DEVELOPMENT OF FOOD GRADE COLLOIDAL SYSTEM FOR …

DEVELOPMENT OF FOOD GRADE COLLOIDAL SYSTEM

FOR DELIVERY OF VITAMIN A AND D

TAHIR MEHMOOD

07-arid-163

Department of Food Technology

Faculty of Crop and Food Sciences

Pir Mehr Ali Shah

Arid Agriculture University Rawalpindi

Pakistan

2018

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DEVELOPMENT OF FOOD GRADE COLLOIDAL SYSTEM

FOR DELIVERY OF VITAMIN A AND D

by

TAHIR MEHMOOD

(07-arid-163)

A thesis submitted in the partial fulfillment of

the requirements for the degree of

Doctor of Philosophy

in

Food Technology

Department of Food Technology

Faculty of Crop and Food Sciences

Pir Mehr Ali Shah

Arid Agriculture University Rawalpindi,

Pakistan

2018

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DEDICATION

This Humble Effort is Solely Dedicated

to the Uplifted hands

of my

Parents, brother and sister

Who urged me to work hard

and to achieve my goals.

The Hands Ever Praying for Me

These Hands may never fall down

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CONTENTS

Page

List of Tables xi

List of Figures xv

Acknowledgments xix

ABSTRACT xxi

1 INTRODUCTION 1

2 REVIEW OF LITERATURE 5

2.1 FORMULATIONS OF NANOEMULSIONS 5

2.1.1 Oil Phase 5

2.1.2 Aqueous Phase 6

2.1.3 Stabilizers 6

2.1.3.1 Emulsifier 7

2.1.3.2 Texture modifiers 9

2.2 NANOEMULSIONS PREPARATION 10

2.2.1 High-Pressure Homogenizer 11

2.2.2 Ultrasonic Homogenizer 12

2.3 DESIGNING OF FUNCTIONAL NANOEMULSIONS 14

2.3.1 Composition of Particle 14

2.3.2 Concentration of Particle 15

2.3.3 Particle Dimensions 16

2.3.4 Interfacial Properties 18

2.3.5 The Physical State of Particle 19

2.4 DROPLET BREAKUP IN NANOEMULSIONS 19

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2.5 ADVANTAGES OF NANOEMULSIONS 21

2.5.1 Antimicrobial Activity 21

2.5.2 Lipophilic Components Encapsulation 22

2.5.3 Control Delivery and Increased Bioavailability of Lipophilic

Components

23

2.5.4 Improved Stability of Nanoemulsions 24

2.5.5 Modification of Texture 25

2.6 BIOLOGICAL FATE OF NANOEMULSIONS 26

2.7 APPLICATION OF THE NANOEMULSIONS IN FOOD

PRODUCTS

28

2.8 POTENTIAL TOXICITY OF NANOEMULSIONS 30

2.8.1 Bioactive Compounds with Increased Bioavailability which

are Toxic at Higher Level

31

2.8.2 Direct Absorption of Smaller Droplets 31

2.8.3 Disturbance in Normal Gastrointestinal Functions 32

2.8.4 Effect of Composition 33

3 MATERIALS AND METHODS 35

3.1 COLLECTION OF MATERIALS 35

3.2 CHARACTERIZATION OF COMPONENTS 35

3.3 NANOEMULSIONS PREPARATION 35

3.4 PARTICLE SIZE ANALYSIS 36

3.5 OPTIMIZATION OF PREPARATION CONDITIONS 36

3.5.1 p-Anisidine Value 40

3.5.2 Beta Carotene Retention 41

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3.6 OPTIMIZATION OF PREPARATION CONDITIONS FOR

VITAMIN D NANOEMULSIONS

42

3.6.1 Droplet Growth Ratio (DGR) 45

3.6.2 Vitamin D2 Retention 46

3.7 CHARACTERIZATION OF NANOEMULSIONS 46

3.7.1 Storage Stability 46

3.7.2 Turbidity Measurement 47

3.8 FACTORS AFFECTING SELECTIVE PARAMETERS 47

3.8.1 Effect of pH 47

3.8.2 Effect of Ionic Strength Variation 47

3.8.3 Thermal Stability 47

3.8.4 Physical Stability 48

3.9 ANIMAL STUDIES 48

3.9.1 In Vivo Toxicity for Vitamin A 48

3.9.2 In Vivo Toxicity for Vitamin D 49

3.9.3 Nuclear Abnormalities Analysis 50

3.9.4 Comet Assay 50

3.9.4.1 Procedure for staining 51

3.9.4.2 Slides Scoring 52

3.10 DEVELOPMENT OF BETA CAROTENE AND VITAMIN

D FORTIFIED BEVERAGES

52

3.10.1 Viscosity 52

3.10.2 °Brix 53

3.10.3 Sensory Evaluation 53

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3.11 STATISTICAL ANALYSIS 53

4 RESULTS AND DISCUSSION 54

4.1 CHARACTERIZATION OF COMPONENTS 54

4.2 OPTIMIZATION OF NANOEMULSIONS 56

4.2.1 Fitting the Model 56

4.2.2 Effect of Independent Variables on Response Variables 58

4.2.2.1 Droplet size 58

4.2.2.2 p-Anisidine value 63

4.2.2.3 β-Carotene retention 64

4.2.3 Optimization of Independent Variables 65

4.2.4 Verification of RSM Model 66

4.3 OPTIMIZATION OF VITAMIN D NANOEMULSIONS 66

4.3.1 Fitting the Model 66

4.3.2 Effects of Independent Variables on Responses 70

4.3.2.1 Droplet size 70

4.3.2.2 Droplet growth ratio 72

4.3.2.3 Vitamin D retention 76

4.3.3 Optimization of Emulsifying Conditions for Vitamin D

Nanoemulsions

77

4.3.4 Verifications of the Model 78

4.4 CHARACTERIZATION OF THE BETA CAROTENE

AND VITAMIN D NANOEMULSION

79

4.4.1 Droplet Growth Ratio and Storage Stability 79

4.4.2 p-Anisidine Value 87

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4.4.3 Turbidity 91

4.5 EFFECT OF ENVIRONMENTAL CONDITION ON BETA

CAROTENE AND VITAMIN D NANOEMULSIONS

93

4.5.1 Effect of pH 95

4.5.2 Effect of Ionic Strength 98

4.5.3 Effect of Temperature 100

4.5.4 Physical Stability (Freeze-Thaw Cycle) 105

4.6 TOXICOLOGICAL STUDIES FOR BETA CAROTENE

AND VITAMIN D NANOEMULSIONS

107

4.6.1 Body Weight 109

4.6.2 Nuclear Abnormalities Analysis 113

4.6.2.1 Bi-nuclear assay 113

4.6.2.2 Multi-nuclear assay 115

4.6.3 Comet Assay 120

4.6.3.1 Tail length 120

4.6.3.2 Tail DNA 126

4.6.3.3 Olive moment 128

4.10 PREPARATION OF FORTIFIED BEVERAGE 133

SUMMARY 136

RECOMMENDATIONS 138

LITERATURE CITED 139

APPENDICES 161

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LIST OF TABLES

Table No.

Page

3.1 Independent variables for optimization of preparation

conditions for β- Carotene nanoemulsion

38

3.2 Different combinations of independent variables for

application of RSM design for optimization of β- Carotene

nanoemulsions

39


application of RSM design for optimization of vitamin D

nanoemulsions

43


application of RSM design for optimization of vitamin D

nanoemulsions

44

4.1 Physicochemical properties of different components of beta

carotene and vitamin D nanoemulsions

55

4.2 Effect of independent variables on responses for β-carotene

nanoemulsions

56

4.3 Regression coefficients for beta carotene nanoemulsions 58

4.4 Optimum preparation conditions and response value for β-

carotene nanoemulsions

68

4.5 Effect of independent variable on responses for optimization

of vitamin D nanoemulsions

69

4.6 Regression coefficients values for vitamin D nanoemulsions 71

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4.7 Optimum preparation conditions for vitamin D

nanoemulsions

80

4.8 ANOVA for droplet growth ratio of beta carotene

nanoemulsions

81

4.9 ANOVA for droplet growth ratio of vitamin D

nanoemulsions

83

4.10 ANOVA for storage stability of beta carotene nanoemulsions 84

4.11 ANOVA for storage stability of vitamin D nanoemulsions 86

4.12 ANOVA for p-Anisidine value of beta carotene

nanoemulsions

88

4.13 ANOVA for p-Anisidine value of vitamin D nanoemulsions 90

4.14 ANOVA for turbidity value of beta carotene nanoemulsions 92

4.15 ANOVA for turbidity value of vitamin D nanoemulsions 94

4.16 ANOVA for pH stability of beta carotene nanoemulsions 96

4.17 ANOVA for pH stability of vitamin D nanoemulsions 97

4.18 ANOVA for stability of beta carotene nanoemulsions against

ionic strength

99

4.19 ANOVA for stability of vitamin D nanoemulsions against

ionic strength

101

4.20 ANOVA for stability of beta carotene nanoemulsions against

higher temperature

103

4.21 ANOVA for stability of vitamin D nanoemulsions against

higher temperature

104

4.22 ANOVA for physical stability of β-carotene nanoemulsions 106

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against freeze-thaw cycle

4.23 ANOVA for physical stability of vitamin D nanoemulsions


108

4.24 ANOVA for effect of beta carotene nanoemulsions on

weight

110

4.25 ANOVA for effect of different treatments of vitamin D

nanoemulsions on the weight of mice

112

4.26 ANOVA for bi-nuclear assay against different treatments of

beta carotene nanoemulsions

114


nanoemulsions on bi-nuclear assay

116

4.28 ANOVA for multi-nuclear assay of different treatment of


118

4.29 Analysis of variance for effect of different treatments of

vitamin D nanoemulsions on multi-nuclear assay

119

4.30 ANOVA for effect of beta carotene nanoemulsions on tail

length

122


nanoemulsions on tail length

125

4.32 ANOVA for effect of different treatments of beta carotene

nanoemulsions on tail DNA

127



129

4.34 ANOVA for effect of different treatments of beta carotene 130

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nanoemulsions on olive moment



132

4.36 Physicochemical properties of beta carotene and vitamin D

fortified beverages

134

4.37 Sensory Evaluation of beta carotene and vitamin D fortified

beverages

134

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LIST OF FIGURES

Figure No. Page

4.1 (A) Particle size distribution of β-carotene

nanoemulsions (B) Visual appearance of β-carotene

nanoemulsions

61

4.2 3D graphic surface optimization of (A) droplet size (nm)

versus surfactant concentration (%) and homogenization

time (Min.) (B) droplet size (nm) versus oil content (%)

and surfactant concentration (%) (C) p-Anisidine value

versus surfactant concentration (%) and homogenization

time (Min.) (D) p-Anisidine value versus oil content (%)

and surfactant concentration (%) (E) β-carotene

retention (%) versus surfactant concentration (%) and

homogenization time (Min.) (F) β-carotene retention

(%) versus oil content (%) and surfactant concentration

(%).

62

4.3 (A) Particle size distribution of vitamin D

nanoemulsions (B) Visual appearance of vitamin D

nanoemulsions

73

4.4 3D graphic surface optimization of (A) droplet size (nm)

versus S/O ratio and homogenization time (Min.) (B)

droplet size (nm) versus disperse phase volume (%) and

S/O ratio (C) Droplet growth ratio versus S/O ratio and

homogenization time (Min.) (D) Droplet growth ratio

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versus disperse phase volume (%) and S/O ratio (E)

Vitamin D retention (%) versus S/O ratio and

homogenization time (Min.) (F) Vitamin D retention

(%) versus disperse phase volume (%) and S/O ratio

4.5 Change in droplet growth ratio of beta carotene

nanoemulsions during one month storage

81

4.6 Effect of time and temperature on storage stability of


83

4.7 Change in droplet growth ratio of vitamin D

nanoemulsions during one month storage

84

4.8 Effect of time and temperature on storage stability of

vitamin D nanoemulsions

86

4.9 Change in p-Anisidine value of beta carotene

nanoemulsions during storage

88

4.10 Change in p-Anisidine value of vitamin D


90

4.11 Effect of time and temperature on turbidity 92

4.12 Effect of time and temperature on turbidity value of

vitamin D nanoemulsions during storage

94

4.13 Effect of pH on the stability of beta carotene

nanoemulsions

96

4.14 Effect of pH on the stability of vitamin D

nanoemulsions

97

4.15 Effect of ionic strength on the stability of beta carotene 99

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nanoemulsions

4.16 Effect of ionic strength on the stability of vitamin D

nanoemulsions

101

4.17 Stability of beta carotene nanoemulsions against higher

temperature

103

4.18 Stability of vitamin D nanoemulsions against higher

temperature

104

4.19 Physical stability of beta carotene nanoemulsions


106

4.20 Physical stability of vitamin D nanoemulsions against

freeze-thaw cycle

108

4.21 Effect of different treatments of beta carotene


110

4.22 Effect of different treatments of vitamin D


112


nanoemulsions on the frequency of bi-nuclear cells

114


nanoemulsions on the frequency of bi-nuclear cells

116


nanoemulsions on multi-nuclear cells frequency

118

4.26 Effect of treatments of vitamin D nanoemulsions on the

frequency of multi-nuclear cells

119

4.27 Effect of beta carotene nanoemulsions on tail length 121

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nanoemulsions on tail length in comet assay

122

4.29 Comet Assay Results for beta carotene nanoemulsions

(A) Group A (B) Group E

124

4.30 Comet Assay Results for vitamin D nanoemulsions (A)

Group A (B) Group E

125

4.31 Effect of beta carotene nanoemulsions on tail DNA 127


nanoemulsions on tail DNA in comet assay

129

4.33 Effect of beta carotene nanoemulsions on olive moment 130

4.34 Effect of vitamin D nanoemulsions on olive moment 132

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ACKNOWLEGEMENTS

All kinds of appreciation and thanks are for Almighty Allah, the

beneficent, the merciful, Who is entire source of wisdom, knowledge and knows

better the mysteries and secrets of universe; who granted me the patience and

persistence to carry out my research study to the end. All respects are for the Holy

Prophet Muhammad (PBUH) who is, forever, a light of guidance of the entire

humanity.

I feel extremely privileged in taking this opportunity to express my

profound gratitude and sense of devotion to my worthy Supervisor Dr. Anwaar

Ahmed, Associate Professor Department of Food Technology, Pir Mehr Ali Shah

Arid Agriculture University, Rawalpindi. It was only because of his inspiring

guidance, cogent and thought provoking suggestions, consistent encouragement,

sympathetic attitude and dynamic supervision during the entire research work that I

could prepare this manuscript.

I am grateful to Prof. Dr. Asif Ahmad, Directior, Institute of Food and

Nutritional Sciences, for his valuable guidance and support at every stage of this

work. His cooperation and assistance made this research paper a worthwhile effort.

His enthusiasm and energy in the field of science is admirable. He has always been

willing to spare time and encourage me when needed.

I also owe debt of gratitude to Dr. Mansoor Abdullah, Faculty of

Veterinary and Animal Sciences, Pir Mehr Ali Shah Arid Agriculture University

Rawalpindi, for his kind behavior and valuable suggestions while completing this

work. Cordial and humble thanks are for Dr. Muhammad Sheeraz Ahmad, for

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his technical and constructive guidance during my research work.

I am highly obliged for indecorous, indemonstrable and endearment

guidance and support of Dr. Zaheer Ahmad, Assistant Professor, Department of

Home and Health Sciences, AIOU, Islamabad, Professor Dr. Sara Qaisar from

NCP and Dr. Abida Raza from NORI Hospital for their sympathetic attitude and

dynamic supervision during the entire research work that I could prepare this

manuscript.

I would like to record my special acknowledgments and sincerest thanks to

all my friends especially Abdul Waheed, Faheem Ilyas, Abdul Wakeel, Muhammad

Imran Yamin, Muhammad Kaleem, Muhammad Ali and Kashif Rafique for their

generous help and cooperation during my research work. Before I close, I would

like to acknowledge the efforts, the patience, the sacrifices rendered by my parents

in growing me up in a way that made it possible for me to achieve the present level.

No words can really express the feeling that I have for my beloved parents, brother

and sister. May Allah give them a long and happy life (Ameen).

TAHIR MEHMOOD

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ABSTRACT

Nutritional deficiency of vitamin A and D is causing a lot of problems in the world.

It is estimated that about one billion people worldwide are either vitamin D

deficient or have insufficient vitamin D intake. In Pakistan about 85% of both

pregnant and non-pregnant mothers have been found vitamin D deficient. Apart

from this, 5.7 million children below 5 years of age and 42.5 % women were

identified as vitamin A deficient in Pakistan. Being food fortification or

supplementation a best approach, the food manufacturers are interested in

fortifying their products with vitamin A and D. As both vitamins are restricted to

fats and oils due to their non-solubility in water. Nanoemulsions are ideal solution

to address this problem because this technique enhances the solubility, kinetic

stability, bio efficacy and bioavailability of encapsulated material due to their

smaller size. The purpose of present study was to fortify beverages with

nanoemulsions of vitamin A and D. The nanoemulsions were prepared by using

food grade surfactants (Tween 80 and soya lecithin), deionized water and vegetable

oil (olive and canola oil). Preparation conditions for beta carotene and vitamin D

nanoemulsions were optimized using response surface methodology. These

nanoemulsions were further characterized against different physico-chemical

parameters. In vivo study was carried out on animal model to investigate the safety

of nanoemulsions. The nanoemulsions based delivery system was used to fortify

the beverages with these vitamins. The results manifested that, ideal optimum

preparation conditions for beta carotene nanoemulsions were 6.07% surfactant,

4.19 minutes homogenization time and 6.50% oil contents. For vitamin D

nanoemulsions, optimum preparation conditions were 4.82 minutes

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homogenization time, 0.67 surfactant to oil ratio (S/O) and 7% disperse phase

volume. During two months of storage studies, these nanoemulsions remained

stable against phase separation and creaming. Moreover, droplet size of

nanoemulsions stored at 4 °C slowly increased as compared to nanoemulsions

stored at 25 °C. Additionally, p-Anisidine value of the vegetable oil (canola and

olive oil) incorporated into nanoemulsions were significantly lower as compared to

free vegetable oil. These nanoemulsions were stable against droplet aggregation

and phase separation over a wide range of pH (2-8), salt concentration (50-400

mM) and temperature (30-80°C). During toxicity study, bi-nuclear assay, multi-

nuclear assay and comet assay did not showed any toxic effect of nanoemulsions

on animal models. During last part of study, vitamin beta carotene and vitamin D

fortified model beverages was developed successfully. Hence, nanoemulsions

based delivery system can be used for fortification of aqueous products with fat

soluble vitamins and other nutraceutical compounds.

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Chapter 1

INTRODUCTION

The food industry is interested in the development of colloidal-based

delivery system which incorporates lipophilic compounds into food and beverages.

These colloidal systems vary in their physicochemical properties, stability and

composition, due to which these differ in functional performance (Mcclements et

al., 2007; Rao and Mcclements, 2011). There are numerous commercial

applications in the food industry where lipophilic compounds (such as flavors,

bioactive lipids, antioxidants, antimicrobials and nutraceuticals) are needed to be

incorporated into the aqueous phase (Given, 2009; Ziani et al., 2012). The most

convenient way to achieve the objective is colloidal- based delivery system i.e.

emulsions, nanoemulsions and microemulsions. It is seen that nanoemulsions are

an ideal colloidal system for the incorporation of lipophilic components into

aqueous media because of their solubility, kinetic stability, bioefficacy and

bioavailability attributed to their smaller size (Ozturk et al., 2014).

Nanoemulsions are kinetically stable system with mean radii of < 100 nm.

These have smaller particle size as compared to light wavelength, due to which

nanemulsions are appeared as transparent or slightly turbid (Mcclements, 2011).

Hence, nanoemulsions can be incorporated into food products where transparent

look is desirable e.g. fortified beverages and water. Furthermore, emulsions have

greater stability against droplet aggregation and sedimentation as compared to

conventional emulsions due to their smaller droplet size (Mcclements and Rao,

2011).

Nanoemulsions can be produced by using high energy (high-pressure

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homogenization, sonication and microfluidization) and low energy (phase inversion

and spontaneous emulsification) methods. During high energy method, intense

disruptive forces are generated to mechanically break the disperse phase into

smaller droplets which can be dispersed into continuous phase. High energy

methods are desirable in food industry for preparation of nanoemulsions by using

low surfactant to oil ratio as compared to low energy methods (Ozturk et al., 2014).

Hence, high energy methods are widely used for the preparation of nanoemulsions.

Low energy methods are not desirable for food industry because it is not possible

to use natural emulsifier (polysaccharides and proteins) for nanoemulsions

preparation in low energy approaches. Additionally, higher amount of synthetic

surfactant is used in low energy methods which is not desirable for food industry

(Mcclements and Rao, 2011).

β- carotene is a member of carotenoid family which is mainly found in

fruits and vegetables. It provides a substantial proportion of vitamin A in human

diet because of retinol precursor with higher conversion rate (Naves and Moreno,

1998). β- carotene is also useful in the prevention of numerous diseases such as

heart diseases, cataracts and cancer (Aherne et al., 2010). Furthermore, it is also

used in food industry as a colorant and antioxidant (Hou et al., 2012). So, food

industry is interested in its incorporation into food products to cater above-

mentioned benefits. But, their incorporation into beverages and various other foods

is challenging due to their poor water solubility, instability in heat, oxygen and

light and appearance in crystalline state at ambient temperature (Mattea et al.,

2009). Consequently, β- carotene are dissolved in oil or any suitable medium in oil

in water emulsions before their incorporation into aqueous food products (Qian et

3

al., 2012b). Stability of beta carotene in oil in water depends on the composition of

emulsion and environmental conditions like heat, surfactant, light, food systems,

singlet oxygen and antioxidant addition (Hou et al., 2010). The most convenient

way to incorporate β- carotene into food products is nanoemulsions based colloidal

system which ensures higher stability, solubility and bioavailability due to smaller

particle size.

Vitamin D is a fat-soluble vitamin and it is produced from 7-

dehydrocholesterol when the skin of our body is exposed to sunlight. It plays an

important role in the development of cartilage, teeth and bone (Cranney et al.,

2008). It is also useful in the prevention of numerous diseases such as heart

diseases, immune diseases and cancer (Haham et al., 2012). Vitamin D possesses

two different active forms: cholecalciferol (vitamin D3) and ergocalciferol (vitamin

D2). Cholecalciferol is synthesized in our skin after exposure of sunlight as well as

ergocalciferol is naturally available in foods in small quantity (Guttoff et al., 2015).

The deficiency of vitamin D is worldwide and it is estimated that about one billion

people on the globe are vitamin D deficient or their consumption of vitamin D is

insufficient (Haham et al., 2012). This deficiency of vitamin D can be easily

addressed by fortifying food products with vitamin D. But, its fortification is

challenging due to poor solubility, bioavailability and chemical degradation under

different environmental conditions (Tsiaras and Weinstock, 2011). The

encapsulation of vitamin D in nanoemulsion-based delivery system is best solution

which exhibit it more solubility, stability and bioavailability.

Presently, a few studies have been carried out on the food grade

nanoemulsions and their potential applications in beverage and food industry. This

4

research was designed to test the hypothesis that food grade colloidal system is a

successful technique for vitamin A and D delivery. This hypothesis was tested

through preparation and characterization of colloidal system (food grade

nanoemulsions). Later on, application of colloidal based delivery system in

beverages. The main objectives of the present study are:

Preparation of food grade nanoemulsion and incorporation of vitamin A and D

as active ingredient.

Characterization of these nanoemulsions for different physicochemical

parameters under different environmental conditions.

Investigation of the safety of these nanoemulsions.

Application of colloidal-based delivery system in beverage and subsequently

characterization of these beverages against different quality parameters.

5

Chapter 2

REVIEW OF LITERATURE

Nanoemulsions are those emulsions which consist of very small droplet size

having diameter in the range of 20-200 nm (Mason et al., 2006). Due to the smaller

particle size, they have many advantages as compared to conventional emulsion

when applied in different food products. Their particle size is smaller as compared

with light wavelength, so these appeared as transparent or slightly turbid (Tadros et

al., 2004). This smaller particle size makes them stable to droplet aggregation and

sedimentation as compared to macroemulsions (Wooster et al., 2008).

Nanoemulsion based colloidal delivery system increases the bioavailability of

encapsulated material. Hence, it can be used to improve the bioavailability of

nutraceutical compounds (Acosta, 2009).

2.1 FORMULATIONS OF NANOEMULSIONS

Nanoemulsions consist of three main components i.e. emulsifier, oil and

water. However, water and oil phase may contain many other compounds and

mixed surfactants. The concentration and characteristics of these components have

major influence on the functional properties of nanoemulsions.

2.1.1 Oil Phase

The oil phase of nanoemulsions is made up of non-polar compounds, which

includes monoglycerides, diglycerides, triglycerides, free fatty acids (FFA),

mineral oils, flavors oils, essential oils, waxes, fat substitutes, fat-soluble vitamins

and various bioactive compounds (Mcclements and Rao, 2011). The preparation,

stability and other properties of nanoemulsions depend on the physicochemical

properties of lipid phase e.g. interfacial tension, solubility in water, polarity,

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6

density, viscosity, refractive index, chemical stability and phase behavior (Anton

and Vandamme, 2009). Preparation of nanoemulsion from triglycerols is desirable

in food industry due to their abundance, low cost and their nutritional and

functional properties e.g. sunflower oil, safflower oil, olive oil, corn oil and fish oil


2.1.2 Aqueous Phase

The aqueous phase of nanoemulsions primarily consists of water but

sometimes it may carry other polar compounds such as alcohols, proteins,

carbohydrates, polyols and minerals. The composition and concentration of polar

compounds determine the physicochemical properties of aqueous phase such as

refractive index, polarity, interfacial tension, ionic strength and phase behavior

(Mcclements and Rao, 2011). The ionic strength and pH of aqueous phase has

major influence on electrostatic interaction of lipid droplets. Viscosity enhancers

are added to aqueous phase before homogenization to reduce the oil droplet size by

increasing disruptive shear stress in homogenizer (Qian and Mcclements, 2011).

