Extraction of key components from cellular material ... · PDF fileExtraction of key components from cellular material: aspects of product and process design PROEFSCHRIFT ter verkrijging

Extraction of key components from cellular material :aspects of product and process designZderic, A.

Published: 01/01/2015

Document VersionPublisher’s PDF, also known as Version of Record (includes final page, issue and volume numbers)

Please check the document version of this publication:

• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differencesbetween the submitted version and the official published version of record. People interested in the research are advised to contact theauthor for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers.

Link to publication

Citation for published version (APA):Zderic, A. (2015). Extraction of key components from cellular material : aspects of product and process designEindhoven: Technische Universiteit Eindhoven

General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.

• Users may download and print one copy of any publication from the public portal for the purpose of private study or research. • You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ?

Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.

Download date: 14. May. 2018

https://research.tue.nl/en/publications/extraction-of-key-components-from-cellular-material--aspects-of-product-and-process-design(aac98f98-5d6a-45c7-a38f-55ce3db82f13).html

Extraction of key components from cellular material:

aspects of product and process design

PROEFSCHRIFT

ter verkrijging van de graad van doctor aan de Technische Universiteit Eindhoven,

op gezag van de rector magnificus prof.dr.ir. F.P.T. Baaijens,

voor een commissie aangewezen door het College voor Promoties, in het openbaar

te verdedigen op dinsdag 26 mei 2015 om 16:00 uur

door

Aleksandra Žderić

geboren te Šabac, Servië

Dit proefschrift is goedgekeurd door de promotoren en de samenstelling van de

promotiecommissie is als volgt:

voorzitter: prof.dr.ir. J.C. Schouten

1e promotor: prof.dr. J. Meuldijk

copromotor(en): dr.ir. E. Zondervan

leden: prof.dr.ir. M.C. Kroon

Prof.Dr.-Ing. G. Schembecker (TU Dortmund)

prof.dr.ing. M.H.M. Eppink (Wageningen UR)

dr. O. Trifunovic (Unilever)

adviseur(s): ir. G.D. Mooiweer (DE Master Blenders)

Extraction of key components from cellular material: aspects of product and

process design

A.Žderić

Eindhoven University of Technology

The research described in this thesis was sponsored by the Institute for Sustainable

Process Technology (ISPT), project number: FO-10-06

A catalogue record is available from the Eindhoven University of Technology

Library ISBN: 978-90-386-3854-6

To my family

Table of Contents

Summary ........................................................................................................ i

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

1.1. Fresh tea leaves and polyphenols ......................................................................... 2

1.2. Soybeans and oil bodies ....................................................................................... 3

1.2.1. Seed structure and chemical composition .................................................... 4

1.2.2. Soybean oil bodies ....................................................................................... 4

1.3. Mild separation pre-treatment techniques in food industry .................................. 6

1.4. Product Driven Process Synthesis (PDPS) methodology ..................................... 8

1.5. Objectives ............................................................................................................. 9

1.6. Outline ................................................................................................................ 10

1.7. References .......................................................................................................... 11

2 A study of mechanism involved during polyphenol extraction from fresh

tea leaves by pulsed electric field ................................................................ 15

2.1. Introduction ........................................................................................................ 16

2.2. Experimental procedure ..................................................................................... 17

2.2.1. Composition of tea leaf ............................................................................. 17

2.2.2. Moisture content analysis .......................................................................... 17

2.2.5. Specific energy input ................................................................................. 19

2.2.6. Determination of extraction yield - measurement of total polyphenols

content 20

2.2.7. Statistical analysis ..................................................................................... 20

2.3. Results and discussion ........................................................................................ 21

2.3.1. Characterization of pulsed electric field process and electric measurements

21

2.3.2. Effect of electric field strength on extraction yield of polyphenols ........... 23

2.3.3. Effect of the total treatment time on the extraction yield of polyphenols .. 25

2.4. Conclusion ......................................................................................................... 27

2.5. References .......................................................................................................... 27

3 Product-driven process synthesis for the extraction of polyphenols from

fresh tea leaves ............................................................................................ 31

3.1. Introduction ........................................................................................................ 32

3.2. Framing level and product ideas ........................................................................ 33

3.3. Input/output level ............................................................................................... 34

3.4. Task network ...................................................................................................... 37

3.5. Mechanism and operating window ..................................................................... 43

3.5.1. Design of experiments ............................................................................... 44

3.5.2. Variables (factors) ..................................................................................... 45

3.5.3. Statistical analysis ..................................................................................... 48

3.5.4. Response contour plots .............................................................................. 52

3.6. Conclusions ........................................................................................................ 53

3.7. References .......................................................................................................... 54

4 Isolation of oil bodies from soybeans in a mild way: definition of

operating window for process design ......................................................... 59

4.1. Introduction ........................................................................................................ 60

4.2. Materials and methods ....................................................................................... 61

4.2.1. Preparation of soybean flour ...................................................................... 61

4.2.2. Aqueous extraction of soybean oil bodies ................................................. 62

4.2.3. Enzyme/ultrasound-assisted aqueous extraction ....................................... 63

4.2.4. Recoveries ................................................................................................. 63

4.3. Results and discussion ........................................................................................ 64

4.3.1. Effect of particle size on the aqueous extraction of soybean oil bodies .... 64

4.3.2. Enzymatic hydrolysis and ultrasonication of the coarse soy flour on the

aqueous extraction of OBs .......................................................................................... 69

4.4. Conclusion ......................................................................................................... 71

4.5. References .......................................................................................................... 72

5 Product-driven process synthesis for the extraction of oil bodies from

soybeans ....................................................................................................... 75

5.1. Introduction ........................................................................................................ 76

5.2. Framing level ..................................................................................................... 77

5.3. Consumer wants and product ideas .................................................................... 78

5.4. Input/output level ............................................................................................... 81

5.5. Task network ...................................................................................................... 82

5.6. Mechanism and operating window ..................................................................... 86

5.7. Equipment integration ........................................................................................ 88

5.8. Conclusions ........................................................................................................ 92

5.9. References .......................................................................................................... 92

6 Conclusions and Outlook ......................................................................... 97

6.1. Conclusions ........................................................................................................ 97

6.1.1. Polyphenols from tea leaves ...................................................................... 98

6.1.2. Oil bodies from soybeans .......................................................................... 99

6.2. Outlook ............................................................................................................. 100

6.2.1. Wax removal from the surface of tea leaves ............................................ 100

6.2.2. Pulsed electric field method .................................................................... 100

6.2.3. Product and equipment integration .......................................................... 101

Acknowledgements................................................................................... 129

List of publications ................................................................................... 131

Curriculum vitae ...................................................................................... 133

i

Summary

Summary

Extraction of key components from cellular material:

aspects of product and process design

Novel engineering techniques promote the development of new technologies that improve

product quality. The increasing consumption volume of food additives/ingredients demands

for stringent requirements to comply with current food industry principles. Extracts from

plant material are a rich source of important compounds for nutraceutical or pharmaceutical

applications.

Tea leaves are rich in polyphenols which can be used in e.g. food, cosmetic and

pharmaceutical industry. Polyphenols have been considered to have a health-promoting

potential as antioxidant agents, which predominantly destroy free radicals.

Soybean grains contain oil bodies that can be used among others as emulsifying agent for a

wide variety of products, ranging from e.g. vaccines, food, cosmetics and personal care

products.

The objective of the work reported in this thesis is to provide basic knowledge and to

subsequently elaborate a conceptual process design for isolation of key components from

fresh tea leaves and soybeans in a mild way. Process costs should be acceptable and

product quality/purity should be suitable. Mild conditions are defined as follows: only use

food grade solvents, avoid strong acidic or alkaline conditions, and applies only mild

temperatures (< 40 oC). The Product Driven Process Synthesis (PDPS) methodology is

applied as a structural approach to deliver the appropriate processing routes for polyphenols

extraction from tea leaves and isolation of oil bodies from soy. The PDPS methodology

includes nine hierarchical levels that connect product design and process synthesis taking

into account the laws of thermodynamics, food, organic, and physical chemistry as well as

chemical engineering principles e.g. transport phenomena and separation technology.

Among different technologies, pulsed electric field (PEF) has been selected due to the fact

that it is a non-invasive method for opening the cell structure in tea leaves. The PEF

application to the tea leaves may result in an increase of temperature (by ohmic heating)

and in electrically stimulated damage of cell membranes (by electroporation). The total

specific energy input and the observed temperature increment point to a non-thermally

based increase of the permeability of the cell membranes for polyphenols. The temperature

of the aqueous suspension of the tea leaves after PEF treatment increased upon

intensification of the applied pulsed electrical energy. The highest treatment temperature

ii

Summary

increase achieved in this study was 7 °C after PEF treatment, using a pulsed electrical

energy of 29 kJ/kg at the highest electric field strength of 1.1kV/cm. The obtained results

indicate that under used conditions the increase of temperature did not exceed 10 oC. This

limited temperature increase provided a valid evidence that pulsed electric field (PEF)

processing is a non-thermal and mild method.

In the input-output level of PDPS it was found that polyphenols (PPs) in fresh tea leaves are

located in plant cell organelles called vacuoles. Prior to the actual extraction step, the cell

structure needs to be open in order to reach the PPs. This finding led into the task network

level where screening of different technologies (the “mechanism” its PDPS nomenclature)

for opening the cell structure was performed.

The extraction process has been described with a polynomial model generated from

statistical analysis of the results obtained by the Design of Experiments (DoE) method

using Box-Behnken design. Three factors that are expected to have a significant impact on

the extraction yield were evaluated: the electric field strength (E), the pulse duration or

pulse width (PD), and the number of pulses (N). The results of statistical analysis

demonstrated that the electric field strength was the most significant factor for the

extraction yield. The model developed was used to optimize the process conditions to

maximize the extraction yield of PPs. The optimal combination of E, PD and N allows 32

% extraction yield of PPs.

The pulsed electric field method is a promising technique for opening the cell structure and

for extraction of cellular material in molecular form.

In the case of soybeans, the aqueous extraction process (AEP) was experimentally tested as

an alternative for the solvent based oil extraction process with the objective to isolate intact

oil bodies (OBs) in a mild way. A simple AEP or benchmark was applied on two soy flours

obtained with different grinding methods, coarse (d90=300 µm) and fine (d90=40 µm). The

extractability of the protein coarse flour was significantly better as compared to that the fine

flour (respectively, 48 % and 40 % based on the total protein content). The oil recovery

from the coarse and fine flour was not significantly different (respectively, 23 % and 24.5

% based on the total soybean oil). In addition, to enhance the extraction yield of protein and

oil, three different pretreatments were applied to the aqueous extraction process. The

pretreatments included enzymatic hydrolysis, application of ultrasound and a combination

of these two. We reported that pretreatment with ultrasound reduced the remaining

insoluble fraction and increased the amount of solids extracted into the aqueous phase. The

combination of ultrasound and enzymes resulted in the cream with the highest lipid-to-

protein weight ratio, i.e. 10:1.

The PDPS approach was applied for the design of a process for isolation of OBs. In the

product design part of PDPS, i.e. in the consumer wants and product ideas level, the

iii

Summary

consumer wants were translated into product formulations. The House of Quality method

was used to provide a link between consumer’s wants and the design of a process bringing

together product attributes and measurable product properties. Depending on the

application, whether OBs will be used as a food additive (e.g. as a natural antioxidant in

mayonnaise) or in cosmetics (e.g. in face creams), the product i.e. OBs themselves requires

different physical, chemical, and microbiological properties. In our particular case, OBs

were produced as an intermediate product and they could be used as food natural

antioxidant in, for instance, a mayonnaise.

In the task network level of PDPS methodology, two alternatives were generated based on

experimental results. The major differences between the two proposed task network

alternatives rely on the mechanism associated to the cell wall disruption task. In the first

alternative, cell wall disruption was performed only with enzymes In the second alternative,

enzymes were combined with ultrasonic treatment. These two different treatments were

applied to the soy flour to improve the extraction of the OBs. Cell wall degrading enzymes

were applied to break the cotyledon cell and to make the structure more permeable.

Ultrasound was applied to increase the transport of elements through cellular membranes

and to extract cellular structures from damaged cells by cavitation. These alternatives were

experimentally verified. At the end a combination of enzymes and ultrasound was chosen,

because this combination improved the purity of the cream (final product), enhanced the

protein-lipid separation, and reduced the processing time. For the selected processing route

an overall process design was made. In addition, the estimation of the economic potential

showed that the proposed process for extraction of OBs had a higher economic potential

than the conventional process for the production of soybean oil due to the use of hexane.

Owing to the complexity of food matrices, the product driven process synthesis

methodology has been successfully applied as a useful and powerful tool for conceptual

process design for the isolation of key components from raw materials e.g. polyphenols

from fresh tea leaves and oil bodies from soybeans.

1

Chapter 1

Chapter 1

Introduction

During the last decade, the food industry has been facing on technical and economic

changes in society and in the manufacturing as well as food processing. These changes

however, have a significant impact on the entire food supply chain. Food products have to

meet the consumers' demand for a healthy lifestyle. Consumer requirements in the field of

food production have changed considerably: in fact, consumers increasingly believe that

food contribute directly to their health. For example, animal fat contribute to e.g. increases

the risk for a heart disease, cancer, and raises the cholesterol level in blood. On the other

hand, seed oils such as soybean oil and safflower oil provide cancer-preventive antioxidants

by lowering “bad cholesterol”. Vegetable seed oils have not been consumed until the 20th

century, simply because we did not have technologies to extract them.

The consumption of processed seed and vegetable oils has increased dramatically in the

past century. These oils are produced and extracted from seeds like soybean, cottonseed,

sunflower and a few others. Figure 1.1 shows how consumption of polyunsaturated fats

present in seed material has increased in the past century (right) and at the same time

consumption of animal origin fats has decreased (left). Both graphs contain data obtained in

United States.

Figure 1.1. Consumption of animal fat (left) and vegetable and seed oils (right) in the United States in the past

century. Source: Authority Nutrition (2011)

However, conventional processing of different seed materials involves harsh process

conditions which destroy natural ordering, protection and preservation of components in the

plant matrix. First, seeds are crushed and free oil is released. Exposure to air leads to

oxidation that causes off-flavors. A second step is extraction step in oil production. For

extraction an organic solvent such as n-hexane is used. A reason for the use of n-hexane is

the high oil solubility but on the other hand there is a possibility of hexane residue in the

2

Introduction

final product. Later in the process, anti-oxidants need to be added to prevent the unsaturated

oils from going rancid. Rancidity results in a number of undesired effects, such as loss in

quality and/or a more difficult separation of components of interest afterwards. Knowing all

these drawbacks of the current production, the necessity for milder release/disclosure of

plant components is obvious.

This PhD project focuses on conceptual process design of novel and mild process routes for

isolation of valuable components from two different types of raw materials: fresh tea leaves

and soybeans. These two raw materials are different in composition: fresh tea leaves, being

naturally high in water content and soybeans having a low water content. Both raw

materials need their own approach, as the properties differ a lot in terms of components, as

well as in terms of interactions between the plant matrix and organelles. In the case of fresh

tea leaves, polyphenols are compounds of interest. Oil bodies and native (not denatured)

proteins are target compounds in soybeans.

1.1. Fresh tea leaves and polyphenols

Green tea processed from Camellia sinensis leaves is a common, globally consumed

beverage. There are two major kinds of tea, black tea and green tea. Tea contains large

amounts of tannins or phenolic substances (5–27 % w/w) consisting of catechin (flavanol)

and gallic acid units, with those in green tea being higher than those in black tea (Leung

and Foster, 1980). Both green and black teas contain caffeine (1–5 % w/w) with small

amounts of other alkaloids also present. Tea composition varies with climate, season, tea

variety, and age of the leaf. In general, fresh green tea leaves contain 36 % w/w

polyphenols, among which catechins prevail. Pharmacological properties of tea are

primarily due to its alkaloids (caffeine) and catechins, which are divided into four primary

compounds (see Figure 1.2), epicatechin (EC), epicatechin-3-gallate (ECG),

epigallocatechin (EGC), epigallocatechin-3-gallate (EGCG), and four secondary

compounds, catechin (C), catechin gallate (CG), gallocatechin (GC), and gallocatechin

gallate (GCG). EGCG is the predominant catechin present in green tea leaves (48–55 % of

total polyphenols) (Perva-Uzunalić et al., 2006).

3

Chapter 1

Figure 1.2. Chemical structure of major catechins in green tea leaves

Green tea is considered to be one of the world's healthiest drinks and contains the highest

amounts of antioxidants of any tea. Polyphenols in green tea are thought to provide anti-

inflammatory and anti-carcinogenic effects. Epigallocatechin-3-gallate (EGCG) is the most

studied (Perva-Uzunalić et al., 2006) and bioactive polyphenol in tea and has been shown

to be the most effective in eliminating free radicals.

1.2. Soybeans and oil bodies

Soybean (Glycine max L.) is a seed belonging to the family Leguminosae. It is presently the

world’s most important oilseed in terms of total production volume and international trade

(Kapchie, et al., 2011). Soybeans account for about 35 % of total harvested area devoted to

annual and perennial oil crops. Worldwide, soybean meal (~98 %) is the primary source of

protein for poultry and livestock industries. Regardless of its nutritional value, only 2 % is

consumed directly by humans, in the form of soy food products (Jung, 2009; Karki, et al.,

2012).

4

Introduction

1.2.1. Seed structure and chemical composition

Soybean seeds have three major parts, the seed shell or hull (8 %), the germ (2 %) and the

cotyledon (90 %) (Salunkhe, et al., 1992). The structure of soybean seed is presented in

Figure 1.3. Typical cotyledon cells have a cylindrical shape; diameter and length of

cotyledon cells about 30 µm in diameter and 70-80 µm respectively (Campbell, 2010). The

wall consists of polysaccharides, proteins and phenolic compounds (lignins) (Ouhida, et al.,

2002). Oil bodies are lipid storage organelles of about 0.2–2.0 μm in diameter for most

oilseeds and 0.2–0.5 μm in the case of soybean (Bair and Snyder, 1980; Murphy, 1993 and

Wu et al., 2012). Oil bodies consist of a lipid core and shell of oleosins and phospholipids.

Figure 1.3. Structure of the soybean seed. Larger organelles in cells represent protein bodies and lipid bodies are

oil bodies (Rosenthal, et al., 1998)

1.2.2. Soybean oil bodies

In nature, soybean oil is encapsulated within micron-sized oil bodies that are present within

mature or germinating soybean seeds, see Figures 1.2 and 1.3. In Figure 1.4 transmission

electronmicrograph of soybean is shown.

5

Chapter 1

Figure 1.4. Transmission electronmicrograph of a soybean cell (Rosenthal, et al., 1998)

Plant cells store lipids as a food reserve for germinative and postgerminative growth. These

lipids are located in the cytoplasm and they are stored in subcellular particles called oil

bodies (OBs) or oleosomes. These oil bodies consist of a central neutral lipid core (94–

98 % w/w) that is surrounded by a phospholipid monolayer (0.5–2 % w/w) and a shell of

strongly amphiphilic oleosin (0.5–3.5 % w/w) (Li et al., 2002; Chen, et al., 2012). To

stabilize the storage lipids, the OBs are coated with a layer of phospholipids. Such particles

alone, however, would not be stable towards coalescence nor their chemical stability is very

limited due to the presence of phospholipases (Kapchie, et al., 2009). A complete layer of

protein (called oleosin) improves the stability in two ways. Firstly, it protects the

phospholipids monolayer from attack by the phospholipases present in the cell. Secondly, it

gives the oil bodies a negatively charged surface, thereby providing colloidal stability i.e.

preventing aggregation (Tzen, 1992; Hsieh and Huang, 2004). Oleosin proteins provide the

oil bodies with physical and chemical protection against environmental stresses, such as

moisture variations, temperature fluctuations, and the presence of oxidative reagents (Chen,

et al., 1998). Soybean OBs have similar or a better physicochemical stability as compared

to the oil droplets in soybean oil-in-water emulsions produced from isolated ingredients

(Chen et al., 1998). Based on both experimental evidence and theoretical calculations, a

structural model of OBs has been proposed (see Figure 1.5) (Rosenthal et al., 1998). Oil

bodies can be depicted as an oil core (94–98 % w/w), surrounded by a monolayer of

phospholipids (0.6–2 % w/w) containing embedded oleosins (0.6–4 % w/w) (Hsieh

and Huang, 2004).

6

Introduction

Figure 1.5. Oil bodies in seed. Left image is a transmission electron micrograph showing large and conspicuous

storage protein bodies and small but numerous oil bodies. Model of an oil body, which includes a matrix of oil (in

blue) enclosed by a layer of phospholipids (red) and the structural protein oleosin (yellow) is presented. The three

types of molecules are drawn to similar scales, whereas the diameter of the oil body has been reduced 24 times to

magnify the surface structure. (Rosenthal, et al., 1998)

Intact OBs are considered as a natural form of an emulsion that, in situ, protects the oil

from oxidation during storage (Campbell, 2010). Moreover, OBs have the advantage over

solvent extracted oil that they required neither emulsifiers nor high pressure

homogenization during processing (Kapchie, et al., 2011). The high stability of the OBs

makes them suitable application in e.g. for many food products, cosmetic, pharmaceutical.

For example, soybean OBs can be used in food products like dressings, sauces, dips,

beverages, and desserts. OBs can also be used as biocapsules for the encapsulation and

controlled delivery of functional components (Iwanaga, et al., 2007).

1.3. Mild separation pre-treatment techniques in food industry

Unfortunately for the food processing, nature does not provide materials of uniform

chemical and/or physical properties. Raw “materials” for foods have important physical

properties, which influence the separation technique to be selected. For example if there is a

difference in density, centrifugation could be applied as a separation technique. In the case

of proteins, usually solubility as physico-chemical property is used to separate them. This

could be done either by adding a solvent (one type of proteins is soluble in certain solvents,

the other not) or by heat supply (thermal denaturation).

7

Chapter 1

In general, physical separation techniques are defined as those operations which isolate

specific ingredients from a mixture without using a chemical reaction. The separations

usually aim to achieve removal of specific components, in order to increase the added value

of the products, which may be the residue, the extracted components or both. All

separations are based on exploiting the differences in physical and chemical properties of

specific components. The main bottleneck is to separate different fractions without

destabilization of one or more of the product fractions. To be able to exploit the complete

raw material without destroying the cellular content, it is necessary to use mild conditions.

Novel techniques to overcome these bottlenecks should be applicable for a variety of end

products aiming to achieve sufficient quality at large quantities.

An example of a mild, non-invasive technique is pulsed electric field (PEF). PEF is

technique in which high electric field strengths are used for simultaneous cell wall and cell

membrane perforation. One of the constraints for using PEF as a cell-opening method is

that processing material has to contain at least 70 % of moisture. Since fresh tea leaves

contain 75 % of moisture, this was reason why PEF was proposed as cell-opening method

in the case of fresh tea leaves. Tea leaf cells contain very rigid cell wall which makes cell

disruption more energy demanding. Therefore, it is needed to first disrupt the cell

walls/membranes to release cell content after which the polyphenols could be extracted.

Another mild technique is ultrasound. Ultrasound utilizes the process of cavitation to

disrupt the cell wall. Collapsing bubbles driven by bulk pressure variation due to ultrasonic

waves can cause cell and even molecule breakage (Alliger and Ciervo, 1975). In the

extraction of oil bodies from soybeans, an ultrasonic device for cell wall degradation was

used. Ultrasound is very low energy intensive technique compared to conventional cell

disruption techniques.

Degradation by enzymes is also a mild cell wall disruption method. Enzymes are not widely

used in industry because of the high costs of cell lysing enzymes. However, enzymes are

very selective in catalyst for cell wall degradation process. The performance depends on the

composition of the cell wall. Therefore, using enzymes is a mild and effective technique for

cell wall disruption. In a soy project we tested enzymes to degrade the strong cell wall of

soybean flour. To degrade such strong cell wall mechanically, a lot of energy is required.

Specific enzymes degrade specific cell wall compounds and weaken the cell wall so further

mechanical degradation can be carried out at a low energy demand. Moreover, the exact

composition of the cell wall is important to be able to select the proper (mixture) of

enzymes.

8

Introduction

1.4. Product Driven Process Synthesis (PDPS) methodology

In this work, the Product Driven Process Synthesis (PDPS) methodology proposed by

Bongers and Almeida-Rivera (2012) is used for conceptual process synthesis. The PDPS

methodology represents basically the extension of conventional process design taking also

product design into account. Design of processes for structured products (e.g. cosmetic

creams and lotions, margarine, and ice cream) is more difficult when using only

conventional process synthesis tools. Structured products have high added value and they

are often complex multi-phase materials where performance of the product is determined

by their microstructure (Bongers and Almeida-Rivera, 2009).

There are nine levels in the PDPS methodology, see Figure 1.6. It is relevant to mention

that the as the scope of the approach expands it becomes wider for multi-product

integration, scheduling and control (Bongers and Almeida-Rivera, 2012). PDPS has the

advantage that by decomposing the problem into a hierarchy of design levels of increasing

refinement, where complex and emerging decisions are made to proceed from one level to

another (Bongers and Almeida-Rivera, 2009).

9

Chapter 1

Figure 1.6. Product Driven Process Synthesis methodology (Bongers and Almeida-Rivera, 2009)

1.5. Objectives

The objective of the work presented in the thesis is to design processes for isolation of key

components from fresh tea leaves and soybeans in a mild way with acceptable process costs

and a suitable product quality/purity. Processes to be designed need to satisfy specific

10

Introduction

demands in the food industry. Only food grade solvents and materials can be used, due to

the fact that end products will be used as food additives. Processes have to be hygienic and

environmentally friendly.

