Experimental studies and modelling of innovative peeling processes for

tough-skinned vegetables

Bagher Emadi

M.Sc. Mechanics of Agricultural Machinery B.Sc. Agricultural Machinery

Thesis submitted as a requirement for the degree of

Doctor of Philosophy

School of Engineering Systems Faculty of Built Environment and Engineering

Queensland University of Technology 2005

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This dissertation is dedicated to my wife, Masoumeh, and my two lovely

children, Roya and Amir Reza

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Keywords peeling, mechanical peeling, abrasive peeling, mechanical properties, tough-skinned vegetables, model, mathematical model, peeling rate, peeling efficiency, peel losses, pumpkin, melon

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Abstract: Tough-skinned vegetables such as pumpkin and melon currently are peeled either

semi-automatically or automatically. The main limitation of both methods, especially

for varieties with an uneven surface, is high peeling losses.

Improvement of current mechanical peeling methods and development of new

mechanical methods for tough-skinned vegetables which are close to the “ideal”

peeling conditions using mechanical properties of the product were the main

objectives of this research.

This research has developed four innovative mechanical peeling methods on the basis

of the mechanical properties of tough-skinned vegetables. For the first time, an

abrasive-cutter brush has been introduced as the best peeling method of tough-skinned

vegetables. This device simultaneously applies abrasive and cutting forces to remove

the peel. The same peeling efficiency at concave and convex areas in addition to high

productivity are the main advantages of the developed method. The developed peeling

method is environmentally friendly, as it minimises water consumption and peeling

wastes.

The peeling process using this method has been simulated in a mathematical model

and the significant influencing parameters have been determined. The parameters are

related to either the product or peeler. Those parameters appeared as the coefficients

of a linear regression model. The coefficients have been determined for Jap and

Jarrahdale as two varieties of pumpkin. The mathematical model has been verified by

experimental results.

The successful implementation of this research has provided essential information for

the design and manufacture of a commercial peeler for tough-skinned vegetables. It is

anticipated that the abrasive-cutting method and the mathematical model will be put

into practical use in the food processing industry, enabling peeling of tough-skinned

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vegetables to be optimised and potentially saving the food industry millions of dollars

in tough-skinned vegetable peeling processes.

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Contents Keywords iii

Abstract iv

List of Symbols and Abbreviations xvi

Authorship xviii

Acknowledgement xix

1 Introduction

1.1 Significance and motivation of the research 1

1.2 Objectives of the research 4

1.3 Originality and major contribution of the thesis 4

1.3.1 Definition of tough-skinned vegetables 4

1.3.2 Determination of mechanical properties

of tough-skinned vegetables 5

1.3.3 Developing new mechanical peeling methods

for tough-skinned vegetables 5

1.3.4 Developing current peeling methods 5

1.3.5 Introducing the best mechanical peeling method

applicable in peeling industry for tough-skinned

vegetables 6

1.3.6 Mathematical modelling of mechanical peeling 6

1.3.7 Determination of design parameters of

tough-skinned vegetable peeler 6

1.4 Thesis organization 7

1.5 Publications (refereed) of the author arising from the PhD

Research 8

2 Literature review

2.1 Mechanical properties of fruits and vegetables and

methods of testing 11

2.1.1 Introduction 11

2.1.2 States of product to be tested 11

2.1.3 Compression test 12

2.1.4 Cutting test 13

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2.1.5 Shear strength test 13

2.1.6 Coefficient friction test 14

2.2 Peeling methods of fruits and vegetables 15

2.2.1 Introduction 15

2.2.2 Mechanical peeling 15

2.2.2.1 Abrasive devices 16

2.2.2.2 Devices using drums 17

2.2.2.3 Devices using rollers 17

2.2.2.4 Knives or blades 17

2.2.2.5 Milling cutter 20

2.2.3 Thermal peeling 22

2.2.3.1 Flame (dry heat peeling) 23

2.2.3.2 Steam (wet heat peeling) 23

2.2.3.3 Thermal blast peeling 25

2.2.3.4 Freeze-thaw 25

2.2.3.5 Vapour explosion (Vacuum peeling) 26

2.2.4 Chemical peeling 26

2.2.4.1 Caustic (lye) peeling 26

2.2.4.2 Enzymic peeling 28

2.3 The current situation of peeling tough-skinned vegetables 30

2.4 Mathematical modelling of peeling process 30

2.5 Conclusions and discussion 32

2.6 Summary 33

3 Testing of mechanical properties of tough-skinned vegetables

3.1 Introduction 35

3.2 Design and construction of instrumentation for testing

vegetables properties 37

3.2.1 Cutter 37

3.2.2 Holder of unpeeled sample 37

3.2.3 Holder of skin sample 38

3.2.4 Indentor 38

3.2.4.1 Spherical end indentor 38

3.2.4.2 Flat end indentor 38

3.2.4.3 Cutting indentor 39

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3.2.5 Curvature meter 39

3.2.6 Friction coefficient tester 39

3.3 Testing methodology 39

3.3.1 Force-deformation test 41

3.3.2 Shear strength test 41

3.3.3 Cutting force test 42

3.3.4 Friction coefficient test 42

3.3.5 The relative contribution of skin to the

unpeeled mechanical properties 43

3.4 Results and discussion 43

3.4.1 Force-deformation relationship 44

3.4.2 Toughness 47

3.4.3 Cutting force 47

3.4.4 Maximum force of shear strength 48

3.4.5 Shear strength 49

3.4.6 Static coefficient of friction 50

3.4.7 The relative contribution of skin to

unpeeled mechanical properties 50

3.4.8 Application of investigated mechanical properties 53

3.5 Summary 55

4 Testing equipment for investigation of mechanical peeling methods

4.1 Introduction 56

4.2 Objectives of the design 57

4.2.1 Adaptability for investigation of different mechanical

peeling tools 57

4.2.2 Possibility of accommodation of different product size 57

4.2.3 Possibility of peeler head position adjustment 57

4.2.4 Possibility of peeler tool position adjustment 57

4.2.5 Possibility of rotation of peeler tool at

different angular velocities 58

4.2.6 Possibility of rotation of vegetable holder at

different angular velocities 58

4.2.7 Simplicity and low cost of manufacturing 58

4.3 Enforcement of the objectives 58

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4.3.1 Chassis and chamber 58

4.3.2 Vegetable holder 58

4.3.3 Peeler head 61

4.3.4 Attachments 63

4.4 Performance of the test rig 64

4.5 Summary 65

5 Preliminary trials of different mechanical peeling methods

5.1 Introduction 66

5.2 Trials of different tools 67

5.2.1 Wire brush 67

5.2.1.1 Rotary wire brush 67

5.2.1.2 Twisted wire brush 68

5.2.2 Ball chain tool 71

5.2.3 Milling cutter 72

5.2.4 Mower trimming lines 73

5.2.5 Abrasive ropes 74

5.2.6 Abrasive pads 74

5.2.7 Abrasive foams 75

5.2.8 Rope covered by spiral blade 75

5.2.9 Sandpaper belt 77

5.2.10 Abrasive plates 78

5.2.11 Abrasive-cutter brush 79

5.2.12 Abrasive bristle products 80

5.3 Conclusions 81

5.4 Summary 82

6 Experimental investigation of mechanical peeling methods

6.1 Introduction 83

6.2 The criteria of experiments 84

6.2.1 Peel losses 84

6.2.2 Peeling efficiency 84

6.2.3 Estimated responses 85

6.2.4 Data analysis 86

6.3 Peeling by using milling cutter 86

6.3.1 Introduction 86

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6.3.2 Material of experiments 86

6.3.3 Results and discussion 88

6.3.4 Optimization and estimation of the responses 90

6.4 Peeling by using abrasive pads 92

6.4.1 Introduction 92

6.4.2 Material of experiments 92

6.4.3 Results and discussion 94

6.4.4 Optimization and estimation of the responses 98

6.5 Peeling by using abrasive foams 98

6.5.1 Introduction 98

6.5.2 Material of experiments 99

6.5.3 Results and discussions 100

6.5.4 Optimization and estimation of the responses 104

6.6 Peeling by using abrasive-cutter brush 105

6.6.1 Introduction 105

6.6.2 Material of experiments 106

6.6.3 Results and discussion 108

6.6.4 Optimization and estimation of the responses 111

6.7 The comparison of the four innovative peeling methods 112

6.8 Potential industrial application of abrasive-cutter brush 113

6.9 Conclusions 113

6.10 Summary 115

7 Abrasive-cutter brush, full factorial experiments, and ANOVA

7.1 Introduction 116

7.2 Material of experiments 117

7.3 Peeling rate 119

7.4 Data analysis 119

7.5 Results and discussion 119

7.5.1 The effect of p. speed on LnP. rate 122

7.5.1.1 The effect of p. speed on LnP.rate for

different levels of coarseness 123

7.5.1.2 The effect of p. speed on LnP.rate

in different locations of product 125

7.5.2 The effect of coarseness on LnP. rate 126

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7.5.2.1 The effect of coarseness on LnP.rate

at different p. speed 127

7.5.2.2 The effect of coarseness on LnP.rate

at different locations of pumpkin 128

7.5.3 The effect of location of product’s surface on LnP.rate 129

7.5.3.1 The effect of location on LnP.rate in

different coarseness of brush 130

7.5.3.2 The effect of location of product’s surface

on LnP.rate at different p. speed 131

7.6 Conclusions and discussion 132

7.7 Summary 134

8 Modelling of mechanical peeling as sum of consumed energy

in peeling process

8.1 Introduction 135

8.2 Theory of the model 136

8.2.1 The assumptions 136

8.2.2 Development of the model 136

8.2.3 Determination of the model coefficients 145

8.2.4 Model validation 145

8.3 Results and discussion 146

8.3.1 Model coefficients 146

8.3.2 Model validation 149

8.3.3 Applicability of the model 150

8.4 Conclusions 151

8.5 Summary 151

9 Conclusions and perspectives

9.1 Thesis summary and conclusions 153

9.2 Directions for future research 155

Appendices 158

1.1 Multiple comparisons of the mean of the mechanical properties 158

1.2 Multiple Comparisons of contribution of skin to the

mechanical properties 171

1.3 Mechanical properties of varieties of melon and pumpkin

in three different states including skin, unpeeled, and flesh 176

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1.4 Relative contribution (%) of skin to different mechanical

properties for three pumpkin varieties including Jarrahdale,

Jap, and Butternut 177

1.5 Drawings of instrumentations 178

2.1 Test rig 184

3.1 Experimental results of using milling cutter 196

3.2 Experimental results of using abrasive pads 196

3.3 Experimental results of using abrasive foams 197

3.4 Experimental results of using abrasive-cutter brush 198

4.1 Normality assessment of peeling rate (g/min) of Jap and

Jarrahdale varieties 199

4.2 Multi comparisons of the mean of LnP.rate among different

levels of independent variables 205

Bibliography 208

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List of Figures 1.1 The top view of pumpkin 3

2.1 Force-deformation curve 13

2.2 An industrial application of an abrasive roller peeler for tuberal

products such as potato 18

2.3 General feature of milling cutter in use 21

2.4 Enzymic peeled (right side) and manual (left side) peeled grapefruit 29

3.1 The instrumentations of testing mechanical properties of vegetables 40

3.2 Effects of force-deformation test (a-d) and relationship between

force (N) and deformation (mm) for melon and pumpkin in two cases

of skin and unpeeled (e-f) 45

3.3 Rupture force of skin and unpeeled states for different varieties

of pumpkin and melon 46

3.4 Toughness of skin and unpeeled states for different varieties of

pumpkin and melon 47

3.5 Cutting force of skin, flesh and unpeeled states for different

varieties of pumpkin and melon 48

3.6 The maximum shear strength force of skin, flesh and unpeeled

states for different varieties of pumpkin and melon 49

3.7 The shear strength of skin, flesh and unpeeled states for different

varieties of pumpkin and melon 50

3.8 The relative contribution (%) of skin to different mechanical

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properties of Pumpkin and Melon 52

4.1 Test rig 59

4.2 Product holder and two available positions 60

4.3 The two D.C. sources for vegetable holder and peeler head 60

4.4 Product holder 61

4.5 Details of the peeler head 62

4.6 Peeler head 62

4.7 Flap with holes in spiral pattern 63

4.8 The auxiliary peeler head as attachment 64

5.1 Rotary wire brush and its peeling effect on pumpkin 67

5.2 Twisted wire brush before and after loosening strands 68

5.3 Affected areas of pumpkin after using twisted wire brush 69

5.4 Improved design of artificial twisted brush in second stage

and its effects 70

5.5 The twisted wire brush in third stage and its peeling effect 71

5.6 Ball chain and its peeling effect after application 71

5.7 Different investigated lathe tools (a) and cutter in cylindrical

shape with triangular side section (b) 72

5.8 The effect of peeling by wedgy side cutter 73

5.9 Abrasive rope and its peeling effect on pumpkin 74

5.10 Different shapes of abrasive foam and their peeling effect

on pumpkin 76

5.11 Rope covered by spiral blade (a), and its peeling effect on pumpkin (b) 77

5.12 Sandpaper belt installed on test rig with and without pumpkin 77

5.13 Grater plate peeling unit and its effect on pumpkin 78

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5.14 Abrasive cutter brush and its effects on two stages 80

5.15 Abrasive bristle products 81

6.1 Disk shape milling cutter with triangular contour 88

6.2 The contribution of independent variables to responses resulted

from using milling cutter 89

6.3 The effects of independent variables on responses resulted from

using milling cutter 91

6.4 Abrasive peeler pads and accessories 93

6.5 The contribution of independent variables to responses resulted

from using abrasive-pads 95

6.6 The effects of independent variables on responses resulted from

using abrasive pads 96

6.7 Abrasive foam and accessories 99

6.8 The contribution of independent variables to responses resulted

from using abrasive foams 102

6.9 The effects of independent variables on responses resulted from

using abrasive foams 103

6.10 Abrasive-cutter brush 107

6.11 The contribution of independent variables to responses resulted

from using abrasive-cutter brush 109

6.12 The effects of independent variables on responses resulted

from using abrasive-cutter brush 110

7.1 The different type of stripes of coarseness used for fabrication

of abrasive-cutter brush 118

7.2 Different parts of product as levels of location variable 118

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7.3 The effect of mean p. speed on LnP.rate 124

7.4 The effect of p. speed on LnP.rate at different levels of coarseness 124

7.5 The effect of p. speed on LnP.rate at different in different

locations of pumpkin 125

7.6 The effect of mean coarseness on LnP.rate 127

7.7 The effect of coarseness on LnP.rate at different speed of

abrasive-cutter brush 128

7.8 The effect of coarseness on LnP.rate at different location

of product 129

7.9 The effect of mean location on LnP.rate 130

7.10 The effect of location on LnP.rate in different coarseness 131

7.11 The effect of location on LnP.rate at different p. speeds 132

8.1 The view of abrasive-cutter brush after penetration to the peel 137

8.2 The cross-sectional view of one protrusion

(two out of four teeth are shown) 138

8.3 Experimental versus predicted values of p. rate (gr/min) 149

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List of Tables 3.1 Static coefficient of friction of three varieties of pumpkin in the flesh,

unpeeled, and without periderm state on three different materials

including stainless steel, Teflon, and wood………………………………....51

6.1 Taguchi experimental design for independent variables and levels………....88

6.2 Taguchi experimental design for independent variables and levels…………94

6.3 Taguchi experimental design for independent variables and levels………...101

6.4 Taguchi experimental design for independent variables and levels………...108

7.1 The results of frequencies analysis on peeling rate…………………………120

7.2 The results of frequencies analysis on LnP.rate…………………………….121

7.3 The results of Levene’s test for homogeneity of variance of LnP.rate……..121

7.4 ANOVA of the mean of LnP. rate among different levels of

independent variables ………………………………………………………122

8.1 The results of multiple regression analysis for coefficients of two

mechanical peeling models……………………………………………........147

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List of Symbols and Abbreviations Pt total expenditure power, N. mm/min P1 expenditure power at fracture part of cutting, N. mm/min P2 expenditure power at forming part of cutting, N. mm/min ηc total peeling efficiency n the number of installed brushes on peeler head ωp the angular velocity of abrasive-cutter brush, rpm Ep penetration energy of abrasive-cutter brush, N. mm Ed the deflection energy of abrasive-cutter brush, N. mm K1 average shearing resistance per unit length of stroke, N/mm Vip linear penetration velocity of brush’s teeth inside peel, mm/s t1 time of stroke, s δ1 deflection of product, mm δ2 the depth of average penetration, mm γ the ratio of toughness of product (Tp) to toughness of tool (Tt) Tp the toughness of product, N. mm Tt the toughness of abrasive-cutter brush, N. mm α the density of protrusions on a brush, number/mm2 l1 the effective length (covered by abrasive strip) of brush, mm d1 the diameter of brush, mm τ the shear strength of product, N/mm2

d2 the diameter of protrusion’s hole, mm l2 the length of each tooth on protrusion, mm θ1 the angle of teeth in protrusion, degree E the modulus of elasticity of the brush, N.mm-2 I the geometrical moment of inertia of the brush, mm4 δ3 the average deflection of the brush at fracture stage, mm L the whole length of brush, mm δ3max the maximum deflection of brush in fracture stage, mm Vop the linear velocity of brush’s teeth in scratching stage, mm/s Fc total cutting force, N Ff friction force, N Fd disintegration force on the structure of product, N Fe the spent force for elastic and plastic deformation, N Ef the expended friction energy, N. mm h the length of removed peel, mm K2 the friction coefficient α the density of protrusion, number/mm2 φ the degree of unevenness of product’s surface μd the dynamic coefficient of friction between the brush’s tooth

and product Rv the total normal reaction, N Fde deflection force of brush, N N the normal reaction force to the weight of brush, N W1 the weight of one brush, g

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θ2 the angle between direction of the weight and direction of the line passes through the gravity centre of brush and is perpendicular to the surface of product in contact point, degree

δ4 the average deflection of brush in second stage of cutting, mm l3 the total projected lengths of protrusion’s teeth engaged in

cutting, mm K3 the coefficient of elastic and plastic force E2 the total required energy of peeling in second stage, N. mm K4 the coefficient of disintegration force K5 scratching coefficient in second stage, number/min ωv angular velocity of vegetable holder, rpm β the number of scratches, number/min P. rate peeling rate, g/min LnP.rate the logarithmic transform of P. rate, g/min K6 transform coefficient of Pt to p. losses, g/N. mm v. speed the angular velocity of vegetable holder, rpm p. speed the angular velocity of peeler head, rpm peeling losses the substantial amount of usable vegetable flesh that is being

discarded because of peeling, % of weight of whole produce before peeling

peel losses the ratio of the weight of removed peel to the weight of whole produce before peeling divided by time of peeling, %/min

peeling efficiency the percentage peel that is removed from the initial skin per unit time, %/min

peeling rate the weight of removed peel divided by peeling time, g/min

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Authorship The work contained in this thesis has not been previously submitted for a degree or diploma at this or any other educational institute. To the best of my knowledge and belief, the thesis contains no material previously published or written by another person except where due reference is made. Signature: …………………… Date: …………………....

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Acknowledgement The foremost gratitude to my God, Allah, who offered me this opportunity to learn

and progress. I appreciate Him for delighting me with kind parents who supported and

encouraged me. I am thankful to Him for blessing me with my wife, Masoumeh, who

showed patience and support during this research.

I would like to express my appreciation to my principal supervisor, Dr. Vladis Kosse,

for his time and valuable suggestions in supervising this thesis. I also thank my

associate supervisor, Prof. Prasad KDV Yarlagadda, for his support and suggestions.

The author wishes to thank Dr. Mahalinga Iyer, Dr. Prasad Gudimetla, and Dr. Kunle

Oloyede, School of Engineering Systems, QUT, for reading thesis and their valuable

comments.

I wish to express my gratitude to the government of Islamic Republic of Iran for

financial support through a PhD scholarship award.

I also wish to thank all former and present members of School of Engineering

Systems. Special thanks to Mr. Terry Beach, Mr. Mark Hayne, and Mr. Abdul Sharif

for their technical support.

Finally, I would like to thank my fellow students and colleagues for their company

and interesting discussions over the past three years.

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Chapter 1

Introduction

1.1 Significance and motivation of the research

The food and beverage sector was the largest sector of Australia’s manufacturing

industry in 2002-03, providing about 20% of total sales and services income. The

total income from sales and services for the Australian food processing industry was

estimated at $65.9 billion in the same year. The industry value added by the food

processing industry was recorded as $16.6 billion in 2002-03 (Department of

Agriculture, Fisheries and Forestry, NSW).

Peeling is an important preliminary stage of fruit and vegetable processing. The

quality and the final price of the processed product is highly dependant on this stage.

Manual peeling is possible for any kind of product but high losses and considerable

consumption of time and labour have encouraged the peeling industry to use other

methods. Mechanical, thermal, and chemical peelings are conventional methods

(Luh, and Woodroof., 1988), each of which has its own benefits and limitations.

Those methods apply mechanical tools, heat or cold, and lye respectively to peel off

the fruit and vegetable skins. As none of the current methods can satisfy all

requirements of producers and consumers, other kinds of peeling methods such as

enzymatic peeling have been developed. Changing the peeling technique has

changed the kind of merits and demerits but the problem is still unsolved. Getting

closer to the “ideal” peeling method is the aim of every researcher in this field. The

“ideal” peeling method possesses the following features (Radhakrishnaiah settee et

al., 1993):

-minimizes product losses

-peels to the extent dictated by the products

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-minimizes energy and chemical usage

-minimizes the pollution loads

-minimizes heat ring formation

Among the current peeling methods, mechanical methods can attract the satisfaction

of consumers as these methods possess some important benefits of the “ideal”

method such as the freshness of the peeled product. As the view of consumers is

important to the food processing industry researchers are encouraged to continue

the search for mechanical peeling methods that are closer to the “ideal” peeling, in

spite of the high losses so far experienced with these methods.

Approaching the “ideal” peeling method through trial and error is difficult and time

consuming. The design of new methods and improvement of current peeling

methods to achieve the “ideal” peeling conditions using physical and mechanical

properties of the product is one of the objectives of researchers (Ohwovoriole et al.,

1988). Depending on the proposed technique, different properties of products have

been applied to improve the efficiency of purposed peeling methods or devices.

However, despite all attempts, some fruits and vegetables, such as mangoes, are

commonly peeled manually (Radhakrishnaiah settee et al., 1993) and methods for

others such as pumpkin are far from the “ideal” peeling conditions.

Tough-skinned vegetables such as pumpkin and melon currently are peeled either

semi-automatically (i.e. Comet Food Ltd.) or automatically (i.e. Dornow Ltd.).

Comet Food Ltd. is a Brisbane-based organization visited by this researcher which

utilises semi-automatic peeling methods of pumpkin and melon. Circular shapes of

rotating graters are applied in the semi-automatic method. Segments of the product

are brought into contact with the grater by an operator. This process is tedious and

time consuming. In the latter method, whole pumpkins are passed through

automatic machines where the floor is covered by many rotator disks (carborundum

or blade). The main limitation of both methods especially for varieties with an

uneven surface is high peeling losses. For pumpkins as a case study, the minimum

peeling losses in an optimistic situation is about 35% (Department of State and

Regional Development, NSW). As Figure1.1.a shows, penetration to the inside of

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concave areas to peel off through grooves is accompanied by high removal of flesh

from convex areas in the current peeling methods.

a. Current peeling methods

b. The “ideal” peeling method

Fig.1.1.The top view of pumpkin

(a) Current peeling methods (b) “ideal” peeling method

The investigation of concepts for new mechanical peeling methods and

development of design recommendations for peeling of tough-skinned vegetables is

a challenging task in this research. The main objective is to achieve even peeling

Concave area Convex area Layer to be

removed

Layer to be removed

Concave area Convex area

4

efficiency from different areas of uneven surfaced products with minimum peeling

losses (Figure1.1.b).

