Emulsification properties of cheese powders in oil …...from Camembert or Cheddar cheeses, with and without the addition of ES. Oil-in-water (O/W) emulsions Oil-in-water (O/W) emulsions

U N I V E R S I T Y O F C O P E N H A G E N

F A C U L T Y O F S C I E N C E

Emulsification properties of cheese powders in

oil-in-water (O/W) emulsions

Master Thesis

Kalliopi Vlachvei (jvr250)

Supervisors: Lilia Ahrné and Denise Felix da Silva

Submitted on: 5th of March 2018

Abstract

Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e I

Abstract Over the last years consumer preferences have changed. Their demands for clean, “green” labels with fewer

ingredients have increased, leading to an increased interest in natural ingredients.

Cheese powders are used as flavor ingredients in food formulations such as dips, sauces, soups and dressings.

In addition to boosting both flavor and taste, cheese powders may also act as emulsifiers when added to

emulsion-like systems. During cheese powder production, the use of different cheeses or the addition of

ingredients, such as emulsifying salts (ES), are able to affect the emulsification properties of the produced

cheese powders due to changes in the protein conformation. Though, no systematic research of the

emulsification properties of cheese powder exists.

The aim of the present project was to investigate the emulsification properties of cheese powders produced

from Camembert or Cheddar cheeses, with and without the addition of ES. Oil-in-water (O/W) emulsions

(20:80 w/w) were prepared using sunflower oil and cheese powders at 1.5, 3.0 and 4.5 % (w/w in protein

basis), homogenized at 60MPa and stored for twenty days. Physical stability, flow properties, particle size,

and microstructure were investigated during storage time.

Results indicated a decrease in particle size with increasing protein concentration, for emulsions containing

cheese powder with or without ES. However, a bimodal (two different populations) size distribution was

observed in the emulsions containing cheese powder without ES. Increasing the protein content from 1.5 to

4.5 % tended to change the flow properties of the emulsions from Newtonian to shear thinning. The physical

stability was significantly improved for all emulsions by increasing the protein content. Light microscopy

images showed spherical particles and confirmed the presence of smaller droplets for all emulsions. Thus,

cheese powder can be successfully used as an emulsifier in O/W emulsions, and a better emulsification was

observed when ES were used during powder manufacture. Hence, the addition of cheese powder can

eliminate or reduce the need for other added emulsifiers.

Acknowledgments

Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e II

Acknowledgments This Master thesis concludes the Master of Science (MSc) in Dairy Science and Technology, at the University

of Copenhagen. This project was performed during the period from 1st of September to 5th of March, at the

Department of Food Science and was supervised by Ph.D. student Denise Felix Da Silva and Professor Lilia

Ahrné.

I would like to thank both of my supervisors for their advice, help and inspiration during the execution of the

project. Professor Lilia steered me in the right direction and motivated me, whilst also proposed different

ways on confirming the validity of my results. Denise contributed a lot with her experience on similar topics,

and was always available when I needed it with a helpful answer and supported me in every situation I faced

during and until the completion of the project. I would also like to thank the associate professor Anni Bygvrå

Hougaard for her assistance and suggestions during the development of the project.

Furthermore, I would like to thank Danai Tziouri and Inger Hansen from Lactosan A/S, for including and

trusting me with this project and for helping me in order to understand the manufacturing process of cheese

powders.

Finally, I would like to express a profound appreciation to all my family, and especially to my parents and my

sister, who supported me when I decided to come to Denmark for my studies. Without their help and

continuous support I wouldn’t achieved my goals. A big thank to all my dearest friends, who supported me

during this two and a half amazing and unforgettable years of master studies and who became a second

family for me in Denmark.

____________________

Kalliopi Vlachvei

5th March 2018

Table of Contents, Figures & Tables

Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e III

Table of Contents Abstract .............................................................................................................................................................. I

Acknowledgments ............................................................................................................................................. II

Abbreviations.................................................................................................................................................... VI

1. Introduction ............................................................................................................................................... 1

2. Objectives .................................................................................................................................................. 3

2.1. General Objectives ............................................................................................................................ 3

2.2. Specific Objectives ............................................................................................................................. 3

3. State of the art ........................................................................................................................................... 4

3.1. Cheese powders ................................................................................................................................ 4

3.2. Emulsions ........................................................................................................................................... 5

3.2.1. Emulsion systems ...................................................................................................................... 5

3.2.2. Emulsion formation and stability .............................................................................................. 5

3.2.3. Emulsifiers ............................................................................................................................... 10

3.3. Analytical methods .......................................................................................................................... 13

3.3.1. Stability analyses ..................................................................................................................... 13

3.3.2. Rheological properties ............................................................................................................. 14

3.3.3. Microstructure ......................................................................................................................... 15

4. Materials and Methods ........................................................................................................................... 17

4.1. Materials .......................................................................................................................................... 17

4.2. Experimental Design ........................................................................................................................ 17

4.3. Methods .......................................................................................................................................... 18

4.3.1. Composition of cheese powders ............................................................................................. 18

4.3.2. Preparation of cheese emulsions ............................................................................................ 18

4.3.3. Particle size measurements ..................................................................................................... 19

4.3.4. Rheological properties ............................................................................................................. 19

4.3.5. Physical stability of emulsions ................................................................................................. 19

4.3.6. pH measurements of emulsions .............................................................................................. 19

4.3.7. Emulsion microstructure ......................................................................................................... 20

4.3.8. Statistical analysis .................................................................................................................... 20

5. Results and Discussion ............................................................................................................................. 21

5.1. Composition of cheese powders ..................................................................................................... 21

5.2. Particle size ...................................................................................................................................... 21

5.3. Rheological behavior ....................................................................................................................... 26


Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e IV

5.4. Physical stability .............................................................................................................................. 30

5.5. Characterization of cheese emulsions ............................................................................................. 32

5.5.1. pH............................................................................................................................................. 32

5.5.2. Microstructure: Light Microscopy (LM) ................................................................................... 32

6. Conclusions .............................................................................................................................................. 34

7. Perspectives ............................................................................................................................................. 35

References ....................................................................................................................................................... 36

Appendix: Statistical analyses ......................................................................................................................... 41

Table of figures

Figure 1:The key role of emulsifiers (i) facilitate the formation of emulsions and (ii) promote emulsion

stability (McClements & Jafari, 2017)................................................................................................................ 6

Figure 2: A two-step emulsification process for oil-in-water emulsions using a high-shear mixer (i) for the

formation of the initial emulsion and a high-pressure valve homogenizer (ii) for the formation of the final

emulsion (McClements & Jafari, 2017; McClements & Gumus, 2016). ............................................................ 7

Figure 3: Instability mechanisms occurring in oil-in-water emulsions (Piorkowski & McClements, 2013;

McClements & Gumus, 2016; McClements & Jafari, 2017). ............................................................................. 9

Figure 4: Lipid droplets are stabilized, by natural emulsifiers, against aggregation via steric and/or

electrostatic interactions. Based on the thickens, chemistry and charge of the emulsifier molecules the

relative magnitude of the mentioned interactions can differ (McClements & Gumus, 2016). ...................... 10

Figure 5: Interfacial structures of different natural emulsifiers (Ozturk & McClements, 2016). .................... 10

Figure 6: Migration of globular proteins to the water – oil interface: A) absorption of proteins on the

droplet surface, B) and C) formation of viscoelastic film (Lam & Nickerson, 2013). ...................................... 12

Figure 7: Viscosity (η) of Newtonian, shear thinning and shear thickening fluids as a function of shear rate

(http://www.rheosense.com/applications/viscosity/newtonian-non-newtonian ). ...................................... 14

Figure 8: Particle size distribution of the two different Camembert type cheese emulsions containing

different protein content in period of twenty days. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts;

RDA: spray drying tower with rotary atomization system; BD: spray drying tower with nozzles and fluid bed

drying). ............................................................................................................................................................. 23

Figure 9: Particle size distribution of the two different Cheddar type cheese emulsions containing different

protein content in period of twenty days. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA:

spray drying tower with rotary atomization system; BD: spray drying tower with nozzles and fluid bed

drying). ............................................................................................................................................................. 24

Figure 10: Apparent viscosity of Camembert and Cheddar type cheese emulsions as a function of shear

rate. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary

atomization system; BD: spray drying tower with nozzles and fluid bed drying). .......................................... 28

Figure 11: Backscattering (%) profiles of O/W cheese emulsions during twenty days. (Cam: Camembert;

Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary atomization system; BD: spray

drying tower with nozzles and fluid bed drying). ............................................................................................ 31

Figure 12: Light micrographs of O/W (20:80) cheese emulsions in different protein contents a) 1.5%, b)

3.0% and c) 4.5%. The scale bar shows a length of 10 μm. (Cam: Camembert; Ched: Cheddar; ES:


Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e V

emulsifying salts; RDA: spray drying tower with rotary atomization system; BD: spray drying tower with

nozzles and fluid bed drying). .......................................................................................................................... 33

Table of tables

Table 1: Characteristics of the industrial grade powders provided by Lactosan A/S (Ringe, Denmark). ....... 17

Table 2: Experimental design of different cheese type emulsions. ................................................................ 18

Table 3: Mean values (±SE below) of the chemical composition of industrial grade cheese powders. ......... 21

Table 4: Mean values (±SE below) of the particles size (μm) obtained from the first and second peak of the

size distribution graphs. .................................................................................................................................. 26

Table 5: Power Law model parameters (mean values ±SE below). ................................................................ 29

Table 6: pH of all cheese emulsions at the first and last day of storage (mean values ±SE). ......................... 32

Abbreviations

Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e VI

Abbreviations BD: belt drier (two-stage spray dryer)

BS: backscattering

CCP: colloidal calcium phosphate

ES: emulsifying salts

LM: light microscopy

O/W/O: oil-in-water-in-oil

O/W: oil-in-water

OR: Ostwald ripening

PIC: phase inversion composition

PIT: phase inversion temperature

R: resolution

RDA: rotary disc atomizer (one-stage spray drier)

SC: sodium caseinate

SE: spontaneous emulsification

SLS: static light scattering

SWP: sweet whey powder

T: transmission

TS: total solids

W/O/W: water-in-oil-in-water

W/O: water-in-oil

Introduction

Emulsification Properties of Cheese Powder in Oil-in-Water (O/W) Emulsions P a g e 1

1. Introduction

Emulsions are widely present in food systems in different forms such as sauces, ice-cream, mayonnaise, salad

dressings or butter (de Figueiredo Furtado et al., 2017). Emulsions are thermodynamically unstable systems

of two immiscible liquids, where one system is dispersed into the other. They are mainly divided into two

categories, oil-in-water (O/W) and water-in-oil (W/O) based on the continuous phase, water or oil

respectively. Besides the two phases, emulsifiers are commonly used in emulsions to create a stable structure

(Walstra, 2005).

Food emulsifiers can exhibit different functions related to texture. Thus, when emulsifiers are added in

emulsion systems, they promote the formation of small droplets during homogenisation, providing stability

and controlling potential destabilisation. Emulsifiers can either be synthetic or natural (Chen, 2015). Lately,

the increased demands from consumers for “green” label products, also increase the interest of industries

for the replacement of synthetic emulsifiers with natural alternatives (Ozturk & McClements, 2016). By

adding the appropriate emulsifier into the oil and water mixture, a molecule orientation at the interface

between the aqueous phase and the oil droplets is performed. The hydrophilic parts of the emulsifier are

absorbed in the water phase and respectively the hydrophobic parts in the oil phase. As a result, the surface

tension of the oil droplets decreases and during mechanical shear the droplets can be subdivided into smaller

ones (Miller, 2016). Therefore, it is clear that in order to form an emulsion, a high mechanical shear rate is

required. The use of rotor-stator or high pressure homogenizer can be beneficial to produce homogeneous

emulsions (Hebishy et al., 2017).

