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Anne Vuholm Sunds Student No. 20113104

Master thesis 2016 Molecular Nutrition and Food Technology - Aarhus University

Evaluation of accelerated shelf life testing of UHT milk Master of Science thesis - 60 ECTS

Title: Evaluation of accelerated shelf life testing of UHT milk

Project period: 3th

August 2015 to 1st July 2016

Defence: 8th

July

Written by: Anne Vuholm Sunds

Student number: 20113104

Education: MSc in Molecular Nutrition and Food Technology

Internal supervisor:

Lotte Bach Larsen, Professor

Department of Food Science, Faculty of Science and Technology

External supervisor:

Valentin Maximilian Rauh, Research Scientist

Arla Strategic Innovation Centre, Ingredients and Milk Science

Project location:

Aarhus University Arla Strategic Innovation Centre

Department of Food Science Ingredients and Milk Science

Blichers Allé 20 Rørdrumvej 2

8830 Tjele 8220 Brabrand

Denmark Denmark

Number of pages: 85

Preface and acknowledgements

This master thesis project is a result of 11 months of work at Arla Strategic Innovation Centre and

the Faculty of Science and Technology, Department of Food Science at Aarhus University, in the

period from August 2015 to July 2016.

My greatest thank goes to my university supervisor Lotte Bach Larsen and my supervisor at Arla

Valentin Maximilian Rauh. Lotte, thank you for your great support and scientific guidance, I am

very glad to have had you as my supervisor. Valentin, thank you for the opportunity to work with

you and your colleagues at Arla, it has been a pleasure and thank you for your great guidance and

proofreading of manuscripts.

I also owe a huge thank to the laboratory technicians at Arla for the help with equipment and data

analysis. Mona Slyngborg and Betina Mikkelsen I appreciate all your help with the functionality

analyses, and for your support. Jan Breinholt Carlsen and Lene Buhelt Johansen, thank you very

much for your help with GC-MS and HPLC. Thank you to Gitte Hald Kristiansen and Ida Sørensen

for your assistance with the quantification of furosine.

Thanks to my fellow master student Lina Berg for great discussions, support and motivational pep

talks, and thank you to my family and friends for their encouragement and support.

Aarhus University, Department of Food Science, July 2016

Anne Vuholm Sunds

Abstract

Development of UHT dairy products requires time consuming and resource intensive shelf life

tests. Thus, a valid accelerated shelf life test would be of high value in the development of new

products. This thesis provides a quantification of chemical and physical changes in commercial

UHT milk stored at different temperatures, with the aim of establishing a valid setup to accelerate

shelf life development. The temperatures selected were; 10 °C, 20 °C, 30 °C, 40 °C and 50 °C as

well as three temperature cycles. The skimmed and full fat UHT milk samples were analysed during

a storage period of 24 weeks. This included chemical analyses of the three phases of the Maillard

reaction (MR) as well as the lipid oxidation. The initial stage of the MR was analysed by a

quantification of furosine using high performance liquid chromatography (HPLC). The intermediate

stage of the MR was analysed by fluorescence spectroscopy and gas chromatography-mass

spectroscopy (GC-MS). Finally, the late stage of the MR was analysed with colour measurements.

An evaluation of physical destabilization was conducted with focus on gravitational separation, in

form of creaming and sedimentation. Physical changes were analysed using; optical stability

analyzers, evaluation of protein and fat distribution in; top, middle and bottom fractions, as well as

analysis of fat globule size distribution.

Exposure to elevated temperatures accelerated both chemical and physical changes over the storage

period. The chemical changes revealed data possible to describe with kinetic models. Formation of

furosine followed a first order reaction kinetic, whereas fluorescence and colour changes followed a

zero order reaction kinetic. Additionally, all three stages of the MR fitted into the Arrhenius

equation. Following corresponding Q10 values were obtained; for the initial MR of 1.5 to 2.3, for

the intermediate MR of 3.9 to 10.9 and for the late MR of 2.8 to 6.

The acceleration of physical changes varied between the applied methods, where different rates of

creaming and sedimentation were observed. No changes in fat globule size distribution were found,

which may indicate that other parameters are affecting the creaming rate, possibly by viscosity and

density changes. Development of the three temperature cycles varied between chemical and

physical parameters analysed. This was illustrating that it is only slightly possible to delay the MR

once it has started, even when exposed to lower storage temperatures. On the other hand, physical

parameters followed the average temperature. For future accelerated shelf life tests, a prediction of

shelf life seems to be possible within the temperature range of 20 °C to 30 °C. These findings are

based on the Arrhenius plots obtained in the present study.

Sammendrag

Udviklingen af UHT mejeri produkter, resulterer i tids- og ressourcekrævende holdbarhedstests.

Derfor vil en valid accelereret holdbarhedstest, være af stor værdi i udviklingen af nye produkter.

Denne specialeafhandling vil give en kvantificering af kemiske og fysiske ændringer i kommerciel

skummet og sød UHT mælk, oplagret ved forskellige temperaturer. Formålet med studiet er at

etablere en gyldig opsætning for acceleration af de processer der har indflydelse på holdbarheden.

De udvalgte temperaturer var; 10 °C, 20 °C, 30 °C, 40 °C og 50 °C så vel som tre temperaturcykler.

UHT mælkeprøverne blev analyseret gennem oplagringsperioden på 24 uger. Dette inkluderede

kemiske analyser af de tre stadier af Maillard reaktionen (MR) samt af lipidoxidationen. Det

indledende stadie af MRén blev analyseret ved en kvantificering af furosin, ved brug af højtydende

væskekromatografi (HPLC). Det intermediære stadie af MRén blev analyseret ved fluorescens

spektroskopi og gaskromatografi-massespektrometri (GC-MS) og det sidste stadie af MRén blev

analyseret ved farvemåling. En evaluering af fysisk destabilisering blev udført med fokus på

tyngdeseparation, i form af dannelse af fløde på overfladen og sedimentation af protein. Fysiske

ændringer blev analyseret ved optiske stabilitetsanalyser, evaluering af protein- og fedtfordeling i

top, midte og bund, samt analyse af fordelingen af fedtkuglestørrelser.

Både kemiske og fysiske ændringer i mælken accelererede over oplagringsperioden ved udsættelse

for forhøjede temperaturer. Det var muligt at beskrive data fra de kemiske analyser med kinetiske

modeller. Dannelse af furosin fulgte en første ordens reaktionskinetik, mens fluorescens- og

farveændringerne fulgte en nulte ordens reaktionskinetik. Desuden passede alle tre stadier af MRén

ind i Arrhenius ligningen. Følgende korresponderende Q10 værdier blev fundet: 1,5 til 2,3 for den

indledende MR, 3,9 til 10,9 for den intermediære MR og 2,8 til 6 for den sene MR.

Accelerationen af fysiske ændringer varierede mellem de benyttede metoder, hvor forskellige rater

af flødedannelse og sedimentation blev observeret. Der blev ikke observeret nogen ændringer i

fordelingen af fedtkuglestørrelse, hvilket kan indikere at andre parametre har indflydelse på den

observerede flødedannelse, muligvis på grund af ændringer i viskositet og densitet. Udviklingen af

de tre temperaturcykler varierede mellem de kemiske og fysiske parametre der blev analyseret.

Dette illustrerer at det kun delvist er muligt at forsinke MRén når først den er startet, selv ved

udsættelse for lavere oplagringstemperaturer. De fysiske parametre fulgte derimod gennemsnits-

temperaturen. En forudsigelse af holdbarheden synes at være mulig mellem 20 °C og 30 °C, for

accelererede holdbarhedstests i fremtiden. Disse resultater er baseret på Arrhenius graferne fra de

kemiske analyser.

Abbreviations

AGE: Advanced glycation end-products

CN: Casein

DAD: Diode array detector

DHS: Dynamic headspace sampling

DTE: Dithioerythritol

DLVO: Deyaguin-Landau-Verwey-Overbeek

ESL: Extended shelf-life

FT-IR: Fourier transform infrared spectroscopy

GC-MS: Gas chromatography–mass spectrometry

HMF: Hydroxymethylfurfural

LA-transformation: Lobry de Bruyn-van Ekenstein-transformation

LC-MS: Liquid chromatography–mass spectrometry

MR: Maillard reaction

MRP: Maillard reaction product

MFG: Milk fat globule

MFGM: Milk fat globule membrane

PCA: Principal component analysis

RP-HPLC: Reversed phase-high pressure liquid chromatography

SIM: Selected ion monitoring

SLS: Static light scattering

SPME: Solid phase micro-extraction

TAG: Triacylglyceride

TIC: Total ion current

UHT: Ultra high temperature

α-La: α-Lactalbumin

β-Lg: β-Lactoglobulin

Table of content

1. Aim and hypothesis……………………………………………………………………………… 1

2. Outline of the thesis………………………………………………………………………………2

3. Introduction……………………………………………………………………………………… 4

3.1 Milk…………………………………………………………………………………………………….. 4

3.1.1 Carbohydrates………………………………………………………………………………………………... 4

3.1.2 Proteins……………………………………………………………………………………………………….. 5

3.1.2.1 Analysis of protein composition by HPLC……………………………………………………………… 7

3.1.3 Lipids………………………………………………………………………………………………………….. 8

3.2 UHT milk………………………………………………………………………………………………. 8

3.3 Changes induced by UHT treatment…………………………………………………………………. 11

3.4 Enzymatic hydrolysis………………………………………………………………………………… 13

3.5 Chemical changes in UHT milk during storage………………………………………………………. 14

3.5.1 Maillard reaction…………………………………………………………………………………………… 15

3.5.2 Lipid oxidation……………………………………………………………………………………………… 19

3.6 Physical changes in UHT milk during storage……………………………………………………….. 21

4. Material and methods…………………………………………………………………………. 25

4.1 Milk samples and treatments…………………………………………………………………………. 25

4.2 Analysis of chemical changes………………………………………………………………………… 25

4.2.1 Peptide analysis by HPLC………………………………………………………………………………… 26

4.2.2 Initial Maillard reactions…………………………………………………………………………………. 26

4.2.3 Intermediate Maillard reactions and lipid oxidation………………………………………………….. 27

4.2.4 Late Maillard reactions……………………………………………………………………………………. 28

4.2.5 Protein composition………………………………………………………………………………………... 28

4.3 Analysis of physical changes…………………………………………………………………………. 29

4.3.1 Physical destabilization…………………………………………………………………………………… 29

4.3.2 Protein and fat content……………………………………………………………………………………. 31

4.3.3 Fat globule size distribution………………………………………………………………………………. 31

4.4 Data analysis………………………………………………………………………………………….. 32

5. Results…………………………………………………………………………………………... 33

5.1 Chemical changes…………………………………………………………………………………….. 33

5.1.1 Enzymatic hydrolysis………………………………………………………………………………………. 33

5.1.2 Initial Maillard reactions…………………………………………………………………………………. 34

5.1.3 Intermediate Maillard reactions and lipid oxidation………………………………………………….. 38

5.1.4 Late Maillard reactions…………………………………………………………………………………… 46

5.1.5 Protein composition………………………………………………………………………………………... 49

5.2 Physical changes……………………………………………………………………………………… 50

5.2.1 Physical destabilization…………………………………………………………………………………… 51

5.2.2 Protein and fat content…………………………………………………………………………………….. 53

5.2.3 Fat globule size distribution……………………………………………………………………………… 55

5.3 Principal component analysis…………………………………………………………………………. 56

6. Discussion………………………………………………………………………………………. 57

6.1 Chemical changes…………………………………………………………………………………….. 57

6.2 Physical changes……………………………………………………………………………………… 67

6.3 Comparison of accelerated parameters……………………………………………………………….. 70

7. Conclusion……………………………………………………………………………………… 71

8. Perspectives…………………………………………………………………………………….. 73

9. List of references………………………………………………………………………………. 74

10. Appendix……………………………………………………………………………………… 84

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1. Aim and hypothesis

Consumers demand high quality dairy products with good sensory attributes and commercial

sterility throughout shelf life. To guarantee these properties heat treatment is almost always applied

to dairy products today (Chavan et al., 2011; Lewis and Deeth, 2008). The main aim of heat

treatment is to inactivate undesired factors of the raw milk, such as pathogenic and spoilage

microorganisms and enzymes. On the other hand it is desired to preserve functional, nutritional and

organoleptic properties, by prevention of undesired heat induced chemical changes (Lewis and

Deeth, 2008; Singh and Waungana, 2001). In this perspective the choice of heat treatment is a

balance between preferences. Different heat treatments are applied to commercial milk products,

mainly high temperature short time (HTST) pasteurization (72 ºC, 15 sec), extended shelf-life

(ESL) (130-145, <1 sec) and ultra-high temperature (UHT) (135-150 ºC, 1-10 sec) (Walstra et al.,

2006). The market for milk treated at UHT is growing worldwide, today these products are found in

most countries, especially in Asia, Europe and South America (Bimbo et al., 2016; Jansson, 2014a).

In addition to prolonged shelf life, UHT processing is beneficial due to low energy costs and

elimination of cooling conditions during distribution and storage (Chavan et al., 2011). The

reported shelf life of UHT dairy products stored at ambient temperatures is between 6-9 months

(Bimbo et al., 2016; Richards et al., 2014). During processing and storage the UHT milk is

subjected to considerable chemical and physical changes, affecting the consumer acceptability and

hence the shelf life of the product. Possible undesirable effects include loss of nutrients, browning,

emulsion instability, age gelation and formation of off-flavours. Flavour changes are a major shelf

life limiting factor in UHT milk, mainly due to the Maillard reaction (MR), but possibly also lipid

oxidation or hydrolysis depending on the UHT treatment (Richards et al., 2014). The MR can be

affected by several factors including temperature, time, pH, water activity, type of sugar etc. (Oliver

et al., 2006). Physical destabilization is another major factor, which can result in creaming of fat

and/or sedimentation of protein (Calvo and de la Hoz, 1992; Chavan et al., 2011).

Food manufacturing today meets high expectations in the development of new products within short

time (Hough et al., 2006). The long shelf life of UHT dairy products result in very expensive and

time consuming shelf life tests in the development of new products. From this perspective

accelerated shelf life tests are highly valuable, with a significant reduction of time from product

development to market (Richards et al., 2014). An accelerated shelf life test can be performed by

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exposing the product to storage conditions with an accelerating effect on physical, chemical or

microbial changes. The accelerating factors depend on the specific product and the normal storage

conditions. Often changes in temperature, humidity or water activity are applied to accelerate shelf

life (Hough et al., 2006; Richards et al., 2014). Exposing the product to such a controlled

environment makes it possible to increase the deterioration rate and hence predict the shelf life

(Richards et al, 2014). Previous studies have attempted to accelerate the shelf life of milk, but

mainly with a focus on sensory attributes (Hough et al., 2006), proteolysis (Button et al., 2011) or

single components from the Maillard reaction (Richards et al., 2014). A valuable tool in the

development of UHT milk would therefore be a valid shelf life test accelerating both chemical and

physical changes, to give a more complete estimate of the predicted shelf life.

Hence the aim of this study is:

To give a quantification of physico-chemical changes depending on storage conditions, and

hereby to establish a valid setup to accelerate shelf life development.

The hypothesis of this study is that:

It is possible to establish a system for accelerated shelf life testing of UHT milk by

exposure to elevated storage temperatures including temperature cycles.

Such an accelerated shelf life test can be used in prediction of shelf life from

characterisation of chemical and physical changes.

A valid accelerated shelf life test for prediction of shelf life of UHT milk is possible.

To test these hypotheses, conventional skimmed and full fat indirect UHT milk were exposed to

five different storage temperatures and three temperature cycles, over a period of 24 weeks.

2. Outline of the thesis

This master thesis gives a presentation of the results obtained in relation to existing knowledge

within the field. To test the hypothesis two commercial UHT milk products were subjected to

different storage temperatures, in order to accelerate the shelf life development over a period of

24 weeks. The selected milk types were skimmed and full fat commercial UHT milk products, from

Arla Foods produced in Pronsfeld, Germany. The accelerating factors used were elevated storage

temperatures, temperature cycling and centrifugation with the use of Lumifuge. Storage

temperatures selected for the study were 10 °C, 20 °C, 30 °C, 40 °C and 50 °C, representing slightly

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cooled, ambient and elevated temperatures. Moreover, three temperature cycles were applied.

Samples in each cycle were switched between a high and a low storage temperature, with two

weeks intervals. Average storage temperatures were included in the study. A general overview of

the temperature cycles is depicted in Figure 1. Temperature cycle 1 was exposed to 10 °C and

30 °C, cycle 2 to 20 °C and 40 °C and cycle 3 to 30 °C and 50 °C.

For each storage condition 3-12 analysis points were chosen based on estimates of reaction rates.

Milk stored at 50 °C and cycle 3 were analysed over 8 weeks, whereas milk stored at 10 °C, 20 °C,

30 °C, 40 °C, cycle 1 and cycle 2 were analysed over 24 weeks. An overview of the milk types,

storage conditions and analyses used in the present study is given in Figure 2. The study elucidates

both chemical and physical changes, focusing on the Maillard reaction as well as physical

destabilization.

Figure 2 – Project overview of; milk types, storage temperatures, analysis methods and analysis information.

Figure 1- General overview of the variations in storage temperature (°C) over time (weeks) for the temperature cycles applied in this project (blue). Included is the corresponding average storage temperature (green).

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3. Introduction

3.1 Milk

Mammalian milk is a biological fluid secreted from the mammary glands. The main type of milk for

human consumption is bovine milk, but also milk from sheep, goat and buffalo are consumed

(Walstra et al., 2006). In the present thesis the term milk refers to bovine milk. It contains 87.1%

water, but nevertheless has a very high nutritional value (Walstra et al., 2006; Fox and Kelly, 2012).

With these properties milk is the primary natural source of nutrition for neonates and has become a

central part of the human diet, in form of several dairy products. From a molecular perspective milk

is a complex physico-chemical system (Nieuwenhuijse and Van Boekel, 2003). The continuous

phase of milk is not a true aqueous solution but rather a suspension of aggregates. This includes

colloidal proteins, emulsified lipids, globular proteins, as well as dissolved lactose, vitamins and

minerals (Walstra et al., 2006; Fox and Kelly, 2012). In addition milk contains bioactive peptides,

enzymes, oligosaccharides and immunoglobulins (Walstra et al., 2006; Jansson, 2014a). The

approximate composition of the main constituents in bovine milk are; 3.5% protein, 4.0% fat, 4.8%

lactose and 0.7% minerals, but the quantity varies with breed, genetic variations, lactation state,

feed composition, health, climate and season (Heck et al., 2009). In the following milk

carbohydrates, proteins and lipids will be reviewed.

3.1.1 Carbohydrates

The predominant carbohydrate of milk is lactose, which is a disaccharide composed of the

monosaccharides D-glucose and D-galactose linked by a β-1.4-glycosidic bond (Fox, 2009; Walstra

et al., 2006). Lactose is unique to milk and has been found in the milk of most mammalian species;

in addition to lactose milk contains trace amounts of glucose and galactose, but no polysaccharides

(Walstra et al., 2006). The concentration of lactose in bovine milk is found to be approximately

4.8%, with the highest content of lactose in the early stages of lactation. Lactose serves two main

functions in milk; it is an important energy source for the neonate and is responsible for about 50%

of the osmotic pressure between blood and milk (Fox, 2009; Jansson, 2014a). The monosaccharides

of lactose can exist in three different steric structures; two cyclic pyranose forms (α and β anomer)

and an open-chain form. The O-C1 bond of the cyclic glucose moiety can break and form the open-

chain form while creating an aldehyde group, as shown in Figure 3.

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Since it contains a free or potentially free carbonyl group (an aldehyde group), lactose is a reducing

carbohydrate (Fox, 2009; Walstra et al., 2006). The conversion of the two cyclic anomers is called a

mutarotation and occurs via the open-chain form. The least preferable and unstable form is the

acyclic open-chain form containing the reducing aldehyde group. In fresh milk less than 0.1% of

lactose is in this form, but at high temperatures and pH the open-chain form is favoured, leading to

an enhanced reactivity of the sugar (Brands et al., 2002; Walstra et al., 2006; Jansson, 2014a).

3.1.2 Proteins

The content of protein in bovine milk varies between 2.3-4.4%, mainly due to variations in breed

and genetics (Walstra et al., 2006; Farrell et al., 2004). Since 1830 it has been known that milk

contains two major protein groups; caseins and whey proteins. The caseins are representing 80% of

the total milk protein, and are hence the major protein component of bovine milk. The caseins are

divided into four individual types; αS1-casein (αS1-CN), αS2-casein (αS2-CN), β-casein (β-CN) and κ-

casein (κ-CN), distributed in the proportions; 40%, 10%, 35% and 15%, respectively (Dalgleish and

Corredig, 2012; Fox, 2003).

