are suitable for nanoemulsion preparation i.e.
ultrasonic devices, microfluidizers and high pressure homogenizers (Tadros et al.,
2004). These high intensity disruptive forces are required to overcome restorative
forces in order to maintain the spherical shape of nanoemulsion droplets (Schubert
and Engel, 2004). A useful tool for the calculation of these disruptive forces is
Laplace Pressure (∆P = γ/2r). The values of Laplace Pressure decreases with
increase in droplet radius and decreasing interfacial tension. Hence, when the
radius of droplets become smaller in homogenizer, it becomes more difficult to
break them further. Additionally, the droplet radius can be predicted using Taylor
equation e.g. r ∝ γ/ ηcγ0. Where γ represent interfacial tension, ηc indicate viscosity
of continuous phase and γ0 is shear rate (Taylor, 1934).
The droplet size of nanoemulsions produced using high energy approaches
depends on design of homogenizer (e.g. force and flow profile), environment (e.g.
temperature), and operating condition of homogenizer (e.g. duration and energy
intensity), physical and chemical properties of component (e.g. viscosity and
interfacial tension) and sample composition (e.g. surfactant concentration,
surfactant type and oil type) (Wooster et al., 2008). Previous studies demonstrated
that the droplet size of nanoemulsions decreased with increase in energy duration
or intensity, decrease in interfacial tension, higher concentration of emulsifier and
certain range of disperse to continuous phase viscosity ratio e.g. 0.05-5 (Tadros et
al., 2004; Walstra, 1993). The range of viscosity ratio which can produce smaller
21
droplets of nanoemulsions depends on type of disruptive forces generated by
homogenizer e.g. extential flow verses simple shear.
Surfactants play an important role in droplet break-up as well as droplet
coalescence. Surfactants help to reduce the droplet size of emulsions by lowering
the value interfacial tension which reduces the resistant against droplet deformation
(Walstra, 1993). Surfactants also prevent the re-coalescence of droplets through
adsorption and stabilization of interface. For this purpose, enough emulsifier
should be present in continuous phase to adsorb on newly formed interface.
Additionally, surfactants with smaller molecules are more desirable for the
preparation of nanoemulsions as compared with larger molecules due to their rapid
adsorption to interfaces and lower interfacial tensions (Leong et al., 2009).
2.5 ADVANTAGES OF NANOEMULSIONS OVER CONVENTIONAL
EMULSIONS
2.5.1 Antimicrobial Activity
Some antimicrobial agents are soluble in water and we cannot incorporate them
into lipid-based products. On the other end, some antimicrobial agents are only
soluble in oil, so they cannot be incorporated into aqueous products. The usability
and effectiveness of these compounds can be increased by encapsulating them in
nanoemulsions. These antimicrobial agents can be encapsulated into amphiphilic
exterior or hydrophobic interior of lipid phase or both (Jochen et al., 2009). The
activity of encapsulated antimicrobial agents depends on the transportation of these
materials from nanoemulsions to bacterial surface. Two different mechanisms may
be involved in this process: (1) direct interaction of droplets and microorganisms or
(2) diffusion of molecules through aqueous phase. Due to smaller droplet size,
22
nanoemulsions can increase the antimicrobial activity against microorganisms in
many different ways. Firstly, due to Laplace effect higher concentration of
antimicrobial agents are present at droplet surfaces which increase the mass
transport into aqueous phase (Mcclements, 2011). Laplace pressure indicates the
difference of pressure between inside and outside of air bubble or droplet. This
Laplace effect is caused due to surface tension between droplet liquid and bulk
liquid interface. It will partition more solute into aqueous phase by keeping
droplets in spherical shape. It acts across the oil-water interface toward the center
of the droplet so that there is a larger pressure inside the droplet than outside of it:
∆PL = 4γ/d. Where γ is interfacial tension and d is droplet diameter (Gupta et al.,
2016). Secondly, the interaction between droplets and microorganism is increased
due to increase in Brownian motion of smaller droplets. Thirdly, nanoemulsions
increased the penetration of antimicrobials into bacterial surfaces by facilitating
their penetration into biological membranes. Despite the potential application of
nanoemulsions based delivery system for delivery of antimicrobial agents, there
benefits over conventional emulsions are not clear due to lack of consistent data.
Some studies reported that the efficiency of nanoemulsions based delivery system
for antimicrobial agents decreased due to smaller particle size due to the adsorption
of antimicrobial at droplet surface instead of microorganisms (Salvia-Trujillo et al.,
2017).
2.5.2 Lipophilic Components Encapsulation
Nanoemulsions are used in beverages and food industry for the
encapsulation of lipophilic components such as colors, flavors, vitamins,
nutraceuticals, preservatives and antioxidants (Given, 2009; Graves and Mason,
23
2008). These components are encapsulated to increase their solubility and
bioavailability, protect them from degradation, incorporate them into food
products, ease of utilization and to control release rate (Mcclements and Rao,
2011). We can also introduce lipophilic compounds into clear or slightly turbid
products without altering their appearance. Numerous types of nanoemulsions have
been developed to encapsulate a variety of lipophilic compounds such as, citral
(Mei et al., 2009), β- carotene (Yin et al., 2009), fat-soluble vitamins (Hatanaka et
al., 2010) and co-Enzyme Q (Ozaki et al., 2010).
Lipophilic components are solubilized in oil prior to emulsification so that
these compounds are trapped within lipid phase during nanoemulsion preparation.
The location of hydrophobic compounds in nanoemulsions depend on
physicochemical and molecular properties, such as surface activity, surface
hydrophobicity, melting point, solubility and partition coefficient between oil-
water. The location of lipophilic compound exerts significant effect on physical as
well as chemical stability of nanoemulsions. For example, chemical degradation
starts in lipophilic compounds when they come in contact with polar compounds.
So, it is important for their stability that lipophilic compounds should be trapped
into oily phase rather than shell (Mcclements, 2011). In the previous study, when
citral (component of flavor molecule) come in contact with proton of water,
chemical degradation start in citral molecules which effect on the stability of
nanoemulsions (Mei et al., 2009).
2.5.3 Control Delivery and Increased Bioavailability of Lipophilic
Components
A number of previous studies reported that bioavailability of bioactive
24
component encapsulated into nanoemulsions increased due to smaller size of
nanoemulsions (Acosta, 2009). This increased in bioavailability is due to different
reasons. Firstly, nanoemulsion droplets have larger surface area. Due to this,
digestive enzyme acts more quickly on nanoemulsion as compared to
nanoemulsions which lead to easy absorption and rapidly release of encapsulated
material. Secondly, smaller droplets of nanoemulsions can penetrate into mucous
layer of epithelium cells in small intestine which increase residence time and they
reached closure to absorption sites. Thirdly, smaller droplets of nanoemulsions can
be transported directly through paracellular or transcellular mechanisms across
epithelium cells (Mcclements, 2011). Additionally, partition into aqueous phase
may be greater due to Laplace pressure which results in higher water solubility of
lipophilic components. Presently, there is a poor understanding about the
significance of these mechanisms for food grade nanoemulsions with different
surface characteristics, composition and droplet size.
Recently, some researchers reported that the bioavailability of curcumin
nanoemulsions can be increased by encapsulating them into nanoemulsions (Huang
et al., 2010; Wang et al., 2008). Various studies confirmed that nanoemulsions are
associated with increased bioavailability of lipophilic components in
pharmaceuticals and nutraceuticals (Hatanaka et al., 2010; Ozaki et al., 2010;
Talegaonkar et al., 2010). Furthermore, nanoemulsions can be effectively used for
the target delivery of bioactive components within human body which results in
improved efficiency (Huang et al., 2010; Salvia-Trujillo et al., 2017).
2.5.4 Improved Stability of Nanoemulsions
Nanoemulsions have smaller droplet size which gives them stability against
25
coalescence, flocculation and gravitational separation. Due to this, the shelf-life of
nanoemulsion containing food products is increased. However, nanoemulsions
should be carefully designed to avoid Ostwald ripening because these are degraded
by this mechanism. This problem can be prevented by using carrier oil which have
lower solubility in water (Li et al., 2009; Wooster et al., 2008) or restricting droplet
size changes through controlling interfacial layer properties (Mun et al., 2006).
Additionally, smaller droplet size of nanoemulsions can promote chemical
degradation of lipophilic components which are encapsulated into nanoemulsions
(Mao et al., 2009). Nanoemulsions have larger surface area as compared to
conventional emulsions which lead to greater chemical degradation such as lipid
oxidation. Additionally, visible and UV light can easily penetrate through
transparent nanoemulsions which can promote chemical degradation due to light-
sensitive reactions. Hence, additional steps may be required to protect the bioactive
components which are encapsulated into nanoemulsions such as addition of
chelating agents or antioxidants.
2.5.5 Modification of Texture
Nanoemulsions have very smaller size droplets due to which interfacial coating
around droplets constitute appreciable proportion of the overall volume of droplets.
As a result of this, it might be possible than nanoemulsion promotes gelation
reactions at lower oil concentration as compared to conventional emulsions. These
properties are desirable in preparation of the products which required gel-like or
viscous appearance such as reduced fat products. Currently, nanoemulsions are not
exploited for the texture modifications of food products. However, some studies on
non-food grade system reported that electrostatic repulsion effect can be used for
26
the preparations of nanoemulsions with transparent look and gel-like characteristics
(Kawada et al., 2010). The present approach may be used for the preparation of
visco-elastic and highly viscous nanoemulsions using lower oil concentrate as
compared to conventional emulsions (Wilking and Mason, 2007).
2.6 BIOLOGICAL FATE AND BIOAVAILABILITY OF
NANOEMULSIONS
During digestion biochemical process occurs in gastrointestinal tract (Golding
and Wooster, 2010). Salts present in the mouth affect the ionic strength of
nanoemulsions and change its stability. Presence of mucin in saliva causes droplet
aggregation by depletion flocculation or bridging. When these nanoemulsions
droplets reach stomach, their aggregation properties are further changed due to
shear conditions, lower pH and higher ionic strength (Salvia-Trujillo et al., 2017).
Gastric lipase present in stomach causes hydrolysis in smaller fraction of lipid, but
majority of lipid is digested in smaller intestine by pancreatic lipase. Emulsifier
molecules displaced from water-oil interface due to the presence of bile salts in
gastrointestinal fluid causes enzyme binding (Reis et al., 2009). During lipid
digestion, free fatty acids, as well as monoglycerols, are generated which are
accumulated on the surface of the oil. Later on, the products of lipid digestion are
removed through bile salts by solubilizing these products in mixed micelles, which
facilitate complete digestion of lipids. Furthermore, calcium ions react with long
chain free fatty acids and form insoluble soaps and facilitating their removal from
oil surface. Finally, lipolysis products and lipophilic compounds (encapsulated in
nanoemulsion) are solubilized in unilamellar phospholipids vesicles or mixed
micelles which are absorbed across the intestinal lumen. Additionally, lipolysis
27
reaction can be interrupted by long-chain free fatty acid and monoglycerols due to
their higher surface activity (Salvia-Trujillo et al., 2017).
Deep understanding regarding gastrointestinal processes is compulsory for
designing nanoemulsions with higher bioavailability and bioaccesibility of
bioactive compounds. Previous researchers proved that co-administration of
lipophilic compounds along with oily face increase their absorption after digestion
(Pouton and Porter, 2008). For example, Yu and coworkers (2012) reported that
bioavailability of curcumin encapsulated in nanoemulsions was increased nine fold
as compared to their crystalline form. Additionally, type of lipid carriers and
droplet size have pronounced effect on the bioavailability of encapsulated
compound. Several researchers reported that the bioavailability of encapsulated
bioactive compounds increased with smaller droplet size due to higher digestion of
lipid phase (Mcclements, 2011; Salvia-Trujillo et al., 2013). However, some
researcher reported that bioavailability of curcumin encapsulated in nanoemulsions
decreased as compared to conventional emulsions (Ahmed et al., 2012). This
decrease might be attributed due to higher chemical degradation of curcumin with
more oil-water interface. So, the nature of bioactive compounds which are
encapsulated in nanoemulsions has significant effect on the bioavailability. For
example, the bioavailability of carotenoids was higher when long-chain
triglycerides were used in nanoemulsions as compared to medium chain
triglycerides (Ahmed et al., 2012; Qian et al., 2012b). This effect may occur due to
the fact that larger hydrophobic core is required for the incorporation of larger
carotenoid molecules. Hence, medium chain free fatty acids containing smaller
hydrophobic core are unable to incorporate longer lipophilic compounds.
28
Nanoemulsions containing digestible lipids (e.g. triglycerides) are rapidly
digested in the gastrointestinal tract. However, they behave differently when they
contain indigestible lipid phase (such as flavor or mineral oil). Biological fate of
encapsulated material depends on the nature of hydrophobic material. Presently,
knowledge gap exists to understand the effect of individual ingredient on the
biological fate of nanoemulsions. Hence, more research is required for better
understanding of the biological fate of nanoparticles in gastrointestinal tract.
2.7 APPLICATION OF NANOEMULSIONS IN FOOD PRODUCTS
Nanoemulsions have a number of potential applications for incorporation of
lipophilic compounds into food products. Number of researchers highlighted the
advantages which are associated with the use of nanoemulsions as delivery system.
Oregano oil based nanoemulsions with droplet size of 150 nm was recently used to
retard the growth of food-borne pathogens in lettuce during their storage in
refrigerator (Bhargava et al., 2015). Nanoemulsions with cinnamaldehyde (droplet
size less than 200 nm) were found effective for deactivation of bacterial growth in
melon juice (Jo et al., 2015). Furthermore, soaking radish, alfalfa and mong been
seed in nanoemulsions containing carvacrol retarded the growth of Enteritidis,
Escherichia coli O157: H7 and Salmonella enterica without affecting their sprout
yield (Landry et al., 2015). Donsi and coworkers investigated the effect of
incorporation of tarpene containing nanoemulsion into pear and orange juice during
their storage at 32 °C for 16 days. They reported that lower concentration (1.0g/L)
of tarpene containing nanoemulsions delayed the growth of microorganisms
(Lactobacillus delbrueckii) while higher concentration (5.0g/L) completely
inactivated the bacterial growth without compromising the sensory properties of
29
fruit juice (Donsì et al., 2011a). Joe and coworkers (2012) observed that the shelf
life of fish steak can be increased by using sunflower oil based nanoemulsions.
They reported the significant reduction in the population of lactic acid, hydrogen
sulfide and heterotrophic bacteria as well as extension of shelf life during storage
as compared to control samples. Mate and others (2016) observed reduced growth
of Listeria monocytogens in vegetable cream and chicken broth treated with nisin
and D-limonene nanoemulsions. Ma and others reported that eugenol or thymol
nanoemulsions exhibit antimicrobial activity in low-fat milk emulsified with LAE
and lecithin (Ma et al., 2016a).
Limited examples are available for the incorporation of bioactive compound
loaded nanoemulsions into commercial food products. However, number of
researchers reported that nanoemulsions can significantly improve the
bioavailability of bioactive compound in different food products (Mehmood, 2015).
Several researchers observed that nanoemulsions increase the bioavailability of
carotenoids from tomato juice (Salvia-Trujillo and Mcclements, 2016), carrots
(Zhang et al., 2016), yellow peppers (Liu et al., 2015) and mangoes (Liu et al.,
2016). Although it is proved that nanoemulsion-based delivery system improved
the bioavailability of encapsulated compounds, more research is required is
required to prove that nanoemulsions are associated with improved bioavailability
of encapsulated materials in complex food matrices.
Although there is no strong scientific evidence which supports the advantages
of bioactive and antimicrobial systems, a number of food industries are using
nanoemulsion-based delivery system for the incorporation of lipophilic compounds
into their products. These compounds include lutein, lycopene, coenzyme Q10, β-
30
carotene, fat-soluble vitamins, omega three fatty acids, isoflavons and phytosterols.
In these cases, food manufacturer claimed the enhance bioavailability of active
ingredient after digestion as well as protection from harsh environmental condition
during food operations (Salvia-Trujillo et al., 2017).
Although, numbers of research studies are carried out to demonstrate the
increased bioavailability of lipophilic compounds which are encapsulated into
nanoemulsions based delivery system, it is the need of time to confirm this
evidence after food handling operations and incorporating these compounds into
complex food matrices. Hence, comprehensive approach is required in future
research on nanoemulsions to investigate the actual advantages which are
associated with nanoemulsions based delivery system. In future research, loss in
the functionality of encapsulated material due to processing, storage and effect of
food matrix should be considered. Furthermore, higher cost related to
nanoemulsions production should be considered due to the requirement of some
equipment and higher energy input.
2.8 POTENTIAL TOXICITY OF NANOEMULSIONS
Currently, very little experimental evidence are available regarding the
potential toxicity which is associated with food grade nanoemulsions. However,
scientists are convinced that a number of physicochemical reaction associated with
smaller droplet size may cause toxicity (Mcclements and Rao, 2011). Currently, no
standard protocol is available to test the toxicity of food-grade nanoemulsions
(Maynard et al., 2006). There is need of further research to investigate the potential
toxicity of nanoemulsions. Potential toxic effects of nanoemulsions are discussed in
this section.
31
2.8.1 Bioactive Compounds with Increased Bioavailability which are Toxic
at Higher Level
Bioavailability of bioactive components increased when their size is reduced to
critical level i.e. in the range of 100-1000nm (Acosta, 2009). Increased
bioavailability of many bioactive compounds are either desirable or have no
adverse effects. However, there are some potential hazards about the increased
bioavailability of some bioactive components that may exert toxic effects when
consumed at higher dose. If any of these components which normally lower
bioavailability are encapsulated into nanoemulsions, may exhibit toxic effects due
to increased bioavailability. These effects were more apparent when we incorporate
bioactive compound into those products which are regularly consumed such as
beverage and soft drink emulsions. Hence, this potential hazard should be
considered before designing of nanoemulsions based delivery system for bioactive
compounds.
2.8.2 Direct Absorption of Smaller Droplets
There are evidence that non-digestible nanoparticles, such as inorganic material
(silicon oxide and titanium dioxide) and metals (gold and silver) can directly cross
the epithelial layer by paracellular and transcellular mechanisms (De Jong et al.,
2008). After absorption, these nanoparticles may be digested, accumulated or
transported into systemic circulation through lymph or blood system (Hu et al.,
2009). The nanoparticles which are transported through epithelial cells are
circulated in the human body, where they may be metabolized, accumulated within
tissues or excreted from the body (Bouwmeester et al., 2009). These mechanisms
depend on physicochemical characteristic of nanoparticles like interfacial tension,
32
charge, shape, size and composition. Presently, no evidence is available which
suggest that the components of food-grade nanoemulsions are directly absorbed in
human body. Direct absorption occurs if indigestible materials (mineral oils and
hydrocarbons) are used for nanoemulsion preparation or indigestible shell (dietary
fiber) is used to coat nanoemulsions droplets. Further research is needed to clarify
that either this mechanism is important for humans or not.
2.8.3 Disturbance in Normal Gastrointestinal Functions
Droplets of nanoemulsions can alter the normal functionality of gastrointestinal
tract during their passage from mouth, stomach and small intestine due to smaller
droplet size, which can cause adverse health effects (Chaudhry et al., 2008). For
example, the possibility exist that these smaller droplets are directly absorbed via
epithelial cells in mouth, esophagus and stomach before their digestion into small
intestine. Smaller droplets have higher curvature and surface area and their surface
activity are also different from bulk materials, which can change the activity and
accumulation of lipase, salts and component of digestive systems at the surface of
droplet, thereby interfering in normal function of gastrointestinal tract. If we take
the example of protein absorption to particle surface, it may lead to loss in normal
functions and denaturation, which can cause adverse health effects on humans
(Hoet et al., 2004). These nanoparticles can attach to receptors of cell membranes
which lead to alteration in cellular metabolism and functions. Hence, it is
concluded that high-surface energy, higher surface area and smaller droplet size
can cause some unpredictable effects on biological systems which are different
from bulk form of this material (Jiang et al., 2009). Further research is needed to
understand the effect of nanoemulsions on gastrointestinal tract functions.
33
2.8.4 Effect of Composition
Some components of nanoemulsion can produce toxic effects when they are
consumed at the higher level e.g. solvents and emulsifiers. During the preparation
of nanoemulsions, surfactants are required in larger amount to cover larger surface
area of nanoemulsion droplets. Presently, small molecule surfactants (co-
surfactants are also used sometimes) are most widely used for the preparation of
food-grade nanoemulsions. These surfactants are used due to their ability to
spontaneous nanoemulsion preparation through low-energy methods (e.g. PIT
method), and reduction of interfacial tension and rapid absorption at droplet surface
in high-energy methods (e.g. ultrasonication). Natural surfactants, such as
phospholipids, proteins and polysaccharides are less effective for nanoemulsions
preparation. Smaller molecule surfactants can cause toxic effects on human health
when these are consumed in higher amount (He et al., 2010). Therefore, higher
amount of surfactant which is used in nanoemulsions preparation as compared to
nanoemulsions must cause some adverse effects on the health of humans.