The stability of an emulsion can be influenced over a period of time. Thermal and gravitational effects lead

to a continuously moving and collision between the dispersed droplets in an emulsion. The kinetic state of a

dispersed droplet and also the interactions between them are responsible for the stability of the final

emulsion. According to Yamashita et al. (2017), by controlling the interface and bulk properties of the

dispersed droplets, the stabilization of an emulsion can be achieved easier. Different destabilization

phenomena, like creaming, sedimentation, coalescence or flocculation can appear upon storage time.

Therefore, the choice of the appropriate emulsifiers is crucial. It is challenging to decrease the interfacial

tensions between two droplets. Hence, the addition of surface active or polysaccharides can be beneficial

due to the formation of an interfacial membrane around the droplets.

The molecular weight and the concentration of the emulsifier are related with the absorption rate. High

molecular weight surfactants, such as proteins or polysaccharides, form an interfacial membrane with

increased viscoelastic properties compared to lower molecular weight surfactants, such as phospholipids.

The formation of an interfacial membrane with highly viscoelastic properties, leads slower kinetic

destabilization by steric and repulsive electrostatic interactions between the droplets and therefore, higher

resistance to stress (Costa et al., 2017).

The amphiphilic nature and electrical charge character of proteins allows them to be used as emulsifiers. The

amphiphilic nature refers to their tendency to be absorbed both on the oil and aqueous phase during

homogenisation. In protein emulsifiers, the interfacial membrane that is formed is quite thin and electrically

charged. Therefore, in order to prevent droplet flocculation and further destabilization, the performance of

electrostatic repulsion is essential. However, emulsions that have stabilized with the addition of protein

based emulsifiers are sensitive both to pH changes and ionic strength effects. More precisely, pH values close

to the isoelectric point of the absorbed proteins, and a high level of ionic strength lead to flocculation of the

Introduction


formed emulsion. This destabilization may occur because the electrostatic repulsion between the droplets is

not enough to overcome the attractive interactions between them (Burgos-Díaz et al., 2016). Protein

ingredients are widely used as emulsifiers and are sold in form of powders (Chen, 2015).

Cheese powders are widely used as flavor ingredients in an extensive variety of food systems. They are also

used as multifunctional ingredients leading to visual changes in different food systems, such as improving

texture, mouth feel and colour. Cheese powder may also act as an emulsifier when added to emulsion-like

systems. However, no systematic investigation of the emulsification properties of cheese powder existed.

Their functionality might be related with their protein content, which is based on the raw cheese materials

from which they are produced (Felix da Silva et al., 2017).

The aim of this study is to investigate the emulsification properties of different cheese powders in oil-in-

water (O/W) emulsions. To achieve this, four different cheese powders provided from Lactosan A/S were

used. For the control sample, sodium caseinate was used. The O/W emulsions (20:80) were prepared in three

different protein concentrations for each cheese powder type. A high pressure homogenizer was used to

obtain the final cheese emulsion. The stability and properties of the obtained emulsions were determined by

analysing the particle size distribution, the physical stability by the Turbiscan method, and the rheological

and microstructural properties of the emulsions.

Objectives


2. Objectives

2.1. General Objectives

The general objective of the study was to evaluate the emulsification properties of different types of cheese

powders as natural emulsifiers, in O/W emulsions.

2.2. Specific Objectives

To understand the emulsification properties of cheese powders manufactured with different cheese

types and the addition of emulsifying salts in O/W emulsions.

To examine the physical and structural deformation of the O/W emulsions, containing 1.5, 3.0 and

4.5% (w/w in protein), due to modifications on the protein concentration.

To evaluate the stability of the O/W emulsions containing cheese powders during storage.

State of the Art


3. State of the art

3.1. Cheese powders

Cheese powders are multifunctional ingredients that improve both the flavor and texture when they are

added to different food products (Felix da Silva et al., 2018). One of the advantages of using cheese powders

as additional ingredients in food products is that they can easily be added on the surface of different snack

foods or incorporated into food formulations (e.g. sauces, dressings, creams, soups). Moreover, due to their

low water activity, cheese powders have a long shelf life, allowing them to be stored for longer periods

without alteration or deterioration of quality. Most importantly, cheese powders can be produced from a big

variety of cheese types (e.g. Cheddar, Gouda, Camembert, or Danbo) giving them a greater diversity of flavor

and functional characteristics (Guinee & Kilcawley, 2017).

The production steps of cheese powder include the cutting and mincing of cheese, the melting of the minced

cheese blended with water, emulsifying salts (ES) and other ingredients such as skim milk solids, whey

lactose, maltodextrins or flavor enhancers. Heating of the melted blend and homogenisation of it is following

in order to form a homogeneous emulsion, called cheese feed. The last step and most important is the spray

drying of the cheese feed in order to produce a powder with low moisture content and increased shelf life

(Koca et al., 2015).

The functionality of cheese powders in an emulsion-like system may be affected by many factors including

the composition of different cheeses used, the addition of ES and the applied spray drying technology (Kelimu

et al., 2017). Addition of different ingredients, like maltodextrin or whey powder, is able to reduce the cost

of the raw cheese materials and upgrade the physical and rehydration properties of the final powders (Felix

da Silva et al., 2018). Moreover, the addition of ES is responsible for keeping the emulsion more stable until

and during spray drying. However, lately, the demands for “green label” products have increased leading to

the reduction of content or the removal of ES (Felix da Silva et al., 2017).

In the food industry there are different spray dryer designs that can be used in food powder production.

However, in the dairy industry, the most commonly used spray dryers are one-stage and two-stage spray

dryers (Felix da Silva et al., 2017). Apart from the different designs, spray dryers can differ also in their

operation systems (atomizer type and pressure, air flow direction, air inlet, outlet temperature or air

humidity). Both flavor and physical characteristics, such as the bulk density, wettability, and solubility, of

cheese powders can be influenced by the different spray dryer designs and their operations (Guinee &

Kilcawley, 2017). Before the cheese feed is ready to pass through the spray dryer, it is important to ensure

that the total solids (TS) content is around 35% in order to get a feed, which at 75oC, is not too viscous for

atomization (Písecký, 2005).

In general, the principle of a one-stage spray dryer is that the product is drying in the drying chamber until a

target final moisture is achieved. The given powder consists of single particles with increased bulk density.

On the contrary, a two-stage spray dryer includes an initial spray drying followed by a second stage of drying

(either in a form of fluid bed or belt dryer), where the final moisture content is achieved. A two-stage spray

drier is preferable for very low moisture content powders. Furthermore, is suitable for improving the thermal

efficiency, lowering the outlet temperature and improving the physical properties of powders by

agglomeration (Felix da Silva et al., 2017).

State of the Art


3.2. Emulsions

3.2.1. Emulsion systems

Emulsion is defined as a mixture of two or more immiscible liquids, where one of them is dispersed in the

other one in a form of small droplets (0.1-100 μm) (Sullo & Norton, 2016; Walstra, 2005; Romero et al., 2017).

Common emulsions consist of two phases: an aqueous and an oil phase. Based on the properties of each

phase, there are two mainly types of emulsions, oil-in-water (O/W) such as milk, cream or salad dressings

and water-in-oil (W/O) like butter and margarine (Lam & Nickerson, 2013). When the oil is the dispersed

phase and water is the continuous one, then the emulsion is called oil-in-water. Respectively, when water is

the dispersed phase and oil the continuous one then the emulsion is called water-in-oil (Lam & Nickerson,

2013; McClements & Gumus, 2016; Romero et al., 2017).

However, there are other types of emulsions which are referring in more advanced systems as multiple

emulsions (W/O/W or O/W/O) or nanoemulsions and can be very beneficial in pharmaceutical applications

(Lam & Nickerson, 2013).

The formation of an emulsion can conventionally be achieved by applying a high mechanical shear (such as

a rotor-stator, high pressure homogenisation or ultrasound) to the mixture (Lam & Nickerson, 2013; Sullo &

Norton, 2016; McClements & Jafari, 2017). This will facilitate the creation of small droplets of the dispersed

phase into the continuous one, until the size of the droplets reaches the desired size of the final product

(Sullo & Norton, 2016). Furthermore, emulsions can be stabilised with the addition of an emulsifier, which

contains hydrophilic and hydrophobic parts. When these parts are absorbed on either water-oil or oil-water

interface, then they combine together in order to reduce the interfacial tension (Lam & Nickerson, 2013).

Based on the properties of the continuous phase, dispersed phase and the interface, the final properties of

an emulsion, such as stability or droplet size, can change (Romero et al., 2017). Therefore, both the type of

the emulsifier that is used and the mechanical energy that is applied to produce emulsions are significant

factors for the reduction of the droplet size and the adsorption of the surfactant onto the interface (Costa et

al., 2017).

3.2.2. Emulsion formation and stability

The key role of emulsifiers in successful emulsions is two-fold. First they accommodate the initial formation

of the emulsions, which is happening during homogenisation, and second they promote the stability of the

lipid droplets once they have been formed and consequently the stability of the final emulsion (Figure 1)

(Ozturk & McClements, 2016; McClements & Gumus, 2016). Emulsifiers are absorbed on the surface of the

small droplets, which have been formed due to mechanical shear, and therefore reduce the interfacial

tension and enable the droplet distribution (Burgos-Díaz et al., 2016). It is important that the surfactant is

soluble in at least one of the two phases so that it is active during emulsification (Walstra, 2005).

State of the Art


Figure 1:The key role of emulsifiers (i) facilitate the formation of emulsions and (ii) promote emulsion stability (McClements & Jafari, 2017).

Formation

The formation of emulsions can be affected either by the choice of the emulsifier and/or the homogenisation

step (McClements & Gumus, 2016; Walstra, 2005; Ozturk & McClements, 2016). To determine whether an

emulsifier is appropriate and effective for the formation of a successful emulsion with small droplets during

the homogenisation step, different parameters should be considered. Such as:

(i) Surface activity: In order to characterize an emulsifier as surface-active, it should have the

appropriate ratio of polar and non-polar groups on its surface so that it is able to adsorb on the oil-

water interfaces (McClements & Jafari, 2017; Ozturk & McClements, 2016). For example, if an

emulsifier has more hydrophilic amino acids, then the surface activity will not be considerable. On

the other hand, emulsifiers with more hydrophobic amino acids tend to be insoluble in water and

can more readily form aggregates with poor surface activity (McClements & Gumus, 2016). According

to McClements and Jafari (2017), the adsorption on the interface is stronger when the emulsifier is

more surface active.

(ii) Adsorption kinetics: Rapid adsorption of the emulsifier on the droplet surface results in rapid

reduction of the interfacial tension and therefore prevents aggregation or coalescence (Ozturk &

McClements, 2016; McClements & Jafari, 2017; McClements & Gumus, 2016; Walstra, 2005). If the

adsorption occurs before the collision of the oil droplets then the prevention of droplet coalescence

will be achieved. Respectively if the adsorption is too slow and the droplets coalesce without the

existence of an emulsifier, then the homogenisation step will not be efficient (McClements & Jafari,

2017). This is strongly connected with the molecular weight of the emulsifier that is used. The smaller

the molecular weight the faster the diffusion on the interface (Lam & Nickerson, 2013; McClements

& Gumus, 2016; Tavernier et al., 2016).