Caseins are hydrophobic and negatively charged proteins, containing many proline groups and few

cysteine groups. These characteristics lead to little secondary and tertiary structure of the casein

molecules and hence to a flexible structure of the primary chain (Dalgleish and Corredig, 2012).

This flexible and open structure makes the caseins very heat stable. The high surface

hydrophobicity of caseins, results in expanded association within and between caseins (Dalgleish,

2011; Walstra et al., 2006). Approximately 95% of the caseins are aggregated in clusters, held

together by hydrogen bonds, electrostatic interactions and hydrophobic interactions. These clusters

are called casein micelles, compromising approximately 94% protein. The remaining 6% are

referred to as colloidal calcium phosphate, mainly consisting of calcium and phosphate, but also

minor amounts of magnesium, citrate and other trace metals (Gaucheron, 2005; Dalgleish and

Figure 3 – Mutarotation of glucose, T = temperature (Jansson, 2014a).

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Corredig, 2012; Walstra et al., 2006). Caseins belong to the group of phosphoproteins, containing

phosphoric acid attached to hydroxyl groups of serine and threonine in the amino acid backbone.

These negatively charged phosphate groups are able to bind organic Ca2+

(Walstra et al., 2006). The

colloidal calcium phosphate is mainly associated to αS1-CN, αS2-CN and β-CN, which are

responsible for structure and partly the stability of the casein micelle (Gaucheron, 2005). The

structure of the casein micelle has been described by several models in literature, but none of these

are completely verified today. Two models mainly referred to are the nanocluster model by Holt

and Horne (1996) and the sub-micelle model presented by Farrell et al (2006) (Dalgleish, 2010;

Dalgleish and Corredig, 2012). The nanocluster model describes caseins as thread-like monomers,

with calcium phosphate nanoclusters mainly bound to the phosphoserines (Farrell Jr. et al., 2006),

whereas the sub-micelle model describes caseins collected in sub-micelles linked by calcium

phosphate (Dalgleish, 2010; Gaucheron, 2005). The casein composition of the micelles is

commonly known (Walstra et al., 2006). The core consists mainly of the hydrophobic and calcium

sensitive β-CN and the outer layer consists predominantly of the more hydrophilic and calcium

insensitive κ-CN, whereas α-CN is found throughout the structure (Walstra et al., 2006). The

surface layer of κ-CN provides steric and electrostatic repulsion and hence stabilises the casein

micelles from aggregation. Steric and electrostatic repulsion is due to the polar C-terminal of the κ-

CN forming a hairy layer, which is negatively charged (Dalgleish and Corredig, 2012). Casein

micelles vary in size with an average diameter of 150-200 nm and the size is highly determined by

the amount of κ-CN available to cover the micelle surface (Dalgleish and Corredig, 2012; Fox and

Kelly, 2012). In contrast to the whey proteins, the caseins are insoluble at pH 4.6, this property

makes it possible to precipitate caseins and enables the production of dairy products like fermented

milk products, caseinates and acid-catalysed cheeses (Fox 2003; Fox and Kelly, 2012).

The whey protein fraction represents the remaining 20% of the total protein content of bovine milk.

These proteins have a high degree of secondary and tertiary structures, making them less heat stable

compared to the caseins. The globular structures are maintained by disulfide bonds, hydrophobic

interactions, Van der Waal´s interactions, hydrogen bonds and ion-pair interactions (Singh and

Havea, 2003; Wijayanti et al., 2014; Walstra et al., 2006). The whey proteins comprise four main

proteins; β-lactoglobulin (β-Lg) (40%), α-lactalbumin (α-La) (20%), immunoglobulins (10%) and

blood serum albumin (10%). The remaining 10% consists of enzymes and proteins in the membrane

of milk fat globules (Farrell et al., 2004; Fox and Kelly, 2012). The native composition of whey

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proteins is characterized by a high amount of cysteine groups and many hydrophilic residues on the

surface. This makes the whey proteins highly soluble in milk, even over a broad range of pH values

(Dissanayake and Vasiljevic, 2009). β-Lg contains 162 amino acids including five cysteine

residues, four of these form disulfide bridges and one is a free residue (Cys121). In the native form

of β-Lg the free thiol group is located in a hydrophobic pocket and is hence not prone to interaction

with other proteins (Kontopidis et al., 2004).

3.1.2.1 Analysis of protein composition by HPLC

The protein composition in milk can be analysed in several ways. Common applied techniques are:

Liquid chromatography (LC), electrophoretic techniques, isoelectric focusing and mass

spectrometry (Bonfatti et al., 2008). In particular, high performance liquid chromatography (HPLC)

provides a rapid and accurate analysis of peptides and proteins from a variety of synthetic or

biological sources with a high resolution (Aguilar, 2004). Proteins can be separated based on

characteristics like hydrophobicity, solubility, charge, size and affinity to specific chemical groups

(Berg et al., 2006). Reversed-phase high-performance liquid chromatography (RP-HPLC) separates

components on the basis of hydrophobicity (Aguilar, 2004). This technique applies a non-polar

stationary phase and a more polar mobile phase. The stationary phase is often a silica-based

membrane with hydrophobic ligands attached, mainly C4-, C8- or C18-alkyl groups. A long carbon

chain results in a high hydrophobicity. The separation of molecules hence depends on their affinity

of binding to the hydrophobic carbon chain attached to the stationary phase (Aguilar, 2004; Berg et

al., 2006). The composition of the mobile phase can either be constant (isocratic condition) or vary

(gradient condition) through the elution. When a gradient elution is applied, the amount of polar

organic solution (e.g. acetonitrile) is often increased in concentration over time. This leads to a

gradual detachment of the hydrophobic peptides and proteins from the stationary phase, followed

by elution and detection. Hence the fastest eluting proteins contain the highest amount of polar

residues (Berg et al., 2006; Bordin et al., 2001). Main factors influencing the elution are pore size of

the stationary phase and length of the carbon chains attached (Wang et al., 2009). Increases in

column temperature usually decrease viscosity of the solution resulting in a faster flow and hence

decreased retention times (Aguilar, 2004). Detection of separated compounds is often with use of a

UV-detector, where peptide bonds are detected at a wavelength of 214 nm and aromatic residues

are 280 nm (Bonfatti et al., 2008). On the resulting chromatogram, peak areas reflect the intensity

of peptide bonds (at 214 nm) detected at a given retention time (Berg et al., 2006).

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3.1.3 Lipids

The lipid fraction of bovine milk is mainly composed of apolar triacylglycerides (TAG) comprising

approximately 98%. In addition 1% is polar phospholipids and the remaining includes

monoglycerides, diglycerides, cholesterol and cholesterol esters (Fox and Kelly, 2012; Walstra et

al., 2006). Nearly all milk fat is concentrated in milk fat globules (MFG), with an average diameter

of 4.5 µm in raw milk, but varying from 0.1-20 µm. The globules are surrounded by an emulsifying

membrane, referred to as the milk fat globule membrane (MFGM) (Walstra et al., 2006). Milk is

therefore an emulsion of fat globules dispersed in the aqueous phase as an oil-in-water emulsion

(Walstra et al., 2006). The TAG´s are found in the hydrophobic core of the MFG, while polar lipids

and membrane-specific proteins are a part of the outer MFGM, serving as emulsifiers. The polar

lipids contained in the MFGM are mainly phospholipids and sphingolipids (Dewettinck et al.,

2008). These membrane-specific proteins and lipids stabilize the emulsion with their amphipathic

structure, containing both a hydrophobic and a hydrophilic part. Other important factors affecting

the stability of emulsions are density differences between the continuous and the dispersed phase as

well as size of the dispersed particles (Fox and Kelly, 2012). In addition to emulsifying properties,

the MFGM provides protection against enzymatic degradation (Dewettinck et al., 2008). The

TAG´s are composed of three fatty acids attached to a glycerol base. The compositional range is

wide and the properties of the milk fat are highly determined by the fatty acid composition (Walstra

et al., 2006). The fatty acids can either be saturated, primarily straight hydrocarbon chains, or

unsaturated containing 1-4 double bonds. In bovine milk approximately 65% of the fatty acids are

saturated and 35% are unsaturated (Samková et al., 2012). If the MFGM is disrupted, unsaturated

fatty acids will be highly prone to thermal and enzymatic degradation (Dewettinck et al., 2008;

Hawke, 1966). The chemical oxidation of lipids is of major focus, since this can be contributing to

nutritional losses, off-flavour and odor in dairy products (Nursten, 2005; Zamora and Hidalgo,

2005). Lipid oxidation will be further reviewed in section 3.5.2.

3.2 UHT milk

Thermal processing is an essential step in the manufacture of all dairy products. The main aim of

such treatment is to limit bacterial load, enzyme activity and increase the keeping quality of the

product (Walstra et al., 2006). The effect and efficiency of the heat treatment is dependent on the

pre-treatment conditions, heating method applied and time-temperature range. Production of heat

treated milk products can vary a lot, covering the spectrum from pasteurization to in-container

sterilization (Sakkas et al., 2014).

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The manufacturing of UHT treated milk includes a thermal processing of 135-150 ºC for 1-10 sec

followed by aseptic packaging (Lewis and Deeth, 2008). This heat treatment results in a

commercially sterile product, which is shelf stable for 6-9 months at room temperature (Bimbo et

al., 2016). Disadvantages related to heat treatment of UHT products are that the nutritional and

organoleptic quality decreases, due to thermal degradation and oxidation of lipids, denaturation of

proteins and reactions between proteins and sugars in the MR (Nursten, 2005). In this perspective

the time and temperature combination should be carefully optimized, depending on the desired

approach with least undesirable chemical changes (Sakkas et al., 2014). For determination of this

optimal time-temperature region for processing of UHT milk, biological and chemical indices have

been developed. A commercially sterile UHT product

has a biological effect of B* >1 and a chemical effect of

C* < 1, as demonstrated in Figure 4. If this area is

reached thermophilic bacterial spores will be reduced

with a 9 decimal and a chemical effect equal to boiling

the product for 1 min, in milk this is correlated with a

3% reduction of thiamine (Lewis and Deeth, 2008;

Kessler, 2002). As shown in Figure 4, the inactivation of

microorganisms is mainly dependent on the heat load

applied, whereas the chemical changes are mainly

dependent on holding time, on this basis it can be

favorable to increase the temperature and decrease the

holding time of a heat treatment (Kessler, 2002).

The processing of UHT milk can be either direct or indirect. In the direct heating system milk is

mixed directly with superheated steam under pressure. After a short holding time the water is

removed from the milk again with the use of vacuum cooling (Kessler, 2002). The indirect heating

system transfers heat to the milk with the use of a medium separating the milk and a heating fluid

mainly steam or hot water. The temperature difference between the milk and hot water facilitates

the heat transfer. Indirect heating can be achieved with the use of a tubular heat exchanger or a plate

heat exchanger, the latter is mainly used (Lewis and Deeth, 2008; Kessler, 2002). The choice of

processing system affects the time-temperature profile of the treatment, as shown in Figure 5.

Figure 4 – Biological (B*) and chemical (C*) effect of the UHT processing area (Kessler, 2002).

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The direct heating system results in high heating and cooling rates compared to the indirect heating

system, which gives a continuous heating and cooling within a longer time period. Minimal

chemical changes are applied to the direct compared to the indirect UHT milk due to the very fast

heating and cooling. This is reflected in lower levels of heat markers in direct UHT milk (Perkins

and Elliott 2005; Datta et al., 2002). Another effect of the reduced heat load of direct UHT milk is

often a higher enzyme activity leading to a higher degree of hydrolysis and age gelation (Lewis and

Deeth, 2008; Datta et al., 2002).

Homogenisation is always applied in combination with UHT treatment. In indirect heating systems

the homogenisation procedure can be applied before or after the heat treatment, while it is always

applied after in the direct heating systems, to avoid protein-protein and fat globule-protein

aggregation (Kessler, 2002). Homogenisation of UHT milk has a significant effect on the storage

stability. The technique delays fat separation by disrupting the MFG´s, resulting in a smaller droplet

size and hence an increased total MFG surface. Milk proteins, mainly caseins and β-LG, are

adsorbed on the MFGM. This incorporation of proteins prevents agglomeration by steric and

electrostatic repulsion (Raikos, 2010). Moreover, the incorporation increases the density of MFG´s,

which contributes to a delay of the creaming rate (Lu et al., 2013).

Figure 5 – Heating profiles of A) direct and B) indirect UHT treatment (Rauh, 2014a).

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3.3 Changes induced by UHT treatment

It is commonly known that commercial UHT treatment of milk induces a number of physico-

chemical changes (Singh and Waungana, 2001). Milk behaves as a complex reaction system when

exposed to heat, resulting in reversible as well as irreversible changes (Datta et al., 2001). Milk heat

treated at UHT is exposed to temperatures between 135-150 ºC, hence leading to several

irreversible changes. A great part of these heat-induced reactions involve lactose. One of them is the

degradation of lactose into galactose and degradation products of glucose, which often includes

organic acids, referred to as sugar fragmentation (Walstra et al., 2006). In addition lactose may

isomerize into other sugars, leading to the formation of lactulose or epilactose, where the glucose

moiety is converted to fructose or mannose respectively (Singh and Waungana, 2001; Fox and

Kelly, 2012). Lactulose is often used as an indicator of the severity of heat treatments, since it is not

affected before or after the UHT treatment (Chavan et al., 2011). Reducing sugars are also likely to

react with amino groups in the MR when heated, leading to browning, off-flavour formation as well

as a reduced nutritional value (Nursten, 2005; Fox and Kelly, 2012). The MR will be discussed in

detail in section 3.5.1.

At high temperatures milk proteins can be subject to structural changes including denaturation,

unfolding, rearrangement of disulfide bonds, aggregation and lactosylation (Datta et al., 2002).

Caseins are very heat stable since the random coiling of their primary chain is hard to destroy

compared to secondary and tertiary structures (Fox, 2003). Dephosphorylation and hydrolysis of

caseins have been documented to occur in milk during UHT treatment, but only to a limited degree

(Nieuwenhuijse and Van Boekel, 2003). Upon heat treatment soluble calcium and phosphate is

converted into the colloidal stage, and colloidal calcium phosphate is increasingly associated with

the casein micelles. Moreover, κ-CN is partially dissociated leading to a reduced size of the casein

micelles (Dalgleish and Corredig, 2012; Singh and Waungana, 2001). On this basis, casein micelles

are not the major factor contributing to heat-induced instability of proteins in milk. Whey proteins,

on the other hand, are highly temperature dependent due to their globular structure. Above 60 °C

significant denaturation of whey proteins occur (Singh and Waungana, 2001). The denaturation is

either reversible corresponding to a partial unfolding, or irreversible corresponding to aggregations

with other proteins mainly through sulfhydryl (-SH)/disulfide (S-S) interactions (Wijayanti et al.,

2014). The whey proteins have different sensitivity to heat treatment, the order has been

documented to be immunoglobulins > bovine serum albumin > β-Lg > α-La (Singh and Waungana,

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2001). The denaturation of β-Lg includes an unfolding of the globular structure exposing

hydrophobic residues and the free thiol group of Cys121 (Nieuwenhuijse and Van Boekel, 2003). In

addition heating leads to denaturation of cysteine disulfide bonds and an increased reactivity of

thiol groups (Datta et al., 2001). At neutral pH the sulphydryl groups of cysteine are ionized and

hence highly reactive. These groups can react intermolecular with other sulphydryl containing

molecules, often κ-caseins on the micelle surface, proteins in the MFGM or other β-Lg (Singh and

Waungana, 2001; Walstra et al., 2006). Such interactions between β-lactoglobulin and κ-caseins

lead to the formation of the so called β-lactoglobulin-κ-casein-complex (βκ-complex). The pH of

milk at heat treatment influences the extent of whey protein association to the casein micelle. At pH

between 6.5-6.7 the βκ-complex remains attached to the casein micelle, whereas at pH above 6.9

the complex dissociates from the micelle (Oldfield et al., 2000). Cross-linking within or between

peptide chains prevent refolding to the native structure, therefore these proteins remain denatured

(Walstra et al., 2006). Generally this leads to changes in the biological properties and may lead to

insoluble precipitates. Such cross-linking of peptide chains may continue during storage,

consequently these changes have been of interest to the dairy industry for many years (Datta et al.,

2002).

Several of the above mentioned processes will possibly decrease the pH of milk (Walstra et al.,

2006). Lactose undergoes reactions with formation of organic acids, to mention is the MR and

direct degradation of lactose with formation of galactose and degradation products, including

various organic acids (Walstra et al., 2006). Casein micelles can undergo dephosphorylation and

hydrolysis at severe heat treatment (Al-Saadi and Deeth, 2008). In addition, colloidal calcium

phosphate equilibrium can be affected leading to association of dissolved calcium and phosphate to

the casein micelle with release of protons. The reaction proceeds (Walstra et al., 2006):

𝐶𝑎2+ + 𝐻2𝑃𝑂4− → 𝐶𝑎𝐻𝑃𝑂4 + 𝐻+ (1)

This reaction is considered reversible at heat treatments below 100 °C (Gaucheron et al., 2011;

Dalgleish and Corredig, 2012).

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3.4 Enzymatic hydrolysis

Former research has shown that bitter off-flavour and physical instability of UHT milk can be

initiated by hydrolysis, due to milk indigenous enzymes and/or exogenous enzymes (Chavan et al.,

2011; Kilara and Panyam, 2003). Exogenous enzymes in UHT milk are formed by psychrotrophic

bacteria, which are capable of growing in the raw milk at temperatures ≤7 ºC. These

microorganisms produce heat stable extracellular enzymes, mainly proteases and lipases, which

continue to degrade milk constituents even after most UHT treatments (Nielsen, 2002). UHT milk

produced from raw milk with a high microbial count will hence be more susceptible to enzymatic

hydrolysis compared to milk with a low microbial count (Chavan et al., 2011). These proteases

differ in specificity, resulting in many different cleavage sites (Nielsen, 2002). They attack all

casein types and are able to hydrolyse hydrophobic domains, which are associated to the bitter

flavour formation (Lemieux and Simard, 1992). The heat stability of proteinases produced by

psychrotrophic bacteria has been found to be higher than the heat stability for indigenous enzymes

(Nieuwenhuijse and Van Boekel, 2003). Raw milk contains two indigenous proteinase systems; the

plasmin and the cathepsin system. The plasmin system is the major native proteinase system in

milk, with a sufficiently high heat stability to survive most UHT processes (Nieuwenhuijse and Van

Boekel, 2003). Plasmin is a serine proteinase mainly present as the inactive plasminogen, regulated

by activators and inhibitors. Plasmin, plasminogen and plasminogen activators are commonly

considered heat stable and the inhibitors heat labile (Ismail and Nielsen, 2010). Plasmin is mainly

present in the casein micelle and the MFGM (Nielsen, 2002). Flavour and colour of UHT milk can

indirectly be affected by enzymatic proteolysis, since an increased number of free amino terminals

will be available for the MR, leading to Strecker degradation products and melanoidins (Rauh,

2014a). Correlations between enzymatic proteolysis and bitter taste were first observed by Murray

and Baker in 1952 (Kilara and Panyam, 2003). Formation of bitter taste from peptides depends

highly on the amino acid composition and the properties of these amino acids. Hydrophobic

properties have been correlated with bitter taste intensity, but also aromatic properties, ammonium

groups and configuration of the α-carbon (Lemieux and Simard, 1992; Gomez et al., 1997). Bitter

peptides originate mainly from αS1-CN and β-CN, since these proteins have a high average

hydrophobicity (Kilara and Panyam, 2003). The most bitter amino acids include phenylalanine and

tryptophan, both with aromatic side chains (Lemieux and Simard, 1992), and the hydrophobic

amino acids; proline, leucine, isoleucine, methionine and valine (Jansson, 2014a). Hydrolysis of

lipids results in formation of short-chain fatty acids, which have a strong aroma and often rancid

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flavour (Singh et al., 2009). Hydrolytic activity is more pronounced in direct treated UHT milk

compared to indirect treated UHT milk, due to the lower heat load achieved by fast heating and

cooling rates (McKellar et al., 1984). This thesis evaluates indirect treated UHT milk hence enzyme

activity is expected to be minimal and insignificant to the results. The degree of hydrolysis will be

evaluated with peptide analysis.