In the thesis, the PDPS methodology has been used as structured approach in order to

deliver the appropriate processing routes for both raw materials: fresh tea leaves and

soybeans. The PDPS methodology is fed by consumer’s preference studies using House of

Quality tool to weigh and rank them. In the scoping stage of PDPS more effort is put in the

process synthesis by selecting appropriate fundamental tasks that can convert raw material

into desired product. Using “heuristics” for decision making, the number of feasible and

possible process alternatives has been reduced. At the end the outcome of the PDPS is how

the new optimal flowsheet is able to realize the production of the desired product cost

effectively under mild process conditions.

1.6. Outline

In the thesis two raw materials: fresh tea leaves and soybeans are considered. Chapters 2

and 3 cover the fundamental aspects and design of the process for extraction of polyphenols

from tea leaves, respectively.

In Chapter 2, the pulsed electric field (PEF) technique is used as a non-invasive method for

opening the cell structure and extraction of polyphenols (PPs). Upon the PEF treatment,

subsequent extraction of PPs occurred. The disintegration of the cellular membrane is

detected indirectly by a total PPs content measurement. The exact mechanism of electric

field applied on leaf tissue to increase permeability is explained based on collected

experimental results. Parameters such as total energy input and electric resistance are

obtained in order to (better) understand and to evaluate mechanism that takes place in the

cellular membrane under exposure of external electric field (Soliva-Fortuny, et al. 2009;

Leong, et al., 2014)

Chapter 3 describes the Product Driven Process Synthesis (PDPS) methodology is applied

for the conceptual design of an extraction process for polyphenols from fresh tea leaves. To

define operating window for PEF mechanism, a design of experiments (DoE) has been

setup and executed. Three factors that influence extraction yield have been studied: electric

field strength, pulse duration and number of pulses. DoE is used to determine which factors

or interactions between factors significantly influence the extraction yield. Optimization is

performed to maximize extraction yield of PPs.

Chapters 4 and 5 report physical background for extraction of oil bodies from soybeans and

conceptual process design, respectively.

11

Chapter 1

In Chapter 4 the result of several lab-scale aqueous extraction processes (AEP) have been

reported for the isolation of intact oil bodies (OBs). First, simple AEP has been performed

on two different flours (coarse and fine) to determine effect of the particle size on OBs

extraction. Second, the soy flour with larger particle size is pretreated with a commercial

enzyme (E), and with ultrasonication (U) during a specific period. These pretreatments are

applied to investigate whether the mass transfer of the cellular components increased,

comparing to a benchmark (no pretreatment) AEP.

Design of the soy process by applying the PDPS has been explained and described in

Chapter 5. In the first part of PDPS, product design was defined taking into consideration

consumer wants. A House of Quality diagram is used to weigh and rank consumer wants.

This led to different product ideas being either food additive (intact OBs can be used as

natural antioxidants) or cosmetics (face/hand creams). Based on the product application,

two process alternatives were generated which were not obvious. Feasibility of these

alternatives was confirmed experimentally. Economic evaluation of conventional process

and proposed alternatives are calculated.

Finally, Chapter 6 summarizes the major conclusions and findings of this PhD project.

Furthermore, an outlook for the future work is presented.

1.7. References

Asavasanti, S., Ersus, S., Ristenpart, W., Stroeve, P., & Barrett, D. M. (2010). Critical

electric field strengths of onion tissues treated by pulsed electric fields. Journal of

Food Science, 75(7), E433–43.

Bhatla, S. C., Kaushik, V., & Yadav, M. K. (2010). Use of oil bodies and oleosins in

recombinant protein production and other biotechnological applications.

Biotechnology Advances, 28(3), 293–300.

Bongers, P. M. M., & Almeida-Rivera, C. (2009). 19th European Symposium on Computer

Aided Process Engineering. Computer Aided Chemical Engineering (Vol. 26, pp.

231–236). Elsevier.

Bongers, P. M. M., & Almeida-Rivera, C. (2012). 11th International Symposium on

Process Systems Engineering. Computer Aided Chemical Engineering (Vol. 31, pp.


Campbell, K. a., & Glatz, C. E. (2009). Mechanisms of aqueous extraction of soybean oil.

Journal of Agricultural and Food Chemistry, 57(22), 10904–10912.

doi:10.1021/jf902298a

12

Introduction

Canatella, P. J., Karr, J. F., Petros, J. A., & Prausnitz, M. R. (2001). Quantitative study of

electroporation-mediated molecular uptake and cell viability. Biophysical Journal,

80(2), 755–64.

Cussler, E.L. and Moggridge, G. D. (2011). Chemical Product Design (Second edi.). New

York: Cambridge

Edwards, M. F. (2006). Product Engineering. Chemical Engineering Research and Design,

84(4), 255–260.

Haberl, S., Miklavcic, D., Sersa, G., Frey, W., & Rubinsky, B. (2013). Cell membrane

electroporation-Part 2: the applications. IEEE Electrical Insulation Magazine, 29(1),

29–37.

Huisman, M. M. H., Schols, H. A., & Voragen, A. G. J. (1999). Enzymatic degradation of

cell wall polysaccharides from soybean meal. Carbohydrate Polymers, 38(4), 299–

307.

Iwanaga, D., Gray, D., & Fisk, I. (2007). Extraction and characterization of oil bodies from

soy beans: a natural source of pre-emulsified soybean oil. Journal of Agricultural …,

8711–8716.

Jung, S. (2009). Aqueous Extraction of Oil and Protein From Soybean and Lupin: a

Comparative Study. Journal of Food Processing and Preservation, 33(4), 547–559.

Kapchie, V. N., Towa, L. T., Hauck, C. C., & Murphy, P. a. (2011). Recovery and

Functional Properties of Soy Storage Proteins from Lab- and Pilot-Plant Scale

Oleosome Production. Journal of the American Oil Chemists’ Society, 89(5), 947–

956.

Lebovka, N. I., Bazhal, M. I., & Vorobiev, E. (2000). Simulation and experimental

investigation of food material breakage using pulsed electric field treatment. Journal

of Food Engineering, 44(4), 213–223.

Lebovka, N. I., Shynkaryk, M. V., El-Belghiti, K., Benjelloun, H., & Vorobiev, E. (2007).

Plasmolysis of sugarbeet: Pulsed electric fields and thermal treatment. Journal of

Food Engineering, 80(2), 639–644.

Li, Z., Huang, D., Tang, Z., & Deng, C. (2010). Microwave-assisted extraction followed by

CE for determination of catechin and epicatechin in green tea. Journal of Separation

Science, 33(8), 1079–84.

Liu, F., & Tang, C.-H. (2013). Soy protein nanoparticle aggregates as pickering stabilizers

for oil-in-water emulsions. Journal of Agricultural and Food Chemistry, 61(37),

8888–98.

13

Chapter 1

Moggridge, G. D., & Cussler, E. L. (2000). An Introduction to Chemical Product Design.

Chemical Engineering Research and Design, 78(1), 5–11.

Monsanto, M., Trifunovic, O., Bongers, P., Meuldijk, J., & Zondervan, E. (2014). Black tea

cream effect on polyphenols optimization using statistical analysis. Computers &

Chemical Engineering, 66, 12–21.

Montgomery, D. (2013). Design and Analysis of Experiments (8th ed.). New York: wiley.

Murphy, D. J. (1993). Structure, function and biogenesis of storage lipid bodies and

oleosins in plants. Progress in Lipid Research, 32(3), 247–280.

Nikiforidis, C. V, & Kiosseoglou, V. (2009). Aqueous extraction of oil bodies from maize

germ (Zea mays) and characterization of the resulting natural oil-in-water emulsion.


Ouhida, I., Pérez, J., & Gasa, J. (2002). Soybean (Glycine max) cell wall composition and

availability to feed enzymes. Journal of Agricultural and Food

Perva-Uzunalić, A., Škerget, M., Knez, Ž., Weinreich, B., Otto, F., & Grüner, S. (2006).

Extraction of active ingredients from green tea (Camellia sinensis): Extraction

efficiency of major catechins and caffeine. Food Chemistry, 96(4), 597–605. 15

Rosenthal, a., Pyle, D. L., & Niranjan, K. (1996). Aqueous and enzymatic processes for

edible oil extraction. Enzyme and Microbial Technology, 19(6), 402–420.

Rosenthal, A., Pyle, D. ., Niranjan, K., Gilmour, S., & Trinca, L. (2001). Combined effect

of operational variables and enzyme activity on aqueous enzymatic extraction of oil

and protein from soybean. Enzyme and Microbial Technology, 28(6), 499–509.

Ruan, J., Haerdter, R., & Gerendás, J. (2010). Impact of nitrogen supply on carbon/nitrogen

allocation: a case study on amino acids and catechins in green tea [Camellia sinensis

(L.) O. Kuntze] plants. Plant Biology (Stuttgart, Germany), 12(5), 724–34.

Salunkhe, D.K., Chavan, J.K., Adsule, R.N. & Kadam, S. S. (n.d.). World Oilseeds.

Chemistry, Technology and Utilization. New York: Van Nostrum Reinhold.

Shirsath, S. R., Sonawane, S. H., & Gogate, P. R. (2012). Intensification of extraction of

natural products using ultrasonic irradiations—A review of current status. Chemical

Engineering and Processing: Process Intensification, 53, 10–23.

Soliva-Fortuny, R., Balasa, A., Knorr, D., & Martín-Belloso, O. (2009). Effects of pulsed

electric fields on bioactive compounds in foods: a review. Trends in Food Science &

Technology, 20(11-12), 544–556.

14

Introduction

Tzen, J. T. (1992). Surface structure and properties of plant seed oil bodies. The Journal of

Cell Biology, 117(2), 327–335. 7

Weaver, J. C. (2000). Electroporation of cells and tissues. IEEE Transactions on Plasma

Science, 28(1), 24–33. doi:10.1109/27.842820

Wilczek, M., Bertling, J., & Hintemann, D. (2004). Optimised technologies for cryogenic

grinding. International Journal of Mineral Processing, 74, S425–S434.

Yarmush, M. L., Golberg, A., Serša, G., Kotnik, T., & Miklavčič, D. (2014).

Electroporation-based technologies for medicine: principles, applications, and

challenges. Annual Review of Biomedical Engineering, 16, 295–320

15

Chapter 2

Chapter 2

A study of mechanism involved during polyphenol

extraction from fresh tea leaves by pulsed electric field

ABSTRACT

The major interest in pulsed electric field (PEF) treatment of biological tissues is derived

from its non-thermal application: increasing cell permeability. This application has an

important implication in extraction of complex organic molecules. In this work, pulsed

electric field treatment is investigated as a mild (non-thermal) processing method for

opening the cell structure in fresh tea leaves. Pulsed electric field utilizes short-duration

high-voltage pulses for opening the cell structure by the process called electroporation.

Upon the treatment subsequent extraction of complex organic molecules, particularly

polyphenols occurs. The amount of extracted polyphenols (in this case the extraction yield)

has been determined as a function of electric field strength, duration and number of applied

pulses, as well as energy input per unit of mass of the sample. The results indicate that the

used conditions during the treatment increase in temperature didn’t exceed 10 oC. This

limited temperature rise provides a valid evidence that pulsed electric field (PEF)

processing is a non-thermal method applied under used conditions.

16

A study of mechanism involved during polyphenol extraction from fresh tea

leaves by pulsed electric field

2.1. Introduction

Recently, commercial interest in extraction of intracellular organic compounds and liquids

from cellular plant tissue using various “solid”-liquid extraction methods has been growing.

One of the factors influencing the extraction process is the degree of cell membrane

disintegration (Bazhal, et al., 2003). Various physical, chemical or biological treatments

damage of the cellular membrane. Pulsed electric field (PEF) technique is a non-thermal

processing method for heterogeneous food materials. Moreover, PEF is based on cell

transformation or rupture under exposure of an external electric field resulting in an

increase of the electrical conductivity and permeability of the cell membrane (Lebovka,et

al., 2000; Soliva-Fortuny, et al., 2009, (Haberl, et al., 2013). The application of electric

fields for a short duration of a few to several hundred microseconds is capable of inducing

cell membrane permeabilization through a phenomenon called “electroporation”

(Asavasanti, et al., 2011). The term electroporation is used to describe the phenomena that

accompany the exposure of cells to transmembrane electrical pulses (Weaver, 2000).

Applying an external electric field to the cells results in pore formation in the membrane.

Because pore formation is a dynamic process depending on the intensity of the PEF

treatment, electroporation can be reversible or irreversible. When induced pores are small

in comparison to the membrane area and if they are generated with PEF treatment of low

intensity the electric breakdown is reversible (Angersbach et al., 2000; Soliva-Fortuny, et

al., 2009). Increasing the intensity of the treatment by increasing the electric field strength

(E) and/or treatment time (t) (which considers the number of pulses and the pulse width

applied in the system) will result in the formation of large pores and reversible

permeabilization will turn into irreversible disruption of the cell membrane. The

irreversible permeabilization of the cell membrane in the plant tissue provides a wide range

of process applications where disruption of the cell membrane is required. Both reversible

and irreversible electroporation have found their application in different disciplines such as

biomedicine, biotechnology and environmental science see e.g. (Haberl, et al., 2013;

Yarmush, et al., 2014). In food processing currently intensive research has been done in

non-thermal preservation and sterilization by microbial inactivation (Wan, et al., 2009;

Monfort et al., 2010; Walkling-Ribeiro et al., 2011; Evrendilek, et al., 2013).

Electric field strength is an important factor that controls the efficiency of electroporation

of cellular tissue. Bazhal and authors (2003) presented a classification of the PEF modes as

low (E≤100-200 V/cm), moderate (E=300-1500 V/cm) and high (E>1500 V/cm). With a

low electric field strength, the treatment time should be longer for electroporation of the

cellular membranes. It has been found experimentally that the time needed for

electroporation of cellular membranes of the different biological tissues is inversely

proportional to the electric field strength (Bouzrara and Vorobiev, 2003).

17

Chapter 2

PEF processing of foods involves the application of short pulses (duration of micro- to

milliseconds) of high electric field intensity. The pulsed electric field application to the tea

leaves can result in increase of temperature (through ohmic heating) and electrically

stimulated damage of cell walls/membranes (through electroporation mechanism).

Therefore, in practice, it is difficult to separate two mechanisms (thermal and/or

electroporation mechanism) and to make conclusions about the real contribution of the

electric field to electroporation followed by transfer of polyphenols from the cell interior to

the surrounding liquid. By measuring the total amount of polyphenols (PPs) transferred it

was possible to monitor the process of pulse-induced membrane permeabilization.

Therefore, the objective of this work is to study the effect of operational parameters

(electric field strength, pulse duration and number of pulses) on extraction yield of

polyphenols. Total specific energy input (kJ/kg leaves) and temperature increment (oC) are

chosen as parameters to describe treatment intensity as non-thermal.

2.2. Experimental procedure

2.2.1. Composition of tea leaf

Fresh tea leaves from Kenya (Camellia Sinensis variety) were used. Tea leaf contains 30 %

of catechins, 2 % simple polyphenols (gallic acid), 3 % caffeine and the rest (proteins,

minerals, organic acids and carbohydrates). The composition is given as weight fraction (%

wt/wt) on dry mater. Catechins, gallic acid and caffeine concentrations have been measured

by HPLC.

2.2.2. Moisture content analysis

Fresh tea leaves were plucked one day before shipment to Europe (The Netherlands) and

they were stored at +5 oC until required. Before treatment, leaves were allowed to reach the

ambient temperature of approximately 20 o

C. To determine the moisture content, fresh

leaves were freeze dried and subsequently subjected to a hot-air oven at 105 o

C. Moisture

content was 75-80 wt %. Samples that were used for the moisture content analysis were

separated from the samples used for PEF treatment. For all experiments, thin slices of fresh

tea leaves were used (approximately 1 cm width).

18



2.2.3. Natural extraction without electrical treatment: “control”

experiments

For control experiments without electrical treatment, slices of fresh tea leaves

(untreated, m = 20 g) were placed into a cylindrical glass beaker. Distilled water (200 g)

was added at 20 °C, and then diffusion was studied. A careful agitation at 250 rpm was

provided. The concentrations of total polyphenols in water were measured after 20 min.

Using the Fourier number it is possible to determine the length of experiments in order to

reach the steady state. In that moment amount of extracted polyphenols is in equilibrium

with the rest of polyphenols in the spent leaves. This dimensionless number represents the

current time to reach the steady-state.

20

R

tDF d

(eq. 2.1)

– Diffusion coefficient (m2/s)

– Time (s)

– Particle radius (m)

When Fourier number reaches 1, steady-state is achieved. Time necessary for that is the

time needed for our experiments. Equilibrium can be presented with the following mass

balance. Letter “d” in subscript presents dispersed PPs (in spent leaves) and “c”, continuous

phase (water) in t=0 and t=∞.

)()( 0,,,0, cccddd ccVCcV (eq. 2.2)

– Volume (m3)

– Concentration (kg/m3)

2.2.4. Pulsed electric field treatments

Tea leaves samples were treated using pulsed electric field (PEF) equipment with batch

treatment configuration of the Nutri-Pulse NP110-60 System (IXL Netherlands B.V.)

which consists of a PEF treatment chamber and a high voltage generator. The batch

treatment chamber (100 mm length × 70 mm width × 50 mm height, 350 mL capacity)

consisted of two parallel stainless steel electrodes of 5 mm thickness separated by a

distance of 20 mm (see Figure 2.1a). A high voltage generator provided rectangular pulses

in the range of 0.1*10-3

-0.1 s with maximum voltage of 2.2 kV and maximum number of

19

Chapter 2

pulses 50. Samples were placed in the treatment chamber between the two stainless steel

electrodes filled with an sterile salt solution (Figure 2.1a). The conductivity of the sterile

salt solution was adjusted to correspond with the conductivity of the sample (σ=3.5

mS/cm). NaCl as a salt was used for preparation of the salt solution. After cutting, the

leaves were subjected to various PEF treatments. All experiments were carried out using

electric field strength (E) ranging from 0.1 to 1.1 kV/cm, pulse duration (PD) from 0.1*10-3

to 0.1 s, and number of pulses (N) from 10 to 50. The total treatment time was defined as

the product of the number of pulses and the pulse width applied in the system (Figure 2.1b).

Apart from the treatment time pause between two pulses (PBP) is the interval between two

pulses and represents the relaxation time.

(a) (b)

Figure 2.1. Experimental set up (lab scale). Scheme of PEF treatment chamber (a) and PEF pulse protocol (b).

The temperature was measured both at the inlet and outlet of the treatment chamber. In all

experiments, the increase of the temperature due to the treatment never exceeded 10 o

C. All

experiments were duplicated.

2.2.5. Specific energy input

The pulse shape (square wave bipolar) was monitored on-line with an oscilloscope (Model

RTM 2000) during the treatment. For a square-wave pulse, the specific energy input for

each PEF-treated sample was calculated based on Eq. (2.3). The total specific energy input

was calculated by multiplying the energy delivered per pulse with the number of pulses

applied into the system:

20



n t

spec

teratment

dttItUm

nW

0 0

)()( (eq.2.3)

Wspec is specific energy input (in kJ/kg). The energy per pulse (in kJ) is calculated from the

power of the pulse (Ppulse) multiplied by pulse duration (s). Ppulse is the result of output

voltage U(t) and the total electric current I(t) supplied to the sample on the basis of Ohm’s

Law. n is pulse number applied to the system (dimensionless) and m is the total weight of

sample (kg) charged to the treatment chamber for the PEF treatment applied.

2.2.6. Determination of extraction yield - measurement of total

polyphenols content

The disintegration of cellular membrane was detected indirectly by a total polyphenols

(PPs) content measurement. Based on the fact that the cellular membrane is ruptured,

transport of the cell material together with polyphenols occurred and the extraction yield is

defined as fractiont of extracted PPs. After treatment, samples were stored at ambient

temperature and left in the aqueous solution for 20 min (extraction time). Upon extraction,

leaves were separated from the aqueous solution. The amount of extracted PPs was

measured in the solution. The total amount of phenols was determined by direct reading of

the absorbance at 725 nm (SpectraMax 190 Absorbance Microplate Reader, USA) of

diluted samples 1/10 (v/v). The total amount of PPs was expressed as gallic acid

equivalents (GAE) by means of a corresponding calibration curve with standard

gallic acid. The extraction yield of PPs was calculated according to equation (eq.2.4):

𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑦𝑖𝑒𝑙𝑑 =𝑝𝑜𝑙𝑦𝑝ℎ𝑒𝑛𝑜𝑙𝑠 (𝑎𝑞𝑢𝑜𝑒𝑢𝑠 𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛)

𝑝𝑜𝑙𝑦𝑝ℎ𝑒𝑛𝑜𝑙𝑠 (𝑓𝑟𝑒𝑠ℎ 𝑡𝑒𝑎 𝑙𝑒𝑎𝑣𝑒𝑠). 100% (eq.2.4)

2.2.7. Statistical analysis

All experiments and measurements of characteristics were repeated at least twice. One-way

analysis of variance was used for statistical analysis of the data using the Statgraphics

Centurion XVI. For each analysis, significance level of 5 % was assumed. The error bars

presented in the figures correspond to the standard deviations.

21

Chapter 2

2.3. Results and discussion

Fresh tea leaves were subjected to pulsed electric field (PEF) treatments. Extraction of

polyphenols occurred due to pore formation and disintegration of cellular membrane.

Therefore, when PEF treated leaves were in contact with an aqueous solution after 20 min

of extraction time, color had changed in yellowish brown. This phenomenon occurs due to

the transport of cellular material into the surrounding aqueous solution and the reaction of

PPs catalyzed by the enzyme polyphenol oxidase (PPO). PPO is located in the cytoplasm of

the plant cells and PPs are in organelles called vacuoles. When PPO and PPs are brought

into contact, oxidized PPs are produced as result of enzymatic oxidation. The formation of

oxidized PPs was identified by visible observation: a change of color of the solution during

the oxidation reaction occurs. Further confirmation was conducted using UV

spectrophotometer analysis, where total PPs were determined by reading the absorbance at

725 nm.

2.3.1. Characterization of pulsed electric field process and electric

measurements

In the experiments performed, electrical measurements: voltage and current were reordered

for each PEF experiment at regular time intervals. Figure 2.2 shows typical recording of

voltage (V) and current (mA) using an oscilloscope.

Figure 2.2. Typical recording of voltage (blue dotted line) and current (red dotted line) during a PEF experiment

-100

0

100

200

300

400

500

600

0

500

1000

1500

2000

2500

-2.00E-04-1.00E-040.00E+001.00E-042.00E-043.00E-044.00E-045.00E-046.00E-04

Cu

rren

t, m

A

Volt

ag

e, V

Time, s

22



In addition, in the experiments carried out in this study next to the electrical measurements

(voltage and current), temperature and resistance were also monitored and recorded at

regular intervals during each experiment. Figure 2.3 shows a typical resistance and

temperature time history during a PEF experiment.

Figure 2.3. Typical recording of resistance (blue dotted line) and temperature (red dotted line) during a PEF

experiment

Consequently, it was necessary to record these parameters (temperature and resistance)

during each PEF experiment in order to obtain a better insight for proper evaluation of the

results. Although PEF was intended to be a non-thermal technique, a temperature rise was

present due to the electric current through in the liquid food (ohmic heating). The average

temperature rise (ΔT) in the sample can roughly be estimated. Table 2.1, collects the PEF

treatment conditions for tea samples as well as the treatment impact on the changes in

voltage, current and temperature.

Table 2.1. Summary of PEF treatment conditions for each PEF experiment and the treatment impact on the

changes in electrical parameters and temperature.

Pulse duration,

[10-3,s]

Number of

pulses, [-]

Specific energy

input, [kJ/kg]

Change in

temperature, oC

Low Electric field strength=0.1 kV/cm

0.1 30 0.9 0.1

50 10 1.4 0.3

50 30 4.0 0.9

21.10

21.30

21.50

21.70

21.90

0.00

2.00

4.00

6.00

8.00

10.00

0 5 10 15

Tem

per

atu

re,

C

Res

ista

nce

, Ω

Time, s

23

Chapter 2

100 30 4.0 1.0

Moderate Electric field strength=0.6 kV/cm

0.1 10 1.7 0.4

0.1 50 7.8 1.9

50 30 7.7 1.8

100 10 2.6 0.6

100 50 12.5 3.0

High Electric field strength=1.1 kV/cm

0.1 30 12.0 2.9

50 10 5.9 1.4

50 50 29.7 7.1

100 30 17.5 4.2

When tea leaves were exposed to different intensities of the pulsed electrical energy,

temperature was measured and calculated to evaluate the degree of cell permeabilization

and the effect of pulsed electric field (PEF) treatment. On average, the temperature of

untreated leaves before subjected to PEF treatment was 20oC. As summarized in Table 2.1,

the temperature increased with the increase in applied pulsed electrical energy at the same

level of the applied electric field strength. This increase of temperature is particularly

significant at 0.6 and 1.1 kV/cm for a number of pulses of 30 and 50. The temperature of

the sample with tea leaves after PEF treatment increased when the applied pulsed electrical

energy was intensified. The highest treatment temperature increase observed in this study

was 7.1 °C after PEF treatment, using pulsed electrical energy of 29.7 kg

kJat electric field

strength level of 1.1 kV/cm.

2.3.2. Effect of electric field strength on extraction yield of

polyphenols

Sale and Hamilton (1967) identified the electric field strength E and the total treatment time

(which considers the number of pulses and the pulse duration applied in the system) as the

main variables determining the efficiency of the PEF damage of the plant tissue. Higher

24



electric field strengths lead to a better damage efficiency (Canatella, et al., 2001; Toepfl, et

al., 2007). However, it was noticed that an optimal value of the electric field strength for

many vegetables and fruit tissue is within 300 to 500 V/cm.