(iii) Interfacial tension reduction: The interfacial tension should be reduced by the absorbed emulsifiers

and therefore promote the droplet disruption during homogenisation (Ozturk & McClements, 2016).

According to Taylor (1998), reduction in interfacial tension can also affect the stability of an emulsion.

(iv) Stabilization: One of the main roles of the absorbed emulsifiers is to protect the formed droplets

from aggregation. This can happen by producing strong repulsive interactions (steric or electrostatic)

(Ozturk & McClements, 2016; McClements & Jafari, 2017; McClements & Gumus, 2016). Small

droplets tend to have more stable emulsions (Walstra, 2005).

State of the Art


(v) Surface coverage: In order to stabilize an emulsion, a specific amount of emulsifier is required. This

amount depends on the mass of the emulsifier per unit surface area at saturation, known as surface

load (Ozturk & McClements, 2016). High surface load leads to an increased amount of emulsifier, so

that the final emulsion remains stable (McClements & Jafari, 2017; Ozturk & McClements, 2016;

McClements & Gumus, 2016; McClements, 2004). According to McClements and Jafari (2017), the

surface load of some commonly used food emulsifiers increases in the following order: small

molecule surfactants < phospholipids < globular proteins < flexible proteins < polysaccharides. If

there is insufficient emulsifier to cover all the droplets of the system, then the formation of gaps

around the droplets will appear and consequently, the possibility of droplet coalescence is highly

likely to occur. This type of coalescence is more likely to perform during homogenisation due to the

formation of new surfaces by the intensive forces of stirring (McClements, 2004).

(vi) Droplet size during homogenisation: The homogenisation step can be performed either by a high

pressure valve homogenizer, which is the most commonly used equipment for the formation of

emulsions (Hebishy et al., 2017; de Figueiredo Furtado et al., 2017; McClements & Gumus, 2016;

McClements & Jafari, 2017) or by low-energy methods, such as spontaneous emulsification (SE),

phase inversion temperature (PIT) and phase inversion composition (PIC) (Lefebvre et al., 2017;

Galindo-Alvarez et al., 2011). The amount of pressure used can affect the droplet size. By increasing

the pressure, the mean droplet diameter decreases. However, the dependence of such a relationship

is based on the emulsifier type and the amount which was used. An excessive amount of emulsifier

with increased homogenisation pressure will lead to a continuous decrease of the droplet diameter.

A commonly used emulsifying method includes the formation of an initial emulsion and afterward the

formation of the final emulsion using a high-pressure valve homogenizer Figure 2. First, the blending process

of oil and water in the presence of an emulsifier creates an initial emulsion with large droplets (d>1 μm)

coated around with the used emulsifier. However, a considerable amount of emulsifier remains in the water

phase and thus the second step of homogenisation is required. For that reason, a high-pressure valve

homogenizer is used resulting in small droplets (d<1 μm) (McClements & Gumus, 2016; McClements & Jafari,

2017). Consequently, in such a process the over mentioned parameters considered important.

Figure 2: A two-step emulsification process for oil-in-water emulsions using a high-shear mixer (i) for the formation of the initial emulsion and a high-pressure valve homogenizer (ii) for the formation of the final emulsion (McClements & Jafari, 2017; McClements & Gumus, 2016).

State of the Art


Stability

Emulsions are thermodynamically unstable systems, meaning that their appearance can change over time

due to many different instability mechanisms that affect the behavior of the droplets in the emulsion

(Walstra, 2005; McClements & Gumus, 2016; McClements & Jafari, 2017). The variety of destabilization

mechanisms includes creaming, sedimentation, flocculation, coalescence and Ostwald ripening (Ozturk &

McClements, 2016; Sullo & Norton, 2016; McClements & Jafari, 2017; McClements & Gumus, 2016; Walstra,

2005; Dickinson, 1997; Piorkowski & McClements, 2013) as described in Figure 3.

The stability, of emulsions, in a period of time, is important for their functionality and is highly depending on

the nature of the used emulsifier (McClements & Gumus, 2016). The different destabilization mechanisms

are outlined below.

Gravitational Separation: Due to gravitational forces the droplets can either rise (creaming) or sink

(sedimentation) and therefore decrease the energy of the entire system (Walstra, 2005). Formation of

droplets with a lower density compared to the density of the aqueous phase leads to an upwards movement

known as creaming effect. On the other hand, the formation of droplets with a density higher than the

aqueous phase leads to a downward movement of the droplets known as sedimentation effect (Piorkowski

& McClements, 2013). Stokes’ Law describes these effects according to the following equation (1)

(McClements & Jafari, 2017):

𝑽 = - 𝟐𝒈𝒓𝟐(𝝆𝟐−𝝆𝟏)

𝟗𝒏𝟏 (1)

Where: v= velocity at which the droplets move, g= gravitational field, r=droplet radius, ρ1= density of the

continuous phase, ρ2= density of the dispersed phase and η= shear viscosity.

Increased droplet size, droplet radius and decreased shear viscosity leads to faster creaming (McClements &

Jafari, 2017; McClements & Gumus, 2016).

Flocculation: The phenomenon where at least two droplets aggregate without losing their individual

dimensions (Piorkowski & McClements, 2013). The aggregation of two protein-covered droplets in an

emulsion occurs due to the free energy of the interaction between them that becomes significantly negative

to a degree of separation (Dickinson, 1997). Strong interactions like van der Waals, hydrophobic or depletion

are developing between the droplets and overshadow the repulsive interaction such as steric or electrostatic

(McClements & Jafari, 2017). Due to flocculation emulsions tend to appear higher in viscosity and are even

capable to form gels leading to undesirable results (Piorkowski & McClements, 2013).

Coalescence or Ostwald ripening: The process where at least two droplets join together creating a large

individual droplet is known as coalescence (McClements & Gumus, 2016). By increasing the particles size,

emulsions tend to cream faster. The nature of the forces that are rising between the droplets and the

resistance of the interfacial layer to breakage, regulates the sensitivity of them to coalescence (Piorkowski &

McClements, 2013). As in flocculation, the attractive forces between droplets overshadow the repulsive

forces. When the droplets merge, the interfacial layers around them incline to breakage. Therefore, by using

mixed emulsifiers with good resistance in breakage, the coalescence process can be suspended (McClements

& Jafari, 2017). When partially crystalline lipid droplets join together, it leads to clump formation. This

process is called partial coalescence due to the fat crystal network inside the droplets that are unable to fully

merge (McClements & Gumus, 2016).

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Similar to coalescence, Ostwald ripening (OR) is the process where small droplets begin to spread by the

continuous phase leading to larger droplets and consequently increasing the average droplet size of the

emulsion (Walstra, 2005). The main reason for this process is the solubility of the oil molecules. Small droplets

are faster solubilized compared to larger droplets due to curvature effects (Taylor, 1998; Kabalnov &

Shchukin, 1992). More soluble oil phases, such as essential oils, tend to create more unstable emulsions

compare to less soluble oil phases (i.e. vegetable oils) (Piorkowski & McClements, 2013).

Figure 3: Instability mechanisms occurring in oil-in-water emulsions (Piorkowski & McClements, 2013; McClements & Gumus, 2016; McClements & Jafari, 2017).

The strength of the interactions between the droplets can be influenced either by the nature of the acting

forces or by the emulsifier layer. As was mentioned above, the type of emulsifier used is responsible for the

creation of destabilization mechanisms. For example, the use of emulsifiers, which produce strong repulsive

interactions, can prevent potential droplet aggregation (Ozturk & McClements, 2016). When attractive

interactions (van der Waals, hydrophobic and depletion) are in majority, then the droplets tend to aggregate.

Respectively, the majority of repulsive interactions (steric and electrostatic) lead to more stable emulsions

(McClements & Gumus, 2016). The different interactions that are arising between the droplets vary in their

type (attractive or repulsive), extent (strong to weak), range (short to long) and the factors that are affecting

them (Piorkowski & McClements, 2013). The mechanisms which provide stability in the emulsions are known

as electrostatic and steric stabilization Figure 4 (McClements & Gumus, 2016).

Steric stabilization: Based on the thickness and the way the emulsifier molecules are packed at their surfaces,

the range and extent of the steric repulsion in between the droplets can be influenced. The formation of

thick interfacial layers leads to short and strong steric repulsion (McClements & Gumus, 2016). Therefore,

when the interfacial layers of two droplets overlap, a short range of repulsive interactions emerges known

as steric stabilization. The thicker and the more hydrophobic the interfacial layers are, the stronger the

repulsive interactions and thus the better the steric stabilization (Ozturk & McClements, 2016).

Electrostatic stabilization: Droplets with electrical charges around their surface are responsible for the

creation of electrical interactions with short-to-long range and strong-to-weak extent (Piorkowski &

McClements, 2013). If the charges are similar then the electrostatic interactions are based on the surface

charge density as well as the ionic strength of the surrounding solution are factors that can influence the

range and the extent of the electrostatic interactions between two droplets (Ozturk & McClements, 2016).

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When the number of charge groups (surface charge density) around the droplets increases and the ionic

strength decreases, then the strength of the repulsive forces between the droplets increases too. Strong

repulsive forces keep the droplets separate before they can make contact and coalesce leading to more

stable emulsions (McClements & Gumus, 2016; Ozturk & McClements, 2016).

However, the stability of the emulsions can also be influenced by other interactions taking place during

emulsification, such as hydrophobic, covalent and overall interactions. These interactions are also based on

the used emulsifier and its properties (Walstra & Smulders, 1997).

Figure 4: Lipid droplets are stabilized, by natural emulsifiers, against aggregation via steric and/or electrostatic interactions. Based on the thickens, chemistry and charge of the emulsifier molecules the relative magnitude of the mentioned interactions can differ (McClements & Gumus, 2016).

3.2.3. Emulsifiers

There are different types of emulsifiers either in the form of low-molecular weight synthetic emulsifiers or

natural emulsifiers (Lam & Nickerson, 2013; Ozturk & McClements, 2016). According to Romero et al. (2017),

in food systems the O/W interface is typically stabilized by proteins, low- molecular weight emulsifiers

(monoglycerides, phospholipids and esters) or a combination of them. Most of the low-molecular weight

emulsifiers that can be found in the food industry are synthetic molecules like Spans, Tweens, CITREM and

DATEM. These have a non-polar tail group and a polar head group (McClements & Jafari, 2017). The term

natural emulsifiers refers to proteins, phospholipids, polysaccharides or other biosurfactants or bioparticles

and are known for their advantages in the food emulsions (Figure 5) (Chen, 2015). Therefore, they have been

used as an alternative to synthetic emulsifiers.

Figure 5: Interfacial structures of different natural emulsifiers (Ozturk & McClements, 2016).

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Proteins

Proteins contain a mixture of both hydrophobic and hydrophilic amino acids and therefore are surface active

meaning that they have the ability to adsorb onto oil-water surfaces and coat the oil droplets which have

been formed during the homogenisation step (Ozturk & McClements, 2016). Since proteins are amphiphilic

substances, they can reduce the interfacial tension due to coating with oil droplets and therefore prevent

from aggregation or coalescence (McClements & Gumus, 2016; Ozturk & McClements, 2016; Lam &

Nickerson, 2013). The relative balance between polar and non-polar amino acids controls the surface activity

of the proteins. Thus, if the hydrophobicity of the surface is significantly high then proteins are more likely

to aggregate, lose their solubility in water and their surface activity (McClements & Gumus, 2016).

