study of the cooking effect induced by...

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STUDY OF THE COOKING EFFECT INDUCED BY STERILIZATION HEAT

TREATMENT PROCESSES FOR CHILLED DAIRY DESSERTS

Master Thesis

by

P. C. Latorre Viteri

Thesis submitted in accordance with the requirements for the MSc Food Technology,

Specialization European Master in Food Studies, in July 2015

Proof-Reader:

Isabelle Barbotteau Nestlé PTC Lisieux, France

Prof. Dr.ir Matthijs Dekker Wageningen University, Netherlands

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ABSTRACT It was studied the cooking effect induced by sterilization heat treatment processes for Chilled Dairy

Desserts.

Samples were prepared at kitchen scale and bench scale. Kitchen samples were used to set the

procedures for the physical and chemical analysis of the samples. During the upscaling of the process in

bench scale a temperature loss was noticed after the holding tube of the sterilization stage. Therefore, a

temperature loss study in the holding tube was conducted and the recipe was adjusted. Temperature

loss was evaluated comparing water against cream dessert recipe. Temperature loss curves were

obtained for cream dessert recipe at different sterilization temperatures for the updated recipe. A small

experimental design was elaborated. The analyzed factors were sterilization temperature and holding

time. Besides, it was also considered with or without cooking step. In order to guarantee different final

products with the experimental design proposed, the onset temperature of the equipment was

calculated to guarantee a quadratic design, at least 5°C difference was obtained for the final trials. Active

Factory curves were elaborated and thermal time and cooking value were calculated.

Samples were analyzed at D+7, D+14, D+21 and D+28. It was analyzed color: value L* and a*, apparent

viscosity and oscillatory measurements: G’and G” at the crossover point, complex viscosity and shear

stress at the crossover point. L* value and shear stress were chosen for further detailed analysis. It was

chosen the results at D+21. Technical sessions were conducted in an attempt to correlate analytical and

sensory measurements. The attributes evaluated were: color, firm at spoon, thick in mouth, caramel

flavor and granular aspect.

Due to the limited number of trials, it was difficult to propose conclusive arguments. However it was

seen that temperature was the more critical variable in color. Color presented a good correlation with

the sensory results. It was hypothesized that higher temperatures and shear inside the line can cause

disruption of native swollen granules leading to a decrease in viscosity. Moreover, not only starch but

also milk protein interactions might play an important role in the texture of cream desserts. The cooking

value can be used for modelling color, apparent viscosity and shear stress but further trials are needed.

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TABLE OF CONTENTS

ABSTRACT ...................................................................................................................................................... 2

TABLE OF CONTENTS ..................................................................................................................................... 4

LIST OF ABBREVIATIONS ................................................................................................................................ 6

1. INTRODUCTION ......................................................................................................................................... 6

1.1 BACKGROUND ..................................................................................................................................... 6

1.2 OBJECTIVE OF THE STUDY ................................................................................................................... 7

2. LITERATURE REVIEW.................................................................................................................................. 7

2.1 INTERACTION BETWEEN INGREDIENTS ............................................................................................... 8

β -Lactoglobulin and κ –carrageenan .................................................................................................... 8

Casein micelles and carrageenans ......................................................................................................... 8

Sugars-starch interaction ...................................................................................................................... 8

Carrageenan-starch interaction ............................................................................................................ 9

Whey protein – starch ........................................................................................................................... 9

Casein-starch ......................................................................................................................................... 9

Whey protein with casein...................................................................................................................... 9

Milk proteins and xanthan gum ............................................................................................................ 9

2.2 EFFECT OF HEAT TREATMENT IN THE INGREDIENTS ......................................................................... 10

Milk ...................................................................................................................................................... 10

Starch ................................................................................................................................................... 10

2.3 CORRELATION BETWEEN ANALYTICS AND SENSORY EVALUATION .................................................. 10

2.4 COOKING VALUE AND THERMAL TIME ............................................................................................. 11

Cooking value ...................................................................................................................................... 11

Cooking Value Calculation ................................................................................................................... 12

Thermal Time ....................................................................................................................................... 13

1.2 STUDY METHODOLOGY ..................................................................................................................... 13

3. MATERIALS AND METHODS..................................................................................................................... 15

3.1 RECIPE AND PROCESS AT KITCHEN SCALE ................................................................................... 15

3.2 RECIPE AND PROCESS AT PILOT PLANT SCALE ............................................................................ 17

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3.3 ANALYTICAL METHODS ............................................................................................................... 21

3.3.1 COLOR ......................................................................................................................................... 21

3.3.2 VISCOSITY ................................................................................................................................... 22

3.3.3 RHEOLOGICAL MEASUREMENTS ................................................................................................ 23

3.3.4 MICROSCOPY OBSERVATION ...................................................................................................... 25

3.4 VISUAL AND SENSORY EVALUATION ........................................................................................... 26

3.4.1 TECHNICAL TASTING ................................................................................................................... 26

3.4.2 VISUAL ASSESSMENT .................................................................................................................. 27

3.5 THERMAL TIME CALCULATION .................................................................................................... 27

3.5.1 DEFINITION ................................................................................................................................. 27

3.5.2 PRINCIPLES FOR CALCULATION .................................................................................................. 28

4. TRIALS AND BUILDING OF DESIGN OF EXPERIMENT (DoE) ..................................................................... 35

4.1 KITCHEN TRIALS ........................................................................................................................... 35

4.2 EXPLORATORY TRIALS.................................................................................................................. 35

4.2.1 Conclusions Exploratory trials: ................................................................................................... 36

4.3 DETERMINATION OF TEMPERATURE LOSS IN THE HOLDING TUBE ............................................ 36

4.3.1 Conclusions of temperature loss evaluation trials: .................................................................... 44

4.4 BUILDING THE EXPERIMENTAL DESIGN (DoE) ............................................................................. 44

4.4.1 Determination of the different factors....................................................................................... 44

4.4.2 Determination of the level of the factors ................................................................................... 45

4.4.3 Initial Design of Experiment ....................................................................................................... 45

4.5 MODIFIED DoE ............................................................................................................................. 46

4.5.1 New Constraints ......................................................................................................................... 46

4.5.2 Determination of the levels of the different factors .................................................................. 48

5. STATISTICAL ANALYSIS ............................................................................................................................. 50

6. RESULTS ................................................................................................................................................... 50

6.1 STATISTCAL RESULTS ......................................................................................................................... 50

6.2 TECHNICAL TASTING AND VISUAL ASSESSMENT ............................................................................... 52

6.3 COLOR ................................................................................................................................................ 58

6.3.1 Value L* ...................................................................................................................................... 58

6.3.2 Value a* ...................................................................................................................................... 61

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6.4 APPARENT VISCOSITY ........................................................................................................................ 61

6.5 RHEOLOGICAL MEASUREMENTS: Oscillatory Measurements........................................................... 65

6.5.1 Shear stress ................................................................................................................................ 65

6.6 MICROSCOPY OBSERVATION ............................................................................................................. 69

7. DISCUSSION ............................................................................................................................................. 71

8. GENERAL DISCUSSION AND CONCLUSION .............................................................................................. 74

8.1 RECOMMENDATIONS ON NEXT STEPS .............................................................................................. 74

9. ACKNOWLEDGEMENT ............................................................................................................................. 74

10. LITERATURE ........................................................................................................................................... 75

ANNEXES ...................................................................................................................................................... 78

LIST OF ABBREVIATIONS AF Active Factory

BSD Line Bench Scale Dessert Line

Cp Centipoise (1 Cp = 1mPas = 10-2 1/s)

DoE Design of Experiments

SMP Skim Milk Powder

PTC Product Technology Center

1. INTRODUCTION

1.1 BACKGROUND Nestlé PTC Lisieux is a Product Technology Center whose competence is the Chilled Dairy Category

which includes fermented products, desserts, dairy products and drinks. A PTC is in charge of

developing products, supporting the industrialization of new processes, developing knowledge and

expertise on dairy ingredients and processing and also contributing with technical support in

manufacturing and engineering for factories.

At PTC Lisieux the recommendations on heat treatment conditions, time/temperature, required for

manufacturing Chilled Dairy Desserts take into account only the food safety aspect (sterilization

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value). The additional part of heat treatment required to obtain the "cooking" effect (cooking value)

that develops the quality attributes of the final product is established during development trials at

pilot plant and validated with sensory panels. Heating and cooling kinetics are specific to the pilot

plant equipment and not always similar to the ones encountered in industrial sterilization plants,

additional trials are required to adjust process parameters and recipes during the industrialization

phase at the factory. As a consequence, heat treatment parameters applied in factories are much

higher than the ones required only for food safety. Therefore, the food safety limit can be optimized

and reduced; and heat treatment conditions could be decreased improving fouling in equipment and

steam consumption.

1.2 OBJECTIVE OF THE STUDY The objective of the study is to:

Understand the impact of heat treatment parameters (time, temperature) on the sensory

quality of the product (color, texture).

Study if a cooking value could allow to calculate or predict this impact.

To be able to predict in a certain extent the effect of heat treatment on the sensory quality of

the deserts.

2. LITERATURE REVIEW Cream desserts are part of the category of Chilled Dairy Desserts produced by Nestle. PTC Lisieux is in

charge of research and improvement of this line of products which are consumed all over the world.

According to literature cream desserts are defined as sheared gels showing a liquid or semi-liquid

rheological behavior which are basically formulated with milk, thickeners (starch and hydrocolloids),

sucrose, aroma and colorants. Usually carrageenans in combination with starches, such as native maize

starch are used in these desserts (Tye, 1988). They are obtained through thermo-mechanical treatment

of a starch suspension in a milk/carrageenan/sucrose mixture and subsequent cooling process under

shear (Matignon, Michon, Reichl, Barey, Mauduit & Sieffermann, 2016; Tárrega & Costell, 2006).

The rheological and sensory properties of these products are strongly influenced by fat content of milk,

type and concentration of starch, and/or type and concentration of hydrocolloids, and their crossed

interactions (De Wijk, Van Gemert, Terpstra & Wilkinson, 2003; Matignon et al., 2016). However starch

and carrageenan can be considered as the most important ones according to Doublier and Durand

(2008).

In literature it was found different descriptions of the system. For instance, Doublier and Durand (2008)

defined it as a suspension of deformable particles (the swollen starch granules) dispersed in a continuous

medium containing milk proteins as well as hydrocolloids. A variation of this description is given by De

Wijk et al. (2003) who described custard desserts as a continuous aqueous phase containing starch and

carrageenan and a dispersed phase of oil droplets that are stabilized by proteins. On the other hand,

Verbeken, Bael, Thas and Dewettinck (2006) suggested that in sterilized dairy desserts κ-carrageenan

interacts with milk proteins leading to the formation of a carrageenan gel network where starch granules

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act as non-interacting fillers and cause a concentration of the other ingredients in the continuous phase

as a result of the exclusion effect. Swollen particles are mainly composed of amylopectin, whereas the

continuous phase contains mostly amylose (Alloncle, Lefebvre, Llamas & Doublier, 1999).

2.1 INTERACTION BETWEEN INGREDIENTS

β -Lactoglobulin and κ –carrageenan

These polymers form a phase-separated gel. Phase-separated networks take place when the polymer species are incompatible among each other forming phase-separated regions within the gel network. (Goh et al., 2008). In addition, Capron, Nicolai, and Durand (1999) studied the effect of κ-carrageenan in heat induced gelation of β –lactoglobulin in presence of salts; they concluded that the gel rheology of the system indicated the melting of κ -carrageenan and the gelation of β –lactoglobulin above 65°C. Moreover, the interactions were temperature, pH and concentration dependent.

Casein micelles and carrageenans

At temperatures below the coil-helix transition temperature casein micelles and carrageenan associate

through electrostatic interactions. The negatively charged sulphated groups of the polysaccharide

interact with a positively charged region of κ-casein. The coil–helix transition is accompanied by an

increase in charge density; therefore attractive interaction between carrageenan and casein micelles

depends on the carrageenan’s charge density (Langendorff, Cuvelier, Michon, Launay, Parker & De kruif,

2000). At temperatures above the coil–helix transition temperature, carrageenan did not adsorb to the

casein micelles, resulting in depletion flocculation (Goh et al., 2008).

Langendorff, Cuvelier, Michon, Launay, Parker and De kruif (2000) concluded that lambda-carrageenan in

coil form adsorbs onto the casein micelles at all temperatures, whilst iota and kappa-carrageenan only

adsorb at temperatures where they are, at least partially, in helical form. These interactions are

thermally irreversible for iota-carrageenan up to 60°C. This is in accordance with Spagnuolo, Dalgleish,

Goff, and Morris (2005) who suggested that both κ-carrageenan – casein micelle interaction and κ-

carrageenan helix aggregation are required to prevent macroscopic phase separation and provide visual

stability in casein and locust bean gum mixtures. These interactions decrease the carrageenan

concentration necessary for gelation and increase the complex and elastic modulus; and the gel strength

of the obtained carrageenan gel (Depypere, Verbeken, Torres & Dewettinck, 2009; Verbeken et al.,

2006).