Figure 2.4 presents experimental results for the extraction yield of PPs from fresh tea leaves

as a function of the electric field strengths for various pulse protocols: N=30, PD=0.05 s

and PBP(EXA)=0.5 s (protocol I); N=30, PD=0.05 s and PBP(EXB)=3 s (protocol II). The

only difference between protocol I and II is interval time between two pulse series, see

Figure 2.1b.

The extraction yield (EY) values of the samples subjected to both protocols increase with

increasing electric field strength. The PEF treatment accelerates the rate of the extraction of

PPs from fresh tea leaves to the surrounding liquid. This is in agreement with the behavior

observed for different fruit and vegetable tissues (Lebovka, 2009). Protocol I resulted in a

maximum value for the extraction yield of 27 % when the electric field strength is 0.9

kV/cm. However, when the interval between pulses is equal to 3 s an electric field of 1.1

kV/cm is needed to obtain the same extraction yield (protocol II).

Figure 2.4. Experimental results for extraction yield of polyphenols from fresh tea leaves vs electric field strength

at two pulse protocols: N=30, PD=0.05 s and PBP=0.5 s (protocol I) and N=30, PD=0.05 s and PBP=3 s

(protocol II). Protocol I is presented with dotted bars, and protocol II with grey squared lines. Displayed error

bars represent extraction yield values +/- standard experimental error. In all cases, a sample was taken 20 min

after the end of the PEF treatment and stored at -30 oC until the extracted amount of total PPs was analyzed. All

experiments were duplicated

For both protocols the same extraction yield was obtained, but at different electric field

strengths. When the interval between two pulse series (pause between pulses) is short

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0.1 0.4 0.6 0.9 1.1

Ex

tract

ion

yie

ld,

%

Electric field strength, kV/cm

25

Chapter 2

(protocol I), a moderate electric field seems to be sufficient to cause cell membrane rupture.

However, protocol II allows a longer relaxation time and a higher electric field is needed to

achieve an extraction yield of 27 %. So these results point to the rate of extraction that is

significantly dependent on the time interval between to pulse series. Also, a longer relation

time asks for higher electric fields to achieve the same extraction yield.

The variation in the electric field strength to obtain the same extraction yield between

protocol I and II can also be related to the ionic transport between the electrodes and

electrolysis and the tissue surface. Depending on the details of contact (geometry and size

of the samples, orientation of the leaf slices, etc.) as well as the composition of the samples

(bud leaf, 1st, 2

nd and 3

rd open leaf), electrolysis may give rise to different amounts of stable

ionic compounds which would result in an increase of conductivity and tissue

disintegration.

2.3.3. Effect of the total treatment time on the extraction yield of

polyphenols

The degree of disintegration strongly depends on the treatment time and the electric field

strength ( Lebovka, 2009). For long times of PEF treatment a smaller electric field is

required. Figure 2.5 presents experimental results for the extraction yield at different

treatment times for two electric field strengths 0.4 and 0.9 kV/cm, respectively.

Lebovka, et al. (2007) reported the effect of pulse duration on the efficiency of PEF-

treatment on sugar beet. Experiments showed that a longer pulse duration see Figure 2.1b

was more effective. This influence of pulse duration was particularly pronounced at

moderate electric field strength (E=0.3 kV/cm). This is partially in agreement with the

observation because the highest extraction yield of 27 % is obtained for moderate electric

field strength (E=0.4 kV/cm) and a treatment time of 2.5 s (Figure 2.5). However, almost

the same extraction yield (EY=26.6 %) is obtained for a higher electric field (E=0.9 kV/cm)

and a shorter treatment time of 1.5 s. When unfortunately the total treatment time was 5 s

(for both electric field strengths) the experiment could not be performed due to problems

with PEF unit itself (low conductivity was detected in the PEF chamber). A possible

explanation lies in Ohm’s law. Electrical resistance is the ratio of voltage over current by

Ohm’s law and conductivity is inversely proportional to resistance. Therefore, the

resistance of the treatment chamber is an important parameter since the maximum allowed

pulse current by the power switch is 600 mA. This means that at 4kV the minimum

resistance is 6 Ohm. If the resistance is lower than this the maximum pulse current of 600

26



mA will be exceeded and if this situation continues for more than 5 pulses the system will

automatically shut down to avoid damage to the high voltage switch. In this particular case,

treatment time was 5 s the total number of pulses (N=50) and the pulse duration (PD=0.1 s).

For the applied electric field strengths of 0.4 and 0.9 kV/cm, respectively, the critical

situation mentioned above is exceed and PEF equipment will shut down.

Figure 2.5. Experimental results for extraction yield of polyphenols from fresh tea leaves vs different treatment

times at different values of electric field strength 0.4 (blue dotted bars) and 0.9 dark dotted bars) kV/cm,

respectively for the fixed value of PBP=0.5 s. Displayed error bars represent extraction yield values +/- standard

experimental error (95 % confidence interval). In all cases, sample was taken 20 min after the end of PEF

treatment and stored at -30 oC until extracted amount of total PPs was analyzed. All experiments were duplicated.

Existing work mainly discusses the effects of pulse duration in the PEF induced

inactivation of different microorganisms. Some authors have demonstrated that inactivation

was more efficient at longer pulse duration (Belloso et al. 1997; Abram et al., 2003).

However, other reported little effect of the pulse duration on inactivation (Raso et al. 2000;

Manas et al. 2000; Sampedro et al. 2007). The effect of pulse duration seems to vary

depending on the electric field strength and a general relationship between PEF-treatment

protocols, type and quality of the soft tissue, contact parameters (geometry and size of the

samples and orientation of the leaf slices), and the resulting degree of material

disintegration requires more thorough study. A quantitative description of the performance

of PEF for extraction of key components from cellular material (e.g. PPs from fresh tea

leaves and proteins from sugar beet leaves) from first principle of chemistry and physics

0

5

10

15

20

25

30

35

40

0.005 0.75 1.25 1.5 2.5 5

Ex

tract

ion

yie

ld,

%

Treatment time, s

27

Chapter 2

cannot be given at the moment. Therefore, a model developed from statistical analysis of

the experimental results will be given in Chapter 3.

2.4. Conclusion

This study provides valid evidence that pulsed electric field (PEF) processing is non-

thermal method (depending on the used conditions) for extraction of polyphenols from

fresh tea leaves. Electric field strength as well as treatment time play an important role in

polyphenols extraction. Moreover, the efficiency of the PEF treatment was indirectly

connected to electric field effect i.e. the relaxation time after a series of pulses. Different

modes of PEF treatment (electric field strengths and total treatment times) were applied to

investigate their effect on the extraction of polyphenols from fresh tea leaves. The amount

of extracted polyphenols from the leaves into the aqueous media strongly depends on the

setting of PEF treatment. Protocol I (EXA) resulted in a maximum extraction yield of 27 %

when the electric field strength is 0.9 kV/cm. However, when the interval between pulses is

longer and equal to 3 s an electric field of 1.1 kV/cm is needed to obtain the same

extraction yield (protocol II-EXB).

The total treatment time was presented as the product of the number of pulses and pulse

width (duration). Experimental results demonstrated that longer pulses which means a

longer treatment time of 2.5 s were more effective for moderate electric field (E=0.4

kV/cm). Moreover, to achieve the same extraction yield of 27 % but with a shorter total

treatment time=1.5 s, a higher electric field (E=0.9 kV/cm) is required. Also a total

treatment time of 5 s (for both electric field strengths) the experiment was unfortunately not

possible due to limitation of the PEF unit.

2.5. References

Asavasanti, S., Ersus, S., Ristenpart, W., Stroeve, P., & Barrett, D. M. (2010). Critical

electric field strengths of onion tissues treated by pulsed electric fields. Journal of

Food Science, 75(7), E433–43.

Bair, C. W., Snyder, H. E., & Technology, F. (1980). , Electron Microscopy of Soybean-

Lipid Bodies Lipid Protein, (September), 279–282.

Bazhal, M. I., Ngadi, M. O., & Raghavan, V. G. S. (2003). Influence of Pulsed

Electroplasmolysis on the Porous Structure of Apple Tissue. Biosystems Engineering,

86(1), 51–57.

28



Ben Ammar, J., Lanoisellé, J.-L., Lebovka, N. I., Van Hecke, E., & Vorobiev, E. (2011).

Impact of a pulsed electric field on damage of plant tissues: effects of cell size and

tissue electrical conductivity. Journal of Food Science, 76(1), E90–7.

Bouzrara, H., & Vorobiev, E. (2003). Solid–liquid expression of cellular materials

enhanced by pulsed electric field. Chemical Engineering and Processing: Process

Intensification, 42(4), 249–257.



80(2), 755–64.

Evrendilek, G. A., Altuntas, J., Sangun, M. K., & Zhang, H. Q. (2013). Apricot Nectar

Processing by Pulsed Electric Fields. International Journal of Food Properties,

16(1), 216–227.

Gonzalez, M. E., & Barrett, D. M. (2010). Thermal, high pressure, and electric field

processing effects on plant cell membrane integrity and relevance to fruit and

vegetable quality. Journal of Food Science, 75(7), R121–30.



29–37.

Lebovka, N. (2009). Electrotechnologies for Extraction from Food Plants and

Biomaterials. New York, NY: Springer New York.

Lebovka, N. ., Bazhal, M. ., & Vorobiev, E. (2001). Pulsed electric field breakage of

cellular tissues: visualisation of percolative properties. Innovative Food Science &

Emerging Technologies, 2(2), 113–125.

Lebovka, N. ., Bazhal, M. ., & Vorobiev, E. (2002). Estimation of characteristic damage

time of food materials in pulsed-electric fields. Journal of Food Engineering, 54(4),

337–346.







Lee, K. J., & Lee, S. H. (2008). Extraction behavior of caffeine and EGCG from green and

black tea. Biotechnology and Bioprocess Engineering, 13(5), 646–649.

29

Chapter 2

Leong, S. Y., Richter, L.-K., Knorr, D., & Oey, I. (2014). Feasibility of using pulsed

electric field processing to inactivate enzymes and reduce the cutting force of carrot

(Daucus carota var. Nantes). Innovative Food Science & Emerging Technologies.

Leung, A., & Foster, S. (1980). Encyclopedia of common natural ingredients. (A. Y.

Leung, Ed.)Encyclopedia of Common Natural Ingredients used in Food Drugs and

Cosmetics (pp. 142–143). John Wiley & Sons,.

Monfort, S., Gayán, E., Saldaña, G., Puértolas, E., Condón, S., Raso, J., & Álvarez, I.

(2010). Inactivation of Salmonella Typhimurium and Staphylococcus aureus by

pulsed electric fields in liquid whole egg. Innovative Food Science & Emerging

Technologies, 11(2), 306–313. doi:10.1016/j.ifset.2009.11.007






efficiency of major catechins and caffeine. Food Chemistry, 96(4), 597–605.




Sale, A., & Hamilton, W. (1967). Effects of high electric fields on microorganismsI. Killing

of bacteria and yeasts. Biochimica et Biophysica Acta (BBA) - General Subjects,

148(3), 781–788.



Technology, 20(11-12), 544–556.

Stadnik, J., & Dolatowski, Z. J. (2011). Influence of sonication on Warner-Bratzler shear

force, colour and myoglobin of beef (m. semimembranosus). European Food

Research and Technology, 233(4), 553–559.

Toepfl, S., Heinz, V., & Knorr, D. (2007). High intensity pulsed electric fields applied for

food preservation. Chemical Engineering and Processing: Process Intensification,

46(6), 537–546.

Vilkhu, K., Mawson, R., Simons, L., & Bates, D. (2008). Applications and opportunities

for ultrasound assisted extraction in the food industry — A review. Innovative Food

Science & Emerging Technologies, 9(2), 161–169.

30



Walkling-Ribeiro, M., Rodríguez-González, O., Jayaram, S., & Griffiths, M. W. (2011).

Microbial inactivation and shelf life comparison of “cold” hurdle processing with

pulsed electric fields and microfiltration, and conventional thermal pasteurisation in

skim milk. International Journal of Food Microbiology, 144(3), 379–86.

Wan, J., Coventry, J., Swiergon, P., Sanguansri, P., & Versteeg, C. (2009). Advances in

innovative processing technologies for microbial inactivation and enhancement of

food safety – pulsed electric field and low-temperature plasma. Trends in Food

Science & Technology, 20(9), 414–424.

Wang, H., Provan, G. J., & Helliwell, K. (2003). HPLC determination of catechins in tea

leaves and tea extracts using relative response factors. Food Chemistry, 81(2), 307–

312.

Weaver, J. C. (2000). Electroporation of cells and tissues. IEEE Transactions on Plasma

Science, 28(1), 24–33.

Yarmush, M. L., Golberg, A., Serša, G., Kotnik, T., & Miklavčič, D. (2014).

Electroporation-based technologies for medicine: principles, applications, and

challenges. Annual Review of Biomedical Engineering, 16, 295–320.

Zhu, W.-L., Shi, H.-S., Wei, Y.-M., Wang, S.-J., Sun, C.-Y., Ding, Z.-B., & Lu, L. (2012).

Green tea polyphenols produce antidepressant-like effects in adult mice.

Pharmacological Research : The Official Journal of the Italian Pharmacological

Society, 65(1), 74–80.

31

Chapter 3

Chapter 3

Product-driven process synthesis for the extraction of

polyphenols from fresh tea leaves

ABSTRACT

Polyphenolics present in fresh tea leaves may reduce the risk of a variety of illnesses,

including cancer and coronary heart diseases. The usefulness of these polyphenols may be

extended by combining them with other consumer products such as food items and vitamin

supplements. However, during conventional tea processing that includes cutting, rolling,

and drying, the extraction step is missing. Therefore, there is a need for an alternative

process to isolate polyphenols under mild conditions. The Product-Driven Process

Synthesis methodology is used as a well-defined structured approach for the conceptual

design of an extraction process for polyphenols from fresh tea leaves. A detailed

specification of the starting material (fresh tea leaves) and product (polyphenols) leads to a

subsequent definition of fundamental tasks to convert our raw material into the desired

product. Among the different mechanisms and techniques that could be used to perform the

tasks under mild conditions, pulsed electric field has been selected as non-invasive and

non-thermal method for cell wall disruption. To define the operating window for pulsed

electric field method an experimental design has been defined and executed (varying

several settings of the pulsed electric field). From the collected data, the analysis of

variance has been used to determine which variables are significant i.e. electric field

strength, pulse duration and number of pulses. Box-Behnken design has been used as part

of statistical analysis to find optimal pulsed electric field settings to maximize the

extraction yield of polyphenols (extraction yield). With obtained optimum settings maximum

value of 32 % of extraction yield was achieved.

32

Product-driven process synthesis for the extraction of polyphenols from fresh

tea leaves

3.1. Introduction

Technological and scientific progress in food industry has been pushed towards extraction

of intracellular compounds and liquids from cellular plant tissue. The shift from

conventional processing of food plant material towards design of smart operation

techniques is made to explore a novel product range. Therefore, in the last ten years the link

between process design and the development of novel consumer products became

increasingly important, especially regarding to the design of processes for structured

products. These structured products have high added value and they are often complex

multi-phase materials (e.g. cosmetics creams and lotions, margarine, ice cream, etc.) see

e.g. Edwards (2006). The Product-Driven Process Synthesis (PDPS) methodology proposed

by Bongers and Almeida-Rivera (2012) connects product design with process synthesis.

The PDPS method comprises a multi-level decision hierarchy with increasing level of

complexity that helps the user in the development of new products and processes.

Table 3.1. General description of each level of PDPS approach (Bongers and Almeida-Rivera, 2009)

Level General description of each level

(0) Framing level

Description of the project background

(BOSCARD) and business context as well as

overall supply chain

(1) Consumer wants

Consumer wants are obtained in qualitative

descriptions consumer likings, focus groups,

interviews and translate them into quantifiable

product attributes

(2) Product ideas

Potential products that meet the consumer

wants are identified and mapped the

quantifiable product attributes onto the product

properties, which are measurable

(3) Input output level

Complete specification of the output is done.

Inputs (ingredients or raw materials) and the

descriptors of the output (e.g. microstructure)

are specified.

(4) Task network

Definition of the fundamental tasks needed to

convert input into output, taken from a cluster

of tasks and its subgroup is performed. Then, a

network is made from the selected tasks and

clusters.

33

Chapter 3

(5) Mechanism and operating

window

Mechanisms* that can perform tasks are

defined. And for every selected task, operating

window needs to be defined.

(6) Multiproduct integration

The outcomes of steps 3 –5 for the different

products are compared to look for overlap and

possibilities to combine the production.

(7) Equipment selection and

design

The operating units are selected taking into

consideration integration possibilities and

controllability.

(8) Multi product-equipment

integration

Multi-stage scheduling of the multiple

products is applied, including plant-wide

control.

* “Mechanisms” is the nomenclature used in the paper of Almeida and Bongers (2010)

In Table 3.1 hierarchy that starts at the framing level and ultimately leads to a complete

conceptual process design (including equipment design, process control and multi-product

equipment integration) is presented. Bongers and Almeida-Rivera (2009) explained the

complete hierarchy in detail.

This contribution will focus on opportunities for product design and process synthesis and

in the strategies towards novel molecular and functional products. In particular, we will use

the isolation of polyphenols from fresh tea leaves to illustrate the applicability and scope of

the PDPS methodology.

3.2. Framing level and product ideas

At the framing level, the background of the project, the business context and the potential

of polyphenols (PPs) as food additives are identified. Polyphenols present in fresh tea

leaves may reduce the risk of a variety of illnesses, including cancer and coronary heart

diseases. The usefulness of these polyphenols may be extended by combining them with

other consumer products such as food items and vitamin supplements. The presence of PPs

in fresh tea leaves is responsible for health benefits associated with green tea consumption.

PPs are now gaining significant attention from both technical and consumer point of view

due to potential health benefit. It has been reported that PPs may reduce risk of cancers,

cardiovascular diseases, dental decay, obesity, diabetes, and improvement in the immune

system (Wang et al., 2003).

34


tea leaves

Industrial tea extraction is mainly based on the maceration method (rolling) combined with

stirring, circulation, ultrasonic, microwave or enzymatic treatment (Perva-Uzunalić et al.,

2006; Lee and Lee, 2008; Zhu et al., 2012). These methods require large volumes of

solvent, high temperatures and lot energy. Extraction efficiencies are generally low.

However, during conventional tea processing that includes cutting, rolling, and drying, the

extraction step is missing. Moreover, process conditions are harsh for example, to destroy

the remaining enzymes and to reduce the moisture content in a leaf, high temperatures have

to be applied (above 80 oC). Therefore, there is a need for an alternative process for the

extraction of polyphenols under mild conditions. A novel alternative process has to be an

effective and green method that will allow extraction of polyphenols from fresh tea leaves.

3.3. Input/output level

At the input output level a complete specification of all exchange streams to the process

inputs (raw material(s)) and target output (product(s)) are identified. Fresh tea leaves

(input) contain approximately 75 wt % moisture and 25 wt % of total solids. PPs account

for approximately 30 % of dry weight of fresh tea leaves (Zhu et al., 2012). Fresh tea leaves

contain caffeine, polyphenols, polysaccharides, and necessary nutrients, such as proteins,

amino acids, lipids, and vitamins. Generally, some chemical components – free amino

acids, total tea polyphenols, and soluble sugars – are considered important indicators of tea

quality (Ruan et al., 2010).

The output of the process is a fraction of polyphenols. Green tea leaves contain low-

molecular-weight polyphenols consisting mainly of flavanol (flavan-3-ol) monomers,

which are referred to as catechins (see Figure 3.1, left). There are several isomers of this

compound: catechin, catechin gallate (CG), gallocatechin, gallocatechin gallate (GCG),

epicatechin, epicatechin gallate (ECG), epigallocatechin, and epigallocatechin gallate

(EGCG). Normally, 10–20 % of the catechins in green tea leaves are epigallocatechin and

EGCG. Black tea polyphenols are formed during the enzymatic oxidation of green tea

leaves. In green tea (non-oxidized leaves) mostly catechins are present, while in black tea

several types of polyphenols formed by enzymatic polymerization of catechins, including

theaflavins can be found (Figure 3.1, right).

35

Chapter 3

Figure 3.1: Catechins structure (left) and theaflavin structure (right) (Monsanto et al., 2014)

The performance of input-output level is assessed by simple economic analysis, which

basically estimates economic potential of the process. The difference between product

revenue and raw material costs is computed on a year basis for 1 ton/hr. To estimate the

economic potential (EP) (Cussler and Moggridge 2011) of the proposed process the

following equation was applied:

EP=Product revenues-Raw material cost

𝐸𝑃 = ∑ 𝐶𝑖 ∙ 𝐹𝑖 − ∑ 𝐶𝑗 ∙ 𝐹𝑗𝑗−𝑟𝑎𝑤 𝑚𝑎𝑡.𝑖−𝑝𝑟𝑜𝑑𝑢𝑐𝑡 eq. (3.1)

where Ci and Cj are the sales prices of the products i and the costs of the raw materials j,

respectively. F denotes the annual flow of products and raw materials. The input materials

for this estimation include the fresh tea leaves, water, and NaCl. NaCl as a salt was used for

preparation of the aqueous medium. As output, three different products are considered: pure

(unconverted) catechins, theaflavins (TF) and thearubigins (TR).TR and TF are oxidized

form of catechins. In Table 3.2 the raw materials and final products costs are collected in

detail. For the calculation of the EP, several assumptions are made. The capacity of the

plant is set at 1 ton/h of fresh tea leaves and 20 h/day, giving a final annual flow of 7300 t

of processed leaves. The mass balance obtained is considered as well as the composition

(dry-weight basis) of the output, since the price will depend on the purity of the product

(amount of catechins, and TF in the output).

36


tea leaves

Table 3.2. Raw materials and final product prices for economic potential

Materials Costs of the raw materials

Input

Fresh tea leavesa €263/ton

NaClb €50/ton

Waterc €1.25/m3

Sales prices of the products

Output

Catechins* €80/ton catechins

Theaflavins (TF)** €238/ton (TF)

Thearubgins (TR)f €119/ton (TR)

a Indexmundi; cEUROSTAT; *estimated price with price of commercial catechins standard (Sunphenon 90LB); **

estimated price with price of commercial theaflavins standard (TF60); f rough estimation

The economic potential for the process for extraction of PPs from fresh tea leaves is around

3 M€/year, which can be used to invest in equipment, facilities, cover operational costs,

labor costs, especially for the downstream processing (Table 3.3).

Table 3.3. Economic potential at input-output level for extraction of polyphenols from fresh tea leaves

M€/year

Cost of raw

materials

Sales prices of

products Economic Potential

2.3 5.23 2.93

37

Chapter 3

3.4. Task network

The next step in the methodology is to identify the fundamental tasks that are needed to

convert the input into the desired output. i.e. determination of the task network . The aim is

to isolate PPs from fresh tea leaves originally present inside organelle (vacuole) in the cells.

To make the polyphenols accessible the following tasks need to be executed (reference

code is included for the sake of simplicity), see also Table 3.4:

1. Size reduction of leaves (C2)

2. Cell wall disruption (C3)

3. Separation of a system into two systems with different composition (G1)

4. Physical/biological stabilization (J1)

These fundamental tasks are the critical and essential tasks based on the requirement to be

obeyed to obtain the desired final properties of the product. These four tasks (size

reduction, cell wall disruption, separation task and biological stabilization) can be

combined leading to 24 (4!=24) different processing routes. Two feasible task networks can

be formulated. Figures 3.2.1 and 3.2.2 depict our proposed task networks alternatives.

C2Size

reduction

C3Cell wall

disruption

G1Extraction of

PPs

J1Physical/chemical

stability

Figure 3.2.1: Feasible task network route 1

C2Size

reduction

C3Cell wall

disruption

G1Extraction of

PPs

J1Physical/chemical

stability

Figure 3.2.2: Feasible task network route 2

The major difference between the two proposed task networks is order of tasks. Task

network route 1 starts with C2: size reduction. However, task network 2 starts directly with

cell wall disruption step (C3). Both routes are possible and feasible due to the fact that tea

leaves tissue is soft tissue containing approximately 75 % wt/wt moisture.

For every task, there are different “mechanisms” that could be used to perform task. In

Table 3.4 all possible mechanisms for execution of these tasks are presented. Heuristics,

38


tea leaves

domain knowledge and project constraints to use mild conditions (i.e. exclusion of organic

solvents, avoiding high temperatures, extreme pH values: strong acidic or alkaline

conditions) are used to eliminate several “mechanisms” and hence reducing the number of

potential alternatives for process synthesis.

Table 3.4: Fundamental tasks and mechanisms

Steps Fundamental task* Mechanisms*

Size reduction of leaves C2

C21: attrition

C22: impact

C23: ultrasound

C24: cutting

C25: enzymes

Cell wall disruption C3

C31: internal cell phase change

C32: electro-magnetic fields

(PEF, ultrasound)

C33: shear

C34: enzymes

C35: chemical

Extraction of PPs G1

G11: molecular size

G12: particle size

G13: electrical charge

G14: solubility

G15: chemical affinity

G16: chemical reaction

G17: (vapour) pressure

G18: gravity

G19: molecular size and

electrical charge

G20: shear

Physical/chemical

stabilization J1 J11: freezing

39

Chapter 3

J12: cooling

* “Mechanisms” is the nomenclature used in the paper of Almeida and Bongers (2010)

All possible combinations result in more than 100 routes that could be followed for

isolation of polyphenols from tea leaves. As this number of alternatives is far from

manageable a further simplification has been proposed for the network based on the

following engineering-driven heuristics (H) and project constraints:

H1: Mechanisms C21, C22, C23 and C25 are not considered because fresh tea leaves and

components inside during processing would be damaged. Only mechanism C24 remains.