During the nanoemulsions preparation through low-energy methods
(evaporation and solvent displacement methods) organic solvents are used which
include ethyl acetate, hexane and acetone (Horn and Rieger, 2001). Although, these
organic solvents are removed through evaporation during the preparation of
nanoemulsions, but some of their residues can remain in nanoemulsions which can
exert toxic effects. So, when we prepare nanoemulsions using organic solvents, the
toxic effect of the residues of that solvent should be considered. The data related to
potential toxicity of solvents and emulsifiers which are used for food grade
nanoemulsion preparations are available on the websites of different organizations
34
such as European Food Safety Authority, Food and Drug Administration and
World Health Organization. Before selection of suitable components for
nanoemulsions, potential toxicity and safe use level of those components should be
considered.
35
Chapter 3
MATERIALS AND METHODS
3.1 COLLECTION OF MATERIALS
RBD (Refined, Bleached and Deodorized) canola oil and olive oil were
purchased from Punjab Oil Mills, Islamabad, Pakistan. Tween 80 (food grade),
Tween 60 and lecithin were purchased from local scientific store. Beta carotene
and vitamin D2 were purchased from Sigma-Aldrich Co USA. Deionized and
distilled water was used in all the experiments.
3.2 CHARACTERIZATION OF NANOEMULSIONS COMPONENTS
The components of nanoemulsion (surfactants and cooking oils) were
characterized before preparation of nanoemulsions to investigate their effect on the
preparation and nanoemulsions stability. Density meter (DS7800, KRUSS,
Hamburg, Germany) was used to determine the density of nanoemulsion
components. Interfacial tension was measured using Tensiometer (DSA100,
KRUSS, Hamburg, Germany). Viscosity was measured through Viscometer
(KV100, Massachusetts, USA).
3.3 NANOEMULSIONS PREPARATION
Nanoemulsions were prepared by mixing 10 % dispersed phase and 90%
continuous phase. Dispersed phase was formulated by dissolving pre-determined
amount of encapsulated material (Beta carotene and vitamin D2) in vegetable oil
(canola oil and olive oil). Continuous phase consist of deionized water carrying
pre-determined amount of mixed surfactants. These components were mixed with
polytron (KRH-I, KONMIX, Shanghai, China) to prepare coarse emulsions. For
35
22
36
the preparation of nanoemulsions, these coarse emulsions were subjected to
ultrasonic homogenization by using 20 kHz sonicator (230VAC, Cole-Parmer,
USA). Ultrasonic homogenization was done by placing the tip horn (20 mm
diameter) of sonicator in coarse emulsions by applying different ultrasonic powers
for different times. The temperature of the emulsion was controlled by placing it in
ice bath during homogenization. These nanoemulsions were stored at room
temperature for further analysis.
3.4 PARTICLE SIZE ANALYSIS
The droplet size of the nanoemulsions was measured by dynamic light
scattering using nanotrac (Microtrac, Tri-Blue, USA). Particles in liquid
suspensions undergo continuous Brownian motion. These particles scatter light in
suspension and change the refractive index through localized changes. As a result
of this, intensity variation is produced which can be analyzed through
autocorrelation function: C(γ) = 1/N ΣN
i=1 I(ti) I (ti+τ). Where N is number of time
this procedure is carried out, I(t) represent intensity of photon and τ is scattering
pattern. Dilution of nanoemulsion is pre-requisite to avoid the effects of multiple
scattering (Leong et al., 2009). In this research, beta carotene and vitamin D
nanoemulsion samples were diluted to 10% using deionized water in order to avoid
multiple scattering effects. The droplet size of nanoemulsions was reported as
average diameter (D4,3).
3.5 OPTIMIZATION OF PREPARATION CONDITIONS FOR β-
CAROTENE NANOEMULSION
Response Surface Methodology (RSM) is a combination of statistical and
mathematical techniques to investigate the relationship between response variables
37
and input variables (Khuri and Mukhopadhyay, 2010). RSM is used for
improvement, development and optimization of processes in which desired
response variable is affected by several independent variables and there is a need to
optimization of this response. Additionally, it is also used for the design and
development of new product and for the design improvement of existing product.
RSM is applied in three stages: (1) selection of independent variables and their
levels, (2) experimental design selection along with prediction as well as
verification of model equation and (3) obtaining contour and response plot (Baş
and Boyacı, 2007).
RSM (Response surface methodology) was used to investigate the effect of
independent variables i.e. surfactant concentration (X1), ultrasonic homogenization
time (X2) and oil contents (X3) on response variables, such as droplet size (Y1), p-
Anisidine value (Y2) and retention of beta carotene (Y3) in nanoemulsions. On the
basis of our previous research findings and through review of literature, these
independent variables and responses were selected due to their significant effect on
the physico-chemical properties and stability of nanoemulsions. RSM design along
with coded and uncoded levels has been presented in Table 3.1. Central composite
design (Five levels) and quadratic model was used to design this experiment.
Twenty treatments, including six axial points, eight fractional factorial points and
six central points were randomly performed according to CCD (central composite
design) which has been summarized in Table 3.2. Real levels of independent
variables for beta carotene nanoemulsions were coded according to the equation
expressed below;
Z = Z0 –ZC / ∆Z (1)
38
Table 3.1: Independent variables for optimization of preparation conditions for β-
Carotene nanoemulsion
Independent variable Symbol Coded levels
-α -1 0 +1 +α
Surfactant concentration (%) X1 2.64 4 6 8 9.36
Homogenization Time (Min.) X2 2.98 4 5.5 7 8.02
Oil Content (%) X3 5.48 6.5 8 9.5 10.52
39
Table 3.2: Different combinations of independent variables for application of RSM
design for optimization of β- Carotene nanoemulsions
Treatments Mixed Surfactants
(%)
Homogenization Time
(Min.)
Oil Contents
(%)
T1 8 4 6.50
T2 6 5.50 8
T3 4 7 6.50
T4 6 5.50 5.48
T5 8 4 9.50
T6 6 8.02 8
T7 9.36 5.50 8
T8 6 5.50 10.52
T9 6 5.50 8
T10 6 5.50 8
T11 8 7 9.50
T12 8 7 6.50
T13 6 5.50 8
T14 6 5.50 8
T15 4 4 6.50
T16 4 4 9.50
T17 6 5.50 8
T18 2.64 5.50 8
T19 6 2.98 8
T20 4 7 9.50
40
Where Z and Z0 indicate coded and real levels of independent variables, ∆Z
represents step change and ZC indicates actual value at central point.
Specific equation for each independent variable was derived from above equation
to code their actual values. Specific equations for surfactant concentration (X1),
Ultrasonic Homogenization time (X2) and oil contents (X3) are mentioned in
equation 2-4:
z1 = (SC – 6) / 2 (2)
z2 = (HT – 5.5) / 1.5 (3)
z3 = (OC – 8) / 1.5 (4)
Where MS, HT and OC represent surfactant concentration, Homogenization time
and oil contents, respectively.
Second order polynomial equation was used to indicate the predicted
responses (droplet size, p-Anisidine value and retention of beta carotene) of mixed
surfactant based beta carotene nanoemulsions as a function of independent variable
as follows:
(5)
Where Z represents response values, indicate the values of linear,
quadratic and interactive coefficients, respectively and is constant. Design
expert software (version. 8.0.7.1) was used to calculate the value of coefficients of
determination.
3.5.1 p-Anisidine Value
p-Anisidine Value is an important indicator of the stability of nanoemulsions.
The oxidative stability of beta carotene nanoemulsions was measured according to
41
the method of Cho et al., (2008). Firstly, 20g of beta carotene nanoemulsion was
incubated for one week at 50 °C. Then, 1g solution was dissolved in n-Hexane
(HPLC Grade) and the absorbance of the solution was measured using UV-
Spectrophotometer at 350nm. After that, 1 mL p-Anisidine reagent (prepared by
dissolving 2.5g of p-Anisidine in one liter of acetic acid) was added in 5 mL of
solution and they were kept for 10 minutes to allow their reaction. Absorbance of
the fat solution was determined as blank in reference cell. p-Aniside value was
determined using following formula:
p-Anisidine Value = 25 × (1.2 AAR – ABR)
M
Where AAR is the absorption of the solution after reaction, ABR represents
absorption before reaction and M denote sample mass in grams.
3.5.2 Beta Carotene Retention
The concentration of beta carotene in nanoemulsions was determined through
spectrophotometric method according to the method of Yuan et al., (2008). Firstly,
1 ml sample was extracted using a mixture of n-Hexane (3ml) and ethanol (2ml).
After that, this mixture was shaken well and phase of hexane was removed. This
extraction procedure was repeated two times further. At the end all hexane phases
were combined and their absorbance was measured through UV-
Spectrophotometer at 450 nm after desired dilution with n-Hexane. The beta
carotene concentration was determined using standard curve prepared under similar
conditions. Vitamin retention was calculated using following formula:
VRBC = VBC,N/ VBC,I × 100
Where VRBC represent beta carotene retention, VBC,N is the concentration of beta
42
carotene in nanoemulsion and VBC,I indicate initial concentration of beta carotene .
3.6 OPTIMIZATION OF PREPARATION CONDITIONS FOR
VITAMIN D NANOEMULSION
A three-factor central composite design (CCD) was used to investigate the
effect of Ultrasonic Homogenization time (X1), surfactant to oil ratio (X2) and
disperse phase volume (X3) on three response variables: droplet size (Y1), droplet
growth ratio (Y2) and vitamin D retention (Y3) in nanoemulsions. On the basis of
our previous research findings and through review of literature, these independent
variables and responses were selected due to their significant effect on the physico-
chemical properties and stability of nanoemulsions. Actual and coded levels of
independent variables are summarized in Table 3.3. The preparation conditions of
nanoemulsion were optimized through three-factor (Five levels) central composite
design and quadratic model. Central composite design was comprised of twenty
treatments, including 6 axial points, 6 central points and eight fractional factorial
points and experiment was randomly performed according to CCD which has been
summarized in Table 3.4. Actual values of independent variables were coded
according to the equation 6:
Y = Y0 –YC / ∆Y (6)
Where Y and Y0 represent coded and actual levels of independent variables,
respectively. ∆Y represents step change while YC indicates actual value at the
central point.
Specific equation for each independent variable was derived from above
equation to code their actual values. Specific equations for surfactant concentration
(X1), Homogenization time (X2) and oil contents (X3) are mentioned below.
43
Table 3.3: Independent variables for optimization of ingredient level for vitamin D
nanoemulsions
Independent variable Symbol Coded levels
-α -1 0 +1 +α
Homogenization Time (Min.) X1 2.48 3.5 5 6.5 7.52
Surfactant to oil ratio (S/O) X2 0.311 0.430 0.605 0.780 0.899
Disperse phase volume (%) X3 6.32 7 8 9 9.68
44
Table 3.4: Different combinations of independent variables for application of RSM
design for optimization of vitamin D nanoemulsions
Treatments Homogenization Time
(Min.)
Surfactant to Oil
Ratio
Disperse Phase Volume
(%)
T1 5 0.605 9.68
T2 5 0.899 8
T3 6.5 0.780 7
T4 5 0.605 8
T5 3.50 0.780 9
T6 3.50 0.430 9
T7 5 0.605 8
T8 6.50 0.780 9
T9 7.52 0.605 8
T10 2.48 0.605 8
T11 3.50 0.780 7
T12 5 0.605 8
T13 6.50 0.430 7
T14 5 0.605 8
T15 5 0.605 8
T16 3.50 0.430 7
T17 5 0.311 8
T18 5 0.605 8
T19 5 0.605 6.32
T20 6.50 0.430 9
45
(7)
(8)
(9)
Where HT, S/O and DPV represents homogenization time, surfactant to oil ratio and
dispersed phase volume, respectively.
The generalized RSM model for expressing variation in response variables
(droplet size, droplet growth ratio and vitamin D retention) as a function of
independent variable is summarized in equation:
(10)
Where Y represent predicted response values, indicate the values of
regression coefficients for intercept, linear, quadratic and interaction, respectively.
Design expert software (version. 8.0.7.1) was used to design experiment, analysis
of data and model building.
3.6.1 Droplet Growth Ratio (DGR)
The stability of nanoemulsions depends on many processes. In our study,
the stability of vitamin D nanoemulsions was measured in term of droplet growth
ratio (DGR). As there is a tendency of droplet aggregation in nanoemulsions during
storage, we can determine nanoemulsion stability by measuring the increase in
droplet size during storage. The droplet growth ratio was determined by comparing
the droplet size after nanoemulsion preparation with droplet size after 14 days of
storage (Mehmood, 2015). Droplet growth ratio was determined using below
mentioned equation:
Droplet Growth Ratio = Droplet size after two weeks – Droplet size at zero day
Droplet size at zero days
46
The droplet size of mixed surfactant based nanoemulsions were reported in the
form of D4,3.
3.6.2 Vitamin D2 Retention
The retention of vitamin D2 in nanoemulsions was determined through
spectrophotometric method by following the method of Khalid et al., (2017).
Firstly, nanoemulsion sample (1ml) was extracted using 9 ml of n-Hexane and after
that; this sample was ultrasonicated for 20 minutes at 100 kHz. Then, the sample
was centrifuged at 9000 rpm for 15 min. Aliquot of supernatant (1 ml) was diluted
five times with n-Hexane and the absorbance was measured at 310 nm. For blank
measurement n-Hexane was used. Vitamin retention was calculated using
following formula:
VRD2 = VD2,N/ VD2,I × 100
Where VRD2 represent beta carotene retention, VD2,N is the concentration of
beta carotene in nanoemulsion and VD2,I is initial concentration of beta carotene .
3.7 CHARACTERIZATION OF NANOEMULSIONS
Optimized treatments of mixed surfactant based beta carotene and vitamin D
nanoemulsions were characterized for their physicochemical parameters such as
droplet growth ratio, storage stability, p-Anisidine value and turbidity. Details of
these parameters are given below:
3.7.1 Storage Stability
The storage stability of nanoemulsion samples was determined by measuring
particle size of beta carotene and vitamin D nanoemulsions after every week for the
duration of two months. The storage stability of nanoemulsions was determined at
two different temperatures i.e. 4°C and 25°C.
47
3.7.2 Turbidity Measurement
The turbidity of nanoemulsions was determined through spectrophotometric
method by using UV-visible spectrophotometer (S-200D) at 600 nm. Turbidity
changes were recorded as described by Rao and Mcclements, (2011). Turbidity of
beta carotene and vitamin D nanoemulsions was measured after every week for the
duration of two months. The turbidity of nanoemulsions was determined at two
different temperatures i.e. 4°C and 25°C
3.8 FACTORS AFFECTING SELECTIVE PARAMETERS
The stability of optimized conditions against different factors was carried out
for the following parameters:
3.8.1 Effect of pH
Freshly prepared nanoemulsion samples (optimized conditions) were placed
in 50 ml beakers and pH of these samples was adjusted between 2 to 8. After that,
these samples were stored in test tubes at ambient temperature. After storage (12
hours), particle size, and creaming stability of these samples were measured
according to the method given by Ozturk et al., (2014).
3.8.2 Effect of Ionic Strength Variation
Freshly prepared beta carotene and vitamin D nanoemulsion sample (optimized
conditions) was adjusted for salt concentration (50-400 mM) by adding 1M NaCl
or buffer solutions. These samples were subjected to vortex, followed by storage at
ambient temperature for 12 hours. The particle size and creaming stability was
measured after desired time according to the method given by Ozturk et al., (2014).
3.8.3 Thermal Stability
Freshly prepared nanoemulsion samples (optimized conditions) were
48
transferred to glass test tubes and these test tubes were kept at different
temperatures (30-90 °C) in water bath. These samples were mixed and stored for
48 hours prior to their analysis for particle size and creaming stability by following
the method of Ozturk et al., (2014).
3.8.4 Physical Stability
Selected nanoemulsion formulations (optimized conditions) were subjected
to alternate freeze and thaw cycle (12 h) for 4 cycles to determine their physical
stability. The samples were stored in plastic bottles for 12 h at -18 ºC and
subsequently at room temperature (25 ºC) for 2 hour duration. After that, particle
size was determined before subjecting these nanoemulsions to next cycle. Particle
size analyzer was used for measuring stability, transparent appearance and particle
size as described by (Donsì et al., 2011c).
3.9 ANIMAL STUDIES
3.9.1 In Vivo Toxicity of Encapsulated Beta Carotene
Albino mice were used as test animals to investigate the toxic effects of
nanoparticles. These mice (n = 30) with initial body weight of 25± 5 g were
purchased from National Institute of Health (NIH), Islamabad. The sample size was
selected on the basis of power analysis. Power calculations were done using G
power software. These mice were acclimatized for one week before the start of
experiment. During experiment, mice were housed in controlled temperature 27±3
with 12 hours of light-dark cycle and free access was provided to water and food
(beta carotene or vitamin A deficient food). Iso-caloric diet was provided to all
mice. In addition to standard diet, these mice were given nanoemulsions containing
different concentration of beta carotene. These mice were randomly divided into
49
six groups: Group A (control group), Group B (oral dose of blank nanoemulsion
(without beta carotene), Group C (oral dose of vitamin beta carotene nanoemulsion,
9000 IU/Kg body weight), Group D (oral dose of beta carotene nanoemulsion,
12000 IU/Kg body weight), Group E (oral dose of beta carotene nanoemulsion,
16000 IU/Kg body weight) and Group F (oral dose of fat soluble beta carotene,
9000 IU/Kg body weight). These animals were monitored against the sign of
toxicity and changes in weight. After 21 days, blood samples of these animals were
collected to investigate their biochemistry and hematology (Sonaje et al., 2009).
All research was carried out in strict compliance with the approved protocols of
PMAS-Arid Agriculture University Institutional Animal Care and Use Committee.
Approval from ethical committee is given in appendix 1.
3.9.2 In Vivo Toxicity of Encapsulated Vitamin D
Albino mice were used as test animals to investigate the toxic effects of
nanoparticles. These mice (n = 30) with initial body weight of 27±5 g were
purchased from National Institute of Health (NIH), Islamabad. The sample size was
selected on the basis of power analysis. Power calculations were done using G
power software. These mice were acclimatized for one week before the start of
experiment. During experiment, mice were housed in controlled temperature 27±3
with 12 hours of light-dark cycle and free access was provided to water and food
(vitamin D deficient food). Iso-caloric diet was provided to all mice. In addition to
standard diet, these mice were given nanoemulsions containing different
concentration of beta carotene. These mice were randomly divided into six groups:
Group A (control group), Group B (oral dose of blank nanoemulsion (without
vitamin D), Group C (oral dose of vitamin D nanoemulsion, 1800 IU/Kg body
50
weight), Group D (oral dose of vitamin D nanoemulsion, 2500 IU/Kg body
weight), Group E (oral dose of vitamin D nanoemulsion, 3000 IU/Kg body weight)
and Group F (oral dose of fat-soluble vitamin D, 1800 IU/Kg body weight). These
animals were monitored against the sign of toxicity and changes in weight. After
21 days, blood samples of these mice groups were collected in order to investigate
nuclear abnormalities as well as genotoxicity. All research was carried out in strict
compliance with the approved protocols of PMAS-Arid Agriculture University
Institutional Animal Care and Use Committee. Approval from ethical committee is
given in appendix 1.
3.9.3 Nuclear Abnormalities Analysis
Before the separation of lymphocytes from whole blood, smear slides were
prepared using cleaned and new glass slides. Later on, these slides were fixed using
methanol for 10 minutes and left for air drying at room temperature. After that,
these slides are stained using 6% May Grunwald-Giemsa in Sorenson Buffer (pH is
adjusted to 6.9). Five slides were prepared for each experimental animal and these
slides were labeled and scored blindly under magnification of 1000X. 100
lymphocytes were observed on each slide and the percentage of bi-nuclear and
multi-nuclear lymphocytes were reported as follows:
Bi-nuclear or Multi-nuclear (%) = Damaged Cells/ Total Cells x 100
3.9.4 Comet Assay
Comet assay is a rapid, simple and sensitive technique for detection of damage
in DNA (DNA-protein and DNA-DNA crosslinks and single or double strand
break) for single cells (Fairbairn et al., 1995). Hence, it is a useful tool for the
investigation of genetic toxicology. Mostly this technique was used for mammalian
51
cells but some studies are also carried out on other organisms (Klobučar et al.,
2003).