Sugars-starch interaction

Hydrophilic solutes like sucrose, glucose and glucose syrups compete for water, and can delay and inhibit starch swelling if present in adequate amounts. By reducing the degree of swelling, sugars make swollen granules less sensitive to mechanical disruption; thus minimizing the tendency of the granules to rupture or

overcook. Furthermore, sugars due to their hydroxyl groups stabilize starch pastes (Mason, 2009). It is well known in literature that the principal effect of sugars on starch is to raise its gelatinization temperature (Beleia, Miller and Hoseney, 1996). For instance, Buck and Walker (1988) found that maize starch increased its gelatinization temperature from 71.6°C to 76.8°C with sucrose addition and to 75.4°C

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with glucose. However, Sudhakar, Singhal and Kulkarni (1995) encountered that this delay in gelatinisation temperature is diminished in the presence of gums, and hence the gums bring the gelatinisation temperature of starch-sugar combinations to almost that of starch alone.

Carrageenan-starch interaction

Carrageenan chains either in coil or helix conformation interact with the endogenous proteins covering

the surface of starch granules. These interactions are possible only in the absence of casein micelles.

These interactions are reversible and led to less starch granule disruption in the final microstructure due

to a protective role of carrageenan for starch granules (Matignon, Moulin, Barey, Desprairies, Mauduit,

Sieffermann and Michon, 2014; Tye, 1988).

In a mixture with skim milk, carrageenan and starch, carrageenan-casein micelles interactions would take

place after carrageenan chains are solvated. Then starch would start swelling at ∼65 °C. Granules absorb

water, leading to a decrease in water volume outside starch granules and, consequently, concentrating

carrageenan and milk proteins in the continuous phase, this is known as the exclusion effect of swollen

starch (Matignon et al., 2014).

Whey protein – starch

At temperatures above 70°C whey proteins denaturate. They expose both SH groups and a hydrophobic

core, which could interact with the endogenous hydrophobic proteins present at the surface of starch,

mainly by hydrophobic interactions or disulphide links (Appelqvist & Debet, 1997). These interactions

could lead to a modification of starch granule surfaces and to an enhancement of the disruptive effects

of thermo-mechanical treatment during swelling (Matignon et al., 2014).

Casein-starch

Matser and Steeneken (1997) proposed that in starch-skim milk systems, casein micelles are excluded from the swollen starch granule. This leads to an increase in the concentration of protein between the swollen starch granules and an increase in the concentration of starch between the milk proteins, in this way casein micelles can contribute significantly to G’ of these systems. Moreover, due to its ionic nature, it is postulated that casein and its hydrolysates may interact readily

with amylose and outer branches of amylopectin through non-covalent hydrogen bonding. (Goel, Singhal

and Kulkarni 1999)

Whey protein with casein

Upon heating, at temperatures higher than 70 °C, whey proteins denature – both SH groups and a

hydrophobic core are exposed (Appelqvist & Debet, 1997). Thus, whey protein/casein micelles

complexes can be formed. Corredig and Dalgleish (1999) established that the two whey proteins, α-

lactoglobulin and β-lactoglobulin, react with each other, form intermediate complexes, and then interact

with casein micelles.

Milk proteins and xanthan gum

Xanthan gum is a polysaccharide with “weak gel” properties. In xanthan gum mixtures with skim milk

powder SMP, depletion flocculation of the casein micelles took place. Moreover, the increase of xanthan

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gum concentration decreased the size of the depleted protein aggregates; the microstructure resembled

a particulate network (Goh et al., 2008).

2.2 EFFECT OF HEAT TREATMENT IN THE INGREDIENTS

Milk

It is well known from literature that denaturation of whey protein starts at temperatures higher than 70

°C. In their study Corredig and Dalgleish (1996) noticed that the temperature range 85-90°C appeared to

be rather critical for the reactions occurring during heat treatment. Increasing the time of treatment

gave more extensive reactions, and higher temperatures caused faster protein-protein interactions

between casein micelles and whey protein in milk.

Furthermore, Rozycki, Buera and Pauletti (2010) studied the heat-induced changes in dairy products

containing sucrose. In their study temperature was the most influential individual variable, in

comparison to pH and protein concentration, on the thermal-induced gelation of milk in the presence of

sucrose. Also, the presence of sucrose increases gelation rate and its dependence on temperature.

The prominent sugar in milk is lactose. Lactose participates in the Maillard reaction as a reducing sugar

but also undergoes degradation by non-enzymatic browning reactions referred to as caramelisation

reactions. These reactions take place at high temperatures usually above 100°C (Newton, Fairbanks,

Golding, Andrewes and Gerrard, 2012). According to Patton (1952) the temperature range 100°C to

120°C appeared critical in the non-enzymatic browning of skim milk. Furthermore, when using glucose

and glucose syrups, care should be taken to avoid Maillard reaction between reducing sugars and milk

protein at the heat treatment step (Early, 1998). Moreover, casein and lactose were observed to be the

principal reactants in production of the color (Patton, 1952).

Starch

It is well known from literature that native maize starch cannot tolerate sterilization temperatures;

instead it is recommended to use a modified starch. Rapaille and Vanhemelrijck reported in their article

Milk based desserts that “adipate cross-linked acetyl-substituted waxy maize starch is very well suited for

use in sterilized dairy desserts” (as cited in Verbeken et al., 2006).

Lagarrigue, Alvarez, Cuvelier and Flick (2008) used in their study a modified waxy starch which increase

of viscosity occurs around 65°C and the maximum viscosity is achieved at 80°C-85°C. On the other hand,

granules of native starches presented degradation when heated above 74°C, since the granules at these

temperatures are quite sensitive to shear.

2.3 CORRELATION BETWEEN ANALYTICS AND SENSORY EVALUATION Thickness is an important sensory attribute in dairy desserts. It is a bulk property and it can be correlated

with rheological measurements since these parameters reflect primarily bulk properties of food (De

Wijk, Prinz and Janssen, 2006).

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De Wijk et al., (2003) found a strong positive relationship between stimulus viscosity and perceived

thickness. Moreover, oral thickness can be related with G” (storage modulus) at the crossover point of

G’-G’’ on dynamic stress sweep tests (De Wijk et al., 2006).

Tárrega and Costell (2007) obtained a good correlation between oral thickness and small deformation

measurements at an oscillatory frequency of 50 rad s-1. They concluded that the initial resistance to flow

(yield stress value) and the complex viscosity at 50 rad s-1 can be useful indices of oral thickness for semi-

solid dairy. This is in accordance with Van Vliet (2002) who proposed that the assessment of thickness for

products with a high viscosity or a yield stress can be related with the pressure (stress) required to

produce significant flow. For instance, Jellema, Janssen, Terpstra, De Wijk and Smilde (2006) found that

the attributes thickness and stickiness could be correlated with G’ (loss modulus) at 100 Pa in a dynamic

stress sweep and with consistency k in a flow curve test; thus related to (the start of) the flow behaviour

and concluded that to assess thickness and stickiness, the product needs to be deformed in the mouth.

Creaminess is another important attribute in semi-solid dairy desserts. De Wijk et al. (2006) proposed that very creamy (and fatty) mouthfeel is associated with foods that require relatively short times to reach maximum viscosities in steady shear measurements. Moreover, creaminess can be predicted rather well with rheological parameters that represent behaviour at break-up of the structure and start-up of flow. For instance, the critical stress at the G’–G” crossover well beyond the linearity limit and critical stress and strain calculated at the crossover point of G’ and G” (Jellema et al., 2006).

This type of analysis can be helpful in an industry due to the fact that some sensory tests can be avoided

at an early stage of the development of a new product.

2.4 COOKING VALUE AND THERMAL TIME

Cooking value

The application of heat during the processing operation causes not only microbial destruction but also

nutrient degradation, texture changes (usually softening) and enzyme inactivation. The final quality of

the product thus depends on the amount of heat it has received. The cooking value can be considered as

a quality indicator and was derived from the F-value definition; this can be explained with the lethal rate

(L) which is a quantitative measure, in minutes, of the rate of inactivation of organisms at a given

temperature. The integrated lethal rate is known as the F-value, as can be seen in the following

equations: (Holdsworth, 2007)

(1) (2)

Where Fr= integrated lethality (at the slowest heating point) (mins), t=time of processing (mins), T =

temperature (°C) at time t,Tref = reference temperature, 121.1 °C (equivalent to 250 °F), z= slope of the

logarithm of the decimal reduction time, D, versus temperature for the specific organism for (Clostridium

botulinum z=10°C) (Holdsworth, 1985).

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In other words D-value (decimal reduction time) is the time necessary at a specific temperature T to

reduce the number of microorganisms to 1/10 of the original value, while the z-value is the increase in

temperature necessary for obtaining the same lethal action or the same effect in one tenth of the time

(Kessler, 1981).

The cooking value concept has been strongly linked to first order kinetic and closed system.

Considering the same constraints used to derive F-value, if a quality factor has first order inactivation

kinetics, it is possible to obtain the following expression for a quality factor in a closed system:

(3)

As was the case for Fr, we can define:

(4)

Then:

Or, on its common form:

(5)

Where Dr value is the destruction rate of the target attribute at a specific temperature and zc is the

sensitivity of the destruction rate to temperature. D values for nutrients are usually much greater than

those for microorganism inactivation. However, z values for destruction of nutrients and quality factors

are much higher than that of microorganisms; due to the fact that biochemical reactions proceed at a

substantially slower rate than microbial inactivation. In general, the z values for nutrients and other

quality factors like vitamins, colors and flavors are 20°C-40°C or even higher (Holdsworth, 2007; Sun,

2012).

Cooking Value Calculation

In this study color, apparent viscosity and shear stress are the factors to be analyzed for the cooking

value calculation. The following equation will be used:

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According to literature the reference cooking value is characterized by zQ= 33.1 °C and Tref =100 °C, which represent the z-value and reference temperature for the most heat labile components. The cooking value, C0, relates the quality loss during a high-temperature thermal process to an equivalent cooking process at 100 °C (Sun, 2012). It was found in literature that the first-order kinetics models Ozawa method and the Kissinger equation

are very well-known models used for characterizing starch gelatinization (Altay and Gunasekaran, 2006).

Whereas, Lund (1984) suggested that the process of gelatinization is complex and not readily described

by pseudo first-order kinetics; due to the fact that in a population of starch granules, each of them has a

unique degree of crystallinity. In addition, even if the process can be empirically modelled the

interpretation of the mechanism from the model can be misinterpreted.

Certainly, these models would explain better the kinetics of starch, but due to the lack of information the

cooking value was chosen for trying to understand the effect of temperature in cream desserts.

Thermal Time

Thermal time is a calculation commonly used for modelling dormancy changes, seed germination and

growth in plants. (Qiu, Bai, Coulman and Romo, 2006). As the environmental temperature (Te) decreases,

their rates of development slow and, if the temperature falls low enough, development will cease at

their lower developmental (base) temperature (Tb). As temperature increases, their rates of

development increase up to a temperature optimum (To), above which they again decrease and

eventually cease at their temperature maximum (Tm). The thermal time, expressed in °C.days, provides a

measure of the physiological time required to complete the developmental process at any temperature

within the range Tb to To (Trudgill, Honek, Li and Van Straalen, 2005). For instance, considering a base

temperature of zero the following equation would apply:

CTU = ∑(𝑇𝑚𝑎𝑥 + 𝑇𝑚𝑖𝑛)

2

𝑛

𝑖

Where CTU represents the cumulative thermal units in degree days, i is the starting date to cumulate

degree days, n is the time required to complete development, Tmax and Tmin are the daily maximum

and minimum temperatures (Dietzel, 2014).

This equation can be applied later for the thermal time calculation of cream desserts produced in a BSD

line.

1.2 STUDY METHODOLOGY The core point of the study will be the experimental part, allowing to determine and show the impact of

the heat treatment conditions on the quality attributes of the product. As a consequence, the previous

steps will be of critical importance to ensure that all parameters to be studied, all variables affecting the

process and all measurements are under control. During the development of the project every phase

was subjected under carefully examination before approaching the next stage. Figure 1 shows a

condensed scheme of the study methodology followed.

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Literature review

Setting up the manufacturing

process

•Validation of 2 creme dessert vanilla recipes, with and without starch, for kitchen scale and bench scale manufacturing

•Validation of the kitchen scale process conditions

Selection and validation of

analytical methods (trials at kitchen

scale)

•Elaboration of a decision table based on analysis available at PTC Nestlè Lisieux and literature research choice of relevant analysis

•Evaluation of protocol for microscopy analysis

•Evaluation of oscillatory sweep test protocol for viscoelasticity measurements

•Repeatibility studies executed on kitchen trials for color and rheology measurements

Validation of trials protocolsduring

exploratory phase (at pilot plant

scale)

•Upscaling of process parameters in BSD line according to pilot plant constraints and factory process conditions.

•Establishment of sampling collection protocols (when, where, how)

•Evaluation of the stablility of the process in BSD line

•Upscaling kitchen recipes in BSD line with exploratory trials

Building of the DoE

•Determination of relevant factors to be studied.