3.5 Chemical changes in UHT milk during storage

Several chemical reactions affect the quality of UHT milk during storage, resulting in changes in

flavour, aroma, colour and/or viscosity. Colour changes in food systems can in general be a result of

two main mechanisms; enzymatic and non-enzymatic browning reactions. Division of these two

reaction mechanisms can in some cases be difficult, but in heat treated food only non-enzymatic

browning occur. The non-enzymatic browning can either be due to caramelisation or the MR

(Nursten, 2005; Van Boekel, 2006). Caramelisation of sugar leads to some of the same products as

the MR, but caramelisation proceeds at higher temperatures and at a slower rate. In the MR, amino

acids play an important role in the catalysis of the reaction resulting in higher amounts of reactive

intermediate products (Van Boekel, 2006; Nursten, 2005; Walstra et al., 2006). Flavour and odor

changes in UHT milk can again be due to the MR, but also hydrolysis and oxidation of proteins and

lipids can result in these changes (Nursten, 2005).

The effect of storage temperature on the rate of chemical reactions is commonly evaluated using the

Arrhenius equation. This equation describes the correlation between the velocity constant and the

absolute temperature (Martins et al., 2001; Kessler, 2002):

𝑘 = 𝐴 ∗ 𝑒−𝐸𝑎𝑅𝑇 (2)

Where k is the velocity constant, Ea is the activation energy (J/mol), R the universal gas constant

(8.314 J/mol K), T the absolute temperature (K) and A is the pre-exponential factor (Kessler, 2002).

This relation can be depicted in a so called Arrhenius plot with use of the natural logarithm. From

the slope of this plot it is possible to calculate the activation energy of a reaction. Another way to

express the correlation between the rate of chemical reactions and the absolute temperature is

referred to as Q10. This value denotes the increase in reaction rate when the temperature is raised

10 °C (Walstra et al., 2006), defined by:

𝑄10 =𝑘(𝑇+10)

𝑘(𝑇) (3)

Where k is the rate constant and T is the absolute temperature.

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3.5.1 Maillard reaction

The MR is a complex cascade of reactions between a reducing sugar and an amino group, first

observed by the French chemist Louis-Camille Maillard in 1912. This reaction proceeds mainly

during processing at elevated temperatures or during long time of storage (Nursten, 2005). A wide

range of reaction products are formed, but the products are not yet fully characterized (Jansson et

al., 2014b). The MR is highly relevant since it is a major challenge in food chemistry due to the

formation of compounds that are related to heat-induced changes in aroma, flavour and colour

(Martins et al., 2001). The resulting changes can be desirable or undesirable depending on the

product. In UHT milk consumer acceptance and shelf life is decreased with these changes. In

addition, the MR can have an effect on digestibility, nutritive value and can produce components

with harmful (mutagenic, allergenic) as well as favorable (antioxidative, antimicrobial) properties

(Van Boekel, 2006; Siciliano et al., 2013). The loss of nutritive value of milk is mainly due to

lactosylation of proteins, which result in less available lysine for metabolic processes. The

lactosylation decreases digestibility of the protein by diminished access of proteases, such as trypsin

and carboxypeptidase (Metha and Deeth, 2016; Van Boekel, 1998). The protein lactosylation can

also have an effect on functionality properties, such as solubility and thermal stability (Wang and

Ismail, 2012). In 1953 Hodge subdivided the MR into three stages; an initial, intermediate and late

stage. This three-part classification is still accepted today and will be described in the following

(Nursten, 2005).

Initial Maillard reactions

The indigenous reducing sugar in milk is lactose, which contains a carbonyl compound in the open-

chain conformation. The reducing sugar reacts with an amine, in milk mainly the ε-amino group of

lysine residues on casein micelles (Nursten, 2005). In milk the amount of free amino acids is

relatively low and most α-amino groups are tied up in peptide bonds. Hence mainly the N-terminal

α-amino group and nitrogen or sulfur containing side-chains of amino acids on proteins are

available for the Maillard reaction (Van Boekel, 2006). In addition to the ε-amino group of lysine

other amino acid side chains can react in the MR. To mention is the indolyl-group of tryptophan

and the guanidino-group of arginine, but these are not as reactive as lysine (Hedegaard and

Skibsted, 2010; O´Brien, 2009). Lysine residues in the caseins are found to be more reactive than

those of serum proteins, while the most reactive casein is the κ-casein (Van Boekel, 1998). In

general, the type of flavour compounds formed in the MR depends on the nature of the reactants,

such as type of sugar and amino acid, while the kinetics of the reactions are influenced by

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parameters such as temperature, time and pH (Van Boekel, 2006). The reaction rate increases with

high pH, temperature and duration of the thermal process. Under these conditions the reactivity

between protein and sugar are increased, since the unprotonated form of the amino group and the

open-chain form of the sugar are favored (Martins et al., 2001; Jansson, 2014a).

The initial stages of the Maillard reaction consists of a sugar-amine condensation and an Amadori

rearrangement as depicted in Figure 6. The first reaction is a nucleophilic attack of the nitrogen

atom in the amino group on the electrophilic carbon of the carbonyl group in a reducing sugar. This

reaction is followed by a condensation reaction forming an unstable Shiff base, which is rapidly

rearranged to the Amadori product, in milk ε-lactulosyllysine. The carboxyl group of the amino acid

is an important factor in the catalysis of the Amadori rearrangement (O´Brien, 2009; Van Boekel,

1998).

Figure 6 – The reaction between lactose and a lysine residue with formation of the Amadori product ε-lactulosyllysine. Gal=Galactose, Prot=Protein (Siciliano et al, 2013).

The Amadori product can be quantified directly by LC-MS following complete enzymatic

hydrolysis of the lactosylated proteins, but this approach is difficult and time consuming (Henle et

al., 1991). In addition indirect methods for evaluation of the early stage of the MR have been

applied in previous studies. A common method is quantification of the artificial amino acid furosine

in acid hydrolysed milk, as shown in Figure 7 (Metha and Deeth, 2016). Furosine is not found

naturally in milk and has hence shown to provide a good estimation of the extent of the early stage

of the MR (Serrano et al., 2002; Guerra-Hernandez et al., 2002). It is not possible to get a direct

measure of the protein lactosylation based on a quantification of furosine, since the conversion of

furosine from Amadori product is incomplete (Delgado et al., 1992), approximately 30-40 % of the

Amadori product is converted into furosine (Van Boekel, 1998).

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Intermediate Maillard reactions

In the intermediate stage of the MR, the Amadori product is degraded into several fission products

as shown in Figure 8. The Amadori product is in equilibrium with 1,2-eneaminol and 2,3-

eneaminol, which take part in the formation of various reactive carbonyl compounds (Van Boekel,

1998; Nursten, 2005). The breakdown pathway of the Amadori product is highly dependent on the

pH in the system. At acidic pH the main breakdown route is the 1,2-enolisation pathway by

formation of the reactive intermediate 3-deoxyosone. This pathway can lead to the formation of

furfural (when pentose sugars are involved) and hydroxymethylfurfural (HMF) (when hexose

sugars are involved) (Martins et al., 2001; O´Brien, 2009). At neutral or alkaline conditions the

Amadori product is mainly degraded via the 2,3-enolisation pathway with formation of 1-

deoxyosone and 4-deoxyosone respectively. The pH of fresh UHT milk is about 6.6, hence the 2,3-

enolisation pathway is favored (Nursten, 2005; Martins et al., 2001). The deoxyosones are degraded

to reductones (e.g. formic acid and acetic acid) and a variety of fission products such as

pyruvaldehyde, diacetyl, acetol and galactose.

Figure 8 – Advanced maillard reaction: The two major pathways for breakdown of the Amadori product (Nursten, 2005).

Figure 7 - Furosine formation by acid hydrolysis (Metha and Deeth, 2016).

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These highly reactive fission products are also referred to as advanced glycation end products

(AGE) (Van Boekel, 1998; Nursten, 2005; Martins et al.., 2001). Most AGE products contain

aromatic residues and conjugated double bonds, which makes them able to absorb and emit light

(Van Boekel, 1998; Lakowicz, 1999). Several studies have previously utilized these fluorescence

properties for evaluation of intermediate and late Maillard reaction products (MRP) (Matiacevich

and Buera, 2006; Birlouez-Aragon et al., 1998). The deoxyosones and fission products containing

carbonyl groups can react with α-amino acids in the so called Strecker degradation. The Strecker

degradation compounds are formed via a decarboxylating transamination, with a release of water

and CO2 and a transfer of ammonia to other compounds in the system. This reaction results in

formation of Strecker aldehydes and α-dicarbonyls (Figure 9) (Nursten, 2005). Strecker aldehydes

previously found in UHT milk are among others 2-methylbutanal and benzaldehyde (Jansson et al.,

2014b). The contributing amino acid will affect the type of Strecker aldehydes and secondary

reaction products formed. Strecker degradation compounds have shown to influence aroma and

flavour formation of milk, but can also take part in further reactions (Van Boekel, 2006; Jansson et

al., 2014b; Nursten, 2005).

Figure 9 – Formation of Strecker degradation products (Jansson, 2014a).

Late Maillard reactions

In the final stage of the MR, brown-colored polymers are formed, known as melanoidins. These

high-molecular weight compounds are formed by all kinds of fragmentation, dehydration,

cyclization and polymerization reactions from reactive compounds formed in the intermediate stage

(Metha and Deeth, 2016; Van Boekel, 2006; Van Boekel, 1998). The reactants are often Strecker

degradation products, fission products or dehydroreductones, as shown in Figure 10 (Martins et al.,

2001; Nursten, 2005). The Strecker degradation products can take part in formation of melanoidins

in two ways. The first way is an aldol condensation of the Strecker aldehydes resulting in nitrogen-

free polymers and the second way is a reaction with amino compounds via aldimines (Nursten,

2005). The final stage of the MR is not well characterized from a chemical point of view. Chemical

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structures of melanoidins are complex and until now only limited parts of melanoidin structures

have been clarified (Martins et al., 2001).

Figure 10 – Overview of volatile compounds identified in this study. Products in green are identified with SPME-GC-MS, in blue with HPLC and orange with analysis of fluorescence and colour changes.

3.5.2 Lipid oxidation

In addition to the MR, oxidation of lipids is also important, contributing to nutritional losses and

off-flavour formation in UHT milk during storage (Nursten, 2005; Zamora and Hidalgo, 2005). The

oxidation products can have an effect on the dairy product, but they can also interact with non-lipid

components and be a part of the MR (O´Brien, 2009; Zamora and Hidalgo, 2005). Formation of

oxidized flavour has in former studies been found to originate from an imbalance of pro-oxidants

and antioxidants (Gutierrez, 2015). Lipids are susceptible to oxidation in the presence of catalysts

or initiators such as heat (Vazquez-Landaverde et al., 2005), light, transition metals (Gutierrez,

2015), enzymes and microorganisms (Shahidi and Zhong, 2010; Jansson, 2014a). Oxidation of

lipids can hence be accelerated at higher temperatures (Shahidi and Zhong, 2010). Unsaturated fatty

acids are the major reactants in lipid oxidation, since it is the double bonds that are prone to

oxidation. Lipid oxidation reactions can occur by complex processes such as autoxidation, photo-

oxidation, thermal or enzymatic oxidation, of which autoxidation is the most common (Shahidi and

Zhong, 2010). Autoxidation is a spontaneous free radical chain mechanism, separated in three

stages; initiation, propagation and termination (Shahidi and Zhong, 2010). In the first part of the

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reaction a hydrogen atom is abstracted from the lipid in the presence of one of the initiators

resulting in a free radical. The radical reacts with oxygen generating primary oxidation products

such as lipid hydroperoxides, which are unstable and will easily attack new lipid molecules leading

to an auto-catalytic propagation process (Shahidi and Zhong, 2010; Jansson, 2014a). This

intermediate stage is repeated until no hydrogen atom is present for reaction or by reaction with an

antioxidant. Antioxidants are able to delay or prevent oxidation by hydrogen or electron transfer

through various pathways (Laguerre et al., 2007). The unstable lipid hydroperoxides can degrade to

a variety of secondary oxidation products including aldehydes, ketones, hydrocarbons, alcohols and

organic acids (Marsili, 1999; Shahidi and Zhong, 2010). Secondary oxidation products are

important contributors to the off-flavour formation, due to very low sensory threshold values

(Gutierrez, 2015). Both the MR and lipid oxidation are very complex cascades of reactions, and are

in addition found to be interrelated (Zamora and Hidalgo, 2005). The two reaction cascades have

common intermediates and can both result in polymerization reactions. Carbonyl-containing

secondary oxidation products are able to react with amino-containing molecules and be important

participants in the MR (O´Brien, 2009; Zamora and Hidalgo, 2005). Thus, oxidation reactions of

lipids are dynamic and often overlapping or correlating with other reactions, hence making accurate

kinetic studies of lipid oxidation or MR very complicated (O´Brien, 2009; Shahidi and Zhong,

2010; Zamora and Hidalgo, 2005).

Volatile products from lipid oxidation and intermediate MRs will in this study be relatively

quantified by solid phase micro extraction-gas chromatography-mass spectroscopy (SPME-GC-

MS). Characterization of volatiles with the use of GC-MS has been applied in many food systems,

including in UHT milk (Vazquez-Landaverde et al., 2006; Valero et al., 2001; Contarini et al.,

1997). Analysis of volatile compounds using SPME-GC-MS includes extraction, separation and

identification, as depicted in Figure 11. SPME is a solvent-free extraction of volatile compounds

using a flow of carrier gas (e.g. helium). This extraction technique uses a fiber coated with a highly

absorbant polymeric film. During extraction two equilibriums are reached; first an equilibrium

between the sample and the head space and secondly an equilibrium between head space and the

contact fibre (Barrious et al., 2013). For optimization of the extraction factors such as sample

volume, temperature, flow and time are important to consider, since they can have a major effect on

the amount of volatile components adsorbed by the SPME fibre (Vazquez- Landaverde et al., 2005;

Jansson, 2014a). The inert gas collects and transports the volatiles to the GC-MS system (Jansson,

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2014a). In the column, compounds are separated according to volatility (Johns et al., 2005). The

separated compounds are hereafter identified, often with use of a mass spectrometry detector

(Jansson, 2014a).

3.6 Physical changes in UHT milk during storage

Milk is a dispersion containing colloidal particles in a wide range of sizes; from 10 nm to 100 µm

(Walstra et al., 2006). These colloids are mainly fat globules and casein micelles. Fat globules are

lyophobic colloids, which in principle are unstable in liquid solvents. These contain a true phase

where surfactants are able to adsorb and improve stability. Casein micelles are on the other hand

lyophilic colloids, which in principle are stable due to high attractive forces to the solvent

(Rousseau, 2002; Walstra et al., 2006). Lyophobic and lyophilic colloids are subject to different

instabilities in milk during storage. Undesired physical changes associated with UHT milk during

storage includes; creaming of fat, sedimentation of protein and in some cases age gelation (Chavan

et al., 2011; Datta and Deeth, 2001). This part of the study will focus on destabilizations resulting in

creaming of fat and sedimentation of protein. Stability of an emulsion depends highly on the ability

to resist changes in colloidal properties over a time period. Two different stabilities are

distinguished in this context; thermodynamic stability and kinetic stability. The thermodynamic

stability determines if a process will occur, and the kinetic stability determines the rate at which the

process will occur (Huppertz and Kelly, 2006). Milk as an emulsion is a thermodynamic unstable

system and will be subject to various physical instabilities. These instabilities include fat droplet

aggregation and gravitational separation leading to more or less inhomogeneous products with

altered properties (Walstra et al., 2006; Huppertz and Kelly, 2006). In food emulsions these

instabilities will all take place to some extent and will be able to influence each other (Walstra et

Figure 11 – The SPME-GC-MS method; including SPME headspace sampling, gas chromatograph and mass spectrometer. Modified from Jansson (2014a) and Sigmaaldrich.com (2016).

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al., 2006). Droplet aggregation is a result of colloidal interactions, leading to contact between

droplets for longer time than random collision by Brownian motion. Physical instabilities due to

droplet aggregation can be in the form of flocculation and coalescence, as shown in Figure 12

(Rousseau, 2002). Flocculation is the aggregation of particles due to weak attractive forces. These

interactions are often described by the Deyaguin-Landau-Verwey-Overbeek (DLVO) theory,

considering the balance between attractive forces by Van der Walls and electrostatic repulsions as a

function of interparticle distance (Rousseau, 2002). During flocculation droplets remain as

individual entities opposite to coalescence. Coalescence is the process where two fat globules

merge by rupture of a thin film consisting of the continuous phase. This interaction is often

irreversible, whereas flocculation is a reversible interaction (Huppertz and Kelly, 2006).

Gravitational separation of emulsions occurs due to density differences between the two phases

influenced by gravity. The process of fat globules moving upward in milk is referred to as

creaming, mainly due to the low density of fat globules compared to milk plasma (Rousseau, 2002).

The velocity of creaming is not affected by colloidal interactions like flocculation and coalescence,

but by gravitational forces, density differences, globule size and the continuous phase viscosity. For

spherical particles the velocity can be obtained by Stockes equation (4) (McClements, 2007;

Huppertz and Kelly, 2006; Walstra et al., 2006).

𝑉 =𝑎∗(𝜌𝑐−𝜌𝑝)∗𝑑2

18∗𝜂𝑐 (4)

Where V is the particle migration velocity (m* s-1

), 𝜌c is the continuous phase density (kg*m-3

), 𝜌p

is the particle density (kg*m-3

), a is the acceleration due to gravitational or centrifugal force and 𝜂c

is the viscosity (m*s-1

) of the continuous phase.

Figure 12 – Instabilities commonly seen in food emulsions: Creaming, sedimentation, flocculation and coalescence, modified from McClements (2007).

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To calculate creaming velocity correctly, requirements must be met. Of particular importance is

that; the globules must be homogeneous spherical particles, other particles present must be smaller

than the globules and Brownian motion must be smaller than the rate of the globules (Huppertz and

Kelly, 2006; Walstra et al., 2006). But the equation has previously shown to predict useful trends

even under conditions that do not meet the requirements (Walstra et al., 2006). Creaming is

enhanced by flocculation or coalescence of the fat globules, since these larger clusters or globules

rise faster than individual fat globules (Rousseau, 2002). The density of milk fat has shown to be

influenced by the proportions of liquid and solid fat, liquid fat with a lower density than solid fat

(Bandari and Singh, 2011). The solubility of fat is affected by temperature and the TAG´s present.

Milk contains over 400 different TAG´s hence their melting point range is wide, going from -40 °C

to 40 °C (Wright and Marangoni, 2006). In addition, the continuous phase viscosity of milk will be

influenced by temperature changes (Rousseau, 2002). Xu et al. (1998) studied the effect of

increased storage temperature on oil-in-water emulsions. In this study a rise in temperature from 5

°C to 22 °C decreased the bulk viscosity leading to emulsion destabilization.

The rate at which an emulsion destabilizes depends on several factors; product composition,

processing and storage conditions (McClements, 2007; Rousseau, 2002). In the awareness of these

factors, processes like; homogenisation, control of temperature and addition of emulsifying agents

or thickeners are often applied. Homogenisation is a key technology to enhance storage stability of

conventional dairy products, disrupting the fat globules and hence increasing the number of small

globules (Lu et al., 2013). Plasma proteins are rapidly adsorbed at the surface of the newly formed

fat globules, due to their amphiphilic properties. These proteins prevent flocculation and

coalescence by steric repulsion, electrostatic repulsion and a reduction in surface tension (Raikos,

2010). Since the surface area of homogenised fat globules is highly covered by plasma proteins,

globules behave more or less like casein micelles. Hence changes causing casein micelles to

aggregate will also lead to fat aggregation, e.g. renneting, souring, heating at high temperatures etc.

(Walstra et al., 2006). Another way to enhance stability of emulsions is by the use of emulsifying

agents or thickeners (Rousseau, 2002). Emulsifying agents will be adsorbed in the MFGM like

natural surfactants, preventing agglomeration of the globules (Lu et al., 2013).

Changes in proteins during storage of UHT milk include; proteolysis, protein-protein interactions,

sulphydryl compound formation, and protein-lactose interactions (Datta et al., 2002). These changes

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can possibly result in two types of instability; sedimentation and gelation. A number of mechanisms

are behind these instabilities, but these are not well defined (Dalgleish, 1992; Datta et al., 2002).