1.2 Objectives of the research

This research develops new mechanical methods and tools for peeling of tough-

skinned vegetables and recommends important design parameters for a peeler on

the basis of the mechanical properties of those products. The main objectives of the

research are as follows:

• Measurement of the mechanical properties of tough-skinned vegetables,

with pumpkin and melon as the case studies (three varieties each) (addressed

in Chapter 3).

• Development of new innovative mechanical peeling methods and adaptation

of existing methods for tough-skinned vegetables (addressed in Chapter 5).

• Selection of the best peeling method close to the “ideal” peeling method

(addressed in Chapter 6).

• Simulation and mathematical modelling of the mechanical peeling process

(addressed in Chapter 8).

• Development of recommendations for design parameters of a mechanical

peeler for tough-skinned vegetables (addressed in Chapters 3 and 8).

1.3 Originality and major contribution of the thesis

The originality and major contributions of the thesis are summarized in the

following sections.

1.3.1 Definition of tough-skinned vegetables

Despite common use of this term, the review of literature shows that there is no

clear definition for the term “tough-skinned” vegetable. As a result of this thesis, for

the first time, the tough-skinned vegetables could be scientifically defined. This

definition will be the first effort for classification of fruits and vegetables on the

basis of their mechanical properties.

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1.3.2 Determination of mechanical properties of tough-skinned

vegetables

For the first time, some mechanical properties of pumpkin and melon - as two kinds

of tough-skinned vegetables - will be determined. The three investigated varieties of

pumpkin are Jarrahdale, Jap and Butternut and the three investigated varieties of

melon are Rockmelon, Watermelon, and Honeydew. Rupture force, cutting force,

shear strength force, and shear strength will be measured. All properties will be

investigated in three states - skin, flesh, and unpeeled product - except rupture force

and toughness that will be studied in two states - skin and unpeeled product. The

static coefficient of friction also will be measured for three states of product -

unpeeled, without periderm and flesh. This property will be determined for three

different materials - stainless steel, Teflon and wood.

1.3.3 Developing new mechanical peeling methods for tough-

skinned vegetables

Inflexibility of current mechanical peeling methods that causing uneven peeling and

high peeling losses is one of the main current problems for the peeling industry

especially for tough-skinned vegetables. This thesis develops new mechanical

peeling devices suitable for tough-skinned vegetables and close to the conditions of

the “ideal” peeling method. The highlighted feature of these designed devices is that

they do not share the limitations of current peeling tools.

1.3.4 Developing current peeling methods

Peeling by the use of a milling cutter has been successfully introduced by some

researchers (Cailliot and Serge, 1988; Gardiner et al., 1963; Boyce, Jose and Calif,

1961). Clogging as the main limitation prevented the industrial application of the

milling cutter as a peeling device. A new shape of milling cutter will be developed

by this study which can be used without the limitation of previous works. The

criteria of this research (evenness of peeling in different areas of product and higher

peeling efficiency) also will be considered in the developed method.

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1.3.5 Introducing the best mechanical peeling method applicable in

the peeling industry for tough-skinned vegetables

Developing and introducing an innovative mechanical peeling method for tough-

skinned vegetables is the main contribution of this study. The development of

method leads to the provision of necessary and industrially applicable knowledge

for the design and manufacture of the proposed peeler machine. The design

knowledge includes information about the peeling tool and product.

1.3.6 Mathematical modeling of mechanical peeling

No mathematical model for mechanical peeling has been known so far. For the first

time a mathematical model of mechanical peeling will be developed in this thesis.

The model simulates the cutting process by abrasive-cutter brush (developed in this

research). The applicability of the model for the peeling industry will be

emphasized. The variables of input and output of the model will be chosen from

important effective parameters related to the product and peeling tool. Those

variables should be easily measurable and empirically adjustable.

1.3.7 Determination of design parameters of tough-skinned

vegetable peeler

Some necessary design parameters of tough-skinned vegetable peelers are

recommended by the obtained results of this study. These recommendations can be

used by the peeling industry to improve the performance of peeler equipment. The

research attempts to explain the role of these determined parameters and those

which require determination in the mechanical peeling processing.

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1.4 Thesis organization

The thesis consists of three main parts: investigation of mechanical properties of

tough-skinned vegetables, development of peeling methods and mathematical

modeling of the results. The content is organized in nine chapters as follows:

Chapter 1 is the introductory chapter that explains the motivation of the research,

and outlines the main objectives and major contributions of the thesis.

Chapter 2 reviews critically the existing peeling methods and background of the

research. This chapter also reviews work done on properties (especially mechanical)

of fruits and vegetables and the developed models in the area of fruit and vegetable

peeling.

Chapter 3 focuses on the mechanical properties of tough-skinned vegetables

including pumpkin and melon (three varieties each). It explains developed and

fabricated instrumentations, measuring methods, results and statistical comparisons

of the results. The mechanical properties, including rupture force, toughness, cutting

force, shear strength force, shear strength, and static coefficient of friction are

investigated in different specimen states.

Chapter 4 describes the test rig. Design and fabrication procedure are described,

specifications and advantages of the test rig that was used to investigate different

peeling methods and devices are also discussed.

Chapter 5 outlines all the attempts undertaken to explore suitable peeling methods

and devices. Although the devices might look simple, they were preliminary

prototypes that were made with regard to the specifications of the products and the

main defined objectives of the research.

Chapter 6 presents the experiments carried out for investigation of four different

peeling methods and devices for the Jap variety of pumpkin. The four different

investigated methods were abrasive pads, abrasive foams, milling cutter, and

8

abrasive-cutter brush. Results and analysis of the results are comprehensively

explained in this chapter.

Chapter 7 reports the results and analysis of full factorial experiments conducted on

two varieties of pumpkin (Jap and Jarrahdale) by abrasive-cutter brush as the best

selected method. The influencing parameters that are related to the product and

abrasive-cutter brush have been comprehensively studied.

Chapter 8 describes mathematical modelling of mechanical peeling. The procedure

of mechanical peeling method using abrasive-cutter brush is simulated and the

influence of different parameters related to the product and peeler are modeled. The

value of the coefficients of the model is determined for Jap and Jarrahdale varieties

of pumpkin. The validation of the model is carried out using experimental data and

the results are discussed using the results of the study of mechanical properties of

tough-skinned vegetables.

Chapter 9 summarizes and concludes the thesis. It also proposes directions for

future studies related to this area.

1.5 Publications (refereed) of the author arising from the

PhD research

1) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Mechanical properties of

pumpkin, International Journal of Food Properties, 8 (2), 277-287.

2) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Design and manufacturing of test

rig for investigation of improved mechanical peeling methods of fruits and

vegetables, International conference on manufacturing and management: GCMM-

2004, pp.574-579, Vellore, India, Dec. 2004.

3) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Mechanical properties of three

varieties of melon, Journal of Texture Studies, Submitted, 20/11/2005.

9

4) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Experimental investigation of

abrasive peeling of pumpkin, 4th International congress on food technology, pp.118-

117, Athens, Greece,Feb.2005.

5) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Relationship between mechanical

properties of pumpkin and skin thickness, 4th International congress on food

technology, pp.111-123, Athens, Greece, Feb. 2005.

6) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Abrasive peeling of pumpkin,

part 1: using abrasive pads. Journal of Food Engineering, Submitted, 23/02/2005.

7) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Abrasive peeling of pumpkin,

part 2: using abrasive foams. Journal of Food Engineering, Submitted, 22/02/2005.

8) Emadi, B., Kosse, V., Yarlagadda, P. K. D. V., Using abrasive disk as innovative

peeling method for vegetables with uneven surfaces, BEE Postgraduate Research

Conference, Brisbane, Australia, Dec. 2005.

10

Chapter 2

Literature review

Peeling of fruits and vegetables in theory and practice has been studied by many

researchers. These studies are very broad and cover various methods of peeling and

products to be peeled. Some products (such as potato) and methods of peeling (such

as chemical methods) are particular matters of interest and have attracted more

attention. The study of those products and methods has been extended to investigate

the physico-chemical behaviour of the product during the peeling process. There is

very little literature pertaining to the peeling of tough-skinned vegetables while

there has been little effort to quantify the tissue properties or any process modelling

of products such as pumpkin and melon.

From a mechanical peeling standpoint, there is evidence that more research is

needed to develop modelling approaches for many peeling operations, for example

the peeling of tough-skinned vegetables such as pumpkin.

This chapter sets out to identify and critically analyse all the previously published

literature with regard to the mechanical properties of fruits and vegetables, peeling

methods, and modelling of the peeling process.

11

2.1 Mechanical properties of fruits and vegetables

and methods of testing

2.1.1 Introduction

The study of the physical and mechanical properties of fruits and vegetables is very

important. It can improve the efficiency of processing equipment, especially peelers.

The agricultural products are subjected to either wanted or unwanted mechanical

loads after harvesting. During the process of mechanical peeling, the products are

loaded purposefully with wanted mechanical loads that are always accompanied by

unwanted loads. The unwanted mechanical loading (compression, impact, and

vibration) is the main reason for bruising of fruits and vegetables during post

harvesting operations (Brusewitz et al., 1991). Reducing the harmful effects of

unwanted loads and improving the effectiveness of wanted loads can be achieved by

knowledge of the mechanical properties (i.e. toughness, cutting force and shear

strength) of the products. Mechanical properties of products can also be used in

design of their mechanical peeler. Researchers have used various techniques to

investigate the mechanical properties of different produce. The following sections

address these issues.

2.1.2 States of product to be tested

The properties of products can be studied for different states including skin, flesh

and unpeeled (overall) state. Among different states of product to be tested,

determination of the mechanical properties of skin always poses a challenge. It can

be done by carrying out experiments on skin directly or indirectly. Several

researchers such as Grotte et al. (2001), Jackman and Stanley (1994), and Voisey et

al. (1970) have used the difference between unpeeled (overall) product and that of

product measured without skin (flesh) to indirectly obtain the result of the force-

deformation test of the skin. This experimental procedure has not been accepted by

others due to the likelihood of some errors in the result. For example, Thompson et

al. (1992) stated that to identify the contribution of the skin to the external puncture

force (in the case of cucumbers) by making measurements before and after skin

12

removal is accompanied by error. In addition, Jackman and Stanley (1992)

concluded that the difference of puncture load displacement between unpeeled

(overall) and without skin (flesh) product cannot provide the load displacement of

the skin itself. Jackman and Stanley’s point was proved by an increase in effective

area of compression during puncture of the skin.

2.1.3 Compression test

The compression (force-deformation) test is the basic and one of the most important

tests in the study of the mechanical properties of fruits and vegetables. The force-

deformation test shows the behaviour of the product under different levels of

compression forces. Some mechanical properties of different states of products

including skin, flesh, and unpeeled states can be determined by using this test

(Mohsenin, 1970). The test can be used for determination of an extended range of

mechanical properties such as modulus of elasticity, rupture force, rupture stress,

toughness, and firmness (Jackman and Stanley, 1994; Voisey and Lyall, 1965a;

Voisey and Lyall, 1965b; Grotte et al., 2001; Holt 1970; Voisey et al., 1970;

Behnasawy et al., 2004; Rybczynski and Dobrzanski, 1994). The same purposes can

be achieved by using the tensile test (Jackman and Stanley, 1994) but, in

comparison with the compression test, implementation of the tensile test is difficult

because of some limitations, such as difficulty in holding the skin specimens during

the test (Su and Humphries, 1972) and creation of premature tensile failure during

specimen preparation (Clevenger and Hamann, 1968; Thompson et al., 1992).

Two important properties resulting from the force-deformation test are rupture point

and toughness (Figure 2.1). Rupture point is a point on the force-deformation curve

at which the axially loaded specimen ruptures under a load (Mohsenin, 1970). The

work required to cause rupture in the product is known as the toughness (Mohsenin,

1970). Finney (1969) also defined the toughness as the area under the force-

deformation curve, recorded through the point of tissue rupture or failure (Figure

2.1). He explained the intercellular adhesion or cementing substances and cell wall

strength are factors quite likely to influence toughness of fruits and vegetables.

13

2.1.4 Cutting test

The cutting test is not as common as the compression test and is used to determine

the resistance of tissue to loading cutting force. Ohwovoriole et al. (1988) applied

this test to identify the necessary cutting force of unpeeled and peeled cassava tuber.

They used the resulting data to design a cassava peeler. A cutting edge in the form

of a sharpened 1.5 mm thick piece of sheet metal was placed between the plungers

of the Universal Testing Machine for that purpose.

Fig.2.1. Force-deformation curve (Finney, 1969)

2.1.5 Shear strength test

Shearing strength of the product is determined by shearing a plug from a slice of the

product. The shearing strength of the product indicates the degree to which the cells

are held together. Knowing shearing force (F), the diameter of the solid cylindrical

die with flat end (d), and the thickness of the slice (t); shearing strength (S) can be

determined (Mohsenin, 1961):

tdFS××

=π

(2.1)

Ohwovoriole et al. (1988) reported using the shear strength test to measure shear

stress of peeled and unpeeled cassava tuber. An 8.7 mm diameter rod was used on

14

an Instron machine to reveal the necessary data for cutting cassava tubers through

the peel. Their report does not mention the shape of the applied indentor.

2.1.6 Coefficient friction test

The coefficient friction test is applied to identify the coefficient of friction for

different states of product on various surface materials. The effective parameters on

these properties are the moisture content of the specimen and the kind of surface

material. Chung and Verma (1989) concluded that the surface material is more

effective on the dynamic than on the static coefficients of friction while Carman

(1996) reported a higher influence of moisture compared with surface material on

the static coefficient of friction. Chung and Verma (1989) concluded the ratio of

static and dynamic coefficient of friction remained almost invariant irrespective of

the moisture content of the sample and the type of surface material.

The coefficient of friction, either static or dynamic, has been measured using

different methods. Those coefficients can be measured by analog or digital systems.

Data obtained by a digital system are more accurate than those taken by an earlier

analog system (Chung and Verma, 1989).

In the analog system, specimens are placed on a table which is manually and slowly

tilted until movement of the specimen and the static coefficient of friction would be

the tangent of the slope angle of the table measured with a protractor. This method

has been used by some researchers (Oje and Ugbor, 1991; Bahnasawy et al., 2004;

Helmy, 1995; Saif and Bahnasaway, 2002; Ohwovoriole, 1988). The main benefit

of using analog systems is simplicity of the method.

The digital measuring system works based on a friction device (disk) modified by

Tsang-Mui-Chung et al. (1984) and improved by Chung and Verma (1989). The

latter authors used a personal computer for data acquisition. They applied the

following equations to calculate the static and dynamic coefficient of frictions:

qWT fas ./=μ (2-2)

qWT fmd ./=μ (2-3)

15

where, μs is static coefficient of friction, Ta is beginning value of torque, μd is the

dynamic coefficient of friction, Tm is the average value of the torque, q is the length

of torque arm, and Wf is the weight of fruits to calculate the dynamic and static

coefficients of friction. The average value of the torque during the rotation of the

disk and the maximum value of torque obtained as the disc started to rotate were

used.

This method has been used by other researchers such as Marakogˇlu et al. (2005),

Çalı ır et al. (2005) and Gupta and Das (1998). They applied this method to

measure the friction coefficients of fresh blackthorn fruits, wild plum fruits, and

sunflower seed and kernel respectively.

2.2 Peeling methods of fruits and vegetables

2.2.1 Introduction

For some kinds of fruits and vegetables, such as mango, manual peeling is

commonly in use. The requirement to develop new methods and tools for peeling

that can be mechanised and automated has led to the versatile current peeling

methods, machinery and equipments. Peeling methods fall into three main groups:

mechanical, thermal and chemical peeling. Much research has been published

related to different methods of peeling and the range of publication is considerably

extensive regarding the variety of products and peeling methods. A literature review,

arranged on the basis of the technique used, along with examples of the latest works

of interest is given here.

2.2.2 Mechanical peeling

There is a variety of mechanical peelers designed to suit the peeling of either a

particular product or a group of products. In general, mechanical peelers are

classified on the basis of the type of mechanism that is incorporated into the peeling

system. Commercial mechanical peelers include abrasive devices, devices with

16

drums, rollers, knifes or blades, and milling cutters. Generally, the quantity of

losses in this kind of peeling is high, but the quality of the final peeled vegetables in

terms of features such as freshness is good. Those devices are briefly described

using related works of interest as follows:

2.2.2.1 Abrasive devices

The abrasive method can be implemented in a very simple way by using gloves

with an abrasive outside layer. Vegetables are rubbed by these gloves to remove the

skin. That is a common method for the peeling of potatoes in small amounts.

Somsen et al. (2004) have proved that manually peeling of potatoes using sandpaper

results in the lowest possible peel losses. They proved that these losses were

normally expected losses (wanted losses). Although some researchers realised that

the abrasive method has a lower quality compared to hand peeling (Barry-Ryan,

2000), it is still used commonly for root vegetables. These researchers criticized this

method as it bruises the underlying tissue to varying degrees and leaves the new

outer layer of cells damaged which leads to leakage of cellular fluids and

encourages microbial growth.

Jasper et al. (2001) patented a peeler equipped with a rough exterior surface. The

peeler abrades the outside surface of fruits and vegetables when it comes into

contact with the outside surface of the product. The surface roughness of the peeler

can be adjusted depending on the skin of the vegetable to be peeled. One of the

clear disadvantages of this device is that it can only be used in a domestic kitchen

environment.

Agrawal et al. (1982) discuss the development of an abrasive brush type ginger

peeling machine. Two continuous and abrasive vertical brush belts are the main

parts of the machine. Ginger, as a product with an irregular shape, passes between

these two belts while it moves in the opposite direction with a downward relative

velocity. The opposite direction of movement of the two belts causes an abrasive

action while the downward relative velocities provide the downward movement of

the product. Agrawal et al. have reported a peeling efficiency of about 75-85%.

17

2.2.2.2 Devices using drums

Singh (1995) describes a power-operated batch type potato peeler that includes a

peeling drum (670 mm in length and 450 mm in diameter) and a water-spraying unit.

The peeling drum with protrusions (2.5-3.0 mm) on the inside surface rotates and

removes skin from potatoes by means of abrasion. The space between two centres

of protrusions in rows and columns were 14 and 7 mm, respectively. A speed of 30

rev/min batch, load of 20 kg and time of 8 min were found to be the best

combination providing higher peeling efficiency and lower peel losses. As a result

of this combination, the peeling efficiency and peel losses were 78% and 6%,

respectively. A large amount of wastewater is a shortcoming of this method.

2.2.2.3 Devices using rollers

Suter (2002) developed a peeling machine for efficient and effective control of the

peeling operation. It applies a set of abrasive rollers (Figure 2.2). The rollers come

together in a longitudinal direction and the distance between them is adjustable. The

feeder feeds the rollers controllably on the basis of the sensed load inside the rollers

by a related sensor. Also, Zittel (1991) used a plurality of rotating abrasive rollers.

The machine had a frame with a pair of end plates that rotatively carried the

longitudinal rollers. Each roller is powered by an individual motor, which is

coupled to that roller. However, those inventors neither achieved higher efficiency

nor could reduce peeling losses because their patents focused mainly on control and

drive mechanisms.

2.2.2.4 Knives or blades

Tardif and He (1999) released a machine equipped with blades to peel vegetables.

The vegetable, which is located in the hollow base of the machine, can be rotated by

a threaded rod on the top. The rod is rotated manually by a handle. A blade, which

is coupled to the supporting rod and urged by a spring, moves towards the vegetable

to be peeled. While the vegetable is rotated, the blade removes the peel.

18

Harding (2001) described an apparatus for peeling a convex surface of a section of a

fruit or vegetable. The machine is attached to a U-shaped peeling blade and a feeder.

The feeder grips the fruit or vegetable at a position about opposite the apex of the

peeling blade. Fruits or vegetables have to pass in front of a peeling blade being

guided by at least one guide. He also patented a melon peeler in 2000. The semi-

manual peeler includes a curved peeling blade which presents a curved surface to

the convex surface of the section of produce. It facilitates peeling of curved sections

of products but can not follow the unevennesses of surface.

Fig.2.2. An industrial application of an abrasive roller peeler for tuberal

products such as potato

(Dornow Food Technology GmbH, 2004)

Gingras (2001) presented equipment for the peeling of vegetables of a round, oval

or elongated shape such as cucumbers. The machine is equipped with a frame

including an adjustable hole to receive and let pass the vegetable to be peeled. The

frame also carries several knives that can be slid toward the corner of a hole.

Ridler (2000) described a peeling apparatus including a traversed blade, which

continuously and intermittently rotates in the opposite direction to a rotating

vegetable. The apparatus is controlled and powered manually. The user rotates the

19

vegetable that is mounted on a slender arbour by one hand and controls the peeling

blade by another hand at the same time.

Martin (2000) reported a peeling machine equipped with a lower and upper holding

assembly connected to a frame securing and rotating the vegetable to be peeled. A

carriage assembly including a cutting assembly is engaged with the end of a second

air cylinder. The extension of the second air cylinder pushes the cutting assembly

against the vegetable as the carriage assembly moves upwards; as a result peeling is

done.

Protte (1999) described a peeling machine for stalk-like vegetables, including a

plurality of knife stations that are successively arranged along the vegetables

moving inside the machine. There are pluralities of pairs of feed rollers, and every

pair is supported between successive knife stations.

Sommer (1997) discussed a device for the peeling of elongated vegetables

especially asparagus. The device comprises housing equipped with a passage

designed to permit a stick of asparagus to be inserted. There are several peeling

blades inside the housing, which are orientated in various directions of the passage

and act on the stick of asparagus. One blade as a minimum can move crosswise to

the elongated direction of the passage and presses flexibly towards the stick of

asparagus.

Rauschning (2001) expounded a device for the peeling of root vegetables. The

device includes a container equipped with at least two rotating discs at its bottom.

These discs have a grating or cutting surface on their upper side.

Odigboh (1976) revealed the development, design and construction of a continuous

process mechanical cassava peeler. The machine includes two cylinders which are

located parallel with 20 mm space and inclined at 15° to the horizontal plane. The

surface of the driver cylinder is covered by knives and rotates clockwise at 200

rev/min. The driven cylinder which has a roughened surface, also rotates clockwise

at 88 rev/min. The cassava pieces with 100 mm length are fed lengthwise to the

spaces between cylinders. Products are being peeled off while they rotate anti-

20

clockwise and move down. Low efficiency of peeling especially for small sizes of

roots (40 mm and less) and inability to be set up for roots of specific sizes are

reported as disadvantages. Although the continuous option of the apparatus is

considered to be one advantage, the necessity to cut roots to pieces of about 100

mm length is a limitation.

Srivastava et al. (1997) reported the design and development of an onion-peeling

machine which uses four scoring blades assisted by compressed air jets to slit the

outer layers of the onion skin. The skin will be loosened and dislodged from the

bulb by the compressed air under the peel. The compressed air penetrates under the

skin through the created slits by scoring blades. A pair of high-speed saw blades is

used to cut the ends of the onion. Srivastava et al. (1997) reported peeling losses as

17%.

