ULTRASONIC CUTTING OF CHEESE AND APPLES - Ideals

ULTRASONIC CUTTING OF CHEESE AND APPLES – EFFECT ON QUALITY ATTRIBUTES DURING STORAGE

BY

GULCIN YILDIZ

THESIS

Submitted in partial fulfillment of the requirements for the degree of Master of Science in Food Science and Human Nutrition

with a concentration in Food Science in the Graduate College of the

University of Illinois at Urbana-Champaign, 2013

Urbana, Illinois

Adviser:

Associate Professor Hao Feng

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ABSTRACT

With advantages such as having excellent cut face, reduced smearing, low product lost,

less deformation, less tendency to shatter for brittle products, and being able to handle sticky or

brittle foods, ultrasonic cutting has become increasingly popular in the food processing industry

in recent years. Although a number of publications have documented the use of ultrasound to cut

food with an improved end-product quality, all previous works were focused on ultrasound or

mechanical aspects of cutting process. No study has been published to investigating the effect of

ultrasound cutting on food quality during storage. My thesis research was conducted to

investigate the effect of ultrasound amplitude on the surface appearance and quality of selected

cheese (Cheddar, mozzarella, and Swiss cheese) and fresh cut apples (red delicious and golden

delicious) during storage.

To examine the effect of ultrasonic cutting on quality of cheese products, cheddar,

mozzarella, and Swiss cheeses were chosen because of their popularity. The focus of the

investigation was on quality changes of cheese samples cut with ultrasound and without

ultrasound in three-weeks of storage. Quality attributes such as total color difference, surface

topography, peroxide values, pH, and sensory characteristics (taste, odor, and overall

acceptability) of the samples were compared. General chemical parameters in ultrasonic cut

samples including lipid oxidation and pH value showed significant differences from that of the

Control. In addition, the L (lightness) values of samples cut with and without ultrasound were

significantly different. Furthermore, all cheeses cut with ultrasound showed shiny and smooth

surface appearance, while the surfaces were relatively rough for samples cut without ultrasound.

The microscope images indicated that ultrasonic cutting resulted in a smoother surface compared

to the Control.

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In the experiments with apples, red delicious and golden delicious apples were used

because of their popular use in fresh-cut apples and the rapid browning of slices (especially red

delicious apple which has a high susceptibility to browning) after preparation. The quality of

apple samples cut with and without ultrasound was evaluated for a period of two weeks. A

significant difference in polyphenol oxidase activity and pH levels was found between samples

cut with and without ultrasound. The L (lightness) values of apples cut with ultrasound were

significantly higher than that in the Control. Furthermore, both types of apples cut with

ultrasound exhibited smooth surface appearance, while the surfaces were relatively rough for

samples cut without ultrasound. The environmental scanning electron microscope images

indicated that ultrasonic cutting resulted in a smoother surface compared to the Control. Sensory

evaluation of cut apples by panelists showed that people favored apples cut with ultrasound.

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ACKNOWLEDGEMENTS

This thesis would not have been possible without the assistance of many people whose

contributions I gratefully acknowledge.

First and foremost thanks and appreciations especially go to my advisor and mentor, Dr.

Hao Feng, who has guided me on each step: research process, scientific thinking, writing and

financial support. I am indebted for the opportunity to do my master’s degree under his guidance.

Without his encouragement, I don’t know if I could go further in academics.

I would also like to thank Dr. Keith Cadwallader and Dr. Graciela Padua for their

willingness to serve on my committee and their support and contribution to my thesis

preparation.

My many thanks must also go to my friends and lab mates for their willingness to share

their knowledge of research with me and for their technical assistance. Thank you all for being

with me during all that stressful time.

I am grateful to my parents for their unconditional and endless love and the values they

have instilled in me since my childhood time. Their care, understanding, trust, and guidance are

essential in my quest for a science career.

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TABLE OF CONTENTS

CHAPTER 1: INTRODUCTION …………………………………………………...……………1

CHAPTER 2: LITERATURE REVIEW………………………………………………………….3

2.1 Fresh-Cut Industry………………………………………...……………………..…....3

2.2 Lipid Oxidation….………………………………………………….…….……….…..6

2.3 Ultrasonic Cutting……….………………………………...…..…………………..…..8

2.4 Figures and Tables…………………………………………………………………...10

CHAPTER 3: ULTRASONIC CUTTING OF CHEDDAR, MOZZARELLA AND SWISS

CHEESES – EFFECT ON QUALITY ATTRIBUTES DURING STORAGE………………….14

3.1 Introduction …………………………………………………...…………….….……14

3.2 Materials and Methods …………………………………………………………..…..15

3.3 Results and Discussion …………………………………………..……………….....19

3.4 Conclusion..…………………………………………………………………….…....26


CHAPTER 4: ULTRASONIC CUTTING OF RED AND GOLDEN DELICIOUS APPLES –

EFFECT ON QUALITY ATTRIBUTES DURING STORAGE………………………………..37

4.1 Introduction …………………………………………………...……………….…….37

4.2 Materials and Methods …………………………….……………………….………..39

4.3 Results and Discussion ………………………………..…………………….……....43

4.4 Conclusion. …………………………………………………………………….…....51


CHAPTER 5: OVERALL CONCLUSIONS AND FUTURE WORK………………………….63

REFERENCES …………………………………………………………….………………...….65

APPENDIX A: PREPARATION SOLUTION

FOR PPO ACTIVITY….………………………………………………………………………..78

APPENDIX B: ABSORBANCE VS. TIME CURVE AND SLOPE OF THE CURVE OF RED

DELICIOUS APPLES CUT WITH AND WITHOUT ULTRASOUND FOR THE FIRST

DAY……………………………………………………………………………………………...79

APPENDIX C: ABSORBANCE VS. TIME CURVE AND SLOPE OF THE CURVE OF

GOLDEN DELICIOUS APPLES CUT WITH AND WITHOUT ULTRASOUND FOR THE

FIRST DAY………………………………………………………………………...……………81

APPENDIX D: ABSORBANCE VS. TIME CURVE AND SLOPE OF THE CURVE OF RED

DELICIOUS APPLES TREATED WITH 1% CaA SOLUTION IN COMBINED WITH

ULTRASOUND (50% AMPLITUDE) AND WITHOUT ULTRASOUND FOR THE FIRST

DAY…………………………………………………………………………..………………….83

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APPENDIX E: ABSORBANCE VS. TIME CURVE AND SLOPE OF THE CURVE OF

GOLDEN DELICIOUS APPLES TREATED WITH 1% CaA SOLUTION IN COMBINED

WITH ULTRASOUND (50% AMPLITUDE) AND WITHOUT ULTRASOUND FOR THE

FIRST DAY……………………………………………………………………………..……….84

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CHAPTER 1

INTRODUCTION

Ultrasonic cutting has become increasingly popular in the food processing industry in

recent years as the technology produces cuts of high quality and accuracy (Lucas et al., 2006).

Poor cutting results in crushed, crumbled or torn products with significant waste. With

conventional cutting methods, the multilayered or textured products are smeared and separated.

In addition, portions are misshapen, distorted, overweight or underweight (Mason, 1998). On the

other hand, ultrasound-assisted cutting of food has several advantages such as having excellent

cut face, reduced smearing, low product lost, less deformation, less tendency to shatter for brittle

products, and being able to handle sticky or brittle foods (Rawson, 1998). The quality of food

cut by ultrasound is affected by the food type and conditions such as frozen and thawed (Brown

et al., 2005). Ultrasound-assisted cutting finds applications in the cutting of fragile and

heterogeneous products (cakes, pastry and bakery products), and fatty (cheeses) or sticky

products (Arnold et al., 2009). This cutting method has been used for cutting of cheese, candy

bars, bakery, confectionary products, and other convenience foods (Schneider et al., 2002).

Cheese cutting is an essential operation as many cheese products are sold in sliced or

other cut forms. In addition, the fresh-cut fruit and vegetable market, especially ready-to-eat

sliced apples, has rapidly grown in recent years due to the health benefits associated with these

foods. However, the processing of these foods has a number of problems. A major problem of

minimally processed apples is enzymatic browning. Because of enzymatic browning some fruits

are discarded. Similarly, for cheese products, lipid oxidation is the main concern. To address

2

these issues, this study was undertaken to investigate ultrasonic cutting and its effect on selected

cheese (Cheddar, mozzarella, and Swiss cheese) and apple (red delicious and golden delicious

apple) products.

Although a number of publications have documented the use of ultrasound to cut food

with an improved end-product quality, all previous works were focused on ultrasound or

mechanical aspects of the cutting process. No study has been published to investigate the effect

of ultrasound cutting on food quality during storage. It was hypothesized that ultrasonic cutting

will improve cut surface appearance and quality of food products compared to conventional

cutting methods. The overall objective of this research was to investigate the effect of ultrasonic

cutting on the quality of two types of products, a fatty product (cheese) sensitive to oxidation and

a porous colloidal product (apple) sensitive to browning reaction during storage.

In the study to cut high fat products with ultrasound, the quality changes in 3 selected

cheeses products, i.e., cheddar, mozzarella, and Swiss cheeses cut with and without ultrasound

was examined during a 3-week period under refrigeration conditions. Quality attributes evaluated

included lipid oxidation, pH, color, surface topography, and sensory properties. The effect of

ultrasonic cutting on plant tissues was conducted with apples during a 2-week period under

refrigeration conditions. Besides considering the polyphenol oxidase (PPO) activities of fresh-

cut red delicious and golden delicious apples, other quality attributes similar to that in cheese

quality evaluations were also evaluated, including pH, color, surface morphology, and sensory

properties.

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CHAPTER 2

LITERATURE REVIEW

2.1 Fresh-Cut Industry

2.1.1 Fresh-cut produce

The International Fresh-cut Produce Association (IFPA) defines fresh-cut products as

fruits or vegetables that have been trimmed and/or peeled and/or cut into 100% usable product

that is bagged or pre-packaged to offer consumers high nutrition, convenience, and flavor while

still maintaining its freshness (Lamikanra, 2002).

The fresh-cut fruit and vegetable market has rapidly grown in recent years due to the

health benefits associated with these foods (Luo and Barbosa-Canovas, 1996). Ready-to-eat

sliced apples, for example, are now being offered by fast-food chains and school cafeterias. With

high fiber and low calorie content, precut produce provides busy consumers with healthful

options.

Fresh-cut produce quality is related to appearance, texture, flavor, and nutritional and

safety aspects of fruits and vegetables. Appearance ranks first affecting consumer purchase

preferences (Lund and Snowdon, 2000). In addition, other organoleptic characteristics such as

aroma, taste, and texture impact on purchase decision.

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2.1.2 Problems of fresh cut foods

Fresh-cut fruits perish faster than whole fruits (Cantwell, 1995). The reason for that is

the wounding associated with processing, which causes several changes that impact on the

quality of the produce (Brecht, 1995; Saltveit, 1997). The visual symptoms of deterioration of

fresh-cut produce include changes in color (especially browning at the cut surfaces), loss of

water, and microbial contamination (Brecht, 1995; King and Bolin, 1989; Varoquaux and Wiley,

1994). Even slightly processing such as peeling, cutting, and washing leads to degradation of the

color, texture and flavor (Kabir, 1994; Varoquaux & Wiley, 1994). In addition, when plant

tissues are wounded, nutrient losses may be arisen (Klein, 1987).

Fresh-cut processing increases the problem because of wounding, and increased

metabolic activities which may cause browning, softening, decay, and off-flavor development

(Watada et al., 1990; Varoquax and Wiley, 1994). For instance, cutting of tropical fruit resulted

in increased rates of respiration and ethylene production within minutes (Abe and Watada, 1991)

and may reduce the shelf life from 1-2 weeks to only 1-3 days even at optimal temperatures

(Ahvenainen, 1996). There are several factors effecting the wounding of fruits, including the

number of cuts, the severity of the cutting treatments or the sharpness of cutting blades. Portela

and Cantwell (2001) showed that cutting melon pieces with a blunt blade increased ethanol

concentrations and off-odors compared to melon pieces cut with a sharp blade. In a similar way,

cutting carrots with sharp blades resulted in reduction on softening and microbial growth (Bolin

and Huxsoll, 1991; Barry-Ryan and O’Beirne, 1998).

The unit operations such as peeling and slicing during processing result in the destruction

of surface cells (Brecht, 1995), and additionally removal of natural barriers such as skins in the

case of fruits making the tissues more liable to water loss and deterioration (Altekruse et al.,

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1997; Agar et al., 1999). This leads to an increase in respiration rate and ethylene production

(Saltveit, 1997; Saltveit et al., 2005). Furthermore, reaction between phenols and polyphenol

oxidase (PPO) causes browning discoloration (Martinez and Whitaker, 1995; Heaton and

Marangoni, 1996).

2.1.2.1 Enzymatic browning and polyphenol oxidase (PPO)

In the fresh cut food industry, enzymatic browning has a very important role. This type of

browning discoloration not only reduces the shelf life of several processed foods, but also

negatively impacts the quality of frozen fruits and vegetables (Shewfelt, 1986; Huxsoll and

Bolin, 1989). Because of enzymatic browning almost half of tropical fruits are discarded due to

quality defects (Whitaker, 1996). Even though enzymatic browning causes unwanted

discoloration, it is a desired reaction in some processes like tea and cocoa fermentation (Haard

and Chism, 1996).

The browning is mainly catalyzed by the enzyme polyphenol oxidase (1,2 benzenedio;

oxygen oxidoreductase; EC 1.10.3.1) which is also known as phenoloxidase, phenolase,

monophenol oxidase, diphenol oxidase and tyrosinase (Marshall et al., 2000). When plant tissues

undergo physical damage such as cutting, bruising or blending, PPO is activated by releasing

into the cytosol. In the presence of atmospheric oxygen and PPO, monophenol is hydrooxylated

to o-diphenol and diphenol can be oxidized to o-quinones, which then undergoes polymerization

to yield dark brown polymers (Fig. 2.1).

Polyphenol oxidase is consisted of monophenol oxidase or diphenol oxidase. Previous

studies on fruits and vegetables, such as apple (Goodenough et al., 1983), avocado (Kahn and

Pomerantz, 1980), eggplant (Perez-Gilabert and Carmona, 2000), grape (Ferrer et al., 1989), and

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potato (Ferrer et al., 1993) showed PPO has both types of activities. On the other hand, those

from lettuce (Heimdal el al., 1994), longan (Jiang, 1999), pineapple (Das et al., 1997), field bean

(Paul and Gowda, 2000) and sunflower (Raymond et al., 1993) lack the hydroxylation properties

and act only on o-diphenols. Diphenol oxidase is the most prevalent form of PPO (Yoruk and

Marshall, 2003) and very important due to its leading reactions to form quinones, which produce

brown pigments, named melanin (Marshall et al., 2000).