H2: C32 ultrasound mechanism for cell wall disruption has not been considered due to

effects of cavitation.

H3: C33, C34, and G20 have been excluded due to the project constraints (i.e. no harsh

conditions).

H4: C35, G15 and G16 have been excluded because of environmental reasons. This project

aims at isolating PPs from fresh tea leaves under mild conditions, and without the use of

chemicals. Furthermore, PPs will be used in the food industry and these compounds have to

be approved by obeying strict law regulations.

H5: G12 has not been considered because PPs are molecules, not particles.

H6: J12 is rejected because PPs (as a final product) have to be stored at -18 oC to avoid

contamination of the product. Therefore, only freezing is applicable.

Applying these heuristics reduce the number of possible and feasible mechanisms. The

selected mechanisms are identified and presented in Table 3.5.

40


tea leaves

Table 3.5: Selected tasks and mechanism

Fundamental task Mechanisms

C2

C24: cutting

C3 C32: electro-magnetic

fields- pulsed electric field

G1

G11: molecular size

G13:electrical charge

G14: solubility

G19: molecular size and

electrical charge

J1 J11: freezing

All mechanisms listed in Table 3.5 are experimentally tested. In the cell wall disruption

step, pulsed electric field (PEF) has been selected as a promising technique, because PEF is

a non-thermal and non-invasive method. Two feasible task networks can be formulated on

the basis of the appropriate mechanisms. Figures 3.3.1 and 3.3.2 depict our proposed task

networks alternatives.

41

Chapter 3

Figure 3.3.1: Proposed task network alternative 1. Codes in the scheme are given in Table 3.5

Figure 3.3.2: Proposed task network alternative 2. Codes in the scheme are given in Table 3.5

After first set of preliminary experiments and testing both alternatives, conclusion was that

alternative 1 was favorable. As a consequence of PEF exposure (mechanism C32), tea

tissue get perforated and transport of cellular material occurred. If however, after PEF

cutting is performed, there is a leakage cellular material. Therefore, alternative 1 has been

selected for further study.

PEF processing of foods involves the application of short pulses (duration of micro- to

milliseconds) with a high electric field intensity inducing cell membrane permeabilization

42


tea leaves

through a phenomenon called “electroporation” (Asavasanti et al., 2011)(Asavasanti, Ersus,

Ristenpart, Stroeve, & Barrett, 2010)(Asavasanti, Ersus, Ristenpart, Stroeve, & Barrett,

2010)(Asavasanti, Ersus, Ristenpart, Stroeve, & Barrett, 2010)(Asavasanti, Ersus,

Ristenpart, Stroeve, & Barrett, 2010). Term electroporation is used to describe the

phenomena that accompany the exposure of cells to transmembrane electrical pulses (Esser,

Smith, Gowrishankar, Vasilkoski, & Weaver, 2010). In Figure 3.4 electroporation process

is presented. Biological membranes are bilayers composed of phospholipids that contain

proteins inserted within the lipid matrix (Gonzalez and Barrett, 2010). Applying an external

electric field to the plant cells results in pore formation on the membrane. Pore formation is

a dynamic process depending on the intensity of the PEF treatment; electroporation can be

reversible or irreversible.

Figure 3.4: Electroporation process of the cell membrane under external electric field exposure (Yang et al.,

2008)

In this work, tea leaves samples were treated using pulsed electric field (PEF) equipment

with batch treatment configuration of the Nutri-Pulse NP110-60 System (IXL Netherlands

B.V.) which consists of a PEF treatment chamber and a high voltage generator. High

voltage generator provided rectangular pulses (see Figure 3.5b) in the range of 0.0001-0.1 s

with maximum voltage of 2.2 kV and maximum number of pulses 50. Samples were placed

in the treatment chamber between two stainless steel electrodes filled with a sterile salt

solution (Figure 3.5a).

43

Chapter 3

(a) (b)

Figure 3.5: Experimental set up (lab scale). Scheme of pulsed electric field treatment chamber (a) and PEF

pulsing protocol (b)

PEF applied on fresh tea leaves (depending on the settings) causes opening the cell

structure and transport of cellular material from the interior to the surrounding liquid

occurs. By measuring the amount of PPs in the surrounding aqueous solution after PEF

treatment, it was possible to monitor the effect of pulsed electric field on opening the cell

structure. Note that here we assume cell opening under PEF exposure not thermal Tg effect.

3.5. Mechanism and operating window

For each mechanism the operating window has to be defined. Since all experiments were

performed on lab scale, for the first step, C24: “cutting” the leaves were cut manually (1 cm

width). The most critical step in the task network is cell wall disruption (C3: pulsed electric

field) and for this step an operating window has to be defined. Three factors that are

expected to have significant impact on the extraction yield (EY) are studied: electric field

strength (E), pulse duration or pulse width (PD), and number of pulses (N). EY is defined

as following eq. (3.2):

𝐸𝑌 (%) =Amount of extracted PPs in aqueous media

Total amount of PPs 𝑥 100% eq. (3.2)

Design of experiments technique has been used to elaborate the influence of E, PD and N

on the extraction yield.

44


tea leaves

3.5.1. Design of experiments

Design of experiments (DoE) as a systematic tool has been applied for statistical analysis

and optimization of applied electric field strength, pulse duration and number of pulses. For

these three variables a maximum (1), minimum (-1) and center point (middle, 0) has been

defined, see Table 3.6.

Table 3.6: Minimum, center point and maximum for selected influence factors for DoE

Factors A: Electric field

strength, kV/cm B: Pulse duration, s C: Number of pulses, #

Minimum (low) -1 -1 -1

Middle 0 0 0

Maximum

(high) 1 1 1

DoE has been employed to fully characterize the selected design space with a polynomial

model, with the objective to maximize the amount of extracted polyphenols, i.e. the

extraction yield (|EY). The resulting model can be used to optimize the response and can

also be extrapolated outside boundaries of the design space see Figure 3.6. Design space

has been defined between minimum (-1), and maximum (+1) for each variable A, B and C.

Black dots in between represent middle (0). Empty dot is center point (0, 0, 0).

45

Chapter 3

Figure 3.6: Design space for three selected independent variables A, B and C minimum (-1) and

maximum (1). Black dots in between represent middle (0). Empty dot is center point (0, 0, 0)

The ranges for the three selected independent variables (factors) i.e. the independent

variables: electric field strength (E), pulse duration or pulse width (PD), and number of

pulses (N) have been selected based on literature.

3.5.2. Variables (factors)

As mentioned before three independent variables (factors) are chosen for the DoE; A:

electric field strength (E), B: pulse duration (PD), and C: number of pulses (N). Besides

selecting these three independent variables it is also necessary to define the DoE design

space, by choosing the range for each variable. For each independent variable the range is

selected based on literature:

(A) electric field strength: for food plant material such as apple, potato and carrot

applied electric field strength was from 400 to 1000 V/cm to enhance extraction of

cellular material (Ben Ammar et al., 2011). Lebovka et al. (2000) used electric

field strength in the range from 200 to 700 V/cm for PEF treatment of potato, pear

and courgette to increase degree of cell damage. In the present paper PEF

treatment has been used to open the cell structure in fresh tea leaves. The range for

electric field strength has been chosen 100 and 1100 V/cm, based on the above

mentioned literature.

(B) pulse duration: De Vito and others (2007) investigated the effect of pulse durations

(i.e.10, 100, and 1000 μs) as well as different numbers of pulses applied on the

A

B

C

46


tea leaves

efficiency of the PEF treatment of sugar beet and apple tissues for electric field

strengths ranging from 100 to 400 V/cm. The same authors reported that samples

exposed to the same PEF treatment time showed noticeably higher disintegration

efficiency for the larger pulse durations. Pulse duration available for this study

from 0.1*10-3

till 0.1 s is selected. Reason for this was the limitation of PEF

equipment. Note that it was not possible to run the equipment at pulse duration

below 100 μs.

(C) number of pulses: Asavasanti et al. (2010) reported that with increasing the

number of pulses from 10 to 100 damage to onion tissue increased at constant

electric field strength 333 V/cm. Above 200 pulses, PEF treatment at E = 333

V/cm caused no significant change in degree of tissue damage, so damage reaches

its maximum limit. This result is in the line with conclusions from other studies

(Lebovka et al., 2001; Lebovka et al., 2002) which demonstrated that PEF has no

effect on membrane breakdown above certain maximum limit. Depending on the

applied electric field strength, the threshold of pulse number can be different. A

slight increase in electric field strength results in a dramatic decrease in number of

pulses required to get the same degree of tissue damage. For example, increasing

E from 200 to 267 V/cm can remarkably reduce the number of pulses from 100 to

10 pulses (Asavasanti et al., 2010). This observation suggests that higher field

strengths result in lower thresholds of pulse number suggesting that there is a

saturation threshold.

Range intervals for selected independent variables are summarized and presented in Table

3.7.

Table 3.7: Range interval for selected independent variables for DoE

Analysis and model fitting have been performed using the coded design variables (A, B and

C) and not design factors with their original units. When the original units are used, the

obtained numerical results in comparison to the coded unit analysis are different and not

Factors Electric field

strength, kV/cm A

Pulse

duration, s B

Number of

pulses, # C

Minimum

(low) 0.1 -1 0.1*10-3 -1 10 -1

Middle 0.6 0 0.05 0 30 0

Maximum

(high) 1.1 1 0.1 1 50 1

47

Chapter 3

easy to interpret (Montgomery, 2013). After defining ranges for selected independent

variables, in order to evaluate DoE objective maximizing the amount of extracted PPs in

aqueous phase, extraction yield (EY) of PPs is chosen response.

The experiments are generated using the StatGraphics ® Centurion XVI software. Note that

center point experiment has been carried out in triplicate, a total of 15 experiments are

collected in Table 3.8. The center points are providing information about the reproducibility

of the process. The experiments are generated in duplicates in a randomized way.

Table 3.8: Experimental design table generated using StatGraphics software

Experimental run Independent variables (factors)

A B C

1 1 -1 0

2 0 -1 -1

3 1 0 1

4 0 -1 1

5 1 0 -1

6 (center point) 0 0 0


8 -1 0 1


10 1 1 0

11 0 1 -1

12 -1 0 -1

13 0 1 1

14 -1 1 0

15 -1 -1 0

Since in this point it is not known whether the independent variables have linear or

nonlinear behavior, a response surface methodology (RSM) and a Box–Behnken design are

used for modeling and optimization of the operational values of E, PD and N. The RSM can

describe linear effects as well as nonlinear (quadratic effects). Statistical tests for

48


tea leaves

significance and the development of quadratic relationships that link the independent

variables to the responses, can be used to optimize the settings that maximize the extracted

amount of polyphenols. The objective of the RSM is to find the best expression for the

function f, while minimizing the number of experiments. The function EY is a polynomial

series that can be represented by eq. (3.3) (Montgomery, 2013):

𝑌 = 𝑏0 + 𝑏1𝐴 + 𝑏2𝐵 + 𝑏3𝐶 + 𝑏12𝐴𝐵 + 𝑏13𝐴𝐶 + 𝑏23𝐵𝐶 + 𝑏11𝐴2 + 𝑏22𝐵2 + 𝑏33𝐶2 + 𝜀

eq .(3.3)

where Y is response (predicted EY of PPs). A, B and C stand for the electric field strength

(E), pulse duration (PD) and number of pulses (N), respectively. b0 is a constant, b1, b2, and

b3 are linear coefficients, b12, b13, and b23 are cross product coefficients, b11, b22, and b33 are

quadratic coefficients and ε represents residuals. When two different letters appear

combined (e.g. AB, BC, . . .), they represent the interaction between two independent

variables. However, when the same letter appears twice (e.g. AA, BB, . . .) it represents a

second order effect for that variable. The observed responses EY are fitted to equation (3.3)

that represents the correlation with the independent variables. The selected RSM design is

the Box–Behnken design. The design consists of triplicated center points and set of points

lying at the midpoints of each edge of the multidimensional cube that defines operational

region (minimum and maximum value of each independent variable), (see Figure 3.5). The

experimental data were processed using the StatGraphics Software.

3.5.3. Statistical analysis

Statistical analysis is performed by using StatGraphics software and Box-Behnken design is

selected to determine optimal settings for three experimental independent variables. In

DoE, analysis of variance (ANOVA) is used to test the statistical significance by comparing

variation within replicated runs with the residual (model error) variation. To test the

significance of the variability in the responses, for each of the selected effects, the ANOVA

procedure calculates the variation ratio (F-ratio). The F-ratio of F-test statistics is the ratio

of the explained-variance-per-degree-of-freedom-used to the unexplained-variance-per-

degree-of-freedom-unused. This ratio determines the significance of the effects under

investigation with respect to the variance of all the terms included in the error term, for a

chosen significance level (Montgomery, 2013; Monsanto et al., 2014). The development of

quadratic relationships that link the influence factors to the responses can be used to

optimize the operational variables, in this case to maximize the extraction yield of

polyphenols. The results are presented in Table 3.9 for a 5 % significance level.

49

Chapter 3

Table 3.9: Variance analysis results (F-ratio)

Source of variance Sum of squares F-ratio

A:electric field strength 380.33 116.7

B:pulse duration 50.552 15.52

C:number of pulses 13.599 4.180

AA 189.93 58.31

AB 0.6889 0.210

AC 40.322 12.38

BB 0.1545 0.05

BC 4.4310 1.36

CC 3.8761 1.19

Figure 3.7 presents the standardized Pareto chart. A Pareto chart allows visualization of the

statistically significant effects. In StatGraphics software statistically significant effects are

calculated using ANOVA procedure.

Figure 3.7: Standardized Pareto chart for selected response (extraction yield of PPs). Black bars represent

positive effect on the response and light color bars indicates an antagonistic effect on the response

The chart presented in Figure 3.7 displays the effects in decreasing order of significance. A

vertical line represents the border of statistical significance. In the Pareto chart the length of

each bar is proportional to the value of a t-statistic calculated for the corresponding effect.

Any bar crossing the vertical line is statistically significant at the selected significance level

50


tea leaves

(5 %). The black (plus) bars means that the effect has a positive effect on the response and

the light color (minus) bars represent a negative (antagonistic) effect. According to the

results collected in Figure 3.7, there are three statistically significant effects for the

extraction yield of PPs; electric field strength (A), second order effect of electric field

strength (AA) and pulse duration (B). The results also clearly show that electric field

strength has the strongest impact on response, i.e. the extraction yield.

Figure 3.8: Main effects plot for extraction yield of PPs (response) variation E for PD=0.005 s and N=30;

variation of PD for E=0.6 kV/cm and N=30; and variation N for E=0.6 kV/cm and PD=0.005 s

Figure 3.8 presents the main effects providing a clear representation of the linear and the

quadratic effect of each factor on the response. The lines indicate the estimated response

change with changing each variable from its low level to its high level, while keeping the

values of variables constant half way their lowest and highest value. Figure 3.8 clearly

shows that none of the factors has a completely linear influence on the extraction yield. All

effects have some curvature in the selected range, meaning that there are second order

effects.

For the selected response (extraction yield of PPs) a regression model has been developed

based on the influence of the independent variables. All regression coefficients have been

calculated, see eq. (3.4):

2001.005.1205.35818.062.16293.25075.059.4427.2346.18 CCBBCABAACBAEY

eq. (3.4)

51

Chapter 3

Moreover, a Parity plot for the response is used to show the fitting of the model with

experimental data. The results in Figure 3.9 show that regression model and experimental

data are in good agreement.

Figure 3.9: Parity plot for the response=extraction yield representing the results of regression model (equation

(3.4)) and the experimental data. In green rectangle, three center points are highlighted.

Figure 3.10: Residual plot representing the difference between results of experimental (measured)data and the

predicted (from regression model) data. In green rectangle, three center points are highlighted

Once a reasonable model has been fit, the residuals from the fit should be examined. In

general, a residual may be thought of as the difference between the observed value of EY

and the value predicted by the model: residual = experimental (measured) EY – predicted

(from regression model) EY. Residual plot is presented in Figure 3.10.

After generating the polynomial equation eq. (3.4) relating dependent and independent

variables, an optimization step was performed in order to maximize extraction yield (EY).

52


tea leaves

Optimization has been performed using concept of desirability function (Monsanto et al.,

2014). Desirability function is an established technique for the determination of the

optimum settings of input variables that can determine the optimum performance levels for

one or more responses. The desirability procedure involves two steps: (1) finding the levels

of the independent variables that simultaneously produce the most desirable predicted

responses for the dependent variables and (2) maximize the overall desirability with respect

to the controllable variables. In this particular case, there is one response (extraction yield

of PPs) to be maximized. The lower and upper limit values of the extraction yield are taken

from the Box–Behnken design levels. The optimization procedure was conducted under

these boundaries. Obtained result from numerical optimization provides optimal value of

extraction yield of 32.5 % that could be achieved for Eoptimal=1.1 kV/cm. PDoptimal=0.1*10-3

s and Noptimal=50 pulses. In Appendix I, detailed explanation how to solve optimization

problem is presented.

3.5.4. Response contour plots

The contour plots are used as the graphical representation to show interactions among three

variables (E, PD and N). Figure 3.11 presents the contour plots for each extraction yield

value obtained from the regression model. Because interactions between the variables are

taken into account in the model, the contour lines of constant extraction yield are

curved. It is desirable to operate in the region where extraction yield is between 30 and 35

%. The contour plots show that several combinations of E, PD and N could obey this

objective. In the Figure 3.11a (E versus PD and for fixed N=50) the extraction yield

increases with an increasing E and decreases with increasing of N reaching maximum of

32.5 % when E is 1.1 kV/cm and is 50 pulses. N versus E for fixed PD=0.1*10-3

s the

extraction yield increases with E and increases with N, reaching a maximum at N=50 and

E=1.1 kV/cm, see Figure 3.11b. On the other hand, at lower pulse duration, extraction yield

is higher which means that increasing pulse duration, extraction yield decreases (Figure

3.11c).

53

Chapter 3

(a) (b) (c)

Figure 3.11: Contour plot representing extraction yield of PPs versus: electric field strength (E) and pulse

duration (PD) for fixed number of pulses N=50 (a); electric field strength (E) and number of pulses for fixed

PD=0.0001s (b) and pulse duration (PD) and number of pulses (N) for fixed electric field strength 1.1 kV/cm (c).

Optimal value for EY is in the circle.

3.6. Conclusions

This chapter presents a sketch of a design methodology which extends the scope of

traditional process design to the molecular level. The extended scope introduces the use of

the product-driven process synthesis methodology for the conceptual design of polyphenols

extraction from fresh tea leaves. In the framing level and product ideas we discussed the

usefulness of polyphenols present in fresh tea leaves. A detailed specification of the input

(fresh tea leaves) and output (polyphenols) that leads to subsequent investigation of

fundamental tasks to convert raw material into the desired product is done. Two feasible

and possible tasks network routes have been proposed. Among the different mechanisms

that could be used to perform the tasks, pulsed electric field has been selected as a non-

invasive and non-thermal “mechanism” for cell wall disruption. To define an operating

window for pulsed electric field technique an experimental design has been setup and

executed (varying several settings of the pulsed electric field). From the collected

experimental data, the analysis of variance has been used to determine which variables i.e.

electric field strength, pulse duration and number of pulses as well as combinations are

significant. Box-Behnken design is used as part of the statistical analysis to find optimal

pulsed electric field settings to maximize the amount of extracted polyphenols. Within the

chosen design settings it has been found that the optimal pulsed electric field settings are:

1.1 kV/cm field strength, 0.1*10-3

s pulse duration and number of pulses 50. With obtained

optimum settings maximum value of 32.5 % of extraction yield was achieved.

54


tea leaves

3.7. References

Asavasanti, S., Ristenpart, W., Stroeve, P., & Barrett, D. M. (2011). Permeabilization of

plant tissues by monopolar pulsed electric fields: effect of frequency. Journal of Food

Science, 76(1), E98–111.

Bazhal, M. I., Ngadi, M. O., & Raghavan, V. G. S. (2003). Influence of Pulsed

Electroplasmolysis on the Porous Structure of Apple Tissue. Biosystems Engineering,

86(1), 51–57.

Ben Ammar, J., Lanoisellé, J.-L., Lebovka, N. I., Van Hecke, E., & Vorobiev, E. (2011).

Impact of a pulsed electric field on damage of plant tissues: effects of cell size and

tissue electrical conductivity. Journal of Food Science, 76(1), E90–7.






231–236).



195–199).






80(2), 755–64.

De Vito, F., Ferrari, G., I. Lebovka, N., V. Shynkaryk, N., & Vorobiev, E. (2007). Pulse

Duration and Efficiency of Soft Cellular Tissue Disintegration by Pulsed Electric

Fields. Food and Bioprocess Technology, 1(4), 307–313. doi:10.1007/s11947-007-

0017-y

Evrendilek, G. A., Altuntas, J., Sangun, M. K., & Zhang, H. Q. (2013). Apricot Nectar

Processing by Pulsed Electric Fields. International Journal of Food Properties,

16(1), 216–227.

55

Chapter 3

Gonzalez, M. E., & Barrett, D. M. (2010). Thermal, high pressure, and electric field

processing effects on plant cell membrane integrity and relevance to fruit and

vegetable quality. Journal of Food Science, 75(7), R121–30.



29–37.

Lamsal, B. P., & Johnson, L. A. (2007). Separating Oil from Aqueous Extraction Fractions

of Soybean. Journal of the American Oil Chemists’ Society, 84(8), 785–792.

Lebovka, N. (2009). Electrotechnologies for Extraction from Food Plants and

Biomaterials. New York, NY: Springer New York. doi:10.1007/978-0-387-79374-0

Lebovka, N. ., Bazhal, M. ., & Vorobiev, E. (2001). Pulsed electric field breakage of

cellular tissues: visualisation of percolative properties. Innovative Food Science &

Emerging Technologies, 2(2), 113–125.

Lebovka, N. ., Bazhal, M. ., & Vorobiev, E. (2002). Estimation of characteristic damage

time of food materials in pulsed-electric fields. Journal of Food Engineering, 54(4),

337–346.







Lee, K. J., & Lee, S. H. (2008). Extraction behavior of caffeine and EGCG from green and

black tea. Biotechnology and Bioprocess Engineering, 13(5), 646–649.

Leong, S. Y., Richter, L.-K., Knorr, D., & Oey, I. (2014). Feasibility of using pulsed

electric field processing to inactivate enzymes and reduce the cutting force of carrot

(Daucus carota var. Nantes). Innovative Food Science & Emerging Technologies.

Leung, A., & Foster, S. (1980). Encyclopedia of common natural ingredients. (A. Y.

Leung, Ed.)Encyclopedia of Common Natural Ingredients used in Food Drugs and

Cosmetics (pp. 142–143). John Wiley & Sons,.

Li, Z., Huang, D., Tang, Z., & Deng, C. (2010). Microwave-assisted extraction followed by

CE for determination of catechin and epicatechin in green tea. Journal of Separation

Science, 33(8), 1079–84.

56


tea leaves

Moggridge, G. D., & Cussler, E. L. (2000). An Introduction to Chemical Product Design.

Chemical Engineering Research and Design, 78(1), 5–11.

Monfort, S., Gayán, E., Saldaña, G., Puértolas, E., Condón, S., Raso, J., & Álvarez, I.

(2010). Inactivation of Salmonella Typhimurium and Staphylococcus aureus by

pulsed electric fields in liquid whole egg. Innovative Food Science & Emerging

Technologies, 11(2), 306–313.




Montgomery, D. (2013). Design and Analysis of Experiments (8th ed.). New York: wiley.







Sale, A., & Hamilton, W. (1967). Effects of high electric fields on microorganismsI. Killing

of bacteria and yeasts. Biochimica et Biophysica Acta (BBA) - General Subjects,

148(3), 781–788.








Technology, 20(11-12), 544–556.

Stadnik, J., & Dolatowski, Z. J. (2011). Influence of sonication on Warner-Bratzler shear

force, colour and myoglobin of beef (m. semimembranosus). European Food

Research and Technology, 233(4), 553–559.

Toepfl, S., Heinz, V., & Knorr, D. (2007). High intensity pulsed electric fields applied for

food preservation. Chemical Engineering and Processing: Process Intensification,

46(6), 537–546.

57

Chapter 3

Wan, J., Coventry, J., Swiergon, P., Sanguansri, P., & Versteeg, C. (2009). Advances in

innovative processing technologies for microbial inactivation and enhancement of

food safety – pulsed electric field and low-temperature plasma. Trends in Food

Science & Technology, 20(9), 414–424.

Wang, H., Provan, G. J., & Helliwell, K. (2003). HPLC determination of catechins in tea

leaves and tea extracts using relative response factors. Food Chemistry, 81(2), 307–

312.

59

Chapter 4

Chapter 4

Isolation of oil bodies from soybeans in a mild way:

definition of operating window for process design

ABSTRACT

In this work, experiments were performed in order to define operating windows for process

parameters for isolation of oil bodies from soybeans in a mild way. Aqueous extraction

process for simultaneous separation of oil bodies and proteins from soybean was tested. In

the first part, the effect of the particle size on the extraction of oil bodies with two different

grinding methods, to obtain one coarse flour (d90 300 µm) and one fine flour (d90 40 µm)

was studied. The extractability of the coarse flour was better compare to fine flour: oil

recoveries from the cream were very similar (23 % and 24.5 % of the total soybean oil),

and the protein extraction yield was higher for the coarse flour (48 % against 40 % of the

total protein). Second, to enhance extraction yield of protein and oil, three different

pretreatments were applied to aqueous extraction process. The pretreatments included

enzymatic hydrolysis, ultrasound and the combination of the two. We found that

pretreatment with ultrasound reduced the remaining insoluble fraction and increased the

amount of solids extracted into the aqueous phase. The combination of ultrasound and

enzymes resulted in the cream with the highest lipid-to-protein ratio of 10:1. Different

aqueous extraction process alternatives were compared with benchmark process (neither

enzymes nor ultrasound).