•Temperature loss and average temperature evaluation using different levels of the holding tube with trials on water and updated recipe

•Measurement of holding tube temperature

•Data collection from Active Factory system

Execution and Analysis

•Execution of the DoE trials in BSD line

•Performed analysis were color, apparent viscosity, rheological measurements, microscopy observation, technical tasting, visual assessment and dry matter

•Interpretation of results

Cooking value calculation and thermal time

•Estimation of the 'cooking value' to evaluate the effect of temperature in the physical paramerters of a cream dessert recipe

•Calculation of "themal time" as a different method to interpret the effect of temperature in cream desserts

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Figure 1. Scheme of the study methodology followed for the project development

3. MATERIALS AND METHODS

3.1 RECIPE AND PROCESS AT KITCHEN SCALE First trials were done at kitchen scale to validate the recipes, which will be used later for the study and to

validate the analytical methods. A non-starch recipe was used at the beginning to determine the effect

of starch but was discarded for the final experimental design trials (Table 2). Further trials have been

done at pilot plant scale for the study of the impact of heat parameters on the production.

The following recipe was used for preparing vanilla cream dessert samples, at kitchen scale and pilot

plant scale during the exploratory phase.

Table 1. Recipe, including starch, used for preparation of samples at kitchen scale and exploratory trials

Ingredient Mass (g) Mass (%)

Fresh milk at 3.6% fat 1036,36 79,72

Milk Cream Liquid Past 34% Fat Bulk 54,08 4,16

Glucose syrup 27,04 2,08

Sugar White Medium EU-Category 2 Bag 81,9 6,30

Milk Skimmed Powder Medium Heat 64,74 4,98

Maize standard Starch ROQUETTE 9,36 0,72

Maize Starch CTEX 6204 22,88 1,76

Flavor Vanillin Powder 0,26 0,02

Carrageenan Satiagum ADC 234 SB 0,78 0,06

Gum Xanthan CX 91 2,6 0,20

Total 1300 100

Table 2. Recipe without starch used for preparation of samples at kitchen scale and exploratory trials

Ingredient Mass (g) Mass (%)

Fresh milk at 3.6% fat 1036,36 79,72


Glucose syrup 27,04 2,08



Butter 20 1,54

Maize standard Starch ROQUETTE 0 0

Maize Starch CTEX 6204 0 0




Total 1300 100

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Process in kitchen scale: The equipment used was THERMOMIX (figure 2) which has a controlled mixing

system with 2 liters volume and is able to reach 100°C as maximum temperature. The process and

conditions used are described in figure 3.

Figure 2. Thermomix used in kitchen trials

The temperature of the product during the process was measured every 1 min with a portable

thermometer.

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Figure 3. Flow process for cream dessert manufacturing in kitchen scale

3.2 RECIPE AND PROCESS AT PILOT PLANT SCALE During the exploratory phase the apparent viscosity of the final products was lower than the one

obtained at kitchen scale (Table 3). During kitchen process water evaporation occurs, therefore the

recipe for pilot plant trials was adjusted by increasing the quantity of all ingredients except milk, Table 4.

Mixing

Milk,cream, and glucose syrup in Thermomix, at

environment temperature

Time: 3 min

Speed: 3

Pre-heating of the mix

Temperature: 90°C

Speed: 3

Pre- mixing of powder ingredients

Addition of powder ingredients

Temperature: 90°C

Speed: 3

Heating

Temperature: 90°C

Time: 10 min

Speed: 3

Cooling at environment temperature

Stirring before dosing in cups

Sealing Cooling at 4°C

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Table 3. Comparison table with results of dry matter and apparent viscosity for exploratory and kitchen trials

Sample Dry matter (%)

Apparent viscosity (Cp)

BSD trial 1 24.1 21067

BSD trial 2 24.2 17600

BSD trial 4 24.2 15450

BSD trial 8 24.5 15267

BSD trial 10 24.3 18933

kitchen trial 3 28.3

91600

kitchen trial 4 101333

kitchen trial 5 - 66067



Table 4. Recipe used for preparation of samples in experimental design trials

Ingredient Mass (kg) Mass (%)

Milk Skimmed Liquid Bulk 18,53 74,12


Glucose Syrup 0,66 2,64



Starch Corn Standard ROQUETTE 0,23 0,92

Starch Corn Modified CTEX06204 0,56 2,24




Total 25 100

Process in bench scale: The equipment used was Bench Scale Dessert Line (BSD) which operates under a

continuous flow rate of 60 l/h, minimum volume of 20 liters, with indirect sterilization using heat plate

exchangers and is able to reach 130°C as a maximum temperature. The flow process is shown in Figure 5.

The line is equipped with 2 holding chambers:

One fixed holding tube ensuring the safety of the product with 170 cm length equivalent to 8

seconds

One additional holding chamber with 14 different levels.

19

Figure 4. Holding chamber with 14 levels

The holding times corresponding to the different levels of the holding chamber were calculated from the

drawings of the holding chamber (Reference= Holding tube Unit 700-supplier HPV/SPX) given in Annex 1.

The calculation described in Table 21 (Annex 2), takes into account the flow rate of the product and the

volume of product in the holding chamber at different levels. The different holding times available are

shown in Table 3.

All lines in pilot plant are supervised by a central data recording system (Active Factory from

Wonderware). This system monitors and registers in a continuous mode all the equipment parameters

during manufacturing process in the BSD line. Curves of the process were elaborated using the following

parameters: flow rate, homogenization pressure, cooking temperature, sterilization temperature,

holding tube temperature, pre-cooling and cooling temperatures.

20

Figure 5. Flow process for manufacturing vanilla cream dessert in Bench Sale Dessert Line

21

Table 5. Scheme of the sterilization holding chamber levels and its corresponding holding times.

# level Seconds per level

Holding time per level without flexible pipes (s)

0 (No holding chamber)

0 10,88

1 17,2 17,2

2 17,2 34,3

3 17,2 51,5

4 17,2 68,6

5 17,2 85,8

6 17,2 103,0

7 17,2 120,1

8 17,2 137,3

9 17,2 154,5

10 17,2 171,6

11 17,2 188,8

12 17,2 205,9

13 17,2 223,1

14 17,2 240,3

3.3 ANALYTICAL METHODS The analytical methods have been chosen form the literature review and from the methods available at

Nestle PTC Lisieux, depending on their relevance for explaining sensory attributes. Repeatability studies

have been carried out on the analytical methods used in the project with kitchen trials (starch and non-

starch recipes). It was used Q-stat software and it was applied the xyz method.

3.3.1 COLOR

Color was measured with ICP Colorimeter Konica Minolta CM5 by reflectance mode for opaque products.

Samples were poured in glass cells 4 cm high and 5.5 cm diameter. Sample was filled above 2cm high.

Samples were analyzed at D+7, D+14, D+21 and D+28 and two measurements were done on each

sample. Registered parameters were L* which represents lightness and ranges between 0 =black to

100=white; a* which represents redness/greenness and can be positive indicating redness or negative

indicating greenness and b* which represents yellowness/blueness with blue at negative b* values and

yellow at positive b* values.

Results of Repeatability Studies

Repeatability studies were done on 10 different samples, with 3 replicates for each sample. The

reference was coffee-mate, as described on the LI (Nestle Internal Laboratory instructions), Table 6.

22

Table 6. Coffee- mate as reference for color repeatability studies, data only available for L*

L*

Reference Standard deviation of repeatability

Repeatability limit at 95% for

duplicate results (%)

Reference LI-00.214 (reference coffee-mate)

0.156 0.43

The repeatability was calculated for L*, a* and b* values, even though for the reference there was only

data available for L*. Below are the results for L*, results for a* and b* are shown in Annex 3 and Annex

4, respectively.

Table 7. Color repeatability results for L* value for kitchen trials for both recipes.

L*

Mean Standard deviation of repeatability

Relative standard deviation of repeatability (%)

Repeatability limit at 95% for duplicate results

Relative repeatability limit at 95% for duplicate results (%)

Recipe with starch

Recipe without starch

All samples 90.89 0.16 0.2 0.43 0.5

3.3.2 VISCOSITY

The apparent viscosity (η) was measured using Brookfield viscometer at 5 rpm speed according to the LI

describing the protocol for chilled dairy products. Samples were measured at 8°C using spindle 92 with

4.8 cm diameter. Three measurements were taken along the height of the pot: top, middle and base

surface along 1 min and the average value per pot is calculated. Three repetitions were done per sample

and the analysis was done at D+7, D+14, D+21 and D+28.


Repeatability studies were done on 10 different samples, with 3 replicates for each sample. The relative

repeatability limit considered was 95%. The references were yogurt and cream dessert, as described on

the LI, Table 10.

23

Table 8. Yogurt and cream dessert as references for apparent viscosity repeatability studies

Reference Relative repeatability limit at 95% for duplicate results (%)

Reference LI-15.062 (yogurt) 12

Reference LI-15.062 (cream dessert) 7

The repeatability was calculated on all measures: top, middle, base surface and average. All results are

included in the range of the references values. Below are the results for the average apparent viscosity.

Other results are shown in Annex 5.

Table 9. Repeatability results for average apparent viscosity in kitchen trials with both recipes

Average Apparent Viscosity

Mean (Cp)

Standard Deviation (Cp)

Standard deviation of repeatability (Cp)


Repeatability limit at 95% for duplicate results (Cp)


Recipe with starch 66811 18260 2189 3,3 6067 9,1


13220 2983 382 2,9 1059 8,0

All samples 50378 43769 667 1,3 1849 3,7

3.3.3 RHEOLOGICAL MEASUREMENTS

After the preparation process the kitchen samples were kept at 4°C for 24h. Samples were analyzed at

Day +1 and D+7. BSD samples were storage at 8°C and were analyzed at D+7, D+14, D+21 and D+28.

Measurements were carried out in a controlled stress rheometer RheoStress 300 (Thermo Haake,

Germany), using parallel plates geometry of 20 mm diameter and 1 mm gap, monitored by a RheoWin

software package. A small-deformation measurement was performed, via oscillatory strain sweep test.

The percent of shear strain (ϒ) was varied from 0.01 to 500% at a constant frequency of 1 Hz. All samples

were allowed to rest for 3 min before starting a measurement. For each measurement a fresh sample

was loaded. All measurements were performed at 8°C and repeated at least once. The values of storage

modulus (G’), the loss modulus (G”), the shear stress (τ); and the complex viscosity (η*) as a function of

shear strain (ϒ) at the G’-G’’ crossover point, were obtained from the RheoWin software. An example of

a rheogram is shown on Figure 6.

24

Figure 6. Illustration of results obtained with an oscillation strain sweep test. Indicated are some of the parameters measured.


Repeatability studies were done on 6 different samples, with 3 replicates for each sample. The relative

repeatability limit considered was 95%. No reference was available for this method, only the storage and

the viscous modulus were used for the study, results are shown below.

Table 10. Repeatability results for storage modulus in kitchen trials with both recipes

Storage modulus

Mean (Pa)

Standard Deviation

(Pa)

Standard deviation of repeatability

(Pa)

Relative standard

deviation of repeatability

(%)

Repeatability limit at 95% for duplicate results (Pa)

Relative repeatability limit at 95% for duplicate

results (%)

Recipe with starch 55.02 8.86 6.7 11.2 17.09 31.1


7.14 0.51

All samples 38.24 44.23 3.22 8.4 8.92 23.3

G’= f(ϒ)

G’’= f(ϒ)

δ= f(ϒ)

G’-G’’ Crossover

point

δ in

°

G’ i

n P

a, G

’’ in

Pa

ϒ in %

25

Table 11. Repeatability results for viscous modulus in kitchen trials with both recipes

Viscous modulus

Mean (Pa)

Standard Deviation

(Pa)


(Pa)

Relative standard

deviation of repeatability

(%)

Repeatability limit at 95% for duplicate results (Pa)

Relative repeatability limit at 95% for duplicate

results (%)

Recipe with starch 57.47 7.79 4.23 7.4 11.73 20.4


7.063

All samples 40.13 46.15 2.51 6.2 6.95 17.3

3.3.4 MICROSCOPY OBSERVATION

Microscopic observation of starch and protein was done using Optical Microscope Olympus BX 53

equipped with a camera DP 25. Coloration with lugol was used for starch granules and bright green for

observation of protein clusters. Samples were measured at room temperature, two plates per sample

were prepared and 5 pictures were taken per plate using an enlargement of 10X. Analysis were done on

samples from kitchen trials but due to huge differences between each picture (Figure 7) , it was not

possible to choose with enough confidence one picture out of them which could be representative of the

product characteristics. Microscopy analysis was used only at the end of the study, to understand the

differences between samples at different cooking times (Section 5.5).

26

Figure 7. Microscopy images of a kitchen trial showing the difference in pictures between two plates prepared for the same sample

3.4 VISUAL AND SENSORY EVALUATION

3.4.1 TECHNICAL TASTING

A technical tasting was carried out with an expert from the sensory team and 2 evaluators. The test was

carried on D+21. One sample of each treatment was used per evaluator. The attributes evaluated were

color, firmness at spoon, thickness, granular aspect and caramel flavor. Table 14 specifies the definition

of each attribute assessed.