2.2 Lipid Oxidation

Lipid oxidation refers to the spontaneous reaction of oxygen with unsaturated lipids and

is often noted by its characteristic ‘rancid’ off-flavors and odors by consumers (Schaich et al.,

2013). In addition to producing off-flavors and odors, oxidation of unsaturated lipids can also

decrease the nutritional quality and safety of foods after cooking and processing due to the

formation of secondary reaction products (Frankel, 1980). Lipid oxidation is a main contributor

to quality degradation in both natural and processed foods. In the presence of catalytic systems

such as light, heat, enzymes, and metals, oxidation of lipids has several negative impacts on

foods such as loss of flavor, development of off-flavors, loss of essential amino acids, loss of

color, nutrient value and functionality (Addis, 1986; Shahidi, 2000; Vercellotti et al.,1992).

2.2.1 Mechanism of lipid oxidation

In general, a lipid oxidation process is described as a complex sequence of chemical

reactions between unsaturated fatty acids and active oxygen species (Frankel, 1998; Nawar,

1996; McClements and Decker, 2000; Min and Boff, 2002). Lipid oxidation involves three

7

stages: initiation, propagation, and termination subsequently (Farmer et al., 1943; Farmer and

Sutton, 1943; Bolland, 1945, 1949; Swern, 1961).

A short explanation of the stages is as below and the possible reaction mechanism is

illustrated in Figure 2.2.

1. Initiation: Formation of free radicals

2. Propagation: Free-radical chain reactions

3. Termination: Formation of non-radical products

2.2.2 Measurements of lipid oxidation

Organoleptic evaluation is used by consumers to evaluate the quality of fats and oils.

Rancidity is the objectionable flavors that result from oxidation reaction of lipids. The test can be

done by individuals tasting or smelling the oil. It is possible to prevent human-error by using

several panels for evaluation of odor and taste and then statistical experimental design

conducted. However, this type of analysis has their own disadvantages such as the length of time

requirement and poor reproducibility. To improve the reproducibility, sensitivity, and

quantitativeness, a number of chemical methods were developed to measure lipid oxidation

(Gray, 1978).

Common assessments of lipid oxidation are shown in Table 2.1. The most common

methods are Peroxide Value (PV) and thiobarbituric acid (TBA) tests.

2.2.2.1 Peroxide method

Peroxide Value (PV) is the parameter which measures the amount of peroxides and

hydroperoxides (primary products) formed during oxidation of unsaturated fats and is one of the

8

most common quality indicators of fats and oils during production and storage (Antolovich et al.,

2002; Kanner and Rosenthal, 1992; Riuz et al., 2001). Hydroperoxides and peroxides oxidize

aqueous iodide to iodine, and then the iodine can be titrated with thiosulfate solution and starch

as end-point indicator (Kanner and Rosenthal, 1992). The primary products of lipid oxidation are

hydroperoxides which are generally referred to as peroxides. Therefore, determining the

concentration of peroxides as a measure of the extent of oxidation seems reasonable (Holman,

1954).

2.3 Ultrasonic Cutting

2.3.1 Introduction of ultrasonic cutting

Ultrasonic cutting is different from conventional cutting because the cutting motion is a

superposition of the conventional cutting movement of a blade and the vibrational movement

generated by ultrasound (Schneider et al, 2011). A typical ultrasonic food cutting system

includes four major components: a power supply, a converter, a booster and a cutting horn (or

knife). The ultrasonic power supply (generator) is an electronic device which converts standard

50/60 Hz AC line voltage to a high frequency electrical energy. The ultrasonic converter is a

sealed electro/mechanical device which is responsible to receive the high frequency electrical

energy, at 20 kHz for instance, from the generator and converts it to high frequency mechanical

vibrations using PZT (piezoelectric) ceramic discs. The booster is a metal mechanical amplifier

which will either raise or lower the amplitude of the horn’s mechanical motion, depending on the

arrangement of the masses at each end. The cutting horn, in other words a knife or a blade horn,

is the device that performs the actual cutting (Muccio, 1999).

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2.3.2 Ultrasonic cutting of foods

Ultrasonic cutting has become increasingly popular in the food processing industry in

recent years as the technology produces cuts of high quality and accuracy (Lucas et al., 2006).

Poor cutting results in crushed, crumbled or torn product with significant waste. The

multilayered or textured products are smeared and separated. Portions are misshapen, distorted,

overweight or underweight (Mason, 1998). On the other hand, ultrasound assisted cutting of food

has several advantages such as having excellent cut face, reduced smearing, low product lost,

less deformation, less tendency to shatter for brittle products, and being able to handle sticky or

brittle foods (Rawson, 1998). The quality of food cut by ultrasound is affected by the food type

and conditions such as frozen and thawed (Brown et al., 2005). The most common application of

ultrasound is in the cutting of fragile foodstuffs. It finds uses in the particular cases of fragile and

heterogeneous products (cakes, pastry and bakery products) and fatty (cheeses) or sticky

products (Arnold et al., 2009). The foods such as cheese, candy bars, bakery and confectionary

products and convenience foods are mainly targeted for ultrasonic cutting (Schneider et al.,

2002). Table 2.2 shows some generic types of food products being successfully cut commercially

(Mason, 1998).

General benefits for the ultrasound-induced cutting of food are:

The quality of the cut face is visually excellent

The product is virtually undisturbed

Smearing is reduced

Multilayered products cut easily

Crumb and debris is significantly reduced

Brittle products have less tendency to shatter (Mason, 1998).

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2.4 Figures and Tables

Figure 2.1. Schematic representation of oxidation reaction by PPO

(Caodi, 2007)

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Figure 2.2. Schematic representation of the lipid oxidation mechanism

Initiation RH + Initial → R•

R’-CH=CH-R’’ + O2 → ROOH

Propagation R• + O2 → ROO•

ROO• + RH → ROOH + R•

ROOH → RO• + HO•

Termination R• + R• → Nonradical products

ROO• + ROO• → R1-CO-R2 +R1-CHOH-R2 + O2

(Kanner and Rosenthal, 1992)

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Table 2.1. Common assay for lipid oxidation detection

Principle Assay Reference

Lipid substrate loss Gas chromatography Slater, 1984

Oxygen consumed for oxidation Oxygen uptake assay Slater, 1984

Generation of peroxides,

hydroperoxides

PV assay Kanner and Rosethal, 1992

Formation of malonaldehyde HPLC; TBA at 532 nm;

Fluorescence at 553 nm

Esterbauer et al., 1984

Formation of conjugated dienes OD at 234 nm Recknagel and Glende, 1984

Formation of carbonyl

compounds

GC-MS; HPLC Esterbauer and Zollner,

1989

Formation of free fatty acids Titration; electric

conductivity

Laubli et al., 1986

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Table 2.2. Types of food suitable for ultrasonic cutting

Bakery products Frozen products Fresh products Bread Cream cakes Fish

Pastry Pies Meat

Pies Ice cream Vegetables

Cakes Ice cream cakes Bakery

Swiss rolls Composite Confectionery

Rich fruit cakes Sorbets (not water ices) Biscuits

Date and nut cakes Cakes

Cream cakes Bread

Tarts

Lemon meringue pie

Meringue

Oatmeal biscuits

(Mason, 1998).

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CHAPTER 3

ULTRASONIC CUTTING OF CHEDDAR, MOZZARELLA AND SWISS CHEESES –

EFFECT ON QUALITY ATTRIBUTES DURING STORAGE

3.1 Introduction

Cheese is one of the most popular food products consumed in the world. The average

U.S. cheese consumption increased from 11 pounds per person in 1970 to 31 pounds per person

in 2003 (Buzby, 2005). Mozzarella and cheddar are the two most consumed types of cheeses,

accounting for 20.9% and 36.7% of the total volume sales of natural cheese in the U.S.,

respectively (IDFA, 2010). Cheeses are rich in high-quality protein, calcium, vitamins, minerals,

and essential fatty acids (Wong, 1974). Texture and color are two important criteria used to

evaluate cheese quality; they are often the primary considerations of consumers when making

purchasing decisions (Lebecque et al., 2001). Retail sales of cheeses are primarily in the form of

processed slices, accounting for 74% of the total supermarket sales (IDFA, 2006). In the United

States, processed cheese is produced and sold in various forms such as loaves (20%), slices

(74%), shreds (1.1.%), cubed (0.3%), spreads (4.5%), and others (0.1%) and is used as an

ingredient in numerous products (IDFA, 2006). Cheese cutting is therefore an essential operation

as many cheese products are sold in sliced or other cut forms. Proper cheese cutting is important

to ensure quality of cheese; it is also an area needing more attention from industry and academia.

Although a number of publications have documented the use of ultrasound to cut foods

with an improved end-product quality mainly from visual observations, all previous works were

15

focused on ultrasound or mechanical aspects of the cutting process (Arnold et al. 2009; Zahn et

al., 2005; Zahn et al., 2006;). No study has been published to investigate the effect of ultrasonic

cutting on the physical, chemical, and sensory quality attributes of a food product right after

cutting and during storage. This work was undertaken to investigate the effect of ultrasound

amplitude on the surface appearance and quality of selected cheese products immediately after

cutting and during a 3-week storage period at refrigeration temperature. Lipid oxidation level of

three different types of cheeses (Cheddar, mozzarella, and Swiss cheeses) cut with and without

ultrasound was compared. Color changes, pH, and surface topography (determined with a

SteREO Discovery V20 microscope) of the cheese samples were measured. Finally, a sensory

study was conducted to discern potential changes of Cheddar, mozzarella, and Swiss cheeses cut

with and without ultrasound on days 0 and 21.

3.2 Materials and Methods

3.2.1 Sample preparation

Cheddar, mozzarella, and Swiss cheeses were chosen for this study because of they are

among the most popular cheese products and all sold in cut forms. Cheddar, mozzarella and

Swiss cheeses produced from the same company (Kraft Foods Inc.) were purchased from a local

market in Springfield, IL. Ultrasonic knife was provided by Sonics & Materials, Inc. (Fig. 3.1).

All cheeses were cut without (control) and with ultrasound at three amplitudes (30%, 40%, and

50%) with the ultrasonic knife.

After being cut with and without ultrasound Cheddar, mozzarella, and Swiss cheeses

were kept under refrigeration conditions (0-4 0C) in wax paper for three weeks, and analyses

16

were done right after cutting and once per week during 3 weeks except sensory analysis. Sensory

analysis was done at 0 and 21 days of storage.

3.2.2 Color measurement

Color measurements were done with a Minolta Chroma Meter CR-300 (Minolta Camera

Co. Ltd., Osaka, Japan) by directly holding the device vertically to the surface of the cut

samples. The color meter was calibrated with a white standard plate. The color readings were

expressed by the lightness (L), redness (a, ±red-green) and yellowness (b, ±yellow-blue). For

each sample, three color readings (L, a, and b values) were taken (one at the center, one from the

left side, and the other from the right side of the sample) at room temperature. The averaged L, a,

and b values were reported. For each treatment, colors of 3 replicated samples were measured.

Color readings were taken right after cutting and once per week during the 3-week storage.

3.2.3 pH

For pH measurement, cut samples (2 g each, small cheese pieces got from the cheese

surface using knife) were placed in 30 ml of deionized distilled water (DDW) and homogenized

for 15 seconds using an Osterizer 12 speed blender (450 W) (Kim et al., 2010). The pH changes

of the homogenate were measured using an Accumet Research AR15 pH meter (Fisher

Scientific, USA). Three replications were used. The pH readings were taken right after cutting

and once per week during the 3-week storage period.

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3.2.4 Lipid extraction and oxidation

Cheese samples were extracted with a Soxtec HT 1043 automated soxhlet extraction unit

following the method described by Soxhlet in 1879 and Priego-Capote et al. (2004) with

modifications. In brief, the cheese samples (10 g, with 2 replications) were dried, ground into

small particles using Osterizer 12 speed blender (450 W), and placed in a Whatman cellulose

extraction thimble and covered with a cotton plug. Extraction cups were filled with 50 milliliters

of hexane. A Thermo Neslab RTE 7 water bath set at 15°C was connected to the extraction unit.

The extraction thimbles were immersed in the boiling solvent for four hours, then raised above

the extraction cup, and rinsed for another four hours. The condenser valves were then closed and

the fan was turned on for approximately twenty minutes for evaporation. After that, the mixture

of lipids and hexane was put into a Precision 14 EG oven (Precision Scientific Inc., Chicago, IL)

at 105 0F and dried for 4 hours to remove all hexane from the mixture. After removal of residual

solvent, the extracted lipid was exposed to a peroxide value test in order to determine lipid

oxidation level of the cheeses. Lipid oxidation was assessed using peroxide value (PV) followed

the AOCS (1998; Cd 8-53) method. Five grams of extracted samples from the cheeses cut with

and without ultrasound were weighed into a 250 mL Erlenmeyer flask with addition of 30 ml

acetic acid - chloroform (3:2) solution. The flask was swirled until the samples were dissolved

and added 0.5 ml saturated potassium iodide (KI) solution. Waited for one minute and then

added 30 ml distilled water. The solution was titrated with 0.01 N sodium thiosulfate (Na2S2O3)

with constant and vigorous shaking. The liberated iodine (I2) was then titrated until the color

changed to light yellow. Added 0.5 ml of 1% soluble starch indicator which gave the solution a

blue color. Shaking the flask vigorously near the endpoint which was a faint blue color in order

to release all of the iodine from the chloroform (CHCl3) layer. Then, the sodium thiosulfate

18

(Na2S2O3) drop-wise until the blue color just disappeared was added. The PV was calculated and

reported as milliequivalents of oxygen per kilogram of sample (meq/kg).

The peroxide value as meq of peroxide /kg of oil was calculated according to the following

formula:

[meq. / kg]

where S = volume of thiosulfate solution (Na2S2O3) required to titrate the sample [ml];

M = 0.01, the concentration of the Na2S2O3 solution.

3.2.5 Sensory evaluation

Panelists (n =7) were used to evaluate sensory properties of the cheeses treated with and

without ultrasound. The sensory parameters were color, odor, taste, overall acceptability, and

off- odor. A 7-point hedonic scale was provided to the panelists as follows: like very much (7),

like moderately (6), like slightly (5), neither like nor dislike (4), dislike slightly (3), dislike

moderately (2), and dislike very much (1). For off-odor, no off-odor (1) and very strong off-odor

(7) were provided. Sensory analysis was done at 0 and 21 days of storage. (Kim et al., 2010).

3.2.6 Surface appearance and surface topography

Photos of the cheddar, Swiss and mozzarella cheeses cut with and without ultrasound

were taken by camera (Sony Cyber-Shot DSC-W570 16.1 MP Digital Still Camera). Surface

topography of the samples was measured by a digital stereo-microscope (ZEISS-SteREO:

Discovery.V20). In order to determine surface profile, samples were cut with and without

ultrasound into 4” × 4” pieces. After the placement of the specimens on the base, the images of

19

surface topography of cheddar, mozzarella, and Swiss cheeses were obtained with a Zeiss

Axiocam MRc color camera associated with the microscope (Zoom factor: 20, magnification:

30×, working distance: 30 mm).

3.2.7 Statistical analysis

Three replications for each treatment were used for all measurements, unless otherwise

stated. The results were analyzed statistically by analysis of variance using the General Linear

Models (PROC GLM) procedure in SAS (version 9.3, SAS Institute, Inc., Cary, North Carolina,

USA). Differences among the mean values were obtained by Fisher's least significant difference

(LSD) test at alpha=0.05.