60

Isolation of oil bodies from soybeans in a mild way: definition of operating

window for process design

4.1. Introduction

Over the last 15 years, a growing interest in developing mild extraction processes for plant

materials has developed. The extraction of intact cellular components is a promising

method for obtaining high-added value products, with a reduced environmental impact.

Soybeans are an important crop worldwide, with a high nutritional value. However, this

value is not efficiently maintained by the current processing conditions. The goal is to

develop an extraction process able to efficiently retrieve intact oil bodies (OBs), native soy

proteins and fibers. Therefore, the need for effective extraction of biologically active

components from plants, without any loss of functionality and high purity, has resulted in

development of novel extraction processes (Shirsath, Sonawane, and Gogate, 2012). The

aqueous extraction process (AEP) is originally suggested as an alternative for the solvent

oil extraction process (Rosenthal et al. 1996). In AEP, water is used as an extracting

medium to remove oil as an emulsion or free oil, unlike organic solvents, which dissolve

the oil (Campbell and Glatz 2009). The AEP of oil can be improved by any treatment that

enhances the dissolution of these other water soluble components (mainly proteins), for

instance, by using enzymes or increasing the temperature (Rosenthal et al. 1996).

Intact OBs can be considered as a natural emulsion that, in situ, protects the lipids from

oxidation during storage (Kerry Alan Campbell, 2010). Moreover, OBs have the advantage

over solvent extracted oil that they required neither emulsifiers nor homogenization during

processing (Kapchie et al., 2011). The high stability of the OBs makes them suitable for

e.g. food, cosmetic, and pharmaceutical applications. OBs may also be interesting for

application in biobased micro capsules and delivery of functional components (Iwanaga et

al., 2007). Harsh process conditions in the current soy process destroy the OBs native

structure. In the present work, the first objective is to study the effect of the particle size of

the soybean flour on the aqueous extraction of OBs by applying mild conditions. Mild

conditions are defined as follows: only use food grade solvents, no extreme pH values (no

strong acidic or alkaline conditions), and mild temperatures (< 40oC). A simple AEP is

performed with two different particle size soy flours (coarse and fine). The yield of oil and

protein extracted from the flour is calculated and the stability of the cream is measured to

determine the integrity of the OBs (diameter is 0.2-0.5 µm). The second objective is to

study the effect of simultaneous enzymatic hydrolysis and ultrasonication of the soybean

flour on the performance of aqueous extraction of OBs. The soy flour is pretreated with a

commercial enzyme mixture, containing different types of cell-wall degrading enzymes,

and with ultrasonication during a specific period. These pretreatments are applied to

investigate whether the mass transfer of the cellular components increased, comparing to a

benchmark AEP. Therefore, based on the experimental results, operating window for

61

Chapter 4

process parameters (i.e. pH, temperature, enzyme, particle size etc.) will be defined and

later used for conceptual design of the process.

4.2. Materials and methods

4.2.1. Preparation of soybean flour

Flour A and B were made from the same soybeans. To prepare soy flour A soybeans were

milled on a Polymix© mill (Kinematica) at 2500 rpm with a screen of 2.0 mm. The full-fat

soybean flour (coarse) was classified using a Vibratory Sieve Shaker AS 200 digit (Retsch)

at a frequency of 70 kHz, with 1.0 mm, 500 µm, 250 µm and 125 µm sieves. The fraction

between 125-250 µm was used for the extraction process. The flour was stored in sealed

aluminum bags at 4 °C until it was used. Soy flour B was obtained by cryogenic milling on

a pilot-plant scale mill (fine flour). Cryogenically milled soy flour was made by placing the

beans in liquid nitrogen and grinding them using a Contraplex CW mill. The particle size

distribution of the different flours (A and B), measured with a Malvern Mastersizer

analyzer 2000, is shown in Figure 4.1. A double distribution was obtained for soy flour A

(fraction between 125 to 250 µm); 90 % of the particles had a particle size lower than 300

µm and around 65 % had a particle size lower than 100 µm. in Appendix D particle size

measurements are presented. Because some oil being extracted from the disrupted cells

(especially since the oil is in liquid state). Free oil caused particles to stick to each other,

and made the separation of the smallest particles (< 125 µm) very difficult. Flour B

presented a normal (Gaussian) distribution; 90 % of the particles had a particle size lower

than 40 µm. Taking into account that cotyledon cells are about 15-20 µm in diameter and

70-80 µm in length (Rosenthal et al. 1996), this results a high proportion of rupturing the

cells. It is important to note that the particle size distribution was measured on the wet

flour; therefore, the result reflects the size of the hydrated particles. This is the reason for

obtaining a higher particle size in flour A than the expected according to the used sieve

(250 µm).

62



Figure 4.1. Particle size distribution of the soybean flours used for the extraction process of oil bodies (A coarse

flour; B flour cryogenically milled fine flour)

4.2.2. Aqueous extraction of soybean oil bodies

OBs were physically isolated from soybean full-fat flour using an water-based flotation

centrifugation method. Soy flour was hydrated for 30 min at 4 °C in a sodium phosphate

buffer (0.1 M, pH=7.2), in a ratio of 1:6 (w/v). The slurry was mixed vigorously using a

high-speed vortex mixer for 1 min, and centrifuged (Sigma 6-16K) at 4700 rpm at 4 °C for

30 min. By the end of the centrifugation a cream fraction (OBs) on the top, a supernatant or

skim, and a residue on the bottom were obtained. The newly formed cream fraction

obtained after the aqueous-extraction was re-suspended with TRIS buffer (0.1 M, pH=8.6)

in a 1:2 solid-liquid weight ratio, and mixed vigorously to remove the storage (non-

oleosins) proteins from the cream. The mixture was centrifuged (4700 rpm at 4 °C for 15

min) to obtain a cream pad on top, a supernatant and a creamy residue at the bottom. The

cream was collected with a spatula; the supernatant was separated and stored at 4 °C for

63

Chapter 4

analysis, and the creamy residue was combined back again with the cream pad. This

“purified” cream was then re-suspended in TRIS buffer (0.1M, pH=7.2) in a 1:2 solid to

liquid weight ratio, before storage at 4 °C. All experiments were performed in duplicate.

4.2.3. Enzyme/ultrasound-assisted aqueous extraction

Detailed description of enzyme assisted and ultrasound extraction is presented in Appendix

A. Soybean flour was hydrated for 30 min at ambient temperature with a sodium phosphate

buffer (0.1 M, pH= 7.2, NaCl concentration 0.25 M), in a 1:6 solid to liquid weight ratio.

Different enzyme mixtures are tested and results are presented in Appendix B. The slurry

was mixed with enzyme solution (5 v/w%) (Ultrazyme AFP L, Novozymes) and placed in

an ultrasound bath (Elma TI-H-20) at 25 kHz (100 % power) at 40 °C for 3h (samples with

no ultrasound pretreatment were incubated in a Medline BS-21 water bath at 40 °C and 150

rpm). After the incubation period, the slurry was mixed vigorously with high speed mixer

for 1 min and centrifuge at 4700 rpm at 4 °C for 1 h. The cream phase was collected with a

spatula. The supernatant and residue fractions were mixed and centrifuged two times more

at 4700 rpm and 4 °C for 30 min. After the centrifugation cycles, all the cream phase was

washed with TRIS buffer (0.1 M, pH=8.6, NaCl concentration 0.25 M) in a 1:2 solid-liquid

weight ratio. This cream slurry was centrifuged again (4700 rpm at 4 °C for 15 min). The

supernatant was separated and re-centrifuged one more time. In this study, the top cream

and the bottom residue were kept separately, and stored at -18°C for further analysis. All

experiments were performed in duplicate.

4.2.4. Recoveries

The mass balances of oil and protein were determined for all procedures. Recoveries were

calculated as follows: protein and oil recovered from cream, supernatants and residues were

calculated as the percentage of total protein or oil present in the unprocessed soybean flour

(starting material). The protein content of the soy flour, residue, supernatant and cream

fraction was calculated by converting the nitrogen (N) content in the samples, using a

multiplication factor of 6.25. The N was determined by the Dumas method using the

Elementar Vario Max CNS Analyser. Glutamic acid was used as standard (N 9.52 %, C

40.72 %) and butter milk as a control (blank) sample. In Appendix C protein and lipid

recovery results from different aqueous extraction procedure are reported.

64



The oil content in the soy flour was determined by extraction with hexane using the Soxtec

System HT6 and 1043 Extraction Unit, according to the manufacture’s manual. Samples (5

g) were extracted with 50 ml of hexane (Program: 20 min under boiling, 40 min rinsing).

Solvent was dried under vacuum (~ 130 mbar, 40 °C), and the remaining fat weighted. The

oil content in the different fractions (cream, supernatant and residue) was determined using

a CEM SMART Trac System. Samples (1-2 g) were dried by microwave and the oil content

determined by Nuclear Magnetic Resonance, according to the manufacture’s manual. The

used method involved drying the sample at 110 °C until constant weight, before measuring

the oil content with NMR.

4.3.Results and discussion

4.3.1. Effect of particle size on the aqueous extraction of soybean oil

bodies

Two different full-fat soybean flours coarse (A-coarse and B-fine) with different levels of

grinding are used as starting material for the OBs extraction process. According to

Rosenthal et al. (1996) the critical step in aqueous extraction process is the grinding

operation, which determined the seed particle size. Efficient grinding which breaks down

the walls of cotyledon cells is essential to extract the cellular content. These two flours (A

and B) are subjected to the aqueous extraction process explained in the Materials &

Methods section. Table 4.1 shows the mass balance of the extraction process is presented.

Table 4.1. Mass balance of the aqueous extraction process of oil bodies from two different soy flours

Soy flour Amount (% w/w dry-weight basis)

Cream

Skim

Residue

A (coarse) 9.6 38.4 47.9

B (fine) 14.7 30.8 52.3

Assuming an ideal separation of the cellular components after extraction, the cream is

expected to consist of only OBs (20 % of the soybean), the skim contains the proteins and

65

Chapter 4

water soluble carbohydrates (~ 65 %), and the residue consists of the soybean fibers (~ 15

%). A bigger amount of cream is obtained from the soy flour B, while less solids are

present in the skim fraction. The higher amount of cream obtained from soy flour B could

be explained by the smaller particle size of the flour and a better extraction of cellular

contents. Although, a high amount of cream does not necessarily mean a higher amount of

OBs. Larger molecules, e.g. storage proteins are part of the emulsion and at the same time

they increase the cream yield. Demonstrated by Table 1 the simple extraction is not

efficient: there are still many soybean solids (~ 50 %) in the residue fraction. These solids

are still inside the cells, but according to the particle size of the flours (especially that of

soy flour B) most of the cells should be broken. On the other hand, extraction conditions

(mixing, temperature, osmotic pressure) are not favoring the transport of cell components to

the extraction medium. Temperature enhances the dissolution of water-soluble components

(e.g. proteins), thus, improving the extraction performance of the OBs from the cell matrix.

Therefore, maximum oil recoveries have occurred at temperatures where soy proteins

remain soluble (not denatured), normally between 40-60 °C (Lamsal & Johnson, 2007). To

keep mild conditions, no heating involved during the extraction process. The protein and oil

composition of the different fractions, as well as that of the starting material, is shown in

Table 4.2.

Table 4.2. Mass balance of the aqueous extraction process of oil bodies from two different soy flours

Treatment

Composition (% w/w dry-weight basis)

Soy flour Cream Skim Residue

Protein Oil Protein Oil Protein Oil Protein Oil

A (coarse) 40.4 21.6 25.4 68.9 47.2 N.D 28.3 18.3

B (fine) 42.4 21.1 33.0 42.2 48.4 N.D 29.8 15.9

The composition of the flours was within the range expected from literature (Salunkhe, et

al. 1992); differences were result of the different used soybean variety. Even though less

cream was obtained from the flour A compare to flour B, cream from flour A contained

almost 70 % of total oil content and 25 % of total proteins content on a dry-weight basis.

On the other hand, the cream from flour B had less lipids (42 %) but more proteins (33 %),

and sum of these two components together comprise 75 % of the total solids in this cream.

The ratio lipid-to-protein in the cream fraction A and B is 2.8 and 1.3, respectively.

According to Campbell and authors Campbell et al. (2010), oil-to-protein ratio in purified

66



OBs of 0.5 µm in diameter, containing an oleosin layer of 3.2 mg/m2,would be 20:1.

Therefore, more “impurities” were present in the cream from flour B. When transferred into

water, the OBs are accompanied by either organelles and/or water-soluble compounds,

including soluble carbohydrates and protein bodies that reduce their purity. The extracted

proteins interact with the surfaces of the OBs and form a secondary layer that impacts the

stability of the OBs (Nikiforidis and Kiosseoglou, 2009). Both creams obtained after the

AEP still contained other storage soy proteins as part of the emulsion.

Both flours (A and B) in the skim contained around 48 % of proteins and no oil were

detected. Separation from the cream phase was difficult and some residual cream was

observed in the skim phase. The detection limit of the used analysis method was not

significant to demonstrate the presence of highly diluted oil in the water phase. No

significant differences were found between the remaining residues of the two soy flours.

Both residues contained high amounts of “lost” lipids and proteins.

Figure 4.2. Protein and oil recovery from the soybean flours in each fraction after aqueous extraction process (A-

course flour, B-fine flour). Blue bars represent protein content, red bars represent oil content.

From the total amount of lipids present in the soybean, 24.5 % were retrieved in the

“purified” cream fraction from soy flour A, and 23 % from soy flour B. In both cases, most

67

Chapter 4

of the oil remained trapped in the residue fraction. The cream fraction from flour B

contained twice as much protein as the cream obtained from flour A. This confirms that the

higher amount of cream obtained for soy flour B was caused by more proteins present in

the emulsion, rather than more oil or OBs as compared with flour A. the extraction of

proteins to the skim fraction however was better for the soy flour A than the flour B.

according to the results collected in the Figure 4.2, 48 % and 40 % of the total proteins

present in the starting flour were retrieved in the skim fraction for soy flour A and soy flour

B, respectively. The residue form soy flour A remained with 44 % of oil and 36 % of the

soy proteins. The residue remaining from the soy flour B contained 43 % of the total oil and

42 % of the total proteins. Overall, from Figure 4.2 it can be observed that the extraction

yield of oil and specially proteins from the soy flour A was slightly higher than extraction

yield achieved with soy flour B. (Rosenthal and co-authors (1998) studied the effect of

particle size of flour on oil and protein aqueous extraction yield. They extracted flour with

mean particle sizes from 800 µm down to 150 µm and demonstrated that oil and protein

extraction yields were directly proportional to the inverse of flour particle size. This result

was attributed to cellular disruption enabling oil and protein release. However, according to

Campbell and Glatz (2009) the mechanism of oil mobility and release is also determined

by other factors, such as the matrix structure. The matrix structure is determined by the

native cellular geometry. The mode of cellular disruption used (e.g. kind of milling), and

the water solubility of the materials in the intercellular space (Campbell and Glatz 2009).

The fact that soy flour B was stored for a long period of time (2 years) had a negative effect

the cellular structure due to the aging. This could be responsible for the lower extractability

of the soy flour B, despite its smaller particle size. Looking at the total values for the AEP,

the lipid recovery was quite low. Between 66 and 68 % of the total lipids were recovered in

the different AEP fractions. The rest most probably remained in the skim fraction, because

the applied centrifugation speed and time were not sufficient to transfer those lipids to the

cream pad layer.

The particle size and micro structure of the cream fractions, obtained from the AEP, was

determined to demonstrate the presence of intact OBs. To obtain more information about

the microstructure of the creams, Confocal Scanning Laser Microscopy (CSLM) was used

to analyze the creams (Figure 4.3).

68



Figure 4.3. Confocal sections of the “purified” cream fraction extracted from soy flour B and stained with Nile

blue (bars=10 µm). Small individual green particles are intact oil bodies. Larger red particles are protein entities.

CSLM allows materials to be observed from different depths. The pictures in the Figure 4.3

show that particles are in the range of 10 µm, as expected from the particle size distribution

(PSD) measurements (data are not shown). However, it is possible to differentiate small

individual green particles (smaller than 1 µm). Explanation of aggregation of particles is the

presence of storage proteins (stained in red). Larger proteins have affinity (e.g. electrostatic

interactions) with the oleosin present in the OBs surface, making those aggregates.

Microscopic studies demonstrated that OBs have an apparent affinity to cell wall, bigger

protein and endoplasmic reticulum Campbell (2010). Also, it is important to consider that,

although the pH of the storage buffer was set at 7.2, where oleosins are expected to have a

negative charge, the pH was not controlled during the process. Note that OBs tend to

aggregate already at pH 6.8 Tzen (1992). Overall, the presence of small individual green

particles so close to each other provides an indication that the OBs were still intact. Free oil

droplets in a aqueous solution would tend to coalesce and form larger droplets. Light

microscopy image of one sample of soy flour A is presented in Appendix E.

OBs fill up the space between protein bodies in the cells, and are enclosed in a matrix of

cytoplasmic proteins (Campbell and Glatz, 2009). Therefore, OB-protein interactions play

an important role in the mechanism of OB release during the AEP. Conditions that favor

protein extraction i.e. temperature below the temperature of denaturation, pH different from

the isoelectric point, use of several extraction steps) generally favor OB mobility and

transfer. When it comes to the effect of the particle size of the flour on the extraction of

OBs and proteins, the obtained result was unexpected. The extraction of oil and proteins

from the soybean was a bit higher for the flour with the larger particle size. However, there

is a second factor that influenced obtained results. As already mentioned, the long storage

time of the cryogenically milled flour (~2 years old) could be responsible for its lower

extractability. Many physical and chemical changes may have occurred (i.e. denaturation)

during the storage period that could affect the solubility of the proteins and subsequently,

the extraction yield of the OBs. Above all, cryogenic milling demands high investment and

operational costs for the AEP, especially the infrastructure necessary to use and recycle

69

Chapter 4

liquid nitrogen (Wilczek, Bertling, & Hintemann, 2004). The utilization of less fine soy

flour and some process aids (i.e. ultrasonication of an aqueous suspension) to improve the

cell wall disruption and transfer of OBs might be a better alternative to improve the

extraction yields.

4.3.2. Enzymatic hydrolysis and ultrasonication of the coarse soy flour

on the aqueous extraction of OBs

It has been reported that the low extraction yields of aqueous processes can be improved by

e.g. using enzymes that hydrolyze the structural polysaccharides forming the cell wall of

oilseeds, or by application of ultrasonication that can increase the mass transfer rates and as

a consequence decrease the extraction times (Rosenthal et al. 2001; Shirsath et al. 2012). A

new AEP process, which included simultaneous enzymatic hydrolysis and ultrasound, was

applied to the coarse flour (earlier flour B). The particle size fraction between 125 and 250

µm was used for the extraction of OBs.

The new AEP involved the appropriate process temperature, the extraction buffers and the

soy flour B pretreatment. First, the process temperature was increased from room

temperature to 40 °C in this new AEP. Generally, higher temperatures are associated with

enhanced extraction. The mass transfer rate is favored by increased solute solubility and

diffusion into the bulk solvent. However, degradation of thermolabile components (i.e.

proteins) should be considered when working at high temperatures (Karki et al., 2012). For

AEP, (Domínguez, Núñez, & Lema, 1994) obtained a maximum oil yield in the extraction

of soybean at temperatures between 40-60 °C, while (Rosenthal et al. (2001) reported a

slight decrease in oil yield for temperatures above 50°C, which they attributed to protein

denaturation. Since the goal was to design a mild aqueous process to extract OBs from

soybean, and it is known that the OBs extraction yield is directly related to the protein

extractability, and extraction temperature of 40 °C was chosen.

Secondly, to improve the separation of exogenous proteins from the OBs cream fraction,

the ionic strength of the extraction buffers was increased to 250 mM NaCl. Interactions

between OBs surface proteins (oleosins) and exogenous proteins may include e.g.

electrostatic repulsions and van der Waals attraction forces, hydration effects, and hydrogen

bonding. When salt is used at low concentration, salt ions provide charge shielding or ion

binding on the charged proteins (Tsumoto, Ejima, Senczuk, Kita, & Arakawa, 2007). Salt

stabilizes proteins against dissociation and heat denaturation. Liu and Tang (2013) found

that increasing salt concentrations from 0.05 to 2.0 M affected the denaturation

70



temperature of the soy protein β-conglycinin to increase from 77 to 100 °C, and for the

protein glycinin to increase from 92 to 113 °C at pH=7.0.

Finally, two different pretreatments were done to the soy flour to improve the extraction of

OBs. The application of cell-wall degrading enzymes was done to break the cotyledon cell

and to make the structure more permeable (Rosenthal et al. 1996). The use of

cellulases/pectinases can potentially increase extraction yield and also allows the

simultaneous extraction of undenatured proteins (Kapchie et al., 2011). Moreover,

ultrasound was applied to increase the transport of elements through cellular membranes,

and extract cellular structures from cells damaged by cavitation (Vilkhu, Mawson, Simons,

& Bates, 2008). In terms of frequency, low frequencies (20-100 kHz) are recommended for

dominant physical effects of cavitation, so as to intensify the mass transfer rates (Shirsath et

al., 2012). The combination of ultrasound and enzyme-assisted extraction is a green

alternative that has shown a synergistic effect by increasing enzyme activity, decreasing the

processing time, thus improving the extraction performance in yield and time (Stadnik and

Dolatowski 2011; Easson et al. 2011). The inaccessibility of the enzymes to their substrate

has been a problem when trying to degrade soybean cell walls (Huisman et al. 1999;

Ouhida et al. 2002). Ultrasound cavitation can enhance enzyme efficiency by improving the

dispersion of the enzymes and opening-up the structure, thus facilitating transport of the

enzyme molecules to the substrate surface (Stadnik and Dolatowski 2011). For this specific

study, the commercial enzyme Ultrazyme AFL P was used simultaneously with

ultrasonication of 25kHz. This enzyme ingredient was chosen after considering its

cellulose, pectinase and xyloglucanase activities (data presented in Appendix E).

Table 4.3 shows demonstrate the mass balances obtained for the different experiments.

Table 4.3. Mass balance of the three main fractions obtained after the new AEP of OBs from soy flour

Treatment Mass balance** (% dry-weight basis)

Cream Skim Residue

Benchmark 17.0 53.0 29.9

E 15.1 57.2 27.4

U 14.3 58.7 27.0

EU 13.5 60.5 26.1

*Benchmark no pretreatment before extraction; E enzymatic hydrolysis (5 % v/w enzymes); U ultrasonication (25

kHz); EU simultaneous enzymatic hydrolysis with ultrasonication.

The results in Table 4.3 demonstrate that the application of ultrasound (with and without

enzyme addition) favored the transport of solids to the aqueous skim fraction. The highest

71

Chapter 4

amount was obtained for the EU experiment with 60.5 % of the solids in the skim, being

not significantly different from that the U experiment. The application of a pretreatment,

irrespective of which one, significantly decreased the amount of residual solids after the

extraction. Cellulolytic enzymes are breaking down large polysaccharides present in the

cell wall and releasing smaller saccharides which may become soluble; on the other hand,

ultrasound can cause the disruption of the cells and decrease the particle size (Stadnik and

Dolatowski, 2011). The combination of enzymatic hydrolysis and ultrasound, therefore,

resulted in the highest decrease of insoluble residue (26.1 % residue).

From the compositional balances (Table 4.4) results show that the lipid-to-protein ratio

increased from 5:1 for the experiment with enzyme pretreatment and to 10:1 for the

enzyme-ultrasound experiment, meaning that the pretreatment (especially ultrasound)

improved the “purity” of the cream. According to OBs structure lipid-to-protein ratio for

intact and “pure” OBs is 20:1, indicating that pretreatment with enzymes combined with

ultrasound gives better results for the lipid-protein separation than pretreatment only with

enzymes.

Table 4.4. Protein and lipid composition of the main aqueous extraction fractions obtained from soy flour

Treatment

Composition (% dry-weight basis)

Cream Skim Residue

Protein Lipids Protein Lipids* Protein Lipids

Benchmark 12.8 75.8 49.4

<10%

23.4 9.5

E 13.2 74.9 45.0 23.5 10.5

U 10.4 81.4 44.9 23.7 7.3

EU 8.6 84.4 43.7 25.0 6.8

* In the skim fraction, no lipids were detected. During the extraction process in the skim fraction, two phases were

observed: the residual (solid) and the supernatant (aqueous) phase. In the supernatant phase of the skim fraction,

the concentration of lipids was less than 1 % on wet basis.

4.4. Conclusion

Aqueous extraction of intact OBs was possible under mild conditions. The results of the

investigation of the particle size effect demonstrated that fine milling, like cryogenic

milling, favored the cream yield, without improving the lipid extraction yield or the purity

of the obtained OBs cream. On the other hand, the soy flour with the larger particle size

resulted in a higher protein extraction yield in the skim fraction. The application of

72



ultrasound did enhance the purity of the final recovered cream fraction, with an oil-to-

protein ratio up to 10:1. The highest amount obtained for the simultaneous enzymatic

hydrolysis with ultrasonication experiment with 60.5 % of the solids in the skim. The

combination of enzymatic hydrolysis and ultrasound, therefore, resulted in the highest

decrease of insoluble residue, improved the purity of the cream, and reduced the processing

time. Finally, operating windows for different extraction parameters (extraction

temperature, pH, particle size, enzyme concentration and ultrasound frequency) were

defined and they formed basis for further conceptual process design.