27

Table 12. Descriptive glossary used for technical tasting of vanilla cream dessert samples.

Attribute Definition

Aspect Color Intensity of the yellow color of cream

Texture

Firmness at spoon The resistance of the product when introducing a spoon to half in the product

Thickness in mouth Necessary force to crush a tablespoon of product in the mouth

Granular Granular aspect of the cream, orange's skin

Flavor Caramel Flavor intensity of cooked milk or cooked sugar notes

3.4.2 VISUAL ASSESSMENT

Pictures were taken to illustrate color, granular aspect and texture. A compact digital camera, Canon

SX600HS, with 18x Optical and 4x Digital Zoom was used. Samples were photographed on D+34 and

D+25 for the older and the latest samples, respectively. For the color test, a half to one spoon of sample

was poured and pressed in a plastic Petri dish. For granular aspect and texture, one spoon of product

was used. For texture, the spoon was turned between 80° to 90° to let it flow a little and the product was

photographed.

3.5 THERMAL TIME CALCULATION

3.5.1 DEFINITION

Thermal time is a term for describing the total amount of energy received by the product during the

manufacturing process. Considering a temperature profile the thermal time will be the estimation of the

area under the curve for temperature above 74°C (Figure 8).

As it is not possible to get a continuous measurement of the product temperature all along its heat

treatment:

Only every 1 min for kitchen scale process

60

80

100

120

35.0 40.0 45.0 50.0 55.0

Pro

du

ct t

em

pe

ratu

re °

C

time (min)

Product temperature profile during cooking

Δt

0

1

2

3

4

Area under the curve

Figure 8. Temperature profile showing the thermal time is the area under the curve

28

As it is not possible to get a continuous measurement of the product temperature all along its heat

treatment:

Only every 1 min for kitchen scale process

Only at temperature sensor location in BSD line

The average temperature and lapse of time between two measurements will be calculated. It will be

consider only the temperatures above 74°C; because this is, in the BSD line, the temperature measured

at the first temperature sensor.

3.5.2 PRINCIPLES FOR CALCULATION

The thermal time in a lapse of time will be the multiplication of the average temperature by ∆time and is

expressed in °C.min.

The sum of the thermal times at different lapses of time for temperatures above 74°C gives the total

thermal time of the product during heat treatment over 74°C.

∑ (Thermal time t0-t1 + Thermal time t1-t2 + Thermal time t2-t1 + Thermal time t2-t3 …) = Sample total

thermal time (Figure 9).

Figure 9. Thermal time calculation principle

The details of calculations are shown in Table 19 in Annex 4 for all kitchen scale relevant trials (trials 3, 4,

6 and 7). The average values of thermal times for kitchen heat treatment for the starch recipe is 1281

°C.min with a standard deviation of 41.3°C.min (Table 15).

60

80

100

120

Pro

du

ct t

em

pe

ratu

re °

C

Duration of heat treatment overcome by the product

Temperature profile

Δt

Δt

Δt

Δt

AvT°

T0

T1

T2

T3

T4

AvT°

AvT° AvT°

74

t4 t3 t2 t1 t0

29

Table 13. Results for thermal time and standard deviation for kitchen scale trials

Average thermal

time (°C.min)

Standard deviation (°C.min)

Kitchen heat treatment

1281 41.3

Kitchen scale: The temperature during the manufacturing of the samples was taken every minute and

temperature profiles were obtained (Figure10). The calculation can be done directly from the

temperature profiles using the method described on section 3.5.2. Kitchen thermal time calculations are

shown in Annex 6.

Figure 10. Temperature profile of thermal time of kitchen trials

During bench scale trials, it was not possible to measure directly the temperature profile undergone by

each individual product sample when flowing through the line.

The temperature profile of the product has to be rebuild form the temperatures measured by the

different temperature sensors located all along the line and the residence time of the product between

these sensors.

Bench scale: For calculating the thermal time, the following steps were followed:

30

Calculation of the volume of product inside the line, which includes: fixed tubes, homogenizer, flexible

pipes, holding tube, and plate heat exchangers between the different temperature sensors. The

temperature sensors tracked are located after the heat exchanger cooking phase, heat exchanger

sterilization phase, holding chamber and after the pre-cooling heat exchanger. The holding tube

temperature sensor has to be installed and connected to Active Factory system in order to have a more

real value of the sterilization temperature of the product. The general equations used for the calculation

are in Table 14. Results of calculation of volumes between temperature sensors are summarized in Table

15.

Table 14. Equations used for calculation of volume

Data Formula Units

F l/h Flow rate 𝐹 ∗ 10−3

3600 m3/s

Section of pipe

𝐴 = 𝜋𝑟2

m2

Speed

m/s

Length of the pipe

L m

Volume of the pipe

𝑉 = 𝜋𝑟2𝐿

or volume of product in equipment given by the

supplier

m3

Time to flow across the pipe 𝑉 (𝑚3)

𝐹 (𝑚3

𝑠)⁄ s

Table 15. Volumes of product in line

Stage in the line Conditions Volume (m3)

Before Cooking sensor with BSD homogenizer 0.00286

with Yogurt line homogenizer 0.00263

Between Cooking and Sterilization sensors

with cooking chamber 0.0042

without cooking chamber 0.0022

Between Sterilization and Holding tube

sensors

additional volume of the different levels of the holding chamber, including the connected pipes and tubes

Level 0 = 0.0002 Level 1 = 0.0005 Level 2 = 0.0008 Level 3 = 0.0010

𝑓𝑙𝑜𝑤 𝑟𝑎𝑡𝑒 (𝑚3

𝑠)

𝑠𝑒𝑐𝑡𝑖𝑜𝑛 𝑜𝑓 𝑝𝑖𝑝𝑒 (𝑚2)

31

Level 4 = 0.0013 Level 5 = 0.0016 Level 6 =0.0019 Level 7 = 0.0022 Level 8 = 0.0025 Level 9 = 0.0028 Level 10 = 0.0030 Level 11 = 0.0033 Level 12 = 0.0036 Level 13 = 0.0039 Level 14 = 0.0042

Between Holding tube and pre- cooling sensors

0.00134

1. Calculation of the time spent by the product between the different sensors taking into account

the real flow rate, around 60 l/h. Results of calculation of time are summarized in Table 16.

Table 16. Elapsed times for the product between the temperature sensors for flowrate equal 60 l/h

Stage in the line Conditions Time (s)

Before Cooking sensor with BSD homogenizer 174

with Yogurt line homogenizer 180

Between Cooking and Sterilization sensors

with cooking chamber 256

without cooking chamber 122

Between Sterilization and Holding tube

sensors

additional volume of the different levels of the holding chamber, including the connected pipes and tubes

Level 0 = 11 Level 1 = 28 Level 2 = 45 Level 3 = 62 Level 4 = 80 Level 5 = 97 Level 6 =114 Level 7 = 131 Level 8 = 148 Level 9 = 166 Level 10 = 182 Level 11 = 200 Level 12 = 217 Level 13 = 234 Level 14 = 251

Between Holding tube and pre- cooling sensors

80

2. Consider the corresponding temperatures at each temperature sensor in Active Factory data

base taking into account the elapsed time between sensors

32

3. Calculation of the thermal time as per general principle (refer to section 3.5.2).

A graphical explanation of these steps is showed below.

33

Figure 11. Calculation of the thermal time for trials manufactured in bench scale

34

An example of an Active Factory curve is shown in Figure 12. These curves of the process were

elaborated after collection of data from Active Factory system. The thermal time calculation was done at

the ‘stability period’ considered as the period of time when all parameters were stable.

Figure 12. Active Factory curve of trial 108°C- level 8- 2 min cooking

Table 17 shows an example of the thermal time estimation and Figure 13 shows its corresponding

temperature profile.

Table 17. Thermal time estimation of trial 108°C- level 8- 2 min cooking

108°C-level 8- 2 min cooking

Time (min)

Temperature °C

Δtime Average

Temperature °C

Δtime*AvTemperature

t0 37.9 74

3.07 81.9 251.2

t1 41.0 89.8

4.05 105.55 427.5

t2 45.0 121.3

2.98 109.4 326.4

t3 48.0 97.5

1.32 78.9 103.8

t4 49.3 60.2

Thermal time 1108.8

35

Figure 13. Temperature Profile of trial 108°C-level 8-2 min cooking

4. TRIALS AND BUILDING OF DESIGN OF EXPERIMENT (DoE)

4.1 KITCHEN TRIALS After few trials needed to adjust the process, all trials show a good repeatability.

4.2 EXPLORATORY TRIALS Exploratory trials were executed in the BSD line after previous manufacturing at kitchen scale. The aim of

this phase was to verify the recipes, the sampling recollection and to solve possible constraints that can

be found during up scaling in the BSD line.

The process conditions used were established according to the process followed at factory scale. Two

recipes were used, one including starch (Table 1) and another where the starch was replaced with fat.

Samples for viscosity analysis were collected at the end of the process in yogurt pots of 125 ml while

samples for dry matter analysis were collected at different times during the manufacturing process.

Besides, an external thermometer was connected after the sterilization holding tube in order to monitor

the exit temperature.

During the elaboration of the samples it was registered the time at which the product starts to pass

through the line, the time at which the Active Factory system starts the recording, the time at which the

product starts going out from the line and the time at which water starts to pass through the line for

cleaning. This information was used to have a better understanding of the active factory curves

elaborated later, Figure 14. The exploratory trials performed are shown in Annex 12- Table 29.

60

80

100

120

35 40 45 50 55

Tem

pe

ratu

re (

°C)

time (min)

Temperature Profile: DoE trial

108°C- level 8- 2 min cooking

0

1

2

3

4

36

Figure 14. Active Factory curve of exploratory trial 130°C-level 5-2 min cooking

During the manufacturing of the samples a big temperature loss was noticed between the sterilization

heat exchanger and the holding tube. Besides, the dry matter samples taken at the beginning of the

process had the lowest value for all the trials. Moreover, while performing laboratory analysis a lack of

texture was observed in all the samples in comparison to the kitchen samples. A technical tasting was

conducted confirming that the samples cannot be evaluated as cream desserts due to its lack of texture.

4.2.1 Conclusions Exploratory trials:

Temperature loss of 15°C between the sterilization and the holding tube units.

Recollection of samples for dry matter analysis has to start later

Lack of texture in all the samples, consequently the recipe was adjusted (refer to section 3.2)

Cancellation of first planned experimental design (DoE) trials.

Planning of new trials to evaluate the temperature loss in the holding tube

4.3 DETERMINATION OF TEMPERATURE LOSS IN THE HOLDING TUBE The aim of this second group of trials consisted on evaluating the temperature loss in the holding tube in

order to measure the exact temperature at the end of the holding tube and know the right temperature

to be studied in the DoE. For this purpose, a temperature sensor connected to Active Factory system

was installed after the exit of the holding tube. Two groups of trials were performed, with water and

with cream dessert recipe. The evaluation was executed at the lowest, the middle and the longest

holding time with 130°C and 125°C. Results of these trials are shown below. Active Factory curves were

elaborated (Figures 19 and 20).

37

Figure 15. Loss of temperature in holding tube for water, evaluated temperatures were 130°C and 125°C.

0

5

10

15

20

25

30

35

40

100

105

110

115

120

125

130

135

140

0 50 100 150 200 250

Loss

in t

em

pe

ratu

re (

°C)

Tem

pe

ratu

re (

°C)

Holding time (s)

Loss of temperature in holding tube for water

Sterilization temperature @130°C

Holding Tube temperature@130°C

Sterilization temperature @125°C

Holding Tube temperature @125°C

Loss in temperature @ 130°C

Loss in temperature @125°C

38

Figure 16. Average Holding temperature in holding tube for water, calculated from the Sterilization and Holding Tube temperatures, temperatures evaluated were 130°C and 125°C

116

117

118

119

120

121

122

123

124

125

126

0 50 100 150 200 250 300

Tem

pe

ratu

re (

°C)

Holding time (s)

Average Holding temperature in holding tube for water

Average Holding temperature @130°C

Average Holding temperature @125°C

39

Figure 17. Loss of temperature in holding tube for cream dessert using the first recipe, evaluated temperatures were 130°C and 125°C.