2.2.2.5 Milling cutter

Cailliot and Serge (1988) claimed that peeling using the milling cutter is one of the

known methods for spherical shape products (Figure 2.3). In this method, one or

more fixed or rotary peeling tools (i.e. knife) with at least one cutting edge take the

peel off the product in a similar way to manual peeling. In the first stage of this

method, a fixed knife or blade was used to peel a rotary spherical product. As the

knife had no flexibility, it could not follow the irregular shape of the product

exactly and in particular it could not penetrate to the inside of thin grooves. The

history of using a milling cutter goes back to Boyce et al. (1961) who used a milling

cutter in the form of a very flat milling cutter, having a large number of cutting

teeth distributed over a considerably large diameter, in order to produce small chips

of peel, the discharge of which is left to chance. The big diameter of the cutter and

the shape of the teeth (like spoons) were two reasons that did not allow the cutter to

properly follow the shape of the product.

To remedy the production of a continuous peel and resulting clogging, Gardiner et

al. (1963) tested a milling cutter with a cylindrical cutting edge, combined with a

disc which supports the cylindrical cutting edge and which was provided with

apertures sharpened in the plane of the disc, so as to cut the ribbon of peel

21

transversely into smaller portions making it easier to discharge it. Although the

problem of clogging was solved, the peeling production was not sufficient. Similar

limitations were experienced by Polk (1972) who used a large rotary milled edge

and rotary vegetable holder.

Couture and Allard (1979) invented a cutting head comprising a blade strip bent

longitudinally into a generally cylindrical shape. The peeler head was pivotally

connected to the body to follow the irregular shape of the product. The machine

included means for moving the cutting head along the supported vegetable in

contact therewith as the vegetable is rotated with the cutting edge and a continuous

strip of peel is cut around the vegetable.

Fig.2.3. General feature of milling cutter in use

(Boyce, San Jose and Calif, 1961)

As the cutting head had no rotation itself and had to follow the shape of the rotating

vegetable, the chance of it getting stuck especially for sharp irregular shapes was

high. Cailliot and Serge (1988) noted the disadvantages of this appliance such as

22

producing a continuos peel and clogging the peeling tool in an automatic appliance.

Cailliot and Serge (1988) claimed one vertical cutter type in their patent. The

diameter of the rotary cutter is small and equipped with two teeth to give balance.

20000 rpm for the rotary cutter gives a speed that is equal to tangential speed of at

least 20 m/s and needs low torque. The depth of penetration is limited by the choice

of a small diameter cutter for example 20 mm. The extra length of each tooth from

outside the diameter of the cutter defines the depth of penetration in this plan.

Cailliot et al. claimed to solve the common problem (clogging) but it seems the low

number of teeth and the shape of the teeth that come out from the surface of the

plate cause clogging for irregular shapes of product such as pumpkin with irregular,

thin and deep grooves. Tardif and He (1999) in another trial used a similar method

to Couture and Allard (1979) with a simple knife (non-rotating). It was found that

low flexibility will definitely lead to clogging as well. All attempts which have been

carried out so far were unsuccessful in solving the clogging problem especially for

products with an uneven surface. It is believed that the high number of teeth in

special shapes without any convex section may reduce the chance of clogging to

zero.

2.2.3 Thermal peeling

Thermal peeling as well as chemical peeling is used for thick-skinned vegetables.

This method can be performed by wet heat (steam) or dry heat (flame, infra red, hot

gases). Floros and Chinnan (1988a) reported that the widespread application of

steam peeling is due to its high level of automation, precise control of time,

temperature and pressure by electronic devices to minimize peeling losses, and due

to the reduced environmental pollution as compared to chemical peeling. This

method of peeling - especially dry heat - causes a cauterizing of the surface, wound

areas, and small pieces of charred skin, which if not removed, give a poor

appearance to vegetables, especially canned ones (Weaver et al., 1980). Different

types of thermal peeling are described below with reference to related works of

interest.

23

2.2.3.1 Flame (dry heat) peeling

Some vegetables such as pepper can be peeled by dry heat (flame). In this method,

vegetables are exposed to direct flame (for about 1 min at 1000ºC) or hot gases in

rotary tube flame peelers. Heat causes steam to develop under skins and this puffs

the skins up so that they can be washed away with water. Each heat treatment

should be immediately followed by cooling in water.

Weaver et al. (1980) report a flame application for the peeling of tomatoes. Dual

Maxon gas-fired burners are mounted at the top of a live-roller conveyor at the

height of 6 in. The affecting time of the flame is controlled by adjusting the speed

of the conveyor. Tomatoes are affected by the flame or infrared irradiation alone or

this is accompanied with boiling water or steam at an atmospheric pressure at 100ºC.

Each heat treatment was immediately followed with a cooling stage by exposure of

the product to water. A rapid splitting of the skin with very little charring is

achieved in thirty seconds of infrared radiation, but it cannot improve the peeling of

green-shoulder tissue on many cultivars. Weaver et al. state that flame peeling can

efficiently remove skin over green shoulders and immature green or yellow areas of

the fruit.

Davies (1996) discusses a vegetable peeling apparatus that has a heating station.

The heating at this station can be carried out by infrared radiation and that is

sufficient to at least partially lift the skin from the flesh.

2.2.3.2 Steam (wet heat) peeling

To eliminate charring, but to keep the effects of the high-temperature of the infrared

or flame, superheated steam is used. The steam pressure that is used in wet heat is

about 10 atm and it leads to the softening of skins and underlying tissues. When the

pressure is suddenly released, steam under the skin expands and causes the skin to

puff and crack. Then the skin is washed away with jets of water at high pressure (up

to 12 atm).

24

Kunz (1978) patented a method and device for peeling pumpkin by using wet steam.

While the pumpkins are shifting on endless conveyors, they are cut into halves and

are placed with the pulp facing downwards. Then they are exposed to pressurised

wet steam for a short time followed by a water cleaning step. Kunz’s device uses

water sprays from the top to remove the skin and water sprays from the bottom to

remove pips and pip pulp. Weaver et al. (1980) applied the superheated steam

method for peeling of tomatoes as well. Fruits were affected directly by the flow of

steam in an open-mesh basket. Tomatoes were exposed two or three times to

superheated steam at three different levels of steam pressure and temperature. Each

heat treatment was instantaneously followed by cooling with water at about 22ºC.

Most efficient peel removal was achieved by using steam at temperatures and flow

rates of 425 to 480ºC and 12-15 lb steam per ft2 min respectively.

Smith (1984) developed a method of superheated steam peeling of apples by

refining conventional caustic and steam peeling methods. He used a batch-type

laboratory pilot-model steam peeler of ¼ bu (8.8 litres) capacity. His pilot-model

accepted either saturated steam at 100 psig (7 kg/cm2) or superheated steam at 100

psig (7kg/cm2) at mean inlet temperatures of 371ºC. He found that steam peeling

with saturated steam followed by flash cooling by injection of water increased

yields, saved labour, eliminated the need for expensive caustic solutions and

caustic-solution disposal, and finally, resulted in high quality apples for further

processing. Peeled yields in excess of 95% were attained in peeling treatment using

superheated steam with or without water injection. Furthermore, as the thermal

conductivity of superheated steam is considerably lower than that of saturated steam

at the same pressure, the amount of heat penetration into the flesh of fruits should

be controlled more easily.

Floros and Chinnan (1988a) explained that ‘in single stage steam peeling, the

mesocarp cells would separate from the rest of the fruit. A large portion of edible

fruit will be washed away during the pressurised cold water treatment, which

follows the steam treatment. Many attempts have been made to date to improve the

efficiency of steam peeling for several commodities’ and therefore, they developed

a multi-stage process for steam peeling of pimiento peppers. Each process included

several repeated cycles at a constant temperature of 215º C and steam pressure of

25

480 KPa. Each cycle was 10 seconds long (except the last which was 5 seconds).

Steam was supplied and pressure built_up for the first 5 seconds. For the next 5

seconds, the steam was disconnected and the door of the chamber was opened, the

temperature was considerably reduced and allowed the pressure to drop

immediately to atmospheric. They observed the effect of various treatments on the

fruit surface by scanning electron microscopy. They also observed considerable

reduction of losses compared to single stage peeling. The reason was the short

consecutive heat treatments that supply sufficient heat to break down the outer

layers of the mesocarp cells with minimum effect on the next layers.

2.2.3.3 Thermal blast peeling

In a patented process developed by Harris and Smith (1986), vegetables and fruits

are placed in a closed and elevated pressure vessel. The products are affected by

infrared heat from the vessel wall and conductive heat from the superheated steam

atmosphere. The heat treatment leads to an increased plasticity of the skin tissues

caused by drying. The plasticized tissues will increase the resistance of peel to

rupture so steam can spread laterally to build the peeling area under the skin. This

stage is too short for heat to penetrate to the edible portion. After heat treatment,

pressure is reduced to atmospheric pressure by instantly opening the vessel. An

explosion leads to blowing up the product from the vessel and blasting the peel up

simultaneously as a result of the instantly and highly energized moisture under skin.

They applied this peeling method to many fruits and vegetables and observed better

results than lye and saturated steam peeling. For example, they tested this method

for Alagold pumpkin under 343.33°C within 45 minutes and got 89.4 percent yield

by weight. They could reduce peeling losses for this variety of pumpkin from 28%

to about 11% for saturated steam and thermal blast peeling respectively.

2.2.3.4 Freeze-thaw

Brown et al. (1970), Thomas et al. (1976), Goud (1983), and Woodroof and Luh

(1988) attempted to eliminate the use of caustic solutions in the peeling of tomatoes

by the use of the freeze-thaw method. In this method tomatoes are immersed in

liquid nitrogen for 5-15 seconds, and then thawed in warm water at 66ºC for 30

26

seconds to loosen the peel. The loss was about 5-7% but this method was not

effective on immature yellow and green shoulder tissues. It was mentioned that the

method is applicable for peaches as well.

2.2.3.5 Vapour explosion (vacuum peeling)

Drooge et al. (1999) tested the vapour explosion method for removing the skins of

fruits and vegetables by explosive vaporization of the moisture under the skin of

fruits and vegetables. They placed the vegetable in a peeling vessel, and the

pressure in the vessel was rapidly reduced (below atmospheric pressure), leading to

explosive vaporization of the moisture. Drooge et al. suggested that it is possible to

reduce the air pressure and to cool the vegetable before the vapour explosion.

Kliamow et al. (1977) called this method vacuum peeling. They applied vacuum at

600-700 mm Hg to tear the peel off tomatoes. They reported high peeling efficiency,

retention of high fruit quality and low energy consumption as well as cost for this

method.

2.2.4 Chemical peeling

To reduce the losses during mechanical and thermal peeling methods, chemical

peeling has been considered. In this method, skins can be softened from the

underlying tissues by submerging vegetables in hot alkali solution. The quantity of

solution and the period of time are different for different kinds and varieties of

vegetables. Generally, lye may be used at a concentration of about 0.5-3%, at about

93ºC (2000 F), for a short period of time (0.5-3 min). The loosened skins are

washed away by high velocity jets of water or compressed air. This method of

peeling reduces the losses but it has harmful effects on the flesh of vegetables and

also is not environmentally friendly. Different kinds of chemical peeling are briefly

described with reference to related works of interest in the following section.

2.2.4.1 Caustic (lye) peeling

27

Floros et al. (1987) evaluated the effect of lye concentration (4 to 12% NaOH),

process temperature (80 to 100ºC) and time (1.5 to 6.5 min) on the yield, peeling

loss and unpeeled skin, in a lye peeling process of pimiento peppers. They

optimized the process to achieve maximum removal of the skin and minimum loss

of edible fruit. They revealed that the high lye concentration (12% NaOH)

accompanied with short processing time (1.6 to 2 min) at a moderate temperature of

around 90ºC should yield an optimum process with removal of all of the skin and

peeling losses as low as 20%.

Floros and Chinnan (1988b) found that the double-stage process was more effective

than the conventional single-stage operation. They tested a double-stage lye

(NaOH) peeling process involving pre-treatment (concentration, c1; temperature, T1;

time, t1), holding time (th), and post-treatment (c2, T2, t2). The effect of seven factors

on four responses (unpeeled skin, peeling loss, product yield, and texture) was

studied. Processing times and lye concentrations were the most important factors,

while processing temperatures and holding times had no significant effect on the

peeling operation. A mild pre-treatment with 3.2% NaOH for 130 seconds

combined with a relatively strong post-treatment of 8% NaOH for 60 seconds at

84ºC and the holding time of 45 seconds were found to result in an optimum

process.

Garrote et al. (1993) surveyed the effect of NaOH concentration (4-20%), process

temperature (55-95ºC) and time (1-7 min) on the yield, peeling quality, unpeeled

skin and total usage of NaOH. They also evaluated titratable NaOH in the potato

tissue, NaOH penetration and “heat ring” depth. The best peeling quality, maximum

yield and minimum total usage of NaOH resulted with the following conditions:

concentration, 11-13%; time, 5-5.70 minutes and temperature, 90-95ºC. The

maximum temperature for which the “heat ring” and NaOH penetration depth were

equal was 72ºC where, at 20% NaOH and 7 minutes, peeling quality was very good

and the “heat ring” was eliminated.

Walter et al. (1982) investigated the effects of heat penetration on sweet potato

tissue under three lye-peeling treatments. Heat-mediated, starch gelatinization, cell

wall separation, chromoplast disruption, and enzymatic discoloration were

evaluated in different conditions according to the peeling treatment. Starch

28

gelatinization, cell wall separation, and chromoplast disruption reduced in the order:

15 minute peel; 30 minute pre-soak (water 78-83ºC); followed by a 6 minute peel.

Discoloration occurred in significant amounts only in the 6 minute peel because

heat penetration was sufficient to disrupt lacticifer organization but insufficient to

inactivate the polyphenol oxidising (PPO) enzyme. The 30 minute pre-soak and 6

minute peel treatment resulted in the best product.

Floros et al. (1987) observed microstructural changes of pimiento peppers, which

were treated with varying degrees of NaOH (lye) solutions (1, 4, and 9%),

maintained at 80ºC, for different times (1, 2, and 3 minutes). They found that NaOH

removes the epicuticular and cuticular waxes, diffuses uniformly into the fruit

where it breaks down epidermal and hypodermal cell walls, and solubilizes the

middle lamella causing separation of the skin. In severe treatments the lye also

dissolves the parenchyma cells of the mesocarp resulting in considerable loss during

processing.

Walter et al. (1982) used the different treatments of peeling sweet potatoes in a

boiling, NaOH solution. The different treatments were: 6 minute peel (6p), 20

minute pre-soak in water (55ºC) followed by a 6 minute peel (20S), 30 minute pre-

soak in water (80ºC), followed by a 6 minute peel (30S), 15 minute peel (15p). The

area of tissue which was affected by heat was excited and analysed for o-

dihydroxyphenols (DP) and carotene destruction and sugar formation. The data

showed that roots peeled by 6P or 20S treatments could discolour as a result of the

PPO-DP reaction. 15P and 30S did not show discoloration because both treatments

are vigorous enough to inactivate the PPO system. All treatments except 6P caused

the inactivation of amylolytic enzymes. Carotenoid destruction was not detected.

2.2.4.2 Enzymic peeling

The adherence of peel to the fruits is done by pectin, cellulose and hemicellulose as

the polysaccharides (Toker and Bayindirli, 2003). Therefore, using corresponding

glycohydrolases to treat the product will lead to enzymic peeling. Janser (1996) has

claimed better texture and appearance for product after enzymatic peeling because

of fewer amounts of broken segments and juice losses. Researchers (Ben-Shalom et

29

al., 1986; Rouhana and Mannheim, 1994; Soffer and Mannheim, 1996; Pretel et al.,

1997) have proved suitability of this method for peeling citrus fruits. Prakash et al.

(2001) studied enzymic peeling of ‘Indian tough nature grapefruit’ by vacuum

infusion (Figure 2.4). They used two commercial peeling enzymes coded as “Brand

A” and “Brand B”. “Brand A” produced by Aspergillus Niger, involves a mixture

of pectinases and cellulase, while “Brand B” produced by Niger and Trichoderma

Reesi, contains pectinases, cellulase and hemi cellulase. Their conclusion was that:

a scalding time of 2 min in a boiling water bath, scoring the peel with four

radial lines, immersion in an mentioned enzyme bath containing enzymes

at 1ml⋅l-1, vacuum infusion at 760 mmHg for 1 min and incubating the

fruit in the enzyme bath for 12 min at ambient temperature (30±2ºC),

followed by hand-peeling under running tap water, were found to be

necessary for easy peeling of Indian tough nature grapefruit.

In continuing the research for peeling of citrus fruits, some trials have been carried

out to assess the feasibility of this method for stone fruits such as apricot, nectarines,

and peaches (Toker and Bayindirli, 2003; Janser, 1996).

Fig.2.4. Enzymic peeled (right side) and manual (left side) peeled

grapefruit

(Prakash et al., 2001)

30

2.3 The current situation of peeling tough-skinned

vegetables

The current situation of tough-skinned vegetable peeling was assessed by this

researcher during an industrial visit to Comet Food Pty. Ltd., Brisbane. This

company carries out fruits and vegetables processing involving peeling. During this

visit technologies that are used in peeling of different vegetables were observed. In

particular, pumpkin is chopped into segments by pivoted hand operated knife, and

then, each segment is rubbed against rotating grater drum. Because of the

unevenness of surface of some pumpkin varieties such as Jap and Jarrahdale (Figure

1.1), this method of peeling has high peeling losses. This limitation is common for

the peeling of tough-skinned vegetables. For example, one of the famous companies

which is active in design and manufacturing of food processing machinery is

Dornow Food Technology GmbH, Germany. Dornow has introduced automated

peelers as the latest peeler for the Hokkaido pumpkin variety which has an even

surface. Whole pumpkins are passed continuously through the machine. The floor

of the machine is equipped with many rotating disks. These disks could be

carborundum or blade. The main limitation of those peelers is also that they have no

flexibility to follow the uneven surface of some varieties of pumpkin such as

Jarrahdale and Jap (Figure 1.1). This limitation causes high peeling losses. The

value of peeling losses for pumpkin is not stated by the company but using similar

machines for peeling potatoes can produce peeling losses from 2.4% to 24%

(Dornow Food Technology GmbH, Year). The rate of peeling losses depends on the

degree of desired peeling. In this case, complete peeling to remove all eyes from

potatoes leads to 24% peeling losses.

2.4 Mathematical modelling of peeling processes

The mathematical modelling of peeling processes has been largely limited to the

chemical peeling process and, only rarely, to the thermal peeling process. Chemical

peeling is a complex phenomenon which involves mass diffusion and chemical

reactions. The general approach to the problem is the assumption that the rate of

peeling is a function of the lye concentration, temperature and treatment time, as

31

well as other variables intrinsic to the product such as form and geometry, ripeness,

peel thickness, and type or variety (Barreiro et al. 1995). The relationship among

the above parameters must be identified for each product to attain the maximum

efficiency and minimum losses during the peeling process.

There are numerous research efforts that have established relationship amongst lye

concentration, temperature and time, and practical results are available for the

chemical peeling of various fruits and vegetables, including products such as

peaches (Olsen, 1941; Lankler and Morgan, 1944), pimiento peppers (Floros and

Chinnan, 1987,1988b), and so on. Most of the previous by mentioned

investigations have been conducted empirically to determine the peeling conditions.

For example, Athanasopoulos and Vagias (1987) adjusted the results for peeling

mandarin segments to a zero and first order reaction for peeling temperature and lye

concentration respectively. Also Floros and Chinnan (1987, 1988b) used a response

surface methodology to optimize the peeling process of pimiento peppers based on

empirical peeling data in one and two stage processes.

Barreiro et al. (1995) developed a mathematical model for the chemical peeling

process of foods with spherical shapes. They used the concept of the unreacted core

model for this purpose. They established some equations for the prediction of

peeling times, weight losses and texture changes during the peeling of guava as a

function of the variables involved in the peeling process. Chavez et al. (1996)

applied a mathematical model to describe the chemical peeling process. They

intended to identify the minimum processing losses of vegetables, energy and

NaOH solution consumption. They used the shrinking core model and the second

Fick`s law to formulate the mathematical model on the basis of mechanisms

included in the peeling process of potatoes. They compared their results to

experimental data and observed good agreement.

Few publications could be found on mathematical modelling of thermal peeling

methods. Somsen et al. (2004) developed two models on the basis of experimental

data of steam peeling for three varieties of potato. They successfully predicted the

heat ring and peel losses as the function of some independent variables such as size,

variety, conditioning temperature, steam pressure, and steam exposure time.

32

No publication on mathematical modelling of mechanical peeling methods or

processes has been found by the date of writing the thesis.

2.5 Conclusions and discussion

The foregoing sections have elaborated on the current state-of-the-art technology in

peeling processes, highlighting some affective mechanical properties of products in

mechanical peeling, the various methods applicable to different food produce

especially tough-skinned vegetables such as pumpkin.

It is evident that each peeling method has its merits and limitations. Some fruits and

vegetables are not well adapted to thermal peeling because this method may cause a

cauterizing of the surface and wound areas. In the dry heat method, small pieces of

charred skin, which are not removed, give a poor appearance to the canned product.

A large amount of wastewater and considerable loss of flesh are other important

disadvantages of this method. It is necessary to find other methods of thermal

peeling that reduce the time required to expose vegetables to heat and subsequently

reduce flesh damage. Floros and Chinnan (1988a) reported that the widespread

application of steam peeling is due to its high level of automation, precise control of

time, temperature and pressure by electronic devices to minimize peeling losses,

and due to the reduced environmental pollution as compared to chemical peeling.

Chemical peeling methods similar to thermal methods also have limitations. Those

methods should be used in very restricted conditions otherwise high peeling losses

will result. For example, Smith et al. (1986) pointed out that if caustic chemicals

such as lye are used for a long time or at high temperature, it will lead to the

softening of the product with a high degree of losses in edible tissues, expensive

caustic solutions and caustic solution disposal. Otherwise, as they stated, this

method cannot be used for the peeling of some vegetables and fruits such as

pumpkin. Also, this researcher believes that there is no guarantee of absence of

harmful effects resulting from the use of chemical materials.

33

The comparison of different peeling methods indicates that mechanical peeling is

preferred as it maintains the freshness of vegetables and protects the flesh either

from the effects of chemical materials or from heat in the thermal methods.

However, mechanical peeling methods have some limitations. For example, every

machine is designed for a specific vegetable and shape. Further, peeling losses and

the amount of wastewater are considerable. Low efficiency is another concern.

To date no recorded work has been conducted to investigate the limitation of

current mechanical peeling methods for tough-skinned vegetables such as pumpkin.

Also there is no knowledge about the tissue properties of this kind of product. High

peeling losses resulting from the current peeling methods of products such as

pumpkin necessitate the development of new automated peeling methods for tough-

skinned vegetables. The selection and development of peeling methods that would

be commercially viable requires identification of tissue properties. These properties

should be determined in relation to the particular peeling methods. For example,

identifying some mechanical properties (i.e. toughness, cutting force and shear

strength) for different states of product will help to clarify the best technique to

mechanically separate skin from under layers. The kind and rate of necessary forces

to apply for the separation of skin from flesh without damaging flesh can be

determined by the study of mechanical properties of product to be peeled.