Moreover, the stabilization of the oil droplets is enhanced due to the existence of the amino acid groups

which contain negative or positive charges and consequently occur electrostatic repulsions (Ozturk &

McClements, 2016). The functional properties of emulsions can be influenced by the electrical properties of

the proteins. Thus, electrostatic repulsion has a crucial meaning in preventing aggregation of oil droplets

(McClements & Gumus, 2016). The physical and chemical stability of the final emulsion can easily be

influenced by the electrical characteristics of the proteins, which can move the charging point from positive

(at a low pH) to negative (at a high pH). The isoelectric point (pI) is the pH where the protein carries no

electrical charge and for most of the food proteins is around pH 5 but for some others is based on the amino

acid composition and can vary from higher to lower pI values (McClements & Jafari, 2017).

In the food industry, the most commonly used protein-based emulsifiers are caseins (αs1-, αs2-, β- and κ-

caseins), which have a flexible structure and whey proteins (α-lactalbumin, β-lactoglobulin, BSA and

immunoglobulins) which are characterized for their globular structure and therefore they are less flexible

compared to caseins (Ozturk & McClements, 2016; McClements & Jafari, 2017; Lam & Nickerson, 2013).

Other protein-based emulsifiers with flexible structures but inferior stabilization properties are gelatins

extracted from cow, pig or fish. Moreover, proteins from plant-sources like peas, soy and corn germ are also

known as protein-based emulsifiers (Ozturk & McClements, 2016). Based on the structure of the protein

emulsifiers, the properties of the interface that is formed, and consequently the properties of the final

emulsion, can be influenced (McClements & Jafari, 2017).

As was mentioned above caseins and whey proteins are widely used for their emulsification properties.

Globular proteins, like whey proteins, consists of polypeptide chains with the hydrophobic amino acids

oriented into the core and the hydrophilic amino acids towards the edges, resulting to a water soluble

behavior (Costa et al., 2017). Though, some of the hydrophobic amino acids are still exposed on their

surfaces, facilitating an adsorption on oil-water interfaces and thereafter improving the surface activity of

globular proteins (McClements & Gumus, 2016). Moreover, due to their conformation and surface charge

density, globular proteins can be very sensitive and be influenced by changes in the temperature or pH (Costa

et al., 2017).

On the other, caseins are more flexible due to their open structure. This flexible structure leads to

conformational changes in such a way so that the hydrophilic groups jut out in the water phase and the

hydrophobic into the oil phase (Ozturk & McClements, 2016). However, after the adsorption of the proteins

into the oil-water interfaces the structure of the proteins can change due to environmental changes

(McClements & Gumus, 2016). For example, globular proteins like whey proteins after adsorption into the

interface can partially unfold and appear groups (non-polar) which are located inside them. Proteins, which

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are adsorbed either into the same or different oil droplets, will react between them. This will result in

formation of cohesive viscoelastic layers (Ozturk & McClements, 2016; McClements & Gumus, 2016).

Proteins are slightly bigger (≈ 10-50 kDa) than saponins and phospholipids (≈ 1.67 kDa and ≈ 0.760 kDa

respectively), and need more time in order to diffuse in the interface. By the moment they reach the

interface, a degree of partial denaturation is required so that the hidden hydrophobic amino acids appear

again on the surface. This procedure is illustrated in Figure 6. The final rearrangement of the proteins on the

oil-water droplets is arranged in such a way that the hydrophobic amino acids are located inside the oil

droplets and the hydrophilic amino groups on the aqueous phase, resulting to the formation of strong

viscoelastic layers (Lam & Nickerson, 2013).

Figure 6: Migration of globular proteins to the water – oil interface: A) absorption of proteins on the droplet surface, B) and C) formation of viscoelastic film (Lam & Nickerson, 2013).

Sodium caseinate

Sodium caseinate (SC) is a commercial milk protein ingredient, which is used as an emulsifier in the food

industry (Liang et al., 2017b; de Figueiredo Furtado et al., 2017). SC molecules have a low-molecular weight

of around 20 kDa and a flexible structure (de Figueiredo Furtado et al., 2017). They consist of four main

caseins (αs1-, αs2-, β-, and κ-) commonly used as a macromolecular soluble emulsifier in a big variety of dairy

products such as ice cream or whipped toppings (Zinoviadou et al., 2012). SC is known for its excellent

functional properties (Hadj Sadok et al., 2008). Colloidal calcium phosphate (CCP) is removed, during the

production of SC, in order to let the casein convert to small aggregates (Huck-Iriart et al., 2016). SC is also

devoid of whey proteins and lactose (Liang et al., 2017a).

During emulsification the basic caseins, which are surface active, easily adsorb at the oil-water interface due

to repulsive stabilization mechanisms (Dickinson, 2006; Zinoviadou et al., 2012; Hebishy et al., 2017; Liang et

al., 2017a). When the pH is close to the isoelectric point of proteins (4.6), then even with the addition of SC,

emulsions are unable to remain stable. This is due to the reduction of electrostatic repulsions between the

oil droplets (Zinoviadou et al., 2012).

According to Costa et al. (2017), the emulsifying properties of SC cannot be influenced by the homogenisation

process. However, changes in the structure have appeared on SC under ultrasound treatment. The changes

on the structure of SC are similar to the structure of globular or fibrous proteins. Ultrasound is a medium to

high energy treatment creating small particles. Ultrasound-treated caseinates have small structure and lower

polydispersity compared to caseinates that have been aggregated into the aqueous phase. Though, the

droplets size, between caseinates that haven’t been treated and caseinates that have been ultra-treated in

order to form emulsions, was similar. Concluding, the adsorption rate of SC into O/W interface is not affected

by changes in the structure and consequently by different homogenisation processes (Costa et al., 2017).

Moreover, much research has been done on the heat stability of SC, and has found that in general extensive

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heating results to polymerization and degradation of SC based also on different heating time (Liang et al.,

2017a).

3.3. Analytical methods

3.3.1. Stability analyses

Particle size distribution

One way of determining the physical stability is by studying the particle size distribution. The size distribution

of different liquid suspensions, emulsions and other ingredients like powders, is important because it can

affect the taste, the appearance, the texture and the stability of the final product. In liquid products, such as

emulsions the size of the dispersed phase droplets has a significant impact on stability and taste and must

therefore be controlled and stabilized during manufacture (Moore & Cerasoli, 2017). Defining the

suspension’s stability of particles or droplets into a liquid medium, is very common for a diverse range of

applications in food industries (Larsson et al., 2012).

Static light scattering (SLS) is a method used for the determination of the particles size. This optical method

measures the intensity of the scattered light in dependence of the scattering angle to obtain information on

the scattering source. In order to calculate the particle size distribution a theory which relates the size

distribution to particle size is required. Mie theory is based on Maxwell’s electromagnetic field equations and

predicts the scattering intensity induced by all particles within the measurement range, either if they are

transparent or opaque. The principle behind Mie’s theory is that the measured particles are large, spherical

and homogeneous so that the light is scattered by one particle and detected before it interacts with other

particles (Moore & Cerasoli, 2017).

Physical stability

The analysis of the destabilization mechanism in concentrated dispersed media is also related with the

determination of the physical stability. Emulsions, in general, have been studied for their physical properties

(e.g. particle size) involving some form of dilution. When a formulation is diluted then the disruption of some

structures facilitates potential destabilization. However, if concentrated formulations, like emulsions, are not

disturbed, diluted or stressed, then at an early stage can show different destabilization phenomena such as

creaming, sedimentation, agglomeration, aggregation, and coalescence. The ability of studying an emulsion

without any kind of dilution or disruption can provide important information about its stability over time.

The Turbiscan method is ideal for scanning the turbidity profile of an emulsion towards the length of glass

tube, which is filled with the sample. The different profiles, extracted from the scanning, compose the

fingerprint of the emulsion over a period of time (Herrera, 2012).

Based on the principle of multiple light scattering, light is sent into the sample. This light after being scattered

by objects in suspension (e.g. droplets or solid particles) emerges from the sample and is detected by the

measurement device. A reading head, which consists of a light source (NIR diode) and two detectors

(transmission (T) and backscattering (BS)), moves upwards and in a vertical direction while scanning the glass

tube that contains the sample. Turbiscan software enables the interpretation of the obtained data and the

quantification of different parameters. BS and T values are related to the particles average diameter (d) and

the volume fraction (φ) and therefore, their profiles allow the calculation of creaming, sedimentation, phase

separation or other mechanisms that makes the dispersion unstable during time (Herrera, 2012).

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3.3.2. Rheological properties

Rheology, studies the deformation and the flow behavior of any kind of material including liquid, solid or gas

(Kasapis & Bannikova, 2016). In food emulsions rheology is related with the texture and mouth feel of foods

obtained from these emulsions (Tatar et al., 2017), but it is also important during processing operations of

emulsion like for example mixing, pumping, and packaging.

The rheological properties are defined based on the stress applied on the material and the consequence

deformation as a function of time. In order to have a comprehensive picture of the deformation that was

caused, it is necessary to collect rheological measurements. The basic parameters involved in these

measurements are stress, strain and viscosity (Kasapis & Bannikova, 2016).

Stress (σ), is the applied force per unit area (Pa or N/m2) and the type of stress is defined by the

direction of the force on the surface of the studied material. The direction of the force can be either

an extension or compression.

Strain, represents the extent of deformation. Also, known as shear rate and means the rate of change

of strain as function of time

Viscosity (η), is the resistance to the flow of a fluid and is determined as the ratio of the applied

shearing stress (τ) to the rate of shear strain (γ̇).

Based on Newton’s law, for viscous liquids, the applied stress is linearly proportional to the rate of shear

strain. Though the applied stress is independent of the strain, meaning that the viscosity (η) is a constant.

Equation (2) refers to Newtonian fluids.

η = 𝝉

𝒅𝜸/𝒅𝒕=

𝝉

�̇� (2)

In Non-Newtonian fluids, the viscosity is shear rate dependent. A shear thinning behavior is achieved when

the viscosity decreases with increasing the shear rate. The solution is said to have pseudoplastic (shear

thinning) flow behavior. On the other hand, when the viscosity of a solution increases with increasing shear

rate, then it has a shear thickening flow behavior (Figure 7) (Chhabra, 2010; Kasapis & Bannikova, 2016).

Figure 7: Viscosity (η) of Newtonian, shear thinning and shear thickening fluids as a function of shear rate (http://www.rheosense.com/applications/viscosity/newtonian-non-newtonian ).

http://www.rheosense.com/applications/viscosity/newtonian-non-newtonian

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The rheological properties of a material can influence the visual and textural perception and also affect the

processing capability. The shear thinning behavior can be measured using the Power Law Model. The use of

this model can be done by calculating the Power law region of a flow curve:

σ = 𝒌 ∗ �̇� ̇𝒏 or η = 𝒌 ∗ �̇�𝒏−𝟏 (3)

Where: k, is the consistency; n, is the power law index; σ, is the shear rate; η, is the viscosity and γ̇, is the

shear rate consistency.

When n=0 it refers to very shear thinning materials and when n=1 it refers to Newtonian materials (Malvern

Instruments Limited, 2015).

3.3.3. Microstructure

Microscopic techniques, like Light Microscopy (LM), provide information about the structure and dimensions

of the emulsions droplets. In order to determine protein location in space and time, microscopic techniques

are valuable. Each of the above techniques works in different principles (Sjollema et al., 2012).