The sedimentation of proteinaceous material is a result of external forces, commonly gravitational

or centrifugal. The sedimentation rate is affected by particle size and density, and can like the

creaming rate be described by Stockes law (4) (McClements, 2007). The denaturation and

unfolding of whey proteins during UHT treatment, lead to exposure of previously hidden

hydrophobic groups and sulphydryl groups (Raikos, 2010). Unfolded whey proteins are capable of

interacting with themselves, micelles or serum κ-CN and αS2-CN with formation of complexes

from 30 to 100 nm (Dalgleish and Corredig, 2012). In addition calcium phosphate can associate to

the casein micelle. These processes, affecting the micelle weight, are considered to increase the

sedimentation rate. Furthermore, cross-linking of proteins may lead to aggregates and insoluble

precipitates, which can contribute to sedimentation (Dalgleish and Corredig, 2012; Datta et al,

2002; Al-Saadi and Deeth, 2015). Gelation on the other hand is described by an increase in

viscosity during storage, often referred to as age gelation (Datta et al., 2002). The gel consists of a

three-dimensional protein network, which can contain both caseins and whey proteins. Formation of

the protein matrix are not well described in literature, but have been suggested to be initiated by

release of the βκ-complex. (Datta et al., 2001). The age gelation resulting from the βκ-complex is

often referred to as a two-step process. In the first step, the βκ-complex dissociates from the casein

micelle. This dissociation can either be enzymatically induced by plasmin or bacterial proteinases,

or as a result of physico-chemical changes. In the second step the βκ-complex cross-links and

aggregates into a three dimensional protein matrix forming the gel (Datta et al., 2001). The extent of

these changes depends on several parameters, but a major parameter is the type of UHT treatment.

More sedimentation and gelation is in general found in direct UHT milk (Datta et al., 2002).

Physical destabilization is commonly evaluated using analytical techniques, such as; light

scattering, spectroscopy and microscopy (Mengual et al., 1999). In this thesis, creaming and

sedimentation are analysed by use of Lumifuge and Turbiscan, both based on light scattering

technologies. Lumifuge is an optical stability analyzer, which accelerates physical destabilization

by centrifugal forces (Ng et al., 2013). Near infrared light illuminates the sample cell while the

system measures transmission continuously during the centrifugation process. Measured

transmission as a function of the local position yields the corresponding transmission profile (Ng et

al., 2013). Turbiscan is another example of an optical stability analyzer. This instrument uses a near

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infrared light source and two detectors; a transmission and backscattering detector. The

backscattering technique enables measurements of concentrated and opaque dispersions (Mengual

et al., 1999). Turbiscan is not able to accelerate physical destabilization, instead exposure to

specific conditions and regular analysis is needed for an accelerated shelf life test (Mengual et al.,

1999).

4. Material and methods

4.1 Milk samples and treatments

Milk used in the trials originated from two batches (A and B) of skimmed and full fat commercial

UHT milk, obtained from Arla Foods Pronsfeld Dairy (Pronsfeld, Germany). The composition

provided by the manufacturer was; 0.3% fat, 5.0% carbohydrates and 3.5% protein in the skimmed

milk and 3.5% fat, 4.8% carbohydrates and 3.3% protein in the full fat milk. The milk was pre-heat

treated at 90 °C for 120 sec, and indirectly UHT treated using a tubular heat exchanger at 140 °C for

6 sec. A single stage homogenization took place upstream at 200/0 bar.

The two milk products were subjected to different storage temperatures, in order to accelerate the

shelf life development over a period of 24 weeks. Storage temperatures selected for the study were

10 °C, 20 °C, 30 °C, 40 °C and 50 °C. Furthermore, three temperature cycles were applied, which

were switched between two temperatures with two weeks intervals. Temperature cycle 1 were

exposed to 10 °C and 30 °C, cycle 2 to 20 °C and 40 °C and cycle 3 to 30 °C and 50 °C (Figure 1).

Milk stored at 50 °C and cycle 3 were analysed over a period of 8 weeks, whereas milk stored for

10 °C to 40 °C including cycle 1 and 2 were analysed over a period of 24 weeks.

4.2 Analysis of chemical changes

The initial MR was indirect measured with a quantification of furosine by reverse phase-high

performance liquid chromatography (RP-HPLC), with diode array detector (DAD). Solid phase

micro extraction-gas chromatography-mass spectrometry (SPME-GC-MS) was used to detect and

relatively quantify volatile compounds; intermediate MRP´s and products from lipid oxidation.

Fluorescence spectroscopy was used to measure both intermediate and late MR´s by the use of a

multi-mode microplate reader. Development of late MR´s was measured as changes in colour.

Additionally, HPLC was used to analyse the protein composition of the samples, and peptide

formation as an indirect measure of enzyme activity.

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4.2.1 Peptide analysis by HPLC

Peptide analysis by the use of HPLC allows a detection and identification of pH 4.6 soluble

peptides and native whey proteins. In this thesis the method was used to demonstrate the absence of

enzyme activity in the UHT milk. Full fat and skimmed UHT milk from week 0 and week 24

(stored at 30 °C) were analysed. The method for peptide analysis was based on Rauh et al. (2014c).

The pH-meter 766 Calimatic (Knick GmbH, Germany) was calibrated with buffer solution pH 7

and 10 from VWR Chemicals, and pH was measured in the milk samples prior to pH adjustment.

Milk samples of 20 mL were adjusted to pH 4.7 with 1 M HCl, stirred and adjusted to a final pH of

4.5. The samples were subsequently stirred for at least 15 min to ensure a constant pH. The pH

adjusted milk samples were centrifuged at 17090 x g for 10 min at 4 °C, and 1.5 mL was frozen for

later use. Prior to HPLC analysis the samples were centrifuged at 11.000 x g for 10 min at 4 °C to

separate fat particles and eventually precipitated casein micelles from the supernatant.

Approximately 1 mL of the clear supernatant was transferred to HPLC vials and 20 µL were

injected into the HPLC system. The column used to separate peptides and whey proteins was

AdvanceBio Peptide Map (Agilent Technologies, 250 mm * 2.1 mm, 2.7 µm), with a temperature

of 45 °C. Two buffers were used for a gradient elution. Buffer A contained Milli-Q water with 0.1%

TFA and buffer B contained acetonitrile with 0.5% TFA. A linear gradient was applied using 100%

of buffer A from 3 min, 100%-45% of buffer A at 45 min with a flow rate of 0.3 mL/min. Detection

of the peptides was conducted with a UV-detector, at a wavelength of 214 nm. Measurements were

performed in duplicates.

4.2.2 Initial Maillard reactions

Furosine formation in the milk samples was measured after acid hydrolysis by RP-HPLC-DAD.

The method was based on Jansson et al. (2014c) and Rauh et al. (2014b). 3 mL of 10 M HCl was

added to 1 mL milk in screw-cap tubes and bubbled with nitrogen for 2 min to avoid oxidation. The

milk was hydrolysed in presence of HCl for 18 hours at 110 ºC. The hydrolysate was cooled and

filtered through a 0.45 µm Whatman filter paper (Black Ribbon 589/1, Schleicher & Schuell

MicroScience GmbH, Germany). The filtered hydrolysate was diluted 5 times with 3 M HCl and

transferred to Whatman Mini-UniPrep filter HPLC vials. 10 µL of this was injected into the HPLC

system. Furosine was analysed by RP-HPLC with isocratic elution, using 0.06 M sodium acetate

buffer with a flow rate of 1 mL/min from 0-4 min, and 0.5 mL/min from 4-15 min.

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Compounds were separated with a Supelco Supercosil LC-8 column (Sigma-Aldrich Inc., 250 mm

* 4.6 mm, 5 µm) with a temperature of 40 °C. Detection was conducted with a DAD-detector

(Sigma-Aldrich Inc.), where furosine was detected at a wavelength of 280 nm. An external standard

was used to quantify the amount of furosine in the UHT milk samples. Stock solutions of pure

furosine standard (99.4%) were prepared and calibration curves were made. This was done by

plotting the furosine standard concentrations as a function of the peak area obtained from the HPLC

analysis.

4.2.3 Intermediate Maillard reactions and lipid oxidation

Fluorescence spectroscopy can be used to detect intermediate and late MRP´s. Fluorophores are

generally aromatic and highly conjugated compounds, able to absorb and emit light. These

compounds include; proteins, pigments, colored substances and flavoring compounds (Van Boekel,

1998; Lakowicz, 1999). Fluorescence intensity was in this study measured at an excitation

wavelength of 360 nm, and emission wavelengths of 380-480 nm. For this approach a Multi-mode

microplate reader (SynergyTM

Mx, BioTek) was used, with the software GEN 5 2.0. Fluorescence

was measured in the milk fraction soluble at pH 4.5, to avoid potential interference from proteins

and fat resulting in quenching and due to the turbidity of milk. The pH-meter 766 Calimatic (Knick

GmbH, Germany) was calibrated with buffer solution pH 7 and 10 from VWR Chemicals. Milk

samples of 20 mL were pH adjusted to 4.5 with 1 M HCl. The milk samples were centrifuged at

4 C for 10 min at 17090 x g to separate precipitated caseins and denatured whey proteins from the

supernatant. The supernatant was diluted with Milli-Q water in the ratio of 1:1 and 200 L of each

diluted sample was transferred to a microtiter plate. Water was added to the last well of each row as

control. Measurements were performed in biological and analytical duplicates.

Additionally, analysis of low molecular weight products, including intermediate MRP´s and lipid

oxidation products, was conducted by SPME-GC-MS. The volatile products were extracted with the

use of SPME (PAL CTC-Analytics), separated by GC and detected by MS. Prior to the analysis the

milk samples were frozen at -20 ºC. 5 mL of milk was injected with the internal standard 5-methyl-

2-hexanone, to enable a relative quantification. This internal standard was chosen on basis of its

structural similarities to the volatile compounds of interest, and in addition on its absence in milk

naturally. Helium was used as carrier gas with 1 mL/min. The compounds were injected into a gas

chromatograph (Agilent Technologies, 6890A) with an inlet temperature of 250 ºC. The separation

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was conducted with an Agilent GC column (HP-FFAP 19091F-433, 30.0 m * 0.25 mm, film

thickness = 0.25 µm) at a temperature of 40 ºC for 2 min, to 200 ºC with a rate of 5 ºC/min.

Identification of the separated volatiles were achieved with a 5973 quadrupole mass spectrometer

(Agilent Technologies). A MS database (NIST MS search 2.0) was used to compare the measured

retention times and mass spectral data with reference spectra. Further identification was conducted

in selected ion monitoring (SIM) mode, where selected ions were used to identify the compounds of

interest. This analysis mode eliminates noise from impurities, and may be preferable when the

compounds of interest are present in low concentrations (Jansson, 2014a).

4.2.4 Late Maillard reactions

Late Maillard reactions lead to the formation of brown coloured

polymers called melanoidins. Formation of these products can be

evaluated by measurement of colour changes (Al-Saadi and

Deeth, 2008). Colour measurements were conducted with the

use of a Chroma-Meter (CR-400, Konica Minolta) using the

software; CR-400 Utility Software (CR-S4w, Ver. 1.10). The

instrument was calibrated with a white Minolta standard plate,

before colour of the milk samples were measured. Colour

parameters were expressed according to the CIELAB system,

with illuminant D65 and a visual angle of 0°. The colour space

components are L* (Black: L* = 0 and white: L* = 100), a* (red-green: negative a* = greenness

and positive a* = redness) and b* (yellow-blue: negative b* = blueness and positive b* =

yellowness) (McGuire, 1992), as depicted in Figure 13. Measurements were performed with two

biological duplicates and two analysis duplicates. Each analysis duplicate was a mean of five

determinations at ambient temperatures. The colour values were determined as means of all

replicates.

4.2.5 Protein composition

Protein composition of the milk samples was analysed using HPLC. This method can be used for

identification and quantification of caseins and whey proteins, and allows an evaluation of the

lactosylation of proteins (Bordin et al., 2001). For this analysis 200 L milk was frozen at -20 °C

until further use. Prior to analysis milk proteins were dissociated by 6 M urea, 0.1 M trisodium

Figure 13 – CIELAB colour model with the three colour space components (dba.med.sc.edu, 2000)

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citrate and reduced by 0.5 M dithioerythritol (DTE). Urea causes an extraction of hydrophobic

bonds and DTE reduces disulfide bonds (S-S). Moreover, sodium citrate functions as a chelating

agent dissolving the casein micelle by ion exchange. Without calcium the micelles will dissociate

(De Jong et al., 1993). From the reduction buffer, of urea and citrate, 1000 µL was added to 200 µL

milk samples followed by 20 µL 0.5 M DTE. After mixing with reduction buffer the samples were

incubated at 30 C for 60 min while shaking to reduce cross-linking, non-covalent bonds and

disulfide bonds. Afterwards the samples were centrifuged at 11.000 x g at 5C for 10 min. A

volume of 5 L supernatant was injected into the HPLC system and separated by a Biosuite column

C18 (PA-B 250 mm x 2.1 mm, pore size of 300 Å and particle size of 3.5 µm) (Waters, USA).

Compounds were separated with a gradient elution using two buffer solutions, and a column

temperature of 40 C. Buffer A contained 0.05% triflouroacetic acid (TFA) in Milli-Q water, and

buffer B contained 0.1% TFA in acetonitrile. A linear gradient of buffer B were applied, from

33.2% to 44.3% (2.8-16.0 min) with a flow of 0.35 mL/min. A UV-detection of 214 nm was used,

since this is the wavelength that is absorbed by peptide bonds. Measurements were performed in

duplicates and the method was based on Bordin et al. (2001) and Bonfatti et al. (2008).

4.3 Analysis of physical changes

Creaming and sedimentation were evaluated during the storage period using; optical stability

analyzers, evaluation of protein and fat distribution in top, middle and bottom fractions and fat

globule size distribution.

4.3.1 Physical destabilization

Analysis of instability due to creaming and sedimentation has been optically characterized with the

use of Lumifuge (L.U.M GmbH, Germany) and Turbiscan (Turbiscan 2000, Sweden). Lumifuge is

an optical stability analyser, which simulates destabilisation processes due to gravitational forces

and hence accelerates shelf life development. This technique applies near infrared light radiated to

the sample during centrifugation and measures transmission from top to bottom of the sample cell

(Ng et al., 2013). Prior to analysis, the milk samples were gently homogenized by shaking from side

to side, whereafter 400 L milk was transferred to Lumifuge sample cells. The samples were

centrifuged at 2300 x g for 43 min at room temperature and transmission was measured at a

wavelength of 865 nm. Transmission was measured for 255 cycles with duration of 10 sec.

Measurements were performed in biological and analytical duplicates.

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Transmission profiles were analysed with the Lumifuge software SEPView. The transmission

profiles correspond to the measured transmission in % as a function of the local position on the

centrifuge tube in mm. From the transmission profiles it is possible to calculate an instability index,

within the range 0 to 1, depending on the instability of the dispersion. The instability index is based

on the following equation:

Instability index = (𝒆𝒏𝒅 𝒕𝒓𝒂𝒏𝒔𝒎𝒊𝒔𝒔𝒊𝒐𝒏−𝒔𝒕𝒂𝒓𝒕 𝒕𝒓𝒂𝒏𝒔𝒎𝒊𝒔𝒔𝒊𝒐𝒏)−(𝒆𝒏𝒅 𝒕𝒓𝒂𝒏𝒔𝒎𝒊𝒔𝒔𝒊𝒐𝒏−𝒄𝒖𝒓𝒓𝒆𝒏𝒕 𝒕𝒓𝒂𝒏𝒔𝒎𝒊𝒔𝒔𝒊𝒐𝒏)

(𝒆𝒏𝒅 𝒕𝒓𝒂𝒏𝒔𝒎𝒊𝒔𝒔𝒊𝒐𝒏−𝒔𝒕𝒂𝒓𝒕 𝒕𝒓𝒂𝒏𝒔𝒎𝒊𝒔𝒔𝒊𝒐𝒏) (9)

Where the start transmission is the first measured transmission, the current transmission is defined

to be the transmission after 2000 sec of centrifugation and the end transmission is the transmission

after 43 min of centrifugation. The values included in the equation are transmission measured at a

defined position on the sample cell. In skimmed milk a clarification of the top fraction was

observed, hence the position in skimmed milk was defined to be 5 mm from the meniscus and down

in the sample. In full fat milk slight clarification was observed in the bottom fraction, hence the

measured position was defined to be 5 mm above the bottom of the sample cell. Examples of the

transmission profiles provided by Lumifuge and the position defined for the current transmission

are illustrated in Appendix 1.

Another way to analyse stability of an emulsion is with Turbiscan. The Turbiscan technique is

based on multiple light scattering measurements. It uses emission of pulsed near infrared light

(wavelength of 850 nm) and detection by the use of transmission and backscattering photodiodes

(Mengual et al, 1999). Light backscattered by the milk sample was measured at an angle of 135°

every 40 µm at the entire length of the sample. Prior to analysis cylindrical glass measurement cells

were sterilized by autoclavation at 120 C for 20 min. 5 mL of milk was transferred into each cell in

a microbiological safety cabinet. The samples were stored at 10 C, 20 C, 30 C and 40 C

including the three temperature cycles and measured continuously during a period of 24 weeks. The

measurements were performed with two biological replicates and three analytical replicates.

Backscattering profiles were analysed with the TurbiSoft 2000 software, corresponding to the

measured backscattering in % as a function of the local position on the sample cell in mm.

Creaming was defined as the maximum backscattering in full fat milk, sedimentation as the

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Figure 14 – Schematic illustration of the separation process with use of negative pressure.

maximum backscattering in skimmed milk and clarification as the backscattering at the local

position of 25 mm from the bottom of the sample cell (Appendix 2).

4.3.2 Protein and fat content

Protein and fat content in the milk samples were determined by

Milkoscan FT1 (Foss, Denmark), which is based on Fourier

transform infrared (FT-IR) spectroscopy. In infrared spectro-

scopy, infrared radiation is passed through the sample. Some of

the infrared radiation is absorbed, resulting in vibrations of

chemical bonds, and the rest is transmitted through the sample

and detected. To convert raw data into an infrared spectrum a

mathematical procedure, referred to as a Fourier transform, is

needed. The resulting spectrum represents the molecular

absorption and transmission, creating a molecular fingerprint of

the sample. Milkoscan is able to recognize and compare spectra

from previous measurements. The milk was measured at room

temperature in three fractions; top, middle and bottom. The milk was transferred from the bottom of

the carton by the use of vacuum through a glass tube, as demonstrated in Figure 14. Measurements

were performed on full fat milk in biological and analytical duplicates.

4.3.3 Fat globule size distribution

The particle size distribution was determined by static light scattering (SLS) using Mastersizer 3000

(Malvern Instrument Ltd., Malvern, UK). The principle of this laser diffraction measurement is that

particles are passed through a focused laser beam. These particles scatter light at angles inversely

proportional to their size. Angular variation in intensity of the scattered light is then measured by a

series of photosensitive detectors. The scattering intensity versus angle is the primary source of

information used to calculate the particle size (Michalski et al., 2001; Malvern Instrument Ltd,

2015). Prior to analysis the milk samples were gently homogenized by shaking from side to side.

The milk samples were diluted in distilled, degassed water and added to the instrument under

agitation at 1000 rpm, until a laser obscuration of approximately 5% was reached. The procedure

was performed with and without urea buffer to dissociate proteins from the fat globules

(Gaucheron, 2005). Milk proteins were dissociated by 6 M urea and 0.1 M trisodium citrate (De

Jong et al, 1993). 9 mL urea buffer was added to 1 mL milk and analysed after 1 hour. Calculation

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of particle size was performed by the Mastersizer 3000 software (version 3.4) using the Mie theory,

which assumes spherical particles and requires refractive indices (milk fat: 1.46, water: 1.33)

(Mickalski et al., 2001). The absorption index used for milk fat was 0.1 (Malvern Instruments,

1997). Milk samples were measured at room temperature and performed in biological and analytical

duplicates. From a volume weighted particle size distribution, the percentiles; Dv10, Dv50 and

Dv90 were calculated. These parameters describe the maximum particle diameter for a given

percentage of the sample volume. Hence it is possible to detect changes in the main, as well as the

extreme particle sizes.

4.4 Data analysis

Means and standard deviations were calculated for all data. A one-way analysis of variance

(ANOVA) was applied to investigate significant effects of UHT milk stored over time at different

temperatures (10-50 °C). Statistical significance was defined at P≤0.05, with a 0.95% confidence

interval. In addition linear regression models were applied to test for linear correlations. These

statistical tests were carried out with Microsoft Excel 2010. Multivariate data analysis in the form

of Principal component analysis (PCA) was carried out with use of the Simca software (version

14.0, Umetrics AB, Umeå, Sweden). To investigate grouping of the samples all quantified

parameters were included from the chemical analyses as well as parameters of protein and fat

distribution and instability index.

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5. Results

This accelerated shelf life test is evaluated with characterisation of chemical and physical

parameters, hence the following is separated into two parts. The first part covers chemical changes

in UHT milk and the second part covers physical changes in UHT milk during the storage period of

24 weeks. The accelerating factor is elevation of storage temperatures including the three

temperature cycles.

5.1 Chemical changes

The acceleration of chemical parameters includes an evaluation of the MR and lipid oxidation. All

samples were tested for batch variations, small differences were detected but these were not

significant.