Comet assay was performed by following the guidelines and
recommendation of previous studies (Singh et al., 1988; Smith et al., 2008). Fully
frosted slides were covered using 100 μl of 0.9% HMP agarose. Meanwhile,
lymphocyte suspension (25 μl) was added to 0.8% low melting agarose. This
mixture was poured on precoated slides containing HMP agarose layer and allowed
to polymerize for 10 min. at 4 °C. After solidification of gel, these slides (coverslip
removed) were immersed in cold lysis solution (2.5 M NaCl, 10mM Tris-HCl, 100
mM Na2EDTA, DMSO 10% and 1% Triton X-100) at 4 °C for 1.5 hours. After
that, deionized water was used for the washing of these slides (3-4 times). These
slides were then kept in alkaline buffer (300 mM NaOH, 1 mM Na2EDTA; pH
value 13) at room temperature for 30 minutes for unwinding of DNA.
Electrophoresis was performed at 320 mA for 25 minutes on horizontal platform by
using ice-cold and fresh alkaline buffer. After that, slides were drained and slowly
washed with neutralization buffer (Tris-HCl (0.4M with 7.5 pH) for 5 minutes. The
whole neutralization procedure was performed three times. Artefactual damage of
DNA was minimized by performing comet assay in dim-light and covering of
electrophoresis tank with black paper. For positive control, control group
lymphocytes were treated H2O2 (150 μM) for one hour at the temperature of 4 °C.
3.9.4.1 Procedure for staining
Slides were stained with 10% ethidium bromide for ten minutes. After that,
excessive ethidium bromide was taking out by curving these slides in chilled
distilled water. Subsequently, coverslips were placed over these slides. Gel drying
52
was prevented during slide scoring by placing slides in dark humidified chamber.
Scoring of slides was performed within 5 hours after staining.
3.9.4.2 Slides scoring
Analysis of slides was performed using Ceti Magnum-T epifluorescence
microscope equipped with 460-550 nm excitation filters. 40X objective lens were
used to capture microphotographs. DNA damage was quantified in term of tail
length, tail DNA and olive moment. The data was obtained from 500 randomly
selected cells from each group of animals.
3.10 DEVELOPMENT OF BETA CAROTENE AND VITAMIN D
FORTIFIED BEVERAGES
Model beverages were developed with added beta carotene and vitamin D.
Firstly, 8% sucrose, 0.1% ascorbic acid and 0.16% citric acid were mixed with
71.67% of water. Then, orange flavor (0.07%) and beta carotene or vitamin D
nanoemulsions (20 g) were being added. After that, all ingredients were thoroughly
mixed using magnetic stirrer. Beta carotene and vitamin D nanoemulsions were
prepared by following the method which is mentioned in nanoemulsion preparation
section. Final concentrations of beta carotene and vitamin D in nanoemulsions were
0.05 mg/ml. These model beverages were filled in sterilized glass bottles. After
that, these beverages were analyzed through visual appearance, pH, viscosity and
°Brix (Kim et al., 2014).
3.10.1 Viscosity
Viscosity of beta carotene and vitamin D fortified beverages was measured
using digital viscometer (DVE, Brookfield, USA). Viscosity was measured at 100
rpm using spindle no 2.
53
3.10.2 °Brix
°Brix of beta carotene and vitamin D fortified beverages was measured using
handheld refractometer (Master-50H, Atago, USA).
3.10.3 Sensory Evaluation
The sensory evaluation of the beta carotene and vitamin D fortified
beverages was conducted by a panel of trained judges. These beverages were
evaluated against different attributes such as taste, flavor, color and overall
acceptability. Fortified beverages samples were scored against nine point hedonic
scale which is given in appendix 2 (Larmond, 1977).
3.11 STATISTICAL ANALYSIS
For the optimization of the preparation conditions of nanoemulsions,
response surface methodology was used. Experimental data was analyzed through
analysis of variance (ANOVA) and Tukey HSD test. All these measurements were
performed three times and the results of these measurements were reported as
means and standard deviation and interpreted as described by Steel and Torrie,
(1980).
54
Chapter 4
RESULTS AND DISCUSSIONS
4.1 CHARACTERIZATION OF NANOEMULSION COMPONENTS
Physico-chemical properties of different components of nanoemulsions are
summarized in Table 4.1. Canola oil has lower viscosity (51.60 ± 0.8 mPa s) as
compared to olive oil (78.60 ± 1.1 mPa s). As a result of this, smaller droplet size
nanoemulsion will be produced in the case of canola oil as compared to olive oil.
The viscosity ratio between disperse and continuos phase has pronounced effect on
the droplet size of nanoemulsion. Smaller droplets were produced when the value
of viscosity ratio is closure to unity (Walstra, 1993). Furthermore, the viscosity
difference can be minimized by variation in surfactants. Canola oil has more
density (920 ± 1 kg m-3
) as compared to olive oil (915 ± 1 kg m-3
). Hence, canola
oil based nanoemulsions will be more stable because of the gravitational separation
of nanoemulsions which depend on density difference between continuous and
disperse phase(Mcclements, 2011). Nanoemulsion prepared from canola and olive
oil will be stable against gravitational separation due to smaller density difference
between aqueous and disperse phase. Additionally, that difference can be further
minimized by using Tween 80 and soy lecithin which lead to development of
nanoemulsions which are stable against gravitational separation. Interfacial tension
also influences the droplet size on nanoemulsions. Interfacial tension value of olive
oil (33.7 ± 0.9 mN m-1
) was higher than canola oil (28.5 ± 0.6 mN m-1
). As a result
of this, higher droplet size will be produced in olive oil based nanoemulsion as
compared to canola oil. When the value of interfacial tension was higher, the larger
droplets were produced due to more energy requirements (Mehmood, 2015).
54
55
Table 4.1: Physicochemical properties of different components of beta carotene and
vitamin D nanoemulsions
Components Viscosity
(mPa s)
Density
(kg m-3
)
Interfacial tension
(mN m-1
)
Canola Oil 51.60 ± 0.8 920 ± 1 28.5 ± 0.6
Olive Oil 78.60 ± 1.1 915 ± 1 33.7 ± 0.9
Tween 80 373 ± 1.6 1088 ± 1 --------------
Lecithin 8000 ± 3.5 1059 ± 1 --------------
56
Surfactants have the ability to lower down interfacial tension and creation of
smaller droplets (Mehmood, 2015).
4.2 OPTIMIZATION OF BETA CAROTENE NANOEMULSIONS
4.2.1 Fitting the Model
Response surface methodology (RSM) is a statistical, theoretical and
mathematical technique for model building in order to optimize the level of
independent variables (Homayoonfal et al., 2015). The effect of independent
variables on droplet size (Y1), p-Anisidine value (Y2) and retention of beta carotene
(Y3) have been presented in Table 4.2. Coefficients of polynomial equation were
computed from experimental data to predict the values of response variable.
Regression equations for each response variable, obtained from response surface
methodology are mentioned in equation 11-13:
Droplet Size = +114.85 – 5.44X1 - 8.01X2 + 2.55X3 + 6.13X12 – 3.95X2
2 +
0.82X32 – 2.88X1X2 - 1.38X1X3 - 0.88X2X3 (11)
p-Anisidine Value = +3.66 – 1.48X1 + 0.64X2 + 1.31X3 + 0.41X12 + 0.43X2
2 +
0.69X32 – 0.038X1X2 + 0.19X1X3 - 0.037X2X3 (12)
β-Carotene Retention = +79.43 + 9.82X1 – 2.42X2 - 3.21X3 - 3.21X12 –
4.27X22 + 2.09X3
2 – 2.37X1X2 - 0.87X1X3 + 0.38X2X3 (13)
Statistical analysis (ANOVA) results revealed that the experimental data
could be represented well with quadratic polynomial model with the coefficient of
determination (R2) values for droplet size (Y1), p-Anisidine value (Y2) and
retention of beta carotene (Y3) being 0.9456, 0.9580 and 0.9604, respectively
(Table 4.3). Lack of fit was non-significant (p≤0.05) relative to pure error for all
57
Table 4.2: Effect of independent variables on responses for mixed surfactant based
β-carotene nanoemulsions
Run
Independent Variables Response Values
Surfactant
(%)
Time
(Min.)
Oil
Content
(%)
Droplet
Size
(nm)
p-Anisidine
Value
β- Carotene
retention
(%)
1 8 4 6.50 121±4 1.5±0.2 94±1
2 6 5.50 8 110±2 3.2±0.4 77±5
3 4 7 6.50 115±5 6.3±0.8 64±3
4 6 5.50 5.48 111±4 3.3±0.3 92±3
5 8 4 9.50 125±5 5.2±0.3 84±2
6 6 8.02 8 89±3 5.6±0.2 66±3
7 9.36 5.50 8 122±2 2.1±0.1 86±1
8 6 5.50 10.52 124±2 7.1±0.4 82±4
9 6 5.50 8 114±1 4.1±0.4 80±4
10 6 5.50 8 110±4 3.7±0.2 76±3
11 8 7 9.50 101±3 5.9±0.3 75±2
12 8 7 6.50 104±2 3.1±0.2 82±2
13 6 5.50 8 117±3 3.6±0.1 83±4
14 6 5.50 8 121±2 3.5±0.2 80±1
15 4 4 6.50 124±4 5.3±0.3 65±2
16 4 4 9.50 130±6 7.5±0.6 60±4
17 6 5.50 8 117±2 4±0.3 80±3
18 2.64 5.50 8 143±3 6.7±0.5 58±3
19 6 2.98 8 119±3 3.3±0.4 72±2
20 4 7 9.50 121±1 9.1±0.4 59±1
58
variables which indicate that our model is statistically accurate. If the value of R2 is
closer to unity then it is the indication of better model fitting to actual data. On the
other end, lower values of R2 indicate that response variables were not appropriate
to explain the variation in behavior (Myers et al., 2016). In the present study,
closure to unity R2 demonstrates that the influence of surfactant concentration (X1),
Ultrasonic Homogenization time (X2) and oil contents (X3) on response variables
could be adequately described through quadratic polynomial model. Significance
level for coefficients of quadratic polynomial model was determined through
analysis of variance (ANOVA). Smaller p-value and larger F-value is the indication
for the highly significant effect of any term on response variable (Quanhong and
Caili, 2005).
4.2.2 Effect of Independent Variables on Response Variables
β-Carotene nanoemulsions were successfully prepared by using different
level of independent variables (Figure 4.1).The effect of independent variables on
droplet size, p-anisidine value and beta carotene retention are given in Table 4.2.
Regression coefficients for independent variables are summarized in Table 4.3.
4.2.2.1 Droplet size
The droplet size of beta carotene nanoemulsions was mainly depended on
surfactant concentration due to its significant effect on droplet size at linear (p <
0.001), quadratic (p < 0.001) and interaction level (p < 0.05) with homogenization
time. Surfactants lower the interfacial tensions between disperse and continuous
phase which leads to smaller droplet formation (Mehmood et al., 2017). Other
independent variables which have significant effect on droplet size were linear term
of homogenization time (p < 0.001) and oil content (p < 0.05), and quadratic terms
59
Table 4.3: Regression coefficients for beta carotene nanoemulsions
Regression
Coefficients
Droplet size
(nm)
p-Anisidine
Value
β- Carotene Retention
(%)
Intercept (α0) 114.85 3.66 79.43
A-Surfactant (α1) -5.44*** -1.48*** 9.82***
B-Time (α2) -8.01***
0.64** -2.42*
C-Oil (α3) 2.55* 1.31*** -3.21**
A2 (α11) 6.13*** 0.41* -3.21**
B2 (α22) -3.95** 0.43* -4.27***
C2 (α33) 0.82 0.69*** 2.09*
AB (α12) -2.88* -0.038 -2.37*
AC (α13) -1.38 0.19 -0.87
BC (α23) -0.88 -0.037 0.38
R2
0.9456 0.9580 0.9604
*Significant at 0.05 level, **Significant at 0.01 level, ***Significant at 0.001 level
60
of homogenization time (p < 0.001). The influence of homogenization time and
surfactant concentration on droplet size of β-carotene nanoemulsions is illustrated
in Figure 4.2 (A). Both these variables exert quadratic effect on droplet size. At
higher surfactant concentration, decrease in droplet size of nanoemulsions was
observed with the increase of homogenization time. This downward trend was
observed due to reduction of interfacial tension with the increase in surfactant
concentration (Polychniatou and Tzia, 2018). At lower surfactant concentration,
droplet size increased with increasing homogenization time. This increase was
observed because enough emulsifier is not present to cover newly formed smaller
droplets which initiate coalescence process (Anarjan et al., 2010).
Figure 4.2 (B) represented the combined effect of oil and surfactant
concentration on the droplet of β-carotene nanoemulsions. Oil content exerts linear
effect while surfactant concentrations have quadratic effect on droplet size of
nanoemulsions. Droplet size increased with rising oil concentration due to increase
in viscosity. As a result of this, higher energy is required to break the droplet which
results in larger droplet size. Additionally, higher oil concentration encourages
aggregation and collision of nanoemulsion droplets which increased the droplet
size (Mehmood, 2015; Zhang et al., 2009). Initially, droplet size decreased with
higher surfactant concentration due to reduction in surface tension. But, after a
minimal level, higher concentration of surfactant caused increased width of
diffusion layer due to excessive coverage of crystalline particles by surfactant. This
mechanism lowers zeta potential value and encourages agglomeration tendency
which increased droplet size of food grade mixed surfactant based β-carotene
nanoemulsions (Mehmood et al., 2017; Tan et al., 2010).
61
Figure 4.1: (A) Particle size distribution of β-carotene nanoemulsions (D4,3) (B)
Visual appearance of β-carotene nanoemulsions
62
Figure 4.2: 3D graphic surface optimization of (A) droplet size D4,3 (nm) versus
surfactant concentration (%) and homogenization time (Min.) (B) droplet size D4,3
(nm) versus oil content (%) and surfactant concentration (%) (C) p-Anisidine value
versus surfactant concentration (%) and homogenization time (Min.) (D) p-
Anisidine value versus oil content (%) and surfactant concentration (%) (E) β-
carotene retention (%) versus surfactant concentration (%) and homogenization
time (Min.) (F) β-carotene retention (%) versus oil content (%) and surfactant
concentration (%)
63
4.2.2.2 p-Anisidine value
p-Anisidine value is an important indicator for measurement of oxidation
products (Cho et al., 2008). As the p-Anisidine value of β-carotene nanoemulsions
was concerned, oil content had significant effect on the p-Anisidine value of β-
carotene nanoemulsions due to its significant effect on p-Anisidine value at linear
(p < 0.001) and quadratic level (p < 0.001). Other factors which significantly
contributes toward p-Anisidine value were linear term of surfactant concentration
(p < 0.001) and homogenization time (p < 0.001), and quadratic term of surfactant
concentration (p < 0.05) and homogenization time (p < 0.05). The lipid oxidation
mechanism is remarkably different in nanoemulsions as compared with bulk oily
phase due to the presence of interface and aqueous phase. In nanoemulsions, lipid
oxidation depends on many factors which include pH, oxygen concentration and
ionic strength of continuous phase, droplet size, thickness and interfacial properties
(Öztürk et al., 2017; Waraho et al., 2011).
The combined effects of homogenization time and surfactant concentration
on p-Anisidine value are illustrated in Figure 4.2 (C) which explicated the linear
effect of both independent variables on p-Anisidine value. When homogenization
time increased, p-Anisidine value also increases while increase in surfactant
concentration results in lower p-Anisidine value. During this study, β-carotene
nanoemulsions were developed using mixed surfactant (Tween 80 and soy lecithin)
which act as interfacial barrier against oxidation. These surfactants built a
protective membrane at interface of aqueous and oily phase which remarkably
reduce pro-oxidant accessibility into oil droplets which results in lower p-Anisidine
value (Hwang et al., 2017). Figure 4.2 (D) depicts the interactive effect of oil
64
content and surfactant concentration on p-Anisidine value. Both variables have
linear effect on p-Anisidine value of β-carotene nanoemulsions. The downward
trend was observed in p-Anisidine value with the increase of surfactant and oil
concentration. Oil concentrations have inverse effect on p-anisidine value because
droplet size increase when oil concentration is more which results in lower p-
Anisidine value due to reduced surface area for oxidation (Mehmood et al., 2017).
4.2.2.3 β-Carotene retention
β-Carotene retention of nanoemulsion was mainly depend on surfactant
concentration as it had significant effect on vitamin retention at linear (p < 0.001),
quadratic (p < 0.01) and interactive level (p < 0.05). Surfactant prevents the
degradation of β-carotene by forming membrane-like structure around new surfaces
(Hejri et al., 2013). Other factors which significantly contributed to β-carotene
retention were linear effect of homogenization time (p < 0.05) and oil content (p <
0.01), quadratic effect of homogenization time (p < 0.001) and oil content (p <
0.05) and interactive effect of homogenization time (p < 0.05).
A contour plot in Fig. 4.2 (E) illustrates the retention of β-carotene as a
function of homogenization time and surfactant concentration. Surfactant
concentrations have linear effect while homogenization time exerts quadratic effect
on the retention of β-carotene. Pre-existence of peroxides in surfactant molecule
cause β-carotene degradation. These peroxides break down into reactive radicals at
elevated temperature and significantly degrade β-carotene during storage (Liu and
Wu, 2010). Fig. 4.2 (F) represents the interactive effect of oil content and
surfactant concentration of the β-carotene retention in nanoemulsions. Surfactants
exert quadratic effect while oil has linear effect on β-carotene retention. With the
65
increase in surfactant concentration, degradation of β-carotene reduced due to the
formation of rigid surfactant shell at water-oil interface. This shell increases the
stability of β-carotene by preventing repulsion of β-carotene and avoiding new
surfaces formation (Hejri et al., 2013). Higher oil content also increases the
stability of β-carotene nanoemulsions by formation of larger droplets which have
lower surface area (Liu and Wu, 2010).
4.2.3 Optimization of Independent Variables
To illustrate the effects of surfactant concentration, homogenization time
and oil content on response variables, response surface graphs were drawn using
design expert software. These graphs were generated by varying two independent
variables within experimental ranges while keeping the third variable at central
point. Fig. 4.2 (A, C and E) were generated by varying the concentration of
surfactant concentration and homogenization time at 8% oil contents while Fig. 4.2
(B, D and F) were drawn by changing the concentration of oil and surfactant at
central value of homogenization time (5.5 Min.). These graphs illustrated complex
interaction among independent variables.
By setting the partial derivatives of droplet size regression equation (11) at
zero, following three equations can be constructed:
-12.16 + 3.06 X1 – 0.96 X2 – 0.46 X3 = 0, (14)
22.83 – 0.96 X1 – 3.52 X2 – 0.39 X3 = 0, (15)
0.74 – 0.46 X1 – 0.39 X2 + 0.74 X3 = 0 (16)
By setting the partial derivatives of p-Anisidine value regression equation
(12) at zero, following three equations can be constructed:
66
-2.40 + 0.20 X1 – 0.013 X2 + 0.063 X3 = 0, (17)
- 1.46 – 0.013 X1 + 0.38 X2 – 0.017 X3 = 0, (18)
- 4.34 + 0.063 X1 – 0.017 X2 + 0.62 X3 = 0 (19)
By setting the partial derivatives of beta carotene retention regression
equation (13) at zero, following three equations can be constructed:
21.23 - 1.60 X1 – 0.79 X2 – 0.29 X3 = 0, (20)
22.68 – 0.79 X1 – 3.80 X2 + 0.17 X3 = 0, (21)
- 16.19 – 0.29 X1 + 0.17 X2 + 1.86 X3 = 0 (22)
Following results were obtained after solving these equations 14-22:
X1 = 5.88%, X2 = 4.07 min and X3 = 6.50%
4.2.4 Verification of RSM Model
Optimized emulsifying conditions were used to check the suitability of the
model for prediction of response values. Optimized preparation conditions were
validated by conducting experiments under optimized conditions. The predicted
response values at optimized preparation conditions were 116.44 nm droplet size,
2.89 p-Anisidine value and 82.71% β-carotene retention. On the other hand, the
experimental values of response were 119.33nm droplet size, 2.67 p-Anisidine
value and 85.63% β-carotene retention (Table 4.4). Experimental response values
were well in agreement with predicted response values.