LM is used in both physical and life science and is considered as a very quantitative method. For the

characterization of emulsion systems, LM is widely used because it can easily be performed and the cost of

use is very low. A light microscope is used to detect small objects by applying visible light. In order to achieve

accurate data, three main aspects are of high importance: the aspects of the microscope, the sample and the

detector. A light microscope consists of three components. These are the eye piece, the objective and an

elimination source, known as condenser, and can influence the quality of the image. The objective and

condenser are made of lenses and thereby their performance is related with the component lenses light

transmission. The power of the objectives is defined by their resolution (R), which defines the ability to

distinguish two significantly small objects. The best R can be obtained when the distance between the two

objects is very small. To determine R different physical parameters are required, such as the wavelength of

light (λ) and the light-gathering power of the objective and the condenser lenses, known as numerical

aperture (A). The following equation defines the limits of light microscopy (Lovitt & Wright, 2014).

𝑹 =𝟎.𝟔𝟏∗𝝀

𝑨 (4)

The numerical aperture describes the ability of the objective to collect the rays coming from each illuminated

point. Large values of the numerical aperture leads to increased resolution (Lovitt & Wright, 2014).

The selection of objective lens is crucial in light microscopy in order to give the best results. The clarity of the

obtained image is a result of six or more pieces of glass combined together. The main role of these glasses is

to provide corrections in order to improve the clarity of the image. In most of the microscopes, the objective

lenses are achromats. Such lenses are suitable for imaging with green light. Green filters are preferable

because they are capable to narrow the bandwidth of the light and allow the achromat objectives to work

effectively (Deagle et al., 2017).

The last and more essential factor in obtaining a good and clear image with a light microscope is the

illumination. This factor is responsible for receiving sufficient levels of light in the sample or object plane. LM

works in a broad field of illumination, meaning that the volume of sample above and below the focusing level

is illuminated evenly and simultaneously. Thus, a thin and relatively transparent sample is required. However,

such a sample sometimes leads to blur and out of focus results, that reduces the resolution. For optimal

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imaging is necessary to obtain bright light around the sample and uniform across the field of view. The image

can be viewed either directly from the eye piece or focused on a detector, like an electronic camera (Lovitt

& Wright, 2014).

For emulsion microstructure, LM has some limitations. Most LM images show only the spherical drops

without in-depth informations about the individual components (Hu et al., 2017).

Materials and Methods


4. Materials and Methods

4.1. Materials

The used cheese powders were industrial grade powders provided by Lactosan A/S (Ringe, Denmark). In total,

four different cheese powder types were studied in this project. The classification of the given cheese

powders was based on the type of cheese (Camembert or Cheddar), the addition of emulsifying salts and the

type of the spray drier in which they were produced. The types of spray dryers were a one-stage spray drier

with a rotary disk atomizer (RDA) and a two-stage spray drier with a belt dryer (BD). The characteristics of

the provided cheese powders are shown in Table 1 below.

Table 1: Characteristics of the industrial grade powders provided by Lactosan A/S (Ringe, Denmark).

Sample Cheese type ES Spray dryer

Cam_noES_RDA Camembert No RDA

Cam_ES_RDA Camembert Yes RDA

Ched_ES_BD Cheddar Yes BD

Ched_ES_RDA Cheddar Yes RDA

Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary atomization system; BD: spray drying tower with nozzles and fluid bed drying.

Sodium caseinate (88.0% protein, 0.30% lactose, 1.5% fat, 6.0% moisture, 1.65% salt, 4.5% ash, pH 6.5) was

purchased from Friesland Campina DMV (Amersfoort, The Netherlands)) and used for the preparation of the

control sample with 1.5% (g/100) concentration.

Sodium azide (M = 65.01 g/mol) was purchased by Merck KGaA (Darmstadt, Germany) was added to all

samples to prevent potential bacterial growth. Sunflower oil was (Svanso, Sacandic Food A/S, Vejle,

Denmark) used for the preparation of the cheese emulsions.

4.2. Experimental Design

A total of twelve O/W emulsions based on different types of cheese powders and protein levels (%) was

prepared in replicates. Four different cheese powders (Cam_noES_RDA, Cam_ES_RDA, Ched_ES_BD,

Ched_ES_RDA) in three protein concentrations (1.5%, 3.0%, 4.5%) were prepared. Sodium caseinate (SC) was

used in a concentration of 1.5 % (w/w) for comparison. The experimental design and the amount of relevant

ingredients used are shown in Table 2. The amount of water and sunflower oil were the same for all of the

samples including the control.

After the preparation of the cheese emulsions all samples were stored at ambient temperature (20oC). The

analyses were performed on day 0 (preparation day), day 5, day 10, day 15 and day 20.



Table 2: Experimental design of different cheese type emulsions.

Sample Protein content (%) SC (%) Water (%) Sunflower oil (%)

Control - 1.5 80 20

Cam_noES_RDA 1.5 - 80 20 3.0 - 80 20 4.5 - 80 20

Cam_ES_RDA 1.5 - 80 20 3.0 - 80 20 4.5 - 80 20

Ched_ES_BD 1.5 - 80 20 3.0 - 80 20 4.5 - 80 20

Ched_ES_RDA 1.5 - 80 20 3.0 - 80 20 4.5 - 80 20

Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary atomization system; BD: spray drying

tower with nozzles and fluid bed drying.

4.3. Methods

4.3.1. Composition of cheese powders

The chemical analyses of the used cheese powders were performed according to the standard techniques

(AOAC, 1990). Fat content was measured by Gerber-van Gulik method, protein content was specified by

Kjeldahl method using a nitrogen-to protein conversion factor of 6.38 and soluble nitrogen at pH 4.6 was

defined by acid precipitation. Both moisture and ash content were determined according to the gravimetric

method at 100oC and 525 ± 25oC, respectively. The salt content was obtained by potentiometric titration

and the pH values were measured using a digital laboratory pH meter with electrode holder (Two-Channel-

Multi-Meter HQ440d, HACH LANGE GMBH, Düsseldorf, Germany). Lactose was measured using an enzymatic

method (ISO 2002a). All chemical measurements were performed in triplicate.

4.3.2. Preparation of cheese emulsions

The emulsions containing cheese powders were prepared in three steps. Firstly, protein solutions were

prepared by mixing the specific amount of cheese powder considering the desired protein concentration

(1.5%, 3.0%, 4.5%) for each sample with distilled water using a magnetic stirrer. In order to avoid any

microbial growth, sodium azide (0.5g/1LH2O) was added to the protein solution. All samples were left on a

magnetic stirrer over-night at room temperature (20oC) to allow protein rehydration (Hebishy et al., 2017;

de Figueiredo Furtado et al., 2017).

In the second step, the protein solutions were heated at 60oC to ensure the complete melting of fat and

homogeneity of the solution and mixed with oil at 4000 rpm for 4 min. In the third step, emulsions were

submitted to a homogenisation at 60 MPa (Emulsiflex C5, AVESTIN, Canada). Emulsions were collected and

left for 2 hours to reach room temperature (20oC) prior to analysis.

Each of the different cheese emulsions was formed on independent occasion. The entire experiment was

repeated twice.



4.3.3. Particle size measurements

The determination of the particle size distribution of the cheese emulsions was based on the static light

scattering method and was performed using Mastersizer 3000 (Malvern Instruments Co. Ltd.,

Worcestershire, UK) at 20oC. For all emulsions the reflective index was set to 1.47, the absorption of the

dispersed phase was set to 0.001 and the refractive index of the continuous water phase was 1.330 (Kelimu

et al., 2017). The cheese emulsions were gently mixed before each measurement and were added in small

droplets into a de-ionized water chamber until the obscuration was approximately 6%. The droplet size

distribution curves were obtained and the mean particle size was calculated. Each cheese emulsion was

measured in triplicate.

4.3.4. Rheological properties

Rheological behavior measurements were performed by a controlled stress Rheometer (AR-G2, TA

Instruments, New Castle, DE, USA). A Peltier Concentric Cylinder Temperature System with a cone and cup

(diameter 30 mm) geometry type using a gap of 7000 μm was used to perform the measurements at 20oC as

previously described by Kelimu et al. (2017).

Initially, all emulsions were gently mixed and approximately 20mL was added in the cup. Two continuous

ramp steps were performed for the determination of the flow measurements and the relevant flow curves

were obtained. The shear rates were increased from 1 to 300 s-1 over 5 min (upward curve) and decreased

from 300 to 1 s-1 over the same time (downward curve). The apparent viscosity along with shear stress and

shear rate values were obtained. The Power Law model (equation 5) was fitted by linear curve fitting in Origin

Pro 9.1 (OriginLab Corporation, Northampton, MA, USA). The flow properties parameters (n and k) were

obtained. (Kelimu et al., 2017; Capitani et al., 2016; Malvern Instruments Limited, 2015). Each emulsion was

measured in triplicate.

𝝈 = 𝒌�̇�𝒏 (5)

Where σ= shear stress (Pa), k= consistency index (Pa sn), �̇�= shear rate consistency (s-1) and n= power law

index or flow behavior index (dimensionless).

4.3.5. Physical stability of emulsions

The stability of cheese emulsions was determined by using a vertical scan analyser Turbiscan MA 2000

(Formulaction, Toulouse, France) in the backscattering (BS) mode. After preparation of the cheese emulsions,

5 mL were pureed in a cylindrical glass tube, sealed with a plastic cap and stored at 20 ± 2.0 °C. Samples were

analyzed during storage in days 0 ( preparation day), 5, 10, 15, 20 and Turbisoft software (Formulaction,

2005) was used to obtain the backscattering curves (Hebishy et al., 2017; Capitani et al., 2016). Each cheese

emulsion was measured in triplicate.

4.3.6. pH measurements of emulsions

The pH of each of the final cheese emulsions was obtained by a digital laboratory pH meter with electrode

holder (Two-Channel-Multi-Meter HQ440d, HACH LANGE GMBH, Düsseldorf, Germany). For the

calibration, buffers of pH 4.0, 7.0 and 10.0 were used. The pH values were obtained on day 0 (preparation

day) and day 20.



4.3.7. Emulsion microstructure

To evaluate the microstructure of all emulsions Light Microscopy (LM) was performed. An optical microscope

OLYMPUS BX53 (Hamburg, Germany) with a lens magnitude of 100x and a digital camera was used. A small

sample of the emulsion was placed on a microscope slide and covered with the relevant glass cover slip of 2

mm thickness (Capitani et al., 2016; de Figueiredo Furtado et al., 2017).

4.3.8. Statistical analysis

The statistical analyses were performed using MINITAB 18.0 software. For the treatment of data, analysis of

variance using generalised linear models (GLM) was conducted to identify differences among samples (p-

value< 0.05). Also, One-way ANOVA was performed for some of the examined factors. When significant

differences were observed, paired comparisons between means were examined using Tukey’s test. However,

for the identification of differences among samples Moreover, the main effects and the interactions between

the factors were also obtained.

Results and Discussion


5. Results and Discussion

5.1. Composition of cheese powders

In Table 3 the composition of the used cheese powders is shown. Statistical significant differences (p< 0.05)

were found in pH, moisture, fat, protein, soluble nitrogen at pH 4.6, ash, salt and lactose content between

the different cheese powders. Camembert type powders had similar pH values around of 5.80 and 5.90,

where Cheddar type was characterized by having a pH value of around 6.00. The moisture content in

Camembert type powders produced by the same spray dryer (RDA) was similar between 2.65% and 2.60%.

The moisture content has increased in BD spray dryer compared to RDA in Cheddar type powders.