0

5

10

15

20

25

30

35

40

90

95

100

105

110

115

120

125

130

135

0 50 100 150 200 250 300

Loss

in t

em

pe

ratu

re (

°C)

Tem

pe

ratu

re (

°C)

Holding time (s)

Loss of temperature in holding tube for cream dessert: First recipe

Sterilization temperature @ 130°CFirst recipe

Holding Tube temperature @ 130°CFirst recipe

Sterlization temperature @ 125°CFirst recipe

Holding Tube temperature @ 125°CFrist recipe

Loss in temperature @ 130°C Firstrecipe

Loss in temperature @ 125°C Firstrecipe

40

Figure 18. Average Holding temperature calculated from the Sterilization and Holding Tube temperatures using the first recipe, temperatures evaluated were 130°C and 125°C

110

112

114

116

118

120

122

124

0 50 100 150 200 250 300

Tem

pe

ratu

re (

°C)

Holding time (s)

Average Holding temperature for cream dessert: First recipe

Average Holding temperature@ 130°C First recipe

Average Holding temperature@ 125°C Frist recipe

41

Figure 19. Active Factory curve: water trial for evaluating the holding tube temperature loss

Figure 20. Active Factory curve: cream dessert trial for evaluating the holding tube temperature loss

0

50

100

150

200

0:04:56 0:09:55 0:14:55 0:19:55 0:24:55

Time

Active Factory Curve: Water 130°C-level 14

Sterilization Temperature

Holding Tube Temperature

Cooking Temperature

Homogenization Pressure

Flow rate

Pre-cooling Temperature

Cooling Temperature

0

50

100

150

200

0:00:00 0:05:00 0:10:00 0:15:01 0:20:01 0:25:01

Time

Active Factory Curve: Cream dessert 130°C-level 14

Sterilization Temperature

Holding Tube Temperature

Cooking temperature

Flow rate

Pre-cooling Temperature

Cooling temperature

42

The loss of temperature in the holding tube was also evaluated when the recipe was updated and in the

elaboration of the DoE trials, these results are shown below.

Figure 21. Loss of temperature in holding tube for cream dessert using the updated recipe and for DoE trials

0

5

10

15

20

25

30

35

90

95

100

105

110

115

120

125

130

135

0 50 100 150 200 250 300

Loss

in t

em

pe

ratu

re (

°C)

Tem

pe

ratu

re (

°C)

Holding time (s)

Loss of temperature in holding tube for product: New recipe and DoE

Sterilization temperature @ 130°CNew recipeSterilization temperature @ 130°CDoESterilization temperature @ 125°CDoESterilization temperature @ 122 °CDoEHolding Tube temperature @ 130°New recipeHolding Tube temperature @ 130°CDoEHolding Tube temperature @ 125°CDoEHolding Tube temperature @ 122°CDoELoss in temperature @ 130°C NewrecipeLoss in temperature @ 130°C DoE

Loss in temperature @125°C DoE

Loss in temperature @ 122°C DoE

43

Figure 22. Average Holding temperature calculated from the Sterilization and Holding Tube temperatures. Results are shown for all the trials with cream dessert: first recipe, updated recipe and DoE trials.

After comparison of the Active Factory curves obtained, with water and with product, it was estimated

the time at which all the parameters were stable, ‘stability period’. For this, it was considered the time

since the valve to let the product pass was open until all the variables registered were constant in the

Active Factory curves (Figure 23). This interval varied from 15 min for the less viscous product until 25

min for the more viscous ones.

For calculating the duration of the trial, in addition to this interval it was also considered the elapsed

time from one sensor to another. Consequently, it was possible to ensure the thermal time estimation at

the ‘stability period’.

The Active Factory system was monitored constantly during the manufacturing of the trials in order to

guarantee the collection of samples at this period. Sampling for dry matter analysis was done at

different times during the ‘stability period’ to ensure the product obtained was not mixed with water. It

was noticed that the first dry matter samples taken when the ‘stability period’ was starting showed a

lower value.

Moreover, at this interval it was also calculated the Average Holding Temperature which is the mean of

the sterilization and holding tube temperatures. The Average Holding Temperature was lower than the

actual temperature set at the sterilization unit. Therefore, the Average Holding temperature was

considered for the elaboration of the new Experimental Design.

108

110

112

114

116

118

120

122

124

0 50 100 150 200 250 300

Tem

pe

ratu

re (

°C)

Holding time (s)

Average Holding temperature for cream dessert

Average Holding temperature@ 130°C First recipe

Average Holding temperature@ 130°C New recipe

Average Holding temperature@ 130°C DoE

Average Holding temperature@ 125°C Frist recipe

Average Holding temperature@ 125°C DoE

Average Holding temperature@ 122 °C DoE

44

4.3.1 Conclusions of temperature loss evaluation trials:

The highest the temperature set presented the highest temperature loss.

The extreme maximum point that can be applied in the new experimental design is 115°C with

maximum holding time.

Figure 23. Active Factory curve

4.4 BUILDING THE EXPERIMENTAL DESIGN (DoE)

4.4.1 Determination of the different factors

In order to define the different heat treatment factors that could have an impact on the cooking effect,

and variables of the process that could have an impact on the sensory attributes of the final product, a

brainstorming session was held. It was decided to study the effect of the following parameters of the

heat treatment:

Time and temperature of the sterilization step

Time and temperature of the cooking step (below 100°C)

It was also decided to study the importance of starch in the recipe and its interactions with the heat

treatment parameters.

On the other hand, it was chosen to keep constant other process parameters that could have an impact

on the sensory attributes of the final product, due to their interference with the heat treatment effect:

Mixing and homogenization temperatures

Homogenization pressure

Pre cooling and cooling temperatures

45

4.4.2 Determination of the level of the factors

For the determination of the level of the factors it was considered the manufacturing process of cream

desserts at factory scale. In factories the cooking step is done at 90°C for 2 min. According to literature

the gelatinization of starch starts between 60°C to 70°C. Therefore, a lower temperature was chosen to

see if there was an impact on the sensory attributes of the final product. 3 levels were decided to be

studied for the cooking step:

90°C 2 minutes

80°C 2 minutes

No cooking

The levels for the sterilization step were also based on factory scale. At factories the sterilization

treatment consists of 130°C during 15 seconds. Due to safety reasons established by the company, the

sterilization temperature cannot be lower than 125°C if the product is aimed to be tasted by an external

panel. Hence, the holding time was the parameter more flexible to be changed. The levels decided to be

study were the following:

For sterilization temperature:

130°C

125°C

For holding time:

15 seconds (implies no using the holding chamber)

90 seconds

4.4.3 Initial Design of Experiment

The experimental design consisted on 16 trials designed with one single 3-levels factor. The first 12 trials

formed a full factorial which aim was to target the recipe with starch and to allow the estimation of the

main effects of all experimental factors, and the interactions between heat treatment factors.

The factors studied were:

• Sterilization temperature: 2 levels 130°C /125°C

• Holding time: 2 levels 15 seconds /90 seconds

• Cooking process: 3 levels no cooking / 80°C for 2 minutes / 90°C for 2 minutes

• Recipe factor: 2 levels with starch / without starch

The other 4 trials formed a fractional factorial design which aim was to target the recipe without starch.

This second part of the experimental design would allow to estimate the main effects of all experimental

factors, but not the interactions between them (Table 18).

46

Table 18. First experimental design proposed

Trial Run

order

Cooking temperature and duration

Sterilization temperature

(°C)

Holding time (sec)

Recipe

T01 9 No cooking step 125 15 With

starch


starch


starch


starch

T05 12 80°C for 2 minutes

125 15 With

starch


125 90 With

starch


130 15 With

starch


130 90 With

starch


125 15 With

starch


125 90 With

starch


130 15 With

starch


130 90 With

starch

T13 7 No cooking step 125 15 No starch

T14 1 No cooking step 130 90 No starch


125 90 No starch


130 15 No starch

4.5 MODIFIED DoE

4.5.1 New Constraints

The temperature loss study limited the overall time of the project; consequently it was decided to

execute a small experimental design. The modifications consisted on discarding the recipe and cooking

process factors; this implies only keeping the recipe with starch and the cooking process of 90°C for 2

47

minutes. The time-temperature combination used as starting point for the elaboration of the DoE was

the heat treatment applied on factory scale (130°C- 15 seconds).

This modified experimental design consisted on 4 trials. These trials formed a full factorial design which

aim was to allow the estimation of the main effects of the experimental factors, and the interactions

between heat treatment factors. The design consisted on 2 factors with 2 levels.

Two factors were studied:

• Sterilization temperature

• Holding time

A central point was added with 2 different cooking times: 90°C for 2 min and 90°C with no cooking time

which allowed assessing the influence of the cooking step. The central point would be estimated with

the average temperature and average holding time of the extreme points. A graphic explanation is

presented on Figure 24. Repetition for this point was planned.

After the first group of trials was done the BSD homogenizer has to be replaced with the Yogurt Line

homogenizer; therefore one of the trials of this first group (130°C – level 14) was repeated each day of

trials in order to verify that the new homogenizer was not affecting the stability of the process. This lead

to a limited number of trials in which the central point lacked a repetition.

Figure 24. Graphic scheme of modified DoE including central point estimation

48

4.5.2 Determination of the levels of the different factors

From the results obtained after the temperature loss study, the final design of the experiment was

observed. It was considered the average between the sterilization and holding tube temperatures

referred as average holding temperature. A small temperature difference of 3°C was found between

treatments at 125°C and 130°C with the longest holding time (extreme point), leading to an

asymmetrical design and the potential risk of having similar final products with the treatments. A

graphical representation is shown on Figure 25 displaying the quadratic scheme expected from the

original DoE and the asymmetrical design obtained after the execution of the trials with water and cream

dessert recipe.

Figure 25. Comparative graphic between the quadratic design expected from the proposed DoE and the asymmetric design obtained after execution of the temperature loss evaluation trials, with water and cream dessert recipe.

After elaboration of the trials at 130°C for 251 seconds, it was seen that the maximum average holding

temperature that can be reached was 115°C; therefore this temperature was chosen for the lowest

extreme point.

To ensure a difference in the final product between treatments the factors were altered.

49

Resulting in:

• Sterilization temperature: 2 factors 130°C /115°C

• Holding time: 2 factors 62 seconds /251 seconds

The lower temperature chosen, 115°C, implied working under the safety limit which discarded the use of

an external panel for the sensory analysis and a technical tasting was effected instead.

Based on the average values of the modified factors the time-temperature combination for the central

point was estimated resulting in 122°C for 156 seconds. This value was between level 8 =148.2 s and

level 9= 165.3s; hence level 8 was arbitrary chosen for the manufacturing of the trials.

To gain one trial an extrapolation of the temperature loss value was done using the temperature loss

curves at 130°C for the New recipe and DoE at 251 seconds (Figure 21); with this value and the average

holding temperature obtained for the trial at the lowest extreme point, it was calculated the sterilization

temperature that need to be set in order to get the same average holding temperature with 115°C for

both holding times 62 seconds and 251 seconds, in that way a quadratic design can be assured. A graphic

explanation is shown on Figure 26.

Figure 26. Graphic explanation of the calculation of the sterilization temperature that need to be set in the sterilization unit for elaboration of trial at lowest temperature 115°C for longest holding time 251s.

For the Doe trials it was also calculated the elapsed times at the different temperature sensors (Annex 13

to Annex 16).

50

5. STATISTICAL ANALYSIS The statistical analysis was based on the results obtained for color (value L and a), apparent viscosity and

shear stress at D+21. It was used the Design-Expert software available at Wageningen University, for two

-level factorial design, being temperature and holding time and considering if the cooking step was

applied or not.

6. RESULTS

6.1 STATISTCAL RESULTS From the statistical analysis it was obtained 2 model equations, for a cooking and no-cooking step and a

3D graphic showing the interaction of the factors. The results are presented on the table below.

Table 19. Statistical results for value L*, a*, apparent viscosity and shear stress at D+21. Presented are p-value, significant factors and model equations with and without cooking step considering a significance level of 0.05

p-value Significant factors

Cooking step No Cooking step

Value L* 0.0304 Temperature "Prob>F"= 0.0188

𝐿= +154.84422− (0.62929 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)− (0.33176 × 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

𝐿= +155.70651− (0.62929 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)− (0.33176 × 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

Value a* 0.0645 Temperature "Prob>F"= 0.0490

𝑎= −34.22436+ (0.29592 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)+ (0.22058 × 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

𝑎= −34.06692+ (0.29592 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)+ (0.22058 × 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

Apparent viscosity

0.2017 No 𝐴𝑝𝑝𝑎𝑟𝑒𝑛𝑡 𝑣𝑖𝑠𝑐𝑜𝑠𝑖𝑡𝑦= +2.92562𝑒+005

− (2250.40401 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)− (636.42832 × 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

𝐴𝑝𝑝𝑎𝑟𝑒𝑛𝑡 𝑣𝑖𝑠𝑐𝑜𝑠𝑖𝑡𝑦= +2.94755𝑒+005

− (2250.40401 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)− (636.42832 × 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

Shear stress

0.0573 Temperature "Prob>F"= 0.0262

𝑠ℎ𝑒𝑎𝑟 𝑠𝑡𝑟𝑒𝑠𝑠−2.8

= −9.84382𝑒−006

+ (9.69590𝑒−008 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)

+ (2.27737𝑒−008

× 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

𝑠ℎ𝑒𝑎𝑟 𝑠𝑡𝑟𝑒𝑠𝑠−2.8

= −1. 00954𝑒−005

+ (9.69590𝑒−008 × 𝑇𝑒𝑚𝑝𝑒𝑟𝑎𝑡𝑢𝑟𝑒)

+ (2.27737𝑒−008

× 𝐻𝑜𝑙𝑑𝑖𝑛𝑔 𝑡𝑖𝑚𝑒)

In the case of the results for color the p-value of 0.0304 for the L* value model equation implies that the

model is significant and temperature is a significant factor with " Prob>F" equal to 0.0188. On the other

hand, the a* value model equation is not significant (p-value =0.0645) and temperature is a significant

factor, however with a " Prob>F" value of 0.0490 just below 0.05. The apparent viscosity model is not

significant (p-value=0.2017) and not significant factors were present. In contrast, The p-value of 0.0573

just above of 0.05 for the shear stress model equation suggested that the model is close to significant

and temperature is a significant factor with " Prob>F" equal to 0.0262. 3D graphics of the models which

include the cooking step are shown below.