The study of mechanical properties is also necessary for any further mathematical

modelling of peeling process. Modelling the peeling process enables identifying

effective parameters related to the peeler and product to be peeled. Knowing those

parameters helps machine manufacturers meet the needs of their food industry

customers to be able to fully control the peeling process, reduce peeling losses and

increase the peeling rate. At this point in time, no publications on the mathematical

modelling of mechanical peeling of fruits and vegetables have been found.

2.6 Summary

The common peeling methods of fruits and vegetables were critically reviewed in

this chapter. The benefits and limitations of mechanical, thermal, and chemical

34

peeling methods along with examples of some interesting works were highlighted.

It was concluded that in spite of low flexibility and high peeling losses, mechanical

peelers are preferred because of their ability to preserve the freshness and quality of

the peeled product. The current situation of tough-skinned vegetable peeling, with

pumpkin as a case study, was considered. Semi-manual peeling of these vegetables

leads to high peeling losses especially on pumpkin varieties that have an uneven

surface. In addition, available automated peelers of pumpkin are not able to follow

uneven surfaces of produce. It is necessary to develop innovative mechanical

peeling methods for these kinds of products. It was concluded that the selection and

development of the mechanical peeling method should be directly related to the

mechanical properties of products. Some mechanical properties such as toughness,

cutting force and shear strength were considered in this review. The comparison of

these properties among different states of products, especially skin and unpeeled

product, will help designers to select the best kind of separating forces and in proper

rates. Modelling of the peeling process was discussed in the last part of review. The

literature research has shown that to date there are no published materials on

mathematical modelling of mechanical peeling.

Therefore, the demand for a commercially applicable mechanical peeling method

and the lack of knowledge about mechanical properties of tough-skinned vegetables,

with pumpkin and melon as case studies, encouraged this research. The results of

this research could be commercially viable both in terms of the peeling methods

developed and the mathematical model. The model will be able to explain the

behaviour of the proposed method mathematically on the basis of properties related

to the product and peeling tool.

It is identified thus, that the first step towards developing mechanical peeling

methods followed by a mathematical modelling for tough-skinned vegetables is the

correct and accurate identification of the mechanical properties of pumpkin and

melon (case studies). This effort is elaborated in Chapter 3.

35

Chapter 3

Testing of mechanical properties of

tough-skinned vegetables

3.1 Introduction

One of the reasons for studying the physical and mechanical properties of fruits

and vegetables is the improvement of efficiency of processing equipment,

especially mechanical peelers. The tissues of most fruit and vegetable products

are subjected to different wanted and unwanted mechanical forces and strains

during the post harvesting stage. The wanted mechanical loading takes place

basically in food processing equipment such as slicers and peelers and is always

accompanied by unwanted loads. Further, unwanted mechanical loading

(compression, impact, and vibration) is the main cause of bruising of products

during post harvesting operations (Brusewitz et al., 1991). Knowledge of the

physical and mechanical properties of products will be useful for the purpose of

increasing the effects of wanted, and decreasing the effects of unwanted,

mechanical loading.

As discussed in Chapter 2, compression testing is one of the basic and most

important tests in the study of mechanical properties of fruits and vegetables.

Mechanical properties of skin, flesh, and unpeeled products can be identified by

using this test (Jackman and Stanley, 1992; Voisey and Lyall, 1965a; Voisey and

Lyall, 1965b; Grotte et al., 2001; Holt, 1970; Voisey et al. 1970; Behnasawy et al.,

2004). In addition to the compression test, a tensile test is carried out to determine

skin properties such as skin strength (Jackman and Stanley, 1994). The latter

method is difficult to implement because of shortcomings such as difficulty in the

36

holding of skin specimens during the test (Su and Humphries, 1972) and the

creation of premature tensile failure during specimen preparation (Clevenger and

Hamann, 1968; Thompson et al., 1992).

Several researchers for example, Grotte et al.( 2001), Jackman & Stanley ( 1994)

and Voisey et al. (1970) have used the difference between unpeeled (overall)

compression test and peeled compression test (flesh only) to obtain indirectly the

result of the force-deformation test of the skin. This experimental procedure has

been rejected by some researchers because of the likelihood of some errors in the

result. For example, Thompson et al. (1992) concluded that to determine the

contribution of the skin to the external puncture force (in the case of cucumber)

by making measurements before and after skin removal is subject to error. Further

Jackman and Stanley (1992) concluded that the difference in puncture load

displacement between unpeeled (overall) and without skin (flesh) product cannot

provide the load displacement of the skin itself. The reason they determined for

this is the increase in the effective area of compression during puncture of the skin.

Attempts to find any useful published data on physical and mechanical properties

of pumpkin and melon varieties have been unsuccessful. This part of the study has

been done in response to the two main queries explained as follows.

Pumpkin and melon belong to the Cucurbitaceous family and are idiomatically

called tough-skinned vegetables. This term is commonly used but no scientific

(including botanical) definition of this term was found in the literature review.

This chapter explains the degree of similarity between these two products of the

Cucurbitaceous family and defines a new classification with the name of ‘tough-

skinned vegetables’ on the basis of mechanical properties.

Then, recommendations are developed with regard to the design and optimization

of processing equipment, especially peelers, for pumpkin and melon. The current

study was conducted on three common varieties each of pumpkin and melon with

the aim of investigating some mechanical properties. Rockmelon, Honeydew, and

Watermelon were the three chosen varieties of melon and the three chosen

varieties of pumpkin were Jarrahdale, Jap and Butternut. Finding the similarities

37

and differences between properties will enable specification of the range of

application of different peelers. The investigation was carried out by means of

using compression testing on different states of the product including skin, flesh,

and unpeeled. The investigation of the skin properties was carried out directly on

separated skin as well as flesh. Force-deformation behaviour, and rupture force

for the two states - skin and unpeeled product - were investigated and toughness

was calculated for both states. Shear strength, cutting force, and maximum force

of shear strength were evaluated for three states - flesh, skin, and unpeeled

product. In addition, the relative contribution of skin to unpeeled product for each

property was calculated. The mean arithmetic value of each property was

statistically compared for different varieties.

3.2 Design and construction of instrumentation for

testing vegetables properties

A number of different devices were designed and built for testing the mechanical

properties of vegetables. As product juices caused the test environment to be

acidic, stainless steel was used as the material for the instrumentations. They are

described below.

3.2.1 Cutter

A drum with a diameter of 80 mm and the edge sharpened at 30° (Figure 3.1.a)

was fabricated from stainless steel. It was used to cut and take samples from

vegetables. The external diameter of the cutter was fitted to the internal diameter

of the unpeeled specimen holder. The specimen taken by the cutter fitted into the

sample holder.

3.2.2 Holder of unpeeled sample

The holder was designed and made to hold the unpeeled specimen. It was made

from stainless steel with internal diameter of 80 mm which is ten times the

diameter of the indentor as shown in Figure 3.1.b. The diameter was chosen to be

38

at least ten times that of the indentor to ensure that the sample reflects the

properties of the whole vegetable. The holder was designed to be installed on the

Universal Testing Machine (UTM) directly. It was used in those experiments to

test the resistance of vegetables to shearing, puncturing and cutting forces.

3.2.3 Holder of skin sample

The holder was designed and made to keep the specimens of skin. It was used in

those experiments to test the resistance of the skin to shearing, puncturing and

cutting forces. It was made from stainless steel with a diameter of 54 mm as

shown in Figure 3.1.c.

3.2.4 Indentor

Three different shapes of indentors were used as the main devices for the shearing,

puncturing and cutting tests. The results of the experiments were different

depending on the shape of the indentor’s end. The following indentors were

designed and made for different experiments.

3.2.4.1 Spherical end indentor

The spherical end indentor was made from stainless steel to be used in the force-

deformation test. On the basis of American Society of Agricultural Engineers

(ASAE), the cylindrical indentor of 8 mm in diameter was made with spherical

end (ASAE S368.4) and a curvature diameter of 25 mm as shown in Figure 3.1.d.

3.2.4.2 Flat end indentor

A flat end indentor was made from stainless steel to be used in the shear strength

test (ASAE S368.4). The end of the indentor was flat and had a diameter of 8 mm

(Figure 3.1.e).

3.2.4.3 Cutting indentor

39

A sharpened (30° included angle of the edges) indentor, which was made from a

1.5 mm thick piece of stainless steel (Figure 3.1.f) was to be used for the cutting

force test (Ohwovoriole et al., 1988).

3.2.5 Curvature meter

The ASAE standard (ASAE S368.4) requires the measurement of the curvature

radius on a sample before force-deformation tests. A special device was designed

and built (Figure 3.1.g) for that purpose. It included a cross bar with four pairs of

holes to install measuring pins at four different positions and a dial gage indicator

with an accuracy of 0.01 mm. The holes on the cross bar provided four different

positions of measurement adapted to the size and the shape of convex specimen.

These positions were 40, 60, 80, and 100 mm. It enabled the measurement of the

maximum and minimum radii of curvature at the point of indentation.

3.2.6 Friction coefficient tester

The apparatus was designed and built to measure the frictional coefficient of

vegetable samples by means of sliding on a stainless steel chute with adjustable

tilt angle. The chute could also be plated with wood or Teflon as shown in

Fig.3.1.h.

3.3 Testing methodology

Experiments were carried out to investigate mechanical properties of different

varieties of melon and pumpkin (Cucurbitaceae family) by using instrumentations

for testing vegetable properties. Toughness, rupture force, shear strength, and

cutting force were determined for the Jarrahdale, Jap, and Butternut varieties of

pumpkin and the Rockmelon, Honeydew, and Watermelon varieties of melon.

The investigation was carried out in three states - flesh, skin and unpeeled product

- ignoring the toughness and rupture force of flesh. Relative contribution of skin -

40

a. Vegetable cutter b. Sample holder

c. Skin sample holder d. Spherical end indentor

e. Flat end indentor f. Cutting indentor

g. Curvature meter h. Friction coefficient tester

Figure 3.1.The instrumentations of testing mechanical properties of vegetables

i i ffi i

41

to unpeeled state of each property was estimated. The obtained results were

statistically analysed.

3.3.1 Force-deformation test

A study of the force-deformation relationship of agricultural products will give

valuable data for engineering analysis and design. Rupture point, stiffness or

rigidity, toughness, bioyield point, plasticity and degree of elasticity could be

considered as important parameters. The behaviour of samples under the force-

deformation test and determination of rupture force and toughness for two

different states involving skin and unpeeled samples were the objectives of this

test. Tests were carried out according to ASAE standard (ASAE S368.4). On the

basis of the standard, the maximum and minimum radii of curvature at the point

of indentation on the product were measured and recorded by means of the

curvature meter. Because conducting the test on the whole vegetable was

impossible, the unpeeled specimens with a circular shape of 80 mm in diameter

and 10 mm thick (flesh depth) were prepared from whole pumpkin by using a

special cutter device. Skin specimens were prepared with a diameter of about 30

mm and flesh was removed by means of scraping to avoid any ambient effects on

the test results. Experiments were carried out using a Universal Testing Machine

(Hounsfield Test Equipment-H5000M). The machine subjected the specimens to

compression at the speed of 20 mm/min (ASAE S368.4). The specimens were

kept in their special holders during tests. The increasing compression force led to

loosening the resistance of the sample and finally rupturing of the sample at

rupture point. Applied forces (N) and the resulting deformations (mm) could be

read off the machine and recorded on the connected computer. Every experiment

gave one force-deformation curve. The test was repeated at least 20 times.

3.3.2 Shear strength test

The maximum shear stress that a material is capable of sustaining is called shear

strength (Mohsenin, 1970). It is calculated from the maximum load during a shear

or torsion test and on the basis of original dimensions (the cross section) of the

42

specimen. The shear strength test was carried out on three different states of the

products: skin, flesh, and unpeeled sample. Initially the test was carried out on

skin, which is not supported by the flesh. The holder of skin sample and flat end

indentor were used. Skin samples had a diameter of at least three times that of the

indentor to facilitate them being held by the skin holder. Tests for the different

varieties of pumpkin and melon (three varieties each) were carried out. The

samples in different states were selected from whole product of different sizes and

from different parts of the vegetable (from the top, bottom, and middle parts of all

varieties and from convex and concave areas for pumpkin). The size and other

specifications of the skin and unpeeled specimens were similar to that described

in the previous section. Middle layers of flesh close to skin were chosen to be

picked up as circular shaped flesh specimens of 30 mm diameter and 5 mm

thickness. The UTM machine with the speed of 20 mm/min was used to apply

shearing force. The test was repeated at least 20 times for every state.

3.3.3 Cutting force test

This test was carried out to determine the necessary cutting force of a product in

three states involving unpeeled, skin and flesh of different varieties of pumpkin

and melon. Samples were prepared from different parts of the product and kept in

the holder. The cutting indentor and UTM were applied. The speed of the loading

cutting force was 20 mm/min. The test was repeated ten times and the amount of

applied force was read directly from the machine and from the force-displacement

plot.

3.3.4 Friction Coefficient test

The test was carried out to measure the static coefficient of friction of each variety

of melon and pumpkin. Products were tested in three different states: unpeeled,

without periderm, and flesh. They were also tested on three different surface

materials: stainless steel, Teflon, and wood by using the friction coefficient tester.

There was no necessity to do statistical comparisons for the obtained results

because the purpose of the test was to develop design recommendations for

43

different possible materials applied to the peeling machine. The test was carried

out on samples of different sizes of product and repeated ten times for each. The

moisture content of samples was measured simultaneously with the testing of

properties. The sample which was used for the moisture content test was removed

from the original piece of product for the property test. Each sample was a cube

with 10 mm in each dimension. The experiments were conducted under the same

conditions of temperature and humidity as in the previous experiments on

mechanical properties.

The sample was placed on the chute with adjustable tilt angle. The chute was

moved up until the sample started to slide. The tangent of angle of chute in this

position was the static coefficient of friction. The chute could also be plated with

wood or Teflon to measure the static coefficient of friction on this materials.

3.3.5 The relative contribution of skin to the unpeeled mechanical

properties

The percentage contribution of skin to unpeeled mechanical properties was

calculated by dividing the values of the mechanical properties of skin by the same

property of unpeeled products and multiplying by 100. In addition to this

determination of the skin’s contribution to the unpeeled mechanical properties,

this property can be used in comparisons of investigated varieties with other fruits

and vegetables. Although direct comparison of the same properties obtained by

different researchers for different vegetables is extremely difficult because of

different conditions of experiments, it is possible to assess the relative

contribution (%) of skin. The standard experimental methodology suggested by

ASAE was used in this research to simplify comparisons of the same properties

for different products in the future.

3.4 Results and discussion

The results of the mechanical properties investigation for the three varieties of

both pumpkin and melon are shown in Figures 3.2 to 3.8 and Table 3.1. The

44

obtained results for each property except friction coefficient and also the results of

statistical comparison among different varieties are shown in Appendix 1. One-

way analysis of variance (ANOVA) with post-hoc comparisons by using SPSS

(version 12 for windows) software was used for statistical comparisons of the

results. Variations in the mean values of each property for different varieties of

products were determined by Least Significant Difference (LSD). LSD values

were calculated at the 5% level of probability (p).

3.4.1 Force-deformation relationship

The sectional view of a pumpkin’s skin layers and flesh before and after the force-

deformation test is shown in Figure 3.2.a-d. High cohesion of the cells leads to a

high need of force and deformation to cause the rupture of the unpeeled product.

The high rate of rupture force causes bruising of the flesh to a depth of twice the

depth of penetration immediately after rupture. The necessary rupture force of

skin was 41 N for Jarrahdale and it reached 189 N for Butternut which also

showed a strong cohesion of skin cells itself. Typical examples of force-

deformation curves for skin and unpeeled products are shown in Figures 3.2.e and

3.2.f. The peak point of the curve (rupture point) is important because the area

under the curve from the origin to this point represents the toughness of the

sample. The high rupture force and low deformation of Jarrahdale compared to

Rockmelon can be easily recognised but this does not necessarily mean a high

difference of toughness. The linear compression representation of the skin and

unpeeled states for both vegetables along a clear peak point (rupture point) can be

easily seen in the curvatures. The rupture point also shows the maximum point in

the range of flesh elasticity such that flesh collapses at this point. Both melon

curves, especially for the skin case, showed a round shape at the peak points.

Harker et al. (1997) found similar behaviour for the shearing of Watermelon flesh.

They attributed this to either a change in the mechanical properties of the cell

walls just before tissue failure or a gradual progression of breakage of individual

cells until rupture point. After reaching the rupture point, the force falls to a much

lower level for Rockmelon than it does for Jarrahdale. This shows that Jarrahdale

has tougher flesh than Rockmelon. The other minor peak points after reaching the

45

a. Pumpkin sample before test

b. Tissue deformation before rupture (Indenter ∅8 mm, Tip radius R = 12.5mm Depth of indenter penetration h= 4.20mm)

c. Tissue deformation after rupture (Indenter ∅8mm, Tip radius R = 12.5 mm Depth of indenter penetration h=8.44 mm)

d. Pumpkin sample after indentation test Tissue is affected to the depth of twice the depth of penetration

-500

50100150200250300

0 5 10 15

Deformation, mm

Forc

e, N

UnpeeledSkin

0

20

40

60

80

100

120

0 2 4 6 8 10Deformation, mm

Forc

e, N

UnpeeledSkin

e. Force-deformation curve of Jarrahdale variety of pumpkin (skin and unpeeled)

f. Force-deformation curve of Rockmelon variety of melon (skin and unpeeled)

Figure 3.2. Effects of force-deformation test (a-d) and relationship between

force (N) and deformation (mm) for melon and pumpkin in two states (skin and unpeeled) (e-f)

46

rupture point for unpeeled Jarrahdale may be considered the result of friction on

the sides of the indentor (Grotte et al., 2001).

Pumpkin varieties showed higher unpeeled rupture force compared to the varieties

of melon (Figure 3.3). There was no significant difference among unpeeled

varieties of pumpkin (Appendix 1). The rupture force of unpeeled Rockmelon was

significantly (p < 0.05) different than the two other varieties of melon.

While the varieties of pumpkin were significantly different than melon in

unpeeled rupture force, some similarities were found in the rupture force of the

skin (Appendix 1). Jap pumpkin and Rockmelon had similar rupture force of skin

as well as Butternut with Honeydew and Watermelon. Rupture force of skin and

unpeeled product were in the range of 40.68-189.37 N and 100.01-265.49 N

respectively.

050

100150200250300

Jap

Jarrah

dale

Buttern

ut

Rockm

elon

Honey

dew

Wate

rmelo

n

Vegetable

Rup

ture

forc

e (N

) Unpeeledskin

Figure 3.3. Rupture force of skin and unpeeled states for different varieties of

pumpkin and melon

47

3.4.2 Toughness

Unpeeled toughness of the varieties of pumpkin and melon were statistically alike

and also no significant difference was found between Honeydew and Watermelon

(Appendix 1). The range of difference of unpeeled toughness was between 601.26

and 1079.66 N. mm. The comparison of skin toughness among all products

revealed no significant difference between Butternut and Rockmelon as well as

between Rockmelon and Honeydew. The skin toughness of Jap and Jarrahdale

was also statistically similar. The skin toughness varied from 13.87 to 436.36 N.

mm for Jarrahdale and Watermelon respectively (Figure 3.4).

0200400600800

10001200

Jap

Jarrah

dale

Buttern

ut

Rockm

elon

Honey

dew

Wate

rmelo

n

Vegetable

Toug

hnes

s (N

.mm

)

Unpeeledskin

Figure 3.4. Toughness of skin and unpeeled states for different varieties of

pumpkin and melon

3.4.3 Cutting Force

Except for the Butternut and Jarrahdale, the products did show close values of

unpeeled cutting force. There was no significant difference between Jap and the

other three varieties of melon. While Honeydew and Watermelon were like the

Jap they were significantly different to unpeeled Rockmelon. The cutting force of

Jarrahdale with 5.15 N and Butternut with 20.48 N were the lowest and the

48

highest unpeeled cutting force respectively (Figure 3.5). The same order was also

seen in the cutting force of skin. The difference varied from 2.82 to 17.31 N. The

skin cutting force of Jap was like that of Honeydew and Watermelon. Honeydew

and Rockmelon also showed similar properties. The cutting forces of flesh for

different varieties of melon were statistically alike and significantly (P < 0.05)

lower than pumpkin varieties. It ranged from 0.27 to 5.43 N for Honeydew and

Butternut respectively.

0

510

1520

25

Jap

Jarrah

dale

Buttern

ut

Rockm

elon

Honey

dew

Wate

rmelo

n

Vegetable

Cut

ting

forc

e (N

) UnpeeledSkinFlesh

Figure 3.5. Cutting force of skin, flesh and unpeeled states for different varieties

of pumpkin and melon

3.4.4 Maximum Force of Shear Strength

The maximum shear strength force of unpeeled product varied from 99.69 N for

Rockmelon to 250 N for Butternut. There was no significant difference among

pumpkin varieties in this case as Figure 3.6 clearly shows.

Although Watermelon was like the other varieties of melon, Honeydew and

Rockmelon did show significant difference (P < 0.05). Similarities were found

between Jap and Rockmelon as well as Butternut with Honeydew and

Watermelon in the case of skin. The maximum shear strength force varied

between 57 and 168 N for Jarrahdale and Butternut, respectively. The investigated

property in the flesh state did not show significant difference among melon

49

varieties and also between Jap and Butternut. The lowest and highest values of

this property belong to Rockmelon and Butternut (8.82-64.15 N).

050

100150200250300

Jap

Jarrah

dale

Buttern

ut

Rockm

elon

Honey

dew

Wate

rmelo

n

Vegetable

Max

. she

ar fo

rce

(N) Unpeeled

SkinFlesh

Fig.3.6.The maximum shear strength force of skin, flesh and unpeeled states for

different varieties of pumpkin and melon

3.4.5 Shear Strength

There was no significant difference among varieties of melon in the case of

unpeeled shear strength. Jap and Butternut were alike in this property. The

difference ranged between 0.51 and 2.42 N.mm-2 for Rockmelon and Jap,

respectively (Figure 3.7). The same order of vegetables was seen for the shear

strength of skin and it ranged from 0.71 to 3.29 N.mm-2. The skin of Jarrahdale,

Butternut, and Honeydew had similar shear strength. There was also no

significant difference between Rockmelon and Watermelon in this case. In the

statistical comparison of shear strength of flesh only varieties of melon were alike.

The lowest and highest values of shear strength of flesh belong to Honeydew

(0.09 N. mm-2) and Butternut (0.55 N.mm-2) respectively.

50

00.5

11.5

22.5

33.5

Jap

Jarrah

dale

Buttern

ut

Rockm

elon

Honey

dew

Wate

rmelo

n

Vegetable

Shea

r st

reng

th (N

.mm-2

) UnpeeledSkinFlesh

Figure 3.7. The shear strength of skin, flesh and unpeeled states for different

varieties of pumpkin and melon

3.4.6 Static coefficient of friction

Wood, stainless steel, and Teflon generally showed increasing static coefficients

of friction, respectively (Table 3.1). The static coefficient of friction of unpeeled

products ranged from 0.15 to 1.70 for Watermelon and Jap respectively on Teflon

and wood. That was varied for flesh from 0.27 (Watermelon on stainless steel) to

2.40 (Butternut on wood). The varieties of melon did not show any sliding on

wood in the case of flesh. The products in the state without periderm in total had a

higher rate of this property. While Watermelon without periderm just showed

slide on Teflon (0.88 gradient), the rest were found in the range of 0.34 (Jap on

Teflon) and 2.42 (Rockmelon on stainless steel).