4.5. References


Lipid Bodies lOO [] Lipid ] Protein, (September), 279–282.




Campbell, K. a, & Glatz, C. E. (2010). Protein recovery from enzyme-assisted aqueous

extraction of soybean. Biotechnology Progress, 26(2), 488–95.

Campbell, K. a., & Glatz, C. E. (2009). Mechanisms of aqueous extraction of soybean oil.


Cells, T., Hsieh, K., & Huang, A. H. C. (2004). Endoplasmic Reticulum , Oleosins , and

Oils in Seeds, 136(November), 3427–3434.

Deckers, H.M., van Rooijen, G., Boothe, J., Goll, J. and Moloney, M. M. (2003). Product

for Topical Applications Comprising Oil Bodies. United States.

Domínguez, H., Núñez, M. J., & Lema, J. M. (1994). Enzymatic pretreatment to enhance

oil extraction from fruits and oilseeds: a review. Food Chemistry, 49(3), 271–286.

Easson, M. W., Condon, B., Dien, B. S., Iten, L., Slopek, R., Yoshioka-Tarver, M., …

Smith, J. (2011). The application of ultrasound in the enzymatic hydrolysis of

switchgrass. Applied Biochemistry and Biotechnology, 165(5-6), 1322–31.



307.

73

Chapter 4


soy beans: a natural source of pre-emulsified soybean oil. Journal of Agricultural ,

8711–8716.






956.

Kapchie, V. N., Towa, L. T., Hauck, C., & Murphy, P. a. (2009). Recycling of Aqueous

Supernatants in Soybean Oleosome Isolation. Journal of the American Oil Chemists’

Society, 87(2), 223–231.

Kapchie, V. N., Towa, L. T., Hauck, C., & Murphy, P. a. (2010). Evaluation of enzyme

efficiency for soy oleosome isolation and ultrastructural aspects. Food Research

International, 43(1), 241–247.

Karki, B., Maurer, D., Box, S., Kim, T. H., & Jung, S. (2012). Ethanol Production from

Soybean Fiber, a Co-product of Aqueous Oil Extraction, Using a Soaking in Aqueous

Ammonia Pretreatment. Journal of the American Oil Chemists’ Society, 1345–1353.



Liu, F., & Tang, C.-H. (2013). Soy protein nanoparticle aggregates as pickering stabilizers

for oil-in-water emulsions. Journal of Agricultural and Food Chemistry, 61(37),

8888–98.










74












Cell Biology, 117(2), 327–335.






Wu, N.-N., Huang, X., Yang, X.-Q., Guo, J., Zheng, E.-L., Yin, S.-W., Zhang, J.-B. (2012).

Stabilization of soybean oil body emulsions using ι-carrageenan: Effects of salt,

thermal treatment and freeze-thaw cycling. Food Hydrocolloids, 28(1), 110–120.

75

Chapter 5

Chapter 5

Product-driven process synthesis for the extraction of

oil bodies from soybeans

ABSTRACT

In this chapter the Product-driven Process Synthesis methodology was used as a well-

defined structured approach for the conceptual design of an extraction process for the

isolation of intact oil bodies from soybeans. In the first part of this chapter, the product-

related design stages of the Product-driven Process Synthesis methodology were addressed.

This was done by defining and framing the product problem and subsequently mapping

consumer’s wants onto product attributes. The concept of House of Quality was used to link

both design spaces and additionally to map the product attributes onto product properties.

From this exercise a problem formulation was generated that basically established the

input (soybeans) and the output (intact oil bodies). Further, we identified the fundamental

tasks to convert raw materials into a final product which led ultimately to two alternative

process flow-sheets. These process flow-sheets were not obvious and hence were

experimentally verified. In this chapter, we demonstrated that the process alternative based

on combined enzymes and ultrasound improved the purity of the final product, provided a

better separation for the protein-lipid, and reduced processing time. For the selected

alternative, we defined the operating window and developed an overall process design.

76

Product-driven process synthesis for the extraction of oil bodies from soybeans

5.1. Introduction

In classical petrochemical industry the product design is separate from process design;

product properties are not so much dependent on the way they are produced as long as

sufficient purity is achieved. Chemical product design by Moggridge and Cussler (2000) is

explained in detail. On the other hand, Douglas (1985) introduced process synthesis as a

structured route for developing a process flow-sheet. Therefore, in the last ten years the link

between process design and the development of novel consumer products became

increasingly important. Especially in regard to the design of processes for structured

products, which are more difficult when using only process synthesis tools. These

structured products have high added value and they are often complex multi-phase

materials (e.g. cosmetics creams and lotions, margarine, ice cream, etc.) Edwards (2006).

The Product-Driven Process Synthesis (PDPS) methodology proposed by Bongers and

Almeida-Rivera (2012) connects product design with process synthesis. The product-driven

process synthesis method comprises a multi-level decision hierarchy with increasing level

of complexity that aids the user in the development of new products and processes.

Figure 1.5 in Introduction Section shows the hierarchy that starts at the framing level and

ultimately leads to a complete conceptual process design (including equipment design and

multi-product equipment integration). Bongers and Almeida-Rivera (2009) explained the

complete hierarchy in detail. There are nine levels in the PDPS methodology, see Figure

3.1in the Chapter 3. It is relevant to mention that the scope of the approach expands over

design spaces of multi product integration, scheduling and control (Bongers and Almeida-

Rivera, 2012).

In this chapter we will use the isolation of intact oil bodies (OBs) from soy beans to

illustrate the applicability and scope of the methodology. In Figure 5.1, images of soybean

and oil bodies are presented. Oil bodies are located in cotyledon cell surrounded by protein

bodies.

77

Chapter 5

Figure 5.1: Structure of a soybean grain (left) and transmission electron micrograph of a soybean cell (A.

Rosenthal et al., 1998) (right)

5.2. Framing level

At the framing level, the background of the project, the business context and the potential

of OBs as food additives are identified. Oil bodies (OBs) obtained from oilseeds have been

exploited for a variety of applications in biotechnology. These applications are based on

their non-coalescing nature, ease of extraction and the presence of unique membrane

proteins (oleosins). In a suspension, OBs exist as separate entities and hence they can be

used as emulsifying agent for a wide variety of products, ranging from vaccines, food,

cosmetics and personal care products (Bhatla, Kaushik, & Yadav, 2010; Kapchie, Yao,

Hauck, Wang, & Murphy, 2013). Currently, OBs are mainly used in the personal care and

cosmetic industry. OBs have a significant affinity to the skin, and can be used as delivery

systems for exogenous oils or vitamins. Some of the products include sunscreens, make-up

removers and hair products. Most of those applications involve synthetic OBs. To date,

SemBioSys Ltd (Canada) is the only company with patents on natural OBs. This company

obtains OBs from (genetically modified) safflower and using them as protein carriers in

personal care and pharmaceutical applications (Deckers et al. 2003). The process used by

SemBioSys company is based on the aqueous extraction process (AEP) of seeds. From an

experimental study we concluded that AEP is a suitable mild extraction technique for

extraction of OBs. In addition, the experimental results helped us to define the operational

windows for all process conditions e.g. process temperature, pH, desired particle size of soy

flour, salt concentration. Soybean OBs can be used in food products like dressings, sauces,

78


dips, beverages, and desserts. In food, OBs are used either to prevent lipids against

oxidation as “natural antioxidants”. Lipids are protected by a layer of proteins and therefore

protected from oxidation. In fat-containing food products (e.g. mayonnaise or margarine)

OBs could be used as “natural antioxidants”.

5.3. Consumer wants and product ideas

At the level of consumer wants and product ideas we translate what a consumer actually

wants into product characteristics such as smoothness, whiteness and creaminess. In this

section we propose a flow diagram that assists in translating the consumer wishes into

product formulations (see Figure 5.2). Three different shapes can be distinguished in the

diagram. The rectangles represent “processing” steps such as detailed interviews with

consumers, design of product recipe, measurements of functional requirements, tasting

sessions by panels and optimizing the product formulation. Blocks are reserved for

collecting the data after interviews with consumers, scoring of product characteristics and at

the end when we finally have a product that satisfies the consumer wants. The diamond

shape represents the decision making moment. Round shaped blocks represent start and end

of product design algorithm.

79

Chapter 5

Rough interview with

consumers

(first round)

Detailed interview

(second round)

Ranking of

consumer

needs

Scoring of the

product

characteristics

Design product

recipe

Measurement of

functional

requirements

Testing session

Scoring of the

product

characteristics

Consumers

satisfied

Modify recipe of

the product

New designed

product and

correlation between

attributes and

characteristics

Process Synthesis part

(continuation of PDPS

methodology)

YES

NO

Figure 5.2: Product design algorithm with collecting data steps (blocks), processing data steps (rectangles) and

decision making (diamond)

The most efficient and direct method for collecting product ideas is to ask consumers what

type of product they would like to get and to record those ideas. The ideas collected in this

way form the core of our further research. Our starting point in the product design

algorithm is, therefore, called a “rough interview with consumers - first round”. At this

stage, for instance, we could introduce to the consumer a new type of mayonnaise that

contains OBs. Firstly, we need to evaluate what the consumer values the most. For

example, we could find out whether “the product should be healthy”, or, “the product

should be easy to use”. After collecting all possible ideas that are coming directly from

consumers, we rank and sort them. For instance, a “healthy product” could be considered to

be more important than an “easy-to-open package”; or offering a cheap product could be

equally important as the product appearance. Organizing the ideas which we have generated

from the consumer interviews in this way can closely approach the final product idea.

After ranking and sorting the product ideas, a second, more detailed interview with

consumers takes place. At this stage, consumers can be asked to define in more detail what

the expected characteristics of the product should be. Some examples of the questions

used for the second (detailed) interview include the following:

1. What do you consider as a healthy product?

2. Do you prefer a solid or a liquid product?

80


This is a qualitative way to describe product characteristics. The characteristics are scored

and those with the highest scores are those that will have the most outspoken effect on the

overall design of the product recipe. To analyze the collected data in a more structured and

organized manner, i.e. the House of Quality (HoQ) or sometimes referred to as the Quality

Function Deployment (QFD) concept can be used (see for example Dawson and Askin

(1999) and Karsak et al. (2003)).

The HoQ is a diagram resembling a house that is composed of several blocks (the consumer

requirements, a planning matrix, technical requirements, interrelationships, and the “roof”

of the house). Figure 5.4 presents the HoQ diagram. At the right hand side of the house, the

consumer requirements are listed. In this particular case, we are producing OBs, which are

an intermediate product and will be used as food natural antioxidant in, for instance, a

mayonnaise. Upon adding OBs to mayonnaise we have to ensure that the newly designed

mayonnaise with OBs has the same characteristics as the existing one. This means that the

designed product has to satisfy the following requirements identified by the consumer as

relevant: to have good taste, to have good texture, to be a healthy product and to have an

attractive price for value. All these requirements are collected on the left hand side in the

HoQ as demanded quality/consumer requirements. Detailed descrption of HoQ method is

presented in Appendix H.

These consumer wants (what’s) are mapped onto a set of product attributes (how’s).

Examples of attributes include creaminess, thickness, and ease to be removed from the

spoon, smooth appearance and microbiologically stability. The relationships between the

consumer- and product attributes are shown in Figure 5.3 with four grades of correlation

(strong, moderate, weak and none). For example, taste and creaminess have a strong

relationship, which is provided by the level of fat in the recipe. In fact, high fat level

products are expected to be deliver high creaminess scores and taste profiles.

A strong advantage of this matrix is the “roof” block where we correlate the product

attributes (how’s) that characterize the product. This is done by using the symbols ++

(strong positive), + (positive) and – (negative) correlation. In this particular case the couple

creaminess-smoothness is strongly correlated. The reason for this is obvious as a smooth

mayonnaise has to be creamy as well. Any increase in creaminess is directly improving the

product smoothness. Moreover, to make clear how the designed product attributes should

look like, an improvement block is included below the “roof” of the house. At this block it

we have the possibility to state which technical product attribute should be maximized (e.g.

microbiologically safety) and which needs hit a specific target (e.g. appearance, creaminess

and smoothness).

81

Chapter 5

Figure 5.3: House of Quality diagram including all blocks (consumer requirements, planning matrix, technical

requirements, interrelationships, and “roof” of the house). Legend: Θ-strong relationship, Ο-moderate

relationship, ∆-weak relationship; +: positive correlation, +-: moderate correlation.

5.4. Input/output level

At this level a complete specification of all exchange streams to the process (inputs/raw

material(s) and target output/product(s) are identified. The consumer wants and ideas level

leads to the formulation of a product formulation, for instance a mayonnaise that contains

OBs as “natural antioxidants”. In this case we define as input (feed) the soybeans with their

composition and as output (product) the amounts and the condition in which we would like

to isolate the OBs from the soy. In soy beans the OBs are located in the cells and

surrounded by protein bodies. The product should contain approximately 80 % (w/w) of the

intact OBs present in the soy bean. Visual inspection of the microstructure can be used as

an indicator for intact OBs. A desired microstructure (intact OBs) is identified by Confocal

Scanning Laser Microscopy (CSLM) which can be used to analyze the obtained OBs

fraction. Figure 5.4 shows a CSLM picture of intact OBs and protein bodies as well as

shape and size of these entities and their position in the microstructure. Most of the soybean

82


protein and oil are stored in the cotyledon tissue in the organelles (also called protein

bodies) and oil bodies (oleosomes), respectively (images presented earlier in Introduction

section, page 12). The typical soybean composition is 1 % (w/w) free oil, 21 % (w/w) OBs,

38 % (w/w) of protein bodies, 35 % (w/w) carbohydrates and 5 % (w/w) ash.

Figure 5.4: Confocal Scanning micrographs of product (intact OBs) staining with Nile blue dye (bar 10 µm);

(small individual green particles (intact OBs) and bigger particles stained in red (protein bodies)

5.5. Task network

The next step in the methodology is to identify the fundamental tasks that are needed to

convert the input into the desired output. i.e. determination of the task network . The aim is

to isolate intact OBs from soybeans originally present inside cotyledon cells. To make the

oil bodies accessible the following tasks need to be executed (reference code is included for

the sake of simplicity), see also Table 5.1:

1. Size reduction of particulates (C2)

2. Cell wall disruption (C3)

3. Separation of a system into two systems with different composition (G1)

4. Physical/biological stabilization (J1)

These fundamental tasks are the critical and essential tasks based on the required to obey

desired final structure of the product. These four tasks (size reduction, cell wall disruption,

separation task and biological stabilization) can be combined leading to 24 (4!=24)

different processing routes. For example, task C3 could be performed first then task C2,

83

Chapter 5

after that J1 and at the final task G1. Among these possible combinations, only one is

feasible: C2, C3, G1 and J1. Moreover, for every task, there are different “mechanisms”

that could be used to perform task. In Table 5.1 all possible mechanisms for execution of

these tasks are presented. Heuristics, domain knowledge and project constraints to use mild

conditions (i.e. exclusion of organic solvents, high temperatures, extreme pH values: strong

acidic or alkaline conditions) are used to eliminate several of mechanisms and hence

reducing the number of potential alternatives.

Table 5.1: Fundamental tasks and mechanisms

Steps Fundamental task* Mechanisms*

Particle size reduction C2

C21: attrition

C22: impact

C23: ultrasound

C24: cutting

C25: enzymes


C31: internal cell phase change

C32: electro-magnetic fields

(PEF, ultrasound)

C33: shear

C34: enzymes

C35: chemical

Extraction of OBs G1

G11: molecular size

G12: particle size


G14: solubility

G15: chemical affinity

G16: chemical reaction

G17: (vapour) pressure

G18: gravity

G19: molecular size and electrical

charge

G20: shear

Physical/biological

stabilization J1

J11: freezing

J12: cooling * “Mechanisms” is the nomenclature used in the paper of Almeida and Bongers (2010)

All possible combinations result in more than 100 routes that could be followed. As this

number of alternatives is far from manageable a further simplification is proposed for the

network based on the following engineering-driven heuristics (H) and project constraints:

H1: Mechanisms C22 and C24 are not considered because soybeans are solid.

H2: C23 and C25 are excluded because these mechanisms will be used for the cell

wall disruption step.

84


H3: C32 has been excluded due to the low water content in soybeans. PEF was

considered after soaking, but an external electric field could increase temperature

at micro level. This fact is crucial as OBs are heat sensitive materials.

H4: G17 and G20 are also not considered due to project constraints (i.e. no harsh

conditions).

H5: Experiments showed that proteins present in the cream fractions were

identified based on their molecular size and electrical charge by sodium duodecyl

sulphate-polyacrylamide gel electrophoresis (SDS-PAGE). But this method was

not used to separate protein and oil bodies. This is the reason why task G19 has

not been considered.

H6: C35, G15 and G16 have been excluded because of environmental reasons.

This project aims at isolating OBs from soybeans under mild conditions, hence

without the use of chemicals. Furthermore, OBs will be used in the food industry

and these compounds have to be approved by obeying strict law regulations.

H7: J12 is rejected because OBs (as a final product) have to be stored at -18 oC to

avoid contamination of the product. Therefore, cooling is not sufficient.

Table 5.2: Selected tasks and mechanism

Steps Fundamental task Mechanisms

Particle size reduction C2 C21: attrition


C32: electro-magnetic fields-

ultrasound

C34: enzymes

Extraction of OBs G1

G11: molecular size

G12: particle size

G13: electrical charge

G14: solubility

Physical/biological

stabilization J1 J11: freezing

After applying these heuristics, the remaining possible and feasible mechanisms are

identified (Table 5.2). All listed mechanisms in Table 5.2 have been experimentally tested.

Two feasible task networks can be formulated on the basis of the appropriate mechanisms.

Figures 5.5.1 and 5.5.2 depict our proposed task network alternatives.

85

Chapter 5

Figure 5.5.1: Proposed task network for alternative 1. Codes in the scheme are given in Table 5.1

Figure 5.5.2: Proposed task network for alternative 2. Codes in the scheme are given in Table 5.1.

86


The major differences between the two proposed task network alternatives rely on the

mechanism associated to the cell wall disruption task. In alternative 1 a cell wall disruption

is performed only with enzymes, and in alterative 2 enzymes are combined with ultrasonic

treatment. These two different treatments are applied to the soy flour to improve the

extraction of the OBs. Cell wall degrading enzymes are applied to break the cotyledon cell

and to make the structure more permeable. Moreover, ultrasound is applied to increase the

transport of elements through cellular membranes, and to extract cellular structures from

damaged cells by cavitation (Vilkhu et al., 2008). In Table 5.3 the compositional mass

balance collected from experiments for two task network alternatives is presented. The total

protein content in the different fractions is around 80 % of the total solids. This is due to the

fact that some of the proteins remained trapped in the residue. From the compositional

balances it can be seen that the lipid-to-protein ratio increased from 5:1 for the experiment

with enzyme pretreatment and to 10:1 for the enzyme-ultrasound experiment, meaning that

the pretreatment (especially ultrasound) improved the “purity” of the cream. The theoretical

lipid-to-protein ratio for intact and “pure” OBs is 20:1, indicating that pretreatment with

enzymes combined with ultrasound gives better results for the lipid-protein separation than

pretreatment only with enzymes. Moreover, ultrasound increased the enzyme activity which

reduced the processing time. Finally, among the two task networks, task network 2 has

been selected because of its better results for extraction of OBs in cream fraction.

Table 5.3. Protein and lipid composition obtained from two different alternatives

Treatment


Cream Skim Residue


Enzyme

(alternative 1) 13.2 74.9 45.0

< 10%

23.5 10.5

Enzyme combined

with ultrasound

(alternative 2)

8.6 84.4 43.7 25.0 6.8

* In the skim fraction, no lipids were detected. During the extraction process in the skim fraction, two phases were

observed: the residual (solid) and the supernatant (aqueous) phase. In the supernatant phase of the skim fraction,

the concentration of lipids was less than 1 % on wet basis.

5.6. Mechanism and operating window

For each mechanism the operating window has to be defined. The first step in the process is

the milling/grinding operation which determines the particle size of the soy flour. For

soybean extraction using ultrasound and enzymes a frequency of 25 kHz is selected,

because low frequencies (20-100 kHz) are recommended for dominant physical effects of

87

Chapter 5

cavitation. In addition, this frequency range intensifies the mass transfer rates (Shirsath et

al., 2012). The application of a cell wall degrading enzyme solution (cellulases/pectinases)

of around 2-5 % v/w during an incubation time of 1-3 hours is proposed. The process

temperature is increased from room temperature to 40°C while incubating. The mass

transfer rate is favored by increased solute solubility and diffusion into the bulk solvent;

however, degradation of thermo-labile components (i.e. proteins) should be considered

when working at high temperatures. For aqueous extraction Jung (2009) obtained a

maximum oil yield in the extraction of soybean at temperatures between 40-60 °C, while

Rosenthal et al. (2001) noted a slight decrease in oil yield for temperatures above 50 °C,

which they attributed to protein denaturation. This was one of the reasons that in our case a

temperature of 40 °C was chosen.

The bulk of proteins is stored in protein bodies, which may vary in size from 2-20 μm in

diameter. Oil is located in smaller oil bodies which are 0.2-0.5 μm in diameter and are

surrounded by the protein bodies. Separation of oil and protein bodies can be done based on

their molecular size. With filtration the oil bodies can be further separated from larger

molecules (protein and other large molecules). OBs are coated with a layer of proteins

(oleosins) that protects the phospholipids monolayer from contact with phospholipases that

are present in the cell. Moreover, this layer gives the OBs a negatively charged surface,

while at the same time preventing OBs from aggregation. To improve the separation of

exogenous proteins from the OBs cream, the ionic strength of the extraction buffers plays

an important role. Interactions between OBs surface proteins and exogenous proteins

include electrostatic and van der Waals forces, hydration effects, hydrogen bonding, salt

bridging, and ion binding. When salt is used at low concentration, salt ions provide charge

shielding or ion binding on the charged proteins (Tsumoto et al., 2007). This can result in

repulsive interactions between the protein bodies and oleosins proteins, and a subsequent

increase in OBs purity (electrical charge effect). Finally, we can summarize the

fundamental tasks, mechanisms and operating window in Table 5.4.

Table 5.4. Selected mechanisms and operating windows

Fundamental task Mechanisms Operating window

C2

C21: attrition

C21: Milling / size ring: 0.2μm

C3

C32: electro-magnetic fields-

ultrasound

C34: enzymes

C32: Frequency: 25 kHz

C34:Concentration:5%(v/w);

incubation: 3 h at 40oC

G1

G11: molecular size

G12: particle size


G11: Membrane size: ≥0.6μm

G12: Centrifuge: 4700rpm at 4oC

G13: Buffer: 250mM NaCl

88


G14: solubility

G14: Hydration for 30min at 4oC

in sodium phosphate buffer 0.1M

pH7.2

J1 J11: freezing J11: -18oC

5.7. Equipment integration

Finally, the fundamental tasks and operating window are translated into suitable processing

equipment. In Figure 5.6 the proposed process flow sheet is presented. It is noted that the

purity of the product could be chosen differently because it depends on the application of

the product (food or cosmetics). One of the main constraints is that only food grade type of

solvents may be used. For this reason water is selected as a solvent. Firstly, the soy is

grinded in a grinding mill to create soy flour of the preferred particle size. Secondly, the

soy flour is hydrated with a sodium phosphate buffer in a mixing tank. After mixing the

slurry is blended with an (2-5 % (w/v)) enzyme solution and the mixture is exposed to an

ultrasonic treatment while it is reacting in a stirred tank reactor. After reaction a three

phase centrifuge is used to separate the cream fraction with OBs from the supernatant

(skim) and residue of the bottom. A washing steps with sodium chloride follows. A

secondary treatment with a three phase centrifuge is required to separate the purified cream

from the supernatant and residue left after washing. Ultimately an ultra-filtration membrane

unit separates the oil bodies from the proteins on the basis of their molecular size.

89

Chapter 5

Figure 5.6. Proposed flow sheet for the process of extraction of OBs from soybeans

90


The performance of the proposed process is assessed by a simple economic analysis and

compared with the conventional process. The difference between product revenue and raw

material costs is computed on a year basis for 1 ton/hr. To estimate the economic potential

(EP) (Cussler and Moggridge 2011) of the proposed process the following equation was

applied:

EP=Product revenues-Raw material cost

𝐸𝑃 = ∑ 𝐶𝑖 ∙ 𝐹𝑖 − ∑ 𝐶𝑗 ∙ 𝐹𝑗𝑗−𝑟𝑎𝑤 𝑚𝑎𝑡.𝑖−𝑝𝑟𝑜𝑑𝑢𝑐𝑡 eq. (5.1)

where Ci and Cj are the sales prices of the products i and the costs of the raw materials j,

respectively. F denotes the annual flow of products and raw materials. The input materials

for this estimation include the soybeans, water, NaCl and the enzyme. As output, the three

fractions obtained from the aqueous extraction process (cream, skim and residue) are

considered. The cream fraction can be sold as a high-value soybean OBs isolate (OBs). The

skim requires some concentration (by membrane filtration or evaporation) to be sold as a

high quality protein concentrate (SPC) for the food industry, but more natural and with

better functionality than the current products in the market. Finally, the residue can be sold

as soybean meal (SBM) for the feed industry or as a source for fermentable sugars for the

production of bioethanol or enzymes. In Table 5.5 the raw materials and final products

costs are detailed.