5.1.1 Enzymatic hydrolysis

Enzymatic hydrolysis can affect physical stability as well as the MR during storage of UHT milk.

Based on this, enzymatic activity was indirectly investigated by a peptide analysis using HPLC. The

enzymatic hydrolysis is reflected by the formation of pH 4.6 soluble peptides in the milk during

storage. Figure 15 shows the development in peptide profiles of selected skimmed UHT milk stored

for 0 weeks and 24 weeks at 30 °C. The same pattern was observed for full fat UHT milk.

Figure 15 –Peptide profile of pH 4.6 soluble peptides in skimmed UHT milk. Chromatogram in green is skimmed UHT milk from week 0 and chromatogram in blue is skimmed UHT milk stored at 30 °C after 24 weeks.

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Storage time (weeks)

0 5 10 15 20 25

mg f

uro

sin

e /

10

0 g

pro

tein

0

100

200

300

400

500

600

700

800

10 oC

20 oC

30 oC

40 oC

50 oC

Cycle 1

Cycle 2

Cycle 3

Retention time (min)

0 2 4 6 8 10 12 14

Absorb

ance (

mA

U)

-20

0

20

40

60

80

100

120

140

160

Fu

rosin

e (

7.0

33

)

Overall the total peak area of pH 4.6 soluble peptides increased. The total peak area (AU) from the

peptide profiles were in week 0 found to be 0.46 *105 and 0.57 *10

5 for full fat and skimmed milk

respectively, whereas the peak area in week 24 were found to be 0.95 *105 and 0.94 *10

5 for full fat

and skimmed milk. Increases in the peak area were mainly observed between 25 to 45 min, which is

probably due to lactosylations. Peaks between 36 and 38 min are plasmin degradation products of

β-CN, based on similar chromatographic patterns from previous studies (Rauh et al., 2014c). These

peaks were observed to broaden with time and temperature. pH 4.6 soluble peptides eluted between

10 and 20 min approximately, have previously been identified as small hydrophobic peptides,

mainly formed in presence of hydrolytic enzymes (Rauh et al., 2014c). In this region no remarkable

increases were seen.

5.1.2 Initial Maillard reactions

Detection of furosine in acid hydrolysed milk was measured using RP-HPLC-DAD, to give an

indirect quantification of the initial MRP, lactulosyllysine. Furosine was detected at 280 nm with a

retention time of approximately 7 min, as shown in Figure 16. Retention times of standard furosine

fractions coincided with retention times of the eluted peaks. The formation of furosine was analysed

in full fat and skimmed UHT milk, stored at temperatures of 10 °C, 20 °C, 30 °C, 40 °C, and 50 °C

including the three temperature cycles, over periods of 8 weeks (50 °C and cycle 3) and 24 weeks

(10-40 °C, cycle 1 and 2). Figure 17 illustrates the effect of storage temperature on the formation of

furosine over time.

Figure 17 – Furosine concentration in skimmed UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles. Error bars indicate standard deviation, n=2.

Figure 16 – HPLC chromatogram of furosine detected at 280 nm.

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For simplification only skimmed milk is included in Figure 17, since the formation of furosine in

full fat milk followed the same pattern and no significant differences were detected. The data

included is based on mean values from biological duplicates. The formation of furosine was

significantly increasing in skimmed as well as full fat UHT milk stored at 20 °C and above, affected

by storage time and temperature.

The concentration of furosine (mg furosine/100g protein) after 8 weeks was highest in milk stored

at 50 °C, followed by 40 °C, 30 °C, 20 °C and 10 °C, indicating a strong temperature dependence of

the reaction. In temperature cycle 1, stored at 10 °C and 30 °C, concentrations of furosine were

significantly higher than in samples stored at 20 °C. The same tendency was seen for cycle 2, stored

at 20 °C and 40 °C, which showed higher concentrations than at 30 °C, and cycle 3 stored at 30 °C

and 50 °C, showed higher concentrations than milk stored at 40 °C.

The furosine concentration after 24 weeks at 20 °C was 338mg furosine/100g protein, which is

corresponding to the concentration at 30 °C after 8 weeks, and 40 °C after 3 weeks of storage. After

the period of 24 weeks the furosine content was approximately 1.5 times higher in milk stored at

30 °C than in milk stored at the ambient temperature of 20 °C, and approximately 2.2 times higher

in milk stored at 40 °C than in milk stored at 20 °C. The formation of furosine does not seem to be

linearly correlated with storage time, since it levels off with time. On this background the formation

seems to fit well to a first order reaction kinetic, indicating that the furosine formation can be

kinetically described. The common first order reaction kinetic for product formation follows the

equation:

𝐶𝑡 = 𝐶𝑚𝑎𝑥(1 − 𝑒−𝑘𝑡) + 𝑐 (5)

Where Ct is the concentration at a time t, Cmax is the maximum concentration, k is the rate constant,

and c is the concentration at the beginning of the reaction. A first order kinetic resulted in k, Cmax

and R2

values presented in table 1. Both k and Cmax were found to increase with temperature. An

elevation of the storage temperature from 20 °C to 50 °C increased k 7.2 times in skimmed and 6.7

times in full fat milk, whereas Cmax increased 2.2 times in skimmed and 1.9 times in full fat milk. R2

values were above 0.9 for all plots.

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Table 1 – Kinetic parameters for first order formation of furosine in skimmed and full fat UHT milk stored at temperatures between 10 °C and 50 °C, including temperature cycles.

The effect of storage temperature on the velocity of chemical reactions can be evaluated with use of

the Arrhenius equation (Martins et al., 2001). This correlation between the rate constant and the

absolute temperature can be depicted in an Arrhenius plot, based on the natural logarithm of the

Arrhenius equation:

ln(𝑘) = ln(𝐴) −𝐸𝑎

𝑅∗

1

𝑇 (6)

Where k is the rate constant, Ea is the activation energy (J/mol), R the universal gas constant (8.314

J/mol K), T the absolute temperature (K) and A is the pre-exponential factor (Kessler, 2002). The

Arrhenius plot in Figure 18 depicts the natural logarithm of the rate constants, from formation of

furosine, as a function of the inverse temperature. This plot illustrates a linear correlation between

changes in reaction rate and storage temperature. R2 from these linear regressions were 0.993 and

0.989, for skimmed and full fat milk respectively. This correlation can be supported by Q10 values,

corresponding to the changes in rate for each 10 °C elevation in storage temperature. Q10 can be

calculated from equation 3. In this analysis Q10 for all steps were in the range of 1.5 and 2.3. From

Milk type Storge temperature

k Cmax R2

Skimmed 10 °C 0,016 40 0,921

Full fat 10 °C 0,026 39 0,994

Skimmed 20 °C 0,045 202 0,994

Full fat 20 °C 0,049 229 0,970

Skimmed 30 °C 0,093 245 0,992

Full fat 30 °C 0,090 309 0,985

Skimmed 40 °C 0,144 415 0,933

Full fat 40 °C 0,143 398 0,997

Skimmed 50 °C 0,330 457 0,997

Full fat 50 °C 0,329 446 0,992

Skimmed Cycle 1 0,180 170 0,998

Full fat Cycle 1 0,209 210 0,946

Skimmed Cycle 2 0,150 350 0,998

Full fat Cycle 2 0,140 315 0,990

Skimmed Cycle 3 0,181 530 0,995

Full fat Cycle 3 0,180 630 0,999

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Figure 19 – pH values in skimmed UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles. Error bars indicate standard deviation, n=2.

the slope of the Arrhenius plot it is possible to calculate the activation energy. The activation

energies were found to be 51 kJ/mol and 46.7 kJ/mol for skimmed and full fat milk respectively.

Figure 18 – Effect of storage temperature (10 °C to 50 °C) on the rate constants for furosine formation, in skimmed and full fat UHT milk. Linear regressions are included.

Changes in pH were measured in full fat and skimmed UHT milk, stored at different temperatures.

Figure 19 demonstrates the development of pH in skimmed UHT milk, with data representing mean

values of biological duplicates.


0 5 10 15 20 25

pH

0,0

6,3

6,4

6,5

6,6

6,7

10 o C

20 o C

30 o C

40 o C

50 o C

Cycle 1

Cycle 2

Cycle 3

1/T (10-3

* K-1

)

0,0030 0,0031 0,0032 0,0033 0,0034 0,0035 0,0036

ln k

(k in s

-1)

-4,5

-4,0

-3,5

-3,0

-2,5

-2,0

-1,5

-1,0

-0,5

Skimmed milk

Full fat milk

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The pH value decreased with time and temperature in skimmed milk as well as in full fat milk. At

the beginning of the study pH in the milk samples were 6.7 for skimmed milk and 6.65 for full fat

milk. During storage the pH of all samples decreased significantly, though changes in milk stored at

10 °C were minimal. The final pH of skimmed UHT milk stored at 10 °C, 20 °C, 30 °C and 40 °C

for 24 weeks were 6.67, 6.62, 6.58, and 6.36 respectively. Only milk stored at 40 °C and 50 °C

follows a linear regression with R2 above 0.9.

5.1.3 Intermediate Maillard reactions and lipid oxidation

Formation of fluorescent compounds were analysed in the serum phase of skimmed and full fat

UHT milk, using a Multi-mode microplate reader at excitations of 360 nm. Increases in

fluorescence intensities can possibly be an indication of fluorescent intermediate and late MRPs

(Birlouez-Aragon et al., 2002; Bosch et al., 2007). Figure 20 shows fluorescence intensities

detected in the serum phase of skimmed UHT milk during storage at different temperatures. Data

presented in the figure corresponds to mean max values of fluorescence intensities, based on

biological and analytical duplicates.

The formation of fluorescent compounds was observed to increase with the same pattern in

skimmed and full fat UHT milk, but with significantly higher intensities in skimmed compared to

full fat milk (p<0.05). Overall this formation seems to follow a linear relation, though a short lag

Figure 20 – Fluorescence intensity (ex 360 nm) in skimmed UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles. Linear regression lines and error bars are included, which indicate standard deviation, n=4.


0 5 10 15 20 25

Flu

ore

scen

ce in

ten

sity (

ex 3

60 n

m)

0

20000

30000

40000

50000

10 oC

20 oC

30 oC

40 oC

50 oC

Cycle 1

Cycle 2

Cycle 3

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phase was observed in milk stored at 50 °C and cycle 3, during the first weeks of storage. The linear

relation indicates that the formation of fluorescent compounds follows a zero order reaction kinetic.

The zero order rate constants (k) for the formation were calculated using following equation:

𝐶𝑡 = 𝑘𝑡 + 𝐶0 (7)

Where C0 is the fluorescence intensities at time 0 (beginning of storage), Ct is the fluorescence

intensities after t (storage time in minutes) at a given storage temperature and k is the rate constant.

Kinetic parameters based on a linear regression model are presented in table 2. The p-values

indicates a significant increase in fluorescence intensities with time and temperatures from 30 °C to

50 °C (p<0.05). After 24 weeks the intensity in skimmed UHT milk stored at 40 °C were 2 times

higher than the intensity measured at ambient temperatures (20 °C). Fluorescent compounds formed

in milk exposed to temperature cycle 1 revealed rate constants higher than at 20°C, temperature

cycle 2 revealed rate constants higher than at 30 °C and temperature cycle 3 higher than at 40 °C

(table 2).

Table 2 - Linear regression parameters from changes in fluorescence intensity in skimmed and full fat UHT milk, during storage at temperatures between 10 °C and 50 °C, including temperature cycles.

Milk type Storge temperature

Fluorescence intensity ( ex 360 nm)

k R2 P-value 95% conf.

Skimmed 10 °C 8,52 0,132 0.637 ±66.62

Full fat 10 °C 29,85 0,979 0.100 ±13.14

Skimmed 20 °C 11,73 0,059 0.629 ±58.81

Full fat 20 °C -5,42 0,003 0.903 ±109.45

Skimmed 30 °C 128,16 0,681 0.022 ±100.82

Full fat 30 °C 70,47 0,567 0.050 ±70.77

Skimmed 40 °C 872,09 0,966 0.000 ±109.11

Full fat 40 °C 817,49 0,934 0.000 ±144.39

Skimmed 50 °C 3474,96 0,951 0.000 ±705.10

Full fat 50 °C 2953,95 0,920 0.000 ±779.95

Skimmed Cycle 1 16,38 0,028 0.832 ±292.73

Full fat Cycle 1 63,77 0,333 0.422 ±274.25

Skimmed Cycle 2 301,90 0,982 0.001 ±73.31

Full fat Cycle 2 189,29 0,841 0.028 ±151.18

Skimmed Cycle 3 1413,21 0,973 0.105 ±3010.25

Full fat Cycle 3 1064,75 0,981 0.088 ±1893.13

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Storage temperature ( oC)

0 10 20 30 40 50 60

k (

flu

ore

sce

nce

in

ten

sity /

we

ek)

0

1000

2000

3000

4000

Skimmed milk

Full fat milk

1/T (10-3

* K-1

)

0,0030 0,0031 0,0032 0,0033 0,0034 0,0035 0,0036 0,0037

ln k

(k in

s-1

)

1

2

3

4

5

6

7

8

9

Skimmed milk

Full fat milk

Figure 21 is based on the rate constants presented in table 2, plotted as a function of the storage

temperature. The figure indicates that the rate at which fluorescent compounds are formed increases

for every 10 °C. Q10 values calculated from equation 3 were in skimmed milk; 1.3, 10.9, 6.8 and 3.9

for each 10 °C rise in temperature. In full fat milk the following Q10 values were found; 0.2, 13,

11.6, and 3.6. This effect of storage temperature on the rate can also be illustrated with use of the

Arrhenius equation, as depicted in Figure 22. The plot is based on the natural logarithm of the

Arrhenius equation (6) and illustrates a correlation between the rate and the storage temperature

from 20 °C to 50 °C. The rates corresponding to UHT milk stored at 10 °C do not seem to fit into

the Arrhenius plot (furthest to the right in Figure 22). This may indicate that reactions occurring at

20 °C and above are not present at 10 °C. Data from milk stored at 10 °C is therefore not included

in the linear regressions from Figure 22. The linear correlations are supported by R2 values for the

regression lines, which is 0.992 for skimmed milk and 0.986 for full fat milk. From the slope of

such an Arrhenius plot it is possible to calculate the activation energy, but since the fluorescence

intensity reflects several reactions it can be hard to draw conclusions about activation energies.

Figure 21 – Velocity constants (k) from development in fluorescence intensity as a function of storage temperature (10 °C to 50 °C) in skimmed and full fat UHT milk.

Figure 22 - Effect of storage temperature on the rate constants for formation of fluorescent compounds, in skimmed and full fat UHT milk. Linear regressions include data from 20 °C to 50 °C.

of 85

Detection of specific intermediate MRP´s was conducted with the use of GC-MS. Due to technical

problems with the GC-MS coupled to dynamic head space (DHS) there was only time for a single

determination using SPME. Hence no standard deviations are included in the following results.

Both methods are sensitive and reproducible, but their specificity for volatiles differs. DHS has

shown to provide a higher quantity and number of different volatile compounds, mainly due to a

larger surface area of the adsorbent trap (Barrious et al., 2013; Jansson, 2014a). Compounds related

to lipid oxidation and the intermediate stage of the MR were analysed in total ion current (TIC)

chromatogram mode. For identification, measured retention times and mass spectral data were

compared with reference spectra in an MS database (NIST MS search 2.0) and following analysed

in selected ion monitoring (SIM) mode. SIM enhances the sensitivity and accuracy of quantitative

results by selection of specific mass-to-charge ratios for identification of particular compounds

(Jansson, 2014a). All concentrations measured with GC-MS are in this study based on peak areas

relative to the internal standard 5-methyl-2-hexanone. Table 3 gives an overview of the volatile

compounds detected in this study including retention times and ions selected for identification and

relative quantification in SIM mode. Volatiles detected in this study are; furfural, 2-furanmethanol,

2-ethylfulan, 2-heptanone, 2-nonanone and 2-undecanone.

Table 3 – Volatile compounds detected by SPME-GC-MS, retention times and ions used in SIM mode.

Volatile compounds Retention time (min) m/z

Furfural 14.1 96/95

2-furanmethanol 18.7 98/81

2-ethylfuran 2.7 81/96

2-heptanone 6.7 58/114

2-nonanone 11.9 58/142

2-undecanone 17 58/170

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0 5 10 15 20 25

Re

lative

in

ten

sity (

AU

)

0,000

0,005

0,010

0,015

0,020

0,025

0,030

40 oC

50 oC


0 5 10 15 20 25

Re

lative

in

ten

sity (

AU

)

0,0

0,2

0,4

0,6

0,8

1,0

1,2

30 oC

40 oC

50 oC

Figure 23 and 24 shows the formation of the two volatile compounds furfural and 2-furanmethanol.

The development of these products was measured in full fat UHT milk during storage at different

temperatures. Figure 23 depicts the relative concentration of furfural, which can be formed in the 3-

deoxyosone pathway of the MR, favoured by acidic pH. This compound was only detected in milk

stored at 40 °C and 50 °C. In Figure 24 the relative formation of 2-furanmethanol is shown, which

may also be a product from the 3-deoxyosone pathway (Van Boekel, 1998). This compound was

detected in milk stored at 30 °C, 40 °C and 50 °C.

The relative concentrations of furfural and 2-furanmethanol were both increasing significantly with

time and temperature at 40 °C and 50 °C. After storage at 40 °C for 24 weeks the relative

concentration of furfural was 0.017 AU, corresponding to the relative concentration after storage at

50 °C for 6 weeks. The relative concentration of 2-furanmethanol after storage at 40 °C for

24 weeks were 0.755 AU, corresponding to the concentration at 50 °C after 6-7 weeks. Hence an

elevation of the temperature from 40 °C to 50 °C seems to speed up both processes approximately

4 times.

Figure 23 – GC-MS analysis of furfural in full fat UHT milk during storage at 40 and 50 °C.

Figure 24 – GC-MS analysis of 2-furanmethanol in full fat UHT milk during storage at 30, 40 and 50 °C.

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Figure 25 – GC-MS analysis of a) 2-ethylfuran b) 2-heptanone c) 2-nonanone and d) 2-undecanone in full fat UHT milk during storage at 10 °C, 20 °C, 30 °C, 40 °C and 50 °C. Linear regression lines are included.


0 5 10 15 20 25

Rela

tive inte

nsity (

AU

)

0,0

0,2

0,4

0,6

0,8

1,0

10 oC

20 oC

30 oC

40 oC

50 oC

d)


0 5 10 15 20 25

Re

lative

in

ten

sity (

AU

)

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

4,0

c)


0 5 10 15 20 25

Re

lative

in

ten

sity (

AU

)

0,000

0,005

0,010

0,015

0,020

0,025

0,030

a)


0 5 10 15 20 25

Re

lative inte

nsity (

AU

)

0

2

4

6

8

10

10 oC

20 oC

30 oC

40 oC

50 oC

b)

In addition to furfural and 2-furanmethanol four other volatile compounds were looked for with

SPME-GC-MS and analysed in SIM mode. Figure 24 a) reveals the relative formation of 2-

ethylfuran and Figure 24 b), c) and d) reveal the relative formation of three ketones; 2-heptanone, 2-

nonanone and 2-undecanone respectively. These compounds have been analysed in full fat UHT

milk during storage at temperatures between 10 °C and 50 °C. 2-ethylfuran has been found to

originate from specific Strecker degradation products, lipid oxidation and degradation of

carbohydrates (Limacher et al., 2008; Jansson, 2014a), as shown in Figure 10.

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After 24 weeks of storage the 2-ethylfuran content was approximately 3.8 times higher in milk

stored at 30 °C than in milk stored at the ambient temperature of 20 °C, and approximately 7.2 times

higher in milk stored at 40 °C than in milk stored at 20 °C. 2-heptanone, 2-nonanone and 2-

undecanone are ketones formed by lipid oxidation or thermal degradation (Jansson, 2014a). 2-

ethylfuran follows a pattern similar to that of the ketones as shown in Figure 25. Formation of these

four volatile compounds seems to correlate linearly with storage time and has been fitted into a

linear model. From table 3 it can be seen that the relative intensities of the compounds were

significantly correlated with the storage time in UHT milk stored between 30 °C and 50 °C

(p<0.05).

The rate constants for 2-heptanone, 2-nonanone and 2-undecanone are negative at 10 °C, reflecting

uncertainties at these low concentrations (table 4). In addition the rate constants increased with

temperature, indicating that these reactions are temperature dependent. This has been further

investigated with use of the Arrhenius equation (6). Figure 26 reveals an Arrhenius plot illustrating

the temperature dependence of the reaction rates from formation of 2-ethylfuran, 2-heptanone, 2-

nonanone and 2-undecanone.