3.4.7 The relative contribution of skin to unpeeled mechanical

properties

The relative contribution percentage of skin to shear strength of unpeeled product

was significantly high for all products (Figure 3.8). It ranged from 102 to 336%

for Butternut and Honeydew, respectively. The higher percentage of contribution

51

revealed higher strength of skin to shear compared to the unpeeled state, or in

other words, the tough-skinned product.

Table.3.1. Static coefficient of friction of three varieties of pumpkin in the states

of flesh, unpeeled, and without periderm on three different materials including

stainless steel, Teflon, and wood.

Jarrahdale Jap Butternut Rockmelon Honeydew Water-

melon

St. Steel 0.46 0.45 0.56 1.04 0.78 0.27

Teflon 0.43 0.33 0.60 0.83 0.65 0.40

Flesh

Wood 1.05 0.63 2.40 No Slide No Slide No Slide

St. Steel 0.30 0.62 0.44 0.60 0.41 0.46

Teflon 0.19 0.63 0.16 0.19 0.17 0.15

Unpeeled

Wood 0.45 1.70 0.50 0.77 0.40 0.47

St. Steel 0.61 0.76 0.99 2.42 -* No Slide

Teflon 0.40 0.34 0.69 0.53 -* 0.88

Without

periderm

Wood 0.92 1.01 0.97 2.10 -* No Slide

*Honeydew had no periderm

The relative contribution of the skin of Honeydew to shear strength was

significantly (P < 0.05) different to that of other vegetables. Butternut was also

statistically different to Jap, Watermelon and Jarrahdale. The lowest relative

contribution (%) of skin to the investigated properties of unpeeled products

belongs to toughness. Jarrahdale and Jap were significantly similar and had the

lowest contribution (%) of skin to toughness. Butternut statistically had no

difference with the Rockmelon and Honeydew varieties of melon. The relative

contribution (%) of skin to the toughness of unpeeled investigated products

ranged between 1 and 50 N. mm. Grotte et al. (2001) reported 45% of the same

property for the Golden Delicious apple at harvest. This value increased to 78%

after 210-day storage at 2º C. They did the measurement indirectly by calculating

the difference of toughness with and without skin.

52

The comparison of contributions in cutting force showed that Jap and Butternut

were similar to the varieties of melon except Rockmelon. This property ranged

from 53 to 102 N for all varieties. Relative contribution of skin to cutting force of

unpeeled Cassava tuber was calculated indirectly by using reported data

(Ohwovoriole et al., 1988) between peeled and unpeeled product. It was 76% and

is very close to the obtained values for Jap and Butternut varieties.

050

100150200250300350400

Jarrah

dale Jap

Buttern

ut

Rockm

elon

Honey

dew

Wate

rmelo

n

Vegetable

Con

trib

utio

n (%

)

Rupture forceToughnessCutting forceMax. shear strength forceShear strength

Figure 3.8. The relative contribution (%) of skin to different mechanical

properties of pumpkin and melon

The Butternut skin in rupture force was similar to that of Honeydew. That was

close to the reported values for other products. Thompson et al. (1992) reported

58 to 88% of the same property by doing a puncture test on different fruits

including avocado, Bartlett pear, McIntosh apple and also vegetables such as

eggplant, green bell pepper, slicing-type cucumber, zucchini and squash. Also

Grotte et al. (2001) obtained 65 to 70% of relative contribution of skin to different

unpeeled varieties of apples. Jap with Jarrahdale and Rockmelon with two other

varieties of melon were found to be similar in the case of rupture force. The

varieties of pumpkin were significantly different to the melon varieties in skin

contribution to maximum shear strength force. No difference was found among

the varieties of melon in this case. The skin of Honeydew and Watermelon had

53

higher and lower contribution (%) to shear strength of unpeeled product

respectively. The skin contribution (%) of Honeydew was significantly (p<0.05)

different to all other vegetables and except for the significant existing difference

of Jap with Jarrahdale and Watermelon, the remaining were alike in this case.

Table3.3. Relative contribution (%) of skin to different mechanical properties

(Mean ±Standard Deviation)

Properties

Varieties

Rupture

force

N

Toughness

N. mm

Cutting force

N

Max. shear

Strength force,

N

Shear

strength

N.mm-2

Jarrahdale 16±9 2±1 53±12 28±7 153±55

Jap 22±7 1±0.7 85±23 42±27 145±41

Butternut 72±6 22±9 84±8 67±8 102±16

Rockmelon 89±6 28±14 102±17 95±8 141±30

Honeydew 82±16 21±18 102±25 89±17 336±86

Watermelon 97±2 50±15 100±14 97±8 178±43

3.4.8 Application of investigated mechanical properties

The value of investigated properties could be used in the development of design

specifications for a peeler and the application range for different vegetables. The

“ideal” peeling target is removal of the skin without wasting the underlying good

tissue. Maximum permitted rupture force to break the skin without rupturing the

whole pumpkin with regard to standard deviations can be considered about 200 N.

Values higher than 200 N will lead to rupturing and wasting of the whole

Jarrahdale and less than that, probably would not give results in rupturing of the

Butternut skin. The above range can not be used for melon varieties and

determination of a specific limit for them is not possible. The rupture forces of

different varieties of melon are different from each other and it is close for the

54

skin and unpeeled states of each variety. It is not applicable in the case of

Watermelon for which the values of rupture force of skin and unpeeled states are

the same. The suggested applicable rupture force of skin to protect the whole

product and save energy is 95 and 160 N for Rockmelon and Honeydew

respectively. Values of toughness showed different work necessary to perform

rupture of skin for different varieties. To save energy, it should not be considered

more than 22, 62, and 164 N. mm for Jarrahdale, Jap and Butternut varieties of

pumpkin respectively. The suggested values of melon varieties are 266, 397, and

527 N. mm for Rockmelon, Honeydew, and Watermelon respectively. Cutting

force and maximum shear strength force of skin showed the maximum force

needed to cut through the peel without injuring the whole product. Although 188

N as the maximum force of shear strength can be applied effectively without any

harm to the whole pumpkin except the Jarrahdale, determination of any value for

the melon variety is not possible because of the overlap of skin and unpeeled

melon in this case. Determining one value of cutting force for all varieties is also

impossible. Injuring the variety with lower thickness as well as wasting energy are

the reasons to consider different cutting force of skin to that obtained. There is

also overlap in the skin and unpeeled states for cutting force of Jap and all three

varieties of melon. Butternut showed the same value for shear strength of skin and

unpeeled specimens due to higher skin thickness. This property for skin is

considerably higher than the unpeeled state for all varieties of investigated

vegetables. Higher value of shear strength for skin when compared with unpeeled

products of different varieties can be a possible reason for skin toughness of

melon and pumpkin, which should be considered as an important point for peeler

design. The scientific definition of tough-skinned vegetables in spite of common

use could not be found in literature review and can be suggested by this writer as

follows:

Vegetables could be defined as tough-skinned vegetables when the shear strength

of skin is equal to or higher than the shear strength of unpeeled product in the

same condition of experiment.

The significance, therefore, of this research is that no work has been done to

classify the vegetables and fruits on the basis of mechanical properties and the

55

above definition can introduce the first classification of the vegetables on the

basis of mechanical properties.

The obtained results of static coefficients of friction recommend using wood,

Teflon, and stainless steel as the peeler material in the ranges of 0.15-1.70, 0.27-

2.4, and 0.34-2.42 for unpeeled, flesh, and without periderm states respectively.

3.5 Summary

Some mechanical properties and their applications for three different varieties of

melon (Rockmelon, Honeydew, and Watermelon) and pumpkin (Jarrahdale, Jap,

and Butternut) were investigated. The investigation was conducted on different

states of product, namely, skin, flesh and unpeeled. The measurement of the skin

properties was carried out directly on separated skin and also flesh. Rupture force

and toughness for two states of unpeeled and skin in addition to cutting force,

shear strength and maximum force of shear strength for skin, flesh, and unpeeled

states were determined by means of a direct compression test for each case. The

existence of similarity among those six varieties of tough-skinned vegetables was

investigated statistically. The results were applied firstly to define tough-skinned

vegetables on the basis of mechanical properties for the first time. Secondly, they

were used to find out the best potential peeling methods in the preliminary stage.

Those results, thirdly, were suggested for consideration as the design parameters

for tough-skinned vegetable peelers.

56

Chapter 4

Testing equipment for investigation of

mechanical peeling methods

4.1 Introduction

The simulation of real peeling circumstances was made possible by the design and

fabrication of a new test rig. The purpose of the design was investigation of

different mechanical peeling methods. Indeed, design was conducted for the

purpose of investigation of the effects of different peeling tools on the product;

peeling of the whole product (design of an industrially applicable peeler machine)

was not an objective of this research. The effect of peeling tools on different areas

of skin was assessed for the circular band area formed on a product. The width of

the band on skin depended on the kind of peeling tool. At the stage of design of the

test rig, the prediction of what methods or tools will be used was difficult. Therefore

the process of design and manufacture of the test rig was completed during testing,

and additional components are described in section 4.3.4 (“Attachment”) of this

chapter. The important objectives and the methods of their achievement are

explained below and relevant drawings are shown in Appendix 2.

57

4.2 Objectives of the design

4.2.1 Adaptability for investigation of different mechanical peeling

tools

The test rig was designed to be as versatile as possible, to enable testing of different

mechanical peeling tools: blades, knives, and abrasive devices. The flexibility of the

test rig for investigation of improved features of those existing and of new

mechanical peeling tools was considered. Milling cutter, wire brush and abrasive

ropes were some examples of peeling tools of interest to be investigated in the test

rig.

4.2.2 Possibility of accommodation of different product size

As the variation in product size is considerable, it was attempted to design a test rig

in which it would be possible to use different sizes of products. The range of

product size variation was taken into account in designing the peeler head.

4.2.3 Possibility of peeler head position adjustment

To cover the whole surface of products of different sizes, it was necessary to enable

the peeler head to adjust its position. It was desirable to adjust its position in three

main directions: axial, lateral and vertical. As the number of runs for different

experiments could be large, it was essential to provide the means for simple and

quick adjustment.

4.2.4 Possibility of peeler tool position adjustment

To enable investigation of different angles of acting forces on the product by peeler

tools, it was necessary to make possible positioning of the peeler head in both the

vertical and horizontal planes.

58

4.2.5 Possibility of rotation of peeler tool at different angular

velocities

In some methods, the rotation of the peeler tool at different angular velocities is

needed. Rotary blades and some abrasive tools require rotational movement to

accomplish the task. The role of impact force is fundamentally important in the

efficiency of peeling for those methods. Changing angular velocities was the easiest

way to adjust the impact force in the test rig.

4.2.6 Possibility of rotation of vegetable holder at different angular

velocities

Peeling the whole circumference of one product was necessary for evaluation of the

peeling results. The rotation of the product was assumed to be easier than rotating

of the peeler head around the product. Further, as the different angular velocities of

the product during peeling lead to different results, the table with a product holder

should be spun to achieve a large range of speed variation.

4.2.7 Simplicity and low cost of manufacturing

Low manufacturing cost is one of the objectives of every design. Attempts were

made to reduce the number of components of the test rig. Simple spring and screw

mechanisms were used to provide necessary adjustments.

4.3 Enforcement of the objectives

4.3.1 Chassis and Chamber

The chassis was designed as a portable body equipped with one chamber at the top

and expandable to two separate chambers. Stainless steel was used as the material in

order to provide corrosion resistance. The spacious chamber was designed to

accommodate large size products and the peeler head. The product holder was

59

mounted at the base of the chamber and the peeler head was installed at the front

side of the chamber (Figure 4.1). There were two possible positions of the product

holder; on the centre line of the peeler head and offset (50 mm width and 90 mm

depth) in the lateral direction (Figure 4.2). Such a solution was selected for two

reasons: firstly, to enable handling of different product sizes (120 to 240 mm

diameter), and secondly, to enable peeling by both or just one side of the peeler

head.

Fig.4.1. Test rig

4.3.2 Vegetable holder

The product holder was designed as a rotating table that can carry the product

(Figure 4.2). The product could be fixed on the disc by three sharp blades that form

a pyramid to provide access to the sides and the top. The pyramid with sharp blades

was made in two different sizes to enable handling of small and large vegetables

(120 to 240 mm in diameter). Although the blades make cuts on the vegetable, from

the standpoint of simplicity of machine and access to the most areas of product, the

use of blades was preferred for the test rig in this stage.

Vegetable holder

DC Motor

Peeler head

60

Fig.4.2. Product holder and two available positions

A 24 V DC motor coupled to the worm gearbox was selected to provide up to 270

rpm depending on the voltage supplied (Figure 4.3). The adjustment of angular

velocity of the product holder was carried out by changing the supplied voltage

through the voltage volume in the DC supplier. The speed was measured by an

optical tachometer (G4958, Smiths). The DC motor was installed outside under the

base of the chamber and transferred the torque directly to the shaft of the vegetable

holder. This assembly (details shown in Figure 4.4) can be easily repositioned. To

reduce the friction between the vegetable holder and the table of the test rig, a

Teflon washer (N.6 in Figure 4.4) was used. The diameter of the plate (position 3 in

Figure 4.4) was chosen to meet two limitations: firstly, the plate should be able to

carry heavy products mostly with large diameters and secondly, it should not

interfere with the peeling tools during peeling of small sized products.

Fig.4.3.The two DC sources for vegetable holder and peeler head

61

Fig.4.4. Product holder

1. Shaft 2.Tube 3.Plate 4. Blade 5, 7.Bush 6.Teflon

4.3.3 Peeler head

The mechanism of the peeler head was designed to enable adjustment in three

different directions. Two vertical rods enable movement in the vertical direction (Z

axis) along the front wall of the chamber (Figure 4.1). The adjustment range varied

from 0 to 300 mm in this direction. Position adjustment in the longitudinal direction

(X axis) is provided by a spring (position 7 in Figure 4.5) and screw thread of main

shaft of the peeler head. The adjustment range varied from 0 to 90 mm. The

adjustment of the peeler head in the lateral direction (Y axis) can be achieved by

shifting the vegetable holder in two fixed positions (80 mm distance). Resilient

ability of the holder of the peeling tools was required to enable tools to follow the

irregular shape of different products. The spring mechanism enabled this adjustment.

Peeler tools can be installed on rotary flaps (position 9 in Figure 4.5). There are six

flaps with an adjustable angular position with the plane of rotation parallel to the

product.

62

Fig.4.5. Details of the peeler head

1.Shaft 2.Lock nut 3.Nut 4.Motor 5.Frame 6, 13.Washer 7, 12.Spring 8.Bush

9.Flap 10.Nut Screw 11.Grip screw

Fig.4.6. Peeler head

Ten holes were made in each flap to facilitate the installation of different peeling

tools. The holes were placed in a spiral pattern to improve the yield of peeling

production (Figure 4.7). The angular position of flaps could be adjusted from 0 to

30o. A diameter of 251 mm was selected for the size of the peeler head (flap’s angle

is 0°) to accommodate tough-skinned vegetables of diameters from 120 to 240 mm.

Flaps were adjusted by means of a screw mechanism that contains a spring and a

lock screw (positions 10 and 12 in Figure 4.5). The angular adjustment enables

flaps to accommodate different shapes and sizes of product. The main shaft is

63

driven by a DC motor that can provide angular velocities up to 300 rpm. The

adjustment of angular velocity of peeler head was carried out by changing the

supplied voltage through voltage volume in DC supplier. The DC motor was

installed at the end of the shaft. The rpm could be changed by changing the supply

voltage of the DC motor and was measured by using an optical tachometer (G4958,

Smiths). Different peeler tools can be installed on the flaps using holes and fixtures.

Fig.4.7. Flap with holes in spiral pattern

4.3.4 Attachments

Preliminary experiments (see Chapter 5) revealed that adjustment of flaps of the

peeler head parallel to the product can not provide enough penetration for the

peeling tools. For example, abrasive brushes have to reach the inside of concave

areas of the product for efficient peeling. It was noticed that the possibility of

motion in the vertical plane and perpendicular to the surface of the product will lead

to higher peeling efficiency especially in concave areas because centrifugal force

will help the abrasive brushes to stand straight. To achieve this objective, one

auxiliary peeler head as an attachment was fabricated. The attachment was basically

a pivoted frame equipped with two solid plates that can carry peeling tools in the

plane perpendicular to the product surface. The shaft was coupled to a DC motor

(Figure 4.8). The DC motor was 24 V DC that could provide up to 2000 rpm. The

rpm was controlled by the supply voltage and was measured by an optical

tachometer.

64

Fig.4.8.The auxiliary peeler head as attachment

The attachment was installed on the frame of the main peeler head. The position in

the vertical direction was adjustable by means of two main rods similar to the

previous peeler head. The position in the other two directions could be adjusted by

using two bars with a set of holes. The peeler head was installed on a pivoted

bracket and connected to the frame by a spring to enable following the shape of

product. Therefore the abrasive tool which was installed on one end of the peeler

head was able to move in the radial direction (related to the product). Constant force

of interaction of the peeling tool with the product was maintained by means of dead

weight attached to the bracket through pulleys.

4.4 Performance of the test rig

As the test environment is acidic because of product juices, stainless steel was used

as the material of the test rig. In application, the test rig showed good performance

and versatility enabling the use of different peeling tools and handling tough-

skinned vegetables of different size. Flexibility of the test rig and the ease of

adjustment and installation of different peeling tools including abrasive, knife and

blade tools were excellent. The test rig enabled access to the whole surface of

product except the area engaged with the mounting table.

DC Motor

Pivoted point

Solid plates

65

The test rig has shown the ability to extend the range of application for investigation

of different new mechanical peeling tools. In addition, the peeling of some other

fruits and vegetables can be investigated in the future by the use of this test rig.

4.5 Summary

The test rig for investigation of new concepts of mechanical peeling methods was

designed and manufactured. Versatility and the ability to use different peeling tools

on different sized products and different prospective peeling tools were the criteria

in design of the test rig. High flexibility and possibility of peeler head adjustments

as well as simplicity and low cost of manufacturing enabled experimental

verification of a wide range of mechanical peeling devices.

The test rig proved to be reliable and easy to use. Those capabilities allow the

extension of the range of test rig applications for more and different kinds of

products in the future. It is also believed that investigation of new concepts of

peeling tools is easily possible on the available test rig.

66

Chapter 5

Preliminary trials of different mechanical

peeling methods

5.1 Introduction

Mechanical peeling methods can be classified depending on the type of peelers used.

Mechanical peeling methods include the use of different types of abrasive tools,

knifes, disks etc., and the choice of a peeler is dictated by the type of product that

needs to be peeled. The efficiency of all mechanical peeling tools depends to a large

degree on their shape. The shapes of peeling tools have been developed to

accommodate the different shapes of fruits and vegetables. In addition to the shape,

the specifications of the product to be peeled such as its physical and mechanical

properties, and the reasons for peeling it, are also important. Trial and error as a

simple approach to the development of new shapes of peeling tools was used in this

research. The target was to find a tool of an appropriate shape that could follow the

surface contours of tough-skinned vegetables such as pumpkin. The shape of the

tool had to be able to impart necessary forces to remove the tough skin. A review of

some important trials of different shaped of peeling tools on the Jap variety of

pumpkin form this chapter. The criteria of effectiveness of peeling in experiments

were equal peeling from convex and concave areas with high peeling rate. In each

experiment different parameters were selected that would have a significant

influence on peeling process. The preliminary results and conclusions could help

the author to choose the best tools and methods for further investigations.

67

5.2 Trials of different tools

5.2.1 Wire brushes

Different kinds of wire brushes were tested because of their flexibility and ability to

accommodate the pumpkin shape. The product could be peeled by the end tip of a

wire brush. Two main kinds of wire brushes are available in the market - rotary and

twisted wire brushes. In this case study the effects of both kinds of wire brushes

were investigated.

5.2.1.1 Rotary wire brush

This abrasive tool is designed to strip paint and clean objects (Figure 5.1.a). These

brushes are available in different diameters and thicknesses. They have a

trapezoidal contour in cross-section. For this investigation, it was necessary to

reshape the side section of the brushes for two reasons: firstly, edges with an acute

angle will cause uneven tissue removal and secondly, right angled edges couldn’t

access grooves effectively. The side section of the brush was reshaped to a

triangular contour with a fillet radius of 3 mm. Preliminary experiments were

carried out. The effective parameters were found to be the pushing force of the

brush, the angular velocity of the vegetable holder (v. speed) and angular velocity

of the peeler head (p. speed).

(a) (b)

Fig.5.1.Rotary wire brush and its peeling effect on a pumpkin

68

The brush was brought into contact with the pumpkin with different pushing forces

(0.2-1.4 N), angular velocities of the peeler head (300-1000 rpm) and the vegetable

holder (5-20 rpm). The uncovered ranges of values were unlikely to generate

effective results. The pressure of the pushing force on the peeling tool was applied

through a spring and a pulley. The results showed that the brush did not completely

follow the shape of pumpkin and caused excessive flesh removal in convex areas

(Figure 5.1.b). Indeed these convex areas completely disappeared. This high loss of

flesh in the peeling process was the main limitation.

5.2.1.2 Twisted wire brush

A multi-strand stainless steel wire brush was used (Figure 5.2.a). Firstly, one end of

the wire was loosened to form the shape of the brush and it was fixed to a holder

bush (Figure 5.2.b) at the other end. Several brushes were installed on the flaps of

the peeler head (Figure 5.2.b). Preliminary experiments were conducted. The

significant parameters were found to be the v. speed, p. speed and the angle of flaps.

Experiments were carried out under different angular velocities of the peeler head

(300-1000 rpm) and pumpkin (5-20 rpm). The flaps were also tilted at different

angles (0-30°). The uncovered ranges of values were unlikely to generate effective

results. The values produced from investigated ranges did not generate satisfactory

results. There was excessive flesh removal at convex areas (Figure 5.3) but the

concave areas left unpeeled.

(a) (b)

Fig.5.2. Twisted wire brush before and after loosening the strands

Holder bush

69

Fig.5.3. Affected areas of pumpkin after using the twisted wire brush

In the second stage, an attempt was made to improve the shape and the flexibility of

the brush. For the stainless steel brush, first, the strands were loosened and then

wires in the secondary strands were also loosened (Figure 5.4.a). Four brushes in a

new configuration were clamped between the two disks of the peeler head

attachment at 90 degrees to each other with each pair having a different length

(Figure 5.4.b). Experiments were conducted under the same conditions as in the

previous stage. Better results were obtained compared to the previous stage. Peeling

was initiated at the grooves and then worked towards the convex areas. For one

adjusted distance, peeling at the grooves by the brush tips was quite effective but in

convex areas the side strands of the wires were just touching the pumpkin. More

flexibility of the wires at the side areas caused low peeling productivity compared

to at the grooves. So in order to peel in the convex areas, a large amount of flesh

needed to be removed from the concave areas. Figures 5.4.c and d show the

pumpkin after 30 minutes of continuous peeling.

At the third stage, to reduce the flexibility of the side areas of the brush, each

secondary strand was restricted by an aluminium clamp (Figure 5.5.a). Experiments

were conducted under the same conditions like as in the previous stages.

The results were not as encouraging as at the second stage because there was much

lower flexibility at the side areas of the brush. Also, because the width of the brush

tip was bigger than the width of grooves, more flesh was needed to be removed

from the concave areas in order to reach to the floor of grooves.