3.3 Results and Discussion

3.3.1 Color changes

The color changes of the cheddar, mozzarella and Swiss cheeses cut with and without

ultrasound are shown in Tables 3.1, 3.2, and 3.3. The L (lightness) values of all ultrasound cut

cheeses were significantly higher than the control for all storage times. The L values increased

with an increase of ultrasound amplitude in all the samples, and the highest L value was observed

for the samples cut with 50% amplitude. No significant changes were observed between cheeses

cut with ultrasound and w/o ultrasound in their a (redness) and b (yellowness) values during 3

weeks of storage. The L values decreased slightly with the storage time in all the samples

(Cheddar, mozzarella, and Swiss) and all treatments (0%, 30%, 40%, and 50% amplitude). The

highest L value was observed for the samples on day 0, and the lowest L value was observed for

the last (third) week samples. Especially, a significant decrease in L values was observed

20

between day 0 and day 21 of the Swiss cheese cut w/o ultrasound. The a values slightly

increased with the storage time in all the samples. Similarly, the b values in all cheeses slightly

increased during storage, with the lowest b values observed on day 0 (all types of cheeses and

methods as well) and the highest observed on day 21.

Color is an important quality attribute of cheese, and it can range from pale yellow to

deep red-orange, depending on the production method and consumer preference (EL-Nimr et al.,

2010). The color of a food product is mostly due to the presence of natural colorant(s). Color can

also be changed by enzymatic and non-enzymatic reactions (Francis, 1980). Usually, a decrease

in L value indicates browning development (Rico et al., 2007). In this study, the browning of the

cheese was monitored using the L*a*b system. The L (lightness) values of all types of cheeses

and treatments decreased, while a (redness) and b (yellowness) increased during the storage,

indicating browning activities. Piergiovanni et al. (1989) found a similar result from a model

cheese system, for which zero-order kinetics was found to yield an adequate description of the

non-enzymatic browning at 20 0C, 25

0C and 30

0C. During peeling and cutting operations, if the

equipment used is not in the best condition, for example, if dull knives and blades are used,

damage to the product will occur; thus, the sharpness of knife blades can significantly affect

product quality (Bolin et al., 1977). In addition, browning is easy to develop when the product is

cut because the cut surfaces allow oxygen in the air to react with the enzyme and other chemicals

(Brecht, 1995). In ultrasonic cutting, less damage and a relatively smooth surface was observed

on the cheese surfaces (Figure 3.2 & 3.3). Cheese samples cut with ultrasound were less

susceptible to browning development or lipid oxidation. This can be attributed to less surface

damage and relatively smooth cut surface from ultrasonic cutting that reduce the surface area and

thus access of oxygen responsible to lipid oxidation and subsequent color changes. Barnicoat

21

(1950) studied the mechanism of discoloration in cheeses and concluded that it was resulted from

oxidation and the more open-textured cheeses tended to be more discolored. Additionally,

ultrasonic cutting reduced the contact time of the knife with cheese. The contact time between

the knife and the cheeses was 1.2 seconds for the samples cut with 50% amplitude ultrasound

and 2.1 seconds for the samples cut w/o ultrasound. Results of visual color evaluations by the

panelists showed that even though there were slight differences between samples cut with and

w/o ultrasound, people liked the color of cheeses cut with ultrasound compared to the cheeses cut

without ultrasound.

3.3.2 pH changes

The pH changes measured at room temperature for cheddar, Swiss and mozzarella

cheeses treated with and without ultrasound are shown in Table 3.4. The pH values of the

cheddar cheese were in the range of 5.63 to 6.07 on day 0, and they were from 5.82 to 5.98 for

the Swiss cheese, and 5.78 to 5.86 for the mozzarella cheese, respectively. The changes in pH

values of three cheeses followed the same trend in the following storage times. A decrease in pH

values was recorded for all types of cheeses cut with ultrasound during three weeks. The pH

values increased slightly with the storage time in all samples (Cheddar, mozzarella, and Swiss)

and all methods (0%, 30%, 40%, and 50% amplitude). The lowest pH value was observed for the

samples on day 0, and the highest pH value was observed for the last (twenty-first) day samples.

This is in agreement with the work of Hassan et al. (2004) who reported a slight increase in pH

during storage for Cheddar cheese. Changes in pH plays an important role in the development of

the texture and a decrease in pH is a main determinant of the hardness and fracture properties of

cheese (Fox et al., 1993; Creamer & Olson, 2005). The pH changes reported in this study might

22

be due to the surface textural changes during cutting since during ultrasonic cutting the texture of

cheeses did not get any severe damages compared to the cheeses cut w/o ultrasound. The pH of

cheese is an important attribute that influences its quality (Upreti & Metzger, 2007). Cheeses

that have a higher pH values spoil most quickly. Conversely, cheeses have low pH and low water

activity retain their desirable eating qualities for long periods (Ledenbach & Marshall, 2010). It

is therefore a favorable outcome when the pH values of cheeses were lowered by ultrasonic

cutting.

3.3.3 Lipid oxidation

The peroxide values (PV) of cheddar, Swiss and mozzarella cheeses as affected by

treatment and storage time are tabulated in Table 3.5. On day 0, no lipid peroxidation was

observed. Starting from day 7, lipid peroxidation was detected. The peroxide values of the

cheddar cheese were in the range of 3 to 4.5 meq/kg, and they were from 3 to 5 meq/kg for the

Swiss cheese, and 2 to 3.5 meq/kg for the mozzarella cheese, respectively. The peroxide values

for all three cheeses kept increasing on day 14 and reached the highest values on day 21. The

ultrasonic cutting helped to reduce lipid peroxidation, as shown by lower peroxide values in the

ultrasound cut cheeses, especially in the samples cut with 50% amplitude ultrasound. Even

though for the fourteenth and twenty-first days there was no significant differences between

samples cut with and w/o ultrasound, a decrease in PV was observed for the samples cut with

ultrasound for all types of cheeses.

The oxidation in the Swiss cheese was more pronounced as shown by higher PV values

during storage. The PV values in the cheddar were moderate while those in the mozzarella were

the lowest. Cheddar whey is more prone to lipid oxidation than mozzarella whey, resulting in a

23

higher concentration of rancid flavors such as sour aromatic and cardboard notes. Researchers

believe that the mesophilic starter cultures used in Cheddar manufacturing initiate the oxidation

process and produce more rancid off-flavors compared with thermophilic starter cultures used in

mozzarella manufacturing (Campbell et al., 2011a,b). It might be the reason why the PV values

in cheddar cheese were higher compared to the mozzarella cheese. Sensory evaluation of cheeses

by panelists supported the result. Even though no off-odor was observed for all types of cheeses

on both days 14 and 21, the panelists that evaluated the cheeses odor gave the highest scores to

Mozzarella cheeses where the least lipid peroxidation (i.e. lowest PVs) was reported among the

cheese samples.

The amount of peroxides of lipids indicates the degree of primary oxidation and therefore

its likeliness of becoming rancid. A lower number of peroxides indicate a good quality of oil and

a good preservation status. A suggested limit of peroxide value for quality and acceptability of

oils for human consumption is 8 meq/kg (Boran et al. 2006). The data reported in this work

demonstrated that cheeses cut with ultrasound were less susceptible to lipid peroxidation. This

may be due to the fact that the cut samples had less open/damaged surfaces and thus less

exposure to air/oxygen compared to those cut with a conventional cutting method.


Table 3.6 show scores of visual evaluation on cheddar, Swiss and mozzarella cheeses

treated by ultrasound and w/o ultrasound on day 0 and day 21, respectively. The panel seemed to

like the colors of ultrasound cut cheeses slightly more than the control as can be seen by higher

scores for all ultrasonic cut cheeses. However, the differences in color scores between the

ultrasound cut cheeses and the control were not significantly different. Since visual color

24

evaluation is a measure of the overall liking of the individuals on the color of the cheeses, it is

understandable that it did not yield a significant difference among the treated samples while the

machine color readings in L values reported significant differences. This may be caused by the

fact that the visual color scores were from seven individual who may have different color

perception of cheese whereas the L values were from a single instrument and thus were with less

variation. Similarly, the differences among the treatments for other visual quality parameters,

i.e., odor, taste and overall acceptability were not statistically different, although slightly higher

scores were reported for the ultrasound cut samples. In addition, on days 0 and 21, no off-odor

was detected by panelists (n=7) for all 3 types of cheeses and treatments (control, with 30%,

40%, and 50% amplitude). The sensory scores of all three cheeses on day 21 were lower

compared to that on day 0, showing a quality degradation during the 3-week storage. Among the

samples, the lowest sensory scores for color, odor, taste, and overall acceptability were reported

in the Swiss cheese. The lower scores of Swiss cheese in the sensory tests may be a reflection of

the preferences of the panel among the cheese types rather than being an indication of the overall

quality the Swiss cheese among the three cheese types.

3.3.5 Surface topography and surface appearance

The surface topography of cheddar, Swiss and mozzarella cheeses cut with and without

ultrasound obtained by Zeiss SteREO is shown in Figure 3.2.

It can be seen that the surfaces of cheeses from ultrasonic cutting were smooth (Fig. 3.2a,

3.2c, and 3.2e), and that cut without ultrasound were rough (Fig. 3.2b, 3.2d, and 3.2f). Schneider

et al. (2011) observed the plastic deformation of cutting surfaces of some products such as short

pastry dough, hamburger bun, and multiple-layer bakery products were avoided with ultrasonic

25

cutting. In addition, a better quality of the cutting surface and less damaged product structure

was observed for yeast dumplings, hamburger buns, and whole-grain bread after ultrasonic

cutting (Zahn et al., 2005). It is known that ultrasonic cutting reduces the friction between the

blade and the product (i.e. cheese) (Feng and Yang, 2005) and thus less tearing and relocation of

the materials on cheese surfaces is expected. The relatively smooth surface of cheeses cut with

ultrasound can thus be attributed to the reduced friction and resistance to cutting. There is also a

difference among the 3 cheeses on their surface topography. The Swiss cheese samples exhibited

a much rougher surface topography compared to the others when observed with under a

magnification of 30. Cutting with ultrasound can cause a secondary effect, resulting in a rise of

cut surface temperature due to absorption of acoustic energy (Schneider et al., 2011). The small

“lumps” on the surface of Swiss cheese may be an indication of melting of the fat due to heat for

the fat fractions in Swiss cheese with a low melting point.

The impact of ultrasonic cutting on the appearance of cut surface of cheddar, Swiss and

mozzarella cheeses is shown in Figure 3.3. All cheeses cut with ultrasound showed shiny and

smooth surface, while the surfaces were less smooth for cheeses cut without ultrasound. An

overall color change among the three cheese types when the ultrasound amplitude increased from

0 to 50% can be observed in Fig. 3.3; the cheese turned to a whiter and less yellow color. This

observation was in good agreement with the Hunter L (lightness) readings, and was especially

true for Swiss cheeses cut with ultrasound. Sensory evaluations of panelists showed that people

liked the lighter color of cheeses and all types of cheeses cut with ultrasound were given higher

scores in color evaluation.

26

3.4 Conclusion

Cheese is a dynamic system; it continuously undergoes microbial, enzymatic and

chemical modifications. For cheddar, mozzarella, and Swiss cheese types, the focus of the

investigation was on quality changes of cheese samples cut with and without ultrasound during a

three-week storage period. General chemical parameters in ultrasonic cut samples such as lipid

oxidation as well as the pH-value showed significant differences. The ultrasonic cutting helped

to reduce lipid peroxidation, as shown by lower peroxide values in the ultrasound cut cheeses,

especially in the samples cut with 50% amplitude ultrasound. Even though for the fourteenth and

twenty-first days there was no significant differences between samples cut with and w/o

ultrasound, a decrease in PV was observed for the samples cut with ultrasound for all types of

cheeses. Moreover, a decrease in pH values was recorded for all types of cheeses cut with

ultrasound during three weeks. The pH values increased slightly with the storage time in all

samples (Cheddar, mozzarella, and Swiss) and all methods (0%, 30%, 40%, and 50% amplitude).

The lowest pH value was observed for the samples on day 0, and the highest pH value was

observed for the last (twenty-first) day samples. In addition, the L (lightness) values of samples

cut with ultrasound and w/o ultrasound showed significant differences. The L values increased

with an increase of ultrasound amplitude in all the samples, and the highest L value was observed

for the samples cut with 50% amplitude. The L values decreased slightly with the storage time in

all the samples (Cheddar, mozzarella, and Swiss) and all treatments (0%, 30%, 40%, and 50%

amplitude). The highest L value was observed for the samples on day 0, and the lowest L value

was observed for the last (twenty-first) day samples. Furthermore, all cheeses cut with ultrasound

showed shiny and smooth surface appearance, while the surfaces were relatively rough for

27

samples cut without ultrasound. The microscope images indicated that ultrasonic cutting resulted

in a smoother surface compared to the Control. In visual quality evaluation, the panel seemed to

like the colors of ultrasound cut cheeses slightly more than the control. However, the differences

in color scores between the ultrasound cut cheeses and the control were not significantly

different. Similarly, the differences among the treatments for other visual quality parameters, i.e.,

odor, taste and overall acceptability were not statistically different, although slightly higher

scores were reported for the ultrasound cut samples. In addition, on days 0 and 21, no off-odor

was detected by panelists (n=7) for all 3 types of cheeses and treatments (control, with 30%,

40%, and 50% amplitude). The sensory scores of all three cheeses on day 21 were lower

compared to that on day 0, showing quality degradation during a 3-week storage period. Overall,

cheeses cut with ultrasound showed a better quality during storage compared to the control.

28


Figure 3.1. Ultrasonic knife used for cutting tests (Sonics& Materials, Inc.)

Booster

Cutting horn

Power supply

Converter

29

Table 3.1. Changes in L (lightness) values for cheddar, Swiss and mozzarella cheeses treated

with ultrasound and w/o ultrasound during a three-week period

Sample and amplitude (%) L ( lightness) values

Day 0 Day 7 Day 14 Day 21

Cheddar cheese

0% amplitude 68.287c (x)

67.933b (x)

65.537b (x)

64.890b (x)

30% amplitude 69.703b (x)

68.777ab (x)

66.693b (x)

66.777b (x)

40% amplitude 70.363ab (x)

70.120a (x)

66.883b (x)

66.900b (x)

50% amplitude 70.750a (x)

70.263a (x)

68.857a (x)

68.230a (x)

Mozzarella cheese


78.940b (x)

78.363b (x)

73.173b (x)

30% amplitude 80.563b(x)

78.963b (x)

78.067b (x)

76.640a (x)


78.720b (x)

79.367b (x)

76.950a (x)


81.097a (x)

80.967a (x)

77.380a (x)

Swiss cheese

0% amplitude 73.780c (x)

73.523b (x)

72.077c (x)

55.183b (y)


75.450ab (x)

72.597bc (x)

71.870a (x)


76.103a (x)

75.617ab (x)

73.623a (x)


76.383a (x)

76.063a (x)

74.467a (x)

a-c Treatment means within treatments (columns) with the same letter in each sample are not significantly different

(p<0.05).

x-y Treatment means within time (rows) with the same letter in each sample are not significantly different (p<0.05).