Table 4 - Linear regression parameters of 2-ethylfuran, 2-heptanone, 2-nonanone and 2-undecanone, during storage at 10 °C to 50 °C.

Storge temp.

2-ethylfuran 2-heptanone



10 °C 2.4*10-6 0.006 0.921 ±9*10-5 -0.0009 0.051 0.772 ±0.011

20 °C 4.4*10-5 0.561 0.052 ±4*10-5 0.0132 0.786 0.007 ±0.007

30 °C 0.0004 0.934 0.0003 ±0.0004 0.071 0.938 0.0003 ±0.020

40 °C 0.0008 0.940 1.8*10-7 ±0.0001 0.213 0.959 2.7*10-8 ±0.030

50 °C 0.002 0.916 4.9*10-5 ±0.0006 0.775 0.921 4*10-5 ±0.202

Storge temp.

2-nonanone 2-undecanone



10 °C -0.002 0.846 0.080 ±0.003 -0.001 0.836 0.085 ±0.001

20 °C 0.003 0.267 0.234 ±0.005 0.0002 0.016 0.781 ±0.001

30 °C 0.029 0.923 0.0005 ±0.009 0.005 0.869 0.002 ±0.002

40 °C 0.104 0.951 7*10-8 ±0.016 0.023 0.939 2*10-7 ±0.004

50 °C 0.375 0.952 7*10-6 ±0.075 0.086 0.954 6*10-6 ±0.016

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The negative rate constants for 2-heptanone, 2-nonanone and 2-undecanone at 10 °C are not

included in the Arrhenius plot. In general elevated temperatures increase the fraction of collisions

with higher energy than Ea, leading to an increase of the reaction rate. In Figure 26, a linear relation

between rate constants for 2-ethylfuran and storage temperatures is observed within two

temperature ranges; 10-30 °C and 30-50 °C. This breaking point at 30 °C indicates changes in the

reactions at temperatures above. The breaking point is most evident in the Arrhenius plot for 2-

ethylfuran and 2-undecanone and is only slightly observed for 2-heptanone and 2-nonanone. Higher

increases in reaction rates were seen between 10 °C and 30 °C than between 30 °C and 50 °C. This

correlation illustrated in Figure 26 can be supported by Q10 values (3), corresponding to the changes

in rate for each 10 °C elevation in temperature. Between 20 °C and 30 °C, Q10 values of 12.5 and 29

were found for 2-ethylfuran and 2-undecanone respectively, whereas Q10 values of 2.8 and 3.7 were

found for the same compounds between 40 °C and 50 °C.

Figure 26 – Effect of storage temperature on the rate constant (k) of the relative formation of 2-ethylfuran, 2-heptanone, 2-nonanone and 2-undecanone, in full fat UHT milk. Included are linear regression lines within the temperature ranges: 10-30 °C and 30-50 °C.

1/T (10-3

* K-1

)

3,1 3,2 3,3 3,4 3,5 3,6

ln k

(k in

s-1

)

-14

-12

-10

-8

-6

-4

-2

0

2-ethylfuran

2-heptanone

2-nonanone

2-undecanone

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0 5 10 15 20 25

b*

0

2

4

6

8

10

12

14

16

10 oC

20 oC

30 oC

40 oC

50 oC

Cycle 1

Cycle 2

Cycle 3

c)


0 5 10 15 20 25

L*

0

70

71

72

73

74

75

76

77

78

79

a)


0 5 10 15 20 25

a*

-5

-4

-3

-2

-1

0

b)

5.1.4 Late Maillard reactions

Late Maillard reaction products were analysed by evaluation of colour changes measured with a

Chroma-Meter. Brown colour development can give an indication of the formation of melanoidins

formed in the MR. These changes were analysed in skimmed and full fat UHT milk during storage

at different temperatures. Figure 27 illustrates the changes in skimmed UHT milk, where each value

reported is a mean of biological and analytical duplicates. Changes in the colour space component

L* are depicted in Figure 27 a) indicating the changes in lightness with time and temperature, b)

depicts changes in a* (negative a* = greenness and positive a* = redness) and c) depicts changes in

b* (negative b* = blueness and positive b* = yellowness). Colour of full fat and skimmed UHT

milk changed with the same pattern over time, but with different offset. The offset in full fat milk of

L*, a* and b* were found to 81, -2.6 and 4.6 respectively.

Figure 27 - Colour changes (L*, a*, b*) (a, b, c) in skimmed UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles. Linear regression lines and error bars are included, indicating standard deviation, n=4.

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In skimmed milk the detected offset values were lower for all three colour space components, found

to be 76.6, -4.4 and 2.8 as shown in Figure 27. Changes in L*, a* and b* values were observed to

correlate linearly with the storage time. Linear regression parameters are presented in table 4. This

linear correlation indicates that the formation of brown coloured polymers follows a zero order

reaction kinetic. The zero order rate constants (k) for the development of colour space components

a* and b* were determined on basis of equation 7. Due to the decreasing development of L*, the

following equation has been applied for calculation of k.

𝐶𝑡 = −𝑘𝑡 + 𝐶0 (8)

As shown in table 5, the L* values were significantly decreasing with time in milk stored at 20 °C

to 50 °C, indicating a darkening. At the same time a* and b* values were significantly increasing in

milk stored at 30 °C to 50 °C (p<0.05), resulting in more red and yellow colours. Skimmed UHT

milk stored at 20 °C for 24 weeks revealed a L* value of 75.6, similar to the value detected in milk

stored at 30 °C for 20 weeks and 40 °C for 6 weeks.

Table 5 – Linear regression parameters from L*, a* and b* changes in skimmed and full fat UHT milk at temperatures between 10 °C and 50 °C, including temperature cycles.

Milk type Storge temp.

L* a* b*

k R2 P-

value 95% conf.

k R2 P-

value 95% conf.

k R2 P-

value 95% conf.

Skimmed 10 °C 0.0626 0.707 0.158 ±0.120 -0.009 0.747 0.135 ±0.015 -0.018 0.847 0.079 ±0.023

Full fat 10 °C 0.0159 0.728 0.146 ±0.029 0.002 0.154 0.608 ±0.014 0.0055 0.681 0.174 ±0.011

Skimmed 20 °C 0.0432 0.926 0.0005 ±0.014 0.0003 0.019 0.770 ±0.003 0.0026 0.089 0.537 ±0.010

Full fat 20 °C 0.0130 0.604 0.039 ±0.012 0.0033 0.189 0.513 ±0.012 0.0170 0.406 0.123 ±0.023

Skimmed 30 °C 0.0770 0,921 0.0006 ±0.026 0.0226 0.912 0.0008 ±0.008 0.0802 0.967 0.000 ±0.016

Full fat 30 °C 0.0414 0.991 0.000 ±0.004 0.0330 0.919 0.0006 ±0.011 0.0498 0.872 0.002 ±0.021

Skimmed 40 °C 0.2670 0.979 0.000 ±0.025 0.0918 0.965 0.000 ±0.011 0.4289 0.997 0.000 ±0.016

Full fat 40 °C 0.1458 0.9956 0.000 ±0.006 0.0945 0.977 0.000 ±0.009 0.3037 0.989 0.000 ±0.015

Skimmed 50 °C 0.8230 0.972 0.000

±0.124 0.3461 0.975 0.000 ±0.049 1.4507 0.736 0.000 ±0.126

Full fat 50 °C 0.5360 0.9909 0.000 ±0.046 0.3382 0.982 0.000 ±0.040 1.0783 0.989 0.000 ±0.102

Skimmed Cycle 1 0.0830 0.889 0.061 ±0.093 0.0041 0.111 0.666 ±0.035 0.0156 0.736 0.142 ±0.028

Full fat Cycle 1 0.0189 0.278 0.472 ±0.090 0.0189 0.898 0.666 ±0.035 0.0071 0.373 0.389 ±0.028

Skimmed Cycle 2 0.1720 0.956 0.003 ±0.068 0.0363 0.798 0.040 ±0.033 0.1646 0.987 0.0006 ±0.034

Full fat Cycle 2 0.0948 0.979 0.001 ±0.025 0.0539 0.924 0.009 ±0.028 0.1350 0.987 0.0007 ±0.030

Skimmed Cycle 3 0.4640 0.981 0.087 ±0.811 0.2325 0.996 0.039 ±0.018 0.7593 0.999 0.016 ±0.247

Full fat Cycle 3 0.3890 0.986 0.071 ±0.589 0.2415 0.987 0.071 ±0.346 0.5306 0.981 0.088 ±0.944

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Storage temperature (oC)

0 10 20 30 40 50 60

k (

b*/

week)

0,0

0,2

0,4

0,6

0,8

1,0

1,2

1,4

1,6

Skimmed milk

Full fat milk

c)


0 10 20 30 40 50 60

k (

L*

/ w

ee

k)

0,0

0,1

0,2

0,3

0,4

0,5

0,6

0,7

0,8

0,9

Skimmed milk

Full fat milk

a)


0 10 20 30 40 50 60

k (

a*

/ w

ee

k)

0,0

0,1

0,2

0,3

0,4

Skimmed milk

Full fat milk

b)

On this basis the lightness was found to decrease 1.2 and 4 times when exposed to storage

temperatures of 30 °C and 40 °C respectively, compared to at 20 °C. The b* value is often used as

an indicator of browning in investigations of the MR (Al-Saadi and Deeth, 2015). At the ambient

temperature of 20 °C no significant changes in the b* value were detected. After the period of

24 weeks the b* value increased 1.6 and 4.3 times when exposed to 30 °C and 40 °C respectively,

compared to at 20 °C. At the end of the study, the L* value was significantly changed when

exposed to temperatures of 30 °C compared to 20 °C (p=0.04), whereas a* and b* values were

significantly changed when exposed to 40 °C compared to 20 °C, with p-values of 0.012 and 0.001

respectively. The rate constants (table 5) were increasing with temperature, as illustrated in

Figure 28. This increase was observed for both skimmed and full fat milk, though with a smaller

increase of the rate for full fat in L* and b * (Figure 28a and Figure 28c).

Figure 28 – Rate constants (k) from development in colour space components a) L*, b) a* and c) b* as a function of storage temperature (10 °C to 50 °C) in skimmed and full fat UHT milk.

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1/T (10-3

* K-1

)

0,0030 0,0031 0,0032 0,0033 0,0034 0,0035 0,0036

ln k

(k in

s-1

)

-10

-8

-6

-4

-2

0

2

L*

a*

b*

a)

1/T (10-3

*K-1

)

0,0030 0,0031 0,0032 0,0033 0,0034 0,0035 0,0036

ln k

(k in

s-1

)

-7

-6

-5

-4

-3

-2

-1

0

1

L*

a*

b*

b)

The Q10 value for L* within the interval of 30 °C to 50 °C was between 3.0 and 3.6, for both

skimmed and full fat UHT milk, whereas Q10 values for a* and b* within the interval of 30 °C to

50 °C were between 2.8 and 6. The dependence of temperature on the rate constant has been plotted

in an Arrhenius plot as shown in Figure 29. From the Arrhenius plots it is noticeable that the rate

constants for milk stored at 10 °C (furthest to the right in Figure 29a and Figure 29b) seems to

follow another pattern than milk stored at higher temperatures. Hence only data from 20 °C to 50 °C

are included in the regression lines. A linear correlation of an Arrhenius plot indicates that the rate

increases with the same factor over a temperature range. R2 for L*, a* and b* for skimmed UHT

milk were 0.971, 0.928 and 0.910 respectively and for full fat UHT milk 0.997, 0.988 and 0.972.

5.1.5 Protein composition

The protein composition of UHT milk stored at different temperatures was investigated using RP-

HPLC. Chromatographic profiles of skimmed UHT milk are presented in Figure 30. The

chromatogram represents profiles of UHT milk stored at 10 °C for 8 weeks (blue), 40 °C for

2 weeks (black), 40 °C for 6 weeks (red) and 40 °C for 10 weeks (green). The composition of

bovine milk proteins have in previous studies been analysed with RP-HPLC (Bonfatti et al., 2008;

Jansson, 2014a; Al-Saadi and Deeth, 2015), with chromatograms following the same pattern as

shown in Figure 30. The following elution order were documented in these studies; κ-CN, αS2-CN,

αS1-CN, β-CN, α-La and β-Lg. Based on these findings the six fractions noticeable in the

Figure 29 – Effect of storage temperature on the rate constants (k) for development in the colour space components; L*, a* and b*, in a) skimmed and b) full fat UHT milk. Linear regressions include data from 20 °C to 50 °C.

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chromatogram of milk stored at 10 °C for 8 weeks were identified. Only small differences were

observed between the chromatograms corresponding to milk stored at 10 °C for 8 weeks (blue) and

40 °C for 2 weeks (black). More evident changes of the chromatograms were observed in milk

stored at 40 °C for 6 weeks (red) and 40 °C for 10 weeks (green). These changes were seen as

broader peaks and in some cases overlapping. It was considered to analyze protein lactosylations on

basis of mass spectral data, which can be determined by a mass shift of +324 Da. The high degree

of modifications made this approach difficult due the overlapping peaks. Therefore it was decided

not to do further analyses on protein composition. From the chromatographic profiles presented in

Figure 30 it is shown that particularly the fractions of κ-CN and αS1-CN are modified with time and

temperature. These findings from analysis of protein composition indicate extensive changes in the

proteins during storage of UHT milk at elevated storage temperatures.

Figure 30 – Protein composition in selected milk samples (Blue: 10 °C week 8, black: 40 °C week 2, red: 40 °C week 6, green: 40 °C week 10).

5.2 Physical changes

To investigate acceleration of physical destabilization processes in full fat and skimmed UHT milk,

different analytical techniques have been applied. Creaming of fat and sedimentation of proteins

have been the major focus in this part of the study and will be evaluated with use of optical stability

analyzers, particle size measurement and evaluation of protein and fat content in three fractions;

top, middle and bottom.

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5.2.1 Physical destabilization

Optical centrifugation was applied for the investigation of creaming of fat and sedimentation of

proteinaceous material. The optical stability analyzer, Lumifuge, accelerates physical

destabilization by centrifugal forces and measures transmission of light in the full length of the

sample cell (Ng et al., 2013). The transmission profiles correspond to the measured transmission

in % as a function of the local position on the centrifuge tube in mm. From the transmission profiles

an instability index has been calculated based on equation 9. This index is within the range 0 to 1,

depending on the instability of the dispersion.

Figure 31 reveals the instability index based on transmission measured in a) skimmed and b) full fat

UHT milk during storage at the temperatures; 10 °C, 20 °C, 30 °C, 40 °C and 50 °C including the

three temperature cycles. Data are based on mean values from biological and analytical duplicates.

Figure 31a illustrates instability of skimmed milk over time reflecting sedimentation, and Figure

31b illustrates instability of full fat milk over time reflecting creaming. Differences of instability

index over time are statistically significant (p<0.05) for all skimmed milk and full fat milk, except

from cycle 1 for full fat (p=0.27). The instability of skimmed milk seems mainly to increase within

the first 10 weeks of storage. An instability index of 0.57 was observed in skimmed UHT milk

stored at 20 °C for 24 weeks, corresponding to instabilities at 30 °C for 8 weeks and 40 °C for 2

weeks approximately.


0 5 10 15 20 25

Insta

bili

ty in

de

x

0,00

0,50

0,52

0,54

0,56

0,58

0,60

0,62

a)


0 5 10 15 20 25

Insta

bili

ty ind

ex

0,00

0,03

0,04

0,05

0,06

10 oC

20 oC

30 oC

40 oC

50 oC

Cycle 1

Cycle 2

Cycle 3

b)

Figure 31 – Instability index in a) skimmed UHT milk and b) full fat UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles. Error bars indicate standard deviation, n=4.

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Light scattering has also been applied with use of Turbiscan. This optical stability analyzer uses a

near infrared light source and two detectors; a transmission and a backscattering detector. The

backscattering technique enables analysis of opaque dispersions like full fat milk (Mengual et al.,

1999). The acceleration of physical destabilization was based on exposure to elevated temperatures

and temperature cycles. Milk was stored in sterilized sample cells for the period of 24 weeks.

Backscattering profiles correspond to the measured backscattering in % as a function of the local

position on the sample cell in mm (Appendix 2).

Figure 32 depicts backscattering measured during storage of skimmed and full fat UHT milk.

Figure 32a depicts the creaming in full fat milk, Figure 32b clarification of middle fraction in full

fat milk, Figure 32c sedimentation in skimmed milk and Figure 32d clarification of middle fraction

in skimmed milk. Data included are mean values of biological and analytical duplicates. The

definition of creaming, sedimentation and clarification of the middle fraction are described in

section 4.3.1.

The major changes in creaming (Figure 32a) and sedimentation (Figure 32c) were observed within

the first 10 weeks of storage. After 24 weeks of storage the variation in backscattering was higher

for sedimentation than for creaming. After the same period at 20 °C, backscattering from the

creaming layer was 85.5 %, corresponding approximately to the backscattering at 40 °C after 6

weeks. Sedimentation in skimmed UHT milk stored at 20 °C for 24 weeks were observed with a

backscattering of 61 %, corresponding to the backscattering at 40 °C after 12 weeks approximately.

Clarification of the middle fraction was proceeding slightly faster in full fat milk (Figure 32b)

compared to skimmed milk (Figure 32d). After 24 weeks at 20 °C backscattering of the middle

fraction was observed to correspond to backscattering after 12 weeks at 40 °C in full fat milk and

after 14 weeks at 40 °C in skimmed milk.

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0 5 10 15 20 25

Backscatt

ering (

%)

0

36

39

42

45

48

51

54

10 oC

20 oC

30 oC

40 oC

Cycle 1

Cycle 2

Cycle 3

d)


0 5 10 15 20 25

Ba

cksca

tte

rin

g (

%)

0

50

52

54

56

58

60

62

64 c)


0 5 10 15 20 25

Ba

cksca

tte

rin

g (

%)

0

70

72

74

76

78

80

82

84

86

88

90 a)


0 5 10 15 20 25

Ba

cksca

tte

rin

g (

%)

0

48

50

52

54

56

58

60

62

64

66

68

70

72

74

10 oC

20 oC

30 oC

40 oC

Cycle 1

Cycle 2

Cycle 3

b)

Figure 32 – Backscattering reflecting a) creaming in full fat UHT milk, b) clarification in full fat UHT milk (25 mm from the bottom), c) sedimentation in skimmed UHT milk, d) clarification in skimmed UHT milk (25 mm from the bottom). During storage at 10 °C, 20 °C, 30 °C and 40 °C, including temperature cycles. Error bars indicate standard deviation, n=4.

5.2.2 Protein and fat content

Protein and fat content were investigated in three fractions; top, middle and bottom, analysed by

Milkoscan FT1 (Foss, Denmark). Figure 33 depicts the fat content in top (Figure 33 a), middle

(Figure 33 b) and bottom (Figure 33 c), during storage at different temperatures. Figure 34 depicts

the protein content in the three fractions; top (Figure 34 a), middle (Figure 34 b) and bottom

(Figure 34 c), during storage at different temperatures. Values included are based on means from

biological and analytical duplicates. The top layer was not measured using Milkoscan, since the

high fat content of the creaming layer can be harmful to the equipment. Instead the top fraction is

calculated based on the content of the bottom and middle fractions.

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0 2 4 6 8 10 12 14 16 18 20 22 24 26

%

0

1

2

3

4

5

6

7

8

%

0

1

2

3

4

5

6

7

8

a)

%

0

1

2

3

4

5

6

7

8

b)

c)

a)

%

0,0

2,6

2,8

3,0

3,2

3,4

3,6

3,8

b)

%

0,0

2,6

2,8

3,0

3,2

3,4

3,6

3,8

c)


0 2 4 6 8 10 12 14 16 18 20 22 24 26

%

0,0

2,6

2,8

3,0

3,2

3,4

3,6

3,8

10 oC

20 oC

30 oC

40 oC

50 oC

Cycle 1

Cycle 2

Cycle 3

All changes in fat content over the time period were significant (p<0.05), whereas only the protein

content at 40 °C in top and bottom were significantly changing over time. Creaming of fat in the top

fraction was observed to proceed approximately twice as fast when stored at 40 °C compared to at

20 °C (Figure 33a). Similarly, the sedimentation process of proteins was proceeding approximately

twice as fast when stored at 40 °C compared to at 20 °C (Figure 34c). Temperature cycle 1,

Figure 33 – Fat content (%) in full fat UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles, in a) top, b) middle and c) bottom fractions. Error bars indicate standard deviation, n=4.

Figure 34 – Protein content (%) in full fat UHT milk during storage at temperatures between 10 °C and 50 °C, including temperature cycles, in a) top, b) middle and c) bottom fractions. Error bars indicate standard deviation, n=4.