70

(a) (b)

(c) (d)

Fig.5.4.Improved design of the artificial twisted brush in the second stage and its

effects

At the fourth stage, each secondary strand was cut at a different length and then

held by a clamp before being loosened. The brushes were installed on the

attachment of the peeler head and experiments were conducted under the same

conditions as in the previous stages. Peeling at the grooves was effective but only

70% of the convex areas were peeled. This could be attributed to the flexibility of

the both the wire brush and the peeler head.

71

(a) (b)

Fig.5.5.The twisted wire brush in the third stage and its peeling effect

5.2.2 Ball chain tool

In this method, stainless steel ball chains (Figure 5.6.a) were used. It was believed

that the heat produced from the energy released from impact would enable the

pumpkin to be easily peeled by softening the affected areas. Several ball chains

were prepared and clamped between two discs and installed on the peeler head

attachment.

(a) (b)

Fig.5.6.Ball chain and its peeling effect after application

Aluminium clamp

72

The preliminary experiments were conducted at different levels of significant

parameters such as the angular velocity of the peeler head (300-1000 rpm) and

pumpkin (5-20 rpm). The uncovered ranges of values were unlikely to generate

effective results. The values produced from investigated ranges did not generate

satisfactory results. (Figure 5.6.b). Peeling was irregular, and the tool did not follow

the entire surface.

5.2.3 Milling cutters

Rotary milling cutters were also tested. Different shaped of cutters are available in

the market. For peeling purposes, five different shaped of cutters were selected:

cylindrical (in two different diameters), semi-elliptical, spherical, tapered (Figure

5.7.a), and cutters of a cylindrical shape with triangular side sections (Figure 5.7.b)

were the different shapes to be investigated.

(a) (b)

Fig.5.7.Different milling cutter tools investigated (a) and cutter of a cylindrical

shape with triangular side section (b)

The preliminary experiments were carried out. The effective parameters were found

to be the shape of milling cutter, v. speed and p. speed. The results were compared

for different levels of v. speed (5-20 rpm), p. speed (300-1000 rpm) and each shape

of the milling cutter. The uncovered ranges of values were unlikely to generate

effective results. The first four shapes quickly became clogged during the peeling

73

process. Also the removal rate of the peel was very low and the decision was taken

to discontinue experiments with these tools. The cylindrical shaped cutter with the

triangular side section showed significantly better results in preliminary

experiments. High removal rates of peel with no clogging were important outcomes

of these experiments. The tool followed the uneven surface of the pumpkin very

well, and its action was self cleaning. Figures 5.8.a and 5.8b show how the pumpkin

was peeled by the cylindrical shape cutter with triangular side section. Figure 5.8.a

shows the comparison between the effects of peeling by the milling cutter (bottom

side) and the effects of peeling by the twisted wire brush (top side). The results

were encouraging.

(a) (b)

Fig.5.8.The effect of peeling by milling cutter of a cylindrical shape with triangular

side sections

5.2.4 Mower trimming lines

The trimmer line that is used in lawn movers for gardening was used in this

experiment. The one available in black colour with “star” cross-section shapes of 3

mm thickness was chosen. One brush was made from several lines (stands) and

installed between two discs of peeler head attachment. The effectiveness of peeling

at different angular velocities of the peeler head (300-1000 rpm) and the product (5-

20 rpm) as two significant parameters were examined. The uncovered ranges of

values were unlikely to generate effective results. The result was unsatisfactory, and

74

this could be attributed to the light weight and speed of lines and consecutively low

kinetic energy. The available weight of the trimmer line needed to be of a much

higher rpm, and this was impossible to achieve in the current test rig.

5.2.5 Abrasive ropes

Abrasive particles of different abrasion grades and sizes were glued to the end of

syntetic ropes (4 mm diameter) and installed between two discs on the peeler head

attachment (Figure 5.9.a). The angular velocity of the abrasive ropes (p. speed) and

pumpkin (v. speed) were significant parameters. Experiments for different angular

velocities of abrasive ropes (300-1000 rpm) and of pumpkins (5-20 rpm) were

conducted. The uncovered ranges of values were unlikely to generate effective

results. The results were unsatisfactory (Figure 5.9. b). Despite having a high degree

of flexibility they could only scratch the convex areas. The unsatisfactory result

could be attributed to light weight of the tool and the low speed that resulted in a

low energy of impact.

(a) (b)

Fig.5.9. Abrasive rope and its peeling effect on a pumpkin

5.2.6 Abrasive Pads

Abrasive pads that are used for removing paints were tested. Rectangular shaped

abrasive pads were prepared from a standard pad (Grit: 60/60, S/carbide, Size:

75

120 98 13 mm). They were preliminarily tested by hand and the removal rate of

peel proved satisfactory. As the result was promising, they were chosen for a future

experiment. Abrasive tools using of these pads were made and tested and the results

are described in the next chapter.

5.2.7 Abrasive foams

As the results of applying abrasive pads were good, an attempt was made to

improve this method, especially in respect to the shape of the peeler tool. To

maintain flexibility during the peeling process and also test the ease of using of

different shapes of peelers, foam was chosen as the material. Foams of the same

material (HR 30-60 density) but of different shapes were used. (Figure 5.10.a-d).

Different shapes of abrasive foams including horny shape (a), spiral paraboloid (b),

disk with flat face and 60˚ included angle (c), and disk with mirrored edges and 75˚

included angle (d) were tested. Abrasion grade, the angular velocity of abrasive

foam and pumpkin were realised as effective parameters on peeling experiments.

Abrasive particles with different abrasion grades were glued to the foams and the

experiments were conducted at different angular velocities of peeler head (300-1000

rpm) and pumpkin (5-20 rpm). ). The uncovered ranges of values were unlikely to

generate effective results. Shapes (a) and (b) showed unsatisfactory results.

Experiments with shapes (c) and (d) were promising (see Figure 5.10.e).

5.2.8 Rope covered by spiral blade

Spiral blades made from thin stainless steel strips were used. One edge of the blade

was sharpened in a chisel pattern. The blade was twisted around a rope and clamped

in a peeler head (Figure 5.11.a). The preliminary experiments with different levels

of independent variables including angular velocities of ropes (300-1000 rpm) and

product (5-20 rpm) as two significant parameters were conducted. The values out of

those ranges were unlikely to be effective in the results. Results were unsatisfactory

(Figure 5.11.b); blades were easily bent and peeling was uneven.

76

(a) (b)

(c) (d)

(e)

Fig.5.10. Different shapes of abrasive foam and their peeling effect on pumpkin

(a) horny shape; (b) spiral paraboloid; (c) disk with flat face and 60˚ included angle;

and (d) disk with mirrored edges and 75˚ included angle; (e) abrasive foam in use as

peeler tool

77

(a) (b)

Fig.5.11. Rope covered by spiral blade (a), and its peeling effect on pumpkin (b)

5.2.9 Sandpaper belt

In this experiment narrow strips of sandpaper were used (Figure 5.12). During the

preliminary test it was proven that the strip can not follow the irregular shape of the

pumpkin. The strip was easily twisted in places of changing curvature.

(a) (b)

Fig.5.12. Sandpaper belt installed on test rig with and without pumpkin

78

5.2.10 Abrasive plates

Grater plates were shaped and applied to investigate another peeling tool. Grater

plates were cut to form a triangular contour to produce better access to grooves

(Figure 5.13.a). They were made in different lengths from coarse grade of grater to

access the groove floor. The grater plates were fixed on the flaps of the peeler head

and the experiments were conducted at different tilt angles (0-30°). The peeling

efficiency in concave and convex areas was also examined at different angular

velocities of the peeler head (300-1000 rpm) and pumpkin (5-20 rpm). These two

parameters were found to be significant. The values out of those ranges were

unlikely to be effective in the results. The results did show high removal rate of skin

from convex areas but the peeling units were not able to penetrate inside the

grooves. Peeling off the grooves required high peel removal from convex areas

(Figure 5.13.b) and caused high peeling losses. Two circumstances caused

unsatisfactory results: firstly, flexibility of abrasive plates was not sufficient to

allow penetration into the grooves and secondly, the shape and design of the peeler

head was not fully suitable for that purpose. The abrasive plate along the flaps of

the peeler head was rotating in the plane parallel to the surface of the pumpkin.

When one plate was in the position to penetrate inside the groove, other plates

which were in contact with convex areas lifted flaps, reducing the effectiveness of

the peeling.

(a) (b)

Fig.5.13. Grater plate peeling unit and its effect on pumpkin

79

5.2.11 Abrasive-cutter brush

Abrasive-cutter brushes were designed and applied to eliminate the limitation of the

abrasive plate tool. The stainless steel ropes were covered from one end with

twisted strips of coarse grater. At the first trial, the strip of coarse grade was simply

wrapped around the thin rope (2.5 mm diameter) of stainless steel (Figure 5.14.a).

This design was more flexible than the previous one described in section 5.2.10.

The two ropes, 120 mm long, were installed between the two disks of peeler head

attachment (Figure 5.14.b). The attachment did provide the possibility of peeling

the pumpkin in the plane perpendicular to the surface of the product to solve the

fundamental problem (penetration into grooves) of the peeler head. Experiments

were conducted at different angular velocities of abrasive-cutter brush (300-1000

rpm) and pumpkin (5-20 rpm) as two significant parameters. The values out of

those ranges were unlikely to be effective in the results. The results of peeling

especially for higher angular velocities of brushes (1000 rpm) and lower speed of

the vegetable holder (5 rpm) were satisfactory (Figure 5.14.b). The second variant

of design was developed to improve flexibility and productivity of the abrasive-

cutter brush. The strips of coarse grade were twisted around of thicker rope in 4 mm

diameter (Figure 5.14.c). They were installed on the peeler attachment in the same

way as before. Preliminary experiments were conducted under the same conditions

as in previous ones.

The performance of this more flexible brush in the experimental environment was

investigated and good results were obtained (Figure 5.14.d). Peel at affected areas -

either concave or convex - was removed evenly. Since this tool appeared to be one

of the most promising more experiments were planned to be carried out and the

results are described in the next chapter.

80

(a) (b)

(c) (d)

Fig.5.14. Abrasive-cutter brush and its effects on two stages

First design of abrasive-cutter brush (a) and its effect (b), the second design (c) and

its effect (d)

5.2.12 Abrasive bristle products

These products are ready to use and available in the market. They are made from

rubber-like substance with abrasive particles embedded into it. They are used in the

polishing industry and are available from different suppliers in Australia (i.e. 3M

Australia). The supplier advertises the benefits of bristle products such as higher

safety, productivity, versatility, and lower cost compared to normal abrasive wires.

They are available in two different shapes of wheels and disks in different sizes and

abrasion grades. The brown, yellow and green colour radial disks (75 mm) with

abrasion grade of 220, 80, and 50 (Figure 5.15) respectively were applied to

investigate the peeling effects. The abrasion grade of disks, angular velocity of

81

disks and pumpkin were found to be significant parameters. The investigation was

carried out at different angular velocities of disks (300-1000 rpm), pumpkin (5-20

rpm) and different pushing forces (1-5 N). The values out of those ranges were

unlikely to be effective in the results.

(a) Abrasive bristle disk (b) Variety of shapes and sizes

Fig.5.15. Abrasive bristle products

The green disks at high value of speed and low value of angular velocity of

pumpkin gave positive results only if the bristle disks are brought into contact with

the pumpkin with the application of high pushing forces (bigger than 4 N).

Application of high pushing forces (compression) to the tool decreased the

flexibility of peeler and produced an uneven peeled surface.

5.3 Conclusions

The comparison of the results of preliminary experiments proved that the use of

abrasive-cutter brush, abrasive foam, abrasive pads, and milling cutters could be

considered for further investigation. They could perform peeling of an uneven

surface of product equally with higher productivity. Flexibility and the capability of

imparting necessary peeling forces were the main advantages of these tools.

82

5.4 Summary

Preliminary experiments were carried out to identify some peeling tools suitable for

tough-skinned vegetables with an uneven surface such as pumpkin. High peeling

rate with equal flesh removal from convex and concave areas was the main criteria

of comparison. Different shapes of tools were tested. Ease of manufacture of these

tools and possibility of their installation on the test rig were considered. The

selected tools mostly work on the basis of the abrasive peeling method and possess

the required flexibility. Abrasive-cutter brush, abrasive foam, abrasive pads, and

milling cutters were selected from the tested tools for further investigation, which

will be addressed in Chapter 6.

83

Chapter 6

Experimental investigation of mechanical

peeling methods

6.1 Introduction

New approaches to mechanical peeling methods of tough-skinned vegetables were

tested. The four selected peeling tools from preliminary experiments (Chapter 5)

were used for further investigation. The chosen methods were the milling cutter,

abrasive pads, abrasive foams, and abrasive-cutter brush. The significant factors

that could mainly reflect the results of applying each method were selected for

experiments. The effects of either five factors (abrasive foam method) or four

factors (the three other methods) that have significant impact on peeling were

considered for analysis. Factors were investigated at three levels each. As carrying

out full factorial peeling experiments (at least 81 runs each method) is costly and

time consuming, the Taguchi method was used. This fractional factorial design

allowed the running of a minimum number of necessary experiments for

determination of criteria for each peeling method. The criteria involving the

evenness of efficiency (%/min) in concave and convex areas of the product and the

peel losses (%/min) were optimized by using the recommended Taguchi formula.

The optimized results were compared to identify the best peeling method of tough-

skinned vegetables for further investigation.

84

6.2 The criteria of experiments

The following two criteria were used to identify the optimum combination of

independent variables in each method and also comparison of different methods:

• A minimum possible difference between peeling efficiencies in concave and

convex areas

• High efficiency of peeling in concave and convex areas along with low peel

losses

6.2.1 Peel losses

Peel losses in percentage can be calculated by using the weight of product before

and after peeling (Willard, 1971), by applying the following formula:

1001

211 ×

×−

=tW

WWy( (6.1)

where, Ў1 is peel losses in %/min; t is time of peeling in minute; W1 and W2 are

weight of unpeeled and peeled pumpkin respectively; and W2 is not equal either to

zero or to W1.

Pumpkins were weighed before and immediately after peeling by analogue scale

with ± 0.1 gram accuracy.

6.2.2 Peeling efficiency

Peeling efficiency is the percentage peel that is removed from the initial skin per

unit time (min). Three places (120° including angle) at the circular affected area on

the pumpkin for each convex and concave area were considered for the

measurement of peeling efficiency. The peeling efficiency (%/min) after each time

interval (t1 to t4) of peeling was measured at the same place, and the mean value

was calculated for further discussion. An indicator with internal diameter of 15 mm

was used for the measurement of effect. Optical judgement was made. Judgement

85

was made by three observers and the average value was reported. Remaining peel

inside the indicator with notice of the different colours of skin layers, thickness and

area were the main criteria for assessment. The suggested formula by Singh and

Shukla (1995) was used and developed for calculation of peeling efficiency as

follows:

1001

212 ×

×−

=tAAAy( (6.2)

where, Ў2 is peeling efficiency in %/min; t is peeling time in minute; A1 is the

fraction of peel inside the indicator before peeling (assumed 100); and A2 is the

fraction of remaining peel inside the indicator after peeling. In this chapter, the terms

of “concave efficiency” and “convex efficiency” refer to the peeling efficiency at

concave and convex areas respectively.

6.2.3 Estimated responses

The estimation of the mean response in optimum combination of variables was

carried out on the basis of the Taguchi ANOVA by applying the following equation

(Ranjit, 1990):

(6.3)

where:

μ( = estimate of the mean response

T = mean of all experimental data

xnLS = optimal level sum response for the significant factor at the level of

interest.

( ) ( ) ( )TLSTLSTLST xnxx −++−+−+= L(

21μ

86

6.2.4 Data analysis

Analysis of variance (ANOVA) was carried out on the basis of the Taguchi method.

It was used to calculate the percentage contribution of independent variables and

their effect on the response variables. Optimization was also carried out using the

suggested Taguchi method.

6.3 Peeling by using milling cutter

6.3.1 Introduction

Five different shapes of milling cutters were used in the preliminary experiments of

peeling (Chapter 5). A semi-ovate, elongated cylindrical shape in small and large

diameter and a disk shape with triangular contour were investigated (Figure 5.7). It

was revealed that except for the disk shape with triangular contour, other shapes of

milling cutters became clogged very quickly. This could be attributed to

arrangement of the teeth in a perpendicular direction that did not allow the clogged

cutter to self clean. The disk shape with a triangular contour did produce good

results without any clogging in preliminary experiments. The teeth were tilted in

two directions so that they could easily discharge the removed peel. This shape of

milling cutter was considered for further tests.

6.3.2 Material of experiments

The Jap variety of pumpkin (Cucurbitaceous family) from different local farms

around Brisbane (Queensland, Australia) was used for the experiments. The

products were randomly selected from ripe and defect-free and quite similar sized

(18-23 cm diameter) pumpkins. They were kept under conditions of controlled

temperature and humidity for at least 24 hours before testing. The environment

temperature was limited to 20-25 ˚C and 50-55% relative humidity.

87

The milling cutter in a disk shape with triangular contour was used (Figure 6.1).

The large and small diameters of head of the cutter were 25 and 21 mm respectively.

The teeth in the serrated area were tilted to one side and this facilitated discharge of

particles from the cutter during the peeling. The milling cutter was installed on the

peeler head attachment (Figure 5.8).

Fig.6.1. Disk shape milling cutter with triangular contour

The Taguchi method was used for the design of the experiments (DOE). Among

different variables that potentially could affect the results four more significant

independent variables were chosen. The array of L9 was applied for those

independent variables including the angular velocity of the peeler head (p. speed),

the angular velocity of the vegetable holder (v. speed), the location of the peeling

over on the vegetable (location: M for middle; T for top; and B for bottom areas),

and applied force for pushing the milling cutter towards the pumpkin (force).

Independent variables were investigated in three levels each (Table 6.1).

Experiments were carried out in four time intervals (t1 to t4). The measurements

were taken after each time interval (5 min). Peel losses, and peeling efficiency in

two cases including convex and concave areas were calculated and measured

respectively as dependent variables. The average values of the results (t1 to t4) were

calculated and used for discussion.

88

6.3.3 Results and discussion

The experimental results for three dependent variables are shown in Appendix 3.

The contribution of four independent variables involving force, v. speed, p. speed,

and location to three dependent variables while neglecting the interactions is shown

in Figure 6.2. There was no likely interaction among variables to be considered.

Table 6.1. Taguchi experimental design for independent variables and levels

Variable levelsb Exp.no.a

χ1 χ2 χ3 χ4

1 0.66 M 5 1000

2 0.66 T 10 800

3 0.66 B 15 600

4 1 M 10 600

5 1 T 15 1000

6 1 B 5 800

7 0.33 M 15 800

8 0.33 T 5 600

9 0.33 B 10 1000

aExperiments were randomly performed. bχ1=force (N), χ2=location (M: middle; T: top; and B: bottom areas), χ3=v. speed

(rpm), χ4=p. speed (rpm)

As the aim of this study was to investigate the method and not the peeler, the

manufactured test rig was designed to enable peeling on a circumferential band (40

mm average width) around the whole pumpkin and experimental data relates to that

area. Experimental results for three dependent variables involving peel losses

(%/min), peeling efficiency (%/min) at concave and convex areas were obtained

89

and the main effects of independent variables on them are illustrated in Figure 6.3.

In this figure logarithmic scale for y axes was used to enable comparison between

peel loses and efficiencies.

The comparison of the results shows that concave efficiency was considerably

influenced by location and force variables (Figure 6.2). The location also made a

high contribution to the peel losses. While the rate of convex efficiency remained

constant for different areas of pumpkin (Figure 6.3), the concave efficiency at the

top of product was smaller than at other areas. As the concave efficiency at the

bottom of pumpkin was smaller than at the middle as well, the direction of

application of the force on the milling cutter was also important. The line of action

was perpendicular for middle areas while the included angle between that line and

tangential line to the surface of pumpkin for the other areas was smaller than 90˚

depending on the curvature of the whole pumpkin in the vertical direction. Peel

losses showed a similar trend as concave efficiency except at the bottom area.

Although the concave efficiency at the bottom was higher than at the top areas, the

peel losses were smaller.

010203040506070

Force Location v.speed p.speedIndependent variables

Con

trib

utio

n (%

) Peel lossesConcave efficiencyConvex efficiency

Fig.6.2. The contribution of independent variables to responses resulted from using

milling cutter

90

One likely reason of that might be the thinner thickness of skin at the bottom of the

pumpkin that is less exposed to the sun. Force as the second important contributor,

had greater effect on convex than concave efficiency (20%/min). While convex

efficiency remained constant for the last two levels, concave efficiency did show an

increasing trend up to the last level of force which obtained almost the same value

as convex efficiency. Although the contribution of the force to the peel losses was

not considerable, applied force at mid-level (0.66 N) caused lower peel losses. The

contribution of angular velocity of the milling cutter and vegetable on peeling of

concave areas was negligible. p. speed also did show negligible contribution to peel

losses and the same contribution to convex efficiency as v. speed. The effect of

different values of v. speed and p. speed on peeling efficiencies in general,

remained constant when considering a little deviation for mid-levels. In spite of that

constancy, the peel losses were considerably higher for mid level of the p. speed

and the last high level of the v. speed (15 rpm).

6.3.4 Optimization and estimation of the responses

High peeling efficiency in concave and convex areas with low peel losses as well as

a small difference between concave and convex efficiency were the criteria for the

best combination of parameter levels. The performance at optimum combination of

variables was estimated only from the significant factors. Variables were considered

significant when their contribution percentage to the dependent variables was at

least 10%. Therefore, the counting of the v. speed in estimation of the concave

efficiency and p. speed in concave efficiency and peel losses was neglected because

of inconsiderable contribution. Also the effect of the force on calculation of

response estimation of peel losses was neglected for the same reason. High level of

force (1 N) that showed high efficiencies and small difference for concave and

convex areas was chosen for optimization. Although peeling in the middle areas of

the pumpkin gave high peel losses, because of equality of peeling efficiencies, it

was chosen as the criteria of optimization. A lower level of the v. speed (5 rpm)

because of lower peel losses and difference of peeling efficiencies was selected for

optimization.

91

0.1

1

10

100

0.33 0.66 1

Force (N)

Peel

loss

es &

effi

cien

cies

(%/m

in)

Peel losses (%)Concave efficiency (%)Convex efficiency (%)

0.1

1

10

100

M T B

Location (M, T, and B)

Peel

loss

es &

effi

cien

cies

(%/m

in)

Peel losses (%)Concave efficiency (%)Convex efficiency (%)

(a) (b)

0.1

1

10

100

5 10 15

V. speed (rpm)

Peel

loss

es &

effi

cien

cies

(%/m

in)

Peel losses (%)Concave efficiency (%)Convex efficiency (%)

0.1

1

10

100

600 800 1000

P. speed (rpm)

Peel

loss

es &

eff

icie

ncie

s (%

/min

)

Peel losses (%)Concave efficiency (%)Convex efficiency (%)

(c) (d)

Fig.6.3. The effects of independent variables on responses resulted from using

milling cutter

The p. speed in the mid level (800 rpm) led to higher and more equal peeling

efficiencies and was used for calculating optimized results. Estimated mean

responses for concave and convex efficiency were obtained at 27.22 and

25.85%/min respectively at 0.59%/min peel losses per minute.

92

6.4 Peeling by using abrasive pads

6.4.1 Introduction

Preliminary experiments using abrasive pads in reciprocating motion under pressure

contact with the products showed that this method can remove the peel satisfactorily.