Table 3: Mean values (±SE below) of the chemical composition of industrial grade cheese powders.

Sample pH Moisture

(%) Fat (%)

Protein (%)

pH 4.6 Soluble

Nitrogen (%)

Ash (%)

Salt (%)

Lactose (%)

Cam_noES_RDA 5.90

± 0.00 2.65

± 0.35 40.00 ± 0.00

42.90 ± 0.28

13.45 ± 0.07

9.00 ± 0.00

4.45 ± 0.07

0.67 ± 0.01

Cam_ES_RDA 5.80

± 0.00 2.60

± 0.00 42.00 ± 0.00

40.85 ± 0.21

11.50 ± 0.00

9.80 ± 0.00

3.90 ± 0.00

0.33 ± 0.00

Ched_ES_BD 6.07

± 0.02 2.75

± 0.07 46.00 ± 0.00

36.99 ± 0.16

11.13 ± 0.15

10.10 ± 0.00

2.85 ± 0.21

0.22 ± 0.00

Ched_ES_RDA 5.87

± 0.01 2.00

± 0.00 45.00 ± 0.00

35.52 ± 0.19

9.03 ± 0.04

10.30 ± 0.00

3.50 ± 0.14

2.70 ± 0.14


Concerning the fat content, Cheddar cheese powders had significantly higher values (46% and 45%)

compared to Camembert powders (40% and 42%). The protein content in Camembert type powders was

higher (around 41-43%) compared to Cheddar type (around 35.5-37.0%). Soluble nitrogen found to be higher

in Camembert type and more precisely higher in a formulation without addition of ES. Ched_ES_BD sample

detected with higher soluble nitrogen content at pH 4.6 compared to Ched_ES_RDA. The highest content of

lactose was found for sample Ched_ES_RDA (2.70% ± 0.14). In the formulation of Ched_ES_RDA, sweet whey

powder (SWP) was added during manufacturing. Therefore, the high value of lactose (%) in the composition

of Ched_ES_RDA can be explained.

5.2. Particle size

The particle size distribution and the mean oil droplets particle size of the different cheese emulsions over

storage time are shown in Figure 8 & Figure 9 and Table 4 respectively.

The particle size was statistically significant different (p< 0.05) in O/W emulsions containing 1.5%, 3.0% and

4.5% protein content. However, no differences (p= 0.051) were observed in each sample over storage time.

Therefore, the results will be discussed based on the last day of the evaluation.



Sodium caseinate has been widely used as emulsifier in O/W emulsions (de Figueiredo Furtado et al., 2017),

therefore it has been used as control in this study. For the control sample (1.5% SC), the size distribution was

stable with mean particle size of 0.63 (± 0.00) μm. On the contrary, for Camembert cheese emulsions with

and without the addition of ES, different particle size distribution curves were obtained. At 1.5% of protein

content of sample Cam_noES_RDA, two peaks of different particle size were detected, with the highest

percentage of small particles in the first peak (0.76 ± 0.10). By increasing the protein content to 3.0% a

reduction in the size of the first peak (0.49 ± 0.00) was observed in Cam_noES_RDA. Further increase to 4.5%

of protein resulted to lower particle size (0.38 ± 0.00). On the other hand, in the presence of ES a unimodal

distribution was detected. A slight shift of the particle size distribution towards the smaller sizes and a

decrease in the mean size was found for Cam_ES_RDA by increasing the protein contents. Cam_ES_RDA

samples had similar size distribution to the control.

Same pattern was observed in Cheddar type emulsions. In Ched_ES_RDA a unimodal size distribution was

detected, where the mean size slightly changed with an increase in the protein content. More precisely, an

increase in the protein content from 1.5% to 4.5% reduces the mean size of the particles from 0.63 (± 0.00)

μm to 0.38 (± 0.00) μm respectively. For sample Ched_ES_BD, the formation of a bimodal size distribution

was observed, with the highest percentage of smaller size in the first peak. Though, the mean size of the first

peak decreases from 0.72 (± 0.00) μm to 0.33 (± 0.00) μm by increasing the protein content from 1.5% to

4.5% respectively.



Figure 8: Particle size distribution of the two different Camembert type cheese emulsions containing different protein content in period of twenty days. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary

atomization system; BD: spray drying tower with nozzles and fluid bed drying).



Figure 9: Particle size distribution of the two different Cheddar type cheese emulsions containing different protein content in period of twenty days. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary

atomization system; BD: spray drying tower with nozzles and fluid bed drying).

Different particle size distributions with more than one peak were observed. The first and most important

parameter for the formation of small droplets is the homogenisation step. The use of high pressure

homogeniser affects the droplet size. At high pressure the mean droplet diameter decreases (Hebishy et al.,

2017; McClements & Jafari, 2017). The addition of ES enabled the reduction of droplet size. Addition of ES

result in dispersion of the insoluble casein and hydration of it. The hydrated casein act as an emulsifier that

forms the membrane layer around the fat droplet during heating and shearing (El-Bakry et al., 2010). One of

the main factors responsible for the dispersion of caseins, is the isolation of calcium, by braking the calcium-

phosphate protein network and exposing charged residues (phosphoserine) leading to an increase of the

repulsions between the charges of the casein particles (Lucey et al., 2011). Therefore, the presence of ES in

the cheese powders has enable the protein to be more dispersed and thus to act as a natural emulsifier

compared to the cheese powder without ES addition. According to Kelimu et al. (2017), the presence of ES



resulted to lower particle size due to the alteration of insoluble intact casein and peptide aggregates into

hydrated emulsifier. This may explain the better performance of cheese powders containing ES in the O/W

emulsions compared to Cam_noES_RDA. Moreover, the increase in the protein content positively affected

the structure of the emulsions. Protein acts as emulsifier providing stabilisation of the oil droplets by

occurring electrostatic repulsions between the droplets (Lam & Nickerson, 2013). Cheddar type emulsions

correspond to the positive effect of protein concentration. Though, the appearance of a new peak with

increased protein content was seen in the size distribution for Cam_noES_RDA samples. It is challenging to

compare this behavior with other studies, because Camembert cheese type emulsions are more complex

systems compared to O/W emulsions with the addition of SC as a protein source. Based on Hebishy et al.

(2017), the emulsion formation and stability is determined by the droplet size and when the surfactant

concentration exceeds a limit, no further reduction occurs on the droplet size. Concerning the control sample

(1.5% SC), a low particle size distribution was observed. During emulsification, the surface active caseins are

absorbed in the oil-water interface and stabilize the droplets due to electrostatic stabilization mechanism

(Dickinson, 2006). Comparing the particle size distribution graphs of Cheddar type emulsions, the existence

of a second peak in Ched_ES_BD samples indicates that powders dried with a BD spray dryer and used as

emulsifiers in the production of O/W emulsions, are able to affect the formation of small particles during

homogenisation. A two-stage spray dryer is related with agglomerated powders (Felix da Silva et al., 2018).

Therefore, the above result in Ched_ES_BD samples, might be due to the presence of not completed

dispersed cheese powder.



Table 4: Mean values (±SE below) of the particles size (μm) obtained from the first and second peak of the size distribution graphs.

Sample Protein content

(%)

Day 0 Day 5 Day 10 Day 15 Day 20

Peak 1

Peak 2

Peak 1

Peak 2

Peak 1

Peak 2

Peak 1

Peak 2

Peak 1

Peak 2

Control 1.5 0.49

±0.00

0.49 ±0.00

0.63

±0.00

0.63 ±0.00

0.63

±0.00

Cam_noES_RDA

1.5 0.77

±0.05 4.12

±1.57 0.72

±0.00 6.08

±0.59 0.79

±0.06 5.44

±0.27 0.79

±0.05 4.89

±0.00 0.76

±0.10 5.01

±0.48

3.0 0.43

±0.00 9.25

±0.01 0.43

±0.00 7.16

±0.00 0.50

±0.03 8.88

±0.57 0.49

±0.00 8.14

±0.00 0.49

±0.00 8.14

±0.00

4.5 0.37

±0.02 5.22

±0.36 0.38

±0.00 5.55

±0.00 0.38

±0.00 5.55

±0.00 0.38

±0.00 5.55

±0.00 0.38

±0.00 6.31

±0.00

Cam_ES_RDA

1.5 0.52

±0.16

0.49 ±0.09

0.49

±0.00

0.51 ±0.13

0.47

±0.08

3.0 0.50

±0.05

0.57 ±0.13

0.72

±0.00

0.66 ±0.10

0.58

±0.09

4.5 0.38

±0.00

0.39 ±0.02

0.43

±0.00

0.42 ±0.02

0.41

±0.04

Ched_ES_BD

1.5 0.72

±0.00 3.56

±0.25 0.77

±0.05 2.76

±0.19 0.72

±0.00 3.51

±0.63 0.72

±0.00 0.00

±0.00 0.72

±0.00 4.30

±0.00

3.0 0.49

±0.00 3.30

±0.02 0.43

±0.00 2.93

±0.00 0.43

±0.00 2.58

±0.02 0.60

±0.24 1.75

±0.00 0.43

±0.00 2.27

±0.00

4.5 0.33

±0.00 4.27

±0.02 0.33

±0.00 2.58

±0.00 0.33

±0.00 2.58

±0.00 0.26

±0.00 1.99

±0.01 0.34

±0.00 2.61

±0.04

Ched_ES_RDA

1.5 0.63

±0.00

0.55 ±0.00

0.63

±0.00

0.63 ±0.00

0.63

±0.00

3.0 0.48

±0.00

0.43 ±0.00

0.43

±0.00

0.39 ±0.00

0.49

±0.00

4.5 0.44

±0.00

0.38 ±0.00

0.38

±0.00

0.38 ±0.00

0.38

±0.00


5.3. Rheological behavior

Consistency coefficient (k) and flow behavior index (n) values estimated from the Power Law model for all of

the cheese emulsions are shown in Table 5. The rheological parameters were affected by the cheese powder

formulation that was used for the emulsions and the protein content in which all emulsions were

standardized. Statistical significant (p= 0.00) differences on k and n values were observed between the

different protein contents. However, no differences were detected during the storage time.

Lower n values were observed for Cam_noES_RDA emulsions compared to Cam_ES_RDA for all

concentrations except 1.5%, indicating that the addition of ES increases the flow behavior index and

concomitant decreases the consistency coefficient. In Cheddar type emulsions, higher k and lower n values

were observed for Ched_ES_BD compared to Ched_ES_RDA. This result might be due to the formation of two

populations in the particle size distribution graphs. Moreover, significant differences (p< 0.05) were found



regarding the different protein content in both cheese type emulsions. By increasing the protein content the

k values increased and concomitantly the n values decreased.

The apparent viscosity of all samples as a function of shear rate was evaluated. Early data points were not

considered, using only the steady flow (the linear region of the curve). Most of the samples, showed

Newtonian behavior (n=1). However, sample Ched_ES_BD was detected with slightly shear-thinning behavior

(n<1). A low apparent viscosity was observed for the control sample. For Camembert type emulsions, samples

without ES showed an increase in apparent viscosity (Figure 10) by increasing the protein content to 3.0%

and 4.5%. This increase in protein content, shifted the rheogram of Cam_noES_RDA samples upwards with

maximum apparent viscosity of 0.0095 Pa s. For sample Cam_ES_RDA, there were no significant differences

between 1.5% and 3.0% of protein content and only at 4.5% there was a slightly increase of the viscosity at

around 0.0060 Pa s.