Apart from this, additions of viscosity enhancer into nanoemulsions change their

stability by slowing droplet collisions and gravitational separation. Additionally,

lipid oxidation can be prevented in nanoemulsions by addition of anti-oxidants in

aqueous phase (Mcclements and Decker, 2000). So, we can control functional

properties, stability and formation of nanoemulsions by controlling the composition

of its aqueous phase.

2.1.3 Stabilizers

Nanoemulsions are kinetically stable but thermodynamically unstable

system. Hence, appropriate amount of surfactant is required to stabilize aqueous

7

and lipid phase (Wooster et al., 2008). Emulsifiers facilitate smaller droplet

formation during homogenization and stabilize droplets against droplet aggregation

after homogenization. Different stabilizers (such as ripening inhibitors, texture

modifier and weighting agent) are intentionally added into nanoemulsions to

prevent Ostwald ripening, gravitational separation and droplet aggregation


2.1.3.1 Emulsifier

Emulsifiers are added in nanoemulsions to prevent the separation of

aqueous and oily phase. Emulsifiers are those surface active molecules which are

adsorbed on the surface of droplet to facilitate disruption of droplets and protect

them from droplet aggregation (Kralova and Sjöblom, 2009). Molecular structure

of surfactant comprises of lipophilic and hydrophilic parts. Hydrophilic part has

affinity for hydrophilic media such as water, while hydrophobic part has affinity

for hydrophobic media such as oil. Hydrophilic-lipophilic balance is good indicator

of emulsifier affinity for aqueous and oily phase. Emulsifier with more than 10

HLB (Hydrophilic-lipophilic balance) number has greater affinity for hydrophilic

groups while those with lower than 10 HLB number have affinity for lipophilic

compounds (Kralova and Sjöblom, 2009). Emulsifier helps in droplet disruption

during homogenization by lowering the interfacial tension. The concentration of

emulsifiers plays an important role in the development of nanoemulsions because

of their larger surface area. Hence, greater surfactant concentration is required to

cover larger surface area as compared to conventional emulsions. Previous studies

reported that the size of oil droplet significantly reduced with the increase in

surfactant concentration in both low and high energy homogenization methods

8

(Qian and Mcclements, 2011; Rao and Mcclements, 2011). Choice of emulsifier

selected for nanoemulsions preparation varies according to characteristic of oily

phase. Generally, protein and smaller molecular based surfactants are preferred in

the preparation of food-grade nanoemulsions due to their ability to adsorb at the

interface of oil and water (Bos and Van Vliet, 2001). Proteins produce larger

droplets as compared to surfactant because these are slowly adsorbed at interface

during homogenization and are less effective for interfacial tension reduction

(Stang et al., 1994).

Electrical characteristic can be used to classify emulsifiers among different

groups which include anionic (negative), zwitterionic (both negative and positive),

cationic (positive) on non-ionic (neutral). Electrical properties on emulsifiers have

significant effect on preparation, functional properties and stability of food-grade

nanoemulsions (Mcclements, 2011). Examples of anionic surfactants are sodium

lauryl sulfate (SLS), diacetyl tartaric acid esters of monoglycerides (DATEM) and

sodium stearoyl lactylate (SSL) (Wooster et al., 2008). Examples of non-ionic

surfactants are esters of sucrose such as sucrose monopalmitate, Tweens and Brij.

Nonionic surfactant did not charge oily droplets but they may charge oil droplets if

they contain impurities or preferential adsorption of water ions. Mostly non-ionic

surfactant is used for the preparation of food grade nanoemulsion due to ease of

nanoemulsion preparation in low energy and high energy methods, lower toxicity

and lack of irritation e.g. Tweens (Chiu, 2006; Henry et al., 2009; Jafari et al.,

2007). Food industry rarely used cationic surfactant except for lauric alginate due

to stronger antimicrobial properties (Ziani et al., 2012). Another group of

surfactant is zwitterion which contains two or more ionizable groups having

9

opposite charge on the same molecule. Zwitterionic surfactants include protein and

lecithin (Hoeller et al., 2009). Apart from preparation and stability, surfactant plays

an important role in loading and protection of active ingredients. Furthermore,

some surfactants such as lauric arginate (LAE) or SDS have antimicrobial activity

in addition to stabilization of nanoemulsions (Ziani et al., 2011).

2.1.3.2 Texture modifiers

Hydrocolloids are commonly used in aqueous solutions based food

formulations due to their gelling and thickening properties (Saha and Bhattacharya,

2010). They are commonly used in nanoemulsions for texture modification or

stability improvement against gravitational separation. Modified rheological

properties change the mouth-feel, texture and retard movement of droplets

(Mcclements, 2011). Polysaccharides with hydrated and extended structures are

commonly used for texture modification due to their ability for gel formation and

thickening of solution. Amphiphilic based polysaccharides are widely used as

emulsifiers which include pectins, modified alginates, modified starches, modified

celluloses, cellulose derivatives or galactomannans and gum arabic (Dickinson,

2009). Polysaccharides may negatively affect the stability of nanoemulsions due to

depletion flocculation or bridging. Hydrocolloids may form multilayers by

interacting with already absorbed molecules (Dickinson, 2003). Hence, due to these

properties, hydrocolloids are commonly used in nanoemulsions based delivery

system for different food products. The bioactivity, as well as digestibility of the

compound encapsulated into nanoemulsions depends on the nature of biopolymers.

Additionally, hydrocolloids may affect the gastrointestinal fate of nanoemulsions

which lead to change in the nutritional properties of encapsulated materials

10

(Gidley, 2013).

2.2 NANOEMULSIONS PREPARATION

Nanoemulsions can be prepared by using different methods but we can

broadly categorize them into low and high energy methods on the basis of

underlying principles (Acosta, 2009; Anton and Vandamme, 2009; Leong et al.,

2009; Tadros et al., 2004). In high energy methods, mechanical devices are used

which generate disruptive force that disrupts and intermingle the aqueous and oil

phase into smaller droplets e.g. sonication, microfluidizer and high-pressure

homogenizers. These are mostly preferred in the food industry because we can

prepare nanoemulsions from different materials by using these methods (Gutiérrez

et al., 2008; Leong et al., 2009; Velikov and Pelan, 2008; Wooster et al., 2008). In

low energy methods, tiny oil droplets are formed spontaneously by altering the

environmental conditions and composition of oil-water-surfactant system e.g.

phase inversion and spontaneous emulsification methods (Bouchemal et al., 2004;

Freitas et al., 2005; Tadros et al., 2004). There are number of advantages which are

associated with high energy approaches as compared to low energy approaches

which include use of natural emulsifier, lower concentration of emulsifiers, large-

scale production and widely utilized equipment.

When two immiscible liquids are mixed together, they have tendency to

gain thermodynamically stable – oily layer on the top of water layer (Mcclements,

2011). Hence, mechanical stress is required to disrupt and mix lipid and aqueous

phases. Interfacial free energy (∆G1) is equal to increase in contact area between

the oil and water phases (∆A) multiplied by the interfacial tension of

nanoemulsions (γ): ∆G1 = γ∆A (Walstra, 1993). Interfacial free energy positively

11

changes with the decrease in oil droplets, because contact area increase after

homogenization, and therefore it oppose nanoemulsions formation. Hence, more

energy is required to break down droplets into smaller ones. Surfactants decrease

the interfacial tension of the system. As a result of this, lower energy is required to

break the droplets into smaller ones (Mcclements and Rao, 2011). Apart from this,

enough surfactant should be present in emulsifying chamber to cover newly formed

droplets and prevent the process of coalescence. Mostly, high- pressure

homogenizer and sonicator are used for the preparation of nanoemulsions due to

their capability for generation of higher energy densities.

2.2.1 High-Pressure Homogenizer

High-pressure homogenizer is commonly used in food industry for preparation

of emulsions and nanoemulsions due to their scaling up possibility and versatility.

There are many types of high-pressure homogenizer, but few of them are able to

break the droplets up to nanometer range. Most commonly used high- pressure

homogenizers are microfluidizers and high-pressure valve homogenizer.

Most widely used method for conventional emulsion preparation is high-

pressure valve homogenizer. This method can be used for the preparation of

nanoemulsions by pumping coarse emulsion through narrow valve which is located

at the end of chamber (Mcclements and Rao, 2011). Operating pressure, geometry

of homogenizer and number of passes has remarkable effect on the droplet size

distribution of nanoemulsions. With the increase in value of pressure or number of

cycles, nanoemulsions with smaller droplet size were produced (Donsì et al.,

2011b).

Microfluidizer is quite similar to high-pressure valve homogenizer, but their

12

disruption chamber differs in design. Just like high-pressure valve homogenizer,

coarse emulsions are passed through interaction chamber in microfluidizer, but the

interaction chamber is divided into two flow channels. As a result of this, intense

disruptive forces are generated when fast-moving streams of nanoemulsions strike

with each other’s which result in disruption of droplets having larger size into

smaller size (Mahdi Jafari et al., 2006). Channels of microfluidizers are available in

different shapes but Y- shaped channels are most widely used in pharmaceutical

and food industry for the preparation of nanoemulsions. The droplet size of

nanoemulsions can be reduced in microfluidizer through increasing the number of

cycle or increase in operating pressure, but over processing promote droplet

coalescence which results in larger droplet size (Salvia-Trujillo et al., 2013).

During high-pressure homogenization, temperature of the emulsifying chamber

significantly increases, which should be taken into account when dealing with heat-

sensitive material. The temperature can be controlled by installing cooling coils

outside the treatment chamber. Several previous studies reported the degradation of

active material due to increase in temperature in high-pressure homogenization

(Donsì et al., 2012; Shukat and Relkin, 2011). Hence, temperature of high-pressure

homogenization chamber must be controlled when designing nanoemulsions based

delivery system for heat sensitive materials.

2.2.2 Ultrasonic Homogenizer

High-intensity ultrasonic waves (>20kHz frequency) are utilized in ultrasonic

homogenizer to breakdown aqueous and lipid phases into smaller droplets.

Sonication is used in liquid products for inactivation of microbes, extraction and

emulsification (Vilkhu et al., 2008). Ultrasonic homogenizer reduces the size of

13

droplets through cavitation effect. This cavitation effect is generated through

pressure fluctuation within fluid which results in compression and cyclical growth

of air bubbles in the fluid. After reaching a critical size, these air bubbles become

unstable and collapse violently which result in generation of turbulence, high shear

forces and hot spots in cavitation zone. Due to these effects, oil droplet breaks into

smaller droplets, leading to nanoemulsion development (Soria and Villamiel,

2010).

The main variables which affect the droplet size during ultrasonic

homogenization are intensity and treatment time. With the increase in residence

time and intensity of ultrasonic waves, droplet size of nanoemulsions significantly

reduced (Salvia-Trujillo et al., 2013). Ultrasonic homogenizers are available in

batch and continuous design. In continuous sonication, broader range of particle-

size distribution was observed as compared to batch type design. Reduction in

droplet is independent of design but overpressure increases the process efficiency

(Leong et al., 2009).

Several drawbacks are also associated with the preparation of nanoemulsion

through ultrasonic homogenizer. Firstly, high shear rate and hot spots generated as

a result of bubble disruption increase the temperature of emulsifying chamber (up

to 80 °C) which leads to degradation of heat-sensitive compounds which are

present in emulsions. Additionally, cavitation effect can cause oxidation or

hydrolysis of triglycerides which leads to lipid degradation due to the formation of

reactive species (Chemat et al., 2004). Furthermore, it is also possible that particle

from sonication probe may release in form of metal ions into products (Freitas et

al., 2006).

14

2.3 DESIGNING OF FUNCTIONAL NANOEMULSIONS

The properties of nanoemulsion particles ultimately affect the bulk of

functional and physicochemical properties of nanoemulsions containing food

products e.g., release characteristics, digestibility, rheology, stability and optical

properties. Important characteristics of droplets which control the functional

properties of nanoemulsions are highlighted in this section.

2.3.1 Composition of Particle

The properties of nanoemulsions particles can be controlled by careful

selection of processing operations and ingredients. Droplets of O/W nanoemulsions

comprises of surface active material containing shell and lipophilic core

(Mcclements, 2011). The lipophilic core can be created using a variety of

ingredients (non-polar) which include free fatty acids, monoacylglycerols,

diacylglycerols, triacylglycerols, waxes, fat-soluble vitamins, essential oils, fat

substitutes, flavor oils essential oils, nutraceutical compounds (such as Co-enzyme

Q, curcumin, phytosterols and carotenoids). All of these ingredients have different

physico-chemical properties, including melting behavior, viscosities, refractive

index and densities, which significantly affect the overall functional properties of

nanoemulsions (Mehmood, 2015). Shell of nanoemulsion droplets can be created

using different surface active ingredients (food grade) which include phospholipids,

surfactants, polysaccharides, proteins, solid particles and mineral oils. The

selections of these ingredients have critical impact on the properties of

nanoemulsion particles, including release characteristics, physical stability, and

digestibility and release characteristics (Mcclements and Rao, 2011).

The thickness of shell is much smaller in conventional emulsions as compared

15

to core radius while in case of nanoemulsions, shell thickness is approximately

equal to core radius. Hence, shell also exerts pronounced effect on the composition

of particles (Mason et al., 2006). Furthermore, particle composition also depends

on size which has numerous practical utilizations. First, particle size has impact on

the properties of particles, including permeability, refractive index and densities

which change the stability (such as creaming rate, optical properties and release

characteristics) and physicochemical properties of nanoemulsions. Second, the

loading capacity of nanoemulsion particles decrease because these have less

fraction of lipophilic core as compared to conventional emulsions. Third, size

dependence of particle composition may affect the accuracy of particle size

measurement data obtained from different techniques such as dynamic light

scattering, spectro-turbidity and laser diffraction (Mcclements et al., 2007). The

mathematical models used by different instruments for the calculation of particle

size distribution using measurable physical property such as pattern of light-

scattering assumed that nanoemulsion droplets have well-defined physical

properties (i.e. densities and refractive index) and homogenous sphere. As a result

of this, there may be error in reported results of particle size distribution because

nanoemulsions droplets comprise of core-shell structure rather than homogenous

spheres.

2.3.2 Concentration of Particle

Generally, concentration of particles in colloidal dispersions are expressed as

mass, number, or total system mass or per unit volume of particles (Mcclements

and Rao, 2011). In conventional emulsions, particle concentrations of O/W

emulsions are reported in term of oil volume per unit emulsion volume. In case of

16

nanoemulsions, particle concentration is pure disperse phase because effective

volume comprised of sum of core and shell volume fractions. Due to this, there is a

remarkable difference in functional and physicochemical properties of

nanoemulsions (e.g. stability and rheology) as compared to conventional emulsions

(Mason et al., 2006; Tadros et al., 2004).

During the preparation of nanoemulsions, particle concentration is controlled

by controlling disperse and continuous phase. However, after the preparation of

nanoemulsions, particle concentration can be controlled through concentration

(such as centrifugation, filtration, evaporation or gravitational separation) or

dilution (addition of continuous phase) methods. The concentration of

nanoemulsions using these methods is much difficult than conventional emulsions

due to very smaller droplet size. The droplet size of nanoemulsions can be changed

by the addition of emulsifier or altering the conditions of the solution which effect

electrostatic interactions (e.g. by changing ionic strength or pH) (Mcclements et al.,

2007).

2.3.3 Particle Dimensions

Particle dimension is an important characteristic of nanoemulsions due to their

effect on rheological characteristics, optical properties, release characteristics and

biological fate. The particle dimensions are usually reported as particle size

distribution which represents the classes of particle fractions with discrete size

(Mehmood et al., 2017). Particle size distribution is usually reported in tabulated

form or graph of concentration of particles (e.g., number or volume percentage)

versus size of particles (e.g., radius or diameter). Central tendency of distribution

(such as mean or median) and distribution width (such as polydispersity index or

17

standard deviation) can be used for convenient representation of particle size

distribution.

Particle size distribution of nanoemulsions can be controlled by changing

system composition as well as preparation conditions. For example, in low energy

methods, particle size of nanoemulsions depend on different factors, including

composition of systems (e.g. ionic strength, type of surfactant and surfactant-oil-

water ratio) and environmental conditions (e.g. stirring speed and temperature-time

history) (Anton and Vandamme, 2009). In high energy approaches, nanoemulsions

droplet size depends on duration and intensity of energy input, relative viscosities

of continuous and disperse phases, interfacial tension, as well as nature and

concentration of surfactants (Jafari et al., 2007; Mahdi Jafari et al., 2006). Smaller

droplet of nanoemulsions can be produced by the intensity as well as duration of

homogenization, controlling viscosity ratio and using higher concentration of

surfactants (Schubert and Engel, 2004; Wooster et al., 2008). After the preparation

of nanoemulsions, stabilization of nanoparticles is mandatory to avoid and

undesirable change in particle dimensions during their utilization or storage.

The droplet size of nanoemulsions can be measured through dynamic light

scattering techniques. These techniques are based on measurement of translational

diffusion coefficient of droplets determined by analyzing the interaction between a

laser beam and nanoemulsions (Leung et al., 2006). Hydrodynamic diameter can be

calculated using Stokes-Einstein equation: (DH = kT/6πηD). Where DH represent

hydrodynamic diameter, k represent Boltzmann’s constant, D is coefficient of

translational diffusion, η indicate viscosity and T is absolute temperature. The two

most commonly used translational diffusion coefficient based methods are photon

18

correlation spectroscopy and doppler shift spectroscopy (Kaszuba et al., 2008).

2.3.4 Interfacial Properties

Interfacial characteristics of particles can be controlled in order to design

nanoemulsions with desirable functional attributes (Mason et al., 2006). Important

interfacial properties of particles which have pronounced effect on the functional

properties of nanoemulsions are rheology, interfacial permeability, environmental

responsiveness and interactions. Some surface active material creates interfacial

layer which is rigid and closely packed. Hence, it prevents the diffusion of other

components such as mineral oils, lipids and enzymes. On the other end, some

surface active molecule can be used to prepare interfacial layer with dynamic and

open structure which allow the passage of other molecules. In principle, selectively

permeable interfacial layers can be designed by careful selection of surface active

molecules (Mcclements et al., 2007).

Interaction of nanoemulsions particles with other surfaces and particles can be

prevented by controlling particle charge. For example, negatively charged particle

tends to stick with positively charged droplets and vice versa. Hydrophilic polymer

such as polyethylene glycol can be attached to particles for surface modification

which change their stealth character in human body (Howard et al., 2008). Particles

which are hydrophilic in nature are less susceptible to removal by natural defense

which increase particle residence time in systemic circulation. Surface active

polymers with non-polar characteristics (thermal or surface denatured globular

protein) can be used to increase the hydrophobicity of particle surface (Hashida et

al., 2005).

In nanoemulsions, interfacial properties of nanoemulsions can be controlled

19

using a particular type of emulsifiers, such as particular protein, surfactant,

polysaccharide or phospholipids. For example, fluid-like thin layers can be formed

using smaller molecule surfactants, thick fluid like layers can be formed using

biopolymers and thin elastic type layer can be formed using globular protein (soy

or whey protein) (Dickinson, 2003; Dickinson, 2009). Interfacial characteristics can

also be controlled using a combination of emulsifiers instead of using a single

emulsifier. Finally, another method for alteration of the interfacial characteristic is

the deposition of charged biopolymers successive layers on oil droplets containing

opposite charge to create nanolaminated coating having different environmental

responsiveness, charge or thickness (Guzey and Mcclements, 2006; Johnston et al.,

2006).

2.3.5 The Physical State of Particle

Usually, nanoemulsions are formulated using liquid oils, but these can be

prepared using lipids which are partially or fully crystallize at final temperature of

their usage (Weiss et al., 2008). During this situation, liquid state of lipid phase is

used during nanoemulsion preparation i.e., temperature should be more than lipid

melting point. After preparation, oil droplets of nanoemulsions are crystallized by

cooling them below their melting temperature (Mehmood et al., 2017; Wissing et

al., 2004). This approach can be used for the preparation of nanostructured lipid

carriers or solid lipid nanoparticles. These are nanoemulsions with partly or fully

solidify oil phase (Mller et al., 2004).

2.4 DROPLET BREAKUP IN NANOEMULSIONS

In general, shearing processes are used for the preparation of nanoemulsions

(Walstra, 1993). The droplet size of nanoemulsion depends on the two processes

20

which are occurred in homogenizer i.e. break-up of droplets and re-coalescence of

droplets (Jafari et al., 2008). The mechanical devices which have capacity to

generate intense disruptive forces are suitable for nanoemulsion preparation i.e.

ultrasonic devices, microfluidizers and high pressure homogenizers (Tadros et al.,

2004). These high intensity disruptive forces are required to overcome restorative

forces in order to maintain the spherical shape of nanoemulsion droplets (Schubert

and Engel, 2004). A useful tool for the calculation of these disruptive forces is

Laplace Pressure (∆P = γ/2r). The values of Laplace Pressure decreases with

increase in droplet radius and decreasing interfacial tension. Hence, when the

radius of droplets become smaller in homogenizer, it becomes more difficult to

break them further. Additionally, the droplet radius can be predicted using Taylor

equation e.g. r ∝ γ/ ηcγ0. Where γ represent interfacial tension, ηc indicate viscosity

of continuous phase and γ0 is shear rate (Taylor, 1934).

The droplet size of nanoemulsions produced using high energy approaches

depends on design of homogenizer (e.g. force and flow profile), environment (e.g.

temperature), and operating condition of homogenizer (e.g. duration and energy

intensity), physical and chemical properties of component (e.g. viscosity and

interfacial tension) and sample composition (e.g. surfactant concentration,

surfactant type and oil type) (Wooster et al., 2008). Previous studies demonstrated

that the droplet size of nanoemulsions decreased with increase in energy duration

or intensity, decrease in interfacial tension, higher concentration of emulsifier and

certain range of disperse to continuous phase viscosity ratio e.g. 0.05-5 (Tadros et

al., 2004; Walstra, 1993). The range of viscosity ratio which can produce smaller

21

droplets of nanoemulsions depends on type of disruptive forces generated by

homogenizer e.g. extential flow verses simple shear.

Surfactants play an important role in droplet break-up as well as droplet

coalescence. Surfactants help to reduce the droplet size of emulsions by lowering

the value interfacial tension which reduces the resistant against droplet deformation

(Walstra, 1993). Surfactants also prevent the re-coalescence of droplets through

adsorption and stabilization of interface. For this purpose, enough emulsifier

should be present in continuous phase to adsorb on newly formed interface.

Additionally, surfactants with smaller molecules are more desirable for the

preparation of nanoemulsions as compared with larger molecules due to their rapid

adsorption to interfaces and lower interfacial tensions (Leong et al., 2009).

2.5 ADVANTAGES OF NANOEMULSIONS OVER CONVENTIONAL

EMULSIONS

2.5.1 Antimicrobial Activity

Some antimicrobial agents are soluble in water and we cannot incorporate them

into lipid-based products. On the other end, some antimicrobial agents are only

soluble in oil, so they cannot be incorporated into aqueous products. The usability

and effectiveness of these compounds can be increased by encapsulating them in

nanoemulsions. These antimicrobial agents can be encapsulated into amphiphilic

exterior or hydrophobic interior of lipid phase or both (Jochen et al., 2009). The

activity of encapsulated antimicrobial agents depends on the transportation of these

materials from nanoemulsions to bacterial surface. Two different mechanisms may

be involved in this process: (1) direct interaction of droplets and microorganisms or

(2) diffusion of molecules through aqueous phase. Due to smaller droplet size,

22

nanoemulsions can increase the antimicrobial activity against microorganisms in

many different ways. Firstly, due to Laplace effect higher concentration of

antimicrobial agents are present at droplet surfaces which increase the mass

transport into aqueous phase (Mcclements, 2011). Laplace pressure indicates the

difference of pressure between inside and outside of air bubble or droplet. This

Laplace effect is caused due to surface tension between droplet liquid and bulk

liquid interface. It will partition more solute into aqueous phase by keeping

droplets in spherical shape. It acts across the oil-water interface toward the center

of the droplet so that there is a larger pressure inside the droplet than outside of it:

∆PL = 4γ/d. Where γ is interfacial tension and d is droplet diameter (Gupta et al.,

2016). Secondly, the interaction between droplets and microorganism is increased

due to increase in Brownian motion of smaller droplets. Thirdly, nanoemulsions

increased the penetration of antimicrobials into bacterial surfaces by facilitating

their penetration into biological membranes. Despite the potential application of

nanoemulsions based delivery system for delivery of antimicrobial agents, there

benefits over conventional emulsions are not clear due to lack of consistent data.

Some studies reported that the efficiency of nanoemulsions based delivery system

for antimicrobial agents decreased due to smaller particle size due to the adsorption

of antimicrobial at droplet surface instead of microorganisms (Salvia-Trujillo et al.,

2017).

2.5.2 Lipophilic Components Encapsulation

Nanoemulsions are used in beverages and food industry for the

encapsulation of lipophilic components such as colors, flavors, vitamins,

nutraceuticals, preservatives and antioxidants (Given, 2009; Graves and Mason,

23

2008). These components are encapsulated to increase their solubility and

bioavailability, protect them from degradation, incorporate them into food

products, ease of utilization and to control release rate (Mcclements and Rao,

2011). We can also introduce lipophilic compounds into clear or slightly turbid

products without altering their appearance. Numerous types of nanoemulsions have

been developed to encapsulate a variety of lipophilic compounds such as, citral

(Mei et al., 2009), β- carotene (Yin et al., 2009), fat-soluble vitamins (Hatanaka et

al., 2010) and co-Enzyme Q (Ozaki et al., 2010).

Lipophilic components are solubilized in oil prior to emulsification so that

these compounds are trapped within lipid phase during nanoemulsion preparation.

The location of hydrophobic compounds in nanoemulsions depend on

physicochemical and molecular properties, such as surface activity, surface

hydrophobicity, melting point, solubility and partition coefficient between oil-

water. The location of lipophilic compound exerts significant effect on physical as

well as chemical stability of nanoemulsions. For example, chemical degradation

starts in lipophilic compounds when they come in contact with polar compounds.