The abrasive peeling pads were designed and manufactured for the first time.

Nothing similar has been found in the research literature. The innovative design was

carried out to reflect the contradictory requirements for the new peeling tool. Tool

flexibility and the ability to peel evenly in concave and convex areas simultaneously

with contact under necessary force were considered as the main criteria of design.

6.4.2 Material of experiments

The Jap variety of pumpkin (Cucurbitaceous family) from different local farms

around Brisbane (Queensland, Australia) was used for the experiments. The

products were randomly selected from ripe and defect-free and quite similar sized

(18-23 cm diameter) pumpkins. They were kept under conditions of controlled

temperature and humidity for at least 24 hours before testing. The environment

temperature was maintained in the range of 20-25 ˚C as well as 50-55% humidity.

Abrasive pads were shaped and installed on the flaps of the peeler head.

Rectangular abrasive pads were selected among the pads available in the market

(standard pad, Grit: 60/60, S/carbide, Size: 120×98×13 mm). They were cut in two

different shapes: triangular and rectangular (Figure 6.4.a). Those shapes were

prepared in short and long lengths. Pads were placed in metal holders and glued to

them. To provide flexibility to each abrasive unit, foams in a wedge shape were

used at the peripheral side of the units (Figure 6.4.b). The wedge shape was

considered to give easy access to the grooves of the product during peeling. As

triangular shape units are supposed to penetrate and work inside grooves, they were

positioned higher on the flaps of the peeler head. Then, two different thicknesses of

foams were considered: a thicker one (35 mm) and a thinner one (25 mm) for

triangular and rectangular units respectively.

93

The peeler head was equipped with six flaps. On each flap, two different shapes of

abrasive pad units were installed. The pads were installed on the peeler head at two

different circles (Figure 6.4.c). The short units were placed in the inner circle due to

space limitation. Units were installed on flaps located on flexible spring suspension

to enable following of the product shape. The peeler head was installed in the test

rig offset (90 mm) to the centre of pumpkin. Just one side of the peeler head was in

contact with the pumpkin during peeling to increase efficiency.

(a) Abrasive units in different shapes

(b) Foams in wage shape under each

abrasive unit

(e) Assembled peeler head

Fig.6.4. Abrasive peeler pads and accessories

Experiments were planned on the basis of the Taguchi method. L9 array was used.

The experimental design with uncoded and coded levels is shown in Table 6.2. It

94

enabled experiments for four factors in three levels each. Factors were the angular

velocity of the peeler head (p. speed), angular velocity of the vegetable holder (v.

speed), angle of the flaps (angle) and overlap between radius lines of abrasive unit

and pumpkin (overlap). Experiments were carried out in four time intervals (t1 to t4)

at 5 minutes increments. The dependent variables were measured after each five

minutes and the mean in percentage per unit time (minute) was used for assessment.

Table 6.2. Taguchi experimental design for independent variables and levels

Variable levelsb Exp.no.a

χ1 χ2 χ3 χ4

1 0 140 10 21.5

2 0 200 20 26.5

3 0 160 5 16.5

4 5 140 20 16.5

5 5 200 5 21.5

6 5 160 10 26.5

7 10 140 5 26.5

8 10 200 10 16.5

9 10 160 20 21.5

aExperiments were randomly performed. bχ1=angle (degree), χ2=peeler speed (rpm), χ3=vegetable speed (rpm), χ4=overlap

(mm)

6.4.3 Results and discussion

The experimental results for three dependent variables are shown in Appendix 3.

The contribution of four independent variables involving overlaps, v. speed, p.

speed, and angle of flaps on three dependent variables while neglecting the

interactions is shown in Figure 6.5. There was no likely interaction among variables

95

to be considered. As the aim of this study was to investigate the method and not the

peeler, the available test rig was modified to enable peeling on a circumferential

band (40 mm average width) around the whole pumpkin and experimental data

relate to that area. Experimental results for three dependent variables involving peel

losses (%/min), and peeling efficiency (%/min) at concave and convex areas were

measured and the main effects of independent variables on them are illustrated in

Figure 6.6. Very close values of removal rate of peeling in convex and concave

areas could be seen as an important point. As the difference was not significant,

equal peeling in different areas can easily be achieved by improved design. Some

indication of foam clogging was noticed during experiments. Although clogging of

some foam was observed during experiments because of the fine size of particles

(Grade: 60), there were no remaining separated abrasive particles within the flesh

after the experiments. The significant difference of contribution (%) among

independent variables was noted in concave efficiency. While the overlap made a

considerable contribution (78 %), v. speed and angles with 2 and 4% were not

effective contributors to concave efficiency.

0102030405060708090

angle p.speed v.speed overlapIndependent variables

Con

trib

utio

n (%

) Peel lossesConcave efficiencyConvex efficiency

Fig.6.5. The contribution of independent variables to responses resulted from using

abrasive pads

Significantly higher contribution of overlap to the concave efficiency compared

with the two other independent variables revealed that different overlap levels can

96

significantly change the depth of penetration of abrasive pads through the grooves

in concave areas. Figure 6.6.a shows that increasing the overlap can considerably

increase the concave efficiency.

0.01

0.1

1

10

16.5 21.5 26.5

Overlap (mm)

P.lo

sses

& e

ffici

enci

es (%

/min

)

P.lossesConcave efficiencyConvex efficiency

0.01

0.1

1

10

5 10 20

V.speed (rpm)

P.lo

sses

& e

ffici

enci

es (%

/min

)

P.lossesConcave efficiencyConvex efficiency

(a) (b)

0.01

0.1

1

10

140 160 200

P.speed (rpm)

P.lo

sses

& e

ficie

ncie

s (%

/min

)

P.lossesConcave efficiencyConvex efficiency

0.01

0.1

1

10

100

1000

0 5 10

Angle (degree)

P.lo

sses

& e

ffici

enci

es (%

/min

)

P.lossesConcave efficiencyConvex efficiency

(c) (d)

Fig.6.6. The effects of independent variables on responses resulted from using

abrasive pads

The concave efficiency also is decreasing in response to higher angular velocities of

pumpkin (Figure 6.6.b) although its contribution was the lowest. A possible reason

97

for the reduction could be a limited engagement time of abrasive pads with grooves

for higher velocities of vegetable.

The sinusoidal function of efficiency and peel losses (%/min) for different angles of

the peeler flaps specified 0 degree as the best angle to provide the best access to the

inside of grooves. The p. speed as the second important contributor to the concave

efficiency caused reduction of peeling efficiency in concave areas at 160 rpm

velocity but it showed higher removal at 140 compared to 200 rpm. Similar to

concave efficiency, angle also made a low contribution to the convex efficiency

with similar effect. The increasing of pumpkin velocity (p. speed) led to decreasing

convex efficiency (Figure 6.6.b) at a similar rate compared to concave efficiency

but made much higher contribution. It was revealed that higher v. speed caused a

decrease of imposing time of grooves and lower contact with abrasive pads while it

led to a higher rate of contact for convex areas.

The p. speed showed the largest contribution (38%) to the convex efficiency

compared to the other variables. While the increase of the p. speed was expected to

increase the convex efficiency because of increasing the number of contacts, the

decrease was observed at 160 rpm of p. speed. Convex efficiency (%/min) did not

change for the first two levels of overlap but it increased for the higher level of

overlap (26.5 mm). For the highest amounts of overlap, the efficiency of peeling in

convex and concave areas was approaching the same value. This means that higher

overlap could provide the same access to the grooves as to the other areas of the

pumpkin for abrasive pads. Generally the independent variables except the angle

and v. speed did show similar effects on peel losses as peeling efficiency especially

in concave areas. While increasing the overlap led to the higher level of peel losses,

the mid-level of the p. speed did result in lower losses of peel. Angle and v. speed,

despite low contribution, significantly affected peel losses at higher levels

(Figures.6.6.b and d). Increasing the angle may decrease the covered area of the

pumpkin for peeling and then decrease the peel losses.

6.4.4 Optimization and estimation of the responses

98

High peeling efficiency in concave and convex areas with low peel losses as well as

minimum difference between concave and convex efficiency were the criteria for

the best combination of variable levels. The performance at optimum condition was

estimated only from the significant factors related to their contribution percentage

to the dependent variables. Variables were considered significant when their

contribution percentage to the dependent variables was at least 10%. Then, the

effect of v. speed and angle in estimation of concave efficiency was neglected

because of low contribution. Angles of 0 and 5 degrees did show higher efficiency

and lower peel losses. The difference between concave and convex efficiencies was

smaller at 0 degree, which could be considered as the optimum value of angle. The

overlap of 26.5 mm did also result in higher efficiencies with smaller difference.

The peeling productivity at 140 and 200 rpm of p. speed was higher than the same

parameter at 160 rpm but because of the small difference between efficiencies at

140 rpm, it was chosen as the best level of peeler head speed. The best level of v.

speed was chosen as 10 rpm because of higher peeling productivity and lower

difference between efficiencies in concave and convex areas compared to other

levels. Estimated mean responses for concave and convex efficiency were obtained

at 5.31 and 6.24%/min respectively at 0.12%/min peel losses per minute.

6.5 Peeling by using abrasive foams

6.5.1 Introduction

The attempt to increase the flexibility of the abrasive tool by using abrasive pads

was successful. This method was developed using an improved tool. Abrasive foam

as a new approach to the development of the abrasive peeling tool was different to

abrasive pads in shape. The foam works as a unit like the milling cutter and

removes the peel by abrasive particles which cover the active surface of the foam.

In addition to the shape, different sizes of abrasive particles (abrasion grades) were

investigated.

6.5.2 Material of experiments

99

The Jap variety of pumpkin (Cucurbitaceous family) from different local farms

around Brisbane (Queensland, Australia) was used for the experiments. The

products were randomly selected from ripe, defect-free and similar sized (18-23 cm

diameter) pumpkins. They were kept under conditions of controlled temperature

and humidity for at least 24 hours before testing. The surrounding environment

temperature was maintained between 20-25 ˚C as well as 50-55% relative humidity.

The shaped foam disk installed on the peeler head of the test rig was used for

experiments (Figure 6.7.a). Abrasive particles in three different abrasion grades

(Grades of 24, 46, and 60 representing coarse, medium, and fine abrasive particles

respectively) were glued (using grit glue) to the shaped foam disks.

(a) Abrasive peeler disk works

perpendicular to pumpkin surface

(b) Abrasive disk, shape A

(c) Abrasive disk, shape B (d) Abrasive disk , shape C

Fig.6.7 Abrasive foam and accessories

100

Foam disks were shaped in three different shapes of sharpened edge disks marked

as A, B, and C. The foam disks had the same material (HR 30-60 density) and size

(50 mm thickness and 165 mm external diameter sharpened at 75˚). Shape A

(Figure 6.7.b) was continuous without any slots. Shape B (Figure 6.7.c) had six

deep and wide slots (8 mm wide and 20 mm deep) in the outer circumference of the

sharpened edge foam with 60˚ including angle.

The slots were perpendicular to the outer surface of the foam. Shape C (Figure

6.7.d) had narrow and shallow slots (4 mm wide and 5 mm deep). The slots were

made at 45˚ to the radius in the direction of rotation.

Experiments were planned on the basis of the Taguchi method. L27 array was

applied. The first five columns of the L27 table were used for five independent

variables in three levels each. The experimental designs with uncoded and coded

levels are given in Table 6.3.

Factors were the shape (A, B, and C), abrasion grade (Grade: 24, 46, and 60),

angular velocity of the pumpkin (v. speed: 5, 10, and 20 rpm), angular velocity of

the peeler head (p. speed: 600, 800, and 1000 rpm), and force (1, 1.65, and 2.30 N).

Experiments were carried out in four time intervals (t1 to t4) each 1 minute. The

dependent variables were measured after each minute and the mean in percentage

per unit time (minute) was used for assessment.

6.5.3 Results and discussion

The experimental results for three dependent variables are shown in Appendix 3.

The contribution of five independent variables involving shape, abrasion grade, v.

speed, p. speed, and force to three dependent variables while ignoring the

interactions is shown in Figure 6.8. There was no likely interaction among variables

to be considered because in this stage of investigation only the main effects of

independent variables were important.

101

Table6.3. Taguchi experimental design for independent variables and levels

variable levelsb Exp. No.a

χ1 χ2 χ3 χ4 χ 5

1 A 60 5 1000 1.65

2 A 60 5 1000 2.30

3 A 60 5 1000 1.00

4 A 46 10 800 1.65

5 A 46 10 800 2.30

6 A 46 10 800 1.00

7 A 24 15 600 1.65

8 A 24 15 600 2.30

9 A 24 15 600 1.00

10 B 60 10 600 1.65

11 B 60 10 600 2.30

12 B 60 10 600 1.00

13 B 46 15 1000 1.65

14 B 46 15 1000 2.30

15 B 46 15 1000 1.00

16 B 24 5 800 1.65

17 B 24 5 800 2.30

18 B 24 5 800 1.00

19 C 60 15 800 1.65

20 C 60 15 800 2.30

21 C 60 15 800 1.00

22 C 46 5 600 1.65

23 C 46 5 600 2.30

24 C 46 5 600 1.00

25 C 24 10 1000 1.65

26 C 24 10 1000 2.30

27 C 24 10 1000 1.00

aExperiments were randomly performed. bχ1=shape, χ2=abrasion grade, χ3=v. speed (rpm), χ4=p. speed (rpm), χ5=force (N)

As the aim of this study was to investigate the method and not the peeler, the

available test rig facilitated the peeling trial on a circumferential band (28 mm

102

average width) around the whole pumpkin and experimental data relates to that area.

Experimental results for three dependent variables involving peel losses (%/min),

peeling efficiency (%/min) in concave and convex areas were measured and the

effects of independent variables on them are illustrated in Figure 6.9.

05

10152025303540

Shape Grade V.speed P.speed ForceIndependent variables

Con

trib

utio

n (%

) peel lossesConcave efficiencyConvex efficiency

Fig.6.8. The contribution of independent variables to responses resulted from using

abrasive foams

There was no significant difference between the removal rate of peeling in convex

and concave areas. Despite concerns about embedment of abrasive particles into the

flesh of the peeled pumpkin no sign of that was observed. The fine grade (Grade:

60) of abrasive foam did show some clogging. This was also reported in previous

experiments (peeling using abrasive pads). As expected, abrasion grade made a

higher contribution to the all responses compared to the other independent variables.

The convex and concave efficiencies, and peel losses (%/min) respectively were

more affected by the grade of abrasive particles. The coarse grade (Grade: 24) did

show significantly higher skin removal from all areas of product while the two other

grades had almost identical removal rates (Figure 6.9.a). The peel removal was even

in convex and concave areas for different grades of particles except the mid-grade.

103

05

1015

202530

24 46 60Grade (abrasion)

Peel

loss

es &

effi

cien

cies

(%

/min

)Peel lossesConcave efficiencyConvex efficiency

0

5

10

15

20

25

A B CShape (foam)

Peel

loss

es &

effi

cien

cies

(%

/min

)

P.lossesConcave efficiencyConvex efficiency

(a) (b)

0

5

10

15

20

25

5 10 15V.speed (rpm)

Peel

loss

es &

effi

cien

cies

(%

/min

)

Peel lossesConcave efficiencyConvex efficiency

0

5

10

15

20

25

600 800 1000P.speed (rpm)

Peel

loss

es &

effi

cien

cies

(%

/min

)Peel lossesConcave efficiencyConvex efficiency

(c) (d)

0

5

10

15

20

25

1 1.65 2.3Force (N)

Peel

loss

es &

effi

cien

cies

(%

/min

)

Peel lossesConcave efficiencyConvex efficiency

(e)

Fig.6.9. The effects of independent variables on responses resulted from using

abrasive foams

104

The even peeling of different areas of pumpkin also was observed for the shape

variable (Figure 6.9.b). The shape of the abrasive unit had the same order of

contribution as abrasion grade. The skin removal from concave and convex areas

was very close for shape A although it was expected to be much closer for other

shapes. The existence of slots in shapes B and C was expected to increase the

continuous contact time between peeler disk and product and finally higher and

more even peeling of different areas. But shape was not a significant contributor to

the peel losses (%/min) and v. speed did show higher contribution to that. The mid-

level of v. speed (10 rpm) caused higher losses of peel (Figure 6.9.c) and efficiency

especially in convex areas, decreasing with an increase of v. speed. The better peel

removal was observed for the first two levels of v. speed. The development of

efficiency for higher levels of p. speed was in the opposite direction of v. speed

(Figure 6.9.d). Peeling at convex areas for different levels of p. speed, except mid-

level, was higher than at concave areas although the difference was small. Increase

in peel losses was the same as efficiency with increasing p. speed although the

contribution of p. speed to peel losses was lower compared to efficiency. The higher

contribution of force to concave efficiency revealed that applying an appropriate

amount of force can lead to even peeling at different areas of product. High level of

force caused higher peel removal through grooves at concave areas (Figure 6.9.e).

Mid-level of force (1.65 N) showed higher efficiency of even peeling in different

areas.

6.5.4 Optimization and estimation of the responses

High peeling efficiency in concave and convex areas with low peel losses as well as

a small difference between concave and convex efficiency were the criteria for the

best combination of variables. The performance at optimum condition was

estimated only from the significant factors which had high percentage of

contribution to the response variables. Variables were considered significant when

their contribution percentage to the dependent variables was at least 5%. This limit

was chosen because of the highest contribution of variables (35% for grade to

concave efficiency). Therefore, the effect of force, p. speed, and shape in estimation

of peel losses and also the effect of v. speed in estimation of efficiencies was

105

neglected because of insignificant contribution. The abrasion grade of 24 did show

significantly higher efficiency of even peeling and was selected as the best abrasion

grade. The shape A also caused higher peeling efficiency compared to the other

levels. As the small difference between efficiency of peeling at concave and convex

areas was observed at all levels, shape A was chosen as the best shape. The lower

level of v. speed (5 rpm) led to the higher efficiency and lower amount of peel

losses. This level was selected as the best level of v. speed because a small

difference between efficiencies was achieved.

The difference between concave and convex efficiencies was almost similar for all

levels of p. speed and because of higher efficiency of peeling at 1000 rpm it was

chosen for the calculation of optimized results. Mid-level of the force variable (1.65

N) did show higher peeling efficiency with lower difference between concave and

convex efficiency. It was selected as the best level compared to the upper level with

lower efficiency and higher peel losses.

Estimated mean responses for concave and convex efficiency were obtained at

30.96 and 31.66%/min respectively at 0.97%/min peel losses per minute. The

obtained results compared to the results of abrasive pads revealed higher

productivity of this device per unit time. Relative comparison of the results between

the two works also proved that average efficiency has increased 5.42 times; this

increase for peel losses was 8.08 times. The difference possibly shows either the

higher peeling losses of using abrasive foams compared to abrasive pads, or higher

density of inner layers of skin.

6.6 Peeling by using abrasive-cutter brush

6.6.1 Introduction

The mechanical peeling method is done mostly by using either abrasive tools or

knife and blades. Combining these two tools led to the development of another new

innovative tool named the abrasive-cutter brush. The new tool can utilise the

benefits of the two mentioned peeling tools. The tool is basically twisted stainless

106

steel wires with grater strips wrapped around. The flexibility of wires could provide

easy access of the grater protrusions to different areas of the product. Each

protrusion acted as a small cutting unit cut and removed the peel pieces. The cutting

action caused effective peeling with higher production compared with the other

investigated tools.

6.6.2 Material of experiments

The Jap variety of pumpkin (Cucurbitaceous family) from different local farms

around Brisbane (Queensland, Australia) was used for the experiments. The

products were randomly selected from similar sized (18-23 cm diameter) ripe and

defect-free pumpkins. They were kept under controlled temperature and humidity

conditions for at least 24 hours before testing. The environment temperature was

maintained in the range of 20-25 ˚C as well as 50-55% relative humidity.

The attachment of peeler head was used for conducting the experiments. Two

abrasive-cutter brushes (Figure 6.10.a) were installed between solid discs of the

peeler head attachment for each trial. They could be fine, coarse, or a combination

of the two depending on the status of the planned experiment.

Each abrasive-cutter brush was made from stainless steel wire covered by a twisted

strip (Figure 6.10.b) of grater of different grades (coarse or fine). The stainless steel

wires were already double twisted wires of the same materials. The strips of the

grater were cut from common kitchen graters available in the market. The total

length of each brush was 165 mm and the weight 14.75 grams. The materials and

methods used to fabricate the brush provided high flexibility of the brush.

107

(a) (b)

(c) (d)

(e) (f)

Fig. 6.10.Abrasive-cutter brush

a. abrasive-cutter brush; b. strip; c. affected peeled area (after 5 minutes);

d. affected peeled area (after 2 minutes); e and f. other views after peeling

(5 minutes)

Experiments were planned on the basis of the Taguchi method. L9 array was used.

The experimental design with uncoded and coded levels is shown in Table 6.4. It

108

enabled experiments for four factors in three levels each. Factors were the angular

velocity of the abrasive-cutter brush (p. speed), angular velocity of the vegetable

holder (v. speed), vertical position of the brush (position) and the coarseness of the

brush (coarseness: C for coarse; F for fine; and Com. for combined types of brush).

Experiments were carried out in four time intervals (t1 to t4) each 1 minute. The

dependent variables were measured after each time interval and the mean in

percentage per unit time (minute) was used for assessment.

Table 6.4. Taguchi experimental design for independent variables and levels

Variable levelsb Exp.no.a

C 5 700 -20

1 C 10 850 20

2 C 15 550 0

3 F 5 850 0

4 F 10 550 -20

5 F 15 700 20

6 Com. 5 550 20

7 Com. 10 700 0

8 Com. 15 850 -20

9 C 5 700 -20

aExperiments were randomly performed. bχ1=coarseness (course, fine, combined), χ2=vegetable speed (rpm), χ3=brush speed

(rpm), χ4=vertical position (mm)

6.6.3 Results and discussion

The experimental results for the three dependent variables are shown in Appendix 3.

The contribution of four independent variables involving v. speed, p. speed,

coarseness, and vertical position to three dependent variables, while ignoring the

109

interactions, is shown in Figure 6.11. There was no likely interaction among

variables to be considered. As the aim of this study was to investigate the method

and not the peeler, the available test rig facilitated the peeling trial on a

circumferential band (40.66 mm average width) around the whole pumpkin and

experimental data relates to that area. Experimental results for three dependent

variables involving peel losses (%/min), and peeling efficiency (%/min) in concave

and convex areas were measured and the main effects of independent variables on

them are illustrated in Figure 6.12.

0

10

20

30

40

50

60

V. speed Roughness P. speed Position

Independent variables

Con

trib

utio

n (%

)

Peel lossesConcave efficiencyConvex efficiency

Fig.6.11. The contribution of independent variables to responses resulted from

using the abrasive-cutter brush

There was no significant difference between removal rate of peeling in convex and

concave areas except in the third level of position (20 mm). The higher contribution

of coarseness to concave efficiency can be seen as the first important point in Figure

6.11. This independent variable also had higher percentage of contribution to peel

losses and convex efficiency compared with the other independent variables.