4.3 OPTIMIZATION OF VITAMIN D NANOEMULSIONS
4.3.1 Fitting the Model
Response surface methodology (RSM) is a statistical, theoretical and mathematical
67
technique for model building in order to optimize the level of independent variables
(Tan et al., 2016). The effect of independent variables (vitamin D nanoemulsions)
on droplet size (Y1), droplet growth ratio (Y2) and retention of vitamin D (Y3) are
given in Table 4.5. Coefficients of the polynomial equation were computed from
experimental data to predict the values of response variable. Regression equations
for each response variable, obtained from response surface methodology are
mentioned in Eq. 23-25:
Droplet Size = +120.32 - 14.74Y1 - 9.11Y2 +6.42Y3 – 4.60Y12 – 3.79Y2
2 –
1.06Y32 – 1.00Y1Y2 – 5.25Y1Y3 – 1.50Y2Y3 (23)
Droplet Growth Ratio = +0.16 + 0.024Y1 – 0.042Y2 + 7.35Y3 + 0.021Y12 +
0.036Y22 + 4.80Y3
2 – 0.032Y1Y2 + 5.75Y1Y3 + 9.00Y2Y3 (24)
Vitamin D Retention = + 72.87 + 4.63Y1 + 6.95Y2 + 1.61Y3 – 2.62Y12 +
2.86Y22 + 3.92Y3
2 + 1.63Y1Y2 – 0.12Y1Y3 – 3.12Y2Y3 (25)
Statistical analysis (ANOVA) results revealed that the experimental data
could be represented well with quadratic polynomial model with coefficient of
determination (R2) values for droplet size (Y1), droplet growth ratio (Y2) and
retention of vitamin D (Y3) being 0.9524, 0.9791 and 0.9513, respectively (Table
4.6).
Lack of fit was non-significant (p≤0.05) relative to pure error for all
variables which indicate that our model is statistically accurate. If the value of R2 is
closer to unity then it is the indication of better model fitting to actual data. On the
other end, lower values of R2 indicate that response variables were not appropriate
to explain the variation in behavior (Myers et al., 2016). In our study, all response
variables have values closure to unity (Table 4.6).
68
Table 4.4: Optimum preparation conditions and response value for β-carotene
nanoemulsions
Optimum Conditions Coded Levels Actual Levels
Surfactant Concentration (%) -0.06 5.88
Homogenization Time (Min.) -0.95 4.07
Oil Contents (%) -1.00 6.50
Response Predicted Values Experimental Values
Droplet Size (nm) 116.44 119.33 ± 2.5
p-Anisidine Value 2.89 2.67 ± 0.9
β- Carotene Retention (%) 82.71 85.63 ± 1.5
69
Table 4.5: Effect of independent variable on responses for optimization of vitamin
D nanoemulsions
Run
Independent Variables Response Values
HT1
(Min.)
S/O2
Ratio
DPV3
(%)
Droplet
Size
(nm)
Droplet
Growth
Ratio
Vitamin D
Retention
(%)
1 5 0.6 9.68 130 0.168 86
2 5 0.90 8 111 0.172 91
3 6.5 0.78 7 84 0.146 94
4 5 0.60 8 115 0.148 69
5 3.50 0.78 9 130 0.208 78
6 3.50 0.43 9 153 0.205 69
7 5 0.60 8 121 0.157 74
8 6.50 0.78 9 85 0.202 89
9 7.52 0.60 8 90 0.256 72
10 2.48 0.60 8 130 0.165 60
11 3.50 0.78 7 110 0.182 77
12 5 0.60 8 125 0.162 72
13 6.50 0.43 7 105 0.305 66
14 5 0.60 8 117 0.164 72
15 5 0.60 8 123 0.163 74
16 3.50 0.43 7 125 0.208 61
17 5 0.31 8 135 0.333 72
18 5 0.60 8 120 0.15 76
19 5 0.60 6.32 110 0.163 83
20 6.50 0.43 9 110 0.318 79
1 HT, Homogenization Time;
2S/O Ratio, Surfactant to Oil Ratio;
3DPV, Disperse
Phase Volume
70
In our study, closure to unity R2 demonstrates that the influence of ultrasonic
homogenization time (X1), surfactant to oil ratio (X2) and disperse phase volume
(X3) on response variables could be adequately described through the quadratic
polynomial model. Significance level for coefficients of quadratic polynomial
model was determined through analysis of variance (ANOVA). Smaller p-value
and larger F-value are important indication for highly significant effect of any term
on response variable (Mehmood, 2015).
4.3.2 Effects of Independent Variables on Responses
Vitamin D nanoemulsions were successfully prepared by using different
level of independent variables (Figure 4.3). The effects of independent variables on
the response variables (Droplet size, droplet growth ratio and vitamin D retention)
are given in Table 4.5 while the values of regression coefficients of responses are
summarized in Table 4.6.
4.3.2.1 Droplet size
The droplet size of vitamin D nanoemulsion was mainly depended on the
homogenization time as it had a significant effect on the size of the droplet at linear
(p < 0.001), quadratic (p < 0.01) and interactive term with surfactant to oil ratio (p
< 0.05). When sufficient amount of surfactant is available, the droplet size of
nanoemulsion significantly reduced with higher homogenization time due to
increase in shear and cavitation forces (Anarjan et al., 2010). Other factors which
significantly affect droplet size were linear terms of surfactant to oil ratio (p <
0.001) and disperse phase volume (p < 0.001).
The interactive effects of homogenization time and surfactant to oil ratio on
droplet size of food grade vitamin D nanoemulsions are depicted in Figure 4.4 (A).
71
Table 4.6: Regression coefficients values for vitamin D nanoemulsions
Regression
coefficients
Droplet size
(nm)
Droplet Growth
Ratio
Vitamin D Retention
(%)
Intercept (α0) 120.32 0.16 72.87
A-Time (α1) -14.74*** 0.024*** 4.63***
B-S/O Ratio (α2) -9.11***
-0.042*** 6.95***
C-DPV (α3) 6.42*** 7.352* 1.61
A2 (α11) -4.60** 0.021*** -2.62**
B2 (α22) -3.798 0.036*** 2.86**
C2 (α33) -1.06 4.805 3.92***
AB (α12) -1.00 -0.032*** 1.63
AC (α13) -5.25* 5.750 -0.12
BC (α23) -1.50 9.00 -3.12*
R2
0.9524 0.9791 0.9513
*Significant at 0.05 level, **Significant at 0.01 level, ***Significant at 0.001 level
72
Both these variables exert linear effect on nanoemulsions droplet size. Direct
relation was reported between the droplet size and homogenization time. Droplet
size of vitamin D nanoemulsions reduced with higher homogenization time due to
the generation of strong shear forces by ultrasonic homogenizer. When
nanoemulsions particles are subjected to these shear forces for the longer time, then
it leads to disruption of larger droplets into smaller one (Carpenter and Saharan,
2017). When surfactant to oil ratio was increased, the interfacial tension of the
system was reduced which results in smaller droplet size (Homayoonfal et al.,
2014).
The interactive terms of disperse phase volume and surfactant to oil ratio on
droplet size is shown in Fig. 4 (B). Both these variables exert linear effect on
nanoemulsions droplet size. The smaller droplets were produced during ultrasonic
homogenization at lower disperse phase volume and gradually increase with the
rise in DPV proportion when the concentration of surfactants remains constant.
Surfactant to oil ratio increased at lower disperse phase volume which results in
smaller droplet size due to higher value of interfacial tension and presence of
enough emulsifier to hold newly formed droplets (Ziani et al., 2012). Another
possible reason is that viscosity value of dispersed phase may increase with the
increase of disperse phase volume. Due to increase in viscosity, the disruption of
droplet became more difficult which results in larger droplet size (Mcclements et
al., 2007). A similar result was reported by the previous study regarding the change
of particle structure with the viscosity change (Feng et al., 2009). .
4.3.2.2 Droplet growth ratio
Droplet growth ratio is an important indicator of the stability of nanoemulsions.
73
Figure 4.3: (A) Particle size distribution of vitamin D nanoemulsions (D4,3) (B)
Visual appearance of vitamin D nanoemulsions
74
The DGR of vitamin D nanoemulsion was mainly depended on the homogenization
time and surfactant to oil ratio as these had significant effects on the droplet growth
ratio at linear (p < 0.001), quadratic (p < 0.001) and interactive level (p < 0.001).
Droplet growth ratio of nanoemulsion was reduced with the increase of surfactant
because the newly formed droplets produced during ultrasonic homogenization
were stabilized by the surfactant molecules which prevent them from coalescence
and flocculation (Ahmad et al., 2011). Other factors which had pronounced effects
on the DGR of vitamin D nanoemulsions were the linear term of disperse phase
volume (p < 0.05).
The combined effects of homogenization time and surfactant to oil ratio on
droplet growth ratio of nanoemulsion is explicated in Fig. 4 (C) Both had quadratic
effect on the DRG of oil-in-water nanoemulsions. In the presence of higher
concentration of surfactant, droplet growth ratio was significantly reduced with the
increase in homogenization time due to the formation of smaller size droplets
(covered by surfactant) which were stable against aggregation, coalescence and
flocculation (Mehmood et al., 2017). The nanoemulsions under study exhibit more
stability against droplet growth ratio as compared to other nanoemulsions with
single surfactants (Khalid et al., 2017). This stability was achieved by using mixed
surfactants (Soya lecithin and Tween 80) which significantly enhance the loading
capacity and reduce interfacial tension of dispersed phase by developing
intercalating structure at the interface of water/oil (Cilek et al., 2006; Mehmood et
al., 2017). Higher surfactant to oil ratio had negative influence on droplet growth
ratio. The possible reason behind it is the movement of oil droplets through
surfactant micelles which increase the rate of particle growth (Weiss et al., 2000).
75
Figure 4.4: 3D graphic surface optimization of (A) droplet size D4,3 (nm) versus
S/O ratio and homogenization time (Min.) (B) droplet size D4,3 (nm) versus
disperse phase volume (%) and S/O ratio (C) Droplet growth ratio versus S/O ratio
and homogenization time (Min.) (D) Droplet growth ratio versus disperse phase
volume (%) and S/O ratio (E) Vitamin D retention (%) versus S/O ratio and
homogenization time (Min.) (F) Vitamin D retention (%) versus disperse phase
volume (%) and S/O ratio
76
The interactive effects of surfactant to oil ratio and disperse phase volume are
shown in Figure 4.4 (D). Disperse phase volume has quadratic effects while S/O
ratio has linear effect on the droplet growth ratio of nanoemulsions. Initially,
droplet growth reduced with increase in DPV but higher disperse phase volume
proportion increase DGR by increasing the interfacial tension at water/oil interface.
Hence, larger size droplets were produced which were less stable as
compared to smaller size droplets (Mehmood, 2015). Surfactant to oil ratio has
significant effect on droplet growth ratio. The value of DGR reduced with increase
in S/O ratio because surfactant decreases the interfacial tension between water and
oil interface. Hence, smaller droplets were produced which were more stable than
larger droplets (Homayoonfal et al., 2014).
4.3.2.3 Vitamin D retention
The retention of vitamin D in nanoemulsion was mainly depended on
surfactant to oil ratio as it had a significant effect on the retention of vitamin D at
linear (p < 0.001), quadratic (p < 0.01) and interactive term with disperse phase
volume (p < 0.05). Surfactant prevents the degradation of vitamin D by forming
membrane-like structure around new surfaces (Hejri et al., 2013). Other factors
which significantly affect vitamin D retention were linear terms of homogenization
time (p < 0.001) and quadratic terms of homogenization time (p < 0.01) and
disperse phase volume (p < 0.001).
The interactive effects of homogenization time and surfactant to oil ratio on
retention of vitamin D are depicted in Fig. 4 (E). Both these variables exert linear
effect on vitamin D retention. In the presence of sufficient surfactant, vitamin D
retention improved with increasing homogenization time due to its effects on the
77
adsorption of surfactants around droplets and particle size distribution (Li and
Chiang, 2012). With the increase in surfactant concentration, degradation of
vitamin reduced due to the formation of rigid surfactant shell at water-oil interface.
This shell increases the stability of vitamin D by preventing repulsion of vitamin D
and avoiding new surfaces formation (Hejri et al., 2013).
The interactive terms of disperse phase volume and surfactant to oil ratio on
vitamin D retention are shown in Fig. 4 (F). Both these variables exert linear effect
on vitamin D retention. The nanoemulsions under study exhibit more stability
against vitamin D gradation as compared to other nanoemulsions with single
surfactants (Khalid et al., 2017). This stability was achieved by using mixed
surfactants (Soya lecithin and Tween 80) which significantly enhance the loading
capacity and reduce interfacial tension of dispersed phase by developing
intercalating structure at the interface of water/oil (Cilek et al., 2006; Mehmood,
2015). Higher oil content also increases the stability of vitamin D nanoemulsions
by formation of larger droplets which have lower surface area (Liu and Wu, 2010).
4.3.3 Optimization of Emulsifying Conditions for Vitamin D Nanoemulsions
The effects of emulsifying conditions on responses were visualized through
plotting response surfaces by using Software (Design Expert). For obtaining
optimum conditions for independent variables, graphs of droplet size, droplet
growth ratio and vitamin D retention were drawn (Figure 4.4). These optimization
graphs were created by keeping two independent variables at central values while
changing the values of other two variables. Figure 4.4 (A, C and E) were generated
by changing the concentrations of S/O ratio and homogenization time at 8%
disperse phase volume. By keeping the values of homogenization time at 5
78
Minutes, response plots. Fig. 4 (B, D and F) were drawn by varying the
concentrations of S/O ratio and disperse phase volume. In general, complex levels
of interactions were observed among these variables.
By setting the partial derivatives of droplet size regression equation (23) at
zero, following three equations can be constructed:
40.92 - 4.08 X1 – 3.81 X2 – 3.50 X3 = 0, (26)
35.73 – 3.81 X1 – 0.24 X2 – 8.57 X3 = 0, (27)
46.13 – 3.50 X1 – 8.57 X2 - 2.12 X3 = 0 (28)
By setting the partial derivatives of droplet growth ratio regression equation
(24) at zero, following three equations can be constructed:
-0.03 + 18.42 X1 – 0.12 X2 + 3.83 X3 = 0, (29)
- 1.45 – 0.12 X1 + 2.32 X2 + 0.051 X3 = 0, (30)
- 0.12 + 3.83 X1 + 0.051 X2 + 9.60 X3 = 0 (31)
By setting the partial derivatives of vitamin D retention regression equation
(25) at zero, following three equations can be constructed:
11.66 - 2.34 X1 + 6.19 X2 – 0.083 X3 = 0, (32)
38.75 + 6.19 X1 + 186.58 X2 - 17.86 X3 = 0, (33)
- 49.85 – 0.083 X1 - 17.86 X2 + 7.84 X3 = 0 (34)
Following results were obtained after solving these equations 26-34:
X1 = 4.35, X2 = 0.62 and X3 = 7.00
4.3.4 Verifications of the Model
The desirability of equations for prediction of response was check using
79
optimum preparation conditions (4.35 minutes homogenization time, 0.62
surfactant to oil ratio (S/O) and 7% DPV). The optimized conditions were further
confirmed by performing the experiment under optimum conditions. At optimum
preparation conditions, predicted response values for droplet size, droplet growth
ratio and vitamin D retention were 115.47 nm, 0.148 and 73.44, respectively. The
experimental values of droplet size, droplet growth ratio (DGR) and vitamin D
retention were 112.36 ± 3.6nm, 0.141 ± 0.07 and 76.65 ± 1.7%, respectively (Table
4.7). The experimental results were found in good agreement with the values
predicted by RSM.
4.4 CHARACTERIZATION OF BETA CAROTENE AND VITAMIN D
NANOEMULSIONS
Beta carotene and vitamin D nanoemulsions were prepared using optimized
preparation conditions. These optimized conditions are further characterized
against different parameters which include droplet growth ratio and storage
stability, p-Anisidine value and turbidity.
4.4.1 Droplet Growth Ratio and Storage Stability
The stability of beta carotene nanoemulsions was determined in term of
droplet growth ratio. Figure 4.5 shows the droplet growth ratio of beta carotene
nanoemulsions during one-month storage at room temperature. Storage time have
significant effect (p < 0.05) on the droplet growth ratio of beta carotene
nanoemulsions (Table 4.8). Initially, up to 25 days, droplet growth ratio of
nanoemulsions significantly deviates (p < 0.05) with the passage of time but after
that non-significant (p > 0.05) increase was observed in the droplet growth ratio of
beta carotene nanoemulsions.
80
Table 4.7: Optimum preparation conditions for vitamin D nanoemulsions
Optimum Conditions Coded Levels Actual Levels
Homogenization Time (Min.) -0.43 4.35
Surfactant to Oil Ratio 0.086 0.62
Disperse Phase Volume (%) -1.00 7.00
Response Predicted Values Experimental Values
Droplet Size (nm) 115.47 112.36 ± 3.6
Droplet Growth Ratio 0.148 0.141 ± 0.07
Vitamin D Retention (%) 73.44 76.65 ± 1.7
81
Table 4.8: ANOVA for droplet growth ratio of beta carotene nanoemulsions
Source DF SS MS F P
Storage Time 5 0.07680 0.01536 154 0.0001
Error 12 0.00120 0.00010
Total 17 0.07800
Figure 4.5: Change in droplet growth ratio of beta carotene nanoemulsions during
one month storage
E
D
C
B
A A
0.00
0.05
0.10
0.15
0.20
0.25
0.30
5 10 15 20 25 30
DG
R
Days
82
The stability of vitamin D nanoemulsions was determined in term of droplet
growth ratio. Figure 4.6 shows the droplet growth ratio of vitamin D
nanoemulsions during one-month storage at room temperature. Significant increase
(p < 0.05) was observed in droplet growth of vitamin D nanoemulsions with the
passage of time (Table 4.9). Initially, up to 20 days, droplet growth ratio of vitamin
D nanoemulsions significantly deviates (p < 0.05) with the passage of time but
after that non-significant increase (p > 0.05) was observed in the droplet growth
ratio of vitamin D nanoemulsions.
The storage stability of beta carotene nanoemulsions was evaluated during
their two- month storage at 4 °C and 25 °C. The effect of storage and time on the
droplet size of beta carotene nanoemulsions are given in Figure 4.7. Storage days
have significant effect (p < 0.05) on the mean droplet size of food grade beta
carotene nanoemulsions. Additionally, temperature also has significant (p < 0.05)
effect on the droplet size of beta carotene nanoemulsions (Table 4.10). Apart from
this, the interaction between time and temperature was also found significant (p <
0.05). Initially, sharp increase was observed in the droplet size of nanoemulsions
during initial 25 days of storage at 4 °C and 25 °C. After that, no significant
increase was noted in droplet size. During 60 days of storage, droplet size of beta
carotene nanoemulsions varied from 112.36 to 132.9 at 4 °C and 112.36 to 147.1 at
25 °C. Despite increase in size, the droplet size of beta carotene nanoemulsions is
still in acceptable range. Similar results were reported by other researchers (Henry
et al., 2010; Li and Chiang, 2012).
The stability of vitamin D nanoemulsions was evaluated during their two-
month storage at 4 °C and 25 °C. The effect of storage on droplet size of vitamin
83
Table 4.9: ANOVA for droplet growth ratio of vitamin D nanoemulsions
Source DF SS MS F P
Storage Time 5 0.09145 0.01829 183 0.0001
Error 12 0.00120 0.00010
Total 17 0.09265
Figure 4.6: Change in droplet growth ratio of vitamin D nanoemulsions during one
month storage
E
D
C
B AB A
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
5 10 15 20 25 30
DG
R
Days
84
Table 4.10: ANOVA for storage stability of beta carotene nanoemulsions
Source DF SS MS F P
Storage Time 12 6192.23 516.02 516.02 0.0001
Temperature 1 3111.72 3111.72 3111.72 0.0001
Storage x Temp 12 377.25 31.44 31.44 0.0001
Error 52 52.00 1.00
Total 77 9733.20
Figure 4.7: Effect of time and temperature on storage stability of beta carotene
nanoemulsions
L
I
GH
E
D CD
ABC BCD
ABC ABC ABC AB A
L
KL K
J
I
H
EF EF EF FG EF FG
EF
110
120
130
140
150
0 5 10 15 20 25 30 35 40 45 50 55 60
Dro
ple
t Si
ze D
4,3
(nm
)
Storage Days
25 °C
4 °C
85
D nanoemulsions is given in Figure 4.8. Storage days have significant effect (p <
0.05) on the droplet size of food grade vitamin D nanoemulsions (Table 11).