30

Table 3.2. Changes in a (redness) values for cheddar, Swiss and mozzarella cheeses treated with

ultrasound and w/o ultrasound during a three-week period

Sample and amplitude (%) a (redness) values


Cheddar cheese


12.567a (x)

12.817a (x)

13.827a (x)


12.567a (x)

12.353a (x)

13.207a (x)


12.567a (x)

12.800a (x)

13.421a (x)


12.567a (x)

12.760a (x)

13.723a (x)

Mozzarella cheese

0% amplitude -5.280a (x)

-5.140

a (x) -5.100

a (x) -4.640

a (x)


-5.117a (x)

-5.113a (x)

-4.530a (x)


-5.114a (x)

-4.980a (x)

-4.530a (x)


-5.053a (x)

-4.960a (x)

-4.600a (x)

Swiss cheese


-4.098a (x)

-3.490a (x)

-3.360a (x)


-4.185a (x)

-3.560a (x)

-3.412a (x)


-4.183a (x)

-3.580a (x)

-3.400

a (x)


-4.087a (x)

-3.580a (x)

-3.352a (x)

a Treatment means within treatments (columns) with the same letter in each sample are not significantly different

(p<0.05).

x Treatment means within time (rows) with the same letter in each sample are not significantly different (p<0.05).

31

Table 3.3. Changes in b (yellowness) values for cheddar, Swiss and mozzarella cheeses treated

with ultrasound and w/o ultrasound during a three-week period

Sample and amplitude (%) b (yellowness) values


Cheddar cheese


56.567a (x)

59.540a (x)

59.800a (x)


56.823a (x)

59.540

a (x)

59.730

a (x)


55.800a (x)

59.540a (x)

60.067a (x)


56.650a (x)

59.540a (x)

60.067a (x)

Mozzarella cheese


21.453a (x)

23.693a (x)

24.470a (x)


21.633a (x)

23.633a (x)

25.150a (x)


21.830a (x)

23.047a (x)

25.153

a (x)


21.930a (x)

23.100a (x)

24.470a (x)

Swiss cheese


29.010a (x)

30.093a (x)

30.981a (x)


29.221a (x)

29.033a (x)

31.190a (x)


29.220a (x)

29.173a (x)

31.190a (x)


29.080a (x)

28.863a (x)

31.713a (x)


(p<0.05).


32

Table 3.4. Changes in pH for cheddar, Swiss and mozzarella cheeses treated with ultrasound and

w/o ultrasound during a three-week period

Sample Treatment Amplitude pH changes


Cheddar cheese cut w/o ultrasound 0% 6.07a (x)

5.97a (x)

6.03a (x)

6.08a (x)

cut with ultrasound 30% 5.87b (x)

5.88ab (x)

5.81b (x)

6.05a (x)


5.84b (x)

5.75bc (x)

6.02a (x)

cut with ultrasound 50% 5.63c (x)

5.78b (x)

5.71c (x)

5.90b (x)

Mozzarella cheese cut w/o ultrasound 0% 5.86a (x)

5.86a (x)

5.93a (x)

5.93a (x)

cut with ultrasound 30% 5.84ab (x)

5.73ab (x)

5.88ab (x)

5.88a (x)


5.71ab (x)

5.84ab (x)

5.82b (x)


5.60b (x)

5.78b (x)

5.79b (x)

Swiss cheese cut w/o ultrasound 0% 5.98a (x)

5.94a (x)

5.95a (x)

5.98a (x)


5.81b (x)

5.82b (x)

5.87b (x)


5.79b (x)

5.81b (x)

5.85b (x)


5.77b (x)

5.65c (x)

5.84c (x)


(p<0.05).


33

Table 3.5. Peroxide values for cheddar, Swiss and mozzarella cheeses treated with ultrasound

and w/o ultrasound during a three-week period

Sample Treatment Amplitude Peroxide values (meq/kg)


Cheddar cheese cut w/o ultrasound 0% Nd

4.5a (z)

8a (y)

11a (x)

cut with ultrasound 30% Nd 4ab (z)

8a (y)

11a (x)

cut with ultrasound 40% Nd

3b (z)

7a (y)

10a (x)


3b (z)

5

a (y) 10

a (x)

Mozzarella cheese cut w/o ultrasound 0% Nd

3.5a (z)

6a (y)

9a (x)

cut with ultrasound 30% Nd 3ab (z)

6a (y)

8a (x)


2.5ab (z)

5a (y)

8a (x)


2b (z)

5a (y)

7.5a (x)

Swiss cheese cut w/o ultrasound 0% Nd

5a (z)

8a (y)

13a (x)

cut with ultrasound 30% Nd 4.5a (z)

7a (y)

12a (x)


4a (z)

7a (y)

10a (x)


3b (z)

7a (y)

10a (x)

a-b Treatment means within treatments (columns) with the same letter in each sample are not significantly different

(p<0.05).

x-z Treatment means within time (rows) with the same letter in each sample are not significantly different (p<0.05).

Nd: Not detected

34

Table 3.6. Sensory attributes changes for cheddar, Swiss and mozzarella cheeses treated with

ultrasound and w/o ultrasound during a three-week period

Amplitude (%) Color Odor Taste Overall acceptability

Day 0 Day 21 Day 0 Day 21 Day 0 Day 21 Day 0 Day 21

Cheddar cheese


5.57a (x)

5.57a (x)

5.50a (x)

6.00a (x)

5.79a (x)

6.07a (x)

5.79a (x)


5.71a (x)

5.71a (x)

5.50a (x)

6.00a (x)

5.86a (x)

6.07a (x)

5.93a (x)


5.64a (x)

5.71a (x)

5.57a (x)

6.14a (x)

5.93a (x)

6.14a (x)

5.93a (x)


6.00a (x)

5.71a (x)

5.57a (x)

6.14a (x)

5.93a (x)

6.21a (x)

6.00a (x)

Mozzarella cheese


5.57a (x)

6.00a (x)

5.57a (x)

5.71a (x)

5.50a (x)

5.86a (x)

5.57a (x)


5.64a (x)

6.00a (x)

5.86a (x)

5.71a (x)

5.57a (x)

5.93a (x)

5.57a (x)


5.57a (x)

6.00a (x)

5.86a (x)

5.79a (x)

5.57a (x)

5.93a (x)

5.64a (x)


5.71a (x)

6.14a (x)

6.00a (x)

5.86a (x)

5.64a (x)

6.00a (x)

5.64a (x)

Swiss cheese


4.71a (y)

5.29a (x)

5.21a (x)

5.14a (x)

3.86a (y)

5.36a (x)

4.79a (y)


4.79a (y)

5.50a (x)

5.29a (x)

5.29a (x)

4.00a (y)

5.36a (x)

4.79a (y)


4.71a (y)

5.50a (x)

5.29a (x)

5.14a (x)

4.14a (y)

5.43a (x)

4.79a (y)


4.93a (y)

5.64a (x)

5.50a (x)

5.29a (x)

4.14a (y)

5.50a (x)

4.86a (y)


(p<0.05).


* On days 0 and 21, no off-odor was detected by panelists (n=7) for all 3 types of cheeses and treatments (control,

with 30%, 40%, and 50% amplitude).

35

Figure 3.2. Surface topography of cheddar, Swiss and mozzarella cheeses cut with and without

ultrasound

(a) cheddar cheese cut with ultrasound (50% amplitude-30x magnification); (b) cheddar cheese cut without

ultrasound (30x magnification); (c) mozzarella cheese cut with ultrasound (50%amplitude-30x magnification); (d)

mozzarella cheese cut without ultrasound (30x magnification); (e) Swiss cheese cut with ultrasound (50%amplitude-

30x magnification); (f) Swiss cheese cut without ultrasound (30x magnification).

36

Figure 3.3. Impact of ultrasonic cutting on the appearance of cut surface of cheddar, Swiss and

mozzarella cheeses

(a) cheddar cheese cut without ultrasound; (b) cheddar cheese cut with 30% amplitude; (c) cheddar cheese cut with

40% amplitude; (d) cheddar cheese cut with 50% amplitude; (e) mozzarella cheese cut without ultrasound; (f)

mozzarella cheese cut with 30% amplitude; (g) mozzarella cheese cut with 40% amplitude; (h) mozzarella cheese

cut with 50% amplitude; (i) Swiss cheese cut without ultrasound; (j) Swiss cheese cut with 30% amplitude; (k)

Swiss cheese cut with 40% amplitude; (l) Swiss cheese cut with 50% amplitude.

37

CHAPTER 4

ULTRASONIC CUTTING OF RED DELICIOUS AND GOLDEN DELICIOUS APPLES

– EFFECT ON QUALITY ATTRIBUTES DURING STORAGE

4.1 Introduction

The fresh-cut fruit and vegetable market has grown rapidly in recent years due to

consumers’ demand for fresh, convenient and nutritious foods (Luo et al., 2011). Currently,

ready-to-eat sliced apples have been distributed to fast-food and grocery chains and also

approved for school lunch programs in the US. However, the production of fresh-cut fruits and

vegetables are facing two challenges, one is the preservation of their quality during storage and

the other is microbial safety. The major quality problem of minimally processes apples is

enzymatic browning (Kim et al., 1993). The cells of apples and other products such as pears,

bananas, peaches, potatoes contain an enzyme called polyphenol oxidase (PPO) or tyrosinase.

When the enzyme is in contact with oxygen, it causes biochemical conversion of plant phenolic

compounds to brown pigments known as melanins. The browning can be seen when the fruit is

cut or bruised because these actions damage the cells and allow oxygen in the air to react with

the enzyme and other chemicals. This reaction occurs at warm temperatures when the pH of the

plant tissues is between 5.0 and 7.0. Enzymatic browning also speeds up by the presence of irons

from a rusted knife or copper bowl. Portela and Cantwell (2001) showed that cutting melon

pieces with a blunt blade resulted in increased ethanol concentrations and off-odors compared to

the melon pieces cut with a sharp blade. In a similar way, carrots cut with sharp cutting blades

38

showed reduced softening and microbial growth (Bolin and Huxsoll, 1991; Barry-Ryan and

O’Beirne, 1998). On the other hand, there are several ways to prevent the browning. For

example, the reaction can be slowed or prevented by inactivating the enzyme with heat, reducing

the pH on the surface of the fruit (by adding lemon juice or another acids), reducing the amount

of available oxygen (by putting cut fruit under water or vacuum packing it), or by adding certain

preservative chemicals (like sulfur dioxide). Studies have been conducted to develop strategies to

prevent enzymatic browning. Apple slices were packaged by different modified atmosphere

(N2/CO2) methods at 0 °C by Annese et al. (1997). However, the methods were not effective; the

high phenolic contents in fresh-cut apples and pears seemed to have decreased the effectiveness

of high CO2 packaging. Gorny (1997) concluded that the reduction of O2 levels to near 0% was

necessary to prevent polyphenol oxidase (PPO) browning of many fresh-cut fruits. Another

approach is using reducing agents such as ascorbic acid or sodium erythorbate (isoascorbate) to

prevent the browning of apple slices (Sapers et al., 1990).

Because of the advantages associated with ultrasonic cutting, this new cutting method has

been proposed for cutting of fresh produce by the industry and academia. It is expected that

cutting produce with ultrasound will help to resolve the current problems facing the industry and

may also provide improved product quality. To the best of our knowledge, there is no

documented research that has explored cutting apples or other produce with an ultrasonic device.

The purpose of this pilot project was to test the concept of cutting apples with an ultrasonic knife

with a focus on the effect of cutting on the quality of cut apples. Specifically, the effects of

ultrasound amplitude on the surface appearance and selected quality indexes of two apple

varieties right after cutting and during 2-week storage at refrigeration temperature were

examined. Polyphenol oxidase (PPO) activities, the enzyme responsible for post-harvest

39

browning, of red delicious and golden delicious apples cut with and without ultrasound were

compared. Color changes, pH, surface morphology (determined with an Environmental scanning

electron microscope) of the samples were measured. A sensory study was conducted to discern

potential changes of the cut apples during 2 weeks. Finally, the PPO activity of the apple samples

treated by a CaA solution were measured during storage.

4.2 Materials and Methods

4.2.1 Sample preparation

Red delicious and golden delicious apples were chosen for this study because of their

popularity and rapid browning of cut pieces. The red delicious apples are especially

susceptibility to browning. Red delicious and golden delicious apples (Washington Apple

Commission) were purchased from a local market in Springfield, IL. Ultrasonic knife was

provided by Sonics& Materials, Inc. (Fig.3.1). All apples were cut without (Control) and with

ultrasound at three amplitudes (30%, 40%, 50%) by avoiding the core with an ultrasonic knife.

Cut apples were placed into the polyethylene bags and kept in the refrigerated conditions (0-4

0C) for two weeks with samples taken for analysis at the 0, seventh and fourteenth days.

4.2.2 Color measurement

Colors of the sample surfaces were measured with a Minolta Chroma Meter CR-300

(Minolta Camera Co. Ltd., Osaka, Japan) by directly holding the device vertically to the surface

of the samples. The color meter was calibrated with a white standard plate. The numerical values

of the color readings were expressed by the lightness (L), redness (a, ±red-green) and yellowness

40

(b, ±yellow-blue). For each samples color values (L, a, and b) were read 5 times at different

locations on the sample surface (one reading was from the center, one from the left-top side, one

from the right-top side, one from the left-bottom, and one from right-bottom of the sample) at

room temperature. Then these values were averaged, and only one number was obtained for L, a,

and b values. For color analysis, 3 replications were used. Color analysis was done for the 0,

seventh and fourteenth days.

4.2.3 pH

Two grams of apple pieces (obtained from the apple surface using a knife) and 30 ml of

deionized distilled water (DDW) were homogenized for 15 seconds using an Osterizer 12 speed

blender (450 W) (Kim et al., 2010). The pH changes of the homogenate were measured using an

Accumet Research AR15 pH meter (Fisher Scientific, USA). pH analysis was done in triplicates

on the 0, seventh and fourteenth days.

4.2.4 PPO activity analysis

The method proposed by Montgomery and Sgarbieri (1975) was followed to determine

polyphenol oxidase (PPO) activity in the apple samples using an Infinite M200 microplate

spectrophotometer (Tecan). Thirty grams of tissue (from 3 apple surfaces - each slices about 1

cm thick) using were homogenized using an Osterizer 12 speed blender (450 W) in 0.2 g

polyvinylpolypirrolidone (PVPP) and 70 mL of 0.5 M phosphate buffer (pH 6.8) for 50 seconds.

The homogenate was filtered through filter paper (Whatman No. 41) under vacuum to remove

cellular debris. The clear supernatant after centrifugation at 12000 rpm (16,099 X g) (Sorvall

http://www.sciencedirect.com/science/article/pii/S0925521404000791#BIB23

41

Instruments Model RC5C centrifuge, SM10 rotor) for 15 minutes at 4 oC was collected as

enzyme extracts.