51

Figure 27. 3D plot showing the interaction of temperature and holding time for L* at D+21 considering cooking step

Figure 28. 3D plot showing the interaction of temperature and holding time for a* at D+21 considering cooking step

52

Figure 29. 3D plot showing the interaction of temperature and holding time for apparent viscosity at D+21 considering cooking step

Figure 30. 3D plot showing the interaction of temperature and holding time for shear stress at D+21 considering cooking step

6.2 TECHNICAL TASTING AND VISUAL ASSESSMENT Table 20 shows the codification used for the technical sessions. The results from the technical testing on

flavor, color and texture are shown on Figures 31, 32, 33 and 34. A repetition was elaborated for trial

53

103°C- level 14 in order to obtain accurate results, however due to time constraint not technical tasting

and visual assessment was done.

Table 20. Identification codes used for the technical tasting sessions

Code Description

A 114°C-level 14

B 108°C-level 8- 0 min cooking

D 103°C- level 3

E 108°C-level 8- 2 min cooking

F 103°C-level 14

G 114°C-level 3

H 114°C-level 14 (repetition)

Caramel Flavor

Figure 31. Technical tasting evaluation on the attribute caramel flavor from least to most intense

Color

Figure 32. . Technical tasting evaluation on the attribute color from least to most intense

54

Granular aspect

Figure 33. Technical tasting evaluation on the attribute granular aspect from least to most intense

The trial with the lowest extreme point, 103°C- level 3, presents an evident granular aspect in

comparison to the rest of the trials.

55

Firmness at spoon

Figure 34. Technical tasting evaluation on the attribute firmness at spoon from least to most intense

In addition, samples H and A presented powdery perception, sample D was the most texturized sample

with gellified and sticky texture. The least sweet are the samples with no cooked caramel notes, and the

strongest vanilla flavor.

Pictures were taken for showing the temperature and holding time effect on the color (Figure 35), the

thermal time effect (Figure 36) and the cooking time effect (Figure 37). The pictures include only the first

trial 103°-level 14 but not the repetition trial.

56

Figure 35. Picture showing the temperature and holding time effect on the color.

From Figure 35 it can be seen that in the color the effect of temperature is much more important than

the holding time. In addition, it can be seen a dramatic change in color at 114°C-level 14 while the other

samples present a gradual change in color.

57

Figure 36. Color results ordered according to thermal time. For trial 103°C- level 14 the picture belongs to the first trial and not the repetition

The higher thermal time trials present the darker color but the trial with the lowest thermal time, 108°C-

level 8- 0 min cooking doesn’t have the lighter color. Color doesn’t increase with increased thermal time.

Figure 37. Cooking time effect in color

Trials with different cooking times show a little difference in color. In the technical session the trial with

2 min cooking time showed a darker color than the trial without cooking time, even though the picture

doesn’t give a good visualization of it (Figure 37).

58

From the sensory evaluation and sensory tests it was seen that the samples with higher thermal

treatment presented higher caramel notes, darker color and powdery perception, while the sample with

less heat treatment, 103°C-level 3, was the least sweet, with a strongest vanilla flavor, no caramel notes,

lighter color, higher granular aspect and firmness. The samples representing the middle points, with

cooking and not cooking time, were also sensed at least sweet, with strong vanilla flavor and no caramel

notes. However, in the tests of granular aspect and firmness, the sample with no cooking time was

ranked much higher than the sample with cooking time, while in the color test the latter was ranked

slightly higher than the trial with no cooking time.

6.3 COLOR The repetition for trial 103°C – level 14 presented the same results for both parameters describing color,

L* and a*. Therefore, the graphics were not altered and the results for the previous trial were

considered.

6.3.1 Value L*

Figure 38 shows the development of L* value along the shelf life of the product. The L* value seems

constant along the shelf life except at D+14 when a change was noticed.

Figure 38. L* value at D+7, D+14 D+21 and D+28. For trial 103°C-level 14 data for D+28 was not considered

76

78

80

82

84

86

88

6 8 10 12 14 16 18 20 22 24 26 28 30

L*

Days

Value L* during shelf life

103°C - level 3= 62 s

103°C - level 14= 251 s

108 °C- level 8= 148 s - 0 mincooking

108°C- level 8= 148 s - 2 mincooking

114°C - level 3= 62 s

114°C -level 14= 251 s

59

Figure 39. L* value at D+21 versus average holding temperature also showing sensory evaluation in color from least to most intense and visual assessment

Figure 39 shows that increasing the treatment temperature leads to a darker color of the sample,

expressed in higher values for lighter samples and lower values for the darker ones. Moreover, the

sensory results for color are in accordance with the L*values obtained in the equipment. Additionally,

from the statistical results the model for the L* value presented the best fit and temperature was a

significant factor in the model. Furthermore, the samples present a gradual increase in the darker color

of the samples; whereas the trial with the strongest heat treatment presented a dramatic change.

Figure 40. L* value at D+21 versus holding time, it is also presented color sensory evaluation from least to most intense and visual assessment

In this study the holding time doesn’t seem to have a big effect on L* value. With increasing holding time

almost all the samples present the same brightness, except for the samples with the strongest heat

60

treatment which presented a notorious darker color. Nevertheless, the model obtained for L* value with

the statistical results didn’t consider the holding time as a significant factor.

Figure 41. L* value at D+21 versus thermal time also related with color sensory evaluation from least to most intense and visual assessment

It was expected that a higher thermal time would result in darker samples, lower L* values. However not

a clear tendency can be seen with thermal time increasing. Despite the thermal time value all samples

present similar brightness. On the contrary, the samples with the extreme highest treatment showed a

darker color from the rest of the trials.

61

Figure 42. L* value at D+21 versus Cooking value, for z = 33°C and reference temperature= 100°C

As expected a higher cooking value presented a higher effect in L* value. From the results it can be seen

that almost all the samples presented similar cooking values which corresponding similar values for

brightness, except for the samples with the highest thermal treatment whose cooking value is quite high

in comparison to the other trials, and consequently presented a darker color. Lastly, for the results

obtained it can be seen that the cooking value can be useful for modelling L* for color, however more

trials are needed to prove this hypothesis.

6.3.2 Value a*

From the statistical results it was seen that the equation model for a* value was not significant, thus the

results were not considered for the analysis but are presented in Annex 17 to Annex 21.

6.4 APPARENT VISCOSITY For trial 103°C-level 14 a repetition trial was done. However, not all the analysis was completed and

some data is missing in the graphics. The values of apparent viscosity for the first trial were 1.4 times

higher (data not shown) than the values of apparent viscosity for the repetition trial. While the thermal

time value remained quite the same.

76

78

80

82

84

86

88

5 10 15 20 25

L*

Cooking Value

Value L*: Day 21

103°C - level 3=62 s

103°C - level14= 251 s

108 °C- level 8=148 s - 0 mincooking108°C- level 8=148 s - 2 mincooking114°C - level 3=62 s

114°C -level 14=251 s

62

Figure 43. Apparent viscosity at D+7, D+14, D+21 and D+28. For trial 103°C-level 14 data for D+28 was not considered

Figure 43 shows the development of apparent viscosity during shelf life. For almost all samples the

apparent viscosity seems to be stable, except for the sample with no cooking time which presents more

fluctuations. This observation might not be accurate due to the lack of statistical backups.

Figure 44. Apparent viscosity at D+21 versus average holding temperature compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. For trial 103 °C-level 14 no technical tasting session was done, it was a repetition trial

21000

31000

41000

51000

61000

71000

6 8 10 12 14 16 18 20 22 24 26 28 30

η (

Cp

)

Days

Apparent Viscosity during shelf life

103°C - level 3= 62 s

103°C - level 14= 251 s

108 °C- level 8= 148 s -0 mincooking


114°C - level 3= 62 s

114°C -level 14= 251 s

63

Figure 44 shows that increasing the treatment temperature leads to a lower viscosity. However, for

average holding temperatures above 108°C and 2 min cooking, the trials present similar values for

apparent viscosity. These viscosities are less in comparison to the trials with a less intense heat

treatment. In contrast, the sample with no cooking time presents a significant higher viscosity in

comparison to the sample with cooking process. Furthermore, the sensory attribute of thickness was

assessed as more intense for the sample with lower average holding temperature and less intense for

the highest average holding temperature, 114°C. Additionally, the trial without cooking time was

assessed as more thick and firmer at spoon than the trial with cooking time. On the other hand, the

attribute of firmness at spoon was assessed similar to the thickness attribute, with lower values at higher

average holding temperatures and vice versa; however the repetition trials 114°C- level 14 were quite

different, which was unexpected. From the graphic it can be seen a certain correlation between the

attribute thickness and apparent viscosity. Despite these observations, the apparent viscosity model

equation was not significant and not significant factors were present.

Figure 45. Apparent viscosity at D+21 versus average holding time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. For trial 103 °C-level 14 no technical tasting session was done, it was a repetition trial

Increasing the holding time leads to a decrease in viscosity when the average holding temperature is low. On the other hand, trials with 2 min cooking and above 108°C at different holding times have similar viscosities. In general, it seems that trials with less heat treatment have higher apparent viscosities. On the other hand the sample with no cooking time presents a higher viscosity than the sample with cooking time at the same holding time. In addition, the sensory attributes thick in mouth and firm at

64

spoon present a good correlation with the apparent viscosity of the samples at the middle point of the experimental plan, with cooking and no cooking time. The sample with no cooking time presented a higher viscosity and was ranked higher for these two sensory attributes in comparison to the sample with cooking time, which presents a lower viscosity and lower thickness and firmness at spoon. These observations might not be accurate due to the fact that in the model equation for apparent viscosity the model was not considered significant and no significant factors were present.

Figure 46. Apparent viscosity at D+21 versus thermal time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. For trial 103 °C-level 14 no technical tasting session was done, it was a repetition trial

Samples with similar thermal time values present different viscosity. A higher thermal time doesn’t imply a lower viscosity. Moreover, thick in mouth and firm at spoon couldn’t be correlated with the results obtained, except for the trials with cooking and without cooking time. Trial without cooking time has a lower thermal time, presented a higher viscosity, thick in mouth and firmness; while the trial with cooking time has higher thermal time, lower apparent viscosity and was ranked lower in these sensory attributes.

65

Figure 47. Apparent viscosity at D+21 versus Cooking value, for z = 33°C and reference temperature= 100°C

A higher cooking value entails higher effect on the apparent viscosity. The higher the cooking value the

lower the viscosity and vice versa. From the graphic it can be said that the cooking value model can be

useful for predicting apparent viscosity, nevertheless more trials are needed to confirm this observation.

6.5 RHEOLOGICAL MEASUREMENTS: Oscillatory Measurements

The rheological variables analyzed were complex viscosity, loss modulus (G”) and storage modulus (G’) at

the crossover point and shear stress at this point. However, as the tendency of the results was similar for

all the three parameters only shear stress variable was chosen for the analysis. The other results are

shown in Annex 22 to Annex 31. It was noticed that both trials for conditions 103°C-level 14 presented

very similar values for all the rheological measurements (data not shown). Hence, the shear stress results

for the repetition trial were used.

6.5.1 Shear stress

21000

31000

41000

51000

61000

71000

5 10 15 20 25

η (

Cp

)

Cooking Value

Apparent Viscosity η: Day 21 103°C - level 3=62 s

103°C - level14= 251 s

108 °C- level 8=148 s -0 mincooking108°C- level 8=148 s - 2 mincooking114°C - level 3=62 s

114°C -level 14=251 s

66

Figure 48. Shear stress at D+7, D+14, D+21 and D+28. Value of D+7 of trial 103°C-level 14 was not available

Figure 48 show that the samples were stable during shelf life. Even though, the data is incomplete for

the repetition trial 103°C-level 14 it can be noticed that the trial without cooking time presented more

variability. Nevertheless, these observations might not be accurate due to the lack of statistical backup.

Figure 49. Shear stress at D+21 versus average holding temperature compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. For trial 103 °C-level 14 no technical tasting session was done, it was a repetition trial

Increasing average holding temperature leads to a decrease in shear stress values. Furthermore, the trial

with the least heat treatment process presents the higher stress value while the other samples present

shear values within a closer range. In addition, the sensory attribute thick in mouth was more closely

0

50

100

150

200

250

300

350

400

6 8 10 12 14 16 18 20 22 24 26 28 30

τ (P

a)

Days

Shear Stress τ during shelf life

103°C - level 3= 62 s

103°C - level 14= 251 s



114°C - level 3= 62 s

114°C -level 14= 251 s

67

related to the results than firm at spoon, due to that repetition trials for the highest treatment process

were ranked differently in this attribute. Moreover, trials with and without cooking time presented

different shear stress values. The trial with no cooking time presents higher shear stress and was ranked

higher for thickness and firmness in comparison to the trial with cooking time. Lastly, for the statistical

results it was obtained a shear stress model close to significant in which temperature was a significant

factor.