So, it is important for their stability that lipophilic compounds should be trapped

into oily phase rather than shell (Mcclements, 2011). In the previous study, when

citral (component of flavor molecule) come in contact with proton of water,

chemical degradation start in citral molecules which effect on the stability of

nanoemulsions (Mei et al., 2009).

2.5.3 Control Delivery and Increased Bioavailability of Lipophilic

Components

A number of previous studies reported that bioavailability of bioactive

24

component encapsulated into nanoemulsions increased due to smaller size of

nanoemulsions (Acosta, 2009). This increased in bioavailability is due to different

reasons. Firstly, nanoemulsion droplets have larger surface area. Due to this,

digestive enzyme acts more quickly on nanoemulsion as compared to

nanoemulsions which lead to easy absorption and rapidly release of encapsulated

material. Secondly, smaller droplets of nanoemulsions can penetrate into mucous

layer of epithelium cells in small intestine which increase residence time and they

reached closure to absorption sites. Thirdly, smaller droplets of nanoemulsions can

be transported directly through paracellular or transcellular mechanisms across

epithelium cells (Mcclements, 2011). Additionally, partition into aqueous phase

may be greater due to Laplace pressure which results in higher water solubility of

lipophilic components. Presently, there is a poor understanding about the

significance of these mechanisms for food grade nanoemulsions with different

surface characteristics, composition and droplet size.

Recently, some researchers reported that the bioavailability of curcumin

nanoemulsions can be increased by encapsulating them into nanoemulsions (Huang

et al., 2010; Wang et al., 2008). Various studies confirmed that nanoemulsions are

associated with increased bioavailability of lipophilic components in

pharmaceuticals and nutraceuticals (Hatanaka et al., 2010; Ozaki et al., 2010;

Talegaonkar et al., 2010). Furthermore, nanoemulsions can be effectively used for

the target delivery of bioactive components within human body which results in

improved efficiency (Huang et al., 2010; Salvia-Trujillo et al., 2017).

2.5.4 Improved Stability of Nanoemulsions

Nanoemulsions have smaller droplet size which gives them stability against

25

coalescence, flocculation and gravitational separation. Due to this, the shelf-life of

nanoemulsion containing food products is increased. However, nanoemulsions

should be carefully designed to avoid Ostwald ripening because these are degraded

by this mechanism. This problem can be prevented by using carrier oil which have

lower solubility in water (Li et al., 2009; Wooster et al., 2008) or restricting droplet

size changes through controlling interfacial layer properties (Mun et al., 2006).

Additionally, smaller droplet size of nanoemulsions can promote chemical

degradation of lipophilic components which are encapsulated into nanoemulsions

(Mao et al., 2009). Nanoemulsions have larger surface area as compared to

conventional emulsions which lead to greater chemical degradation such as lipid

oxidation. Additionally, visible and UV light can easily penetrate through

transparent nanoemulsions which can promote chemical degradation due to light-

sensitive reactions. Hence, additional steps may be required to protect the bioactive

components which are encapsulated into nanoemulsions such as addition of

chelating agents or antioxidants.

2.5.5 Modification of Texture

Nanoemulsions have very smaller size droplets due to which interfacial coating

around droplets constitute appreciable proportion of the overall volume of droplets.

As a result of this, it might be possible than nanoemulsion promotes gelation

reactions at lower oil concentration as compared to conventional emulsions. These

properties are desirable in preparation of the products which required gel-like or

viscous appearance such as reduced fat products. Currently, nanoemulsions are not

exploited for the texture modifications of food products. However, some studies on

non-food grade system reported that electrostatic repulsion effect can be used for

26

the preparations of nanoemulsions with transparent look and gel-like characteristics

(Kawada et al., 2010). The present approach may be used for the preparation of

visco-elastic and highly viscous nanoemulsions using lower oil concentrate as

compared to conventional emulsions (Wilking and Mason, 2007).

2.6 BIOLOGICAL FATE AND BIOAVAILABILITY OF

NANOEMULSIONS

During digestion biochemical process occurs in gastrointestinal tract (Golding

and Wooster, 2010). Salts present in the mouth affect the ionic strength of

nanoemulsions and change its stability. Presence of mucin in saliva causes droplet

aggregation by depletion flocculation or bridging. When these nanoemulsions

droplets reach stomach, their aggregation properties are further changed due to

shear conditions, lower pH and higher ionic strength (Salvia-Trujillo et al., 2017).

Gastric lipase present in stomach causes hydrolysis in smaller fraction of lipid, but

majority of lipid is digested in smaller intestine by pancreatic lipase. Emulsifier

molecules displaced from water-oil interface due to the presence of bile salts in

gastrointestinal fluid causes enzyme binding (Reis et al., 2009). During lipid

digestion, free fatty acids, as well as monoglycerols, are generated which are

accumulated on the surface of the oil. Later on, the products of lipid digestion are

removed through bile salts by solubilizing these products in mixed micelles, which

facilitate complete digestion of lipids. Furthermore, calcium ions react with long

chain free fatty acids and form insoluble soaps and facilitating their removal from

oil surface. Finally, lipolysis products and lipophilic compounds (encapsulated in

nanoemulsion) are solubilized in unilamellar phospholipids vesicles or mixed

micelles which are absorbed across the intestinal lumen. Additionally, lipolysis

27

reaction can be interrupted by long-chain free fatty acid and monoglycerols due to

their higher surface activity (Salvia-Trujillo et al., 2017).

Deep understanding regarding gastrointestinal processes is compulsory for

designing nanoemulsions with higher bioavailability and bioaccesibility of

bioactive compounds. Previous researchers proved that co-administration of

lipophilic compounds along with oily face increase their absorption after digestion

(Pouton and Porter, 2008). For example, Yu and coworkers (2012) reported that

bioavailability of curcumin encapsulated in nanoemulsions was increased nine fold

as compared to their crystalline form. Additionally, type of lipid carriers and

droplet size have pronounced effect on the bioavailability of encapsulated

compound. Several researchers reported that the bioavailability of encapsulated

bioactive compounds increased with smaller droplet size due to higher digestion of

lipid phase (Mcclements, 2011; Salvia-Trujillo et al., 2013). However, some

researcher reported that bioavailability of curcumin encapsulated in nanoemulsions

decreased as compared to conventional emulsions (Ahmed et al., 2012). This

decrease might be attributed due to higher chemical degradation of curcumin with

more oil-water interface. So, the nature of bioactive compounds which are

encapsulated in nanoemulsions has significant effect on the bioavailability. For

example, the bioavailability of carotenoids was higher when long-chain

triglycerides were used in nanoemulsions as compared to medium chain

triglycerides (Ahmed et al., 2012; Qian et al., 2012b). This effect may occur due to

the fact that larger hydrophobic core is required for the incorporation of larger

carotenoid molecules. Hence, medium chain free fatty acids containing smaller

hydrophobic core are unable to incorporate longer lipophilic compounds.

28

Nanoemulsions containing digestible lipids (e.g. triglycerides) are rapidly

digested in the gastrointestinal tract. However, they behave differently when they

contain indigestible lipid phase (such as flavor or mineral oil). Biological fate of

encapsulated material depends on the nature of hydrophobic material. Presently,

knowledge gap exists to understand the effect of individual ingredient on the

biological fate of nanoemulsions. Hence, more research is required for better

understanding of the biological fate of nanoparticles in gastrointestinal tract.

2.7 APPLICATION OF NANOEMULSIONS IN FOOD PRODUCTS

Nanoemulsions have a number of potential applications for incorporation of

lipophilic compounds into food products. Number of researchers highlighted the

advantages which are associated with the use of nanoemulsions as delivery system.

Oregano oil based nanoemulsions with droplet size of 150 nm was recently used to

retard the growth of food-borne pathogens in lettuce during their storage in

refrigerator (Bhargava et al., 2015). Nanoemulsions with cinnamaldehyde (droplet

size less than 200 nm) were found effective for deactivation of bacterial growth in

melon juice (Jo et al., 2015). Furthermore, soaking radish, alfalfa and mong been

seed in nanoemulsions containing carvacrol retarded the growth of Enteritidis,

Escherichia coli O157: H7 and Salmonella enterica without affecting their sprout

yield (Landry et al., 2015). Donsi and coworkers investigated the effect of

incorporation of tarpene containing nanoemulsion into pear and orange juice during

their storage at 32 °C for 16 days. They reported that lower concentration (1.0g/L)

of tarpene containing nanoemulsions delayed the growth of microorganisms

(Lactobacillus delbrueckii) while higher concentration (5.0g/L) completely

inactivated the bacterial growth without compromising the sensory properties of

29

fruit juice (Donsì et al., 2011a). Joe and coworkers (2012) observed that the shelf

life of fish steak can be increased by using sunflower oil based nanoemulsions.

They reported the significant reduction in the population of lactic acid, hydrogen

sulfide and heterotrophic bacteria as well as extension of shelf life during storage

as compared to control samples. Mate and others (2016) observed reduced growth

of Listeria monocytogens in vegetable cream and chicken broth treated with nisin

and D-limonene nanoemulsions. Ma and others reported that eugenol or thymol

nanoemulsions exhibit antimicrobial activity in low-fat milk emulsified with LAE

and lecithin (Ma et al., 2016a).

Limited examples are available for the incorporation of bioactive compound

loaded nanoemulsions into commercial food products. However, number of

researchers reported that nanoemulsions can significantly improve the

bioavailability of bioactive compound in different food products (Mehmood, 2015).

Several researchers observed that nanoemulsions increase the bioavailability of

carotenoids from tomato juice (Salvia-Trujillo and Mcclements, 2016), carrots

(Zhang et al., 2016), yellow peppers (Liu et al., 2015) and mangoes (Liu et al.,

2016). Although it is proved that nanoemulsion-based delivery system improved

the bioavailability of encapsulated compounds, more research is required is

required to prove that nanoemulsions are associated with improved bioavailability

of encapsulated materials in complex food matrices.

Although there is no strong scientific evidence which supports the advantages

of bioactive and antimicrobial systems, a number of food industries are using

nanoemulsion-based delivery system for the incorporation of lipophilic compounds

into their products. These compounds include lutein, lycopene, coenzyme Q10, β-

30

carotene, fat-soluble vitamins, omega three fatty acids, isoflavons and phytosterols.

In these cases, food manufacturer claimed the enhance bioavailability of active

ingredient after digestion as well as protection from harsh environmental condition

during food operations (Salvia-Trujillo et al., 2017).

Although, numbers of research studies are carried out to demonstrate the

increased bioavailability of lipophilic compounds which are encapsulated into

nanoemulsions based delivery system, it is the need of time to confirm this

evidence after food handling operations and incorporating these compounds into

complex food matrices. Hence, comprehensive approach is required in future

research on nanoemulsions to investigate the actual advantages which are

associated with nanoemulsions based delivery system. In future research, loss in

the functionality of encapsulated material due to processing, storage and effect of

food matrix should be considered. Furthermore, higher cost related to

nanoemulsions production should be considered due to the requirement of some

equipment and higher energy input.

2.8 POTENTIAL TOXICITY OF NANOEMULSIONS

Currently, very little experimental evidence are available regarding the

potential toxicity which is associated with food grade nanoemulsions. However,

scientists are convinced that a number of physicochemical reaction associated with

smaller droplet size may cause toxicity (Mcclements and Rao, 2011). Currently, no

standard protocol is available to test the toxicity of food-grade nanoemulsions

(Maynard et al., 2006). There is need of further research to investigate the potential

toxicity of nanoemulsions. Potential toxic effects of nanoemulsions are discussed in

this section.

31

2.8.1 Bioactive Compounds with Increased Bioavailability which are Toxic

at Higher Level

Bioavailability of bioactive components increased when their size is reduced to

critical level i.e. in the range of 100-1000nm (Acosta, 2009). Increased

bioavailability of many bioactive compounds are either desirable or have no

adverse effects. However, there are some potential hazards about the increased

bioavailability of some bioactive components that may exert toxic effects when

consumed at higher dose. If any of these components which normally lower

bioavailability are encapsulated into nanoemulsions, may exhibit toxic effects due

to increased bioavailability. These effects were more apparent when we incorporate

bioactive compound into those products which are regularly consumed such as

beverage and soft drink emulsions. Hence, this potential hazard should be

considered before designing of nanoemulsions based delivery system for bioactive

compounds.

2.8.2 Direct Absorption of Smaller Droplets

There are evidence that non-digestible nanoparticles, such as inorganic material

(silicon oxide and titanium dioxide) and metals (gold and silver) can directly cross

the epithelial layer by paracellular and transcellular mechanisms (De Jong et al.,

2008). After absorption, these nanoparticles may be digested, accumulated or

transported into systemic circulation through lymph or blood system (Hu et al.,

2009). The nanoparticles which are transported through epithelial cells are

circulated in the human body, where they may be metabolized, accumulated within

tissues or excreted from the body (Bouwmeester et al., 2009). These mechanisms

depend on physicochemical characteristic of nanoparticles like interfacial tension,

32

charge, shape, size and composition. Presently, no evidence is available which

suggest that the components of food-grade nanoemulsions are directly absorbed in

human body. Direct absorption occurs if indigestible materials (mineral oils and

hydrocarbons) are used for nanoemulsion preparation or indigestible shell (dietary

fiber) is used to coat nanoemulsions droplets. Further research is needed to clarify

that either this mechanism is important for humans or not.

2.8.3 Disturbance in Normal Gastrointestinal Functions

Droplets of nanoemulsions can alter the normal functionality of gastrointestinal

tract during their passage from mouth, stomach and small intestine due to smaller

droplet size, which can cause adverse health effects (Chaudhry et al., 2008). For

example, the possibility exist that these smaller droplets are directly absorbed via

epithelial cells in mouth, esophagus and stomach before their digestion into small

intestine. Smaller droplets have higher curvature and surface area and their surface

activity are also different from bulk materials, which can change the activity and

accumulation of lipase, salts and component of digestive systems at the surface of

droplet, thereby interfering in normal function of gastrointestinal tract. If we take

the example of protein absorption to particle surface, it may lead to loss in normal

functions and denaturation, which can cause adverse health effects on humans

(Hoet et al., 2004). These nanoparticles can attach to receptors of cell membranes

which lead to alteration in cellular metabolism and functions. Hence, it is

concluded that high-surface energy, higher surface area and smaller droplet size

can cause some unpredictable effects on biological systems which are different

from bulk form of this material (Jiang et al., 2009). Further research is needed to

understand the effect of nanoemulsions on gastrointestinal tract functions.

33

2.8.4 Effect of Composition

Some components of nanoemulsion can produce toxic effects when they are

consumed at the higher level e.g. solvents and emulsifiers. During the preparation

of nanoemulsions, surfactants are required in larger amount to cover larger surface

area of nanoemulsion droplets. Presently, small molecule surfactants (co-

surfactants are also used sometimes) are most widely used for the preparation of

food-grade nanoemulsions. These surfactants are used due to their ability to

spontaneous nanoemulsion preparation through low-energy methods (e.g. PIT

method), and reduction of interfacial tension and rapid absorption at droplet surface

in high-energy methods (e.g. ultrasonication). Natural surfactants, such as

phospholipids, proteins and polysaccharides are less effective for nanoemulsions

preparation. Smaller molecule surfactants can cause toxic effects on human health

when these are consumed in higher amount (He et al., 2010). Therefore, higher

amount of surfactant which is used in nanoemulsions preparation as compared to

nanoemulsions must cause some adverse effects on the health of humans.

During the nanoemulsions preparation through low-energy methods

(evaporation and solvent displacement methods) organic solvents are used which

include ethyl acetate, hexane and acetone (Horn and Rieger, 2001). Although, these

organic solvents are removed through evaporation during the preparation of

nanoemulsions, but some of their residues can remain in nanoemulsions which can

exert toxic effects. So, when we prepare nanoemulsions using organic solvents, the

toxic effect of the residues of that solvent should be considered. The data related to

potential toxicity of solvents and emulsifiers which are used for food grade

nanoemulsion preparations are available on the websites of different organizations

34

such as European Food Safety Authority, Food and Drug Administration and

World Health Organization. Before selection of suitable components for

nanoemulsions, potential toxicity and safe use level of those components should be

considered.

35

Chapter 3

MATERIALS AND METHODS

3.1 COLLECTION OF MATERIALS

RBD (Refined, Bleached and Deodorized) canola oil and olive oil were

purchased from Punjab Oil Mills, Islamabad, Pakistan. Tween 80 (food grade),

Tween 60 and lecithin were purchased from local scientific store. Beta carotene

and vitamin D2 were purchased from Sigma-Aldrich Co USA. Deionized and

distilled water was used in all the experiments.

3.2 CHARACTERIZATION OF NANOEMULSIONS COMPONENTS

The components of nanoemulsion (surfactants and cooking oils) were

characterized before preparation of nanoemulsions to investigate their effect on the

preparation and nanoemulsions stability. Density meter (DS7800, KRUSS,

Hamburg, Germany) was used to determine the density of nanoemulsion

components. Interfacial tension was measured using Tensiometer (DSA100,

KRUSS, Hamburg, Germany). Viscosity was measured through Viscometer

(KV100, Massachusetts, USA).

3.3 NANOEMULSIONS PREPARATION

Nanoemulsions were prepared by mixing 10 % dispersed phase and 90%

continuous phase. Dispersed phase was formulated by dissolving pre-determined

amount of encapsulated material (Beta carotene and vitamin D2) in vegetable oil

(canola oil and olive oil). Continuous phase consist of deionized water carrying

pre-determined amount of mixed surfactants. These components were mixed with

polytron (KRH-I, KONMIX, Shanghai, China) to prepare coarse emulsions. For

35

22

36

the preparation of nanoemulsions, these coarse emulsions were subjected to

ultrasonic homogenization by using 20 kHz sonicator (230VAC, Cole-Parmer,

USA). Ultrasonic homogenization was done by placing the tip horn (20 mm

diameter) of sonicator in coarse emulsions by applying different ultrasonic powers

for different times. The temperature of the emulsion was controlled by placing it in

ice bath during homogenization. These nanoemulsions were stored at room

temperature for further analysis.

3.4 PARTICLE SIZE ANALYSIS

The droplet size of the nanoemulsions was measured by dynamic light

scattering using nanotrac (Microtrac, Tri-Blue, USA). Particles in liquid

suspensions undergo continuous Brownian motion. These particles scatter light in

suspension and change the refractive index through localized changes. As a result

of this, intensity variation is produced which can be analyzed through

autocorrelation function: C(γ) = 1/N ΣN

i=1 I(ti) I (ti+τ). Where N is number of time

this procedure is carried out, I(t) represent intensity of photon and τ is scattering

pattern. Dilution of nanoemulsion is pre-requisite to avoid the effects of multiple

scattering (Leong et al., 2009). In this research, beta carotene and vitamin D

nanoemulsion samples were diluted to 10% using deionized water in order to avoid

multiple scattering effects. The droplet size of nanoemulsions was reported as

average diameter (D4,3).

3.5 OPTIMIZATION OF PREPARATION CONDITIONS FOR β-

CAROTENE NANOEMULSION

Response Surface Methodology (RSM) is a combination of statistical and

mathematical techniques to investigate the relationship between response variables

37

and input variables (Khuri and Mukhopadhyay, 2010). RSM is used for

improvement, development and optimization of processes in which desired

response variable is affected by several independent variables and there is a need to

optimization of this response. Additionally, it is also used for the design and

development of new product and for the design improvement of existing product.

RSM is applied in three stages: (1) selection of independent variables and their

levels, (2) experimental design selection along with prediction as well as

verification of model equation and (3) obtaining contour and response plot (Baş

and Boyacı, 2007).

RSM (Response surface methodology) was used to investigate the effect of

independent variables i.e. surfactant concentration (X1), ultrasonic homogenization

time (X2) and oil contents (X3) on response variables, such as droplet size (Y1), p-

Anisidine value (Y2) and retention of beta carotene (Y3) in nanoemulsions. On the

basis of our previous research findings and through review of literature, these

independent variables and responses were selected due to their significant effect on

the physico-chemical properties and stability of nanoemulsions. RSM design along

with coded and uncoded levels has been presented in Table 3.1. Central composite

design (Five levels) and quadratic model was used to design this experiment.

Twenty treatments, including six axial points, eight fractional factorial points and

six central points were randomly performed according to CCD (central composite

design) which has been summarized in Table 3.2. Real levels of independent

variables for beta carotene nanoemulsions were coded according to the equation

expressed below;

Z = Z0 –ZC / ∆Z (1)

38

Table 3.1: Independent variables for optimization of preparation conditions for β-

Carotene nanoemulsion

Independent variable Symbol Coded levels

-α -1 0 +1 +α

Surfactant concentration (%) X1 2.64 4 6 8 9.36

Homogenization Time (Min.) X2 2.98 4 5.5 7 8.02

Oil Content (%) X3 5.48 6.5 8 9.5 10.52

39

Table 3.2: Different combinations of independent variables for application of RSM

design for optimization of β- Carotene nanoemulsions

Treatments Mixed Surfactants

(%)

Homogenization Time

(Min.)

Oil Contents

(%)

T1 8 4 6.50

T2 6 5.50 8

T3 4 7 6.50

T4 6 5.50 5.48

T5 8 4 9.50

T6 6 8.02 8

T7 9.36 5.50 8

T8 6 5.50 10.52

T9 6 5.50 8

T10 6 5.50 8

T11 8 7 9.50

T12 8 7 6.50

T13 6 5.50 8

T14 6 5.50 8

T15 4 4 6.50

T16 4 4 9.50

T17 6 5.50 8

T18 2.64 5.50 8

T19 6 2.98 8

T20 4 7 9.50

40

Where Z and Z0 indicate coded and real levels of independent variables, ∆Z

represents step change and ZC indicates actual value at central point.

Specific equation for each independent variable was derived from above equation

to code their actual values. Specific equations for surfactant concentration (X1),

Ultrasonic Homogenization time (X2) and oil contents (X3) are mentioned in

equation 2-4:

z1 = (SC – 6) / 2 (2)

z2 = (HT – 5.5) / 1.5 (3)

z3 = (OC – 8) / 1.5 (4)

Where MS, HT and OC represent surfactant concentration, Homogenization time

and oil contents, respectively.

Second order polynomial equation was used to indicate the predicted

responses (droplet size, p-Anisidine value and retention of beta carotene) of mixed

surfactant based beta carotene nanoemulsions as a function of independent variable

as follows:

(5)

Where Z represents response values, indicate the values of linear,

quadratic and interactive coefficients, respectively and is constant. Design

expert software (version. 8.0.7.1) was used to calculate the value of coefficients of

determination.

3.5.1 p-Anisidine Value

p-Anisidine Value is an important indicator of the stability of nanoemulsions.

The oxidative stability of beta carotene nanoemulsions was measured according to

41

the method of Cho et al., (2008). Firstly, 20g of beta carotene nanoemulsion was

incubated for one week at 50 °C. Then, 1g solution was dissolved in n-Hexane

(HPLC Grade) and the absorbance of the solution was measured using UV-

Spectrophotometer at 350nm. After that, 1 mL p-Anisidine reagent (prepared by

dissolving 2.5g of p-Anisidine in one liter of acetic acid) was added in 5 mL of

solution and they were kept for 10 minutes to allow their reaction. Absorbance of

the fat solution was determined as blank in reference cell. p-Aniside value was

determined using following formula:

p-Anisidine Value = 25 × (1.2 AAR – ABR)

M

Where AAR is the absorption of the solution after reaction, ABR represents

absorption before reaction and M denote sample mass in grams.

3.5.2 Beta Carotene Retention

The concentration of beta carotene in nanoemulsions was determined through

spectrophotometric method according to the method of Yuan et al., (2008). Firstly,

1 ml sample was extracted using a mixture of n-Hexane (3ml) and ethanol (2ml).

After that, this mixture was shaken well and phase of hexane was removed. This

extraction procedure was repeated two times further. At the end all hexane phases

were combined and their absorbance was measured through UV-

Spectrophotometer at 450 nm after desired dilution with n-Hexane. The beta

carotene concentration was determined using standard curve prepared under similar

conditions. Vitamin retention was calculated using following formula:

VRBC = VBC,N/ VBC,I × 100

Where VRBC represent beta carotene retention, VBC,N is the concentration of beta

42

carotene in nanoemulsion and VBC,I indicate initial concentration of beta carotene .

3.6 OPTIMIZATION OF PREPARATION CONDITIONS FOR

VITAMIN D NANOEMULSION

A three-factor central composite design (CCD) was used to investigate the

effect of Ultrasonic Homogenization time (X1), surfactant to oil ratio (X2) and

disperse phase volume (X3) on three response variables: droplet size (Y1), droplet

growth ratio (Y2) and vitamin D retention (Y3) in nanoemulsions. On the basis of

our previous research findings and through review of literature, these independent

variables and responses were selected due to their significant effect on the physico-

chemical properties and stability of nanoemulsions. Actual and coded levels of

independent variables are summarized in Table 3.3. The preparation conditions of

nanoemulsion were optimized through three-factor (Five levels) central composite

design and quadratic model. Central composite design was comprised of twenty

treatments, including 6 axial points, 6 central points and eight fractional factorial

points and experiment was randomly performed according to CCD which has been

summarized in Table 3.4. Actual values of independent variables were coded

according to the equation 6:

Y = Y0 –YC / ∆Y (6)

Where Y and Y0 represent coded and actual levels of independent variables,

respectively. ∆Y represents step change while YC indicates actual value at the

central point.

Specific equation for each independent variable was derived from above

equation to code their actual values. Specific equations for surfactant concentration

(X1), Homogenization time (X2) and oil contents (X3) are mentioned below.

43

Table 3.3: Independent variables for optimization of ingredient level for vitamin D

nanoemulsions


-α -1 0 +1 +α

Homogenization Time (Min.) X1 2.48 3.5 5 6.5 7.52

Surfactant to oil ratio (S/O) X2 0.311 0.430 0.605 0.780 0.899

Disperse phase volume (%) X3 6.32 7 8 9 9.68

44

Table 3.4: Different combinations of independent variables for application of RSM

design for optimization of vitamin D nanoemulsions

Treatments Homogenization Time

(Min.)