Two milliliters of phosphate buffer (0.05 M) stored in the refrigerator at 4 0C and 0.5 mL

enzyme extract were added to a glass tube. Before the reading, 0.5 mL catechol (0.02 M)

prepared fresh daily was added to the mixture. The mixture was poured into cuvettes and

inserted in a plate reader (TECAN-infinite M200). The increase in absorbance was read over 3

minutes in every 15 seconds at 420 nm. PPO activity was reported as “U/mL” according to

formula proposed by Cemeroglu (2007). PPO activity analysis was done for the first (after 24

hours later), seventh and fourteenth days.

The absorbance (420 nm) of the assay solution was plotted against the reaction time (180

s) to demonstrate the enzyme kinetics. Slope of the absorbance vs. time curve was calculated,

and the result was reported as a “unit/FW”. Since one unit of enzyme activity is defined as the

amount enzyme causing a change in absorbance of 0.001 per minute (Yue-Ming, et al. 1997), the

data was divided by 0.001 and PPO activity was reported as “U/mL” according to formula

proposed by Cemeroglu (2007) (1).

(1)

where E is the slope of the absorbance vs. time curve, 0.001 is a constant value (using for

converting abs/min to unit), He is the volume of the enzyme extract in the reaction mixture (mL),

Hrk is the total volume of the reaction mixture (mL), and Sf is a dilution factor.

4.2.5 Sensory analysis

Panelists (n =10) were used to evaluate sensory properties of the apples treated with and

without ultrasound. The sensory parameters were color, odor, overall acceptability, and off-odor.

42

A 9 point hedonic scale was provided to the panelists as follows: like extremely (9), like very

much (8), like moderately (7), like slightly (6), neither like nor dislike (5), dislike slightly (4),

dislike moderately (3), dislike very much (2), and dislike extremely (1). For off-odor, no off-odor

(1) and very strong off-odor (9) were provided. The form that used to evaluate the sensory

properties of apples treated with ultrasound and w/o ultrasound is shown in the Fig. 4.1. Sensory

analysis was done on the first (24 hours later), seventh and fourteenth days.

4.2.6 Surface appearance and surface morphology

Photos of red delicious and golden delicious apples cut with and without ultrasound were

taken by a camera (Sony Cyber-Shot DSC-W570 16.1 MP Digital Still Camera). Surface

morphology of the samples was obtained using an Environmental scanning electron microscope

(ESEM). In order to determine surface profile, samples cut with and without ultrasound in four

pieces equally from the center and one piece of them was taken for the surface analysis. After the

placement of the specimens in the microscope, the images of surface morphology of red

delicious and golden delicious apples were obtained with the microscope (D8.7, magnification:

40x, 2 mm, and D4.8, magnification: 100x, 1mm).

4.2.7 Calcium ascorbate (CaA) application

To prevent PPO browning on the apples, calcium ascorbate (Ca-A, SIGMA-ALDRICH,

Inc.) solution was used and effect of CaA on browning were compared with ultrasonic cutting

and without ultrasonic cutting. After cutting, the apple slices were dipped into solutions of 1%

CaA for 3 minutes, drained with towel, placed into the polyethylene bags, and kept under the

refrigerated conditions (0-4 0C). At the end of the first day (24 hours later), cut surface PPO

43

activity (cut with 50% amplitude) were evaluated and combined with CaA treatment were

measured. For the seventh and fourteenth days PPO activity of samples were also evaluated.

4.2.8 Statistical analysis

The results were analyzed statistically by analysis of variance using the General Linear

Models (PROC GLM) procedure in SAS (version 9.3, SAS Institute, Inc., Cary, North Carolina,

USA). The results analyzed were obtained in triplicate, unless otherwise stated. Differences

among the mean values were obtained by Fisher's least significant difference (LSD) test at

alpha=0.05.

4.3 Results and Discussion

4.3.1 Color changes

The color changes of the red delicious and golden delicious apples cut with and w/o

ultrasound are shown in Tables 4.1, 4.2, and 4.3. The L (lightness) values of ultrasound-cut

apples for both types (red delicious and golden delicious) were significantly higher than the

control during two weeks. The L values increased with an increase of ultrasound amplitude in

both samples, and the highest L values were observed for the samples cut with 50% amplitude.

No significant changes were observed between apples cut with ultrasound and w/o ultrasound in

their a (redness) and b (yellowness) values during two weeks. The L values decreased

significantly with the storage time in both apples and all treatments (0%, 30%, 40%, and 50%

amplitude). The highest L value was observed for the 0 day samples, and the lowest L value was

44

observed for the last (second) week samples. When comparing the a (redness) values of the

apples during storage, a significant increase were observed. While the lowest a values were

observed on day 0 (both types of apples and all the treatments), the highest a values were

observed on day 14. Similarly, when b (yellowness) values of samples compared during storage,

they significantly increased with the storage time in all samples. While the lowest b values were

observed on day 0 (both types of apples and methods as well), the highest b values were

observed on day 14. An increase in redness (a) and yellowness (b) values, and a decrease in

lightness (L) values indicated an increased enzymatic browning in all cut apples during storage.

Pérez-Gago et al. (2005) also reported similar results where color changes of apple pieces were

featured by a decrease in L (lightness) values, and increase in a (redness) and b (yellowness)

values during the storage.

Fresh-cut products should have a bright surface color and be free of decay. Appearance

characteristics can be measured subjectively by using naked eyes or objectively by using the

specific instruments. For visual evaluation, color charts may be used as references but results

may be affected by human error and evaluation conditions such as type of lighting. Several

authors employed subjective rating scales to evaluate general appearance of fresh-cut produce

such as peaches and nectarines (Gorny et al., 1999; Aguayo et al., 2006; Amodio & Colelli,

2008), and vegetable mix (Amodio et al., 2006). Kader and Cantwell (2004) used rating scales

and color charts to evaluate the appearance of both whole and fresh-cut produce.

In this study, sensory panelists showed that there were significantly differences between

their color evaluations’ of samples cut with and w/o ultrasound. They liked the color of apples

cut with ultrasound compared to the apples cut without ultrasound. Usually, an increase in L

(lightness) value shows the development of whiteness in samples, and a decrease in this

45

parameter is correlated with the development of browning (Rico et al., 2007). Since the apples

cut without ultrasound had lower L values, the browning development on the apple surface was

more obvious when compared to those cut with ultrasound. The PPO activity measurement of the

fresh-cut apples supported the claim that the browning development on the apple surface cut

without ultrasound since the samples cut with ultrasound had lower PPO activity compared to the

control. During peeling and cutting operations, if the equipment used is not in the best condition,

for example, if dull knives and blades are used, damage occurs in more tissue layers than

intended; thus, the sharpness of knife blades can significantly affect product storage life (Bolin et

al., 1977). In addition, the browning can be seen when the product is cut because these actions

damage the cells in/on the food and allow oxygen in the air to react with the enzyme and other

chemicals. The unit operations such as peeling and slicing during processing result in the

destruction of surface cells (Brecht, 1995). By applying ultrasonic knife, less damage was

observed on the apples’ surface. Thus, samples cut with ultrasound were less susceptible to

browning development. Additionally, apples cut with ultrasound were exposed to the air less

time due to the ultrasonic knife made the cutting process faster. The contact time between knife

and the apples during cutting for the samples cut with 50% amplitude was: 1.8 seconds while it

was 2.4 seconds for the samples cut w/o ultrasound.

4.3.2 pH changes

The pH changes measured of red delicious and golden delicious treated with and without

ultrasound are shown in Table 4.4. The pH values of the red delicious were in the range of 4.10

to 4.20 in day 0, and were from 3.84 to 3.98 for the golden delicious. The pH of red delicious

apple ranged from 4.16 to 4.29 in day 7, and that for golden delicious was 3.90 to 4.05. On day

46

14, the ranges of pH were from 4.38 to 4.64 for red delicious, from 3.98 to 4.14 for golden

delicious. The pH values of the red delicious and golden delicious apple were affected by

ultrasound cutting and a significant decrease in pH values was recorded for both types of apples

cut with ultrasound during two weeks. Kim et al. (1993) indicated that compared to other

compounds acids are used during respiration quickly. This decrease in pH values might be

related to increased respiration rates following cutting process. The pH values were increased

significantly with the storage time in both samples (red delicious and golden delicious) and all

treatments (0%, 30%, 40%, and 50% amplitude) probably due to the buffering capacity of the

apple tissue. The lowest pH value was observed for the 0 day samples, and the highest pH value

was observed for the last (second) week samples.

While the optimum PPO has been reported as ranging from acid to neutral, little PPO

activity is detected below pH 4.5 in most fruits and vegetables (Whitaker, 1994). However,

apple and grape PPO have broad acidic pH optima with the values between pH 3.5 to 4.5 (Valero

et. al., 1988; Marques et. al., 1995). It has also been reported that irreversible inactivation of

PPO might be achieved below 3.0 (Richardson& Hyslop, 1985). On the other hand, it has also

been reported that apple PPO is tolerant to acidity. It retains 40% of its maximum activity at pH

3.0 (Nicolas et al., 1994). The optimal pH values of the two apples used in this study were not

determined. But from literature data mentioned above, the changes in pH caused by ultrasonic

cutting may have several positive implications such as low activity of polyphenol oxidases in

these ranges of pH and reduced microbiological development which will contribute to the

preservation of the apple (Frazier & Westhoff, 1988).

47

4.3.3 PPO activity

The PPO activities of red delicious and golden delicious apples treated with and w/o

ultrasound are shown in Table 4.5. The PPO activities of the red delicious were in the range of

360 to 792 U/mL on day 1, and they were from 288 to 684 U/mL for golden delicious. On day 7,

the PPO activities of the red delicious were in the range of 432 to 828 U/mL, and those for the

golden delicious were from 360 to 720 U/mL. The PPO activities of the red delicious were in the

range of 504 to 864 U/mL on the fourteenth day, and they were from 432 to 756 U/mL for

golden delicious. The ultrasound cutting affected the PPO activities during two weeks and a

significant decrease in the PPO activity was recorded for samples cut with ultrasound. The PPO

activities increased with the storage time. While the first day PPO activities of the samples were

low, they were increased when measured on the seventh and fourteenth day. The highest PPO

activities occurred in the second week samples. It was observed that red delicious samples had a

higher PPO activity compared to golden delicious. Sensory evaluation by the panelists supported

the result. The panelists evaluated the apples color according to the browning on the apple slices

and gave higher scores to samples cut with ultrasound for both types of apples. In addition, they

gave higher color scores to the golden delicious rather than the red delicious which supported the

claim that red delicious had higher PPO activities compared to the golden delicious.

Fresh-cut process creates wounding on fruits, and thus increases metabolic activities

which may cause browning, softening, decay, and off-flavor development (Watada et al., 1990;

Varoquax and Wiley, 1994). There are several factors affecting the wounding of fruits. For

example, the number of cuts, the severity of the cutting treatments, and the sharpness of cutting

blades all influence the extent of wounding. Portela and Cantwell (2001) showed that cutting

melon pieces with a blunt blade showed increased ethanol concentrations and off-odors

48

compared to melon pieces cut with a sharp blade. In a similar way, cutting with sharp blades

showed reduced softening and microbial growth in fresh-cut carrots (Bolin and Huxsoll, 1991;

Barry-Ryan and O’Beirne, 1998). The unit operations such as peeling and slicing result in the

destruction of surface cells (Brecht, 1995) and removal of natural barriers such as skins in the

case of fruits which causes water loss and deterioration (Altekruse et al., 1997; Agar et al.,

1999). It also leads to an increase in respiration rate and ethylene production (Saltveit, 1997;

Saltveit et al., 2005). Furthermore, reaction between phenols and PPO causes browning

discoloration (Martinez and Whitaker, 1995; Heaton and Marangoni, 1996).

Cutting apples with ultrasound produced less damage on the cut apple surfaces. Thus,

samples cut with ultrasound were less susceptible to browning development since they had less

open/damaged surfaces that exposed to air/oxygen. Besides the differences shown in color

readings and PPO activity measurements among the samples cut with and without ultrasound,

this is also evidenced by the sensory test. The sensory (color) scores showed that people were

favor of the color of apples cut with ultrasound.

4.3.4 Surface morphology and surface appearance

The Environmental Scanning Electron Microscope (ESEM) images of the surface

morphology of red delicious apples treated by ultrasound and w/o ultrasound are shown in Figure

4.2. It can be seen from the ESEM images that the samples cut by ultrasound exhibited a dense

and relatively smooth surface morphology with less cell damage. In contrary, the surface cut

without ultrasound was rugged with more cells tore open. In addition, a macro-crack with a

longitudinal dimension of a few millimeters can be seen on the surface. Obviously, the apple cut

49

without ultrasound had more surfaces and damaged cells exposed to the air which may lead to

more enzymatic browning and quality degradation.

The surface pictures of ultrasonic cut red delicious and golden delicious are shown in

Figure 4.3. Both types of apples cut with ultrasound showed smooth surface appearance, while

the surfaces were rough for samples cut without ultrasound. The samples cut without ultrasound

had a darker color compared to the ultrasound cut especially for the golden delicious apple. This

is in agreement with the Hunter L (lightness) readings where both types of apples cut with

ultrasound had significantly higher L values compared to the control. Color scores given by the

panelists showed that they were favor of the samples cut with ultrasound compared to the

control. Appearance plays a significant role influencing consumer’s perception and subsequent

acceptance of a food product. Appearance ranks first affected consumer purchase preferences

(Lund and Snowdon, 2000). It is possible to predict that people will be favor of purchasing

apples cut with ultrasound rather than apples cut w/o ultrasound since they have less deformation

on the surface and preferable color.


Table 4.6 shows the sensory scores of red delicious and golden delicious treated with

ultrasound and w/o ultrasound during two weeks. The observations on color indicated that there

was a significant difference between the samples cut with and w/o ultrasound for both types of

apples. It seems that the changes of in lightness (L value) were also recognized by the panelists.

Significant differences between the control and ultrasound cut samples were also observed in

odor and overall acceptability evaluation of both type of apple samples on the first, seventh and

fourteenth days. In addition, on day 1, there is no off-odor was observed by panelists (n=10) for

50

both types of apples and treatments (0%, 30%, 40%, and 50% amplitude). However, on the

seventh and fourteenth days, a slight off-odor was observed for both type of apples cut without

ultrasound and with 30% amplitude. No off-odor was observed for the samples cut with 40% and

50% amplitude on the seventh and fourteenth days. On day 1, both types of apples were scored

highest by panelists in terms of color, odor, and overall acceptability compared to the seventh

and fourteenth day’s apple samples. The golden delicious samples were given higher scores by

panelists compared to the red delicious. It may be caused by the higher susceptibility to

browning of red delicious compared to the golden delicious. Therefore, lower color scores was

given by the panelists for red delicious. Overall, the panelists were favor of apples cut with

ultrasound.