91

Chapter 5

Table 5.5. Raw materials and final product prices assumed for economic potential for the AEP of OB from

soybeans

Materials Costs of the raw materials

Input

Soybeansa €550/ton

Enzymee €8.7/kg

NaClc €50/ton

Waterd €1.25/m3

Sales prices of the products

Output

OB isolate (OBs)e** €5000/ton oil

Soy protein concentrate (SPC)f €1200/ton protein

Soybean meal (SBM)a €450/ton

* aChicago board of trade; c Indexmundi; d EUROSTAT; e Rough estimation; f Campbell and Glatz (2010)

**Price estimated with the price of high quality vegetable oil

For calculation of the EP for proposed process, several assumptions are made. The capacity

of the plant is set at 1 ton/h of soybeans and 20 h/day, giving a final annual flow of 7300

tons of processed soybeans. The composition mass balance (dry-weight basis) of each of

the streams is considered, since the price depends on the purity of the product (e.g. amount

of oil in the OBs isolate, and amount of protein in the SPC). Finally EP for proposed is

compared with conventional process for production of soybean oil.

Table 5.6. Economic potential for proposed process and conventional soybean oil process

Process

M/year

Cost of raw

materials

Sales prices of

products Economic Potential

Conventional process (with

hexane) € 7.3* € 7.7 € 0.4

Proposed process € 4.1 € 7.6 € 3.5

*In the conventional process use of hexane increases costs of raw materials

92


The estimation of the economic potential showed that the conventional process involved

high costs: the use of hexane and it represented around 40 % of the total input costs. High

economic potential is obtained for proposed process with a value of around €3.5

million/year, available for investment in the process.

5.8. Conclusions

We have demonstrated the use of the product-driven process synthesis methodology for the

conceptual design of OBs extraction from soy beans. In the first part of the methodology

the House of Quality method was used to provide a link between consumer’s wants and the

design of the process bringing together product attributes and measurable product

properties. Depending on the application, whether OBs will be used as food additive (e.g.

as a natural antioxidant in mayonnaise) or in cosmetics (e.g. in face creams), the product

(OBs) itself requires different physical, chemical, and microbiological properties. Next, we

identified the fundamental tasks to convert raw materials into a final product which led to

two alternative process flow sheets which were not obvious. These alternatives were

experimentally verified. In this work, we have shown that the alternative with a

combination of enzymes and ultrasound improved the purity of the cream (final product),

enhanced the protein-lipid separation, and reduced the processing time. For the selected

processing route, we defined an operating window and constructed an overall process

design. In addition, the estimation of economic potential showed that proposed process for

extraction of OBs has higher EP compare to the conventional process for production of

soybean oil. The use of hexane in the conventional process ensures purity of the final

product (soybean oil purity > 95 %), but at the same time increases costs of raw materials.

5.9. References


Lipid Bodies and Lipid- Protein, (September), 279–282.







93

Chapter 5







Campbell, K. A, & Glatz, C. E. (2010). Protein recovery from enzyme-assisted aqueous

extraction of soybean. Biotechnology Progress, 26(2), 488–95.

Campbell, K. A., & Glatz, C. E. (2009). Mechanisms of aqueous extraction of soybean oil.


Campbell, K. A., Glatz, C. E., Johnson, L. A., Jung, S., de Moura, J. M. N., Kapchie, V., &

Murphy, P. (2010). Advances in Aqueous Extraction Processing of Soybeans.

Journal of the American Oil Chemists’ Society, 88(4), 449–465.



80(2), 755–64.

Cells, T., Hsieh, K., & Huang, A. H. C. (2004). Endoplasmic Reticulum , Oleosins , and

Oils in Seeds, 136(November), 3427–3434. d

Cussler, E.L. and Moggridge, G. D. (2011). Chemical Product Design (Second edi.). New

York: Cambridge University Press.

Deckers, H.M., van Rooijen, G., Boothe, J., Goll, J. and Moloney, M. M. (2003). Product

for Topical Applications Comprising Oil Bodies. United States.

Domínguez, H., Núñez, M. J., & Lema, J. M. (1994). Enzymatic pretreatment to enhance

oil extraction from fruits and oilseeds: a review. Food Chemistry, 49(3), 271–286.

Esser, A. T., Smith, K. C., Gowrishankar, T. R., Vasilkoski, Z., & Weaver, J. C. (2010).

Mechanisms for the intracellular manipulation of organelles by conventional

electroporation. Biophysical Journal, 98(11),



307.


soy beans: a natural source of pre-emulsified soybean oil. Journal of Agricultural …,

8711–8716.

94







956.

Kapchie, V. N., Towa, L. T., Hauck, C., & Murphy, P. a. (2009). Recycling of Aqueous

Supernatants in Soybean Oleosome Isolation. Journal of the American Oil Chemists’

Society, 87(2), 223–231.

Kapchie, V. N., Towa, L. T., Hauck, C., & Murphy, P. a. (2010). Evaluation of enzyme

efficiency for soy oleosome isolation and ultrastructural aspects. Food Research

International, 43(1), 241–247.

Karki, B., Maurer, D., Box, S., Kim, T. H., & Jung, S. (2012). Ethanol Production from

Soybean Fiber, a Co-product of Aqueous Oil Extraction, Using a Soaking in Aqueous

Ammonia Pretreatment. Journal of the American Oil Chemists’ Society, 1345–1353.


















95

Chapter 5

Rosenthal, A., Pyle, D. L., & Niranjan, K. (1996). Aqueous and enzymatic processes for





SALE, A., & HAMILTON, W. (1967). Effects of high electric fields on microorganismsI.

Killing of bacteria and yeasts. Biochimica et Biophysica Acta (BBA) - General

Subjects, 148(3), 781–788.







Cell Biology, 117(2), 327–335.






97

Chapter 6

Chapter 6

Conclusions and Outlook

6.1. Conclusions

The food industry is facing the challenge of developing new food products with

excellent health benefits and meeting consumers’ appreciation. Plant extracts have

as compared to products with an animal source or to synthetic products benefits,

especially towards environmental burden. There is also a need to develop novel

dietary strategies, especially with reference to the potential health properties such

as the antioxidant property of polyphenols from fresh tea leaves.

The structured foods that use natural ingredients with a vegetable origin as food

additives are also a trend in the food producing industry. Oil bodies from soybeans

represent a good example as a natural food additive that can be used in e.g. sauces,

margarine, and mayonnaise.

This thesis deals with development of food grade and sustainable processes for

isolation of key components from two different raw materials: fresh tea leaves and

soybeans. The development of such processes that use only food grade solvents

provide not only additional health benefits beyond basic nutrients, but products

with label “natural” based on a natural source.

To meet economic and environmental requirements for processes to process two

completely different plant materials i.e. fresh tea leaves and soybeans, the Product

Driven Process Synthesis (PDPS) methodology introduced by Bongers and

Almeida-Rivera (2009) has been applied. PDPS combines product design and

process synthesis in a structured and systematic approach.

Separation of polyphenols from fresh tea leaves has been difficult due to leaves and

polyphenols instability i.e. undesired degradation reactions. Isolation of oil bodies

from soybeans has been proven to be difficult due to their fragile structure and

degradation. Furthermore, the presence of other cell constituents such as e.g.

protein bodies that interact with oil bodies increases the level of complexity for the

isolation of the oil bodies.

98


Increasing the knowledge about how components are present and anchored in the

original vegetable matrix and how their individual properties depend on the

conditions (moisture, pH, ionic strength, temperature, etc.) is prerequisite to

provide the possibility to allow a successful contribution of these components to

the food market of the future.

6.1.1. Polyphenols from tea leaves

One interesting process alternative to extract polyphenols is to open the cell

structure in the fresh tea leaves by applying intensive electrical pulses. The

disadvantage would be the increase in temperature on micro (cellular) level due to

the high electric field strength and the related currents. The work reported in this

thesis provides a valid evidence that pulsed electric field (PEF) processing is a non-

thermal method applied under the used conditions. With a correct combination of

operational factors (electric field strength, pulse duration and number of pulses)

from the pulsed electric field (PEF) method we observed a very limited

temperature increase. Opening of the cell membranes seems to be the key factor in

allowing polyphenols to be transported from the interior of the cell to the

surrounding liquid. Both electric field strength and the total treatment time (product

of pulse duration and number of pulses) play an important role in opening the cell

structure and subsequent polyphenols extraction. An extraction yield of about 30 %

has been obtained in the work reported in this thesis. This extraction yield has been

obtained for the total treatment time of 2.5 s and field strength of 0.4 kV/cm. To

achieve the same extraction yield but with shorter total treatment time (1.5 s)

higher electric field strength (0.9 kV/cm) is required. When total treatment time

was 5 s (for both electric field strengths 0.4 and 0.9 kV/cm) the experiment was not

performed due to limitations of with PEF equipment (low conductivity was

detected in the PEF chamber).

As a part of the PDPS approach the statistical analysis applied by using the Design

of the Experiments method demonstrates that electric field strength is a key factor

to maximize the amount of extracted polyphenols from fresh tea leaves while

minimizing pulse duration. Polynomial models developed from a Box-Behnken

design of experimental approach were used to determine the optimal conditions for

PEF. Operating factors that have a significant influence on the extraction yield of

99

Chapter 6

polyphenols are electric filed strength, pulse duration and number of pulses. The

optimal results allow an extraction yield of polyphenols of 32 %.

The pulsed electric field method is a promising technique for opening the cell

structure and for extraction of cellular material in molecular form.

6.1.2. Oil bodies from soybeans

To prevent degradation of oil bodies (OBs) by applying high temperatures and to

avoid organic solvents (e.g. n-hexane) residue in the final product, an aqueous

extraction process is a promising alternative for the separation of oil bodies and

proteins from soybeans. Depending on the application, whether OBs will be used

as a food additive (e.g. as a natural antioxidant in mayonnaise) or in cosmetics (e.g.

in face creams), the product (OBs) itself requires different physical, chemical, and

microbiological properties.

The outcome of the task network level of PDPS methodology leads to two

alternative process flow sheets which were not obvious. In a systematic screening

study three pretreatments have been tested: enzymatic degradation of the cell wall,

ultrasound induced opening of the cell wall and a combination of both.

Experimental results show that pretreatment with ultrasound reduced the remaining

insoluble fraction in the residue and increased the amount of oil bodies extracted

into the surrounding aqueous phase. In addition, an estimation of the economic

potential showed that the proposed extraction process of oil bodies based on the

combination of enzymes and ultrasound has a higher economic potential as

compared to the conventional process for production of soybean oil. For the

proposed process the input materials for economic estimation include the soybeans,

water, NaCl and the enzyme. As output, the three fractions obtained from the

aqueous extraction process (cream, skim and residue) are considered. On the other

hand, for the conventional process input are soybeans and n-hexane necessary for

extraction of the oil. The outcome of the conventional process is pure soybean oil.

The conventional process involved high costs: the use of hexane and it represented

around 40 % of the total input costs. For the capacity of 1000 kg soybeans per hour

high economic potential is obtained for proposed novel process with added value of

around 3.5 M€/year. The use of n-hexane in the conventional process ensures

100


purity of the final product (soybean oil purity > 95 %), but at the same time

increases costs of raw materials.

6.2. Outlook

6.2.1. Wax removal from the surface of tea leaves

Besides extraction of polyphenols from fresh tea leaves, removal of the waxy layer

from the leaf surface in an early stage of processing would be beneficial. Waxes

are complicated mixtures of long aliphatic alcohols, fatty acid esters, etc. and

introduce an additional mass transfer resistance during drying of tea leaves. In tea

production, waxes participate in complex formation reactions with polyphenols and

cause sediment formations that later in the process have to be additionally

separated. This leads to product losses i.e. polyphenols and addition of separation

tasks and high process investment which can be probably avoided if the waxes are

removed prior.

6.2.2. Pulsed electric field method

As described throughout this thesis, pulsed electric field (PEF) method is a

promising technique for the opening the cell membrane. According to the electrical

measurements presented in section 2.3.1. pulsed electric field exerted opening the

cell membrane. This means that under the operating settings the temperature

increment was not pronounced (< 10 oC). Phospholipid is the main component of

the cell membrane. A phospholipid based vesicle could serve as a good model

species to examine and to elucidate in detail electroporation (opening the

membrane structure) and thermal effects (Tg - glass transition temperature effect)

caused by external electric field. Further, the study of the physicochemical process

involved in phospholipid vesicle membrane can provide useful information about

the complex phenomenon of electroporation. Also fundamental insight can be

gained for the multi stage extraction process.

101

Chapter 6

Next to this project, PEF method was used as a pretreatment prior blending or

pressing during processing of sugar beet leaves in the same project cluster (A.

Kiskini, Wageningen University and ISPT). PEF was introduced to enhance the

protein extraction yield from sugar beet leaves. Experiments were carried out on

semi-industrial continuous equipment with different operating factors as compared

to the batch laboratory scale PEF equipment used in this project. The continuous

PEF process is more difficult to control as compared to batch PEF unit due to the

fact that vegetable material is placed on the belt passing between two high voltage

electrodes. Due to the different size and orientation of sugar beet leaves, exposure

of the material under high voltage is not uniform.

6.2.3. Product and equipment integration

In the last level of PDPS, idea is to integrate different products and/or operational

units. In the case of soybeans depending on the application of oil bodies whether

they will be used as food additives or in cosmetics, purity demands of the final

products are different. The proposed process for extraction of oil bodies from

soybeans could be used for production of various products. However, the order of

the tasks execution would be different. For example, purity of oil body’s stream

that will be used in personal care products is not necessary to be high, e.g. around

60 % of oil bodies in the stream. On the other hand, oil bodies that will be used as a

food additive require a high purity above 90 %. Therefore an additional separation

steps should be introduced in order to reach desired product purity.

As described in the thesis, equipment for production of oil bodies from soybeans

has been selected. However, there is also room to optimize selected unit operations.

In the proposed process for isolation of oil bodies from soybeans to disrupt the cell

wall a combination of enzymes and ultrasound was reported. The time constant for

enzymes degradation of the cell wall in a bioreactor will take around 3 hours. On

the other hand, ultrasound process is several seconds. Therefore, control of such

system is complicated and requires optimization of each unit operation.

Owing to the complexity of food matrices, product driven process synthesis

methodology has been applied as a useful tool for conceptual process design for

isolation of key components from raw materials e.g. fresh tea leaves and soybeans.

103

Appendices

Appendix A

A.1. Enzyme-Assisted Extraction

The cell wall is the primary mechanical barrier for the extraction of the OBs from the cells,

therefore it must be broken for any significant extraction to occur (Rosenthal et al., 1998).

In plant cells, the primary cell wall is constructed of pectins (homogalacturonan,

rhamnogalacturonan, xylogalacturonan), hemicelluloses (xyloglucan, arabinoxylan), and

crystalline micro fibrils of cellulose, crosslinked with proteins. Within the primary cell wall

is a secondary cell wall of cellulose and hemicellulose. The cells are held together by a

middle lamella composed of mostly pectins ( Campbell, 2010).

Figure A.1. Structure of the primary cell wall (Cosgrove, 2005)

The utilization of hydrolytic enzymes, such as cellulases, hemicellulases and pectinases, to

break the cell walls and assist the extraction process can potentially increase the extraction

yield. Moreover, cell wall hydrolysis allows the extraction of undenatured proteins, which

is an important advantage over traditional extraction processes.

Soybean cell wall is considered to have very complex fibers. It contains pectins with a

considerable amount of arabinan, galactan or arabinogalactan side chains (Huisman et al.,

104

Appendices

1999). Several attempts have been made to completely degrade the soybean cell wall with

many enzymes. Huisman and authors (Huisman et al., 1999) applied a powerful

commercial enzyme mixture into the intact soybean cell wall polysaccharides. However,

the network of the cell wall polysaccharides present in soybean was too complex or too

dense to be penetrated by the applied enzymes. Ouhida et al. (2002) needed an extensive

sequential fractionation of the cell wall polysaccharides (using chelating and alkali

solutions) to increase the enzyme accessibility to the substrate, especially to the xylans and

cellulose. Kasai and others (Kasai et al., 2004) needed prolonged reaction times,

mechanical breaking and strong heat treatments (autoclaving) to obtain a solubilisation of

83-85 % of okara (residue from soymilk production containing the fibers). Although, the

complete degradation of the soybean cell wall is not the goal during OBs extraction. The

role of hydrolytic enzymes such as cellulases, hemicellulases and pectinases in these

processes is to make the structure more permeable (Rosenthal et al., 1996) and to increase

the diffusion of cell components (protein and oil bodies) to the extraction medium without

damage (Jung, 2012).

Kapchie et al. (Kapchie, 2008) could recover twice the amount of oil from OBs just by

using a mixture of hydrolytic enzymes during the AEP. After four consecutive extraction

steps, with 3 % of enzyme cocktail (Multifect Pectinase FE, Cellulase A, and Multifect CX

13L), 85 % of the total soybean oil was recovered as oleosomes. According to these

researchers, the enzyme assisted procedure mainly depended on the enzyme concentration

combined to the mechanical disruption of the cells to obtain maximum yields. Figure A.2

shows the effect of enzyme treatment on a previously grinded seed. The enzyme action

makes the structure more permeable; the extend will depend on the particle size (Rosenthal,

1996).

105

Appendices

Figure A.2. Effect of milling and enzymatic treatment on oilseed cell structure (Rosenthal et al., 1996)

The EA-AEP has successfully recovered up to 93 % of oil (pilot plant scale) from the

starting material and 40-50 % of protein in the skim fraction (Kapchie et al., 2011).

However, most of the applied extraction procedures involved long treatment times (15 to 20

h) (Kapchie, et al., 2010). Reducing the incubation and/or extraction times is essential for

reducing microbial risks and costs in EA-AEP (Karki et al., 2012).

A.2. Ultrasound-Assisted Extraction

The application of ultrasound-assisted extraction (UAE) in food processing is of interest for

enhancing existing extraction processes, but also for enabling novel extraction

opportunities. Some of the applications of UAE include the extraction of herbal, oil, protein

and bioactives compounds from plant materials (e.g. flavones, polyphenols) (Vilkhu et al.,

2008).

Intensification of extraction efficacy using ultrasound has been attributed to the propagation

of ultrasound pressure waves through the solvent, resulting in cavitation phenomena.

Ultrasonic cavitation creates significant shear forces that can disrupt the natural liquid

layers system close the phase boundaries, and consequently stimulate the process of mass

transfer. Cavitation provides another advantage in the form of destruction of cellular

structure, and consequently the release of cell contents into the surrounding solution (see

106

Appendices

Figure A.3) (Stadnik and Dolatowski, 2011). If the substrate is dry, then ultrasound may be

used to facilitate swelling and hydration and cause enlargement of plant cell wall.

Figure A.3. The mechanism of cell wall disruption (a) breaking the cell wall due to cavitation, (b) diffusion of

solvent into the cell structure (Shirsath et al., 2012)

Diffusion through the plant cell walls, disruption and washing out of the cell contents are

attributed to improved extraction performance. The corresponding reduction in the size of

the vegetable material particles by ultrasound disintegration will increase the number of

cells directly exposed to the extraction solvent and ultrasonic cavitation (Vilkhu et al.,

2008).

It has been reported that the major impact of ultrasound on the efficacy of extraction was in

terms of reduction in required time and slight increase in the overall extraction yield

(Vilkhu et al., 2008). Li and authors (Li, e al., 2010) studied the UAE of oil from soybean

flour, using a 20 kHz ultrasonic generator for a period up to 3 h. Compared with a non-

sonicated control, the oil yield increased 11.2 % (intensity of 47.6 W/cm2). Results of the

GC fatty acid profile showed that ultrasonication did not noticeably influence the

composition of the extracted oil (0.52 % decreased in linoleic acid). UEA can also provide

the opportunity for enhanced extraction of heat sensitive bioactive and food components at

lower processing temperatures (Vilkhu et al., 2008).

Furthermore, UAE can be conveniently coupled with other extraction techniques such as

supercritical fluid extraction, microwave assisted extraction, vacuum distillation and

enzymatic treatment (Shirsath et al., 2012). The combination of ultrasound with enzyme

treatment have shown synergistic effects (Stadnik and Dolatowski, 2011). Ultrasound

improves the transport of enzyme without generating an excessive amount of highly

107

Appendices

reactive intermediates which may cause deactivation of enzymes. Moreover, ultrasound can

also activate the catalytic performance of the enzyme adsorbed onto the surface of substrate

and enhance removal of the products from the reaction zone. Thus ultrasound increases the

efficiency of enzymatic treatment with higher extraction yield and lower times (Li et al.,

2010). Kapchie et al. (2009) investigated the effect of ultrasound on the EA-AEP of OBs

from soybean. Only 3 min ultrasonication prior enzymatic hydrolysis resulted in high oil

recoveries in the oleosome fraction (~80 % with 3 % enzymes). Four consecutive extraction

cycles were needed to obtain the same oil yield without ultrasound pretreatment. No

confirmation of OB integrity was reported in this study.

In the following table A.1, a summary of some of the most recent work in OBs AEP is

presented. Typically, the processes involved the use of alkaline TRIS buffers with moderate

salt concentrations, to buffers with 0.5 M NaCl and 0.4 M sucrose, under acidic conditions.

It is believed that high sucrose and salt concentrations are necessary to preserve the OBs

organelle integrity. Moreover, using high salt concentration increases protein solubility at

low pH, allowing cellulase-assisted extraction to occur near the protein pI (4.3-4.5).

However, the separation and purification of the proteins from those osmotic solutions (e.g.

by ultrafiltration or isoelectric precipitation) still need to be assessed to obtain a valuable

fraction at the end (Campbell et al., 2010).

108

Appendices

Table A.1. Summary of some of the latest works intended to extract intact oil bodies

NR not reported; AEP Aqueous extraction process; EA-AEP Enzyme-assisted aqueous extraction process a Taking the initial amount of oil or protein present in the original material as 100 %

Reference Starting

Material Pretreatment Extraction process

Extraction

medium

Recoverya Oil:Protein

ratio in

cream Oil from

cream

Protein from

supernatant

Iwanaga, et

al., 2007 Soybeans

Soaking in

buffer solution

(pH 8.6), 4-

6°C, overnight

Alkaline AEP

3mM MgCl2,

100mM Tris-HCl

buffer, pH 8.6

36% NR 4.6:1

Kapchie, et

al., 2008

Full-fat

soybean

flour

Ultrasonication

(3min, 70W)

EA- AEP

(incubation 3%

enzyme 57°C/20h)

2 to 4 cycles of

residue extraction

Flour extraction:

Potassium acetate,

pH 4.6 with 0.5M

NaCl and 0.4M

sucrose

Residue extraction:

Tris-HCl buffer,

pH 7.2, with 0.5M

NaCl and 0.4M

sucrose

No

pretreatment

(4 cycles):

84.65±1.46%

Pretreatment

(2-cycles):

78.87±7.19%

No

pretreatment:56.76±0.56% NR

Nikiforidis,

(2009)

Maize

germ

flour

(<0.8mm)

Soaking in

water, RT, 24h

Alkaline AEP

3 extraction cycles

NaOH solution (pH

9.0) 75.50% NR 4.3:1

Kapchie, et

al., 2010

Full-fat

dehulled

soybean

flour

Soaking at

57°C/16h in

osmotic

solution (0.4M

sucrose, 0.5M

NaCl)

EA-AEP

(incubation 3%

enzyme 57°C/20h)

4 extraction cycles

Potassium acetate,

pH 4.6 with 0.5M

NaCl and 0.4M

sucrose

77.42% 43.19% NR

109

Appendices

Kapchie, et

al., 2011

Full-fat

dehulled

soybean

flour

Pilot-Plant Scale

Continuous EA-EP

(incubation 3%

enzymes, 57°C/15h);

Recirculation of

supernatant and

residue 8h

Potassium acetate,

pH 4.6 with 0.5M

NaCl and 0.4M

sucrose

91.44±1.31% 79% 4.2:1

Chen et al.,

2012 Soybeans

Soaking

overnight 4-

6°C in buffer

(pH 8.6)

AEP 3mM MgCl2 in

Tris-HCl, pH 8.6 65% NR 14:1

110

Appendices

Appendix B

B.1. Measurement of enzyme activity of different commercial enzymes

In order to select an enzyme mixture to treat the soy flour, the enzymatic activity of

different commercials enzymes was measured by the 3,5-dinitrosalicilyc acid (DNSA)

assay. The cellulase, pectinase and xyloglucanase activity of each commercial preparation

was measured by using sodium carboxymethyl cellulose (9M31XF, Hercules), low

methylated pectic (32 % DE, Danisco) and tamarind xyloglucan (Megazyme) solutions (1

% w/v) as substrates, respectively. The activity was measured at 40 °C and pH 7.2 (see

Table B.1).

Table B.1. Enzyme activity measured by the DNSA assay and price of the different commercial enzymes

Enzyme activity (Ua/ml)

Substrate*

Costs (€/kg)

CMC LMP XG SF

Rapidase TF (DSM) 4.34 6.22 22.13 1.32 18

Ultrazyme AFP L (Novozymes) 1.93 13.15 14.49 1.85 8.7

CMC Carboxymethyl cellulose; LMP Low methylated pectic; XG Xyloglucan; SF soy flour. aU=µmol of glucose release per min, at 40°C and pH 7.2.

Enzyme preparations were purified using a PD-10 Sephadex column (GE Healthcare) to get

rid of free sugars, and diluted 100 times before activity measurement. A volume of 0.3 ml

of the substrate solution was mixed with 0.3 ml of the enzyme solution, and incubated at 40

°C/ 30min. After this period, 0.6 ml of the DNSA reagent was added, and the reaction

mixture was incubated at 95 °C/5 min to develop color. Samples were cooled; centrifuged

(14000 rpm/10 min) and diluted with distilled water, to finally measure the absorbance at

540 nm (Shimadzu UV-1601). Substrate and enzyme blanks, as well as calibration with

different glucose solutions (0-6mg/ml), were taken into consideration. Glucose calibration

curve is presented in the Figure B.1. An enzyme unit (U) was defined as the µmols of

glucose released per minute, under the conditions used.