Figure 50. Shear stress at D+21 versus average holding temperature compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. For trial 103 °C-level 14 no technical tasting session was done, it was a repetition trial

Holding time doesn’t have an important effect on shear stress. For samples with lower average holding

temperature it can be seen a decrease in shear stress. Samples with high average holding temperature

and different holding times don’t appear to have different shear stress values. Furthermore, all samples

seem to have similar stress values except for the trial with the slightest thermal treatment. Moreover,

the samples with and without cooking time don’t appear to show different shear stress results. The

sensory attributes evaluated don’t appear to be correlated with the results. For instance, the samples

with and without cooking time were ranked quite different during the technical session while their shear

stress appears to be very similar. In addition, the model equation for shear stress don’t show holding

time as a significant factor.

68

Figure 51. . Shear stress at D+21 versus thermal time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. For trial 103 °C-level 14 no technical tasting session was done, it was a repetition trial

It can be said that higher thermal time leads to a lower shear stress and vice versa. However this

reasoning only applies to the extreme points of the experimental trials. For the trial with the slightest

heat treatment a high stress value was obtained, while the other trials with different thermal time values

present shear stresses within a similar range. These observations might not be conclusive due to lack of

statistical data.

Figure 52. Shear stress at D+21 versus Cooking value, for z = 33°C and reference temperature= 100°C

0

50

100

150

200

250

300

350

400

5 10 15 20 25

τ (P

a)

Cooking Value

Shear Stress τ: Day 21

103°C - level 3=62 s

103°C - level14= 251 s


114°C -level 14=251 s

69

A higher cooking value not necessarily entails a lower shear stress and vice versa. It can be seen that

increasing the cooking value leads to a decrease in the shear stress until it became constant, apparently.

It can be said that the cooking value model can be useful for predicting shear stress; nevertheless more

trials are needed to confirm this hypothesis.

6.6 MICROSCOPY OBSERVATION Microscopy images were used for understanding the cooking effect. For the trial with no cooking time it

can be seen reduce presence of protein aggregation, indicated by the green clusters Figure 53. For the

trial with 2 min of cooking time, Figure 54, the protein aggregation is more evident. For both samples

there is presence of overcooked starch particles, broken particles of starch and medium cooked starch.

Figure 53. Microscopy images for trial 108°C- level 8- 0 min cooking. Presented are proteins in green color and starch in brown.

70

Figure 54. Microscopy images for trial 108°C- level 8- 2 min cooking. Presented are proteins in green color and starch in brown.

71

7. DISCUSSION

Color: L* value

In this parameter, temperature was the most important variable. The model equation for L*value

presented the best fit and temperature was a significant factor in the model.

Increasing the temperature entails to a darker color, lower values of L*, and vice versa; in the cream

desserts prepared in this study. The samples with the slightest heat treatment presented lighter color

while the trials with the strongest heat treatment were darker. These results are expected since lactose

and glucose syrup participate in the Maillard reaction as reducing sugars (Early, 1998; Newton et al.,

2012). Furthermore, lactose participates in non-enzymatic browning reactions, usually above 100°C,

leading to darker color in milk products (Newton et al., 2012). Additionally, Patton (1952) observed that

casein and lactose were the principal reactants in production of the color in milk. This hypothesis can be

confirmed since the recipe used contained skim milk, milk cream, skim milk powder and glucose syrup.

Moreover, a gradual change in color was noticed for all samples except for the extreme highest point,

114°C-level 14, where a dramatic drop was seen, this effect could imply that there is a critical

temperature at which the effect in color is more accelerated in dairy desserts. A possible explanation for

this is that the temperature range 100°C to 120°C appeared critical in the non-enzymatic browning of

skim milk (Patton, 1952), thus 114°C is closer to the higher value of the range given by Patton.

Furthermore, the sensory evaluation was well correlated with the L* values obtained, even though not

statistical analysis was performed. These results are in accordance with Tárrega and Costell (2007) who

found that parameter L* presented significant negative correlations with sensory results for color in

semi-solid dairy desserts using the Spearman correlation coefficient. Additionally, during storage at 8°C it

can be presume that color didn’t change, even if statistical analysis were not performed. This can be

supported by the study of Patton (1952) who suggested that a greater color development occurs at

higher storage temperatures and proved that storage at 4 ° C was quite effective in preventing color

formation during storage.

Finally, a decrease in L* value was noticed for all the samples at D+14, however in literature it was not

possible to find an explanation for this result.

Apparent viscosity

From the statistical results it was found that the apparent viscosity model equation was not significant

and not significant factors were present. However, some samples present a decrease in viscosity when

increasing the average holding temperature. Moreover, for average holding temperatures above 108°C

and 2 min cooking, the trials present similar values for apparent viscosity. It is known from literature that

swollen starch granules are susceptible to disintegration if subjected to physical impact or a severe

pressure drop. Pasted (cooked) starch granules can be disrupted by shear, resulting in lost viscosity,

shortness and textural stability. On the other hand, cross-linked starch, which is less subject to

degradation due to shear and gives a shorter, more viscous paste after severe shear, is required for

applications involving high shear after cooking and sterilization temperatures (Mason, 2009).

72

Furthermore, the gelatinization of native starch is between 62°C-72°C (Appelqvist & Debet, 1997) with a

maximum viscosity achieved at 80°C (Lund, 1984); while for modified waxy starch is around 65°C with a

maximum viscosity achieved at 80°C-85°C (Lagarrigue et al., 2008). In addition, Lagarrigue (2008) found

that native maize starches presented degradation when heated above 74°C, since the granules at these

temperatures are quite sensitive to shear. Moreover, modified waxy maize starch granules were found

to maintain their structure during a heat treatment of 120°C for 60 seconds. In this study the

temperatures used were 60°C, 74°C, 90°C and 114°C (maximum temperature). From the temperature

loss study and literature it is known that the onset temperature is higher than the actual temperature of

the product. Therefore, it is expected that at 60°C and 74°C (onset temperatures) the native starch is

partially disrupted. However, at 90°C it is possible that a higher disruption of the granules occurred.

Since modified starch is 2.4 times higher than native starch in the recipe used, this theory can partially

explain why at temperatures higher than 108°C a similar apparent viscosity was found.

Another reason for the loss in viscosity is given by Matignon et al., (2014) who found that the presence

of lactose or milk proteins seemed to favour starch swelling when the pasting was done at pilot

scale. Matignon, Neveu, Ducept, Chantoiseau, Barey, Mauduit and Michon (2015) explained that

aggregated whey proteins adsorpt onto swollen starch granules. The starch granules surfaces would

become rougher. When sheared vigorously starch granules rub at one another. A rougher surface would

lead to a higher stress. Finally, due to the rougher surfaces and higher shear stresses on the surfaces,

endogenous proteins could be detached from the surfaces of the starch granules resulting in a

weakening of the surfaces that could modify the dynamics of starch swelling: they would swell and

disrupt more easily. This hypothesis can apply to this study since whey proteins are more abundant than

modified starch.

Moreover, these 2 hypothesis: high shear applied on swollen starch granules and presence of milk

proteins favouring the starch swelling at pilot scale; might also explain why the trial with no cooking time

presented higher apparent viscosity than the trial with cooking time. Lagarrigue (2008) suggested that

few minutes of shearing at maximum starch swelling can disrupt granules structure. Moreover,

microscopy images can confirm this hypothesis.

According to the technical tasting the least sweet are the samples with no cooked caramel notes, and the

strongest vanilla flavor, which correspond to 108°C – level 8 with and without cooking time and 103°C –

level 3. The trial with the slightest treatment, 103°C-level 3 was the most texturized sample with gellified

and sticky texture while the trial without cooking time was ranked on second place with the highest

apparent viscosity. These results are in accordance with Costell, Peyrolón and Durán (2000) who showed

that gel strength modifies sweetness perception: soft gels of κ-carrageenan or gellan gels were judged

sweeter than medium or strong gels, which did not differ in sweetness intensity. Furthermore, according

to Gunasekaran and Mehmet (2000) in literature is well established that the intensity of perceived taste

and flavour decreases as the product thickness increases.

Furthermore, thickness in the mouth presented a better correlation than firmness at spoon with the

results of apparent viscosity. Even though no statistical results were elaborated it is well known from

literature that thickness and apparent viscosity can be correlated with oscillatory measurements and/or

73

Brookfield measurements. For instance, De Wijk et al., (2006) found strongest associations between

thickness and viscosity for viscosities measured with the Brookfield rheometer. Moreover, due to the

lack of data and limited number of trials the results were not conclusive.

In addition to this, unexpected results were found when the pre-cooling and cooling temperature were

increased. In trial 103°C – level 14 these temperatures were changed during the manufacturing process

due to safety reasons. The pre-cooling from 60°C to 80°C and the cooling from 20°C to 60°C. The

apparent viscosity of this failed trial (data not shown) was much higher than the repetition trial with the

original temperatures. This change in the pre-cooling and cooling stages only affected the apparent

viscosity but not the color or the rheological results. It can be hypothesized that interaction between

milk proteins took place. Upon heating, at temperatures higher than 70°C, whey proteins denature –

both SH groups and a hydrophobic core are exposed (Appelqvist & Debet, 1997). Thus, whey

protein/casein micelles complexes can be formed. It can be assumed that during the 2 min cooking step

the native starch granules were disrupted, however also milk proteins interactions started to take place

at this temperature. Increasing the temperature to 80°C and 60°C might have led to more formation of

whey protein/casein micelles complexes. In addition to this, Rozycki et al., (2010) concluded that the

presence of sucrose increases gelation rate in dairy products and its dependence on temperature.

During storage it was seen that the apparent viscosity was stable for almost all trials except for the trial

108°C- level 8-0 min cooking, however further trials and statistical analysis are needed to confirm this

observation.

Shear stress

The shear stress model equation suggested that the model is close to significant and temperature is a

significant factor. From the results it was seen that increasing average holding temperature leads to a

decrease in shear stress values. This can be interpreted as higher temperatures affect the internal

assembly of the product therefore less force is needed to break up its structure. In addition, the sensory

attribute thick in mouth was more closely related to the results than firm at spoon. It was found in

literature that a good correlation can be obtained between oral thickness and small deformation

measurements at an oscillatory frequency of 50 rad s-1 (Tárrega and Costell, 2007). However, for the

analysis of the cream desserts prepared in this study these conditions were adjusted in order to achieve

proper rheograms.

The equation model obtained can be useful for predicting shear stress in cream desserts. However,

further trials and statistical analysis shall be done in order to confirm that the shear stress under the

adjusted conditions can be correlated with sensory results. Additionally, the rheograms obtained for the

cream desserts prepared in this study were typical of gelled materials with G’ values higher than G” ones

and both showing little variation with frequency which was also the case for Tárrega, Durán and Costell

(2005).

Cooking value

It can be hypothesized that the cooking value can be a useful model for predicting color and texture

properties in cream desserts. However, further trials shall be done in order to confirm this.

74

8. GENERAL DISCUSSION AND CONCLUSION In this study average holding temperature was the most important variable affecting color and texture of

the cream desserts. L* value presented a good correlation to sensory results, even though not statistical

analysis was performed. In cream desserts not only starch but also milk proteins play an important role

in determining the texture of the product. Shear during the thermomechanical treatment can affect the

swelling of starch granules and therefore the final texture of the product. Lastly, is important to confirm

that all the variables are under control during the manufacturing process in order to don’t misinterpret

the latter results obtained. The cooking value can be useful for predicting color and texture in cream

desserts but more trials are needed. In general, further trials and statistical analysis are required in order

to confirm the hypothesis presented in this study.

8.1 RECOMMENDATIONS ON NEXT STEPS Additional studies can be done on the temperature loss in other pilot lines at PTC Nestle Lisieux

Study the effect of pre-cooling and cooling temperatures in cream desserts

Study the effect of cooking time in cream desserts at different temperatures and holding times

Evaluate if other cooking value models fix better to the results obtained

Study the effect of starch in cream desserts comparing with a no starch recipe

Study the effect of shear in cream desserts in pilot scale

Study the effect of hydration time in the hydrocolloids used in this study in order to achieve its

maximum benefit

Study the effect of changing the order of the ingredients

9. ACKNOWLEDGEMENT I would like to say thank you to all the PTC Lisieux people for the shared moments during my internship

there.

I am also very grateful to all the people who directly or indirectly were involved in this project:

The pilot plant personnel Jean-Emmanuel S., Jean- Marie D., Pascal C., Eric C., Dominique and Amandine.

The chemistry lab staff Geraldine H., Christine M. and Chantal C.

The members of the sensory department Muriele R-G., Audrey D. and Mary.

Special thanks to Nicolas P., Ann-Gael C. and Francois P.

And last but not least, my academic and company supervisors Matthijs Dekker and Isabelle Barbotteau.

Thanks to all of you for your patience, help, time and support.