Surfactant to Oil

Ratio

Disperse Phase Volume

(%)

T1 5 0.605 9.68

T2 5 0.899 8

T3 6.5 0.780 7

T4 5 0.605 8

T5 3.50 0.780 9

T6 3.50 0.430 9

T7 5 0.605 8

T8 6.50 0.780 9

T9 7.52 0.605 8

T10 2.48 0.605 8

T11 3.50 0.780 7

T12 5 0.605 8

T13 6.50 0.430 7

T14 5 0.605 8

T15 5 0.605 8

T16 3.50 0.430 7

T17 5 0.311 8

T18 5 0.605 8

T19 5 0.605 6.32

T20 6.50 0.430 9

45

(7)

(8)

(9)

Where HT, S/O and DPV represents homogenization time, surfactant to oil ratio and

dispersed phase volume, respectively.

The generalized RSM model for expressing variation in response variables

(droplet size, droplet growth ratio and vitamin D retention) as a function of

independent variable is summarized in equation:

(10)

Where Y represent predicted response values, indicate the values of

regression coefficients for intercept, linear, quadratic and interaction, respectively.

Design expert software (version. 8.0.7.1) was used to design experiment, analysis

of data and model building.

3.6.1 Droplet Growth Ratio (DGR)

The stability of nanoemulsions depends on many processes. In our study,

the stability of vitamin D nanoemulsions was measured in term of droplet growth

ratio (DGR). As there is a tendency of droplet aggregation in nanoemulsions during

storage, we can determine nanoemulsion stability by measuring the increase in

droplet size during storage. The droplet growth ratio was determined by comparing

the droplet size after nanoemulsion preparation with droplet size after 14 days of

storage (Mehmood, 2015). Droplet growth ratio was determined using below

mentioned equation:

Droplet Growth Ratio = Droplet size after two weeks – Droplet size at zero day

Droplet size at zero days

46

The droplet size of mixed surfactant based nanoemulsions were reported in the

form of D4,3.

3.6.2 Vitamin D2 Retention

The retention of vitamin D2 in nanoemulsions was determined through

spectrophotometric method by following the method of Khalid et al., (2017).

Firstly, nanoemulsion sample (1ml) was extracted using 9 ml of n-Hexane and after

that; this sample was ultrasonicated for 20 minutes at 100 kHz. Then, the sample

was centrifuged at 9000 rpm for 15 min. Aliquot of supernatant (1 ml) was diluted

five times with n-Hexane and the absorbance was measured at 310 nm. For blank

measurement n-Hexane was used. Vitamin retention was calculated using

following formula:

VRD2 = VD2,N/ VD2,I × 100

Where VRD2 represent beta carotene retention, VD2,N is the concentration of

beta carotene in nanoemulsion and VD2,I is initial concentration of beta carotene .

3.7 CHARACTERIZATION OF NANOEMULSIONS

Optimized treatments of mixed surfactant based beta carotene and vitamin D

nanoemulsions were characterized for their physicochemical parameters such as

droplet growth ratio, storage stability, p-Anisidine value and turbidity. Details of

these parameters are given below:

3.7.1 Storage Stability

The storage stability of nanoemulsion samples was determined by measuring

particle size of beta carotene and vitamin D nanoemulsions after every week for the

duration of two months. The storage stability of nanoemulsions was determined at

two different temperatures i.e. 4°C and 25°C.

47

3.7.2 Turbidity Measurement

The turbidity of nanoemulsions was determined through spectrophotometric

method by using UV-visible spectrophotometer (S-200D) at 600 nm. Turbidity

changes were recorded as described by Rao and Mcclements, (2011). Turbidity of

beta carotene and vitamin D nanoemulsions was measured after every week for the

duration of two months. The turbidity of nanoemulsions was determined at two

different temperatures i.e. 4°C and 25°C

3.8 FACTORS AFFECTING SELECTIVE PARAMETERS

The stability of optimized conditions against different factors was carried out

for the following parameters:

3.8.1 Effect of pH

Freshly prepared nanoemulsion samples (optimized conditions) were placed

in 50 ml beakers and pH of these samples was adjusted between 2 to 8. After that,

these samples were stored in test tubes at ambient temperature. After storage (12

hours), particle size, and creaming stability of these samples were measured

according to the method given by Ozturk et al., (2014).

3.8.2 Effect of Ionic Strength Variation

Freshly prepared beta carotene and vitamin D nanoemulsion sample (optimized

conditions) was adjusted for salt concentration (50-400 mM) by adding 1M NaCl

or buffer solutions. These samples were subjected to vortex, followed by storage at

ambient temperature for 12 hours. The particle size and creaming stability was

measured after desired time according to the method given by Ozturk et al., (2014).

3.8.3 Thermal Stability

Freshly prepared nanoemulsion samples (optimized conditions) were

48

transferred to glass test tubes and these test tubes were kept at different

temperatures (30-90 °C) in water bath. These samples were mixed and stored for

48 hours prior to their analysis for particle size and creaming stability by following

the method of Ozturk et al., (2014).

3.8.4 Physical Stability

Selected nanoemulsion formulations (optimized conditions) were subjected

to alternate freeze and thaw cycle (12 h) for 4 cycles to determine their physical

stability. The samples were stored in plastic bottles for 12 h at -18 ºC and

subsequently at room temperature (25 ºC) for 2 hour duration. After that, particle

size was determined before subjecting these nanoemulsions to next cycle. Particle

size analyzer was used for measuring stability, transparent appearance and particle

size as described by (Donsì et al., 2011c).

3.9 ANIMAL STUDIES

3.9.1 In Vivo Toxicity of Encapsulated Beta Carotene

Albino mice were used as test animals to investigate the toxic effects of

nanoparticles. These mice (n = 30) with initial body weight of 25± 5 g were

purchased from National Institute of Health (NIH), Islamabad. The sample size was

selected on the basis of power analysis. Power calculations were done using G

power software. These mice were acclimatized for one week before the start of

experiment. During experiment, mice were housed in controlled temperature 27±3

with 12 hours of light-dark cycle and free access was provided to water and food

(beta carotene or vitamin A deficient food). Iso-caloric diet was provided to all

mice. In addition to standard diet, these mice were given nanoemulsions containing

different concentration of beta carotene. These mice were randomly divided into

49

six groups: Group A (control group), Group B (oral dose of blank nanoemulsion

(without beta carotene), Group C (oral dose of vitamin beta carotene nanoemulsion,

9000 IU/Kg body weight), Group D (oral dose of beta carotene nanoemulsion,

12000 IU/Kg body weight), Group E (oral dose of beta carotene nanoemulsion,

16000 IU/Kg body weight) and Group F (oral dose of fat soluble beta carotene,

9000 IU/Kg body weight). These animals were monitored against the sign of

toxicity and changes in weight. After 21 days, blood samples of these animals were

collected to investigate their biochemistry and hematology (Sonaje et al., 2009).

All research was carried out in strict compliance with the approved protocols of

PMAS-Arid Agriculture University Institutional Animal Care and Use Committee.

Approval from ethical committee is given in appendix 1.

3.9.2 In Vivo Toxicity of Encapsulated Vitamin D

Albino mice were used as test animals to investigate the toxic effects of

nanoparticles. These mice (n = 30) with initial body weight of 27±5 g were

purchased from National Institute of Health (NIH), Islamabad. The sample size was

selected on the basis of power analysis. Power calculations were done using G

power software. These mice were acclimatized for one week before the start of

experiment. During experiment, mice were housed in controlled temperature 27±3

with 12 hours of light-dark cycle and free access was provided to water and food

(vitamin D deficient food). Iso-caloric diet was provided to all mice. In addition to

standard diet, these mice were given nanoemulsions containing different

concentration of beta carotene. These mice were randomly divided into six groups:

Group A (control group), Group B (oral dose of blank nanoemulsion (without

vitamin D), Group C (oral dose of vitamin D nanoemulsion, 1800 IU/Kg body

50

weight), Group D (oral dose of vitamin D nanoemulsion, 2500 IU/Kg body

weight), Group E (oral dose of vitamin D nanoemulsion, 3000 IU/Kg body weight)

and Group F (oral dose of fat-soluble vitamin D, 1800 IU/Kg body weight). These

animals were monitored against the sign of toxicity and changes in weight. After

21 days, blood samples of these mice groups were collected in order to investigate

nuclear abnormalities as well as genotoxicity. All research was carried out in strict

compliance with the approved protocols of PMAS-Arid Agriculture University

Institutional Animal Care and Use Committee. Approval from ethical committee is

given in appendix 1.

3.9.3 Nuclear Abnormalities Analysis

Before the separation of lymphocytes from whole blood, smear slides were

prepared using cleaned and new glass slides. Later on, these slides were fixed using

methanol for 10 minutes and left for air drying at room temperature. After that,

these slides are stained using 6% May Grunwald-Giemsa in Sorenson Buffer (pH is

adjusted to 6.9). Five slides were prepared for each experimental animal and these

slides were labeled and scored blindly under magnification of 1000X. 100

lymphocytes were observed on each slide and the percentage of bi-nuclear and

multi-nuclear lymphocytes were reported as follows:

Bi-nuclear or Multi-nuclear (%) = Damaged Cells/ Total Cells x 100

3.9.4 Comet Assay

Comet assay is a rapid, simple and sensitive technique for detection of damage

in DNA (DNA-protein and DNA-DNA crosslinks and single or double strand

break) for single cells (Fairbairn et al., 1995). Hence, it is a useful tool for the

investigation of genetic toxicology. Mostly this technique was used for mammalian

51

cells but some studies are also carried out on other organisms (Klobučar et al.,

2003).

Comet assay was performed by following the guidelines and

recommendation of previous studies (Singh et al., 1988; Smith et al., 2008). Fully

frosted slides were covered using 100 μl of 0.9% HMP agarose. Meanwhile,

lymphocyte suspension (25 μl) was added to 0.8% low melting agarose. This

mixture was poured on precoated slides containing HMP agarose layer and allowed

to polymerize for 10 min. at 4 °C. After solidification of gel, these slides (coverslip

removed) were immersed in cold lysis solution (2.5 M NaCl, 10mM Tris-HCl, 100

mM Na2EDTA, DMSO 10% and 1% Triton X-100) at 4 °C for 1.5 hours. After

that, deionized water was used for the washing of these slides (3-4 times). These

slides were then kept in alkaline buffer (300 mM NaOH, 1 mM Na2EDTA; pH

value 13) at room temperature for 30 minutes for unwinding of DNA.

Electrophoresis was performed at 320 mA for 25 minutes on horizontal platform by

using ice-cold and fresh alkaline buffer. After that, slides were drained and slowly

washed with neutralization buffer (Tris-HCl (0.4M with 7.5 pH) for 5 minutes. The

whole neutralization procedure was performed three times. Artefactual damage of

DNA was minimized by performing comet assay in dim-light and covering of

electrophoresis tank with black paper. For positive control, control group

lymphocytes were treated H2O2 (150 μM) for one hour at the temperature of 4 °C.

3.9.4.1 Procedure for staining

Slides were stained with 10% ethidium bromide for ten minutes. After that,

excessive ethidium bromide was taking out by curving these slides in chilled

distilled water. Subsequently, coverslips were placed over these slides. Gel drying

52

was prevented during slide scoring by placing slides in dark humidified chamber.

Scoring of slides was performed within 5 hours after staining.

3.9.4.2 Slides scoring

Analysis of slides was performed using Ceti Magnum-T epifluorescence

microscope equipped with 460-550 nm excitation filters. 40X objective lens were

used to capture microphotographs. DNA damage was quantified in term of tail

length, tail DNA and olive moment. The data was obtained from 500 randomly

selected cells from each group of animals.

3.10 DEVELOPMENT OF BETA CAROTENE AND VITAMIN D

FORTIFIED BEVERAGES

Model beverages were developed with added beta carotene and vitamin D.

Firstly, 8% sucrose, 0.1% ascorbic acid and 0.16% citric acid were mixed with

71.67% of water. Then, orange flavor (0.07%) and beta carotene or vitamin D

nanoemulsions (20 g) were being added. After that, all ingredients were thoroughly

mixed using magnetic stirrer. Beta carotene and vitamin D nanoemulsions were

prepared by following the method which is mentioned in nanoemulsion preparation

section. Final concentrations of beta carotene and vitamin D in nanoemulsions were

0.05 mg/ml. These model beverages were filled in sterilized glass bottles. After

that, these beverages were analyzed through visual appearance, pH, viscosity and

°Brix (Kim et al., 2014).

3.10.1 Viscosity

Viscosity of beta carotene and vitamin D fortified beverages was measured

using digital viscometer (DVE, Brookfield, USA). Viscosity was measured at 100

rpm using spindle no 2.

53

3.10.2 °Brix

°Brix of beta carotene and vitamin D fortified beverages was measured using

handheld refractometer (Master-50H, Atago, USA).

3.10.3 Sensory Evaluation

The sensory evaluation of the beta carotene and vitamin D fortified

beverages was conducted by a panel of trained judges. These beverages were

evaluated against different attributes such as taste, flavor, color and overall

acceptability. Fortified beverages samples were scored against nine point hedonic

scale which is given in appendix 2 (Larmond, 1977).

3.11 STATISTICAL ANALYSIS

For the optimization of the preparation conditions of nanoemulsions,

response surface methodology was used. Experimental data was analyzed through

analysis of variance (ANOVA) and Tukey HSD test. All these measurements were

performed three times and the results of these measurements were reported as

means and standard deviation and interpreted as described by Steel and Torrie,

(1980).

54

Chapter 4

RESULTS AND DISCUSSIONS

4.1 CHARACTERIZATION OF NANOEMULSION COMPONENTS

Physico-chemical properties of different components of nanoemulsions are

summarized in Table 4.1. Canola oil has lower viscosity (51.60 ± 0.8 mPa s) as

compared to olive oil (78.60 ± 1.1 mPa s). As a result of this, smaller droplet size

nanoemulsion will be produced in the case of canola oil as compared to olive oil.

The viscosity ratio between disperse and continuos phase has pronounced effect on

the droplet size of nanoemulsion. Smaller droplets were produced when the value

of viscosity ratio is closure to unity (Walstra, 1993). Furthermore, the viscosity

difference can be minimized by variation in surfactants. Canola oil has more

density (920 ± 1 kg m-3

) as compared to olive oil (915 ± 1 kg m-3

). Hence, canola

oil based nanoemulsions will be more stable because of the gravitational separation

of nanoemulsions which depend on density difference between continuous and

disperse phase(Mcclements, 2011). Nanoemulsion prepared from canola and olive

oil will be stable against gravitational separation due to smaller density difference

between aqueous and disperse phase. Additionally, that difference can be further

minimized by using Tween 80 and soy lecithin which lead to development of

nanoemulsions which are stable against gravitational separation. Interfacial tension

also influences the droplet size on nanoemulsions. Interfacial tension value of olive

oil (33.7 ± 0.9 mN m-1

) was higher than canola oil (28.5 ± 0.6 mN m-1

). As a result

of this, higher droplet size will be produced in olive oil based nanoemulsion as

compared to canola oil. When the value of interfacial tension was higher, the larger

droplets were produced due to more energy requirements (Mehmood, 2015).

54

55

Table 4.1: Physicochemical properties of different components of beta carotene and

vitamin D nanoemulsions

Components Viscosity

(mPa s)

Density

(kg m-3

)

Interfacial tension

(mN m-1

)

Canola Oil 51.60 ± 0.8 920 ± 1 28.5 ± 0.6

Olive Oil 78.60 ± 1.1 915 ± 1 33.7 ± 0.9

Tween 80 373 ± 1.6 1088 ± 1 --------------

Lecithin 8000 ± 3.5 1059 ± 1 --------------

56

Surfactants have the ability to lower down interfacial tension and creation of

smaller droplets (Mehmood, 2015).

4.2 OPTIMIZATION OF BETA CAROTENE NANOEMULSIONS

4.2.1 Fitting the Model

Response surface methodology (RSM) is a statistical, theoretical and

mathematical technique for model building in order to optimize the level of

independent variables (Homayoonfal et al., 2015). The effect of independent

variables on droplet size (Y1), p-Anisidine value (Y2) and retention of beta carotene

(Y3) have been presented in Table 4.2. Coefficients of polynomial equation were

computed from experimental data to predict the values of response variable.

Regression equations for each response variable, obtained from response surface

methodology are mentioned in equation 11-13:

Droplet Size = +114.85 – 5.44X1 - 8.01X2 + 2.55X3 + 6.13X12 – 3.95X2

2 +

0.82X32 – 2.88X1X2 - 1.38X1X3 - 0.88X2X3 (11)

p-Anisidine Value = +3.66 – 1.48X1 + 0.64X2 + 1.31X3 + 0.41X12 + 0.43X2

2 +

0.69X32 – 0.038X1X2 + 0.19X1X3 - 0.037X2X3 (12)

β-Carotene Retention = +79.43 + 9.82X1 – 2.42X2 - 3.21X3 - 3.21X12 –

4.27X22 + 2.09X3

2 – 2.37X1X2 - 0.87X1X3 + 0.38X2X3 (13)

Statistical analysis (ANOVA) results revealed that the experimental data

could be represented well with quadratic polynomial model with the coefficient of

determination (R2) values for droplet size (Y1), p-Anisidine value (Y2) and

retention of beta carotene (Y3) being 0.9456, 0.9580 and 0.9604, respectively

(Table 4.3). Lack of fit was non-significant (p≤0.05) relative to pure error for all

57

Table 4.2: Effect of independent variables on responses for mixed surfactant based

β-carotene nanoemulsions

Run

Independent Variables Response Values

Surfactant

(%)

Time

(Min.)

Oil

Content

(%)

Droplet

Size

(nm)

p-Anisidine

Value

β- Carotene

retention

(%)

1 8 4 6.50 121±4 1.5±0.2 94±1

2 6 5.50 8 110±2 3.2±0.4 77±5

3 4 7 6.50 115±5 6.3±0.8 64±3

4 6 5.50 5.48 111±4 3.3±0.3 92±3

5 8 4 9.50 125±5 5.2±0.3 84±2

6 6 8.02 8 89±3 5.6±0.2 66±3

7 9.36 5.50 8 122±2 2.1±0.1 86±1

8 6 5.50 10.52 124±2 7.1±0.4 82±4

9 6 5.50 8 114±1 4.1±0.4 80±4

10 6 5.50 8 110±4 3.7±0.2 76±3

11 8 7 9.50 101±3 5.9±0.3 75±2

12 8 7 6.50 104±2 3.1±0.2 82±2

13 6 5.50 8 117±3 3.6±0.1 83±4

14 6 5.50 8 121±2 3.5±0.2 80±1

15 4 4 6.50 124±4 5.3±0.3 65±2

16 4 4 9.50 130±6 7.5±0.6 60±4

17 6 5.50 8 117±2 4±0.3 80±3

18 2.64 5.50 8 143±3 6.7±0.5 58±3

19 6 2.98 8 119±3 3.3±0.4 72±2

20 4 7 9.50 121±1 9.1±0.4 59±1

58

variables which indicate that our model is statistically accurate. If the value of R2 is

closer to unity then it is the indication of better model fitting to actual data. On the

other end, lower values of R2 indicate that response variables were not appropriate

to explain the variation in behavior (Myers et al., 2016). In the present study,

closure to unity R2 demonstrates that the influence of surfactant concentration (X1),

Ultrasonic Homogenization time (X2) and oil contents (X3) on response variables

could be adequately described through quadratic polynomial model. Significance

level for coefficients of quadratic polynomial model was determined through

analysis of variance (ANOVA). Smaller p-value and larger F-value is the indication

for the highly significant effect of any term on response variable (Quanhong and

Caili, 2005).

4.2.2 Effect of Independent Variables on Response Variables

β-Carotene nanoemulsions were successfully prepared by using different

level of independent variables (Figure 4.1).The effect of independent variables on

droplet size, p-anisidine value and beta carotene retention are given in Table 4.2.

Regression coefficients for independent variables are summarized in Table 4.3.

4.2.2.1 Droplet size

The droplet size of beta carotene nanoemulsions was mainly depended on

surfactant concentration due to its significant effect on droplet size at linear (p <

0.001), quadratic (p < 0.001) and interaction level (p < 0.05) with homogenization

time. Surfactants lower the interfacial tensions between disperse and continuous

phase which leads to smaller droplet formation (Mehmood et al., 2017). Other

independent variables which have significant effect on droplet size were linear term

of homogenization time (p < 0.001) and oil content (p < 0.05), and quadratic terms

59

Table 4.3: Regression coefficients for beta carotene nanoemulsions

Regression

Coefficients

Droplet size

(nm)

p-Anisidine

Value

β- Carotene Retention

(%)

Intercept (α0) 114.85 3.66 79.43

A-Surfactant (α1) -5.44*** -1.48*** 9.82***

B-Time (α2) -8.01***

0.64** -2.42*

C-Oil (α3) 2.55* 1.31*** -3.21**

A2 (α11) 6.13*** 0.41* -3.21**

B2 (α22) -3.95** 0.43* -4.27***

C2 (α33) 0.82 0.69*** 2.09*

AB (α12) -2.88* -0.038 -2.37*

AC (α13) -1.38 0.19 -0.87

BC (α23) -0.88 -0.037 0.38

R2

0.9456 0.9580 0.9604

*Significant at 0.05 level, **Significant at 0.01 level, ***Significant at 0.001 level

60

of homogenization time (p < 0.001). The influence of homogenization time and

surfactant concentration on droplet size of β-carotene nanoemulsions is illustrated

in Figure 4.2 (A). Both these variables exert quadratic effect on droplet size. At

higher surfactant concentration, decrease in droplet size of nanoemulsions was

observed with the increase of homogenization time. This downward trend was

observed due to reduction of interfacial tension with the increase in surfactant

concentration (Polychniatou and Tzia, 2018). At lower surfactant concentration,

droplet size increased with increasing homogenization time. This increase was

observed because enough emulsifier is not present to cover newly formed smaller

droplets which initiate coalescence process (Anarjan et al., 2010).

Figure 4.2 (B) represented the combined effect of oil and surfactant

concentration on the droplet of β-carotene nanoemulsions. Oil content exerts linear

effect while surfactant concentrations have quadratic effect on droplet size of

nanoemulsions. Droplet size increased with rising oil concentration due to increase

in viscosity. As a result of this, higher energy is required to break the droplet which

results in larger droplet size. Additionally, higher oil concentration encourages

aggregation and collision of nanoemulsion droplets which increased the droplet

size (Mehmood, 2015; Zhang et al., 2009). Initially, droplet size decreased with

higher surfactant concentration due to reduction in surface tension. But, after a

minimal level, higher concentration of surfactant caused increased width of

diffusion layer due to excessive coverage of crystalline particles by surfactant. This

mechanism lowers zeta potential value and encourages agglomeration tendency

which increased droplet size of food grade mixed surfactant based β-carotene

nanoemulsions (Mehmood et al., 2017; Tan et al., 2010).

61

Figure 4.1: (A) Particle size distribution of β-carotene nanoemulsions (D4,3) (B)

Visual appearance of β-carotene nanoemulsions

62

Figure 4.2: 3D graphic surface optimization of (A) droplet size D4,3 (nm) versus

surfactant concentration (%) and homogenization time (Min.) (B) droplet size D4,3

(nm) versus oil content (%) and surfactant concentration (%) (C) p-Anisidine value

versus surfactant concentration (%) and homogenization time (Min.) (D) p-

Anisidine value versus oil content (%) and surfactant concentration (%) (E) β-

carotene retention (%) versus surfactant concentration (%) and homogenization

time (Min.) (F) β-carotene retention (%) versus oil content (%) and surfactant

concentration (%)

63

4.2.2.2 p-Anisidine value

p-Anisidine value is an important indicator for measurement of oxidation

products (Cho et al., 2008). As the p-Anisidine value of β-carotene nanoemulsions

was concerned, oil content had significant effect on the p-Anisidine value of β-

carotene nanoemulsions due to its significant effect on p-Anisidine value at linear

(p < 0.001) and quadratic level (p < 0.001). Other factors which significantly

contributes toward p-Anisidine value were linear term of surfactant concentration

(p < 0.001) and homogenization time (p < 0.001), and quadratic term of surfactant

concentration (p < 0.05) and homogenization time (p < 0.05). The lipid oxidation

mechanism is remarkably different in nanoemulsions as compared with bulk oily

phase due to the presence of interface and aqueous phase. In nanoemulsions, lipid

oxidation depends on many factors which include pH, oxygen concentration and

ionic strength of continuous phase, droplet size, thickness and interfacial properties

(Öztürk et al., 2017; Waraho et al., 2011).

The combined effects of homogenization time and surfactant concentration

on p-Anisidine value are illustrated in Figure 4.2 (C) which explicated the linear

effect of both independent variables on p-Anisidine value. When homogenization

time increased, p-Anisidine value also increases while increase in surfactant

concentration results in lower p-Anisidine value. During this study, β-carotene

nanoemulsions were developed using mixed surfactant (Tween 80 and soy lecithin)

which act as interfacial barrier against oxidation. These surfactants built a

protective membrane at interface of aqueous and oily phase which remarkably

reduce pro-oxidant accessibility into oil droplets which results in lower p-Anisidine

value (Hwang et al., 2017). Figure 4.2 (D) depicts the interactive effect of oil

64

content and surfactant concentration on p-Anisidine value. Both variables have

linear effect on p-Anisidine value of β-carotene nanoemulsions. The downward

trend was observed in p-Anisidine value with the increase of surfactant and oil

concentration. Oil concentrations have inverse effect on p-anisidine value because

droplet size increase when oil concentration is more which results in lower p-

Anisidine value due to reduced surface area for oxidation (Mehmood et al., 2017).

4.2.2.3 β-Carotene retention

β-Carotene retention of nanoemulsion was mainly depend on surfactant

concentration as it had significant effect on vitamin retention at linear (p < 0.001),

quadratic (p < 0.01) and interactive level (p < 0.05). Surfactant prevents the

degradation of β-carotene by forming membrane-like structure around new surfaces

(Hejri et al., 2013). Other factors which significantly contributed to β-carotene

retention were linear effect of homogenization time (p < 0.05) and oil content (p <

0.01), quadratic effect of homogenization time (p < 0.001) and oil content (p <

0.05) and interactive effect of homogenization time (p < 0.05).