111

Appendices

Figure B.2. Glucose calibration curve for the enzyme activity DNSA assay

112

Appendices

Appendix C

C.1. Protein and lipid recoveries from different extraction procedures

In the following table, the dry-weight composition of the different AEP fractions is shown.

Table C.1. Protein and lipid composition of the main aqueous extraction fractions obtained from soy flour

Treatment


Cream Skim Residue


Control 12.8 75.8 49.4

<10%

23.4 9.5

E 13.2 74.9 45.0 23.5 10.5

U 10.4 81.4 44.9 23.7 7.3

EU 8.6 84.4 43.7 25.0 6.8

113

Appendices

Figure C.3. Protein and lipid recoveries in the different fractions from the aqueous extraction process of soy flour (the Total yield was obtained by addition of the protein

or lipids found in the skim1, residue, skim2, top and bottom cream)

114

Appendices

Appendix D

D.1. Particle size measurement: effect of the particle size on extraction of

OBs

Figure D.1. Particle size distribution of the soybean flours used for the AEP of OBs (A flour produce by a lab

scale Polymix mill; B flour cryogenically milled in a pilot plant scale Contraplex mill)

Right after milling the beans, flour A was immediately sieved using a vibratory sieve

shaker, however, efficient size classification was not achieved, as it can be seen in Figure

115

Appendices

D.1A. A double distribution was obtained with smaller particles than expected (125 to 250

µm); 90 % of the particles had a particle size lower than 300 µm and around 65 % had a

particle size lower than 100 µm. A possible reason is that, no matter the level of milling,

there is always some oil being extracted from the disrupted cells (especially since the oil is

in liquid state). Therefore, it is possible that free oil caused particles to stick to each other,

and made the separation of the smallest particles (<12 5µm) very difficult.

Flour B presented a normal distribution; 90 % of the particles had a particle size lower than

40 µm. Considering that cotyledon cells are about 15-20 µm in diameter and 70-80 µm in

length , such a particle size probably resulted in the rupture of a high proportion of the cells.

It is important to note that the particle size distribution was measured on the wet flour;

therefore, the result reflects the size of the hydrated particles. This might be the reason for

obtaining a higher particle size in flour A than the expected according to the sieve used

(250 µm).

Figure D.2. Particle size distribution of the fresh and aged (6 days at 4°C) “purified” cream fractions, obtained

from the AEP of two different soy flours (A produce by a lab scale Polymix mill; B cryogenically milled in a pilot

plant scale Contraplex mill)

The particle size and micro structure of the cream fractions, obtained from the AEP, was

analyzed as an attempt to determine the presence of intact OBs. In the following Figure

D.2, the average particle size of the fresh and aged (6 days at 4°C) cream fractions is

presented.

Intact soybean OBs have a diameter between 0.2-0.5 µm. However, as it can be seen in

Figure D.2, the average particle size of the majority of the particles was in the range

between 1 to 10 µm. The presence of non-oleosins proteins in the cream (as confirmed by

the lipid-to-protein ratio of the cream fractions) most probably caused the higher particle

116

Appendices

size in the emulsions. Moreover, the cream from flour B, which contained a higher amount

of proteins, had a wider size distribution, confirming that non-oleosins proteins are part of

the emulsion and increasing the particle size.

The particle size distribution was also measured after 6 days of storage to check if the

extracted OBs were intact and stable against coalescence. As seen in the Figure D.2, the

particle size of both creams did not change significantly over time. Moreover, no free oil

was observed in the creams after storage. Although no direct conclusion can be made, this

is an indication that the emulsion was stable and that the oil was protected against

coalescence.

D.2. Particle size measurement: effect of the pretreatments on extraction of

OBs

The particle size distribution of the top “purified” cream was measured by light scattering

to check if the size of the particles were similar to the expected OBs size (Figure D.3).

Figure D.3. Particle size distribution of the cream fraction obtained from the different AEP of soy flour

All fractions had similar particle size distribution: 90 % of the particles had a size of 1.5-1.9

µm or less; showing smaller particle size those creams from the ultrasonicated experiments.

In this case, particles as small as 0.4 µm were obtained, which are in the range of OBs size

117

Appendices

(0.2-0.5 µm). Nikiforidis and Kiosseoglou (Nikiforidis, 2009) have reported that maize

OBs contained a secondary external layer of extraneous germ seed proteins, which

interacted between each other and formed an OBs network. As already discussed before,

the “purified” top cream still contained some extra proteins, which could be forming a

complex network and slightly increasing the OB particle size.

The cream fraction was also stored for 7 days at 4°C, and the particle size was measured

again to check whether the emulsion was stable or coalescence of OBs occurred (Figure

C.4):

Figure D.4. Particle size distribution of the cream fraction after 7 days storage at 4°C

As seen in the Figure D.4, no big differences were obtained from the different cream

fractions. In the case of the cream obtained by enzymatic hydrolysis, the particle size

slightly increased, which could mean that the enzymes had some protease side activity and

oleosins were degraded, making the OBs unstable. However, no free oil was detected on the

top of the cream. Differences can be also a result of the normal variation of the instrument

measurement.

Overall, no big differences were found between the different AEP procedures. However,

some trends were observed: the application of a pretreatment favored the extraction of

lipids and proteins from the soybean solids to the aqueous media. Irrespectively of the

pretreatment, the remaining residue always decreased. However, the recovery of those

extracted components was not as expected. The Control treatment showed the highest oil

118

Appendices

recovery in the cream fraction. Meanwhile the ultrasonicated experiments showed the

highest protein recovery in the skim fraction. The lost of OBs into the skim fraction and the

inefficient detection method, were critical factors that might have caused the apparent high

oil losses. The combination of enzymatic hydrolysis with ultrasound resulted in the highest

lipid-to-protein ratio in the cream (10:1), while the washing step permitted a further

increment (as high as 14:1). However, some non-oleosins proteins are strongly bound to the

OBs, making the purification difficult.

119

Appendices

Appendix E

E.1. Microscopy analysis

One sample of the cream from soy flour A was analyzed by light microscopy (Figure E.1).

A few big droplets are seen in the range on 20-30 µm. Disruption of the natural OB

structure is difficult to avoid during the grinding of the soybeans; therefore, oil coalescence

may occurred during the AEP. However, many very small droplets are also appreciated in

the picture, which could be intact OBs.

Figure E.1. Image of cream fraction form soy flour A with a 20x (left) objective

In order to obtain more information on the microstructure of the creams, Confocal Scanning

Laser Microscopy (CSLM) was used to analyze the creams. When CSLM is used, materials

can be observed from different depths. The microscope makes an image of a certain section

of specific thickness; how deep in the sample the image is taken can be controlled by the

instrument operator. Therefore particles can be seen from the top, the bottom or the inside.

In this particular case, the sample was stained with Nile blue, which stains based on

polarity. Highly non-polar components are colored green; less non-polar components are

colored red, and polar components (i.e. water) are in black.

120

Appendices

Appendix F

F.1. Differential scanning calorimetry (DSC) results for the cryogenically

milled soy flour

Methodology:

DSC thermographs were recorded on a DSC 8500 (Perkin Elmer) using 0.1 ml vessels. Soy

flour and the extraction fraction were heated from 15 to 140 °C, at a heating rate of 10 °C/

min and subsequently cooled to 15 °C at the same rate. After this first heating cycle, a

second heating cycle was done to investigate the reversibility of the denaturation. The

instrument was calibrated with indium.

Results:

Protein denaturation is the unfolding of the protein from a structured native state into an

(partially) unstructured state with no or little fixed residual structure, which is not far from

a random coil (De Graaf, 2000).

Figure F.1. DSC thermogram of the soy flour B (red line first heating cycle, green line second heating cycle)

The thermogram of the soy flour B (cryogenically grinded) is given below, and shows two

small peaks at temperatures of 54 °C and 90 °C, which disappear after the first heating. The

main proteins in soy are β-conglycinin (7S) and glycinin (11S). The temperature of

denaturation ranges from 68-82 °C for 7S and 83-95 °C for 11S (Cramp, 2007). However,

121

Appendices

most of the thermal denaturation studies in soy proteins have been done in model systems

with solutions of purified proteins.

One of the possible reasons for these low peak areas is that soy flour was analyzed dry;

neither hydration nor a solution was made before analysis. Water is essential to allow

thermal motion of molecules (Sochava, 1997). The denaturation temperature of the protein,

Td, strongly depends on the water content up to a water content of 10–20 % (De Graaf,

2000), as detailed in the next figure.

Figure F.2. Effect of moisture on thermal denaturation of pure soy proteins (triangles glycinin, black circles β-

conglycinin) (Sessa, 1992)

The flour sample contained around 7 % of moisture; at such water contents, Td was

expected to be higher than the maximum temperature used during analysis (140 °C).

Rosenthal et al (Rosenthal, 1998), encountered a wide absorption peak between 150-180 °C

for soy flour, while the absorption peaks below 100 °C were negligible. Moreover, soy

flour is a complex system and interaction between proteins and other components (fat) may

have occurred, especially at low moisture contents (Sessa, 1992), which may have affected

Td as well.

It can be concluded that the small peaks at 54 and 90 °C cannot be attributed to soy protein

denaturation. Other thermodynamic changes may have occurred in the flour giving the

above result. It is necessary to increase the temperature of analysis of the water content of

the sample to be able to see the endotherms of the soy proteins.

122

Appendices

Appendix H

H.1. House of Quality (HoQ) method

HoQ represents matrix form or diagram resembling the house and it is the most recognized

for of Quality Function Deployment (QFD). It is utilised by multi-disciplinary team to

translate set of customer requirements (wishes and needs), market research, and technical

engineering data to meet a new product design. HoQ matrix is built of several blocks (see

Figure H.1):

1. Customer requirements (red block)

2. Planning matrix (green block)

3. Technical requirements (purple block)

4. Inter-relationships (yellow block)

5. Roof of the house

Figure H. 1. House of Quality scheme including all blocks (customer requirements, planning matrix, technical

requirements, inter-relationships, and roof)

1. Customer requirements

This is generally the first part of HoQ matrix that has to be completed and also very

important. It documents a structured list of consumer requirements described in their own

words. This information is usually gathered through conversation with customer in which

123

Appendices

they are encouraged to describe their needs and problems. The list of their requirements

gathered in such exercise has to be structured before its entry HoQ matrix.

2. Planning matrix

The planning matrix is attached to right side of HoQ matrix and serves several purposes.

Firstly, it quantifies customers’ requirement priorities and their perception of existing

product. Secondly it allows these properties to be adjusted based on the issues that concerns

design team.

The measures used in this part of HoQ matrix are gathered form questionnaire that

customers filled in before. The first and most important measure is important weighting.

This figure quantifies the relative importance of each of the customer requirements from

their own perspective (described in the left hand side of HoQ). This measure is often shown

alongside the customer requirements description in the block: customer requirements. The

questionnaire is used to collect these important weightings. To demonstrate this in the

Table H.1, example of mayonnaise is presented.

Table H. 1. Planning matrix example of mayonnaise

Rank the following requirements on their relative importance (5 – very important, 1 –

unimportant)

Easy to spread 1 2 3 4 5

Light in colour 1 2 3 4 5

Full mouth-feel 1 2 3 4 5

124

Appendices

Table H. 2. Planning matrix

When combining questionnaire data gathered from a certain and predefined number of

customers, one more thing should be taken into consideration: single market segment. This

means, that HoQ matrix is valid and perform for one market (e.g. Western Europe).

Customers from different regions have different habits in food, beverages, preparation of

meals. If sample includes different market segment, mean figure will not useful nor be of

any value to the product design team.

Moreover, planning matrix provides a measure of the satisfaction of customers with

available/existing products. Customers are asked to consider the performance of each of the

existing products in fulfilling their specified requirements.

3. Technical requirements

This section of HoQ is referred to as the engineering characteristics. It basically describes

the product in terms of the company. This information is generated by company team who

can identify all the measurable characteristics of the product. These measurable

characteristics that are perceived by company team are related with specified customer

requirements. In the same way that customer requirements are analyzed and structured, the

same approach has to be applied to interpret product characteristics.

4. Interrelationships

This section forms the main body of the HoQ matrix and can be very time consuming to

complete. Purpose is to translate the requirements as expressed by the customer into the

product technical characteristics of the product. Structure is simple-standard two

dimensional matrix with cells that relate combinations of individual customer and technical

requirements. The level of interrelationship is weighted usually on four scale point scale

(high, medium, low, none) and a symbol representing this level of interrelationship is

entered into matrix cell.

Imp

ort

ance

Easy to spread 5

Light in colour 2

Full mouth-feel 3

125

Appendices

Figure H. 2. Example of interrelationship matrix (Θ - strong relationship; Ο – medium; ▲- weak relationship)

5. Roof of the House

The triangular “roof” matrix of the HoQ is used to identify where the technical

requirements that characterize the product, support or impede each other. For example, does

improving one requirement cause deterioration or improvement in the other technical

requirement? Where the answer is a deterioration we product design team is going for

another option: engineering trade-off. To keep it structured in the “roof” matrix, a symbol is

entered that represents this (usually ‘-‘). Where improving one requirement automatically

leads to an improvement in the other requirement, an alternative symbol is entered (‘+’).

126

Appendices

Figure H. 3. Example of “roof” matrix (++ strong positive correlation; + positive correlation; - negative

correlation)

This information recorded in the “roof” matrix is useful to the design team in several ways.

It highlights where a focused design improvement could lead to a range of benefits to the

product. Also, it focuses on the negative relationships in the design. These can represent

opportunities for innovative solutions to be developed.

127

Appendices

Appendix I

Solving optimization models with the Lagrange multiplier method

In Chapter 2, optimization was used to maximize the extraction yield of polyphenols as

function of three variables (electric field strength, pulse duration and number of pulses). In

this appendix we will explain how the Lagrange multiplier method can be used to optimize

a given objective function. The general form of an optimization model is as follows:

max 𝑓(𝑥)

s.t.

𝑔𝑖(𝑥) = 𝑏 (P1)

ℎ𝑗(𝑥) > 𝑐

𝑥 > 0

where f(x) is the objective, gi(x) the equality constraints and hj(x) the inequality constraints.

All x’s are positive. To find a local optimum of P1 the Langrange multiplier method could

be used.

The Langrange multiplier method is based on solving the necessary and sufficient

conditions of optimality. We first start with the formulation the so called Lagrangian

function-

𝐿 = 𝑓(𝑥) + ∑ 𝜆𝑖(𝑔𝑖(𝑥) − 𝑏)𝑖 + ∑ 𝜈𝑖(ℎ𝑗(𝑥) − 𝑐)𝑗 (E2)

Where and are the Lagrange multipliers. From the necessary and sufficient conditions

of optimality follows that an optimum x* can be found if the partial derivatives of the

Lagrangian function with respect to the decision variables x and the Lagrange multipliers

are set to zero and solved:

∇𝐿|𝑥∗ = 0 (E3)

The Langrange multiplier method can be demonstrated with a small numerical example.

128

Appendices

Suppose we have following optimization model:

max 𝑓(𝑥) = 𝑥12 + 𝑥2

2

s.t.

𝑔(𝑥) = 2𝑥1 − 5𝑥2 = 0 (P2)

ℎ(𝑥) = 𝑥1 + 𝑥2 = 3

𝑥1, 𝑥2 > 0

We first define the Lagrangian function according to E2:

𝐿 = (𝑥12 + 𝑥2

2) + 𝜆1(2𝑥1 − 5𝑥2) + 𝜆2(𝑥1 + 𝑥2 − 3) (E4)

Now we set the partial derivatives with respect to x and the multipliers to zero:

𝜕𝐿

𝜕𝑥1= 0 = 2𝑥1 + 2𝜆1 + 𝜆2 (E5)

𝜕𝐿

𝜕𝑥2= 0 = 2𝑥2 − 5𝜆1 + 𝜆2 (E6)

𝜕𝐿

𝜕𝜆1= 0 = 2𝑥1 − 5𝑥2 (E7)

𝜕𝐿

𝜕𝜆2= 0 = 𝑥1 + 𝑥2 − 3 (E8)

In this case equations 5 to 8 form a linear system of four equations with four unknowns that

can be solved with for example Gaussian elimination. The optimum is located at x1=2.1429,

x2=0.8571, 1=-0.3673, 2=-3.5510. The objective value at optimum is f=5.3265.

129

Acknowledgements

Acknowledgements

After four years, my PhD journey is approaching the end. For me this was a great adventure

where I met lot of people, I travelled and I learned something about engineering and food.

But all of this would not be possible without amazing people who helped me through all

these years.

First of all I would like to thank Prof. Peter Bongers†. I met him when I was a post master

(PPD) student. You selected me among other students to do the second year project in

Unilever and after six months you offered me to continue with a PhD. Unfortunately, today

you are not among us to see the final result of the project. It was a great pleasure to work

with you.

I would like to thank professor Jan Meuldijk for all the support and understanding I needed

when I moved to his group in 2012. His extensive knowledge as well as supervision helped

me to bring this project till the end.

Especially I would like to thank my daily supervisor Edwin Zondervan. At the beginning

of my PhD, it was not clear who would be my daily supervisor. The decision was made.

Peter Bongers decided that you will be my daily supervisor. It was really a great pleasure

working with you all these years. From all people within the project, you are the only one

that stayed with me till the end. I truly thank you for all meetings, advices, discussions…

Dear Edwin, thank you for pushing me forward and supporting me in difficult moments in

my life.

This project was supported by the Institute for Sustainable Process Technology (ISPT). It

was nice to be part of this consortium. In particular, I would like to thank Frans van den

Akker and Daniella Vrijling.

In addition, I would like to thank Unilever for hosting me in the first three years of the

project. During my PhD I had two nice ladies as my project leaders, Olivera Trifunovic and

Nasim Hooshyar. Also, a word of appreciation to Ardjan Krijgsman, Cristhian Almeida-

Rivera, Hilde Wijngaard, and Hans Hoogland for the valuable input as well as pleasant time

that we had together.

I greatly acknowledge the members of my doctoral committee: prof.dr.ir. M.C. Kroon,

prof.dr.-ing. G. Schembecker, prof.dr.ing. M.H.M. Eppink, dr. O. Trifunovic and ir. G.D.

Mooiweer. Not only for taking part in this committee, but also for the feedback on this

thesis.

130

Acknowledgements

I would also like to thank the other industrial project members Reinoud Noordman from

Heineken, Edwin Poiesz and Tjerk van Mil from Cosun. In addition, prof. Harry Gruppen,

Jean-Paul Vincken, Atze Jan van den Goot, Peter Wierenga from Wageningen University

for the nice discussions and valuable feedback during our project meetings. In addition a

warm word of thanks to my project ladies Alexandra, Annewieke and Laura. Dear ladies, it

was really a pleasure to work and to travel with you.

My special and huge thanks to all my students: Carla, Tugba and Feipeng for your hard

work and contribution to this thesis. I enjoyed working with you guys.

I would like to thank all members from the Chemical Reactor Engineering (SCR) group:

Emila, Dulce, Paola, Shohreh, Lara, Violeta, Carlos, Michiel, Slavisa, Lana, Vladan. I also

thank Denise for help throughout my PhD. A big thank to my officemates: Miguelito,

Tom, Martijn and Arend. Thank you guys for the pleasant trips, coffee breaks, biertjes,

sports and inburgering …

To all the students of the PPD program for all the parties, coffee breaks, drinks in the

FORT and the Zwarte Doos. A big thank to Leontien for all help and support in the last four

years. Big thank to my Serbian crew Dragana and Jovana (mojim Cucama). Ladies you

make my life even more crazy

I would like to thank all my friends in Serbia: Nevena, Smiljka, Irena, Vojkan, Marija,

tetka Ljilja i cika Momir, kumovi Jokici. Hvala na podršci i razumevanju Not to forget

Vucicevic in USA

At the end I would like to thank my family for all support and understanding in the last four

years. I thank my sister Jelena, my nephew Bogdan and brother in law Dusan. Without you

at my side, all of this would not have been possible. Mati, još jedna stepenica, i još jedna

diploma. Kao što ti meni uvek kažeš “najkraćim putem do pobede”.

131

List of publications


Journal Publications

Zderic, A. Mastwijk, H., Zondervan, E., Meuldijk, J. A study of mechanism involved

during polyphenol extraction from fresh tea leaves by pulsed electric field (2015),

submitted to Biosystems Engineering

Zderic, A., Meuldijk, J., Zondervan, E. Product-driven process synthesis for the extraction

of polyphenols from fresh tea leaves (2015), submitted to Industrial and Engineering

Chemistry Research

Zderic, A., Araya-Cluotier, C., Zondervan, E., Meuldijk, J. Isolation of oil bodies from

soybeans in a mild way: definition of operating window for process design (2015),

submitted to Applied Biochemistry and Biotechnology Journal

Zderic, A., Tarakci, T., Almeida-Rivera, C., Meuldijk, J., Zondervan, E. Product-driven

process synthesis for the extraction of oil bodies from soybeans (2015), submitted to American Institute of Chemical Engineers Journal

Peer Reviewed Conference Proceedings

Zderic, A., Zondervan, E., Meuldijk, J. Breakage of Cellular Tissue by Pulsed Electric

Field: Extraction of Polyphenols from Fresh Tea Leaves, Proceeding of the 11th

International Conference on Chemical and Process Engineering (ICheaP 11), 2-5 June

2013, Milan, Italy, pp. 1795-1800

Zderic, A., Tarakci, T., Hooshyar, N., Zondervan, E., Meuldijk, J. Process Design for

Extraction of Soybean Oil Bodies by Applying the Product Driven Process Synthesis

Methodology, Proceeding of the 24th

European Symposium on Computer Aided Process

Engineering (ESCAPE 24), 15-18 June 2014, Budapest, Hungary, pp. 193–198


of polyphenols from fresh tea leaves, Proceeding of the 12th

International Conference on

Chemical and Process Engineering (ICheaP 12), 19-22 May, 2015, Milan, Italy

132


Oral Presentations

Zderic, A., Zondervan, E., Meuldijk, J. Breakage of Cellular Tissue by Pulsed Electric

Field: Extraction of Polyphenols from Fresh Tea Leaves, 11th


Chemical and Process Engineering (ICheaP 11), 2-5 June 2013, Milan, Italy

Zderic, A., Zondervan, E., Meuldijk, J. Extraction of protein in a mild way, Computer

Aided Process Engineering (CAPE Forum), 12-14 May 2014, Milan, Italy

Poster Presentations

Zderic, A., Zondervan, E., Trifunovic, O., Bongers, P. Selective opening and fractionation

of the natural raw material, Netherlands Process Technology Symposium (NPS), 24-26

October 2011, Papendal, The Netherlands

Zderic, A., Zondervan, E., Meuldijk, J. Statistical analysis of data from pulsed electric field

tests to extract polyphenols, 9th

European Congress of Chemical Engineering (ECCE9),

21-25 April 2013, The Hague, The Netherlands

Zderic, A., Tarakci, T., Hooshyar, N., Zondervan, E., Meuldijk, J. Process Design for

Extraction of Soybean Oil Bodies by Applying the Product Driven Process Synthesis

Methodology, 24th

European Symposium on Computer Aided Process Engineering

(ESCAPE 24), 15-18 June 2014, Budapest, Hungary

Zderic, A., Zondervan, E., Meuldijk, J. Pulsed electric field as cell opening method:

extraction of polyphenols from fresh tea leaves, Netherlands Process Technology

Symposium (NPS), 3-5 November 2014, Maarsen, The Netherlands


of polyphenols from fresh tea leaves, Proceeding of the 12th


Chemical and Process Engineering (ICheaP 12), 19-22 May 2015, Milan, Italy

133

Curriculum vitae

Curriculum vitae

Aleksandra Žderić was born on 10 July 1981 in Šabac, Serbia. After finishing secondary

school in 2001, she started Chemical Engineering studies in the Faculty of Technology and

Metallurgy, University of Belgrade. In 2007, she did her graduation project (6 months) at

the Eindhoven University, The Netherlands in the Process Systems Engineering group

under the supervision of prof.dr.ir. Andre de Haan. In 2008 she obtained her Master’s

degree in Chemical Engineering from Belgrade University. Her Master thesis was in the

field of separation technology on the project “Strategies for host-guest extraction of

Immunoglobulin G”. After her Master studies in 2009, she enrolled in the two years Post-

Master program “Process and Product Design”. In 2010 she started the second year project

with Unilever R&D Vlaardingen under the supervision of prof.dr.ir. Peter Bongers and

prof.dr. Jan Meuldijk. She wrote her thesis on “New routes for liquid tea extraction”. In

March 2011 she received her PDEng diploma from Eindhoven University of Technology.

In April 2011, she started her PhD in the field of process and product design on the project

“Selective opening and fractionation of natural raw materials” at the Eindhoven University

of Technology in the group of prof.dr.ir. Peter Bongers and dr.ir. Edwin Zondervan. Since

2012 she moved to the Polymer Reaction Engineering group under the supervision of

prof.dr. Jan Meuldijk and dr.ir. Edwin Zondervan. Her project was sponsored by the

Institute for Sustainable Process Technology (ISPT) in cooperation with several industrial

partners such as Unilever, Heineken, Cosun, DSM and Synthon and her work during this

PhD project led to this thesis.

Documents

Extraction of key components from cellular material ... · PDF fileExtraction of key components from cellular material: aspects of product and process design PROEFSCHRIFT ter verkrijging