A similar profile was observed for Cheddar type emulsions. Increase in protein content resulted to higher

apparent viscosity. The rheogram for Ched_ES_BD shifted upwards at 4.5% protein content having a more

shear-thinning behavior compared to other samples. On the contrary Ched_ES_RDA samples behaved similar

to the control.

Particle interactions and structural changes are responsible for different rheological profiles (Kelimu et al.,

2017). Small or not enough interactions between particles may be responsible for a Newtonian flow behavior

with low viscosity (Hebishy et al., 2017). The low particle size of the droplets may explain the high flow

behavior and therefore low viscosity for all cheese emulsions. Similar to other studies, increase in the protein

content results to higher consistency coefficient (k). However, the extent of this change in the consistency

doesn’t necessarily result in a significant change also in the viscosity (Hebishy et al., 2017). Higher protein

content results in more interactions between the components within the O/W matrix. Therefore, the small

changes in the flow behavior from Newtonian to shear thinning when the protein content increases from

3.0% to 4.5%, may be due to increase amount of protein in the continuous phase. Strong interactions like

depletion flocculation between the droplets and the formation of casein aggregates tend to increase the

viscosity of emulsions (McClements & Jafari, 2017).



Figure 10: Apparent viscosity of Camembert and Cheddar type cheese emulsions as a function of shear rate. (Cam:

Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary atomization system; BD: spray drying tower with nozzles and fluid bed drying).



Table 5: Power Law model parameters (mean values ±SE below).

Sample Protein content

(%)

Consistency coefficient (K) (Pa.sn) Flow behavior index (n)

Day 0 Day 5 Day 10 Day 15 Day 20 Day 0 Day 5 Day 10 Day 15 Day 20

Control 1.5 0.0031 ±0.000

0.0034 ±0.000

0.0029 ±0.000

0.0020 ±0.000

0.0029 ±0.000

1.0312 ±0.003

1.0162 ±0.023

1.0412 ±0.003

1.0391 ±0.004

1.0407 ±0.002

Cam_noES_RDA

1.5 0.0031 ±0.000

0.0041 ±0.001

0.0031 ±0.000

0.0030 ±0.000

0.0032 ±0.000

1.0395 ±0.003

1.0282 ±0.014

1.0428 ±0.005

1.0407 ±0.003

1.0382 ±0.003

3.0 0.0116 ±0.000

0.0099 ±0.000

0.0090 ±0.000

0.0083 ±0.000

0.0085 ±0.000

0.9456 ±0.002

0.9587 ±0.003

0.9684 ±0.000

0.9785 ±0.003

0.9772 ±0.002

4.5 0.0119 ±0.000

0.0109 ±0.000

0.0107 ±0.000

0.0098 ±0.000

0.0101 ±0.000

0.9563 ±0.003

0.9671 ±0.004

0.9647 ±0.003

0.9758 ±0.003

0.9763 ±0.005

Cam_ES_RDA

1.5 0.0033 ±0.000

0.0041 ±0.000

0.0035 ±0.000

0.0039 ±0.000

0.0038 ±0.000

1.0290 ± 0.007

1.0215 ±0.005

1.0334 ±0.009

1.0277 ±0.003

1.0330 ±0.004

3.0 0.0043 ±0.000

0.0029 ±0.000

0.0031 ±0.000

0.0032 ±0.000

0.0032 ±0.010

1.0201 ± 0.003

1.0458 ±0.004

1.0397 ±0.000

1.0395 ±0.005

1.0408 ±0.013

4.5 0.0061 ±0.000

0.0052 ±0.000

0.0051 ±0.000

0.0052 ±0.000

0.0052 ±0.000

1.0029 ± 0.003

1.0180 ±0.006

1.0159 ±0.003

1.0150 ±0.003

1.0154 ±0.004

Ched_ES_BD

1.5 0.0046 ±0.000

0.0048 ±0.000

0.0055 ±0.000

0.0051 ±0.000

0.0048 ±0.000

1.0122 ±0.005

1.0095 ±0.001

0.9984 ±0.003

1.0067 ±0.003

1.0154 ±0.009

3.0 0.0098 ±0.000

0.0146 ±0.000

0.0171 ±0.001

0.0153 ±0.000

0.0137 ±0.000

0.9520 ±0.004

0.9176 ±0.004

0.8977 ±0.006

0.9138 ±0.003

0.9277 ±0.004

4.5 0.0655 ±0.002

0.0958 ±0.007

0.1133 ±0.006

0.0758 ±0.004

0.0557 ±0.001

0.7703 ±0.006

0.7395 ±0.008

0.7136 ±0.009

0.7414 ±0.006

0.8024 ±0.001

Ched_ES_RDA

1.5 0.0030 ±0.000

0.0028 ±0.000

0.0029 ±0.000

0.0029 ±0.000

0.0028 ±0.000

1.0436 ±0.003

1.0482 ±0.005

1.0426 ±0.003

1.0412 ±0.003

1.0489 ±0.002

3.0 0.0041 ±0.000

0.0042 ±0.000

0.0042 ±0.000

0.0045 ±0.000

0.0043 ±0.000

1.0240 ±0.002

1.0250 ±0.001

1.0235 ±0.006

1.0151 ±0.003

1.0270 ±0.001

4.5 0.0079 ±0.003

0.0065 ±0.000

0.0064 ±0.000

0.0067 ±0.000

0.0074 ±0.000

0.9752 ±0.049

0.9937 ±0.001

0.9984 ±0.003

0.9955 ±0.003

0.9893 ±0.003




5.4. Physical stability

Figure 11 shows the backscattering profiles for all emulsions prepared by Camembert and Cheddar cheese

powders respectively.

Visual examination of graphics shows longer stability of cheese emulsions at 3.0% and 4.5% of protein

content. A decrease in the backscattering profiles in relation with storage time (days) can be observed in

both Cam_noES_RDA and Cam_ES_RDA at 1.5% of protein, due to clarification of the mixture at the bottom

of the tube. The stability of these samples changed in a period of twenty days from 90% to around 30% and

40% backscattering respectively for Cam_noES_RDA and Cam_ES_RDA. At 3.0% protein content a smaller

degree of reduced backscattering was observed at both samples of about 65% and 70% respectively.

However, no decrease in backscattering was detected at higher protein content (4.5%) and the obtained

profiles found to be even more stable than the control. This indicates that the addition of ES provides higher

stability and in a combination of high protein concentration the stability was improved.

Similar backscattering profiles were observed for Cheddar type emulsions. The increase in the protein

content improved the stability of the emulsions. At 1.5% protein Ched_ES_BD and Ched_ES_RDA had a

decrease in the backscattering of 39% and 43%, respectively. The increase in the protein content, significantly

improved the stability of both Cheddar type emulsions. However, due to different composition on soluble

nitrogen at pH 4.6, Cheddar emulsions were more stable than Camembert type.

Increase in the protein content resulted in better stability; shown by backscattering profiles. When proteins

are adsorbed on the interface they create viscoelastic layers that stabilize the emulsions. Therefore, with an

increased amount of proteins, the interfacial layers become thicker. That leads to stronger repulsive

interactions and consequently better steric stabilization (Ozturk & McClements, 2016). However, at low

protein concentration (1.5%) the decrease in the backscattering indicates clarification at the bottom of the

tube. Due to this kind of clarification, the shelf life of the emulsions was limited.



Figure 11: Backscattering (%) profiles of O/W cheese emulsions during twenty days. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower with rotary atomization system; BD: spray drying tower with nozzles and fluid bed drying).



5.5. Characterization of cheese emulsions

5.5.1. pH

The pH of all samples is shown in Table 6. A significant (p= 0.03) reduction of pH values was observed for all

samples between the preparation day (day 0) and the last day of storage (day 20). For sample

Cam_noES_RDA the pH values were higher compared to Cam_ES_RDA, indicating that the addition of ES

influenced the acidity of the emulsions. Statistical significant differences (p< 0.05) on the pH were also found

between the different protein contents. Increase in the protein content resulted to decrease in the pH of all

emulsions. Similar profiles were found for Cheddar type emulsions.

These results come in agreement with the pH measurements from the cheese powders. Therefore, a similar

tendency was expected. Protein-stabilized emulsions are sensitive to pH. The existence of proteins in the

emulsions is responsible for the changes in the pH. The buffering capacity of proteins affects the pH values.

An increase in the protein content results in a decrease in the pH values. The protein-protein interactions are

increased and therefore, their buffering capacity was increased too. Caseins have a strong buffering capacity

in the region of pH 5.8 – 6.0 (Fox et al., 2017).

Table 6: pH of all cheese emulsions at the first and last day of storage (mean values ±SE).

Sample Protein content (%) pH

Day 0 Day 20

Control 1.5 7.09 ± 0.11 6.77 ± 0.01

Cam_noES_RDA 1.5 6.70 ± 0.13 6.44 ± 0.04 3.0 6.45 ± 0.14 6.27 ± 0.07 4.5 6.49 ± 0.19 6.25 ± 0.17

Cam_ES_RDA 1.5 6.11 ± 0.04 6.08 ± 0.12 3.0 6.10 ± 0.18 6.09 ± 0.05 4.5 5.89 ± 0.07 5.92 ± 0.02

Ched_ES_BD 1.5 6.47 ± 0.03 6.39 ± 0.06 3.0 6.33 ± 0.02 6.26 ± 0.01 4.5 6.24 ± 0.02 6.19 ± 0.01

Ched_ES_RDA 1.5 6.33 ± 0.04 6.25 ± 0.02 3.0 6.22 ± 0.03 6.12 ± 0.02 4.5 6.12 ± 0.02 6.05 ± 0.03


5.5.2. Microstructure: Light Microscopy (LM)

No clear differences in the microstructure of emulsions was observed within twenty days of storage.

Therefore, the microstructure of emulsions measured at the last day of evaluation (day 20) in different

protein content is shown in Figure 12. In Cam_noES_RDA samples, small and big droplets were observed,

confirming the existence of the bimodal size distribution that was detected in particle size analyses. Similar,

but smaller in size droplets were observed for sample Ched_ES_BD, which also had two populations of small

and large particles. For the other two samples (Cam_ES_RDA and Ched_ES_RDA), the existence of small

droplets was found confirming the unimodal size distributions that were detected in previous analysis.

Concerning the protein content, larger droplets were observed at 1.5% of protein. A slight decrease in the

droplets size of the emulsions was observed at 3.0% and 4.5% of protein content. However, no aggregation



between the droplets was observed. The small droplet size is correlated to the low viscosity of the emulsions

and the low particle size.

One of the factors that determines the droplet size is the homogenization. Studies with similar results on the

particle size but with the use of ultrasound, showed that a reduction in the particle size and increase in the

interfacial area can also leads to a modification of the protein structure at the interface (Huck-Iriart et al.,

2011). The increase of the protein content resulted in a greater coverage of the oil droplet surface by proteins

(McClements, 2004).

Figure 12: Light micrographs of O/W (20:80) cheese emulsions in different protein contents a) 1.5%, b) 3.0% and c) 4.5%. The scale bar shows a length of 10 μm. (Cam: Camembert; Ched: Cheddar; ES: emulsifying salts; RDA: spray drying tower

with rotary atomization system; BD: spray drying tower with nozzles and fluid bed drying).

Conclusions


6. Conclusions

The objective of this project was to investigate the influence of different cheese powders, added as natural

emulsifiers, in O/W emulsions based on the cheese type and in the presence of ES in the powder formulation.