A contour plot in Fig. 4.2 (E) illustrates the retention of β-carotene as a

function of homogenization time and surfactant concentration. Surfactant

concentrations have linear effect while homogenization time exerts quadratic effect

on the retention of β-carotene. Pre-existence of peroxides in surfactant molecule

cause β-carotene degradation. These peroxides break down into reactive radicals at

elevated temperature and significantly degrade β-carotene during storage (Liu and

Wu, 2010). Fig. 4.2 (F) represents the interactive effect of oil content and

surfactant concentration of the β-carotene retention in nanoemulsions. Surfactants

exert quadratic effect while oil has linear effect on β-carotene retention. With the

65

increase in surfactant concentration, degradation of β-carotene reduced due to the

formation of rigid surfactant shell at water-oil interface. This shell increases the

stability of β-carotene by preventing repulsion of β-carotene and avoiding new

surfaces formation (Hejri et al., 2013). Higher oil content also increases the

stability of β-carotene nanoemulsions by formation of larger droplets which have

lower surface area (Liu and Wu, 2010).

4.2.3 Optimization of Independent Variables

To illustrate the effects of surfactant concentration, homogenization time

and oil content on response variables, response surface graphs were drawn using

design expert software. These graphs were generated by varying two independent

variables within experimental ranges while keeping the third variable at central

point. Fig. 4.2 (A, C and E) were generated by varying the concentration of

surfactant concentration and homogenization time at 8% oil contents while Fig. 4.2

(B, D and F) were drawn by changing the concentration of oil and surfactant at

central value of homogenization time (5.5 Min.). These graphs illustrated complex

interaction among independent variables.

By setting the partial derivatives of droplet size regression equation (11) at

zero, following three equations can be constructed:

-12.16 + 3.06 X1 – 0.96 X2 – 0.46 X3 = 0, (14)

22.83 – 0.96 X1 – 3.52 X2 – 0.39 X3 = 0, (15)

0.74 – 0.46 X1 – 0.39 X2 + 0.74 X3 = 0 (16)

By setting the partial derivatives of p-Anisidine value regression equation

(12) at zero, following three equations can be constructed:

66

-2.40 + 0.20 X1 – 0.013 X2 + 0.063 X3 = 0, (17)

- 1.46 – 0.013 X1 + 0.38 X2 – 0.017 X3 = 0, (18)

- 4.34 + 0.063 X1 – 0.017 X2 + 0.62 X3 = 0 (19)

By setting the partial derivatives of beta carotene retention regression

equation (13) at zero, following three equations can be constructed:

21.23 - 1.60 X1 – 0.79 X2 – 0.29 X3 = 0, (20)

22.68 – 0.79 X1 – 3.80 X2 + 0.17 X3 = 0, (21)

- 16.19 – 0.29 X1 + 0.17 X2 + 1.86 X3 = 0 (22)

Following results were obtained after solving these equations 14-22:

X1 = 5.88%, X2 = 4.07 min and X3 = 6.50%

4.2.4 Verification of RSM Model

Optimized emulsifying conditions were used to check the suitability of the

model for prediction of response values. Optimized preparation conditions were

validated by conducting experiments under optimized conditions. The predicted

response values at optimized preparation conditions were 116.44 nm droplet size,

2.89 p-Anisidine value and 82.71% β-carotene retention. On the other hand, the

experimental values of response were 119.33nm droplet size, 2.67 p-Anisidine

value and 85.63% β-carotene retention (Table 4.4). Experimental response values

were well in agreement with predicted response values.

4.3 OPTIMIZATION OF VITAMIN D NANOEMULSIONS

4.3.1 Fitting the Model

Response surface methodology (RSM) is a statistical, theoretical and mathematical

67

technique for model building in order to optimize the level of independent variables

(Tan et al., 2016). The effect of independent variables (vitamin D nanoemulsions)

on droplet size (Y1), droplet growth ratio (Y2) and retention of vitamin D (Y3) are

given in Table 4.5. Coefficients of the polynomial equation were computed from

experimental data to predict the values of response variable. Regression equations

for each response variable, obtained from response surface methodology are

mentioned in Eq. 23-25:

Droplet Size = +120.32 - 14.74Y1 - 9.11Y2 +6.42Y3 – 4.60Y12 – 3.79Y2

2 –

1.06Y32 – 1.00Y1Y2 – 5.25Y1Y3 – 1.50Y2Y3 (23)

Droplet Growth Ratio = +0.16 + 0.024Y1 – 0.042Y2 + 7.35Y3 + 0.021Y12 +

0.036Y22 + 4.80Y3

2 – 0.032Y1Y2 + 5.75Y1Y3 + 9.00Y2Y3 (24)

Vitamin D Retention = + 72.87 + 4.63Y1 + 6.95Y2 + 1.61Y3 – 2.62Y12 +

2.86Y22 + 3.92Y3

2 + 1.63Y1Y2 – 0.12Y1Y3 – 3.12Y2Y3 (25)

Statistical analysis (ANOVA) results revealed that the experimental data

could be represented well with quadratic polynomial model with coefficient of

determination (R2) values for droplet size (Y1), droplet growth ratio (Y2) and

retention of vitamin D (Y3) being 0.9524, 0.9791 and 0.9513, respectively (Table

4.6).

Lack of fit was non-significant (p≤0.05) relative to pure error for all

variables which indicate that our model is statistically accurate. If the value of R2 is

closer to unity then it is the indication of better model fitting to actual data. On the

other end, lower values of R2 indicate that response variables were not appropriate

to explain the variation in behavior (Myers et al., 2016). In our study, all response

variables have values closure to unity (Table 4.6).

68

Table 4.4: Optimum preparation conditions and response value for β-carotene

nanoemulsions

Optimum Conditions Coded Levels Actual Levels

Surfactant Concentration (%) -0.06 5.88

Homogenization Time (Min.) -0.95 4.07

Oil Contents (%) -1.00 6.50

Response Predicted Values Experimental Values

Droplet Size (nm) 116.44 119.33 ± 2.5

p-Anisidine Value 2.89 2.67 ± 0.9

β- Carotene Retention (%) 82.71 85.63 ± 1.5

69

Table 4.5: Effect of independent variable on responses for optimization of vitamin

D nanoemulsions

Run

Independent Variables Response Values

HT1

(Min.)

S/O2

Ratio

DPV3

(%)

Droplet

Size

(nm)

Droplet

Growth

Ratio

Vitamin D

Retention

(%)

1 5 0.6 9.68 130 0.168 86

2 5 0.90 8 111 0.172 91

3 6.5 0.78 7 84 0.146 94

4 5 0.60 8 115 0.148 69

5 3.50 0.78 9 130 0.208 78

6 3.50 0.43 9 153 0.205 69

7 5 0.60 8 121 0.157 74

8 6.50 0.78 9 85 0.202 89

9 7.52 0.60 8 90 0.256 72

10 2.48 0.60 8 130 0.165 60

11 3.50 0.78 7 110 0.182 77

12 5 0.60 8 125 0.162 72

13 6.50 0.43 7 105 0.305 66

14 5 0.60 8 117 0.164 72

15 5 0.60 8 123 0.163 74

16 3.50 0.43 7 125 0.208 61

17 5 0.31 8 135 0.333 72

18 5 0.60 8 120 0.15 76

19 5 0.60 6.32 110 0.163 83

20 6.50 0.43 9 110 0.318 79

1 HT, Homogenization Time;

2S/O Ratio, Surfactant to Oil Ratio;

3DPV, Disperse

Phase Volume

70

In our study, closure to unity R2 demonstrates that the influence of ultrasonic

homogenization time (X1), surfactant to oil ratio (X2) and disperse phase volume

(X3) on response variables could be adequately described through the quadratic

polynomial model. Significance level for coefficients of quadratic polynomial

model was determined through analysis of variance (ANOVA). Smaller p-value

and larger F-value are important indication for highly significant effect of any term

on response variable (Mehmood, 2015).

4.3.2 Effects of Independent Variables on Responses

Vitamin D nanoemulsions were successfully prepared by using different

level of independent variables (Figure 4.3). The effects of independent variables on

the response variables (Droplet size, droplet growth ratio and vitamin D retention)

are given in Table 4.5 while the values of regression coefficients of responses are

summarized in Table 4.6.

4.3.2.1 Droplet size

The droplet size of vitamin D nanoemulsion was mainly depended on the

homogenization time as it had a significant effect on the size of the droplet at linear

(p < 0.001), quadratic (p < 0.01) and interactive term with surfactant to oil ratio (p

< 0.05). When sufficient amount of surfactant is available, the droplet size of

nanoemulsion significantly reduced with higher homogenization time due to

increase in shear and cavitation forces (Anarjan et al., 2010). Other factors which

significantly affect droplet size were linear terms of surfactant to oil ratio (p <

0.001) and disperse phase volume (p < 0.001).

The interactive effects of homogenization time and surfactant to oil ratio on

droplet size of food grade vitamin D nanoemulsions are depicted in Figure 4.4 (A).

71

Table 4.6: Regression coefficients values for vitamin D nanoemulsions

Regression

coefficients

Droplet size

(nm)

Droplet Growth

Ratio

Vitamin D Retention

(%)

Intercept (α0) 120.32 0.16 72.87

A-Time (α1) -14.74*** 0.024*** 4.63***

B-S/O Ratio (α2) -9.11***

-0.042*** 6.95***

C-DPV (α3) 6.42*** 7.352* 1.61

A2 (α11) -4.60** 0.021*** -2.62**

B2 (α22) -3.798 0.036*** 2.86**

C2 (α33) -1.06 4.805 3.92***

AB (α12) -1.00 -0.032*** 1.63

AC (α13) -5.25* 5.750 -0.12

BC (α23) -1.50 9.00 -3.12*

R2

0.9524 0.9791 0.9513

*Significant at 0.05 level, **Significant at 0.01 level, ***Significant at 0.001 level

72

Both these variables exert linear effect on nanoemulsions droplet size. Direct

relation was reported between the droplet size and homogenization time. Droplet

size of vitamin D nanoemulsions reduced with higher homogenization time due to

the generation of strong shear forces by ultrasonic homogenizer. When

nanoemulsions particles are subjected to these shear forces for the longer time, then

it leads to disruption of larger droplets into smaller one (Carpenter and Saharan,

2017). When surfactant to oil ratio was increased, the interfacial tension of the

system was reduced which results in smaller droplet size (Homayoonfal et al.,

2014).

The interactive terms of disperse phase volume and surfactant to oil ratio on

droplet size is shown in Fig. 4 (B). Both these variables exert linear effect on

nanoemulsions droplet size. The smaller droplets were produced during ultrasonic

homogenization at lower disperse phase volume and gradually increase with the

rise in DPV proportion when the concentration of surfactants remains constant.

Surfactant to oil ratio increased at lower disperse phase volume which results in

smaller droplet size due to higher value of interfacial tension and presence of

enough emulsifier to hold newly formed droplets (Ziani et al., 2012). Another

possible reason is that viscosity value of dispersed phase may increase with the

increase of disperse phase volume. Due to increase in viscosity, the disruption of

droplet became more difficult which results in larger droplet size (Mcclements et

al., 2007). A similar result was reported by the previous study regarding the change

of particle structure with the viscosity change (Feng et al., 2009). .

4.3.2.2 Droplet growth ratio

Droplet growth ratio is an important indicator of the stability of nanoemulsions.

73

Figure 4.3: (A) Particle size distribution of vitamin D nanoemulsions (D4,3) (B)

Visual appearance of vitamin D nanoemulsions

74

The DGR of vitamin D nanoemulsion was mainly depended on the homogenization

time and surfactant to oil ratio as these had significant effects on the droplet growth

ratio at linear (p < 0.001), quadratic (p < 0.001) and interactive level (p < 0.001).

Droplet growth ratio of nanoemulsion was reduced with the increase of surfactant

because the newly formed droplets produced during ultrasonic homogenization

were stabilized by the surfactant molecules which prevent them from coalescence

and flocculation (Ahmad et al., 2011). Other factors which had pronounced effects

on the DGR of vitamin D nanoemulsions were the linear term of disperse phase

volume (p < 0.05).

The combined effects of homogenization time and surfactant to oil ratio on

droplet growth ratio of nanoemulsion is explicated in Fig. 4 (C) Both had quadratic

effect on the DRG of oil-in-water nanoemulsions. In the presence of higher

concentration of surfactant, droplet growth ratio was significantly reduced with the

increase in homogenization time due to the formation of smaller size droplets

(covered by surfactant) which were stable against aggregation, coalescence and

flocculation (Mehmood et al., 2017). The nanoemulsions under study exhibit more

stability against droplet growth ratio as compared to other nanoemulsions with

single surfactants (Khalid et al., 2017). This stability was achieved by using mixed

surfactants (Soya lecithin and Tween 80) which significantly enhance the loading

capacity and reduce interfacial tension of dispersed phase by developing

intercalating structure at the interface of water/oil (Cilek et al., 2006; Mehmood et

al., 2017). Higher surfactant to oil ratio had negative influence on droplet growth

ratio. The possible reason behind it is the movement of oil droplets through

surfactant micelles which increase the rate of particle growth (Weiss et al., 2000).

75

Figure 4.4: 3D graphic surface optimization of (A) droplet size D4,3 (nm) versus

S/O ratio and homogenization time (Min.) (B) droplet size D4,3 (nm) versus

disperse phase volume (%) and S/O ratio (C) Droplet growth ratio versus S/O ratio

and homogenization time (Min.) (D) Droplet growth ratio versus disperse phase

volume (%) and S/O ratio (E) Vitamin D retention (%) versus S/O ratio and

homogenization time (Min.) (F) Vitamin D retention (%) versus disperse phase

volume (%) and S/O ratio

76

The interactive effects of surfactant to oil ratio and disperse phase volume are

shown in Figure 4.4 (D). Disperse phase volume has quadratic effects while S/O

ratio has linear effect on the droplet growth ratio of nanoemulsions. Initially,

droplet growth reduced with increase in DPV but higher disperse phase volume

proportion increase DGR by increasing the interfacial tension at water/oil interface.

Hence, larger size droplets were produced which were less stable as

compared to smaller size droplets (Mehmood, 2015). Surfactant to oil ratio has

significant effect on droplet growth ratio. The value of DGR reduced with increase

in S/O ratio because surfactant decreases the interfacial tension between water and

oil interface. Hence, smaller droplets were produced which were more stable than

larger droplets (Homayoonfal et al., 2014).

4.3.2.3 Vitamin D retention

The retention of vitamin D in nanoemulsion was mainly depended on

surfactant to oil ratio as it had a significant effect on the retention of vitamin D at

linear (p < 0.001), quadratic (p < 0.01) and interactive term with disperse phase

volume (p < 0.05). Surfactant prevents the degradation of vitamin D by forming

membrane-like structure around new surfaces (Hejri et al., 2013). Other factors

which significantly affect vitamin D retention were linear terms of homogenization

time (p < 0.001) and quadratic terms of homogenization time (p < 0.01) and

disperse phase volume (p < 0.001).

The interactive effects of homogenization time and surfactant to oil ratio on

retention of vitamin D are depicted in Fig. 4 (E). Both these variables exert linear

effect on vitamin D retention. In the presence of sufficient surfactant, vitamin D

retention improved with increasing homogenization time due to its effects on the

77

adsorption of surfactants around droplets and particle size distribution (Li and

Chiang, 2012). With the increase in surfactant concentration, degradation of

vitamin reduced due to the formation of rigid surfactant shell at water-oil interface.

This shell increases the stability of vitamin D by preventing repulsion of vitamin D

and avoiding new surfaces formation (Hejri et al., 2013).

The interactive terms of disperse phase volume and surfactant to oil ratio on

vitamin D retention are shown in Fig. 4 (F). Both these variables exert linear effect

on vitamin D retention. The nanoemulsions under study exhibit more stability

against vitamin D gradation as compared to other nanoemulsions with single

surfactants (Khalid et al., 2017). This stability was achieved by using mixed

surfactants (Soya lecithin and Tween 80) which significantly enhance the loading

capacity and reduce interfacial tension of dispersed phase by developing

intercalating structure at the interface of water/oil (Cilek et al., 2006; Mehmood,

2015). Higher oil content also increases the stability of vitamin D nanoemulsions

by formation of larger droplets which have lower surface area (Liu and Wu, 2010).

4.3.3 Optimization of Emulsifying Conditions for Vitamin D Nanoemulsions

The effects of emulsifying conditions on responses were visualized through

plotting response surfaces by using Software (Design Expert). For obtaining

optimum conditions for independent variables, graphs of droplet size, droplet

growth ratio and vitamin D retention were drawn (Figure 4.4). These optimization

graphs were created by keeping two independent variables at central values while

changing the values of other two variables. Figure 4.4 (A, C and E) were generated

by changing the concentrations of S/O ratio and homogenization time at 8%

disperse phase volume. By keeping the values of homogenization time at 5

78

Minutes, response plots. Fig. 4 (B, D and F) were drawn by varying the

concentrations of S/O ratio and disperse phase volume. In general, complex levels

of interactions were observed among these variables.

By setting the partial derivatives of droplet size regression equation (23) at

zero, following three equations can be constructed:

40.92 - 4.08 X1 – 3.81 X2 – 3.50 X3 = 0, (26)

35.73 – 3.81 X1 – 0.24 X2 – 8.57 X3 = 0, (27)

46.13 – 3.50 X1 – 8.57 X2 - 2.12 X3 = 0 (28)

By setting the partial derivatives of droplet growth ratio regression equation


-0.03 + 18.42 X1 – 0.12 X2 + 3.83 X3 = 0, (29)

- 1.45 – 0.12 X1 + 2.32 X2 + 0.051 X3 = 0, (30)

- 0.12 + 3.83 X1 + 0.051 X2 + 9.60 X3 = 0 (31)

By setting the partial derivatives of vitamin D retention regression equation


11.66 - 2.34 X1 + 6.19 X2 – 0.083 X3 = 0, (32)

38.75 + 6.19 X1 + 186.58 X2 - 17.86 X3 = 0, (33)

- 49.85 – 0.083 X1 - 17.86 X2 + 7.84 X3 = 0 (34)

Following results were obtained after solving these equations 26-34:

X1 = 4.35, X2 = 0.62 and X3 = 7.00

4.3.4 Verifications of the Model

The desirability of equations for prediction of response was check using

79

optimum preparation conditions (4.35 minutes homogenization time, 0.62

surfactant to oil ratio (S/O) and 7% DPV). The optimized conditions were further

confirmed by performing the experiment under optimum conditions. At optimum

preparation conditions, predicted response values for droplet size, droplet growth

ratio and vitamin D retention were 115.47 nm, 0.148 and 73.44, respectively. The

experimental values of droplet size, droplet growth ratio (DGR) and vitamin D

retention were 112.36 ± 3.6nm, 0.141 ± 0.07 and 76.65 ± 1.7%, respectively (Table

4.7). The experimental results were found in good agreement with the values

predicted by RSM.

4.4 CHARACTERIZATION OF BETA CAROTENE AND VITAMIN D

NANOEMULSIONS

Beta carotene and vitamin D nanoemulsions were prepared using optimized

preparation conditions. These optimized conditions are further characterized

against different parameters which include droplet growth ratio and storage

stability, p-Anisidine value and turbidity.

4.4.1 Droplet Growth Ratio and Storage Stability

The stability of beta carotene nanoemulsions was determined in term of

droplet growth ratio. Figure 4.5 shows the droplet growth ratio of beta carotene

nanoemulsions during one-month storage at room temperature. Storage time have

significant effect (p < 0.05) on the droplet growth ratio of beta carotene

nanoemulsions (Table 4.8). Initially, up to 25 days, droplet growth ratio of

nanoemulsions significantly deviates (p < 0.05) with the passage of time but after

that non-significant (p > 0.05) increase was observed in the droplet growth ratio of

beta carotene nanoemulsions.

80

Table 4.7: Optimum preparation conditions for vitamin D nanoemulsions


Homogenization Time (Min.) -0.43 4.35

Surfactant to Oil Ratio 0.086 0.62

Disperse Phase Volume (%) -1.00 7.00


Droplet Size (nm) 115.47 112.36 ± 3.6

Droplet Growth Ratio 0.148 0.141 ± 0.07

Vitamin D Retention (%) 73.44 76.65 ± 1.7

81

Table 4.8: ANOVA for droplet growth ratio of beta carotene nanoemulsions

Source DF SS MS F P

Storage Time 5 0.07680 0.01536 154 0.0001

Error 12 0.00120 0.00010

Total 17 0.07800

Figure 4.5: Change in droplet growth ratio of beta carotene nanoemulsions during

one month storage

E

D

C

B

A A

0.00

0.05

0.10

0.15

0.20

0.25

0.30

5 10 15 20 25 30

DG

R

Days

82

The stability of vitamin D nanoemulsions was determined in term of droplet

growth ratio. Figure 4.6 shows the droplet growth ratio of vitamin D

nanoemulsions during one-month storage at room temperature. Significant increase

(p < 0.05) was observed in droplet growth of vitamin D nanoemulsions with the

passage of time (Table 4.9). Initially, up to 20 days, droplet growth ratio of vitamin

D nanoemulsions significantly deviates (p < 0.05) with the passage of time but

after that non-significant increase (p > 0.05) was observed in the droplet growth

ratio of vitamin D nanoemulsions.

The storage stability of beta carotene nanoemulsions was evaluated during

their two- month storage at 4 °C and 25 °C. The effect of storage and time on the

droplet size of beta carotene nanoemulsions are given in Figure 4.7. Storage days

have significant effect (p < 0.05) on the mean droplet size of food grade beta

carotene nanoemulsions. Additionally, temperature also has significant (p < 0.05)

effect on the droplet size of beta carotene nanoemulsions (Table 4.10). Apart from

this, the interaction between time and temperature was also found significant (p <

0.05). Initially, sharp increase was observed in the droplet size of nanoemulsions

during initial 25 days of storage at 4 °C and 25 °C. After that, no significant

increase was noted in droplet size. During 60 days of storage, droplet size of beta

carotene nanoemulsions varied from 112.36 to 132.9 at 4 °C and 112.36 to 147.1 at

25 °C. Despite increase in size, the droplet size of beta carotene nanoemulsions is

still in acceptable range. Similar results were reported by other researchers (Henry

et al., 2010; Li and Chiang, 2012).

The stability of vitamin D nanoemulsions was evaluated during their two-

month storage at 4 °C and 25 °C. The effect of storage on droplet size of vitamin

83

Table 4.9: ANOVA for droplet growth ratio of vitamin D nanoemulsions

Source DF SS MS F P

Storage Time 5 0.09145 0.01829 183 0.0001

Error 12 0.00120 0.00010

Total 17 0.09265

Figure 4.6: Change in droplet growth ratio of vitamin D nanoemulsions during one

month storage

E

D

C

B AB A

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

5 10 15 20 25 30

DG

R

Days

84

Table 4.10: ANOVA for storage stability of beta carotene nanoemulsions

Source DF SS MS F P

Storage Time 12 6192.23 516.02 516.02 0.0001

Temperature 1 3111.72 3111.72 3111.72 0.0001

Storage x Temp 12 377.25 31.44 31.44 0.0001

Error 52 52.00 1.00

Total 77 9733.20

Figure 4.7: Effect of time and temperature on storage stability of beta carotene

nanoemulsions

L

I

GH

E

D CD

ABC BCD

ABC ABC ABC AB A

L

KL K

J

I

H

EF EF EF FG EF FG

EF

110

120

130

140

150

0 5 10 15 20 25 30 35 40 45 50 55 60

Dro

ple

t Si

ze D

4,3

(nm

)

Storage Days

25 °C

4 °C

85

D nanoemulsions is given in Figure 4.8. Storage days have significant effect (p <

0.05) on the droplet size of food grade vitamin D nanoemulsions (Table 11).

Additionally, temperature also has significant (p < 0.05) effect on the droplet size

of vitamin D nanoemulsions (Table 4.11). Apart from this, the interaction between

time and temperature was also found significant (p < 0.05). Generally, increase in

droplet size was observed with the passage of time. Initially, sharp increase was

observed in the droplet size of nanoemulsions during initial 30 days of storage at 4

°C and 25 °C. After that, no significant increase was noted in droplet size. During

60 days of storage, droplet size of vitamin D nanoemulsions varied from 119.33 to

140.15 at 4 °C and 119.33 to 155.5 at 25 °C. Despite increase in size, the droplet

size of mixed surfactant based vitamin D nanoemulsions are still in acceptable

range. Similar results were reported by other researchers (Henry et al., 2010; Li and

Chiang, 2012).

The increase in droplet growth rate was associated with non-equilibrium

system of nanoemulsions. To achieve equilibrium state, beta carotene and vitamin

D based nanoemulsions tend to reduce free energy as well as interfacial area

through various breakdown processes which include flocculation, sedimentation,

creaming and Ostwald ripening which leads to increase in droplet growth ratio of

beta carotene and vitamin D nanoemulsions (Tadros et al., 2004). Nanoemulsion

contains smaller particle size which is quite stable against flocculation,

sedimentation, creaming and phase separation, but Ostwald ripening is mainly

responsible for increase in droplet growth ratio of nanoemulsions (Taylor, 2003).

Ostwald ripening occurs due to the difference in the chemical potential of disperse

phase having different droplet size (Mcclements, 2011). During ripening process,

86

Table 4.11: ANOVA for storage stability of vitamin D nanoemulsions

Source DF SS MS F P

Storage Time 12 6821.24 568.44 568.44 0.0001

Temperature 1 2321.70 2321.70 2321.70 0.0001

Storage x Temp 12 307.08 25.59 25.59 0.0001

Error 52 52.00 1.00

Total 77 9502.02

Figure 4.8: Effect of time and temperature on storage stability of vitamin D

nanoemulsions

K

I

GH

EF

D

C BC

AB AB AB A AB A

K J

J

I

H

FG EF EF EF E

EF EF EF

115

125

135

145

155

165

0 5 10 15 20 25 30 35 40 45 50 55 60

Dro

ple

t Si

ze D

4,3 (

nm

)

Storage Days

25 °C

4 °C

87

the size of larger droplet increased due to their collision with smaller one in

continuous phase (Li and Chiang, 2012). Additionally, increase in droplets growth

ratio of beta carotene and vitamin D nanoemulsions might be associated with the

continuous movement of disperse phase droplets through continuous phase which

increase chances of droplet collisions (Henry et al., 2009). Previous studies also

reported increase in droplet growth ratio as a function of time (Henry et al., 2009;

Karadag et al., 2013; Mehmood, 2015).