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0 5 10 15 20 25

Dv (

10

)

0,42

0,43

0,44

0,45

0,46

0,47

0,48

a)


0 5 10 15 20 25

Dv (

50)

0,60

0,62

0,64

0,66

0,68

0,70

b)


0 5 10 15 20 25

Dv (

90

)

0,90

0,95

1,00

1,05

1,10

1,15

c)

fluctuating between 10 °C and 30 °C, was found to follow the same pattern as 20 °C for both fat and

protein distribution. The same was observed for cycle 2 following the same pattern as at 30 °C and

cycle 3 following the same pattern as at 40 °C.

5.2.3 Fat globule size distribution

The fat globule size distribution was analysed with use of static light scattering. Both skimmed and

full fat UHT milk were analysed during storage at different temperatures. The samples were

dissolved in a buffer consisting of urea and citrate, to avoid protein attached to the globules.

Figure 35 depicts the fat globule size distribution of Dv10 (Figure 35a), Dv50 (Figure 35b) and

Dv90 (Figure 35c). Included in these plots are UHT milk samples from all storage temperatures.

Only slight changes with time and temperature were observed, but all changes were insignificant

(p>0.05). To illustrate this insignificance; p-values of 0.946 and 0.999 were observed for Dv50 in

full fat and skimmed milk respectively, stored at 50 °C.

Figure 35 – Fat globule size distribution of a) Dv10, b) Dv50 and c) Dv90 over the storage period. Included are full fat UHT milk samples from storage at all temperatures; 10 °C, 20 °C, 30 °C, 40 °C and 50 °C, including temperature cycle 1, 2 and 3. Straight line indicates the average and dotted lines indicate standard deviation for all data.

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5.3 Principal component analysis

Multivariate data analysis in the form of principal component analysis (PCA) was applied to

provide a holistic characterization of all data obtained. Included in Figure 36 are all quantified

parameters from the chemical analyses as well as parameters of protein and fat distribution and

instability index. The loading scatter plot illustrates grouping of the data analysed. The upper left

part characterized by increasing chemical parameters, the bottom left part characterized by

increasing physical parameters, the bottom right part characterized by decreasing chemical

parameters and the upper right part characterized by decreasing physical parameters. These finding

indicate that even though the same overall pattern is documented for chemical and physical

parameters, they do not seem to be markedly correlated. In addition instability index and protein

content in middle fraction do not seem to correlate with findings from other analyses.

Figure 36 – Loading scatter plot from PCA, including all parameters from chemical analyses as well as parameters of protein and fat distribution and instability index. Bottom pr = protein content in bottom fraction, Bottom fa = fat content in bottom fraction, Middle pr = protein content in middle fraction, Middle fa = fat content in middle fraction, Top prote = protein content in top fraction, Top fat = fat content in top fraction, instability = instability index.

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6. Discussion

In this study, commercial skimmed and full fat UHT milk were exposed to five different storage

temperatures and three temperature cycles, to investigate chemical and physical changes over time.

This included analysis of the three phases of the Maillard reaction as well as the lipid oxidation. An

evaluation of physical destabilization was conducted with focus on the gravitational separation, in

form of creaming and sedimentation. Additionally, a peptide analysis was included to investigate

enzyme activity, which may affect chemical and physical changes. Finally, kinetic parameters and

trends of formation were obtained for discussion and prediction of shelf life, with the aim of

establishing a valid setup to accelerate shelf life development.

6.1 Chemical changes

A peptide analysis of pH 4.6 soluble peptides has been conducted, since peptides formed from

enzymatic hydrolysis will increase the amount of free amino groups in the milk. This will enhance

the MR, and contribute to physical destabilization mainly in the form of gelation. The peptide

analysis based on HPLC, resulted in total peak areas of 0.57 *105 (AU) at weeks 0 and 0.94 *10

5 at

week 24 for skimmed UHT milk stored at 30 °C. The increases in total peak area seemed mainly to

be caused by modifications of peptides formed prior to heat treatment. No noticeable increases were

observed in fractions eluted between approximately 10 and 20 min. These fractions have previously

been identified to small peptides formed in presence of hydrolytic enzymes (Rauh, 2014a). The

observations illustrate that no remarkable enzyme activity is present in the indirect UHT milk

applied. Hence enzyme activity is not expected to influence the following results. These findings

are consistent with previous studies comparing direct and indirect UHT milk (Datta et al., 2002).

Commonly a higher enzyme activity is found in direct UHT milk, due to the reduced heat load

applied for processing of direct UHT milk compared to indirect UHT milk (Lewis and Deeth, 2008;

Datta et al., 2002).

The initial stage of the MR is of major importance to nutritional quality, since lactosylation of

proteins result in less available lysine for metabolic processes. On this background the Amadori

product is often used as indicator for the reduction of nutritional value, and is of importance in an

accelerated shelf life study (Metha and Deeth, 2015). Direct quantification of the Amadori products

is possible with LC-MS after enzymatic hydrolysis of the lactosylated proteins. This is, however, a

difficult and time-consuming analysis (Henle et al., 1991). An alternative approach is an indirect

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quantification of the Amadori product. Two commonly applied methods for this indirect

quantification is to measure furosine or hydroxymethylfurfural (HMF). Formation of HMF is

induced by boiling in oxalic acid, while furosine formation is induced by acid hydrolysis. Both

methods have the disadvantage that the conversion from Amadori product is incomplete (Van

Boekel, 2001). Approximately 30-40 % of the Amadori product is converted into furosine and only

10 % is converted into HMF (Van Boekel, 1998). In contrast to furosine, HMF is naturally formed

in the MR, which can be a challenge since the difference between free HMF (formed in the MR)

and total HMF (formed by oxalic acid) is minor (Van Boekel, 1998).

Based on these considerations, the initial MRP was indirectly measured by a quantification of

furosine using RP-HPLC-DAD. The HPLC chromatogram depicted on Figure 16 shows that other

compounds elute in the same time range as furosine. These compounds are probably also

derivatives from the Amadori product, but since furosine has shown to provide a good estimation of

the early stage of the MR in previous studies, furosine was chosen for the present study (Guerra-

Hernandez et al., 2002). The analysis of furosine illustrated that formation of the initial MRP is

highly temperature dependent. During 24 weeks of storage, the formation was significantly

increasing in both skimmed and full fat UHT milk stored at 20 °C and above. This demonstrates a

continuous formation of lactulosyllysine. In samples stored between 10 °C and 30 °C the furosine

formation seemed to follow a linear trend, but in samples stored between 40 °C and 50 °C the

formation of furosine became non-linear, and was more likely to fit into a first order reaction. On

basis of this, all samples have been fitted into a first order reaction kinetic, common for product

formation (5). This pattern can possibly be due to substrate depletion or because the initial MRP is

used in the intermediate MR´s, with formation of volatile products like Strecker aldehydes. The

latter is most likely to be the reason, since the amino groups are partly recycled in the intermediate

stage of the MR. In addition, previous studies have documented that lactose in milk is not a limiting

factor to the MR (Jansson, 2014a). A similar formation of furosine, with storage time and

temperature, has been observed by Nangpal and Reuters (1990). In this study full fat direct UHT

milk was exposed to 20 °C, 30 °C and 50 °C over a period of 19 weeks. During storage, milk stored

at 20 °C and 30 °C followed a linear trend, whereas at 50 °C the curve leveled off. A decline of

furosine after overheating or during prolonged storage has also been described in literature (Metha

and Deeth, 2016).

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The effect of storage temperature on the reaction rate of furosine has been evaluated with use of the

Arrhenius equation. From this plot a linear correlation was observed between changes in rate

constants and storage temperature. This correlation fitted into linear regressions with R2 of 0.993

and 0.989, for skimmed and full fat milk respectively. A linear correlation indicates a constant

increase in reaction rate with temperature. This was supported by the Q10 values, which were in the

range of 1.5 and 2.3. The temperature dependence of the reaction rate is consistent with previous

studies, which have documented Q10 values of approximately 2 (Labuza et al., 1994). The activation

energies based on the Arrhenius plot were found to be 51 kJ/mol and 46.7 kJ/mol for skimmed and

full fat milk respectively. Activaltion enegies of furosine formation in UHT milk are not well

documented in literature. After 24 weeks, the formation of furosine was observed to be accelerated

3 and 8 times when exposed to 30 °C and 40 °C respectively, compared to at ambient temperatures

(20 °C). This indicates that it is possible to accelerate initial MR´s, and predict shelf life based on

furosine concentrations.

In the intermediate stage of the MR several reactive AGE products are formed, of which most are

able to absorb and emit light (Lakowicz, 1999). In this study, an unspecific detection of

intermediate and late MRP´s has been conducted by measurement of fluorescence changes. A

significant increase in fluorescence intensities over the storage period was observed in samples

stored between 30 °C and 50 °C (p<0.05), meaning that no significant changes were observed at

ambient temperatures. Thus, it can be considered whether these compounds contribute to limitations

of shelf life at ambient temperatures after 6-9 months, which is the reported shelf life of commercial

UHT products. And hence, if they are appropriate to accelerate in a shelf life study.

The formation of fluorescent compounds seemed overall to follow a linear correlation with time,

reflecting that this relation can be described by a zero order reaction kinetic. However a short lag

phase was observed in milk stored at 50 °C and cycle 3 during the first weeks of storage. This

indicates that the formation of these compounds is probably more complex. The insignificant

changes at 10 °C and 20 °C, and the lag phase at higher temperatures may indicate that a formation

of precursors is required before fluorescent compounds can be formed. This tendency fits well into

the pattern observed for the formation of furosine. Furosine increased according to a first order

reaction kinetic, with a steep linear increase followed by a flattening when exposed to higher

storage temperatures. This pattern illustrates a conversion of lactulosyllysine into intermediate

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MRP´s. Similar trends have previously been observed, supporting this theory (Birolouez-Aragon et

al. 1998).

The rate constants depicted in table 2 indicates a high temperature dependency of these intermediate

MR´s. This temperature dependence has been evaluated with an Arrhenius plot illustrating a

correlation between the rate and the storage temperature from 20 °C to 50 °C. At 10 °C it seems that

the rate is almost constant, whereas increasing from 20 °C to 50 °C. This observation could possibly

be due to other reactions proceeding at 10 °C and below. If this is the case, these reactions are using

the fluorescent compounds as substrate or are inhibiting their formation. It is important to note that

the Arrhenius plot includes several elementary reactions, with individual activation energies and

temperature sensitivities. Therefore a more likely explanation to this observation may be that some

of the reactions included at 20 °C and above, require energies above what is available at 10 °C.

Hence these reactions are very slow or absent at 10 °C. Under these cooled conditions it may also

be possible that the concentration of the Amadori product is too low for the intermediate stage to

proceed. The Q10 values calculated between 10 °C and 20 °C were 1.3, whereas values from 20 °C

to 50 °C were 10.9, 6.8 and 3.9 for each 10 °C rise. Based on this, data from milk stored at 10 °C is

not included in the linear regressions from the Arrhenius plot, with R2 of 0.992 for skimmed milk

and 0.986 for full fat milk. Hence the Q10 values vary between 3.9 and 10.9, which is more than

what is previously reported for intermediate MRP´s varying from 4 to 6 approximately (Labuza et

al. 1994). From the slope of an Arrhenius plot it is possible to calculate the activation energy of a

reaction. Activation energies give information about the temperature sensitivity, but in this case the

Arrhenius plot represents various reactions with different temperature sensitivities. Thus, it can be

hard to draw conclusions about activation energies in this case. It is also important to note that the

fluorescent compounds detected can possibly also originate from other reactions e.g. sugar

fragmentations (Morales and Jiménez-Pérez, 1999). Since the detection of fluorescent MRP´s is

unspecific, it does not give information about the composition of compounds included. The

composition of fluorescent compounds may differ between milk types and reflect different sensory

thresholds and different off-flavors, such as cooked, heated or stale flavors. This may be a problem

in order to predict shelf life of newly developed products, with other sensory threshold and hence

other upper limits of the markers. This method has been considered less sensitive for a global

approach compared to detection of specific compounds (Birlouez-Aragon et al., 2001). In this study

specific intermediate MRP´s have been relatively quantified with use of SPME-GC-MS.

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Flavour and aroma changes are major contributors to product deterioration, and hence to limitations

of consumer acceptance. In order to predict shelf life with respect to sensory quality, it is hence

important to select markers with a low sensory threshold. Several studies have investigated specific

volatile components responsible for flavor changes in milk, using GC-MS coupled to different

extraction techniques (Contarini and Polovo, 2002; Vazquez-Landaverde et al., 2005; Marsili,

1999). Two of the most commonly applied extraction techniques for this approach are DHS and

SPME, which particularly have been compared by Contarini and Polovo (2002), Marsili (1999) and

Elmore et al. (1994). Both techniques are non-solvent extraction techniques analyzing the

headspace composition. It seems that both methods are sensitive and reproducible, but their

specificity for volatiles differs. Marsili (1999) investigated volatile lipid oxidation products, and

found that the SPME extraction detected the compounds with higher precision than DHS. In this

study lower variation between replicates and higher linearity of calibration curves were found. In

addition SPME is a rapid and less expensive technique compared to DHS. In another comparative

study Elmore et al. (1997) documented a higher sensitivity of DHS, especially for trace analysis.

This extraction technique provided a higher quantity and number of different volatile compounds

detected by DHS-GC-MS, mainly due to a larger surface area of the adsorbent trap (Barrious et al.,

2013; Jansson, 2014a). Moreover, no equilibrium is required with DHS sampling instead a

continuous flow of carrier gas is purged through and above the sample. This can possibly enhance

the efficiency of the extraction. With SPME two equilibriums are reached; first an equilibrium

between the sample and the head space, and secondly an equilibrium between the head space and

the contact fibre (Barrious et al., 2013). Due to the lower specificity of SPME when used for trace

analysis it can be necessary to quantify in SIM mode.

On basis of the previous studies comparing SPME and DHS, it was considered preferable to use

DHS for detection of intermediate MRP´s, but due to technical problems this was not possible.

Instead a single determination using SPME-GC-MS was applied. Markers for MR and lipid

oxidation were chosen. These were; furfural, 2-furanmethanol, 2-ethylfuran, 2-heptanone, 2-

nonanoneand 2-undecanone. The formation of furfural can proceed in two possible ways. Furfural

can originate from the intermediate stage of the MR, through the pH dependent breakdown of the

Amadori product. This includes an enolization reaction under acidic conditions, followed by a

dehydrogenation of 3-deoxyosone. Secondly furfural can be formed from lactose isomerization by

the so called Lobry de Bruyn-van Ekenstein transformation (LA-transformation) followed by

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degradations (Ferrer et al., 2002). 2-furanmethanol, also referred to as furfurylalcohol, is only

slightly investigated in previous studies. This compound can, like furfural, be a product from the 3-

deoxyosone pathway or from sugar degradation (Van Boekel, 1998). 2-furanmethanol consists of a

furan with a hydroxymethyl group attached, which is hence the reduced form of furfural, consisting

of a furan with an aldehyde group. Furfural has previously shown to be a precursor for other furan

derivatives (Jansson et al., 2014c). Hence it is possible that 2-furanmethanol is formed from furfural

or maybe more likely that furfural is formed from 2-furanmethanol by an oxidation. The formation

of 2-furanmethanol was observed to go through a lag phase during the first weeks of storage,

followed by a steep increase (Figure 24). The low initial rate may indicate that a formation of

precursors is needed before 2-furanmethanol can be formed. This pattern of formation is typical for

an intermediate product, which supports the theory of a formation by the MR. On the other hand,

the formation of furfural and 2-furanmethanol is not likely to be derived from the 3-deoxyosone

pathway, since this reaction proceeds under acidic conditions. In the beginning of the study the

UHT milk had a pH of 6.7, which decreased only slightly during storage. Moreover, the 3-

deoxyosone pathway has been found only to proceed in presence of pentose sugars (Van Boekel,

2006). Since the major carbohydrate in milk is the hexose sugar lactose, it is not likely that the

furfural and 2-furanmethanol detected in milk originates from the MR. In respect to the

predominant carbohydrate of milk; lactose degradation seems to be the most likely reason to the

observed formation of these compounds. In the present study furfural was only detected in milk

stored at 40 °C and 50 °C, and 2-furanmethanol in milk stored at 30 °C, 40 °C and 50 °C. The

absence of these compounds at storage temperatures below 30 °C may again indicate a formation

through sugar degradations, which proceeds at higher temperatures than the MR. The relative

concentrations of the two compounds were increasing significantly with time and temperature at

40 °C and 50 °C. For both compounds an elevation of the storage temperature from 40 °C to 50 °C

seemed to speed up the processes approximately 4 times. Another furfural compound often used as

marker is hydroxymethylfurfural (HMF). This compound is also formed in the 3-deoxyosone

pathway, but in presence of hexose sugars. It is therefore observed naturally in milk (Van Boekel,

1998), though this compound was not detected in the present study. A possible explanation is that

HMF is too polar to be extracted by the SPME fibre.

In addition to furfural and 2-furanmethanol, the furan compound 2-ethylfuran was detected by GC-

MS. 2-ethylfuran consists of a furan with an ethyl group attached and can possibly be formed in

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three ways (Vranová and Ciesarová, 2009; Jansson et al., 2014c). 2-ethylfuran has been found to

originate from the Strecker degradation products acetaldehyde (from alanine) and lactaldehyde

(from threonine). Secondly it can be formed from degradation of carbohydrates and finally from

lipid oxidation (Limacher et al., 2008; Jansson, 2014a; Vranová and Ciesarová, 2009). The latter

way of formation is in literature mainly documented for the parent furan (Vranová and Ciesarová,

2009). The relative intensities of 2-ethylfuran were significantly correlated with the storage time

(p<0.05) in UHT milk stored between 30 °C and 50 °C. After 24 weeks of storage the 2-ethylfuran

content was approximately 3.8 times higher in milk stored at 30 °C than in milk stored at the

ambient temperature of 20 °C, and approximately 7.2 times higher in milk stored at 40 °C than in

milk stored at 20 °C. Jansson et al. (2014c) has investigated the formation of 2-ethylfuran in

conventional and lactose-hydrolysed UHT milk. In this study a significantly higher formation was

observed in conventional compared to lactose hydrolysed milk, indicating that the formation of 2-

ethylfuran is favored in presence of lactose and not glucose and galactose. For most MRP´s the

opposite trend is observed, which can be an explanation for the high concentration of this

compound in the present study. In milk it would have been expected mainly to detect MRP´s from

the 2,3-enolisation pathway, which is favored at neutral pH (Nursten, 2005; Martins et al., 2001).

The absence of these products is considered to be explained by the SPME extraction of the GC-MS

system.

The three following methyl ketones were chosen as markers for lipid oxidation; 2-heptanone, 2-

nonanone and 2-undecanone. Ketones are mainly formed in a heat-induced decarboxylation of β-

oxidized saturated fatty acids, primarily by thermal degradation. Therefore the formation of these

compounds is highly temperature dependent (Jansson et al., 2014c; Vazquez-Landaverde et al.,

2005). The relative formation of these ketones was significantly increasing with storage time when

exposed to storage temperatures of 30 °C and above (p<0.05), as shown in table 3. They were

observed to follow the same pattern as 2-ethylfuran, consistent with findings by Jansson (2014a).

The relative formation was linearly correlated with storage time and all with R2 values above 0.86.

The rate constants observed were in addition increasing with the storage temperatures. This

temperature dependence has previously been documented by Contarini and Povolo (2002) and

Vazquez-Landaverde et al. (2005). They both observed that the amount of these compounds

correlated with the severity of the heat treatment. These three ketones were the most abundant

secondary oxidation products found in the present study. This was also in agreement with the study

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of Vazquez-Landaverde et al. (2005) who observed that 2-heptanone and 2-nonanone were the most

abundant ketones, and concluded that these were major contributors to the flavour changes in heat

treated milk. The temperature dependence has further been investigated with use of the Arrhenius

equation. From the Arrhenius plot (Figure 26) a linear relation between rate constants for 2-

ethylfuran and storage temperatures was observed within two temperature ranges; 10-30 °C and 30-

50 °C. The same tendency was observed for the lipid oxidation products. At storage temperatures

between 10 °C and 30 °C the reaction rates increased more with temperature than between 30 °C

and 50 °C. These findings were supported by Q10 values corresponding to the changes in rate for

each 10 °C. Between 20 °C and 30 °C, Q10 values of 12.5 and 29 were found for 2-ethylfuran and 2-

undecanone respectively, whereas Q10 values of 2.8 and 3.7 were found for the same compounds

between 40 °C and 50 °C. This results in a breaking point at 30 °C, indicating that something affects

the formation of these ketones at higher temperatures. A possible explanation could be that the

ketones are used in other reactions such as the MR, when exposed to temperatures above 30 °C. The

most evident breaking points were observed for 2-ethylfuran and 2-undecanone, which may indicate

that these are more likely to react with non-lipid compounds, possibly in the MR. Secondary

oxidation products, like aldehydes and ketones, can be included in the MR due to their reactive

carbonyl groups (Zamora and Hidalgo 2005). MRP´s on the other hand may reduce lipid oxidation

by the formation of compounds with antioxidant properties, which include melanoidins (Zamora

and Hidalgo 2005). Thus, the MR and lipid oxidation are dynamic and often correlated cascades of

reactions (O´Brien, 2009; Shahidi and Zhong, 2010).