Additionally, temperature also has significant (p < 0.05) effect on the droplet size
of vitamin D nanoemulsions (Table 4.11). Apart from this, the interaction between
time and temperature was also found significant (p < 0.05). Generally, increase in
droplet size was observed with the passage of time. Initially, sharp increase was
observed in the droplet size of nanoemulsions during initial 30 days of storage at 4
°C and 25 °C. After that, no significant increase was noted in droplet size. During
60 days of storage, droplet size of vitamin D nanoemulsions varied from 119.33 to
140.15 at 4 °C and 119.33 to 155.5 at 25 °C. Despite increase in size, the droplet
size of mixed surfactant based vitamin D nanoemulsions are still in acceptable
range. Similar results were reported by other researchers (Henry et al., 2010; Li and
Chiang, 2012).
The increase in droplet growth rate was associated with non-equilibrium
system of nanoemulsions. To achieve equilibrium state, beta carotene and vitamin
D based nanoemulsions tend to reduce free energy as well as interfacial area
through various breakdown processes which include flocculation, sedimentation,
creaming and Ostwald ripening which leads to increase in droplet growth ratio of
beta carotene and vitamin D nanoemulsions (Tadros et al., 2004). Nanoemulsion
contains smaller particle size which is quite stable against flocculation,
sedimentation, creaming and phase separation, but Ostwald ripening is mainly
responsible for increase in droplet growth ratio of nanoemulsions (Taylor, 2003).
Ostwald ripening occurs due to the difference in the chemical potential of disperse
phase having different droplet size (Mcclements, 2011). During ripening process,
86
Table 4.11: ANOVA for storage stability of vitamin D nanoemulsions
Source DF SS MS F P
Storage Time 12 6821.24 568.44 568.44 0.0001
Temperature 1 2321.70 2321.70 2321.70 0.0001
Storage x Temp 12 307.08 25.59 25.59 0.0001
Error 52 52.00 1.00
Total 77 9502.02
Figure 4.8: Effect of time and temperature on storage stability of vitamin D
nanoemulsions
K
I
GH
EF
D
C BC
AB AB AB A AB A
K J
J
I
H
FG EF EF EF E
EF EF EF
115
125
135
145
155
165
0 5 10 15 20 25 30 35 40 45 50 55 60
Dro
ple
t Si
ze D
4,3 (
nm
)
Storage Days
25 °C
4 °C
87
the size of larger droplet increased due to their collision with smaller one in
continuous phase (Li and Chiang, 2012). Additionally, increase in droplets growth
ratio of beta carotene and vitamin D nanoemulsions might be associated with the
continuous movement of disperse phase droplets through continuous phase which
increase chances of droplet collisions (Henry et al., 2009). Previous studies also
reported increase in droplet growth ratio as a function of time (Henry et al., 2009;
Karadag et al., 2013; Mehmood, 2015).
Apart from this, increase in droplet size of beta carotene nanoemulsions was
higher at 25 °C as compared to 4 °C because temperature is reciprocally
proportional to rate of Ostwald ripening. Temperature affects the Ostwald ripening
through interfacial tension, solubility and diffusion coefficient. Previous studied
also reported effect of temperature on the Ostwald ripening in nanoemulsions (Jiao
and Burgess, 2003). However, the process of Ostwald ripening only occur during 4
weeks of initial storage, after that, no appreciable increase was observed in the
droplet size of beta carotene nanoemulsions.
4.4.2 p-Anisidine Value
p-Anisidine value is an important indicator of oxidative stability of nano-
emulsions (Chu et al., 2008). The oxidative stability of beta carotene
nanoemulsions was investigated by comparing the p-Anisidine value of beta
carotene containing free olive oil and olive oil incorporated into beta carotene
nanoemulsions. Effect of storage on the p-Anisidine values of free olive oil as well
as nanoemulsions incorporated olive oil is given in the Figure 4.9. Statistical
analysis indicated that storage duration and treatment has significant effect (p <
0.05) on the p-Anisidine values of beta carotene nanoemulsions (Table 4.12).
88
Table 4.12: ANOVA for p-Anisidine value of beta carotene nanoemulsions
Source DF SS MS F P
Storage Time 7 24368.8 3481.3 202.46 0.0001
Treatment 1 15187.0 15187.0 883.25 0.0001
Storage x Treat 7 9997.5 1428.2 83.06 0.0001
Error 32 550.2 17.2
Total 47 50103.4
FOO = Free olive oil, NOO = Olive oil incorporated into nanoemulsions
Figure 4.9: Change in p-Anisidine value of beta carotene nanoemulsions during
storage
G FG
EF
E
D
C
B
A
G G
G G FG FG
FG
E
0
20
40
60
80
100
120
0 1 2 3 4 5 6 7
p -
An
isid
ine
Va
lue
Storage Days
FOO
NOO
89
During storage, non-significant increase was observed in p-Anisidine value
of olive oil incorporated into beta carotene nanoemulsions (up to 6 days). On the
other hand, free olive oil containing beta carotene remains stable during initial two
days and after that significant (p < 0.05) increase was observed in their p-Anisidine
value. Additionally, p-Anisidine value of free olive oil was significantly higher as
compared to nanoemulsions incorporated olive oil (Figure 4.9).
p-Anisidine value is an important indicator of oxidative stability of
nanoemulsions (Chu et al., 2008). The oxidative stability of vitamin D
nanoemulsions was investigated by comparing the p-Anisidine value of vitamin D
containing free canola oil and canola oil incorporated into vitamin D
nanoemulsions. Effect of storage on the p-Anisidine values of free canola oil as
well as nanoemulsions incorporated canola oil is given in the Figure 4.10.
Statistical analysis indicated that storage duration and treatment has significant
effect (p < 0.05) on p-Anisidine values of vitamin D nanoemulsions (Table 4.13).
During storage, non-significant increase (p > 0.05) was observed in p-Anisidine
value of canola oil incorporated into vitamin D nanoemulsions (up to 3 days). On
the other hand, p-Anisidine value of free canola oil containing vitamin D was
significant increase (p < 0.05) even after one day. Additionally, p-Anisidine value
of free canola oil was significantly higher as compared to nanoemulsions
incorporated canola oil (Figure 4.10).
In nanoemulsions, surfactant droplets help to solubilize beta carotene and
vitamin D (Richards et al., 2002). There is clearly some interaction between mixed
surfactant and beta carotene or vitamin D which protects them from oxidative
damage. As a result of this, olive oil incorporated into beta carotene nanoemulsions
90
Table 4.13: ANOVA for p-Anisidine value of vitamin D nanoemulsions
Source DF SS MS F P
Storage Time 7 27403.1 3481.3 202.46 0.0001
Treatment 1 17694.7 15187.0 883.25 0.0001
Storage x Treat 7 10001.0 1428.2 83.06 0.0001
Error 32 10.2 17.2
Total 47 55109.0
FCO = Free canola oil, NCO = Canola oil incorporated into nanoemulsions
Figure 4.10: Change in p-Anisidine value of vitamin D nanoemulsions during
storage
L
H
F
E
D
C
B
A
L
KL
JK J I H G
E
0
20
40
60
80
100
120
140
0 1 2 3 4 5 6 7
p-A
nis
idin
e V
alu
e
Storage Days
FCO
NCO
91
was more stable as compared to free olive oil. Similarly, canola oil incorporated
into vitamin D nanoemulsions was more stable as compared to free canola oil. The
rate of oxidation increased with the passage of time due to initiation of chain
reaction by oxidative products which lead to higher p-Anisidine value (Chu et al.,
2008). The nanoemulsions which are developed in our study was more oxidative
stable as compared to previous studies (Belhaj et al., 2010; Qian et al., 2012a).
This oxidative stability may be associated due to use of mixed surfactants e.g. soya
lecithin and Tween 80. Mixed surfactants may increase the oxidative stability of
nanoemulsions through increasing partitioning of surfactants at interface.
4.4.3 Turbidity
The turbidity value of nanoemulsions is very important because the
application of nanoemulsions in some food products (transparent or slightly turbid)
depends on the turbidity values of nanoemulsions. Effect of storage time as well as
temperature on the turbidity of beta carotene nanoemulsions is shown in Figure
4.11. Statistical analysis depicted that storage days and temperature have
significant effect (p < 0.05) on the turbidity value of beta carotene nanoemulsions
(Table 4.14). But, the interactive effect of time and temperature on turbidity value
was non-significant (p > 0.05). The turbidity value increased more rapidly in
nanoemulsions stored at 25 °C as compared to 4 °C. More rapid increase was
observed in nanoemulsion turbidity up to 20 days storage. After that, slow increase
was observed in the turbidity values of beta carotene nanoemulsions stored at
different temperatures.
Effect of storage as well as temperature on the turbidity of vitamin D
nanoemulsions is shown in Figure 4.12. Statistical analysis depicted that storage
92
Table 4.14: ANOVA for turbidity value of beta carotene nanoemulsions
Source DF SS MS F P
Storage Time 6 0.41233 0.06872 45.38 0.0001
Temperature 1 0.01339 0.01339 8.84 0.0001
Storage x Temp 6 0.00536 0.00089 0.59 0.7357
Error 28 0.04240 0.00151
Total 41 0.47348
Figure 4.11: Effect of time and temperature on turbidity value of beta carotene
nanoemulsions during storage
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0 5 10 15 20 25 30
Tu
rbid
ity
( c
m-1
)
Storage Days
4 °C
25 °C
93
days and temperature have significant effect (p < 0.05) on the turbidity value of
vitamin D nanoemulsions (Table 4.15). But, the interactive effect of time and
temperature on turbidity value was non-significant (p > 0.05). The turbidity value
increased more rapidly in nanoemulsions stored at 25 °C as compared to 4 °C.
More rapid increase was observed in the turbidity values of nanoemulsion up to 20
days of storage. After that, slow increase was observed in the turbidity values of
vitamin D nanoemulsions stored at different temperatures.
The turbidity value of nanoemulsions are low as compared to conventional
emulsions because smaller droplets scatter light wave weakly which leads to lower
turbidity values (Mcclements, 2011). During storage, turbidity values increased due
to increase in droplet size which scatters light wave strongly. Furthermore, at
higher temperature, the chances of droplets collision is more which results in more
turbidity value (Zahi et al., 2014). Previous studies also reported increase in the
turbidity values of nanoemulsion as a function of storage time (Zahi et al., 2014).
Surfactants can decrease the value of turbidity by either reducing the droplet size of
nanoemulsions or through reducing the refractive index contrast (Saberi et al.,
2013).
4.5 EFFECT OF ENVIRONMENTAL CONDITIONS ON BETA
CAROTENE AND VITAMIN D NANOEMULSIONS
Nanoemulsion based foods may experience different environmental stresses
(such as change in temperature, pH and ionic strength) during food preparations,
storage, transportation, distribution and utilization. Hence, in present study stability
of beta carotene and vitamin D nanoemulsions (optimized conditions) was
investigated against pH, ionic strength, temperature and freeze thaw cycle.
94
Table 4.15: ANOVA for turbidity value of vitamin D nanoemulsions
Source DF SS MS F P
Storage Time 6 0.33523 0.05587 69.22 0.0001
Temperature 1 0.00619 0.00619 7.67 0.0001
Storage x Temp 6 0.00386 0.00064 0.80 0.5807
Error 28 0.02260 0.00081
Total 41 0.36788
Figure 4.12: Effect of time and temperature on turbidity value of vitamin D
nanoemulsions during storage
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0 5 10 15 20 25 30
Tu
rbid
ity
(cm
-1)
Storage Days
4 °C
25 °C
95
4.5.1 Effect of pH
The pH value of emulsion-based food and beverages considerably differ, such
as soft drinks are acidic in nature while some nutritional beverages have pH in
basic range. Hence, in present study, effect of pH on the stability of beta carotene
and vitamin D nanoemulsions was examined. The effect of pH values on the
droplet growth of beta carotene nanoemulsions is given in Figure 4.13. No
significant change (p >0.05) was observed in droplet size of beta carotene
nanoemulsions across entire range of pH (2-8). Furthermore, these nanoemulsions
were also stable against phase separation, creaming and sedimentation at the pH
values range from 2-8 (Table 4.16).
The effect of pH values on the droplet growth of vitamin D nanoemulsions is
given in Figure 4.14. No significant change (p >0.05) was observed in droplet size
of vitamin D nanoemulsions across entire range of pH i.e. 2-8 (Table 4.17).
Furthermore, mixed surfactant based vitamin D nanoemulsions were also stable
against phase separation, creaming and sedimentation at the pH values range from
2-8.
The stability of mixed surfactant based beta carotene and vitamin D
nanoemulsions suggest that interfacial properties are dominated by non-ionic
surfactant i.e. Tween 80. Other surfactant (soya lecithin) undergoes a transition
around pH 2 which significantly reduce surface charge. Aggregation of droplets
occurs when attractive forces (such as hydrophobic and van der Walls) overcomes
repulsive forces (mainly steric and electrostatic forces). So, in the case of beta
carotene and vitamin D nanoemulsions, repulsive forces (steric forces) between
charged droplets are strong enough to overcome the attractive forces of droplets.
96
Table 4.16: ANOVA for pH stability of beta carotene nanoemulsions
Source DF SS MS F P
pH 6 0.6645 0.11074 0.15 0.9849
Error 14 10.0414 0.71724
Total 20 10.7059
Figure 4.13: Effect of pH on the stability of beta carotene nanoemulsions
109
112
115
118
121
0 2 4 6 8 10
Dro
ple
t Si
ze D
4,3
(n
m)
pH
97
Table 4.17: ANOVA for stability of vitamin D nanoemulsions against change in
pH value
Source DF SS MS F P
pH 6 0.0573 0.00954 0.01 1.0000
Error 14 13.8014 0.98581
Total 20 13.8587
Figure 4.14: Effect of pH on the stability of vitamin D nanoemulsions
116
119
122
125
128
0 2 4 6 8 10
Dro
ple
t Si
ze D
4,3
(n
m)
pH
98
Additionally, non-ionic surfactant (Tween 80 in our study) may contain charge due
to preferential absorption of hydrogen ion at lower pH and hydroxyl ion at higher
pH or due to presence of surface active impurities which are ionizable. Hence, non-
ionic surfactant generates strong steric forces which prevent droplets from
aggregation (Ozturk et al., 2014). In our study, the stability of beta carotene and
vitamin D nanoemulsions against different pH values may be associated due to use
of mixed surfactants, which have ability to generate strong steric forces which
prevent the droplets from aggregations.
4.5.2 Effect of Ionic Strength
The concentration of salt appreciably differ in different food and beverages
products, therefore the effect of ionic strength was examined on the stability of
mixed surfactants based beta carotene nanoemulsions. Figure 4.15 shows the effect
of ionic strength on the droplet size of beta carotene nanoemulsions. Statistical
analysis indicates that ionic strength exerts non-significant effect (p >0.05) on
droplet size of beta carotene nanoemulsions (Table 4.18). Additionally, Visual
observations of beta carotene nanoemulsions stored at different ionic strength
indicated that these nanoemulsions remain stable against phase separation,
sedimentation and creaming during their storage at different ionic strength which
ranged between 0 to 400 mM.
Figure 4.16 shows the effect of ionic strength on the droplet size of vitamin D
nanoemulsions. Statistical analysis indicates that ionic strength exerts non-
significant (p >0.05) effect of droplet size of vitamin D nanoemulsions (Table
4.19). Additionally, Visual observations of vitamin D nanoemulsions stored at
different ionic strength indicated that mixed surfactant based vitamin D emulsions
99
Table 4.18: ANOVA for stability of vitamin D nanoemulsions against ionic
strength
Source DF SS MS F P
Salt Con. 8 0.7365 0.09206 0.09 0.9991
Error 18 17.9618 0.99788
Total 26 18.6983
Figure 4.15: Effect of ionic strength on the stability of beta carotene nanoemulsions
110
113
116
119
122
125
0 50 100 150 200 250 300 350 400
Dro
ple
t S
ize
D4
,3 (
nm
)
NaCl Concentration (mM)
100
remain stable against phase separation, sedimentation and creaming during their
storage at different ionic strength which ranged between 0 to 400 mM.
The stability of beta carotene and vitamin D nanoemulsions against different
ionic strength may be attributed because interfacial properties are dominated by the
non-ionic surfactant i.e Tween 80. Other surfactant (lecithin) undergoes a transition
around pH 2 which reduces surface charges. Moreover, Lecithin is a zwitterionic
and its behavior is affected by salt (Ozturk et al., 2014). Additionally, different
concentration of salts does not have ability of change the interfacial membrane
curvature of mixed surfactant based beta carotene and vitamin D nanoemulsions
and remains stable against droplet coalescence (Ogawa et al., 2003). The stability
of beta carotene and vitamin D nanoemulsions against different ionic strength
might be attributed due to the presence of strong steric stabilization which are
strong enough to overcome van der Walls and hydrophobic attractions (Harnsilawat
et al., 2006). Another study (Shu et al., 2016) reported the similar trend in
nanoemulsions stabilized by SC and MO-7S. On the other hand, some researchers
reported destabilization of nanoemulsions against different salt concentration due
to electrostatic screening effect (Ozturk et al., 2014). In our study, the stability of
beta carotene and vitamin D nanoemulsions against different salt concentrations
may be associated due to use of mixed surfactants, which have ability to generate
strong steric forces which prevent the droplets from aggregations.
4.5.3 Effect of Temperature
The temperature of nanoemulsions based food and beverages appreciably
varied during their processing, transportation, utilization and storage of food.
Table 4.19: ANOVA for stability of vitamin D nanoemulsions against ionic
101
strength
Source DF SS MS F P
Salt Con. 8 1.2774 0.15968 0.16 0.9939
Error 18 18.0418 0.00232
Total 26 19.3192
Figure 4.16: Effect of ionic strength on the stability of vitamin D nanoemulsions
Hence, I examined the effect of temperature on the stability of food grade beta
113
116
119
122
125
128
0 100 200 300 400 500
Dro
ple
t S
ize
D4
,3 (
nm
)
NaCl Concentration (mM)
102
carotene and vitamin D nanoemulsions. The effect of different temperature ranges
(30-90 °C) on the mean droplet size of beta carotene nanoemulsions is summarized
in Figure 4.17. After all temperature treatments, no significant change (p >0.05)
was observed in the droplet size of beta carotene nanoemulsions (Table 4.20).
However, small increase in droplet size and color change was observed at 90 °C.
Results of visual observation indicated that these nanoemulsions remained stable
against phase separation, sedimentation and creaming during entire thermal
variations.
The effect of different temperature ranges (30-90 °C) on the mean droplet size
of vitamin D nanoemulsions is summarized in Figure 4.18. After all temperature
treatments, no significant change (p >0.05) was observed in the size of droplets
(Table 4.21). The results of visual observation indicated that these nanoemulsions
remained stable against phase separation, sedimentation and creaming during entire
thermal variations.
So, it is concluded that mixed surfactant based beta carotene and vitamin D
nanoemulsions remained stable during temperature fluctuations. The stability of
mixed surfactant based beta carotene nanoemulsions at high temperature may be
attributed due to steric stabilization which prevent the aggregation of
nanoemulsions droplets (Ozturk et al., 2014). Aggregation of droplets occurs when
attractive forces (such as hydrophobic and van der Walls) overcomes repulsive
forces (mainly steric and electrostatic forces). Previous studies also reported
stability of whey protein isolate and lactoferrin based nanoemulsions against
droplet aggregation at higher temperature (Teo et al., 2016) due to strong repulsive
Table 4.20: ANOVA for stability of beta carotene nanoemulsions against higher
103
temperature
Source DF SS MS F P
Salt Con. 6 28.2682 4.71137 2.55 0.0700
Error 14 25.8814 1.84867
Total 20 54.1496
Figure 4.17: Stability of beta carotene nanoemulsions against higher temperature
Table 4.21: ANOVA for stability of vitamin D nanoemulsions against higher
106
110
114
118
122
126
130
0 20 40 60 80 100
Dro
ple
t S
ize
D4
,3 (
nm
)
Temperature (°C)
104
temperature
Source DF SS MS F P
Salt Con. 6 1.4832 0.24720 0.25 0.9516
Error 14 13.8814 0.99153
Total 20 15.3646
Figure 4.18: Stability of vitamin D nanoemulsions against higher temperature
forces between charged droplets. On the other hand, another study reported that
112
116
120
124
128
132
0 20 40 60 80 100
Dro
ple
t S
ize
D4
,3 (
nm
)
Temperature (°C)
105
whey protein-based nanoemulsions destabilize at higher temperatures due to
unfolding and thermal denaturation of protein (Chu et al., 2008). This difference in
nanoemulsions may be attributed due to difference in heating duration.