Apart from this, increase in droplet size of beta carotene nanoemulsions was

higher at 25 °C as compared to 4 °C because temperature is reciprocally

proportional to rate of Ostwald ripening. Temperature affects the Ostwald ripening

through interfacial tension, solubility and diffusion coefficient. Previous studied

also reported effect of temperature on the Ostwald ripening in nanoemulsions (Jiao

and Burgess, 2003). However, the process of Ostwald ripening only occur during 4

weeks of initial storage, after that, no appreciable increase was observed in the

droplet size of beta carotene nanoemulsions.

4.4.2 p-Anisidine Value

p-Anisidine value is an important indicator of oxidative stability of nano-

emulsions (Chu et al., 2008). The oxidative stability of beta carotene

nanoemulsions was investigated by comparing the p-Anisidine value of beta

carotene containing free olive oil and olive oil incorporated into beta carotene

nanoemulsions. Effect of storage on the p-Anisidine values of free olive oil as well

as nanoemulsions incorporated olive oil is given in the Figure 4.9. Statistical

analysis indicated that storage duration and treatment has significant effect (p <

0.05) on the p-Anisidine values of beta carotene nanoemulsions (Table 4.12).

88

Table 4.12: ANOVA for p-Anisidine value of beta carotene nanoemulsions

Source DF SS MS F P

Storage Time 7 24368.8 3481.3 202.46 0.0001

Treatment 1 15187.0 15187.0 883.25 0.0001

Storage x Treat 7 9997.5 1428.2 83.06 0.0001

Error 32 550.2 17.2

Total 47 50103.4

FOO = Free olive oil, NOO = Olive oil incorporated into nanoemulsions

Figure 4.9: Change in p-Anisidine value of beta carotene nanoemulsions during

storage

G FG

EF

E

D

C

B

A

G G

G G FG FG

FG

E

0

20

40

60

80

100

120

0 1 2 3 4 5 6 7

p -

An

isid

ine

Va

lue

Storage Days

FOO

NOO

89

During storage, non-significant increase was observed in p-Anisidine value

of olive oil incorporated into beta carotene nanoemulsions (up to 6 days). On the

other hand, free olive oil containing beta carotene remains stable during initial two

days and after that significant (p < 0.05) increase was observed in their p-Anisidine

value. Additionally, p-Anisidine value of free olive oil was significantly higher as

compared to nanoemulsions incorporated olive oil (Figure 4.9).

p-Anisidine value is an important indicator of oxidative stability of

nanoemulsions (Chu et al., 2008). The oxidative stability of vitamin D

nanoemulsions was investigated by comparing the p-Anisidine value of vitamin D

containing free canola oil and canola oil incorporated into vitamin D

nanoemulsions. Effect of storage on the p-Anisidine values of free canola oil as

well as nanoemulsions incorporated canola oil is given in the Figure 4.10.

Statistical analysis indicated that storage duration and treatment has significant

effect (p < 0.05) on p-Anisidine values of vitamin D nanoemulsions (Table 4.13).

During storage, non-significant increase (p > 0.05) was observed in p-Anisidine

value of canola oil incorporated into vitamin D nanoemulsions (up to 3 days). On

the other hand, p-Anisidine value of free canola oil containing vitamin D was

significant increase (p < 0.05) even after one day. Additionally, p-Anisidine value

of free canola oil was significantly higher as compared to nanoemulsions

incorporated canola oil (Figure 4.10).

In nanoemulsions, surfactant droplets help to solubilize beta carotene and

vitamin D (Richards et al., 2002). There is clearly some interaction between mixed

surfactant and beta carotene or vitamin D which protects them from oxidative

damage. As a result of this, olive oil incorporated into beta carotene nanoemulsions

90

Table 4.13: ANOVA for p-Anisidine value of vitamin D nanoemulsions

Source DF SS MS F P

Storage Time 7 27403.1 3481.3 202.46 0.0001

Treatment 1 17694.7 15187.0 883.25 0.0001

Storage x Treat 7 10001.0 1428.2 83.06 0.0001

Error 32 10.2 17.2

Total 47 55109.0

FCO = Free canola oil, NCO = Canola oil incorporated into nanoemulsions

Figure 4.10: Change in p-Anisidine value of vitamin D nanoemulsions during

storage

L

H

F

E

D

C

B

A

L

KL

JK J I H G

E

0

20

40

60

80

100

120

140

0 1 2 3 4 5 6 7

p-A

nis

idin

e V

alu

e

Storage Days

FCO

NCO

91

was more stable as compared to free olive oil. Similarly, canola oil incorporated

into vitamin D nanoemulsions was more stable as compared to free canola oil. The

rate of oxidation increased with the passage of time due to initiation of chain

reaction by oxidative products which lead to higher p-Anisidine value (Chu et al.,

2008). The nanoemulsions which are developed in our study was more oxidative

stable as compared to previous studies (Belhaj et al., 2010; Qian et al., 2012a).

This oxidative stability may be associated due to use of mixed surfactants e.g. soya

lecithin and Tween 80. Mixed surfactants may increase the oxidative stability of

nanoemulsions through increasing partitioning of surfactants at interface.

4.4.3 Turbidity

The turbidity value of nanoemulsions is very important because the

application of nanoemulsions in some food products (transparent or slightly turbid)

depends on the turbidity values of nanoemulsions. Effect of storage time as well as

temperature on the turbidity of beta carotene nanoemulsions is shown in Figure

4.11. Statistical analysis depicted that storage days and temperature have

significant effect (p < 0.05) on the turbidity value of beta carotene nanoemulsions

(Table 4.14). But, the interactive effect of time and temperature on turbidity value

was non-significant (p > 0.05). The turbidity value increased more rapidly in

nanoemulsions stored at 25 °C as compared to 4 °C. More rapid increase was

observed in nanoemulsion turbidity up to 20 days storage. After that, slow increase

was observed in the turbidity values of beta carotene nanoemulsions stored at

different temperatures.

Effect of storage as well as temperature on the turbidity of vitamin D

nanoemulsions is shown in Figure 4.12. Statistical analysis depicted that storage

92

Table 4.14: ANOVA for turbidity value of beta carotene nanoemulsions

Source DF SS MS F P

Storage Time 6 0.41233 0.06872 45.38 0.0001

Temperature 1 0.01339 0.01339 8.84 0.0001

Storage x Temp 6 0.00536 0.00089 0.59 0.7357

Error 28 0.04240 0.00151

Total 41 0.47348

Figure 4.11: Effect of time and temperature on turbidity value of beta carotene


0.25

0.3

0.35

0.4

0.45

0.5

0.55

0 5 10 15 20 25 30

Tu

rbid

ity

( c

m-1

)

Storage Days

4 °C

25 °C

93

days and temperature have significant effect (p < 0.05) on the turbidity value of

vitamin D nanoemulsions (Table 4.15). But, the interactive effect of time and

temperature on turbidity value was non-significant (p > 0.05). The turbidity value

increased more rapidly in nanoemulsions stored at 25 °C as compared to 4 °C.

More rapid increase was observed in the turbidity values of nanoemulsion up to 20

days of storage. After that, slow increase was observed in the turbidity values of

vitamin D nanoemulsions stored at different temperatures.

The turbidity value of nanoemulsions are low as compared to conventional

emulsions because smaller droplets scatter light wave weakly which leads to lower

turbidity values (Mcclements, 2011). During storage, turbidity values increased due

to increase in droplet size which scatters light wave strongly. Furthermore, at

higher temperature, the chances of droplets collision is more which results in more

turbidity value (Zahi et al., 2014). Previous studies also reported increase in the

turbidity values of nanoemulsion as a function of storage time (Zahi et al., 2014).

Surfactants can decrease the value of turbidity by either reducing the droplet size of

nanoemulsions or through reducing the refractive index contrast (Saberi et al.,

2013).

4.5 EFFECT OF ENVIRONMENTAL CONDITIONS ON BETA

CAROTENE AND VITAMIN D NANOEMULSIONS

Nanoemulsion based foods may experience different environmental stresses

(such as change in temperature, pH and ionic strength) during food preparations,

storage, transportation, distribution and utilization. Hence, in present study stability

of beta carotene and vitamin D nanoemulsions (optimized conditions) was

investigated against pH, ionic strength, temperature and freeze thaw cycle.

94

Table 4.15: ANOVA for turbidity value of vitamin D nanoemulsions

Source DF SS MS F P

Storage Time 6 0.33523 0.05587 69.22 0.0001

Temperature 1 0.00619 0.00619 7.67 0.0001

Storage x Temp 6 0.00386 0.00064 0.80 0.5807

Error 28 0.02260 0.00081

Total 41 0.36788

Figure 4.12: Effect of time and temperature on turbidity value of vitamin D


0.25

0.3

0.35

0.4

0.45

0.5

0.55

0 5 10 15 20 25 30

Tu

rbid

ity

(cm

-1)

Storage Days

4 °C

25 °C

95

4.5.1 Effect of pH

The pH value of emulsion-based food and beverages considerably differ, such

as soft drinks are acidic in nature while some nutritional beverages have pH in

basic range. Hence, in present study, effect of pH on the stability of beta carotene

and vitamin D nanoemulsions was examined. The effect of pH values on the

droplet growth of beta carotene nanoemulsions is given in Figure 4.13. No

significant change (p >0.05) was observed in droplet size of beta carotene

nanoemulsions across entire range of pH (2-8). Furthermore, these nanoemulsions

were also stable against phase separation, creaming and sedimentation at the pH

values range from 2-8 (Table 4.16).

The effect of pH values on the droplet growth of vitamin D nanoemulsions is

given in Figure 4.14. No significant change (p >0.05) was observed in droplet size

of vitamin D nanoemulsions across entire range of pH i.e. 2-8 (Table 4.17).

Furthermore, mixed surfactant based vitamin D nanoemulsions were also stable

against phase separation, creaming and sedimentation at the pH values range from

2-8.

The stability of mixed surfactant based beta carotene and vitamin D

nanoemulsions suggest that interfacial properties are dominated by non-ionic

surfactant i.e. Tween 80. Other surfactant (soya lecithin) undergoes a transition

around pH 2 which significantly reduce surface charge. Aggregation of droplets

occurs when attractive forces (such as hydrophobic and van der Walls) overcomes

repulsive forces (mainly steric and electrostatic forces). So, in the case of beta

carotene and vitamin D nanoemulsions, repulsive forces (steric forces) between

charged droplets are strong enough to overcome the attractive forces of droplets.

96

Table 4.16: ANOVA for pH stability of beta carotene nanoemulsions

Source DF SS MS F P

pH 6 0.6645 0.11074 0.15 0.9849

Error 14 10.0414 0.71724

Total 20 10.7059

Figure 4.13: Effect of pH on the stability of beta carotene nanoemulsions

109

112

115

118

121

0 2 4 6 8 10

Dro

ple

t Si

ze D

4,3

(n

m)

pH

97

Table 4.17: ANOVA for stability of vitamin D nanoemulsions against change in

pH value

Source DF SS MS F P

pH 6 0.0573 0.00954 0.01 1.0000

Error 14 13.8014 0.98581

Total 20 13.8587

Figure 4.14: Effect of pH on the stability of vitamin D nanoemulsions

116

119

122

125

128

0 2 4 6 8 10

Dro

ple

t Si

ze D

4,3

(n

m)

pH

98

Additionally, non-ionic surfactant (Tween 80 in our study) may contain charge due

to preferential absorption of hydrogen ion at lower pH and hydroxyl ion at higher

pH or due to presence of surface active impurities which are ionizable. Hence, non-

ionic surfactant generates strong steric forces which prevent droplets from

aggregation (Ozturk et al., 2014). In our study, the stability of beta carotene and

vitamin D nanoemulsions against different pH values may be associated due to use

of mixed surfactants, which have ability to generate strong steric forces which

prevent the droplets from aggregations.

4.5.2 Effect of Ionic Strength

The concentration of salt appreciably differ in different food and beverages

products, therefore the effect of ionic strength was examined on the stability of

mixed surfactants based beta carotene nanoemulsions. Figure 4.15 shows the effect

of ionic strength on the droplet size of beta carotene nanoemulsions. Statistical

analysis indicates that ionic strength exerts non-significant effect (p >0.05) on

droplet size of beta carotene nanoemulsions (Table 4.18). Additionally, Visual

observations of beta carotene nanoemulsions stored at different ionic strength

indicated that these nanoemulsions remain stable against phase separation,

sedimentation and creaming during their storage at different ionic strength which

ranged between 0 to 400 mM.

Figure 4.16 shows the effect of ionic strength on the droplet size of vitamin D

nanoemulsions. Statistical analysis indicates that ionic strength exerts non-

significant (p >0.05) effect of droplet size of vitamin D nanoemulsions (Table

4.19). Additionally, Visual observations of vitamin D nanoemulsions stored at

different ionic strength indicated that mixed surfactant based vitamin D emulsions

99

Table 4.18: ANOVA for stability of vitamin D nanoemulsions against ionic

strength

Source DF SS MS F P

Salt Con. 8 0.7365 0.09206 0.09 0.9991

Error 18 17.9618 0.99788

Total 26 18.6983

Figure 4.15: Effect of ionic strength on the stability of beta carotene nanoemulsions

110

113

116

119

122

125

0 50 100 150 200 250 300 350 400

Dro

ple

t S

ize

D4

,3 (

nm

)

NaCl Concentration (mM)

100

remain stable against phase separation, sedimentation and creaming during their

storage at different ionic strength which ranged between 0 to 400 mM.

The stability of beta carotene and vitamin D nanoemulsions against different

ionic strength may be attributed because interfacial properties are dominated by the

non-ionic surfactant i.e Tween 80. Other surfactant (lecithin) undergoes a transition

around pH 2 which reduces surface charges. Moreover, Lecithin is a zwitterionic

and its behavior is affected by salt (Ozturk et al., 2014). Additionally, different

concentration of salts does not have ability of change the interfacial membrane

curvature of mixed surfactant based beta carotene and vitamin D nanoemulsions

and remains stable against droplet coalescence (Ogawa et al., 2003). The stability

of beta carotene and vitamin D nanoemulsions against different ionic strength

might be attributed due to the presence of strong steric stabilization which are

strong enough to overcome van der Walls and hydrophobic attractions (Harnsilawat

et al., 2006). Another study (Shu et al., 2016) reported the similar trend in

nanoemulsions stabilized by SC and MO-7S. On the other hand, some researchers

reported destabilization of nanoemulsions against different salt concentration due

to electrostatic screening effect (Ozturk et al., 2014). In our study, the stability of

beta carotene and vitamin D nanoemulsions against different salt concentrations

may be associated due to use of mixed surfactants, which have ability to generate

strong steric forces which prevent the droplets from aggregations.

4.5.3 Effect of Temperature

The temperature of nanoemulsions based food and beverages appreciably

varied during their processing, transportation, utilization and storage of food.

Table 4.19: ANOVA for stability of vitamin D nanoemulsions against ionic

101

strength

Source DF SS MS F P

Salt Con. 8 1.2774 0.15968 0.16 0.9939

Error 18 18.0418 0.00232

Total 26 19.3192

Figure 4.16: Effect of ionic strength on the stability of vitamin D nanoemulsions

Hence, I examined the effect of temperature on the stability of food grade beta

113

116

119

122

125

128

0 100 200 300 400 500

Dro

ple

t S

ize

D4

,3 (

nm

)

NaCl Concentration (mM)

102

carotene and vitamin D nanoemulsions. The effect of different temperature ranges

(30-90 °C) on the mean droplet size of beta carotene nanoemulsions is summarized

in Figure 4.17. After all temperature treatments, no significant change (p >0.05)

was observed in the droplet size of beta carotene nanoemulsions (Table 4.20).

However, small increase in droplet size and color change was observed at 90 °C.

Results of visual observation indicated that these nanoemulsions remained stable

against phase separation, sedimentation and creaming during entire thermal

variations.

The effect of different temperature ranges (30-90 °C) on the mean droplet size

of vitamin D nanoemulsions is summarized in Figure 4.18. After all temperature

treatments, no significant change (p >0.05) was observed in the size of droplets

(Table 4.21). The results of visual observation indicated that these nanoemulsions

remained stable against phase separation, sedimentation and creaming during entire

thermal variations.

So, it is concluded that mixed surfactant based beta carotene and vitamin D

nanoemulsions remained stable during temperature fluctuations. The stability of

mixed surfactant based beta carotene nanoemulsions at high temperature may be

attributed due to steric stabilization which prevent the aggregation of

nanoemulsions droplets (Ozturk et al., 2014). Aggregation of droplets occurs when

attractive forces (such as hydrophobic and van der Walls) overcomes repulsive

forces (mainly steric and electrostatic forces). Previous studies also reported

stability of whey protein isolate and lactoferrin based nanoemulsions against

droplet aggregation at higher temperature (Teo et al., 2016) due to strong repulsive

Table 4.20: ANOVA for stability of beta carotene nanoemulsions against higher

103

temperature

Source DF SS MS F P

Salt Con. 6 28.2682 4.71137 2.55 0.0700

Error 14 25.8814 1.84867

Total 20 54.1496

Figure 4.17: Stability of beta carotene nanoemulsions against higher temperature

Table 4.21: ANOVA for stability of vitamin D nanoemulsions against higher

106

110

114

118

122

126

130

0 20 40 60 80 100

Dro

ple

t S

ize

D4

,3 (

nm

)

Temperature (°C)

104

temperature

Source DF SS MS F P

Salt Con. 6 1.4832 0.24720 0.25 0.9516

Error 14 13.8814 0.99153

Total 20 15.3646

Figure 4.18: Stability of vitamin D nanoemulsions against higher temperature

forces between charged droplets. On the other hand, another study reported that

112

116

120

124

128

132

0 20 40 60 80 100

Dro

ple

t S

ize

D4

,3 (

nm

)

Temperature (°C)

105

whey protein-based nanoemulsions destabilize at higher temperatures due to

unfolding and thermal denaturation of protein (Chu et al., 2008). This difference in

nanoemulsions may be attributed due to difference in heating duration.

4.5.4 Physical Stability (Freeze-Thaw Cycle)

Aqueous food products are frequently frozen for increasing their shelf life and

presenting food in desirable physical state (Ghosh and Coupland, 2008). To

investigate the possible utilization of mixed surfactant based beta carotene and

vitamin D nanoemulsions in this food category, their stability was tested against

freeze-thaw cycle. The effect of freeze-thaw cycle on the droplet size of beta

carotene nanoemulsions is summarized in Figure 4.19. Freeze-thaw cycles have

significant effect (p < 0.05) on the mean droplet size of nanoemulsions (Table

4.22). The droplet size of nanoemulsions steadily increased after each freeze-thaw

cycle. Initially, the droplet size of beta carotene nanoemulsions was 112.36±1.4 nm

and this value increased to 141.75±0.9 nm after four freeze-thaw cycles.

The effect of freeze-thaw cycle on the droplet size of vitamin D nanoemulsions

is summarized in Figure 4.20. Freeze-thaw cycles have significant effect (p < 0.05)

on the mean droplet size of nanoemulsions (Table 4.23). The droplet size of

nanoemulsions steadily increased after each freeze-thaw cycle. Initially, the droplet

size of nanoemulsions was 119.33±1.6 nm and this value increased to 140.9±1.6

nm after four freeze-thaw cycles. Changes in the droplet size of vitamin D

nanoemulsions indicate that freeze-thaw cycle affects the stability of food grade

vitamin D nanoemulsions.

Changes in the droplet size of nanoemulsions indicate that freeze-thaw cycle

Table 4.22: ANOVA for physical stability of β-carotene nanoemulsions against

106

1 E

D

C

B

A

100

110

120

130

140

150

160

0 0.5 1 1.5 2 2.5 3 3.5 4

Dro

ple

t Si

ze D

4,3

(n

m)

Cycle No

freeze-thaw cycle

Source DF SS MS F P

Cycles 4 1687.79 421.947 421.94 0.0001

Error 10 10.00 1.000

Total 14 1697.79

Figure 4.19: Physical stability of beta carotene nanoemulsions against freeze-thaw

cycle

freeze-thaw cycle affects the stability of food grade beta carotene and vitamin D

107

nanoemulsions. Increase in droplet size was largely contributed by freezing rather

than thawing. Ice crystallization formed during freezing which force the oily

droplets to come closer to remaining continuous phase. As a result of this, water

film is drained between droplets and it leads to semi dry contact of two layers of

surfactant adsorbed on oil droplets. It is also called Newton black film. If repulsive

forces are not strong enough to limit droplet approach as well as film drainage, the

rupturing of Newton film allow the contents of droplets flow together and cause

droplet coalescence (O’regan and Mulvihill, 2010). Additionally, temperature of

the beta carotene and vitamin D nanoemulsions decreased during freezing which

leads to attenuated hydrophobic interactions (endothermic) in micelle core and

reinforcement of hydrogen bonding (Schellman, 1997). The compact droplets relax

after the changes in these forces which results in decomposition of nanoemulsions.

The ice crystals are formed during freezing which leads to disruption and

penetration of interface as well as expulsion of water from interstices. This

mechanism creates channel for bioactive molecule to escape from the core of

micelle (Ma et al., 2016b). However, these nanoemulsions remained stable against

phase separation, creaming and sedimentation after four freeze-thaw cycles.

4.6 TOXICOLOGICAL STUDIES FOR BETA CAROTENE AND

VITAMIN D NANOEMULSIONS

Beta carotene and vitamin D nanoemulsions were investigated against different

toxicological effects by performing different tests which include change in weight,

nuclear abnormalities analysis and comet assay. Albino mice were used as

experimental animals during these studies. The details are mentioned below:

Table 4.23: ANOVA for physical stability of vitamin D nanoemulsions against

108

freeze-thaw cycle

Source DF SS MS F P

Cycles 4 910.194 227.548 228 0.0001

Error 10 10.00 1.000

Total 14 920.194

Figure 4.20: Physical stability of vitamin D nanoemulsions against freeze-thaw

cycle

4.6.1 Body Weight

E D

C

B

A

95

105

115

125

135

145

155

0 0.5 1 1.5 2 2.5 3 3.5 4

Dro

ple

t Si

ze D

4,3

(n

m)

Cycle No

109

Albino mice are divided into six different groups to determine the toxicity

of mixed surfactant based beta carotene nanoemulsions. Each group received

different treatments and change in weight is noted after every week during 21 days

of study. The mean values of weight for different groups during study are

summarized in Figure 4.21. Statistical analysis indicates that significant effect (p <

0.05) of group and time was observed on the weight of albino mice under study

(Table 4.24). In general, nanoemulsions cause increase in weight while higher

amount of beta carotene results in reduction in weight of albino mice. In group A

(control group), weight increase was observed during entire duration of study. But,

higher weight gain was observed in group B as compared to group A. This weight

gain might be increased because nanoemulsions increase the absorption of nutrients

due to smaller droplet size (Mcclements and Rao, 2011). Group C and F received

similar same dose of beta carotene in nanoemulsions and olive oil respectively.

After two weeks, increase in weight was observed in group C as well as group F.

On the other end, weight loss was observed in group D and E due to higher dose.

Beta carotene in higher amount reduce the weight through controlling white

adipose tissues and brown adipose tissues development and function by affecting

the adiposity and body weight. Higher level of beta carotene reduces the adiposity

and lipogenic potential in adipose tissues and increase the thermogenic potential of

muscle (Bonet et al., 2003). The findings of our studies are similar to previous

studies which reported that higher dose of vitamin A cause weight loss (Jeyakumar

et al., 2006; Raoofi et al., 2010). But, these results are not in agreement with some

previous findings which reported non-significant effect of higher dose of vitamin A

Table 4.24: ANOVA for effect of beta carotene nanoemulsions on weight

110

Source DF SS MS F P

Group 5 449.620 89.9239 8992.39 0.0001

Time 3 46.733 15.5775 1557.75 0.0001

Group x Time 15 223.046 14.8697 1486.97 0.0001

Error 48 0.480 0.0100

Total 71 719.878

Figure 4.21: Effect of different treatments of beta carotene nanoemulsions on the

weight of mice

Group A = Control group

Group B = Blank nanoemulsions

Group C = Nanoemulsion containing beta carotene (9000 IU/Kg body weight)

Group D = Nanoemulsion containing beta carotene (12000 IU/Kg body weight)

Group E = Nanoemulsion containing beta carotene (16000 IU/Kg body weight)

Group F = Beta carotene in olive oil (5400 IU/Kg body weight)

on weight loss (Mahassni and Al-Shaikh, 2014).