Moreover, part of the objectives was to evaluate the influence of different protein concentrations (i.e. cheese

powder concentration) on the physical stability and microstructure of the O/W emulsions during storage at

20 o C.

In general, both cheese powders had similar effect on the particle size and the flow behavior of the formed

O/W emulsions. However, Cheddar type cheese powders, at higher protein concentration, produced O/W

emulsions with better stability compared to Camembert cheese powders.

The addition of ES facilitated the reduction of the particle size in the emulsions and consequently the

formation of unimodal size distributions. The presence of ES in the cheese powder improved the flow

behavior and the physical stability of the cheese emulsions.

An increase in the protein concentration reduced the particle size of the O/W emulsions containing cheese

powder with ES. On the contrary, in the absence of ES, the appearance of two peaks at the increased protein

content indicates the existence of two populations of smaller and larger droplets, with the larger droplet

being in abundance. Concerning the rheological properties, the viscosity and flow behavior index are slightly

increased with increase in the protein content. However, for all samples, the physical stability was

significantly improved with 3.0% and 4.5% of protein.

Concerning the storage time, up to twenty days storage at 20o C, no significant differences were detected on

the particle size and the rheological properties of the O/W emulsions. Though, at 1.5% of protein, the stability

of all cheese emulsions was decreased over twenty days of storage, indicating a limited shelf life at this

protein content.

The light micrographs confirmed the small droplet size in the emulsions and also the existence of a unimodal

and bimodal size distribution. Finally, the pH values of all samples were decreased slightly during twenty days

of storage.

The above results highlight that cheese powders can be used as emulsifiers in order to stabilize emulsion

systems. However, the choice of the most effective concentration is a crucial parameter. An excess or limited

amount of the emulsifier absorbed on the oil droplets, might destabilize the system.

Perspectives


7. Perspectives

This study proved that cheese powder can be used as an alternative to natural emulsifiers. Further

investigations should be carried out in order to evaluate the effect of pressure during homogenisation on the

improvement of the particle size and the stability of the emulsion.

Moreover, the extent of the storage time, the use of different protein concentrations above or below 4.5%

and the application of other different cheese powders, could be an indicator for determining the stability of

the obtained emulsions.

Finally, it would be interesting to evaluate the application of the formed emulsions in food systems, such as

sauces, dips or dressings. Thus, the physical stability and the microbial safety of the emulsions would be

crucial parameters for determining the shelf life of the final products.

.

References


References

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(Volume 1). p.pp. 136–138.

Burgos-Díaz, C., Wandersleben, T., Marqués, A.M. & Rubilar, M. (2016). Multilayer emulsions

stabilized by vegetable proteins and polysaccharides. Current Opinion in Colloid and Interface

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Appendix


Appendix: Statistical analyses

Composition of powders

One-way ANOVA: pH versus powder type Method

Null hypothesis All means are equal

Alternative hypothesis Not all means are equal

Significance level α = 0.05

Equal variances were assumed for the analysis.

Analysis of Variance

Source DF Adj SS Adj MS F-Value P-Value

powder type 3 0.076450 0.025483 203.87 0.000

Error 4 0.000500 0.000125

Total 7 0.076950

Tukey Pairwise Comparisons - Grouping Information Using the Tukey Method and 95% Confidence

powder type N Mean Grouping

Ched_ES_BD 2 6.0650 A

Cam_noES_RDA 2 5.900 B

Ched_ES_RDA 2 5.86500 B

Cam_ES_RDA 2 5.800 C

Means that do not share a letter are significantly different.

Appendix


One-way ANOVA: moisture (%) versus powder type Method







powder type 3 0.6900 0.23000 7.08 0.045

Error 4 0.1300 0.03250

Total 7 0.8200




Cam_noES_RDA 2 2.650 A B

Cam_ES_RDA 2 2.600 A B



Appendix


One-way ANOVA: protein versus powder type Method







powder type 3 69.6447 23.2149 494.20 0.000

Error 4 0.1879 0.0470

Total 7 69.8326



Cam_noES_RDA 2 42.900 A

Cam_ES_RDA 2 40.850 B

Ched_ES_BD 2 36.985 C

Ched_ES_RDA 2 35.515 D


Appendix


One-way ANOVA: SN versus powder type Method







powder type 3 19.7859 6.59531 2345.00 0.000

Error 4 0.0112 0.00281

Total 7 19.7972






Ched_ES_RDA 2 9.0250 D


Appendix


One-way ANOVA: salt versus powder type Method







powder type 3 2.72500 0.90833 51.90 0.001

Error 4 0.07000 0.01750

Total 7 2.79500








Appendix


One-way ANOVA: lactose versus powder type Method







powder type 3 8.10920 2.70307 535.26 0.000

Error 4 0.02020 0.00505

Total 7 8.12940



Ched_ES_RDA 2 2.700 A

Cam_noES_RDA 2 0.6700 B




Appendix


One-way ANOVA: fat versus powder type Method







powder type 3 45.4415 15.1472 1176479.75 0.000

Error 4 0.0001 0.0000

Total 7 45.4416






Cam_noES_RDA 2 40.0050 D


Appendix


One-way ANOVA: ash versus powder type Method







powder type 3 1.95856 0.652853 5119917.20 0.000

Error 4 0.00000 0.000000

Total 7 1.95856



Ched_ES_RDA 2 10.3001 A

Ched_ES_BD 2 10.1001 B


Cam_noES_RDA 2 9.00050 D


Appendix


Mean particle size (1st and 2nd peak)

General Linear Model: 1st pick (μm) versus Protein Concentration (%), Day Factor Information

Factor Type Levels Values

Protein Concentration (%) Fixed 3 1.5, 3.0, 4.5

Day Fixed 5 0, 5, 10, 15, 20



Protein Concentration (%) 2 4.62170 2.31085 251.56 0.000

Day 4 0.08763 0.02191 2.38 0.051

Error 383 3.51824 0.00919

Lack-of-Fit 8 0.05742 0.00718 0.78 0.623

Pure Error 375 3.46083 0.00923

Total 389 8.22758

Comparisons for 1st pick (μm) - Grouping Information Using the Tukey Method and 95% Confidence, Tukey Pairwise Comparisons: Protein Concentration (%)

Protein Concentration (%) N Mean Grouping

1.5 150 0.636335 A

3.0 120 0.498705 B

4.5 120 0.374091 C


Tukey Pairwise Comparisons: Day

Day N Mean Grouping

10 78 0.519035 A

15 78 0.517532 A

20 78 0.505111 A

0 78 0.494645 A

5 78 0.478898 A Means that do not share a letter are significantly different.

Appendix


General Linear Model: 2nd pick (μm) versus Protein Concentration (%), Day Factor Information



Day Fixed 5 0, 5, 10, 15, 20




Day 4 15.71 3.928 0.53 0.710

Error 383 2812.19 7.343

Lack-of-Fit 8 10.92 1.365 0.18 0.993

Pure Error 375 2801.27 7.470

Total 389 2913.72

R Large residual

Comparisons for 2nd pick (μm) - Grouping Information Using the Tukey Method and 95% Confidence, Tukey Pairwise Comparisons: Protein Concentration (%)


3.0 120 2.72033 A

4.5 120 2.11003 A B

1.5 150 1.58599 B Means that do not share a letter are significantly different.


Day N Mean Grouping

0 78 2.32781 A

20 78 2.24511 A

10 78 2.23755 A

5 78 2.12476 A

15 78 1.75871 A Means that do not share a letter are significantly different.

Appendix


Main Effects Plot for 1st and 2nd pick (μm)

Power Law properties (k and n)

General Linear Model: k versus Powder Type, Protein Concentration (%), Day Factor Information


Powder Type Fixed 5 Cam/ES/BD, Cam/no ES/RDA, Ched/ES/BD, Ched/ES/RDA, Control


Day Fixed 5 0, 5, 10, 15, 20



Powder Type 4 0.028962 0.007241 28.84 0.000


Day 4 0.000567 0.000142 0.56 0.689

Error 184 0.046192 0.000251

Lack-of-Fit 54 0.045953 0.000851 463.34 0.000

Pure Error 130 0.000239 0.000002

Total 194 0.095589

Appendix


Comparisons for k - Grouping Information Using the Tukey Method and 95% Confidence Tukey Pairwise Comparisons: Powder Type

Powder Type N Mean Grouping

Ched/ES/BD 45 0.0346711 A

Control 15 0.0121376 B

Cam/no ES/RDA 45 0.0078182 B

Ched/ES/RDA 45 0.0047156 B

Cam/ES/BD 45 0.0041422 B


Tukey Pairwise Comparisons: Protein Concentration (%)


4.5 60 0.0268567 A

3.0 60 0.0076502 B

1.5 75 0.0035840 B



Day N Mean Grouping

10 39 0.0149939 A

5 39 0.0136275 A

15 39 0.0133414 A

0 39 0.0112524 A

20 39 0.0102696 A


Main Effects Plot for k

Appendix


General Linear Model: n versus Powder Type, Protein Concentration (%), Day Factor Information


Powder Type Fixed 5 Cam/ES/BD, Cam/no ES/RDA, Ched/ES/BD, Ched/ES/RDA, Control


Day Fixed 5 0, 5, 10, 15, 20



Powder Type 4 0.49962 0.124904 71.82 0.000


Day 4 0.00353 0.000883 0.51 0.730

Error 184 0.31998 0.001739

Lack-of-Fit 54 0.31159 0.005770 89.39 0.000

Pure Error 130 0.00839 0.000065

Total 194 1.15271

Comparisons for n - Grouping Information Using the Tukey Method and 95% Confidence Tukey Pairwise Comparisons: Powder Type

Powder Type N Mean Grouping

Cam/ES/BD 45 1.02652 A

Ched/ES/RDA 45 1.01941 A B

Cam/no ES/RDA 45 0.99053 C

Control 15 0.98640 B C

Ched/ES/BD 45 0.89455 D


Tukey Pairwise Comparisons: Protein Concentration (%)


1.5 75 1.03077 A

Appendix


3.0 60 0.98761 B

4.5 60 0.93206 C



Day N Mean Grouping

20 39 0.991592 A

15 39 0.983731 A

0 39 0.981574 A

5 39 0.980583 A

10 39 0.979925 A


Main Effects Plot for n

pH of emulsions General Linear Model: pH versus Protein content (%), Day Factor Information


Protein content (%) Fixed 3 1.5, 3.0, 4.5

Day Fixed 2 0, 20



Protein content (%) 2 2.9980 1.49898 28.49 0.000

Day 1 0.4783 0.47830 9.09 0.003

Error 152 7.9969 0.05261

Lack-of-Fit 2 0.0420 0.02099 0.40 0.674

Pure Error 150 7.9549 0.05303

Total 155 11.4732

Appendix


Comparisons for pH - Grouping Information Using the Tukey Method and 95% Confidence Tukey Pairwise Comparisons: Protein content (%)

Protein content (%) N Mean Grouping

1.5 60 6.46238 A

3.0 48 6.22750 B

4.5 48 6.14365 B



Day N Mean Grouping

0 78 6.33321 A

20 78 6.22247 B


Main Effects Plot for pH

Appendix


One-way ANOVA: pH versus Powder Type Method





Factor Information

Factor Levels Values

Powder Type 6 Cam/ES/BD, Cam/ES/RDA, Cam/noES/RDA, Ched/ES/BD, Ched/ES/RDA, control



Powder Type 5 8.498 1.69961 85.69 0.000

Error 150 2.975 0.01983

Total 155 11.473

Main Effects Plot for pH Vs Cheese powders

Documents

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