4.5.4 Physical Stability (Freeze-Thaw Cycle)
Aqueous food products are frequently frozen for increasing their shelf life and
presenting food in desirable physical state (Ghosh and Coupland, 2008). To
investigate the possible utilization of mixed surfactant based beta carotene and
vitamin D nanoemulsions in this food category, their stability was tested against
freeze-thaw cycle. The effect of freeze-thaw cycle on the droplet size of beta
carotene nanoemulsions is summarized in Figure 4.19. Freeze-thaw cycles have
significant effect (p < 0.05) on the mean droplet size of nanoemulsions (Table
4.22). The droplet size of nanoemulsions steadily increased after each freeze-thaw
cycle. Initially, the droplet size of beta carotene nanoemulsions was 112.36±1.4 nm
and this value increased to 141.75±0.9 nm after four freeze-thaw cycles.
The effect of freeze-thaw cycle on the droplet size of vitamin D nanoemulsions
is summarized in Figure 4.20. Freeze-thaw cycles have significant effect (p < 0.05)
on the mean droplet size of nanoemulsions (Table 4.23). The droplet size of
nanoemulsions steadily increased after each freeze-thaw cycle. Initially, the droplet
size of nanoemulsions was 119.33±1.6 nm and this value increased to 140.9±1.6
nm after four freeze-thaw cycles. Changes in the droplet size of vitamin D
nanoemulsions indicate that freeze-thaw cycle affects the stability of food grade
vitamin D nanoemulsions.
Changes in the droplet size of nanoemulsions indicate that freeze-thaw cycle
Table 4.22: ANOVA for physical stability of β-carotene nanoemulsions against
106
1 E
D
C
B
A
100
110
120
130
140
150
160
0 0.5 1 1.5 2 2.5 3 3.5 4
Dro
ple
t Si
ze D
4,3
(n
m)
Cycle No
freeze-thaw cycle
Source DF SS MS F P
Cycles 4 1687.79 421.947 421.94 0.0001
Error 10 10.00 1.000
Total 14 1697.79
Figure 4.19: Physical stability of beta carotene nanoemulsions against freeze-thaw
cycle
freeze-thaw cycle affects the stability of food grade beta carotene and vitamin D
107
nanoemulsions. Increase in droplet size was largely contributed by freezing rather
than thawing. Ice crystallization formed during freezing which force the oily
droplets to come closer to remaining continuous phase. As a result of this, water
film is drained between droplets and it leads to semi dry contact of two layers of
surfactant adsorbed on oil droplets. It is also called Newton black film. If repulsive
forces are not strong enough to limit droplet approach as well as film drainage, the
rupturing of Newton film allow the contents of droplets flow together and cause
droplet coalescence (O’regan and Mulvihill, 2010). Additionally, temperature of
the beta carotene and vitamin D nanoemulsions decreased during freezing which
leads to attenuated hydrophobic interactions (endothermic) in micelle core and
reinforcement of hydrogen bonding (Schellman, 1997). The compact droplets relax
after the changes in these forces which results in decomposition of nanoemulsions.
The ice crystals are formed during freezing which leads to disruption and
penetration of interface as well as expulsion of water from interstices. This
mechanism creates channel for bioactive molecule to escape from the core of
micelle (Ma et al., 2016b). However, these nanoemulsions remained stable against
phase separation, creaming and sedimentation after four freeze-thaw cycles.
4.6 TOXICOLOGICAL STUDIES FOR BETA CAROTENE AND
VITAMIN D NANOEMULSIONS
Beta carotene and vitamin D nanoemulsions were investigated against different
toxicological effects by performing different tests which include change in weight,
nuclear abnormalities analysis and comet assay. Albino mice were used as
experimental animals during these studies. The details are mentioned below:
Table 4.23: ANOVA for physical stability of vitamin D nanoemulsions against
108
freeze-thaw cycle
Source DF SS MS F P
Cycles 4 910.194 227.548 228 0.0001
Error 10 10.00 1.000
Total 14 920.194
Figure 4.20: Physical stability of vitamin D nanoemulsions against freeze-thaw
cycle
4.6.1 Body Weight
E D
C
B
A
95
105
115
125
135
145
155
0 0.5 1 1.5 2 2.5 3 3.5 4
Dro
ple
t Si
ze D
4,3
(n
m)
Cycle No
109
Albino mice are divided into six different groups to determine the toxicity
of mixed surfactant based beta carotene nanoemulsions. Each group received
different treatments and change in weight is noted after every week during 21 days
of study. The mean values of weight for different groups during study are
summarized in Figure 4.21. Statistical analysis indicates that significant effect (p <
0.05) of group and time was observed on the weight of albino mice under study
(Table 4.24). In general, nanoemulsions cause increase in weight while higher
amount of beta carotene results in reduction in weight of albino mice. In group A
(control group), weight increase was observed during entire duration of study. But,
higher weight gain was observed in group B as compared to group A. This weight
gain might be increased because nanoemulsions increase the absorption of nutrients
due to smaller droplet size (Mcclements and Rao, 2011). Group C and F received
similar same dose of beta carotene in nanoemulsions and olive oil respectively.
After two weeks, increase in weight was observed in group C as well as group F.
On the other end, weight loss was observed in group D and E due to higher dose.
Beta carotene in higher amount reduce the weight through controlling white
adipose tissues and brown adipose tissues development and function by affecting
the adiposity and body weight. Higher level of beta carotene reduces the adiposity
and lipogenic potential in adipose tissues and increase the thermogenic potential of
muscle (Bonet et al., 2003). The findings of our studies are similar to previous
studies which reported that higher dose of vitamin A cause weight loss (Jeyakumar
et al., 2006; Raoofi et al., 2010). But, these results are not in agreement with some
previous findings which reported non-significant effect of higher dose of vitamin A
Table 4.24: ANOVA for effect of beta carotene nanoemulsions on weight
110
Source DF SS MS F P
Group 5 449.620 89.9239 8992.39 0.0001
Time 3 46.733 15.5775 1557.75 0.0001
Group x Time 15 223.046 14.8697 1486.97 0.0001
Error 48 0.480 0.0100
Total 71 719.878
Figure 4.21: Effect of different treatments of beta carotene nanoemulsions on the
weight of mice
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)
Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
Group F = Beta carotene in olive oil (5400 IU/Kg body weight)
on weight loss (Mahassni and Al-Shaikh, 2014).
M
F G J H L L
D E H
K I I
C D
K M
F F
A
B
N O
E
0
5
10
15
20
25
30
35
40
45
Group A Group B Group C Group D Group E Group F
We
igh
t (g
) 0 Day
7 Days
14 Days
21 Days
111
Albino mice are divided into six different groups to check the effect of vitamin
D nanoemulsions. Each group of mice received different treatments and change in
weight is noted after every week during 21 days of study. Statistical analysis
indicates that significant effect (p < 0.05) of group as well as time was observed on
the weight of albino mice under study (Table 4.25). The mean values of weight for
different groups during study are summarized in Figure 4.22. In general,
nanoemulsions cause increase in weight while higher amount of vitamin D results
in reduction in weight of albino mice. In group A (control group), weight increase
was observed during entire duration of study. But, higher weight gain was observed
in group B as compared to group A. This weight gain was observed because
nanoemulsions increase the absorption of nutrients due to smaller droplet size
(Mcclements and Rao, 2011). Group C and F received similar same dose of vitamin
D in nanoemulsions and canola oil respectively. After two weeks, loss in weight
was observed in group C but no weight loss was observed in group F. The weight
loss might be observed due to higher absorption of vitamin D in group C as
compared to group F. Higher absorption of vitamin D cause weight loss in group C
(Mason et al., 2014). Similarly, weight gain was also observed in group D and E
due to higher amount of vitamin D. Vitamin D reduce the weight through different
mechanisms such as reduction in the formation of new fat cells (Wood, 2008),
reduction in fat accumulation through suppressing fat cells storage (Chang and
Kim, 2016), production of serotonin in higher amount which increase satiety
(Halford and Harrold, 2012) and increase the production of testosterone which
trigger weight loss (Nimptsch et al., 2012). The findings of our studies are similar
Table 4.25: ANOVA for effect of different treatments of vitamin D nanoemulsions
112
on the weight of mice
Source DF SS MS F P
Group 5 408.217 81.6435 8164.35 0.0001
Time 3 18.982 6.3273 632.73 0.0001
Group x Time 15 209.506 13.9671 1396.71 0.0001
Error 48 0.480 0.0100
Total 71 637.185
Figure 4.22: Effect of different treatments of vitamin D nanoemulsions on the
weight of mice
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)
Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
Group F = Vitamin D in canola oil (1800 IU/Kg body weight)
M
HI H J K J K
C E G
L I HI
B D
J
N
FG EF
A
F
M
O
D
0
5
10
15
20
25
30
35
40
45
Group A Group B Group C Group D Gropu E Group F
We
igh
t (g
) 0 Day
7 Days
14 Days
21 Days
113
to previous studies which reported that higher dose of vitamin D cause weight loss
(Leblanc et al., 2012; Mason et al., 2014).
4.6.2 Nuclear Abnormalities Analysis
Nuclear abnormalities were determined through bi-nuclear and multi-
nuclear assay. Albino mice were used as experimental animals during this study.
The detail of nuclear abnormalities assay is mentioned below;
4.6.2.1 Bi-nuclear assay
Effects of mixed surfactant based beta carotene nanoemulsions on bi-nuclear
cells frequency of different albino mice groups (received different dose of beta
carotene nanoemulsions) are summarized in Figure 4.23. Statistical analysis results
depicted that different treatments of beta carotene have significant effect (p < 0.05)
on bi-nuclear cells frequency in different groups of albino mice (Table 4.26).
Frequency of binuclear cells was significantly higher (p < 0.05) in group B (blank
nanoemulsions) as compared to group A (control group). However, non- significant
(p > 0.05) difference was observed between group B (blank nanoemulsions), group
C (Nanoemulsion containing 9000 IU/Kg body weight beta carotene) and group F
(9000 IU/Kg body weight beta carotene in olive oil). Additionally, the frequency of
bi-nuclear cells significantly increased in group D and E due to higher dose of beta
carotene. Although significant effect of beta carotene nanoemulsions (having
different concentration of beta carotene) was observed on different groups of mice,
but the values of bi-nuclear assay still lie in lower limit. Bi-nuclear cell frequency
indicates the cytotoxicity by measuring damage in blood lymphocytes (Sandhu et
al., 2013). Nanoemulsions with lower amount of beta carotene are suitable for
consumption, but nanoemulsions with higher amount of beta carotene can induce
114
Table 4.26: ANOVA for bi-nuclear assay against different treatments of beta
carotene nanoemulsions
Source DF SS MS F P
Groups 5 0.04105 0.00821 82.1 0.0001
Error 12 0.00120 0.00010
Total 17 0.04225
Figure 4.23: Effect of different treatments of beta carotene nanoemulsions on the
frequency of bi-nuclear cells
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)
Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
Group F = Beta carotene in olive oil (9000 IU/Kg body weight)
D
C
C
B
A
C
0 0.05 0.1 0.15 0.2 0.25 0.3
Group A
Group B
Group C
Group D
Group E
Group F
Frequency of BN Cells (%)
115
cytotoxicity due to more absorption of beta carotene (Mcclements and Rao, 2011).
Effects of mixed surfactant based vitamin D nanoemulsions on bi-nuclear cells
frequency of different albino mice groups (received different dose of vitamin D
nanoemulsions) are summarized in Figure 4.24. Statistical analysis results depicted
that different treatments of vitamin D have significant effect (p < 0.05) on bi-
nuclear cells frequency in different groups of albino mice (Table 4.27). Frequency
of binuclear cells was significantly higher (p < 0.05) in group B (blank
nanoemulsions) as compared to group A (control group). However, non-significant
difference (p > 0.05) was observed between group B (blank nanoemulsions), group
C (Nanoemulsion containing 1800 IU/Kg body weight vitamin D) and group F
(1800 IU/Kg body weight vitamin D in canola oil). Additionally, the frequency of
bi-nuclear cells significantly increased in group D and E due to higher dose of
vitamin D. Although significant effect of vitamin D nanoemulsions (having
different concentration of vitamin D) was observed on different groups of mice, the
values of bi-nuclear assay still lie in lower limit. Bi-nuclear cell frequency indicates
the cytotoxicity by measuring damage in blood lymphocytes (Sandhu et al., 2013).
Vitamin D containing lower amount of vitamin D are safe for consumption, but
nanoemulsions with higher amount of vitamin D can induce cytotoxicity due to
more absorption of vitamin D (Mcclements et al., 2007).
4.6.2.2 Multi-nuclear assay
Effects of mixed surfactant based beta carotene nanoemulsions on multi-
nuclear cells frequency of different albino mice groups (received different dose of
beta carotene nanoemulsions) are summarized in Figure 4.25. Statistical analysis
results depicted that the different treatments of beta carotene (vitamin A) have
116
Table 4.27: ANOVA for effect of different treatments of vitamin D nanoemulsions
on bi-nuclear assay
Source DF SS MS F P
Groups 5 0.04345 0.00869 86.9 0.0001
Error 12 0.00120 0.00010
Total 17 0.04465
Figure 4.24: Effect of different treatments of vitamin D nanoemulsions on the
frequency of bi-nuclear cells
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)
Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
Group F = Vitamin D in canola oil (1800 IU/Kg body weight)
D
C
C
B
A
C
0 0.05 0.1 0.15 0.2 0.25 0.3 0.35
Group A
Group B
Group C
Group D
Group E
Group F
Frequency of BN Cells (%)
117
significant effect (p < 0.05) on the multi-nuclear cells frequency in different groups
of albino mice (Table 4.28). Frequency of multi-nuclear cells was significantly
higher (p < 0.05) in group B (blank nanoemulsions) as compared to group A
(control group). Additionally, significant difference was observed between group C
(Nanoemulsion containing 9000 IU/Kg body weight beta carotene) and group F
(9000 IU/Kg body weight beta carotene in olive oil). Additionally, the frequency of
multi-nuclear cells significantly increased in group D and E due to higher dose of
beta carotene. Although significant effect (p < 0.05) of beta carotene
nanoemulsions (having different concentration of beta carotene) was observed on
different groups of mice, the values of multi-nuclear assay still lie in lower limit.
Multi-nuclear cell frequency increased due to production of free radicals which
effect OFR 9oxygen free radical) scavenging enzymes (El-Shenawy et al., 2011).
Mixed surfactant based beta carotene nanoemulsions containing lower amount of
beta carotene are safe for consumption, but nanoemulsions with higher amount of
beta carotene can induce cytotoxicity and other harmful effects due to more
absorption of beta carotene (Mcclements et al., 2007).
Effects of mixed surfactant based vitamin D nanoemulsions on multi-
nuclear cells frequency of different albino mice groups (received different dose of
mixed surfactant based vitamin D nanoemulsions) are summarized in the Figure
4.26. Statistical analysis results depicted that different treatments of vitamin D have
significant effect (p < 0.05) on the multi-nuclear cells frequency in different groups
of albino mice (Table 4.29). Frequency of multi-nuclear cells was significantly
higher (p < 0.05) in group B (blank nanoemulsions) as compared to group A
(control group). Additionally, significant difference (p < 0.05) was observed among
118
Table 4.28: ANOVA for multi-nuclear assay of different treatment of beta carotene
nanoemulsions
Source DF SS MS F P
Groups 5 316.965 63.3930 6339 0.0001
Error 12 0.120 0.0100
Total 17 317.085
Figure 4.25: Effect of different treatments of beta carotene nanoemulsions on
multi-nuclear cells frequency
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)
Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
Group F = Beta carotene in olive oil (9000 IU/Kg body weight)
F
E
C
B
A
D
0 5 10 15 20
Group A
Group B
Group C
Group D
Group E
Group F
Frequency of MN Cells (%)
119
Table 4.29: Analysis of variance for effect of different treatments of vitamin D
nanoemulsions on multi-nuclear assay
Source DF SS MS F P
Groups 5 467.316 93.4632 11193 0.0001
Error 12 0.100 0.0083
Total 17 467.416
Figure 4.26: Effect of treatments of vitamin D nanoemulsions on the frequency of
multi-nuclear cells
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)
Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
Group F = Vitamin D in canola oil (1800 IU/Kg body weight)
E
D
C
B
A
D
0 5 10 15 20 25
Group A
Group B
Group C
Group D
Group E
Group F
Frequency of MN Cells (%)
120
group C (Nanoemulsion containing 1800 IU/Kg body weight vitamin D) and group
F (1800 IU/Kg body weight vitamin D in canola oil). Furthermore, the frequency of
multi-nuclear cells significantly increased (p < 0.05) in group D and E due to
higher dose of vitamin D. Although significant effect of vitamin D nanoemulsions
(having different concentration of vitamin D) was observed on different groups of
mice, the values of multi-nuclear assay still lie in lower limit. Multi-nuclear cell
frequency increased due to production of free radicals which effect OFR oxygen
free radical) scavenging enzymes (El-Shenawy et al., 2011). Nanoemulsions
containing lower amount of vitamin D are safe for consumption, but
nanoemulsions with higher amount of vitamin D can induce cytotoxicity due to
more absorption of vitamin D (Mcclements, 2011).
4.6.3 Comet Assay
After nuclear abnormalities assay, the ability of beta carotene and vitamin D
nanoemulsions to cause DNA damage was detected by comet assay. Comet assay
has a number of potential advantages over conventional methods because in this
method mitotically active form of cells is not required (Lee and Steinert, 2003).
The detail of comet assay parameters is discussed below;
4.6.3.1 Tail length
Tail length indicates the extent of damage in DNA and it indicates the distance
of DNA migration from nuclear core. The effect of beta carotene nanoemulsions on
the tail length of different mice groups are summarized in Figure 4.27. Statistical
analysis results indicate that tail length of different mice groups significantly
deviates (p < 0.05) from each other (Table 4.30). Length of tail was significantly
higher in group B (blank nanoemulsions) as compared to group A (control group).
121
Figure 4.27: Effect of beta carotene nanoemulsions on tail length
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)
Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
Group F = Beta carotene in olive oil (9000 IU/Kg body weight)
PC = Positive Control
F
E
D
C
B
F
A
0 5 10 15 20 25 30 35 40
Group A
Group B
Group C
Group D
Group E
Group F
PC
Tail Length (μm)
122
Table 4.30: ANOVA for effect of beta carotene nanoemulsions on tail length
Source DF SS MS F P
Groups 6 1264.67 210.779 1392 0.0001
Error 14 2.12 0.151
Total 20 1266.79
Figure 4.28: Comet Assay Results for beta carotene nanoemulsions (A) Group A
(B) Group E
Group A = Control group
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
123
However, non-significant (p > 0.05) difference was observed between group A
(control group) and group F (9000 IU/Kg body weight beta carotene in olive oil).
Additionally, the tail length was significantly higher in group D and E due to
higher dose of beta carotene. But, the value of tail length in D and E groups are
significantly lower as compared to positive control (even less than half). Although,
significant effect of beta carotene nanoemulsions (having different concentration of
beta carotene) was observed on tail length of different groups of mice, their values
are significantly lower as compared with positive control. Hence, it is concluded
that beta carotene nanoemulsions with lower amount of beta carotene did not cause
genotoxicity in mice (Figure 4.28), but higher dose of beta carotene cause increase
in tail length. However, these values are not high enough to cause severe
genotoxicity. The results of this study are well in agreement with the findings of
other researchers (Gomes et al., 2013).
The effect of vitamin D nanoemulsions on the tail length of different mice
groups are summarized in Figure 4.29. Statistical analysis results indicate that tail
length of different mice groups significantly deviates (p < 0.05) from each other
(Table 4.31). Length of tail was significantly higher (p < 0.05) in group B (blank
nanoemulsions) as compared to group A (control group). However, non-significant
difference (p > 0.05) was observed between group B (blank nanoemulsions), group
C (Nanoemulsion containing 1800 IU/Kg body weight vitamin D) and group F
(1800 IU/Kg body weight vitamin D in canola oil). Additionally, the tail length was
significantly higher (p < 0.05) in group D and E due to higher dose of vitamin D.