M

F G J H L L

D E H

K I I

C D

K M

F F

A

B

N O

E

0

5

10

15

20

25

30

35

40

45

Group A Group B Group C Group D Group E Group F

We

igh

t (g

) 0 Day

7 Days

14 Days

21 Days

111

Albino mice are divided into six different groups to check the effect of vitamin

D nanoemulsions. Each group of mice received different treatments and change in

weight is noted after every week during 21 days of study. Statistical analysis

indicates that significant effect (p < 0.05) of group as well as time was observed on

the weight of albino mice under study (Table 4.25). The mean values of weight for

different groups during study are summarized in Figure 4.22. In general,

nanoemulsions cause increase in weight while higher amount of vitamin D results

in reduction in weight of albino mice. In group A (control group), weight increase

was observed during entire duration of study. But, higher weight gain was observed

in group B as compared to group A. This weight gain was observed because

nanoemulsions increase the absorption of nutrients due to smaller droplet size

(Mcclements and Rao, 2011). Group C and F received similar same dose of vitamin

D in nanoemulsions and canola oil respectively. After two weeks, loss in weight

was observed in group C but no weight loss was observed in group F. The weight

loss might be observed due to higher absorption of vitamin D in group C as

compared to group F. Higher absorption of vitamin D cause weight loss in group C

(Mason et al., 2014). Similarly, weight gain was also observed in group D and E

due to higher amount of vitamin D. Vitamin D reduce the weight through different

mechanisms such as reduction in the formation of new fat cells (Wood, 2008),

reduction in fat accumulation through suppressing fat cells storage (Chang and

Kim, 2016), production of serotonin in higher amount which increase satiety

(Halford and Harrold, 2012) and increase the production of testosterone which

trigger weight loss (Nimptsch et al., 2012). The findings of our studies are similar

Table 4.25: ANOVA for effect of different treatments of vitamin D nanoemulsions

112

on the weight of mice

Source DF SS MS F P

Group 5 408.217 81.6435 8164.35 0.0001

Time 3 18.982 6.3273 632.73 0.0001

Group x Time 15 209.506 13.9671 1396.71 0.0001

Error 48 0.480 0.0100

Total 71 637.185

Figure 4.22: Effect of different treatments of vitamin D nanoemulsions on the

weight of mice



Group C = Nanoemulsion containing vitamin D (1800 IU/Kg body weight)

Group D = Nanoemulsion containing vitamin D (2500 IU/Kg body weight)

Group E = Nanoemulsion containing vitamin D (3000 IU/Kg body weight)

Group F = Vitamin D in canola oil (1800 IU/Kg body weight)

M

HI H J K J K

C E G

L I HI

B D

J

N

FG EF

A

F

M

O

D

0

5

10

15

20

25

30

35

40

45

Group A Group B Group C Group D Gropu E Group F

We

igh

t (g

) 0 Day

7 Days

14 Days

21 Days

113

to previous studies which reported that higher dose of vitamin D cause weight loss

(Leblanc et al., 2012; Mason et al., 2014).

4.6.2 Nuclear Abnormalities Analysis

Nuclear abnormalities were determined through bi-nuclear and multi-

nuclear assay. Albino mice were used as experimental animals during this study.

The detail of nuclear abnormalities assay is mentioned below;

4.6.2.1 Bi-nuclear assay

Effects of mixed surfactant based beta carotene nanoemulsions on bi-nuclear

cells frequency of different albino mice groups (received different dose of beta

carotene nanoemulsions) are summarized in Figure 4.23. Statistical analysis results

depicted that different treatments of beta carotene have significant effect (p < 0.05)

on bi-nuclear cells frequency in different groups of albino mice (Table 4.26).

Frequency of binuclear cells was significantly higher (p < 0.05) in group B (blank

nanoemulsions) as compared to group A (control group). However, non- significant

(p > 0.05) difference was observed between group B (blank nanoemulsions), group

C (Nanoemulsion containing 9000 IU/Kg body weight beta carotene) and group F

(9000 IU/Kg body weight beta carotene in olive oil). Additionally, the frequency of

bi-nuclear cells significantly increased in group D and E due to higher dose of beta

carotene. Although significant effect of beta carotene nanoemulsions (having

different concentration of beta carotene) was observed on different groups of mice,

but the values of bi-nuclear assay still lie in lower limit. Bi-nuclear cell frequency

indicates the cytotoxicity by measuring damage in blood lymphocytes (Sandhu et

al., 2013). Nanoemulsions with lower amount of beta carotene are suitable for

consumption, but nanoemulsions with higher amount of beta carotene can induce

114

Table 4.26: ANOVA for bi-nuclear assay against different treatments of beta

carotene nanoemulsions

Source DF SS MS F P

Groups 5 0.04105 0.00821 82.1 0.0001

Error 12 0.00120 0.00010

Total 17 0.04225

Figure 4.23: Effect of different treatments of beta carotene nanoemulsions on the

frequency of bi-nuclear cells







D

C

C

B

A

C

0 0.05 0.1 0.15 0.2 0.25 0.3

Group A

Group B

Group C

Group D

Group E

Group F

Frequency of BN Cells (%)

115

cytotoxicity due to more absorption of beta carotene (Mcclements and Rao, 2011).

Effects of mixed surfactant based vitamin D nanoemulsions on bi-nuclear cells

frequency of different albino mice groups (received different dose of vitamin D

nanoemulsions) are summarized in Figure 4.24. Statistical analysis results depicted

that different treatments of vitamin D have significant effect (p < 0.05) on bi-

nuclear cells frequency in different groups of albino mice (Table 4.27). Frequency

of binuclear cells was significantly higher (p < 0.05) in group B (blank

nanoemulsions) as compared to group A (control group). However, non-significant

difference (p > 0.05) was observed between group B (blank nanoemulsions), group

C (Nanoemulsion containing 1800 IU/Kg body weight vitamin D) and group F

(1800 IU/Kg body weight vitamin D in canola oil). Additionally, the frequency of

bi-nuclear cells significantly increased in group D and E due to higher dose of

vitamin D. Although significant effect of vitamin D nanoemulsions (having

different concentration of vitamin D) was observed on different groups of mice, the

values of bi-nuclear assay still lie in lower limit. Bi-nuclear cell frequency indicates

the cytotoxicity by measuring damage in blood lymphocytes (Sandhu et al., 2013).

Vitamin D containing lower amount of vitamin D are safe for consumption, but

nanoemulsions with higher amount of vitamin D can induce cytotoxicity due to

more absorption of vitamin D (Mcclements et al., 2007).

4.6.2.2 Multi-nuclear assay

Effects of mixed surfactant based beta carotene nanoemulsions on multi-

nuclear cells frequency of different albino mice groups (received different dose of

beta carotene nanoemulsions) are summarized in Figure 4.25. Statistical analysis

results depicted that the different treatments of beta carotene (vitamin A) have

116


on bi-nuclear assay

Source DF SS MS F P

Groups 5 0.04345 0.00869 86.9 0.0001

Error 12 0.00120 0.00010

Total 17 0.04465

Figure 4.24: Effect of different treatments of vitamin D nanoemulsions on the

frequency of bi-nuclear cells







D

C

C

B

A

C

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

Group A

Group B

Group C

Group D

Group E

Group F

Frequency of BN Cells (%)

117

significant effect (p < 0.05) on the multi-nuclear cells frequency in different groups

of albino mice (Table 4.28). Frequency of multi-nuclear cells was significantly

higher (p < 0.05) in group B (blank nanoemulsions) as compared to group A

(control group). Additionally, significant difference was observed between group C

(Nanoemulsion containing 9000 IU/Kg body weight beta carotene) and group F

(9000 IU/Kg body weight beta carotene in olive oil). Additionally, the frequency of

multi-nuclear cells significantly increased in group D and E due to higher dose of

beta carotene. Although significant effect (p < 0.05) of beta carotene

nanoemulsions (having different concentration of beta carotene) was observed on

different groups of mice, the values of multi-nuclear assay still lie in lower limit.

Multi-nuclear cell frequency increased due to production of free radicals which

effect OFR 9oxygen free radical) scavenging enzymes (El-Shenawy et al., 2011).

Mixed surfactant based beta carotene nanoemulsions containing lower amount of

beta carotene are safe for consumption, but nanoemulsions with higher amount of

beta carotene can induce cytotoxicity and other harmful effects due to more

absorption of beta carotene (Mcclements et al., 2007).

Effects of mixed surfactant based vitamin D nanoemulsions on multi-

nuclear cells frequency of different albino mice groups (received different dose of

mixed surfactant based vitamin D nanoemulsions) are summarized in the Figure

4.26. Statistical analysis results depicted that different treatments of vitamin D have

significant effect (p < 0.05) on the multi-nuclear cells frequency in different groups

of albino mice (Table 4.29). Frequency of multi-nuclear cells was significantly


(control group). Additionally, significant difference (p < 0.05) was observed among

118

Table 4.28: ANOVA for multi-nuclear assay of different treatment of beta carotene

nanoemulsions

Source DF SS MS F P

Groups 5 316.965 63.3930 6339 0.0001

Error 12 0.120 0.0100

Total 17 317.085

Figure 4.25: Effect of different treatments of beta carotene nanoemulsions on

multi-nuclear cells frequency







F

E

C

B

A

D

0 5 10 15 20

Group A

Group B

Group C

Group D

Group E

Group F

Frequency of MN Cells (%)

119

Table 4.29: Analysis of variance for effect of different treatments of vitamin D

nanoemulsions on multi-nuclear assay

Source DF SS MS F P

Groups 5 467.316 93.4632 11193 0.0001

Error 12 0.100 0.0083

Total 17 467.416

Figure 4.26: Effect of treatments of vitamin D nanoemulsions on the frequency of

multi-nuclear cells







E

D

C

B

A

D

0 5 10 15 20 25

Group A

Group B

Group C

Group D

Group E

Group F

Frequency of MN Cells (%)

120

group C (Nanoemulsion containing 1800 IU/Kg body weight vitamin D) and group

F (1800 IU/Kg body weight vitamin D in canola oil). Furthermore, the frequency of

multi-nuclear cells significantly increased (p < 0.05) in group D and E due to

higher dose of vitamin D. Although significant effect of vitamin D nanoemulsions

(having different concentration of vitamin D) was observed on different groups of

mice, the values of multi-nuclear assay still lie in lower limit. Multi-nuclear cell

frequency increased due to production of free radicals which effect OFR oxygen

free radical) scavenging enzymes (El-Shenawy et al., 2011). Nanoemulsions

containing lower amount of vitamin D are safe for consumption, but

nanoemulsions with higher amount of vitamin D can induce cytotoxicity due to

more absorption of vitamin D (Mcclements, 2011).

4.6.3 Comet Assay

After nuclear abnormalities assay, the ability of beta carotene and vitamin D

nanoemulsions to cause DNA damage was detected by comet assay. Comet assay

has a number of potential advantages over conventional methods because in this

method mitotically active form of cells is not required (Lee and Steinert, 2003).

The detail of comet assay parameters is discussed below;

4.6.3.1 Tail length

Tail length indicates the extent of damage in DNA and it indicates the distance

of DNA migration from nuclear core. The effect of beta carotene nanoemulsions on

the tail length of different mice groups are summarized in Figure 4.27. Statistical

analysis results indicate that tail length of different mice groups significantly

deviates (p < 0.05) from each other (Table 4.30). Length of tail was significantly

higher in group B (blank nanoemulsions) as compared to group A (control group).

121

Figure 4.27: Effect of beta carotene nanoemulsions on tail length







PC = Positive Control

F

E

D

C

B

F

A

0 5 10 15 20 25 30 35 40

Group A

Group B

Group C

Group D

Group E

Group F

PC

Tail Length (μm)

122

Table 4.30: ANOVA for effect of beta carotene nanoemulsions on tail length

Source DF SS MS F P

Groups 6 1264.67 210.779 1392 0.0001

Error 14 2.12 0.151

Total 20 1266.79

Figure 4.28: Comet Assay Results for beta carotene nanoemulsions (A) Group A

(B) Group E



123

However, non-significant (p > 0.05) difference was observed between group A

(control group) and group F (9000 IU/Kg body weight beta carotene in olive oil).

Additionally, the tail length was significantly higher in group D and E due to

higher dose of beta carotene. But, the value of tail length in D and E groups are

significantly lower as compared to positive control (even less than half). Although,

significant effect of beta carotene nanoemulsions (having different concentration of

beta carotene) was observed on tail length of different groups of mice, their values

are significantly lower as compared with positive control. Hence, it is concluded

that beta carotene nanoemulsions with lower amount of beta carotene did not cause

genotoxicity in mice (Figure 4.28), but higher dose of beta carotene cause increase

in tail length. However, these values are not high enough to cause severe

genotoxicity. The results of this study are well in agreement with the findings of

other researchers (Gomes et al., 2013).

The effect of vitamin D nanoemulsions on the tail length of different mice

groups are summarized in Figure 4.29. Statistical analysis results indicate that tail

length of different mice groups significantly deviates (p < 0.05) from each other

(Table 4.31). Length of tail was significantly higher (p < 0.05) in group B (blank

nanoemulsions) as compared to group A (control group). However, non-significant

difference (p > 0.05) was observed between group B (blank nanoemulsions), group

C (Nanoemulsion containing 1800 IU/Kg body weight vitamin D) and group F

(1800 IU/Kg body weight vitamin D in canola oil). Additionally, the tail length was

significantly higher (p < 0.05) in group D and E due to higher dose of vitamin D.

But, the value of tail length in D and E groups are significantly lower as compared

to positive control (even less than half). Although, significant effect (p < 0.05) of

124

Figure 4.29: Effect of different treatments of vitamin D nanoemulsions on tail

length in comet assay








E

D

D

C

B

D

A

0 10 20 30 40 50

Group A

Group B

Group C

Group D

Group E

Group F

PC

Tail Length (μm)

125


on tail length

Source DF SS MS F P

Groups 6 2855.46 475.910 3143 0.0001

Error 14 2.12 0.151

Total 20 2857.58

Figure 4.30: Comet Assay Results for vitamin D nanoemulsions (A) Group A (B)

Group E



126

vitamin D nanoemulsions (having different concentration of vitamin D) was

observed on tail length of different groups of mice, their values are significantly

lower as compared with positive control. Hence, it is concluded that mixed

surfactant based vitamin D nanoemulsions with lower amount of vitamin D did not

cause genotoxicity in mice, but higher dose of vitamin D cause increase in tail

length. However, these values are not high enough to cause severe genotoxicity

(Figure 4.30). The results of this study are well in agreement with the findings of

other researchers (Gomes et al., 2013).

4.6.3.2 Tail DNA

Tail DNA indicates DNA damage and it is the ratio of total tail intensity and

total comet intensity (tail and head together). The effect of different treatments of

nanoemulsions on the tail DNA of different mice groups is given in Figure 4.31.

ANOVA results depicted that treatments have significant effect (p < 0.05) on the

tail DNA of different groups (Table 4.32). The value of tail DNA was significantly


(control group). Furthermore, dose depended response was observed in group C, D

and E. The value of tail DNA significantly increased with the increase in beta

carotene. Despite significant increase, these values were far less as compared to tail

DNA value of control group. Additionally, significant difference (p < 0.05) was

observed between group C (Nanoemulsion containing 9000 IU/Kg body weight

beta carotene) and group F (9000 IU/Kg body weight beta carotene in olive oil).

The values of tail DNA was significantly higher (p < 0.05) in group C as compared

to group F. This increase might be attributed due to more absorption of food grade

beta carotene from nanoemulsions due to smaller droplet size (Mehmood, 2015).

127

Table 4.32: ANOVA for effect of different treatments of beta carotene


Source DF SS MS F P

Groups 6 5929.71 988.284 6526 0.0001

Error 14 2.12 0.151

Total 20 5931.83

Figure 4.31: Effect of beta carotene nanoemulsions on tail DNA








E

D

D

C

B

E

A

0 10 20 30 40 50 60 70

Group A

Group B

Group C

Group D

Group E

Group F

PC

Tail DNA (%)

128

Over findings are similar to the findings of other researchers who found

significant effect of neem oil nanoemulsions on percent tail DNA in comet assay

(Jerobin et al., 2015).

The effects of different treatments of nanoemulsions on the tail DNA of

different mice groups are given in Figure 4.32. ANOVA results depicted that

treatments have significant effect (p < 0.05) on the tail DNA of different groups

(Table 4.33). The value of tail DNA was significantly higher (p < 0.05) in group B

(blank nanoemulsions) as compared to group A (control group). Furthermore, dose

depended response was observed in group C, D and E. The value of tail DNA

significantly increased with the increase in vitamin D. Despite significant increase,

these values were far less as compared to tail DNA value of control group.

Additionally, significant difference was observed between group C (Nanoemulsion

containing 1800 IU/Kg body weight vitamin D) and group F (1800 IU/Kg body

weight vitamin D in canola oil). The values of tail DNA was significantly higher in

group C as compared to group F. This increase might be attributed due to more

absorption of vitamin D from nanoemulsions due to smaller droplet size

(Mehmood, 2015). Over findings are similar to the findings of other researchers

who found significant effect of neem oil nanoemulsions on percent tail DNA in

comet assay (Jerobin et al., 2015).

4.6.3.3 Olive moment

Olive moment is a product of length of tail and total DNA fraction in tail. It

is a useful tool to investigate DNA damage. The effect of beta carotene

nanoemulsions on the olive moment of different mice groups is summarized in

Figure 4.33. Statistical analysis results indicate that olive moment of different mice

129


on tail DNA

Source DF SS MS F P

Groups 6 7339.29 1223.21 8078 0.0001

Error 14 2.12 0.15

Total 20 7341.41

Figure 4.32: Effect of different treatments of vitamin D nanoemulsions on tail

DNA in comet assay








F

E

D

C

B

G

A

0 10 20 30 40 50 60 70 80

Group A

Group B

Group C

Group D

Group E

Group F

PC

Tail DNA (%)

130

Table 4.34: ANOVA for effect of different treatments of beta carotene


Source DF SS MS F P

Groups 6 6.53811 1.08969 720 0.0001

Error 14 0.02120 0.00151

Total 20 6.55931

Figure 4.33: Effect of beta carotene nanoemulsions on olive moment








E

C

C

C

B

D

A

0 0.5 1 1.5 2 2.5

Group A

Group B

Group C

Group D

Group E

Group F

PC

Olive Moment

131

groups significantly deviates (p < 0.05) from each other (Table 4.34). Olive

moment was significantly different (p < 0.05) in group F (9000 IU/Kg body weight

beta carotene in olive oil), group B (blank nanoemulsions) as compared to group A

(control group). However, non-significant difference (p >0.05) was observed

between group C (Nanoemulsion containing 9000 IU/Kg body weight beta

carotene), group B (blank nanoemulsions) and group D (12000 IU/Kg body weight

beta carotene). Additionally, the olive moment was significantly higher (p < 0.05)

in E due to higher dose of beta carotene. But, the value of olive moment in E group

(16000 IU/Kg body weight beta carotene) was significantly lower as compared to

positive control (even less than half). Although, significant effect of beta carotene

nanoemulsions (having different concentration of beta carotene) was observed on

olive moment of different groups of mice, their values are significantly lower as

compared with positive control. Hence, it is concluded that beta carotene

nanoemulsions (with lower amount of beta carotene) did not cause genotoxicity in

mice, but nanoemulsions with higher amount of beta carotene can cause slight

increase in the value of olive moment. The findings of our study are opposite to the

findings of the other researchers who observed non-significant effect of andiroba

oil nanoemulsions on DNA damage (Milhomem-Paixão et al., 2017).

The effect of vitamin D nanoemulsions on the olive moment of different mice

groups is summarized in Figure 4.34. Statistical analysis results indicate that olive

moment of different mice groups significantly deviates from each other (Table

4.35). Olive moment was significantly higher (p < 0.05) in group B (blank

nanoemulsions) as compared to group A (control group). However, group C

(Nanoemulsion containing 1800 IU/Kg body weight vitamin D) significantly

132


on olive moment

Source DF SS MS F P

Groups 6 1264.67 210.779 1392 0.0001

Error 14 2.12 0.151

Total 20 1266.79

Figure 4.34: Effect of vitamin D nanoemulsions on olive moment








F

DE

D

C

B

EF

A

0 0.5 1 1.5 2 2.5 3 3.5

Group A

Group B

Group C

Group D

Group E

Group F

PC

Olive Moment

133

deviate (p < 0.05) from group B (blank nanoemulsions), and group F (1800 IU/Kg

body weight vitamin D in canola oil). Additionally, the olive moment was

significantly higher deviate (p < 0.05) from group B (blank nanoemulsions), in

group D and E due to higher dose of vitamin D. But, the value of olive moment in

D and E groups were significantly lower as compared to positive control (even less

than half). Although, significant effect of vitamin D nanoemulsions (having

different concentration of vitamin D) was observed on olive moment of different

groups of mice, their values are significantly lower as compared with positive

control. Hence it is concluded that vitamin D nanoemulsions (with lower amount of

vitamin D) did not cause genotoxicity in mice, but nanoemulsions with higher

amount of vitamin D can cause slight increase in the value of olive moment. The

findings of our study are opposite to the findings of the other researchers who

observed non-significant effect of andiroba oil nanoemulsions on DNA damage

(Milhomem-Paixão et al., 2017). This difference might be attributed due to use of

different ingredients for the preparation of nanoemulsions.

4.7 PREPARATION OF FORTIFIED BEVERAGE

After toxicology studies, these nanoemulsions were used for the preparation

of beta carotene and D fortified beverages. These fortified beverages are later on

subjected to different physicochemical analysis and results are summarized in

Table 4.36. Degradation of beta carotene and vitamin D was observed during the

storage of beverages. Previous studies also reported degradation of beta carotene

and vitamin D during storage (Chu et al., 2008; Khalid et al., 2017). Additionally,

sensory evaluation of these beverages was carried out determine their overall

acceptability. Sensory evaluation results indicate that the sensory score of these

134

Table 4.36: Physicochemical properties of beta carotene and vitamin D fortified

beverages

Parameters

Beta Carotene Fortified

Beverages

Vitamin D Fortified

Beverages

pH 5.8±0.11 6.1±0.17

Viscosity (cP) 4.22±0.07 4.31±0.03

°Brix 16.0±0.11 16.8±0.06

Vitamin (%) 81± 1.5 84± 1.8

Table 4.37: Sensory Evaluation of beta carotene and vitamin D fortified beverages

Parameters

Beta Carotene Fortified Beverages Vitamin D Fortified Beverages

0 Day 60 Days 0 Day 60 Days

Taste 7.4±1.15a 7.1±1.3b 7.5±1.2a 7.1±1.41b

Color 8.5±0.9a 8.0±1.13b 8±1.22a 7.7±1.25a

Flavor 8.5±1.5a 7.8±1.25b 8.4±1.25a 8±1.15a

Overall

Acceptability

8.2 ±1.7a 7.7±1.3b 7.8±0.9a 7.2±1.1b

135

beverages lies in acceptable limit (Table 4.37). Later on, these nanoemulsions are

stored at room temperature and their sensory evaluation was performed after two

months of storage. Sensory evaluation results indicate that the nanoemulsions

based beverages were still acceptable after two months of storage. The findings of

this study will be helpful for development of beverages fortified with lipophilic

compounds.

136

SUMMARY

Nutritional deficiency of vitamin A and D is causing a lot of problems in the

world. It is estimated that about one billion people worldwide are either vitamin D

deficient or have insufficient vitamin D intake. In Pakistan about 85% of both

pregnant and non-pregnant mothers have been found vitamin D deficient. Apart

from this, 5.7 million children below 5 years of age and 42.5 % women were

identified as vitamin A deficient in Pakistan. Being food fortification or

supplementation a best approach, the food manufacturers are interested in

fortifying their products with vitamin A and D. As both vitamins are restricted to

fats and oils due to their non-solubility in water. Nanoemulsions are ideal solution

to address this problem because this technique enhances the solubility, kinetic

stability, bio efficacy and bioavailability of encapsulated material due to their

smaller size. The purpose of present study was to fortify beverages with

nanoemulsions of vitamin A and D.

The nanoemulsions were prepared by using food grade surfactants (Tween

80 and soya lecithin), deionized water and vegetable oil (olive and canola oil).

Preparation conditions for beta carotene and vitamin D nanoemulsions were

optimized using response surface methodology. These nanoemulsions were further

characterized against different physico-chemical parameters. In vivo study was

carried out on animal model to investigate the safety of nanoemulsions. The

nanoemulsions based delivery system was used to fortify the beverages with these

vitamins.

The results manifested that, ideal optimum preparation conditions for beta

carotene nanoemulsions were 6.07% surfactant, 4.19 minutes homogenization time

136

137

and 6.50% oil contents. The experimental values at optimized preparation

conditions were 119.33nm droplet size, 2.67 p-Anisidine value and 85.63% β-

carotene retention. For vitamin D nanoemulsions, optimum preparation conditions

were 4.82 minutes homogenization time, 0.67 surfactant to oil ratio (S/O) and 7%

disperse phase volume. Whereas, the experimental values for droplet size, droplet

growth ratio (DGR) and vitamin D retention were 112.36 ± 3.6nm, 0.141 ± 0.07

and 76.65 ± 1.7% respectively.

During two months of storage studies, these nanoemulsions remained stable

against phase separation and creaming. Moreover, droplet size of nanoemulsions

stored at 4 °C slowly increased as compared to nanoemulsions stored at 25 °C.

Additionally, p-Anisidine value of the vegetable oil (canola and olive oil)

incorporated into nanoemulsions were significantly lower as compared to free

vegetable oil. These nanoemulsions were stable against droplet aggregation and

phase separation over a wide range of pH (2-8), salt concentration (50-400 mM)

and temperature (30-80°C). Additionally, these nanoemulsions were remain stable

during freeze-thawing cycles.

During toxicity study, bi-nuclear assay, multi-nuclear assay and comet assay

did not showed any toxic effect of nanoemulsions on animal models. However,

when higher amount of vitamins were used then mild toxic effects were observed

which were not higher enough to cause severe damage. Furthermore,

nanoemulsions increased the weight of experimental animals. During last part of

study, vitamin A and D fortified model beverages was developed successfully.

Hence, nanoemulsions based delivery system can be used for fortification of

aqueous products with fat soluble vitamins and other nutraceutical compounds.

138

RECOMMENDATIONS

Mixed surfactants should be used for the development of nanoemulsions

instead of using single surfactant.

Detailed studies should be carried out on nanoemulsion fortified beverages

in order to investigate their different physicochemical parameters.

Additional trail should be conducted at pilot scale for suitability and cost

effectiveness of nanoemulsions based fortified beverages for commercial

applications.

Further research should be conducted to determine the bioavailability of

vitamins in nanoemulsions based delivery system.

Food products should be fortified with fat soluble vitamins to address the

problem of vitamin A and D deficiency.