75

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at High Temperatures and Heating Rates." Carbohydrate Polymers 73.1 (2008): 148-55. Web.

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78

ANNEXES

Annex 1. Holding Tube Unit 700-supplier HPV/SPX showing data used for calculations.

Annex 2-Table 21. Data obtained from Holding Tube Unit 700 scheme. The calculated data are volume and speed inside the holding tube and holding time per level.

Parameter Formula Units (mm) Units (m)

External diameter

12 mm 0,012 m

Width 1 mm 0,001 m

Internal diameter

10 mm 0,01 m

Length of a cylinder

Length of 1 level ( 2 rounds)

3541,8 mm 3,54 m

Length of 1 level + elbow connection

3641,8 mm 3,64 m

Volume of a cylinder

Total volume inside holding tube

0,0002860 m3

Speed

Flow rate

0,0167 L/s

Speed inside holding tube

0,212 m/s

Holding time per level

17,2 s

𝐿 = 𝜋𝑑

𝑉 = 𝜋𝑟2𝐿

𝑓𝑙𝑜𝑤 𝑟𝑎𝑡𝑒 (𝑚3

𝑠 )

𝐴𝑟𝑒𝑎 𝑡𝑢𝑏𝑒 (𝑚2)

Annex 3 - Table 22. Color repeatability results for a* value for kitchen trials for both recipes

a*

Mean Standard deviation of repeatability




Recipe with starch


All samples -1.53 0.08 -5.6 0.24 -15.5

Annex 4 - Table 23. Color repeatability results for b* value for kitchen trials for both recipes

b*

Mean Standard Deviation





Recipe with starch


All samples 18.0 0.7 0.13 0.7 0.35 1.9

Annex 5. Repeatability results for apparent viscosity at different levels of the pot

Annex 6-Table 23. Thermal time calculation for kitchen trials 3rd

, 4th

, 6th

and 7th

Annex 7-Table 24. Elapsed time to reach the cooking temperature sensor with a product flow rate equal to 60 l/h. The BSD homogenizer was changed with the homogenizer from the Yogurt line due to an issue during the first two trials.

Cooking Temperature Sensor

BSD line sections

Description Internal diameter d (mm)

Speed (m/s)

Length (cm)

time inside (s)

Pipe g Before homogenizer 8 0,332 50 1,51

BSD Homogenizer

Tube Fixed tube before and after

homogenizer 22 0,044 84

19,2

75,7 Homogenizer 55 0,007 39,3 56,02

Elbow After homogenizer, connected to a

flexible pipe 10 0,212 10

0,47

Yogurt line Homogenizer

Elbows and tubes

Connected before and after

homogenizer 9 0,262 101,00

3,86

61,9

Homogenizer 56 0,007 39,3 58,1

Pipe a After homogenizer 8 0,332 150 4,52

Tube a Before precooking heat exchanger

22 0,044 35,5 8,10

Cooking heat

exchanger

80.4

Tube b1 Includes cooking heat exchanger

sensor 9 0,065 9

1,37

Elapsed time before cooking sensor (s)

171,6 s with BSD homogenizer

157,8 s with Yogurt line homogenizer

Annex 8 -Table 215. Elapsed time to reach the sterilization temperature sensor with a product flow rate equal to 60 l/h.

Sterilization Temperature Sensor

BSD line sections

Description Internal diameter

(mm)

Speed (m/s)

Length (cm)

time inside

(s)

Tube b2 After cooking heat exchanger sensor 9 0,065 38,5 5,88

Pipe b2 Before cooking holding time chamber 8 0,332 150 4,52

Cooking holding

chamber

120

0

Tube c Includes external temperature sensor 22 0,044 22 5

Pipe c After cooking holding time chamber 8 0,332 150 4,52

Tube d Before sterilization heat exchanger 18 0,065 109 16,64

Sterilization heat

exchanger

80,4

Tube e After sterilization heat exchanger 18 0,065 40 6,11

Tube f Before safety chamber of sterilization heat exchanger

10 0,212 72 3,39

Small safety chamber (s)

8

Tube g1 After safety chamber, includes CCP sensor 10 0,212 8 0,38

Elapsed time between cooking and sterilization temperature sensors (s)

256,5 s with cooking chamber

122,4 s without cooking chamber

Annex 9- Table 22. BSD line sections considered for the calculation of the elapsed time to reach the holding tube temperature sensor

Holding Tube Temperature Sensor

BSD line sections

Description Internal diameter

(mm)

Speed (m/s)

Length (cm)

time inside (s)

Tube g2 After sterilization temperature sensor 10 0,212 10 0,47

Pipe d Before sterilization holding time chamber

8 0,332 150 4,52

Holding Chamber

Consisting on 14 levels 10 0,212 364-5098 17.2-240.3

Pipe e After sterilization holding time chamber

8 0,332 150 4,52

Tube j Before pre-cooling heat exchanger 10 0,212 29 1,37

Annex 10 - Table 27. Elapsed time to reach the holding tube temperature sensor according to the level used in the holding chamber, with a product flow rate equal to 60 l/h.


Seconds per level

# level Holding time without fixed tubes and pipes

Elapsed time between sterilization and holding tube sensors

17,2 0 0,00 11

17,2 1 17,2 28

17,2 2 34,3 45

17,2 3 51,5 62

17,2 4 68,6 80

17,2 5 85,8 97

17,2 6 103,0 114

17,2 7 120,1 131

17,2 8 137,3 148

17,2 9 154,5 165

17,2 10 171,6 182

17,2 11 188,8 200

17,2 12 205,9 217

17,2 13 223,1 234

17,2 14 240,3 251

Annex 11 - Table 238. Elapsed time to reach the pre-cooling temperature sensor

Pre-cooling Temperature Sensor

BSD line section Elapsed time between holding tube and pre-cooling

sensors (s)

Pre- cooling heat exchanger 80,4

Annex 12 - Table 29. Exploratory trials

Date Trial number

NesTMS

Cooking Temperature

(°C)

Cooking time (min)

Set Sterilization

Temperature (°C)

Holding time

(level)

Holding time (s)

Initial recipe

NS S

28/01/2015 19927.002 90 2 130 1 15

S

28/01/2015 19927.003 90 2 130 1 15 NS

02/02/2015 19927.001 90 2 130 1 15

S

03/02/2015 19927.004 90 2 130 5 90

S

03/02/2015 19927.006 90 2 130 5 90 NS

03/02/2015 19927.008 90 2 130 5 90

S

10/02/2015 19927.009 90 2 130 1 15 NS

10/02/2015 19927.010 90 2 130 1 15

S

11/02/2015 19927.011 90 2 130 5 90 NS

11/02/2015 19927.012 90 2 130 5 90

S

Annex 13 – Table 30. Elapsed time to reach the cooking temperature sensor for each DoE trial. The BSD homogenizer was changed with the homogenizer from the Yogurt line due to an issue during the first two trials

Cooking Temperature Sensor

Trial

Pip

e g

(s)

BSD

Ho

mo

gen

izer

(s

)

Yo

gurt

lin

e

Ho

mo

gen

izer

(s)

Pip

e a

(s)

Tub

e a

(s)

Co

oki

ng

hea

t ex

chan

ger

(s)

Tub

e b

1 (

s)

Elap

sed

tim

e b

efo

re

coo

kin

g se

nso

r (s

)

114°C-level 14

1,5

75,7

4,52 8,1 80,4 1,4

171,6 108°C-level 8-0 min cooking

103°C-level 3

61,9 157,8


103°C-level 14

114°C-level 3

114°C-level 14

Annex 14 – Table 31. Elapsed time to reach the sterilization temperature sensor for each DoE trial

Sterilization Temperature Sensor

Tria

l

Tub

e b

2 (

s)

Pip

e b

2 (

s)

Co

oki

ng

ho

ldin

g ch

amb

er (

s)

Tub

e c

(s)

Pip

e c

(s)

Tub

e d

(s)

Ste

riliz

atio

n h

eat

exc

han

ger

(s)

Tub

e e

(s)

Tub

e f

(s)

Smal

l saf

ety

cham

ber

(s)

Tub

e g

1 (

s)

Elap

sed

tim

e

be

twe

en

co

oki

ng

and

ste

riliz

atio

n

sen

sors

(s)

114°C-level 14

7,5

4,52 120 5,02 4,52

16,64 80,4 6,11 3,4 8

0,38 256,5

103°C-level 3


103°C-level 14

114°C-level 3

114°C-level 14

108°C-level 8-0 min cooking

- - - - 0,4 122,4

Annex 15 – Table 32. Elapsed time to reach the holding tube temperature sensor for DoE trials


Trial

Holding Chamber

Tube g2 Pipe d Pipe e Tube j Elapsed time between

sterilization and holding tube sensors

Level

103°C/114°C -level 3

3

0,47 4,52 4,52 1,37

62

108°C-level 8- 2 min/ 0 min

cooking 8 148

103°C/114°C -level 14

14 251

Annex 16 - Table 33. Elapsed time to reach the pre-cooling temperature sensor for all DoE trials

Pre-cooling Temperature Sensor

Pre- cooling heat exchanger Elapsed time between holding tube and pre-cooling

sensors (s)

80,4 80

Annex 17. a* value at D+7, D+14 D+21 and D+28

Annex 18. a* value at D+21 versus average holding temperature also showing color sensory evaluation from least to most intense

-4

-3

-2

-1

0

1

2

3

4

6 8 10 12 14 16 18 20 22 24 26 28 30

a*

Days

Value a* during shelf life

103°C - level 3= 62 s

103°C - level 14= 251 s

108 °C- level 8= 148 s - 0 mincooking


114°C - level 3= 62 s

114°C -level 14= 251 s

Annex 19. a* value at D+21 versus holding time also showing color sensory evaluation from least to most intense

Annex 20. a* value at D+21 versus thermal time also showing color sensory evaluation from least to most intense

Annex 21. a* value at D+21 versus Cooking value, for z = 33°C and reference temperature= 100°C

-3

-2

-1

0

1

2

3

4

5 10 15 20 25

a*

Cooking Value

Value a*: Day 21

103°C - level 3= 62 s

103°C - level 14= 251 s

108 °C- level 8= 148 s -0 min cooking

108°C- level 8= 148 s -2 min cooking

114°C - level 3= 62 s

114°C -level 14= 251 s

Annex 22. Complex viscosity at D+7, D+14 D+21 and D+28. Value of D+7 of trial 103°C-level 14 was not available

Annex 23. Complex viscosity at D+21 versus average holding temperature compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. The X figure shows the real complex viscosity value for trial 103°C-level 14

8

9

10

11

12

13

14

15

16

17

18

19

6 8 10 12 14 16 18 20 22 24 26 28 30

η*

(Cp

)

Days

Complex Viscosity η* during shelf life

103°C - level 3= 62 s

103°C - level 14= 251 s



114°C - level 3= 62 s

114°C -level 14= 251 s

Annex 24. Complex viscosity at D+21 versus holding time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. The X figure shows the real complex viscosity value for trial 103°C-level 14, no technical tasting session was done for this repetition trial

Annex 25. Complex viscosity at D+21 versus thermal time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. The X figure shows the real complex viscosity value for trial 103°C-level 14, no technical tasting session was done for this repetition trial

Annex 26. Complex viscosity at D+21 versus Cooking value, for z = 33°C and reference temperature= 100°C

Annex 27. Complex viscosity at D+7, D+14 D+21 and D+28. Value of D+7 of trial 103°C-level 14 was not available

8

9

10

11

12

13

14

15

16

17

18

19

5 10 15 20 25

η*

(Cp

)

Cooking Value

Complex Viscosity η*: Day 21

103°C - level 3=62 s

103°C - level14= 251 s


35

45

55

65

75

85

6 8 10 12 14 16 18 20 22 24 26 28 30

G' -

G"

Cro

sso

ver

(Pa)

Days

G'-G" Crossover during shelf life

103°C - level 3= 62 s

103°C - level 14= 251 s



114°C - level 3= 62 s

114°C -level 14= 251 s

Annex 28. . G’-G” Crossover at D+21 versus average holding temperature compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. The X figure shows the real G’-G”crossover value for trial 103°C-level 14, no technical tasting session was done for this repetition trial

Annex 29. G’-G” Crossover at D+21 versus holding time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. The X figure shows the real G’-G”crossover value for trial 103°C-level 14, no technical tasting session was done for this repetition trial

Annex 30. G’-G” Crossover at D+21 versus thermal time compared with results from technical tasting on the attributes firmness at spoon and thickness in mouth at D+21. The X figure shows the real G’-G”crossover value for trial 103°C-level 14, no technical tasting session was done for this repetition trial

Annex 31. G’-G” Crossover at D+21 versus Cooking value, for z = 33°C and reference temperature= 100°C

35

45

55

65

75

85

5 10 15 20 25

G'-

G"

Cro

sso

ver

(Pa)

Cooking Value

G'- G" Crossover: Day 21

103°C - level 3= 62 s

103°C - level 14= 251 s

108 °C- level 8= 148 s -0 min cooking

108°C- level 8= 148 s -2 min cooking

114°C - level 3= 62 s

114°C -level 14= 251 s

study of the cooking effect induced by...

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