But, the value of tail length in D and E groups are significantly lower as compared
to positive control (even less than half). Although, significant effect (p < 0.05) of
124
Figure 4.29: Effect of different treatments of vitamin D nanoemulsions on tail
length in comet assay
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)
Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
Group F = Vitamin D in canola oil (1800 IU/Kg body weight)
PC = Positive Control
E
D
D
C
B
D
A
0 10 20 30 40 50
Group A
Group B
Group C
Group D
Group E
Group F
PC
Tail Length (μm)
125
Table 4.31: ANOVA for effect of different treatments of vitamin D nanoemulsions
on tail length
Source DF SS MS F P
Groups 6 2855.46 475.910 3143 0.0001
Error 14 2.12 0.151
Total 20 2857.58
Figure 4.30: Comet Assay Results for vitamin D nanoemulsions (A) Group A (B)
Group E
Group A = Control group
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
126
vitamin D nanoemulsions (having different concentration of vitamin D) was
observed on tail length of different groups of mice, their values are significantly
lower as compared with positive control. Hence, it is concluded that mixed
surfactant based vitamin D nanoemulsions with lower amount of vitamin D did not
cause genotoxicity in mice, but higher dose of vitamin D cause increase in tail
length. However, these values are not high enough to cause severe genotoxicity
(Figure 4.30). The results of this study are well in agreement with the findings of
other researchers (Gomes et al., 2013).
4.6.3.2 Tail DNA
Tail DNA indicates DNA damage and it is the ratio of total tail intensity and
total comet intensity (tail and head together). The effect of different treatments of
nanoemulsions on the tail DNA of different mice groups is given in Figure 4.31.
ANOVA results depicted that treatments have significant effect (p < 0.05) on the
tail DNA of different groups (Table 4.32). The value of tail DNA was significantly
higher (p < 0.05) in group B (blank nanoemulsions) as compared to group A
(control group). Furthermore, dose depended response was observed in group C, D
and E. The value of tail DNA significantly increased with the increase in beta
carotene. Despite significant increase, these values were far less as compared to tail
DNA value of control group. Additionally, significant difference (p < 0.05) was
observed between group C (Nanoemulsion containing 9000 IU/Kg body weight
beta carotene) and group F (9000 IU/Kg body weight beta carotene in olive oil).
The values of tail DNA was significantly higher (p < 0.05) in group C as compared
to group F. This increase might be attributed due to more absorption of food grade
beta carotene from nanoemulsions due to smaller droplet size (Mehmood, 2015).
127
Table 4.32: ANOVA for effect of different treatments of beta carotene
nanoemulsions on tail DNA
Source DF SS MS F P
Groups 6 5929.71 988.284 6526 0.0001
Error 14 2.12 0.151
Total 20 5931.83
Figure 4.31: Effect of beta carotene nanoemulsions on tail DNA
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)
Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
Group F = Beta carotene in olive oil (9000 IU/Kg body weight)
PC = Positive Control
E
D
D
C
B
E
A
0 10 20 30 40 50 60 70
Group A
Group B
Group C
Group D
Group E
Group F
PC
Tail DNA (%)
128
Over findings are similar to the findings of other researchers who found
significant effect of neem oil nanoemulsions on percent tail DNA in comet assay
(Jerobin et al., 2015).
The effects of different treatments of nanoemulsions on the tail DNA of
different mice groups are given in Figure 4.32. ANOVA results depicted that
treatments have significant effect (p < 0.05) on the tail DNA of different groups
(Table 4.33). The value of tail DNA was significantly higher (p < 0.05) in group B
(blank nanoemulsions) as compared to group A (control group). Furthermore, dose
depended response was observed in group C, D and E. The value of tail DNA
significantly increased with the increase in vitamin D. Despite significant increase,
these values were far less as compared to tail DNA value of control group.
Additionally, significant difference was observed between group C (Nanoemulsion
containing 1800 IU/Kg body weight vitamin D) and group F (1800 IU/Kg body
weight vitamin D in canola oil). The values of tail DNA was significantly higher in
group C as compared to group F. This increase might be attributed due to more
absorption of vitamin D from nanoemulsions due to smaller droplet size
(Mehmood, 2015). Over findings are similar to the findings of other researchers
who found significant effect of neem oil nanoemulsions on percent tail DNA in
comet assay (Jerobin et al., 2015).
4.6.3.3 Olive moment
Olive moment is a product of length of tail and total DNA fraction in tail. It
is a useful tool to investigate DNA damage. The effect of beta carotene
nanoemulsions on the olive moment of different mice groups is summarized in
Figure 4.33. Statistical analysis results indicate that olive moment of different mice
129
Table 4.33: ANOVA for effect of different treatments of vitamin D nanoemulsions
on tail DNA
Source DF SS MS F P
Groups 6 7339.29 1223.21 8078 0.0001
Error 14 2.12 0.15
Total 20 7341.41
Figure 4.32: Effect of different treatments of vitamin D nanoemulsions on tail
DNA in comet assay
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)
Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
Group F = Vitamin D in canola oil (1800 IU/Kg body weight)
PC = Positive Control
F
E
D
C
B
G
A
0 10 20 30 40 50 60 70 80
Group A
Group B
Group C
Group D
Group E
Group F
PC
Tail DNA (%)
130
Table 4.34: ANOVA for effect of different treatments of beta carotene
nanoemulsions on olive moment
Source DF SS MS F P
Groups 6 6.53811 1.08969 720 0.0001
Error 14 0.02120 0.00151
Total 20 6.55931
Figure 4.33: Effect of beta carotene nanoemulsions on olive moment
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)
Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)
Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)
Group F = Beta carotene in olive oil (9000 IU/Kg body weight)
PC = Positive Control
E
C
C
C
B
D
A
0 0.5 1 1.5 2 2.5
Group A
Group B
Group C
Group D
Group E
Group F
PC
Olive Moment
131
groups significantly deviates (p < 0.05) from each other (Table 4.34). Olive
moment was significantly different (p < 0.05) in group F (9000 IU/Kg body weight
beta carotene in olive oil), group B (blank nanoemulsions) as compared to group A
(control group). However, non-significant difference (p >0.05) was observed
between group C (Nanoemulsion containing 9000 IU/Kg body weight beta
carotene), group B (blank nanoemulsions) and group D (12000 IU/Kg body weight
beta carotene). Additionally, the olive moment was significantly higher (p < 0.05)
in E due to higher dose of beta carotene. But, the value of olive moment in E group
(16000 IU/Kg body weight beta carotene) was significantly lower as compared to
positive control (even less than half). Although, significant effect of beta carotene
nanoemulsions (having different concentration of beta carotene) was observed on
olive moment of different groups of mice, their values are significantly lower as
compared with positive control. Hence, it is concluded that beta carotene
nanoemulsions (with lower amount of beta carotene) did not cause genotoxicity in
mice, but nanoemulsions with higher amount of beta carotene can cause slight
increase in the value of olive moment. The findings of our study are opposite to the
findings of the other researchers who observed non-significant effect of andiroba
oil nanoemulsions on DNA damage (Milhomem-Paixão et al., 2017).
The effect of vitamin D nanoemulsions on the olive moment of different mice
groups is summarized in Figure 4.34. Statistical analysis results indicate that olive
moment of different mice groups significantly deviates from each other (Table
4.35). Olive moment was significantly higher (p < 0.05) in group B (blank
nanoemulsions) as compared to group A (control group). However, group C
(Nanoemulsion containing 1800 IU/Kg body weight vitamin D) significantly
132
Table 4.35: ANOVA for effect of different treatments of vitamin D nanoemulsions
on olive moment
Source DF SS MS F P
Groups 6 1264.67 210.779 1392 0.0001
Error 14 2.12 0.151
Total 20 1266.79
Figure 4.34: Effect of vitamin D nanoemulsions on olive moment
Group A = Control group
Group B = Blank nanoemulsions
Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)
Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)
Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)
Group F = Vitamin D in canola oil (1800 IU/Kg body weight)
PC = Positive Control
F
DE
D
C
B
EF
A
0 0.5 1 1.5 2 2.5 3 3.5
Group A
Group B
Group C
Group D
Group E
Group F
PC
Olive Moment
133
deviate (p < 0.05) from group B (blank nanoemulsions), and group F (1800 IU/Kg
body weight vitamin D in canola oil). Additionally, the olive moment was
significantly higher deviate (p < 0.05) from group B (blank nanoemulsions), in
group D and E due to higher dose of vitamin D. But, the value of olive moment in
D and E groups were significantly lower as compared to positive control (even less
than half). Although, significant effect of vitamin D nanoemulsions (having
different concentration of vitamin D) was observed on olive moment of different
groups of mice, their values are significantly lower as compared with positive
control. Hence it is concluded that vitamin D nanoemulsions (with lower amount of
vitamin D) did not cause genotoxicity in mice, but nanoemulsions with higher
amount of vitamin D can cause slight increase in the value of olive moment. The
findings of our study are opposite to the findings of the other researchers who
observed non-significant effect of andiroba oil nanoemulsions on DNA damage
(Milhomem-Paixão et al., 2017). This difference might be attributed due to use of
different ingredients for the preparation of nanoemulsions.
4.7 PREPARATION OF FORTIFIED BEVERAGE
After toxicology studies, these nanoemulsions were used for the preparation
of beta carotene and D fortified beverages. These fortified beverages are later on
subjected to different physicochemical analysis and results are summarized in
Table 4.36. Degradation of beta carotene and vitamin D was observed during the
storage of beverages. Previous studies also reported degradation of beta carotene
and vitamin D during storage (Chu et al., 2008; Khalid et al., 2017). Additionally,
sensory evaluation of these beverages was carried out determine their overall
acceptability. Sensory evaluation results indicate that the sensory score of these
134
Table 4.36: Physicochemical properties of beta carotene and vitamin D fortified
beverages
Parameters
Beta Carotene Fortified
Beverages
Vitamin D Fortified
Beverages
pH 5.8±0.11 6.1±0.17
Viscosity (cP) 4.22±0.07 4.31±0.03
°Brix 16.0±0.11 16.8±0.06
Vitamin (%) 81± 1.5 84± 1.8
Table 4.37: Sensory Evaluation of beta carotene and vitamin D fortified beverages
Parameters
Beta Carotene Fortified Beverages Vitamin D Fortified Beverages
0 Day 60 Days 0 Day 60 Days
Taste 7.4±1.15a 7.1±1.3b 7.5±1.2a 7.1±1.41b
Color 8.5±0.9a 8.0±1.13b 8±1.22a 7.7±1.25a
Flavor 8.5±1.5a 7.8±1.25b 8.4±1.25a 8±1.15a
Overall
Acceptability
8.2 ±1.7a 7.7±1.3b 7.8±0.9a 7.2±1.1b
135
beverages lies in acceptable limit (Table 4.37). Later on, these nanoemulsions are
stored at room temperature and their sensory evaluation was performed after two
months of storage. Sensory evaluation results indicate that the nanoemulsions
based beverages were still acceptable after two months of storage. The findings of
this study will be helpful for development of beverages fortified with lipophilic
compounds.
136
SUMMARY
Nutritional deficiency of vitamin A and D is causing a lot of problems in the
world. It is estimated that about one billion people worldwide are either vitamin D
deficient or have insufficient vitamin D intake. In Pakistan about 85% of both
pregnant and non-pregnant mothers have been found vitamin D deficient. Apart
from this, 5.7 million children below 5 years of age and 42.5 % women were
identified as vitamin A deficient in Pakistan. Being food fortification or
supplementation a best approach, the food manufacturers are interested in
fortifying their products with vitamin A and D. As both vitamins are restricted to
fats and oils due to their non-solubility in water. Nanoemulsions are ideal solution
to address this problem because this technique enhances the solubility, kinetic
stability, bio efficacy and bioavailability of encapsulated material due to their
smaller size. The purpose of present study was to fortify beverages with
nanoemulsions of vitamin A and D.
The nanoemulsions were prepared by using food grade surfactants (Tween
80 and soya lecithin), deionized water and vegetable oil (olive and canola oil).
Preparation conditions for beta carotene and vitamin D nanoemulsions were
optimized using response surface methodology. These nanoemulsions were further
characterized against different physico-chemical parameters. In vivo study was
carried out on animal model to investigate the safety of nanoemulsions. The
nanoemulsions based delivery system was used to fortify the beverages with these
vitamins.
The results manifested that, ideal optimum preparation conditions for beta
carotene nanoemulsions were 6.07% surfactant, 4.19 minutes homogenization time
136
137
and 6.50% oil contents. The experimental values at optimized preparation
conditions were 119.33nm droplet size, 2.67 p-Anisidine value and 85.63% β-
carotene retention. For vitamin D nanoemulsions, optimum preparation conditions
were 4.82 minutes homogenization time, 0.67 surfactant to oil ratio (S/O) and 7%
disperse phase volume. Whereas, the experimental values for droplet size, droplet
growth ratio (DGR) and vitamin D retention were 112.36 ± 3.6nm, 0.141 ± 0.07
and 76.65 ± 1.7% respectively.
During two months of storage studies, these nanoemulsions remained stable
against phase separation and creaming. Moreover, droplet size of nanoemulsions
stored at 4 °C slowly increased as compared to nanoemulsions stored at 25 °C.
Additionally, p-Anisidine value of the vegetable oil (canola and olive oil)
incorporated into nanoemulsions were significantly lower as compared to free
vegetable oil. These nanoemulsions were stable against droplet aggregation and
phase separation over a wide range of pH (2-8), salt concentration (50-400 mM)
and temperature (30-80°C). Additionally, these nanoemulsions were remain stable
during freeze-thawing cycles.
During toxicity study, bi-nuclear assay, multi-nuclear assay and comet assay
did not showed any toxic effect of nanoemulsions on animal models. However,
when higher amount of vitamins were used then mild toxic effects were observed
which were not higher enough to cause severe damage. Furthermore,
nanoemulsions increased the weight of experimental animals. During last part of
study, vitamin A and D fortified model beverages was developed successfully.
Hence, nanoemulsions based delivery system can be used for fortification of
aqueous products with fat soluble vitamins and other nutraceutical compounds.
138
RECOMMENDATIONS
Mixed surfactants should be used for the development of nanoemulsions
instead of using single surfactant.
Detailed studies should be carried out on nanoemulsion fortified beverages
in order to investigate their different physicochemical parameters.
Additional trail should be conducted at pilot scale for suitability and cost
effectiveness of nanoemulsions based fortified beverages for commercial
applications.
Further research should be conducted to determine the bioavailability of
vitamins in nanoemulsions based delivery system.
Food products should be fortified with fat soluble vitamins to address the
problem of vitamin A and D deficiency.
138
139
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Appendix 1: Approval certificate from ethical committee
162
Appendix 2: Performa for sensory evaluation of fortified beverages
Name of judge: ___________________________ Date: _____________
Key for scoring
1. Extremely disliked
2. Very much disliked
3. Moderately disliked
4. Slightly disliked
5. Neither disliked nor liked
6. Slightly liked
7. Moderately liked
8. Very much liked
9. Extremely liked
Code Color Taste Flavor Overall acceptability
A
B
C
D
E
F
G
H
I
Signature of the judge: _______________
Contents lists available at ScienceDirect
Food Chemistry
journal homepage: www.elsevier.com/locate/foodchem
Optimization of mixed surfactants-based β-carotene nanoemulsions usingresponse surface methodology: An ultrasonic homogenization approach
Tahir Mehmooda,⁎, Anwaar Ahmeda, Asif Ahmada, Muhammad Sheeraz Ahmadb,Mansur Abdullah Sandhuc
a Institute of Food and Nutritional Sciences, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistanb Institute of Biochemistry and Biotechnology, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistanc Department of Veterinary Biomedical Sciences, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistan
A R T I C L E I N F O
Keywords:β-CaroteneNanoemulsionsRSMDroplet sizeMixed surfactantβ-Carotene retention
A B S T R A C T
In the present study, food grade mixed surfactant-based β-carotene nanoemulsions were prepared without usingany co-surfactant. Response surface methodology (RSM) along with central composite design (CCD) was used toinvestigate the effect of independent variables (surfactant concentration, ultrasonic homogenization time and oilcontent) on response variables. RSM analysis results revealed that experimental results were best fitted into aquadratic polynomial model with regression coefficient values of more than 0.900 for all responses. Optimizedpreparation conditions for β-carotene nanoemulsions were 5.82% surfactant concentration, 4 min ultrasonichomogenization time and 6.50% oil content. The experimental values at optimized preparation conditions were119.33 nm droplet size, 2.67p-Anisidine value and 85.63% β-carotene retention. This study will be helpful forthe fortification of aqueous products with β-carotene.
1. Introduction
β-Carotene is a member of the carotenoid family, which is mainlyfound in fruits and vegetables. It provides a substantial proportion ofvitamin A in the human diet because of its retinol precursor and higherconversion rate (Naves & Moreno, 1998). It is also useful in the pre-vention of numerous diseases, such as heart diseases, cataracts andcancer (Aherne, Daly, Jiwan, O’Sullivan, & O’Brien, 2010). Further-more, it is also used in the food industry as a colorant and antioxidant(Hou et al., 2012). Therefore, the food industry is interested in its in-corporation into food products to take advantage of the above-men-tioned benefits. However, its incorporation into beverages and variousother foods is challenging due to its poor water solubility, instability inheat, oxygen and light and appearance in crystalline state at ambienttemperature (Mattea, Martín, Matías-Gago, & Cocero, 2009). To over-come this problem, β- carotene can be dissolved in oil or another sui-table medium in oil in water emulsions before its incorporation intoaqueous food products (Qian, Decker, Xiao, & McClements, 2012).Stability of β-carotene in oil in water emulsion depends on the com-position of emulsion and environmental conditions, e.g. heat, surfac-tant, light, food systems, singlet oxygen and antioxidant addition (Houet al., 2010). The most convenient way to incorporate β- carotene intofood products is in a nanoemulsion based colloidal system.
Nanoemulsions are kinetically stable systems with mean radiiof< 100 nm. Furthermore, these emulsions have higher stability, so-lubility and bioavailability due to their smaller particle size as com-pared to conventional emulsions (McClements & Rao, 2011). Nanoe-mulsions can be produced using high energy and low energy methods.During high energy methods, intense disruptive force is generated tomechanically break the oil phase into tiny droplets, which can be dis-persed into the aqueous phase. These high energy methods (sonication,high pressure homogenization and microfluidization) are desirable forthe food industry because we can prepare nanoemulsions by usinglower surfactant to oil ratio as compared to low energy methods(Ozturk, Argin, Ozilgen, & McClements, 2014). Previously, some studieswere carried out on the preparation of β-carotene nanoemulsions usinglow energy methods, microfluidization and high pressure homo-genization but no study has been carried out on the preparation ofnanoemulsions through the ultrasonic homogenization method. Hence,the present study was designed to investigate the suitability of ultra-sonic homogenization for development of β-carotene nanoemulsions.
β-Carotene nanoemulsions prepared through the ultrasonic homo-genization method were influenced by multiple variables during ourlaboratory experiments (unpublished data). So, there is a need for op-timization of process or product in order to investigate the relationshipbetween independent variables and response variables. Response
https://doi.org/10.1016/j.foodchem.2018.01.136Received 8 October 2017; Received in revised form 4 January 2018; Accepted 22 January 2018
⁎ Corresponding author at: Institute of Food and Nutritional Sciences, PMAS-Arid Agriculture University, Rawalpindi, Pakistan.E-mail address: [email protected] (T. Mehmood).
Food Chemistry 253 (2018) 179–184
0308-8146/ © 2018 Elsevier Ltd. All rights reserved.
T
surface methodology is an effective mathematical and statistical tech-nique to investigate the effects of multiple independent variables andtheir interaction on response variables (Li, Wang, & Wang, 2017;Mehmood, Ahmad, Ahmed, & Ahmed, 2017). Hence, in our study, wehave used RSM for optimization of emulsifying conditions.
The present study was designed to prepare mixed surfactant-based,co-surfactant free (due to irritation and toxic effects of co-surfactants)β-carotene nanoemulsions using an ultrasonication approach. Afterthat, preparation conditions (surfactant concentration, homogenizationtime and oil content) for β-carotene nanoemulsions were optimizedusing RSM in order to obtain smallest droplet size, lower p-anisidinevalue and maximum β-carotene retention.
2. Material and methods
2.1. Materials
Tween 80 and soya lecithin were obtained from Sigma-Aldrich (St.Louis, USA). Purified β-carotene (powder form) was supplied by BASF(Lampertheim, Germany). Olive oil (refined, bleached and deodorized)was purchased from Hamza Vegetable Oil Refinery and Ghee Mills(Lahore, Pakistan). Double distilled water was used for the preparationof nanoemulsions and solutions.