138

139

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Appendix 1: Approval certificate from ethical committee

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Appendix 2: Performa for sensory evaluation of fortified beverages

Name of judge: ___________________________ Date: _____________

Key for scoring

1. Extremely disliked

2. Very much disliked

3. Moderately disliked

4. Slightly disliked

5. Neither disliked nor liked

6. Slightly liked

7. Moderately liked

8. Very much liked

9. Extremely liked

Code Color Taste Flavor Overall acceptability

A

B

C

D

E

F

G

H

I

Signature of the judge: _______________

Contents lists available at ScienceDirect

Food Chemistry

journal homepage: www.elsevier.com/locate/foodchem

Optimization of mixed surfactants-based β-carotene nanoemulsions usingresponse surface methodology: An ultrasonic homogenization approach

Tahir Mehmooda,⁎, Anwaar Ahmeda, Asif Ahmada, Muhammad Sheeraz Ahmadb,Mansur Abdullah Sandhuc

a Institute of Food and Nutritional Sciences, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistanb Institute of Biochemistry and Biotechnology, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistanc Department of Veterinary Biomedical Sciences, PMAS-Arid Agriculture University, Rawalpindi 46300, Pakistan

A R T I C L E I N F O

Keywords:β-CaroteneNanoemulsionsRSMDroplet sizeMixed surfactantβ-Carotene retention

A B S T R A C T

In the present study, food grade mixed surfactant-based β-carotene nanoemulsions were prepared without usingany co-surfactant. Response surface methodology (RSM) along with central composite design (CCD) was used toinvestigate the effect of independent variables (surfactant concentration, ultrasonic homogenization time and oilcontent) on response variables. RSM analysis results revealed that experimental results were best fitted into aquadratic polynomial model with regression coefficient values of more than 0.900 for all responses. Optimizedpreparation conditions for β-carotene nanoemulsions were 5.82% surfactant concentration, 4 min ultrasonichomogenization time and 6.50% oil content. The experimental values at optimized preparation conditions were119.33 nm droplet size, 2.67p-Anisidine value and 85.63% β-carotene retention. This study will be helpful forthe fortification of aqueous products with β-carotene.

1. Introduction

β-Carotene is a member of the carotenoid family, which is mainlyfound in fruits and vegetables. It provides a substantial proportion ofvitamin A in the human diet because of its retinol precursor and higherconversion rate (Naves & Moreno, 1998). It is also useful in the pre-vention of numerous diseases, such as heart diseases, cataracts andcancer (Aherne, Daly, Jiwan, O’Sullivan, & O’Brien, 2010). Further-more, it is also used in the food industry as a colorant and antioxidant(Hou et al., 2012). Therefore, the food industry is interested in its in-corporation into food products to take advantage of the above-men-tioned benefits. However, its incorporation into beverages and variousother foods is challenging due to its poor water solubility, instability inheat, oxygen and light and appearance in crystalline state at ambienttemperature (Mattea, Martín, Matías-Gago, & Cocero, 2009). To over-come this problem, β- carotene can be dissolved in oil or another sui-table medium in oil in water emulsions before its incorporation intoaqueous food products (Qian, Decker, Xiao, & McClements, 2012).Stability of β-carotene in oil in water emulsion depends on the com-position of emulsion and environmental conditions, e.g. heat, surfac-tant, light, food systems, singlet oxygen and antioxidant addition (Houet al., 2010). The most convenient way to incorporate β- carotene intofood products is in a nanoemulsion based colloidal system.

Nanoemulsions are kinetically stable systems with mean radiiof< 100 nm. Furthermore, these emulsions have higher stability, so-lubility and bioavailability due to their smaller particle size as com-pared to conventional emulsions (McClements & Rao, 2011). Nanoe-mulsions can be produced using high energy and low energy methods.During high energy methods, intense disruptive force is generated tomechanically break the oil phase into tiny droplets, which can be dis-persed into the aqueous phase. These high energy methods (sonication,high pressure homogenization and microfluidization) are desirable forthe food industry because we can prepare nanoemulsions by usinglower surfactant to oil ratio as compared to low energy methods(Ozturk, Argin, Ozilgen, & McClements, 2014). Previously, some studieswere carried out on the preparation of β-carotene nanoemulsions usinglow energy methods, microfluidization and high pressure homo-genization but no study has been carried out on the preparation ofnanoemulsions through the ultrasonic homogenization method. Hence,the present study was designed to investigate the suitability of ultra-sonic homogenization for development of β-carotene nanoemulsions.

β-Carotene nanoemulsions prepared through the ultrasonic homo-genization method were influenced by multiple variables during ourlaboratory experiments (unpublished data). So, there is a need for op-timization of process or product in order to investigate the relationshipbetween independent variables and response variables. Response

https://doi.org/10.1016/j.foodchem.2018.01.136Received 8 October 2017; Received in revised form 4 January 2018; Accepted 22 January 2018

⁎ Corresponding author at: Institute of Food and Nutritional Sciences, PMAS-Arid Agriculture University, Rawalpindi, Pakistan.E-mail address: [email protected] (T. Mehmood).

Food Chemistry 253 (2018) 179–184

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surface methodology is an effective mathematical and statistical tech-nique to investigate the effects of multiple independent variables andtheir interaction on response variables (Li, Wang, & Wang, 2017;Mehmood, Ahmad, Ahmed, & Ahmed, 2017). Hence, in our study, wehave used RSM for optimization of emulsifying conditions.

The present study was designed to prepare mixed surfactant-based,co-surfactant free (due to irritation and toxic effects of co-surfactants)β-carotene nanoemulsions using an ultrasonication approach. Afterthat, preparation conditions (surfactant concentration, homogenizationtime and oil content) for β-carotene nanoemulsions were optimizedusing RSM in order to obtain smallest droplet size, lower p-anisidinevalue and maximum β-carotene retention.

2. Material and methods

2.1. Materials

Tween 80 and soya lecithin were obtained from Sigma-Aldrich (St.Louis, USA). Purified β-carotene (powder form) was supplied by BASF(Lampertheim, Germany). Olive oil (refined, bleached and deodorized)was purchased from Hamza Vegetable Oil Refinery and Ghee Mills(Lahore, Pakistan). Double distilled water was used for the preparationof nanoemulsions and solutions.

2.2. Nanoemulsions preparation

Nanoemulsions were prepared by mixing 10% dispersed phase and90% continuous phase. The dispersed phase was prepared by dissolvinga pre-determined amount of β-carotene in olive oil (5.48–10.52%). Thecontinuous phase consisted of double distilled water carrying pre-de-termined amount of surfactants (2.64–9.36%). These components weremixed with polytron (KRH-I, KONMIX, Shanghai, China) at 8000 rpmfor 7min to prepare coarse emulsions. For the preparation of nanoe-mulsions, these coarse emulsions were subjected to ultrasonic homo-genization by using a 20 kHz sonicator (230VAC, Cole-Parmer, USA).Ultrasonic homogenization was performed by placing the tip horn(20mm diameter) of the sonicator in coarse emulsions and applyingultrasonic powers for different times (2.98–8.02min). The temperatureof the emulsions was controlled by placing them in ice bath duringhomogenization. These nanoemulsions were stored at room tempera-ture for further analysis.

2.3. Droplet size analysis

The droplet size of the nanoemulsions was measured by dynamiclight scattering using nanotrac (Microtrac, Tri-Blue, USA).Nanoemulsion samples were diluted to 10% by using deionized water inorder to avoid multiple scattering effects.

2.4. p-Anisidine value

p-Anisidine value is an important indicator of the stability of na-noemulsions. The oxidative stability of β-carotene nanoemulsions wasdetermined according to the method of Mehmood et al. (2017). Firstly,20 g of β-carotene nanoemulsions were incubated for one week at 50 °C.Then, 1 g of solution was dissolved in n-Hexane (HPLC Grade) and theabsorbance of the solutions was measured using an UV-spectro-photometer at 350 nm. After that, 1 ml p-Anisidine reagent (preparedby dissolving 2.5 g of p-Anisidine in one litre of acetic acid) was addedin 5ml of solution and they were incubated for 10min to allow theirreaction. The absorbance of the fat solution was also determined as ablank in a reference cell. p-Aniside value was determined using Eq. (1):

− =× −p Anisidine Value 25 (1.2A A )

MAR BR

(1)

where AAR is the absorption of the solution after reaction, ABR

represents absorption before reaction and M denotes sample mass ingrams.

2.5. β-Carotene retention

The concentration of β-carotene in nanoemulsions was determinedafter one week by a spectrophotometric method. Firstly, a 1ml samplewas extracted using a mixture of n-Hexane (3ml) and ethanol (2 ml).After that, this mixture was shaken well and the hexane phase wasremoved. This extraction procedure was repeated two times more. Atthe end, all hexane phases were combined and their absorbance wasmeasured through an UV- spectrophotometer at 450 nm after desireddilution with n-Hexane. The β-carotene concentration was determinedusing a standard curve prepared under similar conditions. Vitamin re-tention was calculated using Eq. (2):

= ×VVR /V 100BC BC,N BC,I (2)

where VRBC represents β-carotene retention, VBC,N is the concentrationof β-carotene in the nanoemulsion and VBC,I indicates initial con-centration of β-carotene (Yuan, Gao, Zhao, & Mao, 2008).

2.6. Experimental design

Response surface methodology was used to investigate the effect ofindependent variables, including surfactant concentration (X1), ultra-sonic homogenization time (X2) and oil contents (X3) on responsevariables, such as droplet size (Y1), p-Anisidine value (Y2) and retentionof β-carotene (Y3) in nanoemulsions. RSM design along with coded anduncoded levels is presented in Table 1. Central composite design (Fivelevels) and quadratic model was used to design this experiment. Twentytreatments, including six axial points, eight fractional factorial pointsand six central points were randomly performed according to CCD,which is summarized in Table 1. Real levels of independent variableswere coded according to Eq. (3);

= −−Z ZZ Z /Δ0 C (3)

where Z and Z0 indicate coded and real levels of independent variables,respectively. ΔZ represents step change while ZC indicates actual valueat the central point. The specific equations for each independent vari-able were derived from the above equation to code their actual values.Specific equations for surfactant concentration (X1), ultrasonic homo-genization time (X2) and oil contents (X3) are mentioned in below Eqs.(4)–(6).

= −z (MS 6)/21 (4)

= −z (HT 5.5)/1.52 (5)

= −z (OC 8)/1.53 (6)

where MS, HT and OC represent surfactant concentration, homo-genization time and oil contents, respectively.

A second order polynomial equation was used to indicate the pre-dicted responses (droplet size, p-Anisidine value and retention of β-carotene) as a function of an independent variable as follows (Eq. (7)):

Table 1Independent variables and their corresponding levels for β- Carotene nanoemulsion.


−α −1 0 +1 +α

Surfactant Concentration (%) X1 2.64 4 6 8 9.36Homogenization Time (min) X2 2.98 4 5.5 7 8.02Oil Content (%) X3 5.48 6.5 8 9.5 10.52

T. Mehmood et al. Food Chemistry 253 (2018) 179–184

180

= + + + + + + + +

+

β β Y β Y β Y β Y β Y β Y β Y Y β Y Y

β Y Y

Z 0 1 1 2 2 3 3 11 12

22 22

33 32

12 1 2 13 1 3

23 2 3 (7)

where Z represents response values, β β βj jj jkindicates the values of linear,quadratic and interactive coefficients, respectively and β0is constant.Design expert software (version. 6.0.11) was used to calculate the va-lues of coefficients of determinations.

2.7. Statistical analysis

Experimental data were statistically analyzed using Design ExpertSoftware (version 6.0.11). Numerous statistical parameters (lack-of-fit,predicted and adjusted multiple correlation coefficients and coefficientof variation) of different polynomial models were compared to selectthe best fitting polynomial model. Significant difference was de-termined through analysis of variance by calculating F-value at theprobability of 0.5, 0.1 and 0.01. To understand the effect of emulsifyingconditions on response variables, response plots were generated usingDesign Expert Software (version 6.0.11). All these experiments wereperformed in triplicate.

3. Results and discussion

3.1. Fitting the model

Response surface methodology (RSM) is a statistical, theoretical andmathematical technique for model building in order to optimize thelevel of independent variables (Homayoonfal, Khodaiyan, & Mousavi,2015). The effect of independent variables (β-carotene nanoemulsions)on droplet size (Y1), p-Anisidine value (Y2) and retention of β-carotene(Y3) are given in Table 2. Coefficients of polynomial equation werecomputed from experimental data to predict the values of the responsevariable. Regression equations for each response variable, obtainedfrom response surface methodology are mentioned in Eqs. (8)–(10):

= + − + + + −

+ − − −

Droplet Size 101.66 12.16Y 22.83Y 0.74Y 1.53Y 1.76Y

0.37Y 0.96Y Y 0.46Y Y 0.39Y Y1 2 3 1

222

32

1 2 1 3 2 3 (8)

− = + − − − + +

+ − + −

p Anisidine Value 29.78 2.40Y 1.46Y 4.34Y 0.10Y 0.19Y

0.31Y 0.013Y Y 0.063Y Y 0.017Y Y1 2 3 1

222

32

1 2 1 3 2 3 (9)

− = + + + − −

− + − − +

β Carotene Retention 16.43 21.23Y 22.68Y 16.19Y 0.80Y

1.90Y 0.93Y 0.79Y Y 0.29Y Y 0.17Y Y1 2 3 1

2

22

32

1 2 1 3 2 3

(10)

Statistical analysis (ANOVA) results revealed that the experimentaldata could be represented well with a quadratic polynomial model withcoefficient of determination (R2) values for droplet size (Y1), p-Anisidine value (Y2) and retention of β-carotene (Y3) being 0.9456,0.9580 and 0.9604, respectively (Table 3).

Lack of fit was non-significant (p≤ 0.05) relative to pure error forall variables, which indicates that our model is statistically accurate. Ifthe value of R2 is closer to unity then it is the indication of better modelfitting to actual data. On the other end, lower values of R2 indicate thatresponse variables were not appropriate to explain the variation inbehaviour (Myers, Montgomery, & Anderson-Cook, 2016). In our study,proximity to unity R2 demonstrates that the influence of surfactantconcentration (X1), ultrasonic homogenization time (X2) and oil con-tents (X3) on response variables could be adequately described througha quadratic polynomial model. Significance level for coefficients of thequadratic polynomial model were determined through analysis of var-iance (ANOVA). Smaller P-value and larger F-value is the indication of ahighly significant effect of any term on the response variable(Quanhong & Caili, 2005).

3.2. Effect of independent variables on response variables

β-Carotene nanoemulsions were successfully prepared by usingdifferent levels of independent variables (Fig. 1). The effect of in-dependent variables on droplet size, p-anisidine value and β-caroteneretention are given in Table 2. Regression coefficients for independentvariables are summarized in Table 3.

3.2.1. Droplet sizeThe droplet size of β-carotene nanoemulsions depended on surfac-

tant concentration due to its significant effect on droplet size at a linear(p < 0.001), quadratic (p < 0.001) and interaction level (p < 0.05)with homogenization time. Surfactants lower the interfacial tensionsbetween disperse and continuous phase, which leads to smaller dropletformation (Mehmood et al., 2017). Other independent variables, whichhad significant effect on droplet size were linear term of homogeniza-tion time (p < 0.001) and oil content (p < 0.05), and quadratic termsof homogenization time (p < 0.001).

The influence of homogenization time and surfactant concentrationon droplet size of β-carotene nanoemulsions is illustrated in Fig. 2 (A).Both these variables exert quadratic effect on droplet size. At highersurfactant concentration, decrease in droplet size of nanoemulsions wasobserved with the increase of homogenization time. This downward

Table 2Experimental design for β- Carotene nanoemulsions with independent variables, experi-mental and predicted values of responses.

Run Independent Variables Response Values

Surfactant (%) Time(min)

OilContent(%)

DropletSize (nm)

p-AnisidineValue

β- Caroteneretention(%)

1 8 4 6.50 121 1.5 942 6 5.50 8 110 3.2 773 4 7 6.50 115 6.3 644 6 5.50 5.48 111 3.3 925 8 4 9.50 125 5.2 846 6 8.02 8 89 5.6 667 9.36 5.50 8 122 2.1 868 6 5.50 10.52 124 7.1 829 6 5.50 8 114 4.1 8010 6 5.50 8 110 3.7 7611 8 7 9.50 101 5.9 7512 8 7 6.50 104 3.1 8213 6 5.50 8 117 3.6 8314 6 5.50 8 121 3.5 8015 4 4 6.50 124 5.3 6516 4 4 9.50 130 7.5 6017 6 5.50 8 117 4 8018 2.64 5.50 8 143 6.7 5819 6 2.98 8 119 3.3 7220 4 7 9.50 121 9.1 59

Table 3Regression coefficients values for β- Carotene nanoemulsions.

Regressioncoefficients

Droplet size(nm)

p-AnisidineValue

β- CaroteneRetention (%)

Intercept (α0) 114.85 3.66 79.43A-Surfactant (α1) −5.44*** −1.48*** 9.82***

B-Time (α2) −8.01*** 0.64** −2.42*

C-Oil (α3) 2.55* 1.31*** −3.21**

A2 (α11) 6.13*** 0.41* −3.21**

B2 (α22) −3.95** 0.43* −4.27***

C2 (α33) 0.82 0.69*** 2.09*

AB (α12) −2.88* −0.038 −2.37*

AC (α13) −1.38 0.19 −0.87BC (α23) −0.88 −0.037 0.38R2 0.9456 0.9580 0.9604


181

trend was observed due to reduction of interfacial tension with theincrease in surfactant concentration (Polychniatou & Tzia, 2018). Atlower surfactant concentration, droplet size increased with increasinghomogenization time. This increase was observed because not enoughemulsifier is present to cover newly formed smaller droplets, whichinitiates a coalescence process (Anarjan, Mirhosseini, Baharin, & Tan,2010). Fig. 2(B) represented the combined effect of oil and surfactantconcentration on the droplet of β-carotene nanoemulsions. Oil contentexerts a linear effect while surfactant concentrations have a quadraticeffect on droplet size of nanoemulsions. Droplet size increased withrising oil concentration due to increase in viscosity. As a result of this,higher energy is required to break the droplet, which results in largerdroplet size. Additionally, higher oil concentration encourages ag-gregation and collision of nanoemulsion droplets, which increased thedroplet size (Mehmood, 2015; Zhang, Fan, & Smith, 2009). Initially,droplet size decreased with the increase of surfactant concentration dueto reduction in surface tension. But, after a minimal level, higher con-centration of surfactant caused increased width of the diffusion layerdue to excessive coverage of crystalline particles by surfactant. Thismechanism lowers zeta potential value and encourages agglomerationtendency, which increased droplet size of β-carotene nanoemulsions(Mehmood et al., 2017; Tan, Billa, Roberts, & Burley, 2010).

3.2.2. p-Anisidine valuep-Anisidine value is an important indicator for measurement of

oxidation products (Cho, Kim, Bae, Mok, & Park, 2008). As the p-Ani-sidine value of β-carotene nanoemulsions was concerned, oil contenthad a pronounced effect on the p-Anisidine value of β-carotene na-noemulsions due to its significant effect on p-Anisidine value at a linear(p < 0.001) and quadratic level (p < 0.001). Other factors whichsignificantly contribute toward p-Anisidine value were linear term ofsurfactant concentration (p < 0.001) and homogenization time(p < 0.001), and quadratic term of surfactant concentration(p < 0.05) and homogenization time (p < 0.05). The lipid oxidationmechanism is remarkably different in nanoemulsions as compared withbulk oily phase due to the presence of interface and aqueous phase. Innanoemulsions, lipid oxidation depends on many factors, which includeoxygen concentration, pH and ionic strength of aqueous phase, dropletsize, thickness and interfacial properties (Waraho, McClements, &Decker, 2011; Öztürk, Urgu, & Serdaroğlu, 2017).

The combined effects of homogenization time and surfactant con-centration on p-Anisidine value are illustrated in Fig. 2(C), which ex-plicated the linear effect of both independent variables on p-Anisidinevalue. p-Anisidine value of β-carotene nanoemulsions increased with

the increase in homogenization time while higher concentration ofsurfactants result in a lower p-Anisidine value. During this study, β-carotene nanoemulsions were developed using mixed surfactant(Tween 80 and soya lecithin), which act as an interfacial barrier againstoxidation. These surfactants built a protective membrane at the inter-face of the aqueous and oily phase, which remarkably reduces proox-idant accessibility into oil droplets, which results in lower p-Anisidinevalue (Hwang et al., 2017). Fig. 2(D) depicts the interactive effect of oilcontent and surfactant concentration on p-Anisidine value. Both vari-ables have a linear effect on the p-Anisidine value of β-carotene na-noemulsions. The downward trend was observed in p-Anisidine valuewith the increase of surfactant and oil concentration. Oil concentrationshave an inverse effect on p-anisidine value because droplet size in-creases when oil concentration is high, which results in lower p-Anisi-dine value due to reduced surface area for oxidation (Mehmood et al.,2017).

3.2.3. β-Carotene retentionβ-Carotene retention of nanoemulsion mainly depended on surfac-

tant concentration as it had a significant effect on vitamin retention atlinear (p < 0.001), quadratic (p < 0.01) and interactive level(p < 0.05). Surfactant prevents the degradation of β-carotene byforming a membrane like structure around new surfaces (Hejri,Khosravi, Gharanjig, & Hejazi, 2013). Other factors which significantlycontributed to β-carotene retention were linear effect of homogeniza-tion time (p < 0.05) and oil content (p < 0.01), quadratic effect ofhomogenization time (p < 0.001) and oil content (p < 0.05) and in-teractive effect of homogenization time (p < 0.05).

A contour plot in Fig. 2(E) illustrates the retention of β-carotene as afunction of homogenization time and surfactant concentration. Sur-factant concentrations have a linear effect while homogenization timeexerts a quadratic effect on the retention of β-carotene. At a lower levelof surfactant, β-carotene retention is significantly reduced with in-creasing homogenization time due to the formation of smaller droplets,which are not covered with surfactant molecule. Hence, surface area ofdroplet significantly increases, which encourages β-carotene degrada-tion (Waraho et al., 2011). Additionally, pre-existence of peroxides insurfactant molecules may also cause β-carotene degradation. Theseperoxides breakdown into reactive radicals at elevated temperature andsignificantly degrade β-carotene during storage (Liu & Wu, 2010).Fig. 2(F) represents the interactive effect of oil content and surfactantconcentration on the β-carotene retention in nanoemulsions. Bothemulsifying conditions have a linear effect on β-carotene retention.With the increase in surfactant concentration, degradation of β-

Fig. 1. (A) Particle size distribution of β-carotene nanoe-mulsions (B) Visual appearance of β-carotene nanoemul-sions.


182

carotene reduced due to the formation of a rigid surfactant shell at thewater–oil interface. This shell increases the stability of β-carotene bypreventing repulsion of β-carotene and avoiding new surface formation(Hejri et al., 2013). Higher oil content also increases the stability of β-carotene nanoemulsions by formation of larger droplets, which havelower surface area (Liu & Wu, 2010).

3.3. Optimization of independent variables

To illustrate the effects of surfactant concentration, homogenizationtime and oil content on response variables, response surface graphswere drawn using design expert software. These graphs were generatedby varying two independent variables within experimental ranges while

keeping the third variable at central point. Fig. 2(A, C and E) weregenerated by varying the surfactant concentration and homogenizationtime at 8% oil content, while Fig. 2(B, D and F) were drawn by chan-ging the concentration of oil and surfactant at a central value ofhomogenization time (5.5 min). These graphs illustrated complex in-teraction among independent variables.

After that, numerical optimization was executed by desirabilityfunction using Design Expert Software. The goals selected for the op-timization of β-carotene nanoemulsions were minimum level of sur-factant concentration, homogenization time and oil content in order toobtain smaller droplet size, lower p-Anisidine value and maximum re-tention of β-carotene. Ten different solutions were found which containdifferent levels of independent variables. The solution with maximum

Fig. 2. 3D graphic surface optimization of(A) droplet size (nm) versus surfactant con-centration (%) and homogenization time(min) (B) droplet size (nm) versus oil content(%) and surfactant concentration (%) (C) p-Anisidine value versus surfactant concentra-tion (%) and homogenization time (min) (D)p-Anisidine value versus oil content (%) andsurfactant concentration (%) (E) β-caroteneretention (%) versus surfactant concentra-tion (%) and homogenization time (min) (F)β-carotene retention (%) versus oil content(%) and surfactant concentration (%).


183

desirability value was selected as the optimized emulsifying condition.Combined optimized preparation conditions for β-carotene nanoemul-sions were 5.82% surfactant concentration, 4min. ultrasonic homo-genization time and 6.50% oil content. The response values at opti-mized preparation conditions were 116.46 nm droplet size, 2.937p-Anisidine value and 82.085% β-carotene retention (Table 4).

3.4. Verification of RSM model

Optimized emulsifying conditions were used to check the suitabilityof the model for prediction of response values. Optimized preparationconditions were validated by performing experiments under optimizedconditions. The response values at optimized preparation conditionswere 116.46 nm droplet size, 2.937p-Anisidine value and 82.085% β-carotene retention. On the other hand, the experimental values at op-timized preparation conditions were 119.33 nm droplet size, 2.67p-Anisidine value and 85.63% β-carotene retention. Experimental re-sponse values were well in agreement with predicted response values(Table 4).

4. Conclusions

In this study, we have evaluated the preparation conditions of β-carotene nanoemulsions using ultrasonic homogenization techniquesand incorporated β-carotene in mixed surfactant-based nanoemulsionsin order to protect β-carotene from harsh environmental conditionsduring food fortification. Mixed surfactant-based β-carotene nanoe-mulsions were successfully prepared using an ultrasonic homogeniza-tion approach. This study illustrates that response surface methodologyis a useful tool to optimize the emulsifying conditions of β-carotenenanoemulsions and explore the relationship between independent andresponse variables. The results of this study showed that emulsifyingcondition and ingredients have significant effect on the properties ofnanoemulsions. The current study illustrates that the quadratic modelwas sufficient to describe and predict the responses of droplet size, p-Anisidine value and β-carotene retention, with the change of in-dependent variables (surfactant concentration, homogenization timeand oil content). The optimum condition was obtained through nu-merical optimization using desirability function. Optimized preparationconditions for β-carotene nanoemulsions were 5.82% surfactant con-centration, 4min. ultrasonic homogenization time and 6.50% oil con-tent.

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Table 4Optimum conditions, experimental and predicted value of response at optimized condi-tions.


Surfactant Concentration (%) −0.09 5.82Homogenization Time (min) −1.00 4Oil Contents (%) −1.00 6.50


Droplet Size (nm) 116.46 119.33 ± 2.5p-Anisidine Value 2.937 2.67 ± 0.9β- Carotene Retention (%) 82.085 85.63 ± 1.5


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