The final stage of the MR constitutes a formation of brown-colored polymers, referred to as

melanoidins. The formation and the complex structure of melanoidins are still not well

characterized, which makes a quantification of these components difficult (Van Boekel, 1998;

Brands et al., 2002). Due to the browning these components have detrimental effect on the product,

and hence on the shelf life. For optimization and prediction of these processes colour measurements

have mainly been conducted (Nursten, 2005). Two methods are commonly applied for this

approach; absorption measured at 420 nm and a tristimulus measurement with colour parameters

expressed according to the CIELAB system (Van Boekel, 2001).

This part of the study showed that both skimmed and full fat UHT milk were changing in colour,

with a linear trend over the storage period of 24 weeks. This zero order reaction kinetic is consistent

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with findings from previous studies on UHT milk during storage (Gaucher et al,. 2008; Al-Saadi

and Deeth, 2015). The observed linear formation over time may indicate that the precursors are

present in high amounts, relative to the products. The precursors seem therefore not to be a limiting

factor for these reactions, resulting in a constant formation of melanoidins. The formation of these

brown polymers were observed as a significant decrease of lightness (L*) in samples stored

between 20 °C and 50 °C. Moreover, a significant increase of red (a*) and yellow colour (b*) in

samples stored between 30 °C and 50 °C were observed (p<0.05). The two milk types followed the

same pattern, though with different off set, which is assumed mainly to be due to the whitening

effect of fat in full fat milk. In some studies an induction period has been observed, indicating that

precursors need to be formed prior to the melanoidins, though this was not observed in the present

study. In addition browning curves have been observed to level off due to saturation (Van Boekel,

2001; Matiacevich and Buera, 2006). For this to be observed, an extension of the storage period is

required, or possibly a further elevation of storage temperatures. The storage time and temperature

required to observe such a flattening of the curve, will depend on the composition of the specific

system, and can be hard to predict from these observations.

The colour space component b* is often used as indicator for browning in investigations of the MR

(Al-Saadi and Deeth, 2015) and will therefore mainly be referred to in the following. The b* value

was observed to increase significantly with the elevated storage temperatures. Results obtained

from Al-Saadi and Deeth (2015) and Gaucher et al. (2008) are comparable to results obtained in the

present study. Al-Saadi and Deeth measured a b* value of 6 in skimmed UHT milk stored at 45 °C

after 12 weeks. Over the same period, Gaucher et al. observed a b* value of approximately 12 in

semi-skimmed UHT milk stored at 40 °C. In the present study a b* value of approximately 8 were

observed in skimmed UHT milk stored at 40 °C after 12 weeks. These variations are possibly due to

differences in the UHT treatment or differences in the sensitivity of the applied method. The

temperature dependence of the rate constant for the late MR´s was evaluated with Arrhenius plots

(Figure 29a and b) and Q10 values. The Q10 values calculated for a* and b* within the interval of

30 °C to 50 °C were between 2.8 and 6. Q10 values within the same range are previously found in

studies investigating the late MR´s. According to Nursten (2005) Q10 values corresponding to these

reactions are mainly between 3 and 6.

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The temperature cycles for all three stages of the MR, followed the same pattern of formation. All

temperature cycles with values above those of their average temperature. This indicates that once

the MR is started, it continues at a considerable rate, even when exposed to lower storage

temperatures. In this study only a slight delay in the rate was observed for all three stages of the

MR.

The increase of the MR with storage time and temperature, were supported by an analysis of the

protein composition using HPLC. From the chromatographic profiles it is shown that particularly

the fractions of κ-CN and αS1-CN were modified with time and temperature (Figure 30). This

analysis indicates extensive changes in the milk proteins during storage at different temperatures.

The changes observed in the chromatographic profiles are due to alterations in hydrophobicity of

the proteins. This can possibly be caused by lactosylations, dephosphorylations, deamidations and

polymerizations (Al-Saadi and Deeth, 2015). These results were in agreement with previous

investigations on protein composition of UHT milk at different temperatures. Gaucher et al. (2008)

observed the same tendency in semi-skimmed indirect UHT milk and Al-Saadi and Deeth (2015) on

skimmed indirect UHT milk.

Several parameters affect the pH of milk during storage. In the present study, pH decreased

significantly with time in both skimmed and full fat UHT milk, though changes in milk stored at

10 °C were minimal. The pH of skimmed milk was from the beginning of the study 6.7 and

decreased to 6.67, 6.62, 6.58, and 6.36 when stored at 10 °C, 20 °C, 30 °C and 40 °C for 24 weeks

respectively. These changes can be attributable to various processes occurring during storage. A

major reason to the decreased pH is the high degree of MR observed in the study, especially with

formation of formic acid in the intermediate stage. In addition, degradation of lactose may lead to

formation of organic acids, such as formic and acetic acid (Limacher et al., 2008; Walstra et al.,

2006). Moreover, changes in the salt-equilibria will affect pH. Casein micelles can undergo

dephosphorylation (Al-Saadi and Deeth, 2008) and association of dissolved calcium and phosphate

to the casein micelle will result in a release of protons, which decreases pH (Van Boekel, 1998;

Walstra et al., 2006). It is of major importance to be aware of these pH changes when conducting a

shelf life study. The changes in pH may affect reactions of interest. A decrease in pH may possibly

enhance formation of intermediate products from the 3-deoxyosone pathway. In the present study

the pH decrease was only slight, and was therefore not considered to have a significant effect on the

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observed formation of furfural and 2-furanmethanol. On the other hand, the early MR is enhanced

by increases in pH. This can be explained by deprotonation of the amino groups, resulting in more

nucleophile and reactive amino groups. Additionally, the open-chain form of lactose is favored with

increases in pH. In this study it may be considered that the formation of furosine would have been

higher if the pH was unaffected. This could possibly also contribute to the flattening of the curve

observed for furosine formation, though it is more likely that furosine are used in the intermediate

stage of the MR.

6.2 Physical changes

Different analytical techniques have been applied for the investigation of physical changes during

storage at different temperatures. In this study, an evaluation of physical destabilization was

conducted with use of optical centrifugation, light scattering, particle size measurement as well as

analysis of protein and fat content in three fractions; top, middle and bottom. It was chosen mainly

to analyze sedimentation in skimmed milk and creaming in full fat milk, since it is here the

processes are most pronounced.

From analysis with Lumifuge, an instability index was calculated. A very low instability index was

found for full fat milk relative to skimmed milk. This is possibly due to a very low transmission

through full fat milk, reflected by its opaqueness. The turbidity difference between skimmed and

full fat milk seems to influence the measured transmission, and has hence an impact on the

differences observed. Thus, stability analysis based on transmission does not seem to be suitable for

concentrated and opaque dispersions. On the other hand, backscattering measurements conducted

with Turbiscan seemed to be less affected by the turbidity difference of the two milk types.

Changes in instability index were most pronounced within the first 10 weeks of storage. This

observation was consistent with what was observed for creaming and sedimentation analysed with

Turbiscan and Milkoscan. A possible explanation to this is that a fast creaming and sedimentation

of the largest fat globules and proteins, is proceeding in the start of the storage period. Supported by

Stokes equation, which reveals that particle size is positive correlated with particle migration

velocity. Since the major changes of physical stability take place within the first 10 weeks at all

storage temperatures, it may be considered that these parameters are not the most appropriate for an

accelerated shelf life study. After the storage period of 24 weeks the variation in backscattering

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(measured with Turbiscan) was higher for sedimentation than for creaming. This observation could

indicate that the creaming process has reached a maximum before the sedimentation process.

Fat and protein content was analysed in three fractions; top, middle and bottom, using Milkoscan.

This analysis provided information about the content of fat, going to the top fraction by creaming,

and the content of protein sinking to the bottom by sedimentation. Here it is important to note that a

creaming layer can include proteins attached to fat and a sediment can include fat attached to

proteins. These conditions may result in a confounding estimate of creaming and sedimentation,

when analysed with Milkoscan, since the amount of creaming is based on the fat content of the top

fraction alone. Though, it has previously been observed that relatively little protein is included in

the creaming layer of UHT milk (Nieuwenhuijse and Van Boekel, 2003). The fat content in the top

fraction increased significantly, whereas the middle and bottom fractions decreased. The protein

content decreased in the top fraction, increased in the bottom fraction and remained stable in the

middle fraction. Similar distribution of fat and protein in the top, middle and bottom fractions were

observed by Lu et al. (2013), who investigated the effect of homogenization pressure on physico-

chemical changes in UHT milk. In the present study a similar decreasing trend of fat was observed

in the middle fraction of backscattering profiles provided by Turbiscan, which is depicted in

Figure 32b. Whereas, backscattering in the bottom fraction of full fat milk was more or less

constant over the period, possibly due to sedimentation.

Common for all three analyses is that the physical stability decreased with higher storage

temperatures. The temperature cycles followed the same development as their average temperature.

This pattern was consistent for all physical parameters included in the study. The acceleration of the

different physical parameters varied between the applied methods. Creaming was accelerated

approximately four times when exposed to 40 °C compared to 20 °C when analysed with Turbiscan,

and two times when analysed with Milkoscan. A possible explanation for the higher acceleration of

creaming with Turbiscan may be that proteins attached to fat globules, will contribute to the

backscattering measured at the creaming layer. These proteins will not be measured as a part of the

creaming layer when Milkoscan is applied. Sedimentation was proceeding approximately twice as

fast when exposed to 40 °C compared to 20 °C for milk analysed with Turbiscan as well as

Milkoscan. Whereas the instability index reflecting sedimentation was accelerated 12 times when

analysed with Lumifuge. The instability index provided by Lumifuge reflects the propensity of

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particles to migrate when affected by gravitational forces. Equation 9 describes that a high

instability index is reflected by; a fast change in transmission after a defined time and at a defined

position on the sample cell. In skimmed milk the instability index will therefore reflect how likely

the proteins are to migrate to the bottom under centrifugation. The observations indicate that the

proteins are more likely to migrate, when the milk have been exposed to elevated temperatures prior

to centrifugation. Thus, the outcome from the three techniques applied in the study varies a lot,

especially parameters provided by Lumifuge.

Static light scattering was used to evaluate the effect of elevated storage temperatures on fat globule

size distribution. This analysis would in addition provide information about why these physical

instabilities are occurring during storage. But no significant changes in fat globule size distribution

were observed, over the storage period. It may be possible that fat globules aggregate in the form of

flocculation, which can be disrupted when the milk is homogenized by shaking from side to side,

prior to analysis. In addition this observation reflects that other parameters are accelerating the

destabilizations. According to Stokes low, viscosity and density are parameters affecting the

velocity of creaming. The continuous phase viscosity of milk and the density of milk fat are both

decreasing with temperature, which will increase particle migration velocity (Bandari and Singh,

2011; Rousseau, 2002). Based on this analysis, fat globule size measurements do not seem to be a

good parameter to evaluate in an accelerated shelf life study of UHT milk. Particle size is

considered an important factor to the creaming rate. Hence particle size measurements may be

relevant for products with less stable globules e.g. non homogenized products.

Another parameter of major concern, when evaluating shelf life of UHT milk, is age gelation. The

gelation of UHT milk depends on several factors, to mention is; raw milk quality, proteolysis,

severity and duration of heat treatment and storage conditions (Chavan et al., 2011; Datta et al.,

2001). Previous studies have shown major differences in the degree of gelation between direct and

indirect UHT milk, with the highest degree of gelation in direct UHT milk (Datta et al., 2002). No

gelation was observed in the studied indirect UHT milk. This is considered to be due to the low

enzyme activity observed with the peptide analysis. Datta et al. (2002) reported plasmin and

plasminogen activities in direct and indirect UHT milk. After direct UHT treatment 19% plasmin

activity and 37% plasminogen activity were found, whereas in indirect UHT milk no plasmin

activity were present and 19 % plasminogen activity. In addition indirect UHT milk is exposed to a

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higher heat load over longer time than direct UHT milk, this result in more denaturation of whey

proteins, which will bind to casein micelles and stabilize them. The severe heat treatment will also

enhance chemical cross-linking of casein micelles, making the bonds within them more stable

(Datta et al., 2001).

6.3 Comparison of accelerated parameters

A principal component analysis (PCA) was applied to provide a holistic characterization of the

chemical and physical parameters obtained in the study. On basis of this multivariate data analysis

the chemical and physical parameters did not seem to be markedly correlated. This may indicate

that it is important to evaluate both aspects when conducting a shelf life study, since one of the

parameters do not directly give information about the other. There are, however, processes that

connect chemical and physical parameters during storage of UHT milk. A major factor is chemical

cross-linking that will affect the physical sedimentation and probably delay age gelation.

To save time and resources in the development of long life products, prediction of shelf life through

accelerated shelf life studies are often applied (Hough et al., 2006; Richards et al., 2014). These

tests assume that the accelerated processes fit into a kinetic model. Therefore a main challenge may

be the availability of a valid kinetic model that besides fitting into homogeneous systems also fits

into complex heterogeneous systems (Mizrahi, 2000). In an accelerated shelf life test parameters

considered important to consumer acceptance are speeded up by exposure to modified storage

conditions. Although an increased rate of these processes is aimed for, the deteriorative processes

need to be the same as under ambient conditions. When elevated temperatures are applied the most

favorable condition is hence the maximal temperature, for which the data still fits into the Arrhenius

equation (Mizrahi, 2000; Richards et al., 2014). In the present study an upper limit of the

accelerating factor seems to be 30 °C. From the GC-MS analysis of volatile compounds, 2-

ethylfurane, 2-heptanone, 2-nonanone and 2-undecanone were detected. These compounds revealed

an Arrhenius plot with a breaking point at 30 °C, indicating that something affects the rate of

formation at temperatures above. Moreover, the formation of furfural and 2-furanmethanol were

only detectable from 30 °C and 40 °C, respectively. On basis of these observations it may be hard to

predict shelf life above 30 °C. Though, it is important to note that these perspectives are based on

single determinations. In addition, a prediction of shelf life from UHT milk stored at 10 °C appears

to be challenging. From analysis of fluorescence and colour it seems that some reactions are present

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at 20 °C and above, that are not present at 10 °C. This is not considered a problem to UHT products

since these are mainly stored at room temperature.

When predicting shelf life of a product it is important to note, that complex systems include several

elementary reactions with individual temperature sensitivities. In the present study, varying Q10

values were calculated for the three stages of the MR. The initial stage revealed Q10 values in the

range of 1.5 to 2.3, consistent with previous findings (Labuza et al., 1994). The intermediate stage

revealed Q10 values in the range of 3.9 to 10.9, which is slightly above findings of 4 to 6 (Labuza et

al., 1994) and finally a range from 2.8 to 6 was found for the late MR´s, consistent with 3 to 6

published by Nursten (2005). Thus, the MR seems overall to be highly affected by temperature.

These findings were all validated by fitting into the Arrhenius equation. The variations in Q10 of the

three stages of the MR reflect that these stages have different temperature dependencies. In this

study the highest Q10 were found for the intermediate MR´s, meaning that these reactions seem to

be most temperature sensitive. Elevation in temperature from 20 °C to 30 °C was found to be

preferable for an accelerated shelf life study, based on findings of the present study. Since this is not

a high elevation in temperature, it may be an advantage to use markers with high temperature

sensitivities, for a minimization of time and resources.

7. Conclusion

The present master thesis is a step towards a valid shelf life test, accelerating both chemical and

physical changes in UHT milk. Such a test would be a valuable tool providing a more holistic

prediction of shelf life, compared to previous investigations. The objective of this study was to give

a quantification of physico-chemical changes with use of elevated storage temperatures, to establish

a setup to accelerate shelf life development. Commercial skimmed and full fat UHT milk were

exposed to 10 °C, 20 °C, 30 °C, 40 °C and 50 °C and three temperature cycles. The chemical

analyses included an evaluation of the three stages of the MR as well as the lipid oxidation, and the

physical analyses included an evaluation of physical destabilization.

In the present study, skimmed and full fat UHT milk seemed to follow a similar pattern for all

parameters analysed. The exposure to elevated temperatures accelerated both chemical and physical

changes over the storage period of 24 weeks. Investigation of chemical changes revealed data

possible to describe with kinetic models. Formation of furosine followed a first order reaction

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kinetic for product formation, whereas fluorescence and colour changes followed a zero order

reaction kinetic. Moreover, data obtained for all three stages of the MR fitted into the Arrhenius

equation, with corresponding Q10 values; for the initial MR´s of 1.5 to 2.3, for the intermediate

MR´s of 3.9 to 10.9 and for the late MR´s of 2.8 to 6.

Acceleration of physical changes varied between the applied methods. Creaming was accelerated

approximately four times when exposed to 40 °C compared to 20 °C when analysed with Turbiscan,

and two times when analysed with Milkoscan. Sedimentation was accelerated approximately two

times when exposed to 40 °C compared to 20 °C when analysed with Turbiscan as well as

Milkoscan. Additionally, the instability index for sedimentation was accelerated 12 times when

analysed with Lumifuge. No effect was observed on fat globule size when exposed to elevated

temperature over time. This indicates that other parameters are affecting the creaming observed in

the present study, probably by changes in viscosity of the continuous phase and density of the fat

globules.

Development of the three temperature cycles varied between chemical and physical parameters

analysed. The temperature cycles included in the chemical analyses increased with a higher rate

than at the average temperature of which they were exposed to. Whereas the temperature cycles

included in the physical analyses followed the same development as at the average temperature of

which they were exposed to. This reflects that it is only slightly possible to delay the MR once it

has started, even when exposed to lower storage temperatures.

A prediction of shelf life from characterisation of chemical and physical changes seems to be

possible within the temperature range of 20 °C to 30 °C. Analysis of volatile compounds revealed

an Arrhenius plot for 2-ethylfuran with two temperature ranges from 10-30 °C and 30-50 °C.

Additionally, furfural and 2-furanmethanol were only detected from 30 °C and 40 °C, respectively.

Both observations indicate that other reactions are proceeding at temperatures above 30 °C,

compared to at ambient temperatures. Analysis of fluorescence and colour revealed Arrhenius plots

indicating that the rate is almost constant at 10 °C, and increasing from 20 °C and above. Further

investigations are needed to validate the accelerated shelf life test for prediction of shelf life of

UHT milk.

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8. Perspectives

Accelerated shelf life tests are valuable tools in the prediction of shelf life. For complex

heterogeneous systems like milk it may be a challenge to fit accelerated parameters into kinetic

models. A future approach may be a better characterization of the mechanisms behind the

deterioration processes, with the aim of developing kinetic models for more specific reactions. Such

models would validate future accelerated shelf life tests.

An accelerated shelf life test based on the present setup would be interesting to couple with a

sensory descriptive analysis. This would provide knowledge about the sensory characteristics of the

volatile compounds formed by lipid oxidation and in the intermediate stage of the MR. Due to

differences in sensory thresholds some compounds are affecting flavour and aroma more than

others. This would moreover give information about which volatile compounds should be of

particular importance in an accelerated shelf life test.

Finally, it would be interesting to expand this accelerated shelf life study to other long life products

than UHT milk. Markers relevant for other products would mainly depend on the composition of

the specific product and the severity of heat treatment.

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10. Appendix

Appendix 1: Transmission profiles provided by Lumifuge

Figure 37 – Transmission profile of full fat UHT milk stored at 40 °C, illustrating measured transmission as function of the local position on the sample cell. Red curves indicate the first measurements, which becomes green over time of analysis. The position selected for calculation of instability index is marked with blue.

Figure 38 - Transmission profile of skimmed milk stored at 40 °C, illustrating measured transmission as function of the local position on the sample cell. Red curves indicate the first measurements, which becomes green over time of analysis. The position selected for calculation of instability index is marked with blue.

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Appendix 2: Backscattering profiles provided by Turbiscan

Figure 39 – Backscattering profile of full fat milk stored at 40 °C, illustrating measured backscattering as function of the local position on the sample cell. The blue line indicates clarification of the middle layer, measured 25 mm from the bottom of the sample cell.

Figure 40 - Backscattering profile of skimmed milk stored at 40 °C, illustrating measured backscattering as function of the local position on the sample cell. The blue line indicates clarification of the middle layer, measured 25 mm from the bottom of the sample cell.

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