2.2. Nanoemulsions preparation
Nanoemulsions were prepared by mixing 10% dispersed phase and90% continuous phase. The dispersed phase was prepared by dissolvinga pre-determined amount of β-carotene in olive oil (5.48–10.52%). Thecontinuous phase consisted of double distilled water carrying pre-de-termined amount of surfactants (2.64–9.36%). These components weremixed with polytron (KRH-I, KONMIX, Shanghai, China) at 8000 rpmfor 7min to prepare coarse emulsions. For the preparation of nanoe-mulsions, these coarse emulsions were subjected to ultrasonic homo-genization by using a 20 kHz sonicator (230VAC, Cole-Parmer, USA).Ultrasonic homogenization was performed by placing the tip horn(20mm diameter) of the sonicator in coarse emulsions and applyingultrasonic powers for different times (2.98–8.02min). The temperatureof the emulsions was controlled by placing them in ice bath duringhomogenization. These nanoemulsions were stored at room tempera-ture for further analysis.
2.3. Droplet size analysis
The droplet size of the nanoemulsions was measured by dynamiclight scattering using nanotrac (Microtrac, Tri-Blue, USA).Nanoemulsion samples were diluted to 10% by using deionized water inorder to avoid multiple scattering effects.
2.4. p-Anisidine value
p-Anisidine value is an important indicator of the stability of na-noemulsions. The oxidative stability of β-carotene nanoemulsions wasdetermined according to the method of Mehmood et al. (2017). Firstly,20 g of β-carotene nanoemulsions were incubated for one week at 50 °C.Then, 1 g of solution was dissolved in n-Hexane (HPLC Grade) and theabsorbance of the solutions was measured using an UV-spectro-photometer at 350 nm. After that, 1 ml p-Anisidine reagent (preparedby dissolving 2.5 g of p-Anisidine in one litre of acetic acid) was addedin 5ml of solution and they were incubated for 10min to allow theirreaction. The absorbance of the fat solution was also determined as ablank in a reference cell. p-Aniside value was determined using Eq. (1):
− =× −p Anisidine Value 25 (1.2A A )
MAR BR
(1)
where AAR is the absorption of the solution after reaction, ABR
represents absorption before reaction and M denotes sample mass ingrams.
2.5. β-Carotene retention
The concentration of β-carotene in nanoemulsions was determinedafter one week by a spectrophotometric method. Firstly, a 1ml samplewas extracted using a mixture of n-Hexane (3ml) and ethanol (2 ml).After that, this mixture was shaken well and the hexane phase wasremoved. This extraction procedure was repeated two times more. Atthe end, all hexane phases were combined and their absorbance wasmeasured through an UV- spectrophotometer at 450 nm after desireddilution with n-Hexane. The β-carotene concentration was determinedusing a standard curve prepared under similar conditions. Vitamin re-tention was calculated using Eq. (2):
= ×VVR /V 100BC BC,N BC,I (2)
where VRBC represents β-carotene retention, VBC,N is the concentrationof β-carotene in the nanoemulsion and VBC,I indicates initial con-centration of β-carotene (Yuan, Gao, Zhao, & Mao, 2008).
2.6. Experimental design
Response surface methodology was used to investigate the effect ofindependent variables, including surfactant concentration (X1), ultra-sonic homogenization time (X2) and oil contents (X3) on responsevariables, such as droplet size (Y1), p-Anisidine value (Y2) and retentionof β-carotene (Y3) in nanoemulsions. RSM design along with coded anduncoded levels is presented in Table 1. Central composite design (Fivelevels) and quadratic model was used to design this experiment. Twentytreatments, including six axial points, eight fractional factorial pointsand six central points were randomly performed according to CCD,which is summarized in Table 1. Real levels of independent variableswere coded according to Eq. (3);
= −−Z ZZ Z /Δ0 C (3)
where Z and Z0 indicate coded and real levels of independent variables,respectively. ΔZ represents step change while ZC indicates actual valueat the central point. The specific equations for each independent vari-able were derived from the above equation to code their actual values.Specific equations for surfactant concentration (X1), ultrasonic homo-genization time (X2) and oil contents (X3) are mentioned in below Eqs.(4)–(6).
= −z (MS 6)/21 (4)
= −z (HT 5.5)/1.52 (5)
= −z (OC 8)/1.53 (6)
where MS, HT and OC represent surfactant concentration, homo-genization time and oil contents, respectively.
A second order polynomial equation was used to indicate the pre-dicted responses (droplet size, p-Anisidine value and retention of β-carotene) as a function of an independent variable as follows (Eq. (7)):
Table 1Independent variables and their corresponding levels for β- Carotene nanoemulsion.
Independent variable Symbol Coded levels
−α −1 0 +1 +α
Surfactant Concentration (%) X1 2.64 4 6 8 9.36Homogenization Time (min) X2 2.98 4 5.5 7 8.02Oil Content (%) X3 5.48 6.5 8 9.5 10.52
T. Mehmood et al. Food Chemistry 253 (2018) 179–184
180
= + + + + + + + +
+
β β Y β Y β Y β Y β Y β Y β Y Y β Y Y
β Y Y
Z 0 1 1 2 2 3 3 11 12
22 22
33 32
12 1 2 13 1 3
23 2 3 (7)
where Z represents response values, β β βj jj jkindicates the values of linear,quadratic and interactive coefficients, respectively and β0is constant.Design expert software (version. 6.0.11) was used to calculate the va-lues of coefficients of determinations.
2.7. Statistical analysis
Experimental data were statistically analyzed using Design ExpertSoftware (version 6.0.11). Numerous statistical parameters (lack-of-fit,predicted and adjusted multiple correlation coefficients and coefficientof variation) of different polynomial models were compared to selectthe best fitting polynomial model. Significant difference was de-termined through analysis of variance by calculating F-value at theprobability of 0.5, 0.1 and 0.01. To understand the effect of emulsifyingconditions on response variables, response plots were generated usingDesign Expert Software (version 6.0.11). All these experiments wereperformed in triplicate.
3. Results and discussion
3.1. Fitting the model
Response surface methodology (RSM) is a statistical, theoretical andmathematical technique for model building in order to optimize thelevel of independent variables (Homayoonfal, Khodaiyan, & Mousavi,2015). The effect of independent variables (β-carotene nanoemulsions)on droplet size (Y1), p-Anisidine value (Y2) and retention of β-carotene(Y3) are given in Table 2. Coefficients of polynomial equation werecomputed from experimental data to predict the values of the responsevariable. Regression equations for each response variable, obtainedfrom response surface methodology are mentioned in Eqs. (8)–(10):
= + − + + + −
+ − − −
Droplet Size 101.66 12.16Y 22.83Y 0.74Y 1.53Y 1.76Y
0.37Y 0.96Y Y 0.46Y Y 0.39Y Y1 2 3 1
222
32
1 2 1 3 2 3 (8)
− = + − − − + +
+ − + −
p Anisidine Value 29.78 2.40Y 1.46Y 4.34Y 0.10Y 0.19Y
0.31Y 0.013Y Y 0.063Y Y 0.017Y Y1 2 3 1
222
32
1 2 1 3 2 3 (9)
− = + + + − −
− + − − +
β Carotene Retention 16.43 21.23Y 22.68Y 16.19Y 0.80Y
1.90Y 0.93Y 0.79Y Y 0.29Y Y 0.17Y Y1 2 3 1
2
22
32
1 2 1 3 2 3
(10)
Statistical analysis (ANOVA) results revealed that the experimentaldata could be represented well with a quadratic polynomial model withcoefficient of determination (R2) values for droplet size (Y1), p-Anisidine value (Y2) and retention of β-carotene (Y3) being 0.9456,0.9580 and 0.9604, respectively (Table 3).
Lack of fit was non-significant (p≤ 0.05) relative to pure error forall variables, which indicates that our model is statistically accurate. Ifthe value of R2 is closer to unity then it is the indication of better modelfitting to actual data. On the other end, lower values of R2 indicate thatresponse variables were not appropriate to explain the variation inbehaviour (Myers, Montgomery, & Anderson-Cook, 2016). In our study,proximity to unity R2 demonstrates that the influence of surfactantconcentration (X1), ultrasonic homogenization time (X2) and oil con-tents (X3) on response variables could be adequately described througha quadratic polynomial model. Significance level for coefficients of thequadratic polynomial model were determined through analysis of var-iance (ANOVA). Smaller P-value and larger F-value is the indication of ahighly significant effect of any term on the response variable(Quanhong & Caili, 2005).
3.2. Effect of independent variables on response variables
β-Carotene nanoemulsions were successfully prepared by usingdifferent levels of independent variables (Fig. 1). The effect of in-dependent variables on droplet size, p-anisidine value and β-caroteneretention are given in Table 2. Regression coefficients for independentvariables are summarized in Table 3.
3.2.1. Droplet sizeThe droplet size of β-carotene nanoemulsions depended on surfac-
tant concentration due to its significant effect on droplet size at a linear(p < 0.001), quadratic (p < 0.001) and interaction level (p < 0.05)with homogenization time. Surfactants lower the interfacial tensionsbetween disperse and continuous phase, which leads to smaller dropletformation (Mehmood et al., 2017). Other independent variables, whichhad significant effect on droplet size were linear term of homogeniza-tion time (p < 0.001) and oil content (p < 0.05), and quadratic termsof homogenization time (p < 0.001).
The influence of homogenization time and surfactant concentrationon droplet size of β-carotene nanoemulsions is illustrated in Fig. 2 (A).Both these variables exert quadratic effect on droplet size. At highersurfactant concentration, decrease in droplet size of nanoemulsions wasobserved with the increase of homogenization time. This downward
Table 2Experimental design for β- Carotene nanoemulsions with independent variables, experi-mental and predicted values of responses.
Run Independent Variables Response Values
Surfactant (%) Time(min)
OilContent(%)
DropletSize (nm)
p-AnisidineValue
β- Caroteneretention(%)
1 8 4 6.50 121 1.5 942 6 5.50 8 110 3.2 773 4 7 6.50 115 6.3 644 6 5.50 5.48 111 3.3 925 8 4 9.50 125 5.2 846 6 8.02 8 89 5.6 667 9.36 5.50 8 122 2.1 868 6 5.50 10.52 124 7.1 829 6 5.50 8 114 4.1 8010 6 5.50 8 110 3.7 7611 8 7 9.50 101 5.9 7512 8 7 6.50 104 3.1 8213 6 5.50 8 117 3.6 8314 6 5.50 8 121 3.5 8015 4 4 6.50 124 5.3 6516 4 4 9.50 130 7.5 6017 6 5.50 8 117 4 8018 2.64 5.50 8 143 6.7 5819 6 2.98 8 119 3.3 7220 4 7 9.50 121 9.1 59
Table 3Regression coefficients values for β- Carotene nanoemulsions.
Regressioncoefficients
Droplet size(nm)
p-AnisidineValue
β- CaroteneRetention (%)
Intercept (α0) 114.85 3.66 79.43A-Surfactant (α1) −5.44*** −1.48*** 9.82***
B-Time (α2) −8.01*** 0.64** −2.42*
C-Oil (α3) 2.55* 1.31*** −3.21**
A2 (α11) 6.13*** 0.41* −3.21**
B2 (α22) −3.95** 0.43* −4.27***
C2 (α33) 0.82 0.69*** 2.09*
AB (α12) −2.88* −0.038 −2.37*
AC (α13) −1.38 0.19 −0.87BC (α23) −0.88 −0.037 0.38R2 0.9456 0.9580 0.9604
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trend was observed due to reduction of interfacial tension with theincrease in surfactant concentration (Polychniatou & Tzia, 2018). Atlower surfactant concentration, droplet size increased with increasinghomogenization time. This increase was observed because not enoughemulsifier is present to cover newly formed smaller droplets, whichinitiates a coalescence process (Anarjan, Mirhosseini, Baharin, & Tan,2010). Fig. 2(B) represented the combined effect of oil and surfactantconcentration on the droplet of β-carotene nanoemulsions. Oil contentexerts a linear effect while surfactant concentrations have a quadraticeffect on droplet size of nanoemulsions. Droplet size increased withrising oil concentration due to increase in viscosity. As a result of this,higher energy is required to break the droplet, which results in largerdroplet size. Additionally, higher oil concentration encourages ag-gregation and collision of nanoemulsion droplets, which increased thedroplet size (Mehmood, 2015; Zhang, Fan, & Smith, 2009). Initially,droplet size decreased with the increase of surfactant concentration dueto reduction in surface tension. But, after a minimal level, higher con-centration of surfactant caused increased width of the diffusion layerdue to excessive coverage of crystalline particles by surfactant. Thismechanism lowers zeta potential value and encourages agglomerationtendency, which increased droplet size of β-carotene nanoemulsions(Mehmood et al., 2017; Tan, Billa, Roberts, & Burley, 2010).
3.2.2. p-Anisidine valuep-Anisidine value is an important indicator for measurement of
oxidation products (Cho, Kim, Bae, Mok, & Park, 2008). As the p-Ani-sidine value of β-carotene nanoemulsions was concerned, oil contenthad a pronounced effect on the p-Anisidine value of β-carotene na-noemulsions due to its significant effect on p-Anisidine value at a linear(p < 0.001) and quadratic level (p < 0.001). Other factors whichsignificantly contribute toward p-Anisidine value were linear term ofsurfactant concentration (p < 0.001) and homogenization time(p < 0.001), and quadratic term of surfactant concentration(p < 0.05) and homogenization time (p < 0.05). The lipid oxidationmechanism is remarkably different in nanoemulsions as compared withbulk oily phase due to the presence of interface and aqueous phase. Innanoemulsions, lipid oxidation depends on many factors, which includeoxygen concentration, pH and ionic strength of aqueous phase, dropletsize, thickness and interfacial properties (Waraho, McClements, &Decker, 2011; Öztürk, Urgu, & Serdaroğlu, 2017).
The combined effects of homogenization time and surfactant con-centration on p-Anisidine value are illustrated in Fig. 2(C), which ex-plicated the linear effect of both independent variables on p-Anisidinevalue. p-Anisidine value of β-carotene nanoemulsions increased with
the increase in homogenization time while higher concentration ofsurfactants result in a lower p-Anisidine value. During this study, β-carotene nanoemulsions were developed using mixed surfactant(Tween 80 and soya lecithin), which act as an interfacial barrier againstoxidation. These surfactants built a protective membrane at the inter-face of the aqueous and oily phase, which remarkably reduces proox-idant accessibility into oil droplets, which results in lower p-Anisidinevalue (Hwang et al., 2017). Fig. 2(D) depicts the interactive effect of oilcontent and surfactant concentration on p-Anisidine value. Both vari-ables have a linear effect on the p-Anisidine value of β-carotene na-noemulsions. The downward trend was observed in p-Anisidine valuewith the increase of surfactant and oil concentration. Oil concentrationshave an inverse effect on p-anisidine value because droplet size in-creases when oil concentration is high, which results in lower p-Anisi-dine value due to reduced surface area for oxidation (Mehmood et al.,2017).
3.2.3. β-Carotene retentionβ-Carotene retention of nanoemulsion mainly depended on surfac-
tant concentration as it had a significant effect on vitamin retention atlinear (p < 0.001), quadratic (p < 0.01) and interactive level(p < 0.05). Surfactant prevents the degradation of β-carotene byforming a membrane like structure around new surfaces (Hejri,Khosravi, Gharanjig, & Hejazi, 2013). Other factors which significantlycontributed to β-carotene retention were linear effect of homogeniza-tion time (p < 0.05) and oil content (p < 0.01), quadratic effect ofhomogenization time (p < 0.001) and oil content (p < 0.05) and in-teractive effect of homogenization time (p < 0.05).
A contour plot in Fig. 2(E) illustrates the retention of β-carotene as afunction of homogenization time and surfactant concentration. Sur-factant concentrations have a linear effect while homogenization timeexerts a quadratic effect on the retention of β-carotene. At a lower levelof surfactant, β-carotene retention is significantly reduced with in-creasing homogenization time due to the formation of smaller droplets,which are not covered with surfactant molecule. Hence, surface area ofdroplet significantly increases, which encourages β-carotene degrada-tion (Waraho et al., 2011). Additionally, pre-existence of peroxides insurfactant molecules may also cause β-carotene degradation. Theseperoxides breakdown into reactive radicals at elevated temperature andsignificantly degrade β-carotene during storage (Liu & Wu, 2010).Fig. 2(F) represents the interactive effect of oil content and surfactantconcentration on the β-carotene retention in nanoemulsions. Bothemulsifying conditions have a linear effect on β-carotene retention.With the increase in surfactant concentration, degradation of β-
Fig. 1. (A) Particle size distribution of β-carotene nanoe-mulsions (B) Visual appearance of β-carotene nanoemul-sions.
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carotene reduced due to the formation of a rigid surfactant shell at thewater–oil interface. This shell increases the stability of β-carotene bypreventing repulsion of β-carotene and avoiding new surface formation(Hejri et al., 2013). Higher oil content also increases the stability of β-carotene nanoemulsions by formation of larger droplets, which havelower surface area (Liu & Wu, 2010).
3.3. Optimization of independent variables
To illustrate the effects of surfactant concentration, homogenizationtime and oil content on response variables, response surface graphswere drawn using design expert software. These graphs were generatedby varying two independent variables within experimental ranges while
keeping the third variable at central point. Fig. 2(A, C and E) weregenerated by varying the surfactant concentration and homogenizationtime at 8% oil content, while Fig. 2(B, D and F) were drawn by chan-ging the concentration of oil and surfactant at a central value ofhomogenization time (5.5 min). These graphs illustrated complex in-teraction among independent variables.
After that, numerical optimization was executed by desirabilityfunction using Design Expert Software. The goals selected for the op-timization of β-carotene nanoemulsions were minimum level of sur-factant concentration, homogenization time and oil content in order toobtain smaller droplet size, lower p-Anisidine value and maximum re-tention of β-carotene. Ten different solutions were found which containdifferent levels of independent variables. The solution with maximum
Fig. 2. 3D graphic surface optimization of(A) droplet size (nm) versus surfactant con-centration (%) and homogenization time(min) (B) droplet size (nm) versus oil content(%) and surfactant concentration (%) (C) p-Anisidine value versus surfactant concentra-tion (%) and homogenization time (min) (D)p-Anisidine value versus oil content (%) andsurfactant concentration (%) (E) β-caroteneretention (%) versus surfactant concentra-tion (%) and homogenization time (min) (F)β-carotene retention (%) versus oil content(%) and surfactant concentration (%).
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desirability value was selected as the optimized emulsifying condition.Combined optimized preparation conditions for β-carotene nanoemul-sions were 5.82% surfactant concentration, 4min. ultrasonic homo-genization time and 6.50% oil content. The response values at opti-mized preparation conditions were 116.46 nm droplet size, 2.937p-Anisidine value and 82.085% β-carotene retention (Table 4).
3.4. Verification of RSM model
Optimized emulsifying conditions were used to check the suitabilityof the model for prediction of response values. Optimized preparationconditions were validated by performing experiments under optimizedconditions. The response values at optimized preparation conditionswere 116.46 nm droplet size, 2.937p-Anisidine value and 82.085% β-carotene retention. On the other hand, the experimental values at op-timized preparation conditions were 119.33 nm droplet size, 2.67p-Anisidine value and 85.63% β-carotene retention. Experimental re-sponse values were well in agreement with predicted response values(Table 4).
4. Conclusions
In this study, we have evaluated the preparation conditions of β-carotene nanoemulsions using ultrasonic homogenization techniquesand incorporated β-carotene in mixed surfactant-based nanoemulsionsin order to protect β-carotene from harsh environmental conditionsduring food fortification. Mixed surfactant-based β-carotene nanoe-mulsions were successfully prepared using an ultrasonic homogeniza-tion approach. This study illustrates that response surface methodologyis a useful tool to optimize the emulsifying conditions of β-carotenenanoemulsions and explore the relationship between independent andresponse variables. The results of this study showed that emulsifyingcondition and ingredients have significant effect on the properties ofnanoemulsions. The current study illustrates that the quadratic modelwas sufficient to describe and predict the responses of droplet size, p-Anisidine value and β-carotene retention, with the change of in-dependent variables (surfactant concentration, homogenization timeand oil content). The optimum condition was obtained through nu-merical optimization using desirability function. Optimized preparationconditions for β-carotene nanoemulsions were 5.82% surfactant con-centration, 4min. ultrasonic homogenization time and 6.50% oil con-tent.
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Table 4Optimum conditions, experimental and predicted value of response at optimized condi-tions.
Optimum Conditions Coded Levels Actual Levels
Surfactant Concentration (%) −0.09 5.82Homogenization Time (min) −1.00 4Oil Contents (%) −1.00 6.50
Response Predicted Values Experimental Values
Droplet Size (nm) 116.46 119.33 ± 2.5p-Anisidine Value 2.937 2.67 ± 0.9β- Carotene Retention (%) 82.085 85.63 ± 1.5
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