4.3.6 Calcium ascorbate (CaA) treatment

The PPO activities of red delicious and golden delicious treated with 1% CaA solution in

combination with ultrasound and without ultrasound are shown in Table 4.7. On day 1, the PPO

activity of red delicious treated with 1% CaA solution followed by ultrasonic cutting (50%

amplitude) was 108 U/mL and that without ultrasonic cutting was 180 U/mL. Correspondingly,

on day 1, the PPO activity of golden delicious was 72 U/mL and 144 U/mL, respectively. On the

seventh day, the PPO activity of red delicious treated with 1% CaA solution followed by

ultrasonic cutting (50% amplitude) was 144 U/mL and that without ultrasonic cutting was 252

U/mL. Measured on the same day, the corresponding PPO activity of golden delicious was 108

U/mL and 180 U/mL, respectively. On day 14, the PPO activities of the samples dipped in CaA

solution increased to 216 U/mL and 270 U/mL for red delicious, and 144 U/mL and 227 U/mL

for golden delicious, for treatment with and without ultrasound, respectively. A significant

51

decrease in PPO activity was recorded for samples treated with CaA solution (1%). The lowest

PPO activity among the samples was found in the samples treated by CaA solution and cut with

ultrasound. On the other hand, apples cut without ultrasound and no CaA application had the

highest PPO activity. PPO activities of all samples were increased with the storage time. While

the first day PPO activities of samples were low, they were increased for the seventh and

fourteenth day. It was observed that red delicious samples had a higher PPO activity compared to

golden delicious.

Enzymatic browning can be slowed or prevented by inactivating the enzyme with heat

(cooking), reducing the pH on the surface of the fruit (by adding lemon juice or another acids),

reducing the reaction rate by storing the fruit in the refrigerator, reducing the amount of available

oxygen (by putting cut fruit under water or vacuum packing it), or by adding certain preservative

chemicals (like sulfur dioxide). Several studies have been done to control extent of browning.

One of the approaches to prevent the browning of apple slices is that using reducing agents such

as ascorbic acid or sodium erythorbate (isoascorbate) (Sapers et al., 1990). In this study, calcium

ascorbate was used to prevent/slow down the browning of apple slices. The combination of CaA

treatment in combination with ultrasonic cutting yielded the best result showing less browning

and optimum quality of fresh-cut apples.

4.4 Conclusion

Ultrasonic cutting of apples significantly affected chemical parameters such as

polyphenol oxidase (PPO) and pH-value showed. The ultrasound cutting affected the polyphenol

oxidase (PPO) activities during two weeks and a significant decrease in the PPO activity was

52

recorded for samples cut with ultrasound. The PPO activities increased with the storage time.

While the first day PPO activities of the samples were low, they were increased when measured

on the seventh and fourteenth day. The highest PPO activities occurred in the second week

samples. It was observed that red delicious samples had a higher PPO activity compared to

golden delicious. The pH values of the red delicious and golden delicious apple were affected by

ultrasound cutting and a significant decrease in pH values was recorded for both types of apples

cut with ultrasound during two weeks. The pH values were increased significantly with the

storage time in both samples (red delicious and golden delicious) and all treatments (0%, 30%,

40%, and 50% amplitude). The lowest pH value was observed for the 0 day samples, and the

highest pH value was observed for the last (second) week samples. The samples cut with

ultrasound exhibited a significantly higher L (lightness) value compared to that cut without

ultrasound. The L values increased with an increase of ultrasound amplitude in both samples, and

the highest L values were observed for the samples cut with 50% amplitude. Furthermore, both

types of apples cut with ultrasound showed smooth surface appearance, while the surfaces were

rough for samples cut without ultrasound. ESEM images that the samples cut by ultrasound

exhibited a dense and relatively smooth surface morphology with less cell damage. On the other

hand, the surface cut without ultrasound was rugged with more cells tore open. In visual quality

evaluation, panelists showed higher liking of apples cut with ultrasound. Overall, apples cut

with ultrasound showed a better quality during storage compared to the control, as evidenced by

both measurements with instruments and scores of sensory evaluation.

53


Name:

Date:

Put the numbers (1 to 9) in boxes according to explanation shown in the below (*).

Color evaluation will be done according to the browning on the apple slices.

Odor evaluation will be done according to the characteristic odor of the apples.

Overall acceptability is your point of view about the apple product in terms of appearance,

smell, texture, and etc.

Off-odor evaluation will be done whether the apple product has off-odor or not.

COLOR ODOR OVERALL ACCEPTABILTY OFF-ODOR

SAMPLE 1

SAMPLE 2

SAMPLE 3

SAMPLE 4

SAMPLE 5

SAMPLE 6

SAMPLE 7

SAMPLE 8

*9 Point Hedonic Scale: For off-odor;

9: like extremely

8: like very much 1: no off-odor

7: like moderately 9: very strong off-odor

6: like slightly

5: neither like nor dislike

4: dislike slightly

3: dislike moderately

2: dislike very much

1: dislike extremely

Figure 4.1. The form that used to evaluate the sensory properties of apples treated with

ultrasound and w/o ultrasound

54

Table 4.1. Changes in L (lightness) values for red delicious and golden delicious apples treated

with ultrasound and w/o ultrasound during a two-week period

Sample Treatment Amplitude L ( lightness) values

Day 0 Day 7 Day 14

Red delicious cut w/o ultrasound 0% 75.560b (x)

63.360c (y)

62.460b (y)


69.520b (y)

68.947a (y)

cut with ultrasound 40% 79.160a (x)

72.207ab (y)

70.803a (y)


74.923a (y)

73.330a (y)

Golden delicious cut w/o ultrasound 0% 76.013b (x)

67.183c (y)

65.487b (y)


69.213bc (y)

68.520ab (y)


71.830b (y)

69.873a (y)


75.560a (y)

71.927a (z)


(p<0.05).


55

Table 4.2. Changes in a (redness) values for red delicious and golden delicious apples treated


Sample Treatment Amplitude a (redness) values

Day 0 Day 7 Day 14

Red delicious cut w/o ultrasound 0% -4.9433a (z)

0.6700a (y)

1.3600a (x)

cut with ultrasound 30% -5.0533a (z)

0.8067a (y)

1.3533

a (x)


1.0067a (y)

1.3500a (x)


1.7833a (y)

1.2567a (x)

Golden delicious cut w/o ultrasound 0% -7.4867a (z)

-0.4833a (y)

0.6100

a (x)


-0.5767a (y)

0.5500a (x)


-0.8200a (y)

0.5433a (x)


-0.8433a (y)

0.2567a (x)


(p<0.05).


56

Table 4.3. Changes in b (yellowness) values for red delicious and golden delicious apples treated


Sample Treatment Amplitude b (yellowness) values

Day 0 Day 7 Day 14

Red delicious cut w/o ultrasound 0% 24.743a (y)

34.283

a (x)

34.940

a (x)

cut with ultrasound 30% 23.753a (y)

32.703a (x)

33.770a (x)


32.387a (x)

32.983

a (x)


31.480a (x)

32.013a (x)

Golden delicious cut w/o ultrasound 0% 29.410a (y)

36.713a (x)

38.133a (x)


36.623a (x)

36.743

a (x)


36.117a (x)

36.173a (x)


34.713a (x)

36.117a (x)


(p<0.05).


57

Table 4.4. Changes in pH for red delicious and golden delicious apples treated with ultrasound

and w/o ultrasound during a two-week period

Sample Treatment Amplitude pH changes

Day 0 Day 7 Day 14

Red delicious cut w/o ultrasound 0% 4.20a (y)

4.29a (y)

4.64a (x)

cut with ultrasound 30% 4.12ab (y)

4.26ab (y)

4.45b (x)

cut with ultrasound 40% 4.10b (y)

4.18bc (y)

4.41b (x)


4.16c (y)

4.38b (x)

Golden delicious cut w/o ultrasound 0% 3.98a (y)

4.05a (xy)

4.14a (x)


3.99b (xy)

4.02ab (x)


3.94bc (xy)

3.99b (x)


3.90c (xy)

3.98b (x)


(p<0.05).


58

Table 4.5. Polyphenol oxidase (PPO) activity changes for red delicious and golden delicious

apples treated with ultrasound and w/o ultrasound during a two-week period

Sample Treatment Amplitude PPO activity (U/mL)

1st day 7

th day 14

th day

Red delicious cut w/o ultrasound 0% 792a (z)

828a (y)

864a (x)

cut with ultrasound 30% 468b (z)

504b (y)

612b (x)

cut with ultrasound 40% 450bc (z)

480b (y)

540c (x)

cut with ultrasound 50% 360c (z)

432c (y)

504d (x)

Golden delicious cut w/o ultrasound 0% 684a (z)

720a (y)

756a (x)


408b (y)

504b (x)


385bc (y)

468c (x)

cut with ultrasound 50% 288c (z)

360c (y)

432d (x)

a-d

Treatment means within treatments (columns) with the same letter in each sample are not significantly different

(p<0.05).


59

Figure 4.2. Environmental Scanning Electron Microscope (ESEM) images of the surface

morphology of red delicious apples treated by ultrasound and w/o ultrasound

Left-top image: red delicious apple cut with ultrasound (50% amplitude-40x magnification); right-top image: red

delicious apple cut without ultrasound (40x magnification); left-bottom image: red delicious apple cut with

ultrasound (50% amplitude-100x magnification); right-bottom image: red delicious apple cut without ultrasound

(100x magnification).

60

Figure 4.3. Surface pictures of ultrasonic cut red delicious and golden delicious

Left -top image: red delicious apple cut with ultrasound (50% amplitude); right-top image: red delicious apple cut

without ultrasound; left-bottom image: golden delicious apple cut with ultrasound (50% amplitude); left-bottom

image: golden delicious apple cut without ultrasound.

61

Table 4.6. Sensory attributes changes for red delicious and golden delicious apples treated with ultrasound and w/o ultrasound during

a two-week period

Amplitude (%) Color Odor Overall acceptability Off-odor

1st day 7

th days 14

th days 1

st day 7

th days 14

th days 1

st day 7

th days 14

th days 1

st day 7

th days 14

th days

Red delicious

0% amplitude 5.3d (x)

1.9d (y)

1.6b (y)

5.2c (x)

2.2c (y)

1.9b (y)

4.7c (x)

2.4c (y)

1.7b (y)

1.0a (x)

1.7a (x)

2.6a (x)

30%amplitude 6.8c (x)

4.3c (y)

3.8a (y)

6.0bc (x)

4.3b (y)

4.2a (y)

6.4b (x)

4.7b (y)

4.3a (y)

1.0a (x)

1.4ab (x)

1.9a (x)


5.2b (y)

4.6a (y)

6.6ab (x)

4.7b (y)

4.5a (y)

6.6b (x)

5.0b (y)

4.6a (z)

1.0a (x)

1.0b (x)

1.0b (x)


6.3a (y)

5.2a (z)

7.2a (x)

5.8a (y)

5.3a (y)

8.3a (x)

6.1a (y)

5.7a (y)

1.0a (x)

1.0b (x)

1.0b (x)

Golden delicious

0% amplitude 5.5d (x)

5.1c (y)

3.8c (z)

4.5c (x)

4.3c (xy)

3.8b (y)

4.5d (x)

4.3c (xy)

3.3c (y)

1.0a (x)

1.3a (x)

2.3a (x)

30%amplitude 7.2c (x)

6.3b (y)

4.6b (z)

6.5b (x)

5.4b (y)

3.9b (z)

5.9c (x)

5.7b (xy)

3.9bc (y)

1.0a (x)

1.3a (x)

1.8a (x)


6.8ab (y)

4.8b (z)

7.2b (x)

6.0b (y)

4.6b (z)

7.4b (x)

6.1b (y)

4.6b (z)

1.0a (x)

1.0a (x)

1.0b (x)


7.6a (y)

5.8a (z)

8.3a (x)

7.0a (y)

5.5a (z)

8.4a (x)

7.1a (y)

5.7a (z)

1.0a (x)

1.0a (x)

1.0b (x)

a-d Treatment means within treatments (columns) with the same letter in each sample are not significantly different (p<0.05).


62

Table 4.7. Polyphenol oxidase (PPO) activity changes for red delicious and golden delicious

apples treated with 1% CaA solution in combined with ultrasound and w/o ultrasound during a

two-week period

Sample Treatment Amplitude PPO activity (U/mL)

1st day 7

th day 14

th day

Red delicious cut w/o ultrasound 0% 792a (z)

828a (y)

864a (x)


432b (y)

504b (x)

w/o ultrasound+CaA 0% 180c (z)

252c (y)

270c (x)

with ultrasound+CaA 50% 108d (z)

144d (y)

216d (x)

Golden delicious cut w/o ultrasound 0% 684a (z)

720a (y)

756a (x)


360b (y)

432b (x)

w/o ultrasound+CaA 0% 144c (z)

180c (y)

227c (x)

with ultrasound+CaA 50% 72d (z)

108d (y)

144d (x)

a-d Treatment means within treatments (columns) with the same letter in each sample are not significantly different

(p<0.05).


63

CHAPTER 5

OVERALL CONCLUSIONS AND FUTURE WORK

This thesis describes the effect of ultrasonic cutting on the surface appearance and quality

of selected food products (cheese and apple). Apples and cheeses cut without (control) and with

ultrasound at three amplitudes (30%, 40%, and 50%) with an ultrasonic knife. Quality attributes

such as total color difference, surface texture, peroxide values (for cheeses), pH, polyphenol

oxidase (PPO) activity (for apples) and sensory characteristics of cheeses and apples cut with and

w/o ultrasound were measured and compared. According to the results, a significant difference in

quality and surface appearance of selected food products cut with and without ultrasound were

observed.

By taking into account of the advantages of using ultrasonic knife, it may be possible to

get much more qualified foods, and preserve the foods much longer. In addition, using ultrasonic

knife may help to save the time, and lower the product loss for the food industry.

Overall, this thesis research demonstrated that ultrasonic cutting may provide a promising

alternative to traditional cutting for improving the surface appearance and quality of cut

products.

For future studies, modified atmosphere packaging (MAP) can be combined and designed

with ultrasound and without ultrasound to optimize the quality and shelf-life of fresh-cut apples.

Synergism of the MAP system with an antioxidant treatment (calcium ascorbate) on food quality

and shelf-life can be also investigated. Finally, more detailed analysis based on quality of

64

different food products such as bakery and frozen products should be conducted to fully

understand the benefits of using ultrasound in food cutting.

65

REFERENCES

Abe, K., and Watada, A. E. (1991). Ethylene absorbent to maintain quality of lightly processed

fruits and vegetables. J. Food Sci. 56: 1589-1592.

Addis, P.B. (1986). Occurrence of lipid oxidation products in foods. Food Chem. Toxicol. 24:

1021-1030.

Agar, I. T., Massantini, R., Hess-Pierce, B., and Kader, A. A. (1999). Postharvest CO2 and

ethylene production and quality maintenance of fresh-cut kiwifruit slices. J. Food Sci. 64: 433–

440.

Aguayo, E., Jansasithorn, R., and Kader, A. A. (2006). Combined effects of 1-

methylcyclopropene, calcium chloride dip, and/or atmospheric modification on quality changes

in fresh-cut strawberries. Postharv. Biol. Technol. 40: 269–278.

Ahvenainen, R. (1996). New approaches in improving the shelf life of minimally processed fruit

and vegetables. Trends Food Sci. Technol. 7: 179-187.

Altekruse, S. F., Cohen, M. L., and Swerdlow, D. L. (1997). Emerging foodborne diseases.

Emerg. Infect. Dis. 3: 285–293.

Amodio, M. L., Rinaldi, R., and Coltelli, G. (2006). Influence of atmosphere composition on

quality attributes of ready-to- cook fresh-cut vegetable soup. Acta Hort. 712: 677–684.

Amodio, M. L., and Colelli, G. (2008). Effect of thermal treatment and dipping on quality and

shelf-life of fresh-cut peaches. Advances in Horticultural Science. 1: 21–26.

Annese, M., Manzano, M., and Nicoli, M. C. (1997). Quality of minimally processed apple slices

using different modified atmosphere conditions. J. Food Qual. 20: 359-370.

66

Antolovich, M., Prenzler, P. D., Patsalides, E., Mcdonald, S., and Robards, K. (2002). Analyst.

127: 183–198.

AOCS Official Methods and Recommended Practices. 5th edit. (1998). Official Method Cd 8-

53: Peroxide value. Acetic acid-chloroform method. Am. Oil Chem. Soc., Champaign, IL, USA.

Arnold, G., Leiteritz, L., Zahn, S., and Rohm, H. (2009). Ultrasonic cutting of cheese:

composition affects cutting work reduction and energy demand. Int. Dairy J. 19: 314-320.

Barnicoat, C. R. (1950). Cheese discoloration: oxidation of bixin in annatto-coloured cheeses

promoted by sulphydryl compounds. J. Dairy Res. 8: 209-213.

Barry-Ryan, C., and O’Beirne, D. (1998). Effects of slicing method on the quality and storage-

life of modified atmosphere packaged carrot discs. J. Food Sci. 63: 851–856.

Bolin, H. R., Staftord, A. E. King, A. D. Jr., and Huxsoll, C. C. (1977). Factors affecting the

storage stability of shredded lettuce. J. Food Sci. 42(5): 1319-1321.

Bolin, H. R., and Huxsoll, C. C. (1991). Control of minimally processed carrot (Daucus carota)

surface discoloration caused by abrasion peeling. J. Food Sci. 56: 416–418.

Bolland, J. L. (1945). The course of autoxidation reactions in polyisoprenes and allied

compounds. Part IX. The primary thermal oxidation products of ethyl linoleate. J. Chem. Soc.

445-447.

Bolland, J. L. (1949). Kinetics of olefin oxidation. Q. Rev. 3: 1-21.

Boran, G., Karacam, H., and Boran, M. (2006). Changes in the quality of fish oil due to storage

temperature and time. Food Chemistry. 98: 693–698.

67

Brecht, J. K. (1995). Physiology of lightly processed fruits and vegetables. HortScience. 30:18-

22.

Brown, T., James, S. J., and Purnell, G. L. (2005). Cutting forces in foods: experimental

measurements. J. Food Eng. 70: 165-170.

Buzby, J. C. (2005). Cheese consumption continues to rise. Amber waves. Volume 3, Issue 1.

Retrieved from http://purl.umn.edu/130593.

Campbell, R. E, Miracle, R. E, Gerard, P. D., and Drake, M. A. (2011-a). Effects of Starter

Culture and Storage on the Flavor of Liquid Whey. J Food Sci. 76(5): 354-361.

Campbell, R. E., Miracle, R. E., and Drake, M. A. (2011-b). The effect of starter culture and

annatto on the flavor and functionality of whey protein concentrate. J Dairy Sci. 94(3): 1185-

1193.

Cantwell, M. (1995). Fresh-cut product biology and requirements. Perishables Handling

Newsletter. 81: 4-9.

Caodi, F. (2007). Characterization of polyphenol oxidase and antioxidants from pawpaw

(asimina tribola) fruit. University of Kentucky Master's Theses. Paper 477.

Retrieved from http://uknowledge.uky.edu/gradschool_theses/477.

Cemeroglu, B. (2007). Gıda analizleri. Gıda Teknolojisi Dernegi Yayınları. No: 34, Bizim Büro

Basımevi. Ankara, 535 s.

Creamer, L. K., and Olson, N. F. (2005). Rheological evaluation of maturing cheddar cheese.

Journal of Food Science. 47: 631- 646.

http://purl.umn.edu/130593

http://uknowledge.uky.edu/gradschool_theses/477/

http://uknowledge.uky.edu/gradschool_theses/477

68

Das, J. R., Bhat, S. G., and Gowda, L. R. (1997). Purification and characterization of a

polyphenol oxidase from the Kew cultivar of Indian pineapple fruit. J. Agric. Food Chem. 45:

2031–2035.

EL-Nimr, A. A, Hesham, A. E., El-Abd, M. M., Mehriz A. A, Abbas, H. M., and Bayoumi, H.

M. (2010). Water activity, color characteristics and sensory properties of egyptian gouda cheese

during ripening. JAm Sci. 6(10):447-453.

Esterbauer, H., Lang, J., Zadravec S., and Slater, T. S. (1984). Detection of malonaldehyde by

high-performance liquid chromatography. Methods Enzymol. 105: 319–328.

Esterbauer, H., and Zollner, H. (1989). Methods for dctcrminatioll of aldehydic lipid

peroxidation products. Free Rad. Biol. Med. 7: 197–203.

Farmer, E. H., and Sutton, D. A., (1943). Course of autoxidation reactions in polyisoprenes and

allied compounds. IV. The isolation and constitution of photochemically-formed methyl oleate

peroxide. J. Chem. Soc. 119-122.

Farmer, E. H., Koch, H. P., and Sutton, D. A., (1943). The course of autoxidation reactions in

polyisoprenes and allied compounds. VII. Rearrangement of double bonds during autoxidation.

J. Chem. Soc. 541-547.

Feng, H., and Yang, W. (2005). Power ultrasound. In Handbook of Food Science, Technology,

and Engineering. 121-1-121-9, (ed.) Hui, Y.H. CRC Press, New York.

Ferrer, A. S., Bru, R., and Carmona, F. G. (1989). Novel procedure for extraction of a latent

grape polyphenoloxidase using temperature--induced phase separation in Triton X-114. Plant

Physiol. 91:1481–1487.

69

Ferrer, A. S., Laveda, F., and Carmona, F. G. (1993). Partial purification of soluble potato

polyphenol oxidase by partitioning in aqueous two-phase system. J. Agric. Food. Chem. 41:

1219–1224.

Fox, P. F., Law, J., McSweeney, P. L. H., and Wallace, J. (1993). Biochemistry of cheese

ripening. In P. F. Fox (Eds.). Cheese, chemistry, physics and microbiology. Vol. 1 (pp. 389-438).

UK: Chapman and Hall.

Francis, F. (1980). Color quality evaluation of horticultural crops. Hort. Science. 5: 58-59.

Frankel, E. N. (1980). Lipid oxidation. Pray. Lipid Res. VoL 19. pp. 1-22.

Frankel, E.N. (1998). Lipid Oxidation. The Oily Press. Dundee, Scotland.

Frazier, W. C., and Westhoff, D. C. (1988). In E. Dollinger (Ed.), Food Microbiology (p. 196).

Singapore: McGraw-Hill Book Co.

Goodenough, P. W., Kessell, S., Lea, A. G. H., and Loeffler, T. (1983). Mono- and diphenolase

activity from fruit of Mulus pumilu. Phytochemistry. 22: 359–363.

Gorny, J. R. (1997). Summary of CA and MA requirements and recommendations for fresh - cut

(minimally processed) fruits and vegetables. In: Gorny, J.R. (Ed.), Proceedings of Seventh

International Controlled Atmosphere Conference, Vol. 5. Postharvest Outreach Program,

University of California, Davis, CA, 30 - 66.

Gorny, J. R., Hess-Pierce, B., and Kader, A. A. (1999). Quality changes in freshcut peach and

nectarine slices as affected by cultivar, storage atmosphere and chemical treatments. J. Food Sci.

64: 429–432.

Gray, J. I. (1978). Measurement of lipid oxidation. A review. J. Am. Oil Chem. Soc.,55, 539-46.

70

Haard, N. F., and Chism, G. W. (1996). Characteristics of Edible Plant Tissues. In Food

Chemistry, O.R. Fennema (Eds), p. 994–1007. Marcel Dekker Inc., New York.

Hassan A., Johnson M. E., and Lucey J. A. (2004). Changes in the proportions of soluble and

insoluble calcium during the ripening of Cheddar cheese. J. Dairy Sci. 87 854–862.

Heaton, J. W., and Marangoni, A. G. (1996). Chlorophyll degradation in processed foods and

senescent plant tissues. Trends Food Sci. Technol. 7: 8–15.

Heimdal, H., Larsen, L. M., and Poll, L. (1994). Characterization of polyphenol oxidase from

photosynthetic and vascular lettuce tissues (Lactucu saliva). J. Agric. Food. Chem. 42: 1428–

1433.

Holman, R.T. (1954) in Progress in the Chemistry of Fats and Other Lipids, Vol. 2, Edited by

R.T. Holman, Pergamon Press, London.

Huxsoll, C. C., and Bolin, H. R. (1989). Processing and distribution alternatives for minimally

processed fruits and vegetables. Food Technol. 43:124–128.

IDFA (2006). Dairy facts. Washington, D.C.: Intl. Dairy Foods Assn.

IDFA (2010). Dairy facts. International Dairy Foods Association, Washington, DC.

Jiang, Y. (1999). Purification and some properties of polyphenol oxidase of longan fruit. Food

Chem. 66: 75–79.

Kabir, H. (1994). Fresh-cut vegetables. In A. L. Brods, & V. A. Herndon (Eds.). Modified

atmosphere food packaging (pp. 155-160). Naperville, Illinois: Institute of Packaging

Professionals.

71

Kader, A. A., and Cantwell, M. (2004). Produce Quality Rating Scales and Color Charts.

Postharvest Horticulture Series Number 23, September 2004, revised May 2007. Postharvest

Technology Research and Information Center. University of California Davis, CA.

Kahn, V., and Pomerantz, S. H. (1980). Monophenolase activity of avocado polyphenoloxidases.

Phytochemistry. 19: 379–385.

Kanner, J., and Rosenthal, I. (1992). An assessment of lipid oxidation in foods. Pure & Appl.

Chem. 64: 1959–1964.

Kim, D. M., Smith, N. L., and Lee, C. Y. (1993). Quality of minimally processed apple slices

from selected cultivars. J. Food Sci. 58:1115-1117-1175.

Kim, H. J., Ham, J. S., Kim, K., Ha, J. H., Ha, S. D., and Jo, C. (2010). Quality Evaluation of

Sliced and Pizza Cheeses Treated by Gamma and Electron Beam Irradiation. Asian-Aust. J.

Anim. Sci. 23(8):1112-111.

King, A. D., and Bolin, H. R. (1989). Physiological and microbiological storage stability of

minimally processed fruits and vegetables. Food Technol. 43:132-135.

Klein, B. P. (1987). Nutritional consequences of minimal processing on fruits and vegetables.

Journal of Food Quality. 10: 179-193.

Lamikanra, O. (2002). Preface. In O. Lamikanra (Ed.). Fresh-cut fruits and vegetables. Science,

technology and market. Boca cRaton, FL: CRC Press.

Laubli, M. W., Bruttel, P. A., and Schalch, E. (1986). Determination of the oxidative stability of

fats and oils: comparison between the active oxygen method and the Rancimat method. J. Am.

Oil Chem. Soc. 63: 792–795.

72

Lebecque A., Laguet A., Devaux M. F., and Dufour, E. (2001). Delineation of the texture of

Salers cheese by sensory analysis and physical methods. Le Lait. 81: 609-623.

Ledenbach, L. H., and Marshall R. T. (2010). Microbiological Spoilage of Dairy Products. (Eds.)

W.H. Sperber; M.P.Doyle, Compendium of the Microbiological Spoilage of Foods and

Beverages. Springer-Verlag New York, LLC, pp. 41-67.

Lucas, M., MacBeath, A., McCulloch, E., and Cardoni, A. (2006). A finite element model for

ultrasonic cutting. Department of Mechanical Engineering, University of Glasgow, Glasgow G12

8QQ, United Kingdom, Volume 44, Supplement, 22 December 2006, Pages 503–509.

Lund, B. M., and Snowdon, A. L. (2000). Fresh and processed fruits. Chapter 27. In: The

Microbiological Safety and Quality of Food. Vol. 1, pp. 738–758. Lund, B. M., Baird-Parker, T.

C., and Gould, G. W., Eds., Gaithersburg, Aspen, CO.

Luo, Y., and Barbosa-Canovas, G. V. (1996). Preservation of apple slices using ascorbic acid

and 4-hexylresorcinol. Food Sci. Technol. Int. 2: 315-321.

Luo, Y., Lu, S., Zhou, B., and Feng, H. (2011). Dual effectiveness of sodium chlorite for

enzymatic browning inhibition and microbial inactivation on fresh-cut apples. LTW-Food

Science and Technology 44(7): 1621-1625.

Marques, L., Fleuriet, A., and Macheix, J. (1995). Characterization of multiple forms of

polyphenoloxidase from apple fruit. Plant Physiol. Biochem. 33: 193-200.

Marshall, M. R., Kim, J. M., and Wei, C. I. (2000). Enzymatic browning in fruits, vegetables and

seafoods. http://www.fao.org/ag/ags/agsi/ENZYMEFINAL/Enzymatic%20Browning.html

Martinez, M. V., and Whitaker, J. R. (1995). The biochemistry and control of enzymatic

browning. Trends Food Sci. Technol. 6: 195–200.

http://www.sciencedirect.com/science/journal/0041624X/44/supp/S

http://www.fao.org/ag/ags/agsi/ENZYMEFINAL/Enzymatic%20Browning.html

73

Mason, T. J. (1998). An introduction to ultrasonic food cutting. In: Ultrasound in Food

Processing, edited by Povey, M.J.W. and Mason, T.J. New York: Blackie Academic&

Professional, pp.254-269.

McClements, D. J., and Decker, E. A. (2000). Lipid oxidation in oil-in-water emulsions: impact

of molecular environment on chemical reactions in heterogeneous food systems. J. Food Sci.

65(8): 1270–1282.

Min, D. B., and Boff, J. M. (2002). Lipid oxidation of edible oil. In: Akoh, C.C., and Min, D.B.,

Eds., Food Lipids: Chemistry, Nutrition, and Biotechnology. Marcel Dekker, New York.

Montgomery, M. W., and Sgarbieri, V. C. (1975). Isoenzymes of banana polyphenol oxidase.

Phytochemistry. 14: p. 1245.

Muccio, E. A. (1999). Decoration and assembly of plastic parts. Materials Park, OH: ASM

International.

Nawar, W. W. (1996). Lipids. In Food Chemistry, O.R. Fennema (Eds), p. 225–235. Marcel

Dekker Inc., New York.

Nicolas, J. J., Richard-forget, F. C., Goupy, P. M., Amiot, M., and Aubert, S. Y. (1994).

Enzymatic browning reactions in apple and apple products. Crit. Rev. Food Sci. Nutr. 34: 109-

157.

Paul, B., and Gowda, L. R. (2000). Purification and characterization of polyphenol oxidase from

the seeds of field bean (Dolichos lablab). J. Agric. Food Chem. 48: 3839–3846.

Perez-Gilabert, M., and Carmona, F. G. (2000). Characterization of catecholase and cresolase

activities of eggplant polyphenol oxidase. J. Agric. Food Chem. 48: 695–700.

74

Pérez-Gago, M. B., Serra, M., Alonso, M., Mateos, M., and del Río, M. A. (2005). Effect of

whey protein and hydroxypropyl methylcellulose-based edible composite coatings on color

change of fresh-cut apples. Postharvest Biol and Tech. 36: 77-85.

Piergiovanni, L., Noni, I. D., Fava, P., and Schiraldi, A. (1989). Nonenzymatic browning in

processed cheeses. Kinetics of the Maillard reaction during processing and storage. Italian

Journal of Food Science. 2: 11–20.

Portela, S. I., and Cantwell, M. I. (2001). Cutting blade sharpness affects appearance and other

quality attributes of fresh-cut cantaloupe melon. J. Food Sci. 66: 1265–1270.

Priego-Capote, F., Ruiz-Jimenez, J., Garcia-Olmo, J., and Luque de Castro, M. D. (2004). Fast

method for the determination of total fat and trans fatty-acids content in bakery products based

on microwave-assisted Soxhlet extraction and medium infrared spectroscopy detection.

Analytica Chimica Acta. 517: 13-20

Rawson, F. F. (1998). An introduction to ultrasonic food cutting. In: Povey, M.J.W., Mason, T.J.

(Eds.), Ultrasound in Food Processing. Blackie Academic, London, UK, pp. 254–269.

Raymond, J., Rakariyatham, N., and Azanza, J. L. (1993). Purification and some properties of

polyphenoloxidase from sunflower seeds. Phytochemistry. 34: 927–931.

Recknagel, R. O., and Glende, E.A. (1984). Spectrophotomctric detection of lipid conjugated

dienes. Methods Enzymol. 105: 331–337.

Richardson, T., and Hyslop, D. B. (1985). Enzymes. In Food Chemistry; Fennema, O. R., Ed.;

Marcel Dekker: New York, pp. 371-476.

Rico, D., Mart´ın-Diana, A. B., Barat, J. M., and Barry-Ryan, C. (2007). Extending and

measuring the quality of fresh-cut fruit and vegetables: A review. Trends Food Scie. Technol.

18: 373–386.

http://www.uco.es/investiga/grupos/FQM-227/datos/publications/pub2004.htm

75

Riuz, A., Ayora-Canada, M. J., and Lendl, B. (2001). Bead injection for surface enhanced

Raman spectroscopy: automated on-line monitoring of substrate generation and application in

quantitative analysis. Analyst. 126: 242–246.

Saltveit, M. E. (1997). Physical and physiological changes in minimally processed fruits and

vegetables. In: Phytochemistry of Fruits and Vegetables, pp. 205–220. Tomás-Barberan, F. A.,

and Robins, R. J., Eds., Phytochemistry Society Europa, Clarendon, Oxford.

Saltveit, M. E., Choi, Y. J., and Tomás-Barberán, F. A. (2005). Involvement of components of

the phosopholipid-signalling pathway in wound-induced phenylpropanoid metabolism in lettuce

(Lactuca sativa) leaf tissue. Physiol. Plant. 125: 345–355.

Sapers, G. M., Garzarella, L., and Pilizota, V. (1990). Application of browning inhibitors to cut

apple and potato by vacuum and pressure infiltration. J. Food Sci. 55: 1049-1053.

Schaich, K. M., Shahidi, F., Ying Zhong, N. A., and Eskin, M. (2013). Biochemistry of Foods

Third edition, p. 419-529.

Schneider, Y., Zahn, S., and Linke, L. (2002). Qualitative process evaluation for

ultrasoniccutting of Food. Engineering in Life Sciences. 2: 153-157.

Schneider, Y., Zahn, S., and Rohm, H. (2011). Ultrasonic cutting of foods. In Ultrasound

Technologies for Food and Bioprocessing, (eds.) Feng, H., Barbosa, G.V., Weiss, J. Springer,

New York, NY.

Shahidi, F. (2000). Antioxidants in food and food antioxidants. Nahrung. 44: 158–163.

Shewfelt, R. L. (1986). Flavor and color of fruits as affected by processing. In Commercial Fruit

Processing, J.G. Woodroof and B.S. Luh (Eds), p. 481–529, Avi Publishing Co., Westport, CT.

Slater, T. F. (1984). “Overview of methods for detecting lipid peroxidation.” Methods Enzymol.

105: 283–293.

76

Soxhlet, F. (1879). Die gewichtsanalytische bestimmung des milchfettes. Dingler’s Polyt. J. 232:

461-465.

Swern, D. (1961). Primary products of olefinic autoxidation. In: Lundberg, W.O. (Ed.),

Autoxidation and Antioxidants, Vol. 1. Interscience, New York, pp. 1-54.

Upreti, P., and Metzger L. E. (2007). Influence of calcium and phosphorus, lactose, and salt-to-

moisture ratio on cheddar cheese quality: pH changes during ripening. J Dairy Science. 90(1):1-

12.

Valero, E., Varon, R., and Garcia-carmona, F. (1988). Characterization of polyphenol oxidase

from Airen grapes. J. Food Sci. 53: 1482-1485.

Varoquaux, P., and Wiley, R.C. (1994). Biological and biochemical changes in minimally

processed refrigerated fruits and vegetables. p. 226-268. In: R.C. Wiley (ed.). Minimally

processed refrigerated fruits and vegetables. Chapman and Hall, New York.

Vercellotti, J. R., St. Angelo, A. J., and Spanier, A. M. (1992). in A. J. St. Angelo, ed., Lipid

Oxidation in Food. ACS Symposium Series 500, American Chemical Society, Washington, D.C.,

pp. 1–11.

Watada, A. E., Abe, K., and Yamauchi, N. (1990). Physiological activities of partially processed

fruits and vegetables. Food Technol. 44:116, 118, 120-122.

Whitaker, J. R. (1994). Principles of Enzymology for the Food Sciences. Second Ed., pp. 271-

556, Marcel Dekker, New York.

Whitaker, J. R. (1996). Enzymes. In Food Chemistry, O.R. Fennema (Eds), p. 431–530, Marcel

Dekker Inc., New York, NY.

77

Wong, N. P. (1974). Milk clotting enzymes and cheese chemistry part II. Cheese chemistry. In

"Fundamentals of Dairy Chemistry" 2ed Ed. Edited by web, B.H., Johnson, Company, westport,

Conneticut, USA.

Yoruk, R., and Marshall, M. R. (2003). Physicochemical properties and function of plant

polyphenol oxidase: a review. J. Food Biochem. 27: 361–422.

Yue-Ming, J., Zauberman, G., and Fuchs, Y. (1997). Partial purification and some properties of

polyphenol oxidase extracted from litchi fruit pericarp. Postharvest Biol. Tech. 10: 221-228.

Zahn, S., Schneider, Y., and Rohm, H. (2005). Impact of excitation and material parameters on

the efficiency of ultrasonic cutting of bakery products. Journal of Food Science. 70: 510-513.

Zahn, S., Schneider, Y., and Rohm, H. (2006). Ultrasonic cutting of foods: Effects of excitation

magnitude and cutting velocity on the reduction of cutting work. Innovative Food Science &

Emerging Technologies. 7: 288-293.

78

Appendix A. Preparation solution for PPO activity

0.5 M phosphate buffer

Na2HPO4 (sodium phosphate, dibasic): 14.196 g + 2 L distilled water

NaH2PO4 (monosodium phosphate):15.602 g + 2 L distilled water

Combine these solutions with a magnetic mixer to prepare 0.5 M phosphate buffer.

0.05 M phosphate buffer

Na2HPO4 (sodium phosphate, dibasic): 70.98 g + 1 L distilled water

NaH2PO4 (monosodium phosphate):78.01 g + 1 L distilled water

Combine these solutions with a magnetic mixer to prepare 0.05 M phosphate buffer.

79

Appendix B. Absorbance vs. time curve and slope of the curve of red delicious apples cut

with and without ultrasound for the first day

(a)

The slope of the curve: 0.0022

(b)


Time (s)

Absorbance (420nm)

0 0.9321

15 0.9349

30 0.9455

45 0.9522

60 0.9535

75 0.9543

90 0.9552

105 0.9568

120 0.9579

135 0.9592

150 0.9599

165 0.9609

180 0.9628

Time (s) Absorbance

(420nm)

0 0.7371

15 0.7389

30 0.7405

45 0.7432

60 0.7442

75 0.7443

90 0.7462

105 0.7472

120 0.7487

135 0.7492

150 0.7502

165 0.7515

180 0.7533

y = 0.0022x + 0.9372

0.91

0.92

0.93

0.94

0.95

0.96

0.97

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)

Linear(Absorbance(420nm))

y = 0.0013x + 0.7369

0.725

0.73

0.735

0.74

0.745

0.75

0.755

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


80

(c)


(d)


(a) absorbance vs. time curve of red delicious apples cut without ultrasound for the first day; (b) absorbance vs. time

curve of red delicious apples cut with ultrasound (30% amplitude) for the first day; (c) absorbance vs. time curve of

red delicious apples cut with ultrasound (40% amplitude) for the first day; (d) absorbance vs. time curve of red

delicious apples cut with ultrasound (50% amplitude) for the first day.

Time (s) Absorbance

(420nm)

0 0.822

15 0.824

30 0.827

45 0.83

60 0.835

75 0.84

90 0.848

105 0.855

120 0.895

135 0.905

150 0.925

165 0.948

180 0.972

Time (s) Absorbance

(420nm)

0 0.1085

15 0.1087

30 0.1089

45 0.1092

60 0.1097

75 0.11

90 0.1111

105 0.1123

120 0.1151

135 0.1165

150 0.1173

165 0.1187

180 0.1201

y = 0.0125x + 0.7838

0

0.2

0.4

0.6

0.8

1

1.2

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


y = 0.001x + 0.1055

0.095

0.1

0.105

0.11

0.115

0.12

0.125

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


81

Appendix C. Absorbance vs. time curve and slope of the curve of golden delicious apples

cut with and without ultrasound for the first day

(a)


(b)


Time (s) Absorbance

(420nm)

0 0.8361

15 0.8379

30 0.8495

45 0.8522

60 0.8532

75 0.8543

90 0.8552

105 0.8562

120 0.8577

135 0.8582

150 0.8592

165 0.8605

180 0.8605

Time (s) Absorbance (420nm)

0 0.3826

15 0.384

30 0.3852

45 0.3862

60 0.3872

75 0.3887

90 0.3894

105 0.3921

120 0.3922

135 0.3934

150 0.3938

165 0.3941

180 0.3954

y = 0.0019x + 0.8403

0.82

0.825

0.83

0.835

0.84

0.845

0.85

0.855

0.86

0.865

0.87

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


y = 0.0011x + 0.382

0.375

0.38

0.385

0.39

0.395

0.4

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


82

(c)


(d)


(a) absorbance vs. time curve of golden delicious apples cut without ultrasound for the first day; (b) absorbance vs.

time curve of golden delicious apples cut with ultrasound (30% amplitude) for the first day; (c) absorbance vs. time

curve of golden delicious apples cut with ultrasound (40% amplitude) for the first day; (d) absorbance vs. time curve

of golden delicious apples cut with ultrasound (50% amplitude) for the first day.

y = 0.0008x + 0.1135

0.1080.11

0.1120.1140.1160.118

0.120.1220.1240.126

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)



0 0.296

15 0.2961

30 0.297

45 0.2974

60 0.2985

75 0.2991

90 0.2998

105 0.301

120 0.3025

135 0.3042

150 0.3052

165 0.306

180 0.3086

Time

(s)

Absorbance

(420nm)

0 0.1139

15 0.1155

30 0.116

45 0.1167

60 0.1173

75 0.1178

90 0.1188

105 0.1193

120 0.1201

135 0.1209

150 0.1217

165 0.1225

180 0.1238

y = 0.001x + 0.2936

0.285

0.29

0.295

0.3

0.305

0.31

0 30 60 90 120 150 180A

bso

rban

ce (

42

0 n

m)

Time (s)

Absorbance(420nm)


83

Appendix D. Absorbance vs. time curve and slope of the curve of red delicious apples

treated with 1% CaA solution in combined with ultrasound (50% amplitude) and without

ultrasound for the first day

(a)

0.0003 is the graph's slope.

(b)


(a) absorbance vs. time curve of red delicious apples treated with 1% CaA solution in combined with ultrasound

(50% amplitude); (b) absorbance vs. time curve of red delicious apples treated with 1% CaA solution in combined

without ultrasound.

y = 0.0003x + 0.1192

0.116

0.118

0.12

0.122

0.124

0 30 60 90 120 150 180Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


y = 0.0005x + 0.1108

0.106

0.108

0.11

0.112

0.114

0.116

0.118

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


Time (s) Absorbance

(420nm)

0 0.1186

15 0.1195

30 0.1205

45 0.1209

60 0.1211

75 0.1211

90 0.1213

105 0.1214

120 0.1215

135 0.1218

150 0.122

165 0.1225

180 0.1231

Time (s) Absorbance

(420nm)

0 0.1109

15 0.1115

30 0.1121

45 0.1126

60 0.1132

75 0.1144

90 0.1145

105 0.1148

120 0.1151

135 0.1155

150 0.1158

165 0.1161

180 0.1165

84

Appendix E. Absorbance vs. time curve and slope of the curve of golden delicious apples

treated with 1% CaA solution in combined with ultrasound (50% amplitude) and without

ultrasound for the first day

(a)


(b)


(a) Absorbance vs. time curve of golden delicious apples treated with 1% CaA solution in combined with ultrasound

(50% amplitude); (b) absorbance vs. time curve of golden delicious apples treated with 1% CaA solution in

combined without ultrasound.

y = 0.0002x + 0.1205

0.119

0.12

0.121

0.122

0.123

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)


y = 0.0004x + 0.108

0.1

0.102

0.104

0.106

0.108

0.11

0.112

0.114

0 30 60 90 120 150 180

Ab

sorb

ance

(4

20

nm

)

Time (s)

Absorbance(420nm)



0 0.1208

15 0.1209

30 0.1209

45 0.1211

60 0.1213

75 0.1214

90 0.1214

105 0.1219

120 0.1222

135 0.1223

150 0.1225

165 0.1225

180 0.1227

Time (s) Absorbance

(420nm)

0 0.1056

15 0.1085

30 0.1105

45 0.1109

60 0.1111

75 0.1111

90 0.1114

105 0.1114

120 0.1115

135 0.1118

150 0.1122

165 0.1125

180 0.1131

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ULTRASONIC CUTTING OF CHEESE AND APPLES - Ideals