110

1

10

100

5 10 15V. speed (rpm)

Peel

loss

es a

nd e

ffici

enci

es

(%/m

in)

Peel lossesConcave efficiencyConvex efficiency

0.1

1

10

100

F C M

Roughness

Peel

loss

es a

nd e

ffici

enci

es

(%/m

in)

P.lossesConcave efficiencyConvex efficiency

(a) (b)

0.1

1

10

100

550 700 850

P. speed (rpm)

Peel

loss

es &

effi

cien

cies

(%

/min

)

Peel lossesConcave efficiencyConvex efficiency

1

10

100

-20 0 20Position (mm)

Peel

loss

es &

effi

cien

cies

(%

/min

)

Peel lossesConcave efficiencyConvex efficiency

(c) (d)

Fig.6.12. The effects of independent variables on responses resulted from using

abrasive-cutter brush

The contribution of coarseness to the efficiencies at concave and convex areas was

almost similar. The fine type of abrasive-cutter brush had higher impact on peel

losses and efficiencies among the four investigated variables (Figure 6.12.b). The

combined and coarse abrasive-cutter brushes were located at the next orders

respectively in the statistical comparison. p. speed was the second higher

contributor after coarseness (Figure 6.11). p. speed had lower contribution to

111

response variables than the other two independent variables. This variable, as seen

in Figure 6.12.c, highly affected peel losses and efficiencies at the third level (850

rpm). It did show medium effect on response variables with lower peel losses at the

first level (550 rpm). Position and v. speed showed insignificant and similar

contribution to all response variables. The position’s contribution to convex

efficiency was less than 5% and could be neglected. It means the peel removal in

concave areas can be controllable in micro and micro levels by coarseness and

position parameters respectively. Both v. speed and position variables affected more

peel losses at the mid-level.

6.6.4 Optimization and estimation of the responses

High peeling efficiency in concave and convex areas with low peel losses as well as

small difference between concave and convex efficiency were the criteria for the

best combination of variables. The performance at optimum condition was

estimated only from the significant factors which had high percentage of

contribution to the response variables. Variables were considered significant when

their contribution percentage to the dependent variables was at least 10%. Then the

position variable was not considered in the calculation of optimized result of

efficiency in convex areas because of insignificant contribution in that scenario.

The fine type of abrasive-cutter brush did show significant even peeling in different

areas of the pumpkin. High productivity of peel removal with low difference

between concave and convex areas caused its selection as the optimized level of

coarseness. The first and the third level of v. speed did show similar productivity

with lower peel losses. Although the peel losses were higher for 5 rpm it was

chosen as the optimized level for v. speed because of the lower difference between

efficiencies in different areas of the pumpkin. Except for the third level of p. speed

that caused high peel losses, the other two levels had close efficiencies. The first

level of p. speed (550 rpm) was chosen as the best level because of significantly

lower peel losses. Analysis of the results for the vertical position of the abrasive-

cutter brush showed significant difference at the third level (20 mm) and higher

peels losses at the mid-level (0 mm). The first level of position (-20 mm) was

112

recognised as the best level for optimization because of the low difference of

efficiencies and lower peel losses. Estimated mean responses for concave and

convex efficiency were obtained as 68.74 and 68.75%/min respectively at 1.1%/min

peel losses per minute.

6.7 The comparison of the four innovative peeling

methods

The abrasive-cutter brush can be identified as the best peeling tool among the four

investigated peeling methods of tough-skinned vegetables, with the Jap variety of

pumpkin as a case study. Comparison of the optimized results of efficiencies in

concave and convex areas showed that the abrasive-cutter brush has significantly

higher peeling efficiencies (68.74-68.75%/min). The lower efficiencies with

significant difference belonged to abrasive pads (5.31- 6.24 %/min). The peeling

efficiencies of the other two methods including abrasive foams (30.96-

31.66%/min) and milling cutter (27.22-25.85%/min) were close and located in-

between. In the case of efficiency difference between concave and convex areas,

generally all four methods showed good results.

The results revealed small difference for the abrasive-cutter brush (0.01) and higher

difference for the milling cutter (1.37). Lower difference of efficiencies can be

considered as the main sign of lower peeling losses and therefore what peel losses

(%/min) show could be considered as another peeling production parameter. The

lowest and highest peel losses (%/min) belonged to the abrasive pads (0.12%/min)

and abrasive cutter brush (1.1%/min) respectively. Comparison of the proportion of

peel losses and efficiencies for different tools showed peel losses of the abrasive-

cutter brush could be considered as wanted peeling losses that are expected from

“ideal” peeling. This proportion for the other three methods showed higher peel

losses in proportion to obtained efficiencies. For example, abrasive foam with

0.97 %/min of peel losses which is very close to the abrasive-cutter brush

(1.1%/min) could only produce efficiencies (30.96- 31.66%/min) less than half of

abrasive-cutter brush (68.74-68.75%/min).

113

6.8 Potential industrial application of abrasive-cutter

brush

In addition to meeting the conditions of the “ideal” peeling method, the abrasive-

cutter brush has high potential for industrial application. Peeling machines for

tough- skinned vegetables can be designed and manufactured on the basis of this

method. A peeler can be equipped with one or several peeling units. Each unit

would be able to continuously peel the product. At least six peeler heads should be

installed at different positions to carry out peeling along the six circumferential

bands. The product could be moved on a linear conveyor or a rotary conveyor and

spin around its axis to enable peeling. The linear speed of product, angular velocity

of product and peeler heads should be adjustable. Holding the product during

peeling can be planned either by with using the method introduced in this research

or using pneumatic systems. Using blades to hold the product makes some damage

to the product at the top and bottom centres but it is not a matter of concern

especially if peeling is followed with dicing. The products after the peeling stage

should be cut for further processing (i.e. removing the seeds and cutting into the

small pieces). The product could be also clamped using small disks supported by

pneumatic actuators.

The peeler ability can be improved using available technologies. It is obvious that

the abrasive-cutter brush itself needs to be improved for industrial application. In

addition, the peeling process can be controlled using image processing to identify

when to stop peeling and thereby minimise peeling losses.

6.9 Conclusions

Four selected innovative peeling methods including abrasive pads, abrasive foams,

milling cutter and abrasive-cutter brush were investigated and compared.

Significant independent variables for each method and peeling tool were

investigated. The independent variables of v. speed and p. speed were chosen as

significant parameters for each peeling trial method. Results generally showed that,

in spite of the significant contribution by the v. speed to response variables, its

114

contribution was lower compared to the other independent variables for each

experiment. The v. speed showed greater contribution to the peel losses than

efficiencies for all methods. Its highest contribution was to the peel losses of the

milling cutter (29.89%/min). The best level of v. speed for all methods was found to

be 5 rpm which produces optimum results for defined criteria. It was impossible to

specify the best level of p. speed because the range of variation of the optimized p.

speed for different methods was broad. While the optimized level of p. speed for the

abrasive foam (1000 rpm) and the milling cutter (800 rpm) were close and higher

compared with other levels of the same variety, the optimized p. speed of the

abrasive-cutter brush (550 rpm) and abrasive pads (140 rpm) were at a lower level

compared with other levels of the same variety for each method. It is clear that the

main reason for the variation is because of the technique used for each method and

determination of more accurate optimized level of p. speed needs further

investigation with more levels of p. speed.

Other effective independent variables for all four methods were overlap and the

pushing force of the peeling tool on the product. Higher overlap significantly

increased the efficiencies and peel losses. Optimization of the results showed high

overlap of the abrasive pads (26.5 mm) and the abrasive-cutter brush (-20 mm

position) leads to the best results. The overlap indirectly affected the milling cutting

as maximum pushing force (1N) and led to optimized results and also abrasive

foams at the middle level of force (1.65 N). Although higher level of force 2.3 N

caused higher peel losses (%/min) for abrasive foam it was not chosen as the best

level because of larger difference of efficiencies and insignificant lower efficiencies

compared to the middle level of force.

The comparison of results at optimum conditions revealed that the abrasive-cutter

brush can be selected as the best peeling method for tough-skinned vegetables.

Higher and almost equal peeling efficiencies at concave (68.74%/min) and convex

(68.75%/min) areas along with accepted peel losses (1.1%/min) compared to the

other three methods were the main reasons. This method also has high potential for

industrial application.

115

6.9 Summary

Four peeling tools from preliminary experiments (reported in Chapter 5) were

selected and tested. The chosen tools including the milling cutter, abrasive pads,

abrasive foam, and abrasive-cutter brush were compared in the peeling of a Jap

variety pumpkin by using the Taguchi method. The criteria of comparison were

high efficiency with low difference of peeling efficiency in concave and convex

areas and low peel losses. The results showed that the abrasive-cutter brush has

significantly higher productivity at lower peel losses. Estimated mean responses for

concave and convex efficiency were obtained at 68.74 and 68.75 %/min

respectively, at 1.1 %/min peel losses per minute by using the abrasive-cutter brush.

Also the results showed that v. speed at 5 rpm for each method including the

abrasive-cutter brush method can provide the best result. The comparison of the

results also showed that overlap (for abrasive pads and abrasive-cutter brush) or

pushing force (for abrasive foam and milling cutter) to the pumpkin leads to closer

results for those criteria.

The selected innovative abrasive-cutter brush has high potential for industrial

application. Meeting all conditions of the “ideal” peeling method of fruits and

vegetables makes this method the most suitable for design and development of

industrial peeling machinery. For this purpose more information about significant

factors and their influences is needed and this can be obtained with full factorial

experiments which will be explained in Chapter 7.

116

Chapter 7

Abrasive-cutter brush, full factorial

experiments, and ANOVA

7.1 Introduction

The abrasive-cutter brush was selected as the best method after conducting a series

of designed experiments by preliminary chosen mechanical peeling tools on the Jap

variety of pumpkin (Chapter 6). The analysis of the results showed almost uniform

peeling in convex and concave areas along with higher values of peeling

efficiencies for this method compared with other methods including abrasive pads,

abrasive foam, and milling cutter. Statistical analysis (ANOVA) suggested the

optimum results can be obtained at 5 rpm angular velocity of pumpkin, 550 rpm of

angular velocity of brushes, -20 mm overlap between brushes and pumpkin, and

with application of fine type of abrasive-cutter brush. Further experiments are

required to investigate the influence of different parameters related to the product

and the abrasive-cutter brush on the peeling rate. Two full factorial design tests,

each 64 runs, were conducted on two different varieties of pumpkin including

Jarrahdale and Jap. The abrasive-cutter brushes were applied in four different

coarseness levels - very coarse, coarse, mild, and fine. The peeling rate (g/min) as a

dependent variable was assessed as it was affected by other independent variables

including angular velocity of brushes (4 levels), and location of peeling area on the

product (4 locations). The selection criteria for parameters and their levels were the

importance and commercial applicability of them. This chapter outlines the

conducted experiments and the results of ANOVA.

117

7.2 Material of experiments

Jap and Jarrahdale as two different varieties of pumpkin were used for experiments.

Defect-free and mature products in similar sizes (18-23 cm diameter) were chosen

from the farms around Brisbane, Queensland. The pumpkins were kept in a

controlled environment at least 24 hours before the test. The storage temperature

and relative humidity were controlled in the range of 20-25 ˚C and 50-55%

respectively.

The test rig with attachment, as described in Chapter 4, was used. Abrasive-cutter

brushes were manufactured and installed on the peeler head attachment by using the

same procedure as described in Chapter 6. In addition to fine and coarse brushes,

two other brushes labelled “mild” and “very coarse” were made and applied (Figure

7.1). The mild and very coarse brushes were fabricated by opening further the

protrusions of the strip of the fine and coarse grater respectively. This change

increased the teeth angle by about 20° for each type of strip. It was increased from

about 70° to 90° for both types of strips. This change caused a bigger size of

protrusions and upright standing of the teeth compared with the initial shape (fine or

coarse). The toughness of the four different strips of grater was measured using a

force-deformation test, described in Chapter 3. Each protrusion of those strips was

located under the compression force of the spherical end indentor till it reached

rupture point (loosening the resistance). The test was repeated 15 times for each

type of coarseness. The calculated toughness of the strips was 90, 160, 110, and 170

N. mm for fine, mild, coarse, and very coarse respectively.

Full factorial design was used for the design of experiments (DOE). The total

number of runs was 128 which were divided equally for the two varieties of

products, Jap and Jarrahdale. High number of runs on two different vegetables and

long time of each experiment (half an hour) were reasons to ignore replications. The

experiments were conducted on three independent variables including coarseness of

abrasive-cutter brush (coarseness: coarse, very coarse, fine, and mild), the angular

velocity of the peeler head (p. speed: 400, 550, 700, and 850 rpm), and the peeling

118

location on the product (location: top, top-side, bottom-side, bottom) as shown in

Figure 7.2.

Fig7.1. The strips with different type of coarseness used for fabrication of the

abrasive-cutter brush (from left: very coarse, coarse, mild, fine)

Top

Top-side

Bottom-side

Bottom

Fig.7.2. Different parts of product as levels of location variable

The tests were carried out on four levels of each independent variable. Two brushes

were installed on the peeler head attachment for each run of experiment. The

119

angular velocity of the vegetable holder (or product) was not considered as a

variable because the results of previous experiments (Chapter 6) showed that lower

angular velocity of the product (5 rpm) leads to the optimum results. Therefore, the

angular velocity of the pumpkin was kept fixed at 5 rpm. Also the overlap of the

abrasive-cutter brush and product was considered fixed and equal to 10 mm for all

experiments. This overlap was an independent variable in the previous experiment

(Chapter 6) and results showed that up to an overlap of up to 20 mm can lead to

optimum peel losses. A new overlap distance was chosen as 10 mm to facilitate

adjustment of the peeler head for different locations of product. The running time of

the experiments was 5 minutes and this was long enough to cover the necessary

peeling time. Experiments were carried out continuously in each run until enough

effective peeling (preferably 100%) could be seen. In some combinations complete

peeling (100%) was achieved within less than the determined time (5 min). As

continuation of peeling into flesh caused reduction of accuracy of results, the run

was discontinued after completed skin removal and actual elapsed time was

considered in calculation of the mean of peeling rate. It was measured by a

analogue scale (±0.1 gr accuracy) and weighting of the pumpkin before and after

testing. Mean value per unit time (minute) was calculated for further assessment.

7.3 Peeling rate

Peeling rate is equal to the weight difference of the pumpkin before and after

peeling divided by peeling time in g/min.

7.4 Data analysis

The software package SPSS (version 12.0.1) was used for data analysis of the

results.

7.5 Results and discussion

The results of frequencies analysis on peeling rate are shown in Table 7.1. The

peeling rates were distributed between 0.3 and 8.4 g/min for the Jarrahdale and also

120

ranged from 0.3 to 8 g/min for the Jap. There was a considerable difference between

the mean and median of both products. It was 0.385 and 0.362 g/min for the

Jarrahdale and the Jap respectively. The difference placed the normality of

distribution of data under question. Therefore, further assessment of normality was

needed.

Table 7.1.The results of frequencies analysis on peeling rate

Variety Mean Median Mode Std.

deviation

Variance Range Min Max.

Jarrahdale 2.735 2.35 1.00 1.889 3.570 8.10 0.3 8.40

Jap 2.062 1.70 1.20 1.538 2.366 7.70 0.3 8.00

Normality as a prerequisite for many inferential statistical techniques was explored

graphically in different ways including histogram, stem and leaf plot, boxplot,

normal probability plot, and detrended normal plot (Appendix 4). The tests were

carried out separately for both products. The results of all mentioned techniques

suggested that the peeling rate (g/min) as the dependent variable is not normally

distributed but is significantly positively skewed for each variety of pumpkin. The

boxplots indicated that there are four and two outliers (illustrated by circles) for the

Jarrahdale and Jap varieties respectively. The outlying values of the Jarrahdale were

7.33, 7.6, 7.9, and 8.4 g/min. The outliers of the Jap variety were 5.66 and 5.30

g/min. The boxplot of the Jap also showed two extreme cases as 7.62 and 8 g/min.

Therefore, a natural logarithmic transformation was appropriate to transform the

distribution to normal. The results of assessing normality after logarithmic

transformation are shown in Appendix 4. The preceding statistics and graphs

showed that the natural logarithmic transformation was appropriate because the

distribution of transformed peeling rate, called the LnP.rate, was normal. All the

diagnostic data were satisfactory after transformation and the results of frequencies

analysis for the transformed peeling rate are shown in Table 7.2.

121

Table 7.2. The results of frequencies analysis on LnP.rate

Variety Mean Median Mode Std.

deviation

Variance Range Min. Max.

Jarrahdale 0.770 0.854 0.00 0.725 0.526 3.33 -1.20 2.13

Jap 0.496 0.530 0.18 0.681 0.465 3.28 -1.20 2.08

One-way ANOVA with post-hoc analysis was carried out to investigate the

influence of three different independent variables including coarseness, p. speed,

and location on peeling rate (g/min) as the only dependent variable. LSD at 0.05

was applied in mean comparison. Population normality and homogeneity of

variance were assumed as two basic conditions of conducting ANOVA. Levene’s

test showed the homogeneity assumption has been violated for the peeling rate and

also non-normality of data population for that has already been confirmed. The

homogeneity of variance for the LnP.rate was significantly high (Table 7.3). As two

conditions were met by the LnP.rate, therefore ANOVA focused on this variable.

Table 7.3. The results of Levene’s test for homogeneity of variance of LnP.rate

Independent

variable

Variety Levene statistic df1 df2 Sig.

Product 0.358 1 126 0.551

Coarseness Jarrahdale

Jap

0.100

0.424

3

3

60

60

0.960

0.737

P. speed Jarrahdale

Jap

1.301

1.003

3

3

60

60

0.282

0.398

LnP.rate

Location Jarrahdale

Jap

0.172

1.124

3

3

60

60

0.915

0.346

The results of multiple comparisons (Table 7.4) showed that the mean difference of

LnP.rate between two groups of product (Jarrahdale and Jap) was significant (p <

122

0.05). The comparison of means of the coarseness effect on dependent variable

showed significant difference (p < 0.05) of the F test among different levels of

coarseness for two varieties. The mean comparison of the p. speed for both products

also illustrated significant difference (p < 0.01) among different levels of angular

velocities of peeler head. Although the mean of the LnP.rate in different places of

the Jap variety was significantly different (p < 0.05) the Jarrahdale generally did not

show any difference.

7.5.1 The effect of p. speed on LnP.rate

The high significant effect of the mean of different angular velocities of peeler head

on the mean of LnP.rate (g/min) as the transformed type of peeling rate is shown in

Figure 7.3. The increase of the p. speed led to an increase of the LnP.rate (g/min). It

increased from -0.13 and -0.24 g/min at 400 rpm to 1.51 and 1.22 g/min at 850 rpm

for Jarrahdale and Jap varieties respectively. The pattern of increase was linear with

R square of 0.97 and 0.99 for the Jarrahdale and Jap respectively. This result was

expected because increasing p. speed leads to higher energy and rate of impacts of

brushes on the surface of product.

Table 7.4. ANOVA of the mean of LnP. rate among different levels of independent

variables

Variable Variety Sum of

squares

df Mean

square

F Sig.

Product 2.400

1

2.400

4.844 0.030

Coarseness Jarrahdale

Jap

4.170

4.393

3

3

1.390

1.464

2.881

3.527

0.043

0.020

P. speed Jarrahdale

Jap

23.363

18.716

3

3

7.788

6.239

47.883

35.369

0.000

0.000

Location Jarrahdale

Jap

3.798

4.091

3

3

1.266

1.364

2.590

3.246

0.061

0.028

123

The results of multi comparison of the LnP.rate among different levels of p. speed

(Appendix 4) showed high significant difference (p < 0.05) between each of the two

levels of p. speed for both varieties of pumpkin. General comparison of the two

products showed a higher LnP.rate of Jarrahdale. This could be attributed to lower

effective cutting parameters including cutting force, rupture force, and shear force

of the Jarrahdale’s skin. Also it may be because of higher skin toughness of Jap, as

discussed in Chapter 3. The difference of the LnP.rate at 850 rpm (0.29) was greater

than at 400 rpm (0.11) which confirms that the difference of the peeling rate

(LnP.rate) between the two varieties was greater for higher levels of p. speed. It

means the slope of increasing trend for the Jarrahdale was higher than for the Jap.

The increase of p. speed provides the same amount of impact force for both

varieties but the Jarrahdale did show higher response when increasing the slope of

trend in higher levels of p. speed. It means the resistance of skin tissues against

elastic and plastic deformation for the Jarrahdale decreases more at higher levels of

p. speed compared to the Jap.

7.5.1.1 The effect of p. speed on LnP.rate for different levels of coarseness

The general effect of mean p. speed on the mean LnP.rate for different mean

coarseness of brushes was similar for both varieties (Figure 7.4). The removal rate

of peel in the form of LnP.rate increased in order of the following coarseness: very

coarse, mild, coarse, and fine (Figure 7.4) for both products. The pattern of increase

was almost linear for mild and coarse brushes.

The higher removal rate of fine and coarse brushes means the oblique angle of teeth

helps to remove more peel than the other two brushes. The existence of trends for

different types of coarseness of abrasive-cutter brush from 550 to 700 rpm could be

seen clearly. The output difference out of this range of speed increased especially

for lower speeds (400 rpm). In addition to increasing trend for growing speed all

coarseness levels except mild did show an extra increase of LnP.rate while

illustrating a convex point at 550 rpm for Jarrahdale. The fine brush did show a

subsidence at 700 rpm for both products. The comparison of the very coarse type of

brush showed that it can produce a close output to the other types of brushes

124

between 550 and 700 rpm for both varieties and it considerably subsided at 400 and

850 rpm.

-0.5

0

0.5

1

1.5

2

400 550 700 850

P. speed (rpm)

LnP

. rat

e (g

r/m

in) Jap

Jarrahdale

Fig.7.3. The effect of mean p. speed on LnP.rate

850.00700.00550.00400.00P. speed

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00

Mea

n Ln

P.ra

te

FineCoarseMildVery coarse

Coarseness

850.00700.00550.00400.00

Pspeed

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00

Mea

n Ln

P.ra

te

FineCoarseMildVery coarse

Coarseness

Jarrahdale Jap

Fig. 7.4. The effect of p. speed on LnP.rate at different levels of coarseness

125

7.5.1.2 The effect of p. speed on LnP.rate in different locations of product

Both varieties were affected similarly by p. speed at different parts of product

(Figure 7.5). While a general growing trend of peeling rate for increasing p. speed

was seen at all parts of the two varieties of pumpkin, except at the top areas that

illustrated a peak point at 550 rpm, which reveals high peel removal at this speed.

This result confirms selection of 550 rpm as the optimal angular velocity of the

peeler head equipped with the abrasive-cutter brush in the previous chapter

(Chapter 6).

850.00700.00550.00400.00Pspeed

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00

Mea

n Ln

P.r

ate

Top-sideBottom-sideTopBottomLocation

850.00700.00550.00400.00Pspeed

1.50

1.00

0.50

0.00

-0.50

Mea

n Ln

P.ra

teTop-sideBottom-sideTopBottom

Location

Jarrahdale Jap

Fig. 7.5. The effect of p. speed on LnP.rate at different locations of pumpkin

The skin removal at the top and top-side areas varied at different levels of p. speed

for both varieties. While the peel removal at these areas was approaching each other

at 400 and about 700 rpm, the difference increased at 550 and 850 rpm. Lower

removal at the top areas for 550 rpm was the cause of difference because the

LnP.rate for 550 rpm of p. speed at top areas did not follow the shape of other

locations at this point. The peel removal at top side areas became smaller than at top

points at higher levels of p. speed for both products. This reduction happened for

126

Jap and Jarrahdale before and after 700 rpm respectively. Although the depth and

width of grooves at the top side areas are considerably bigger than at other areas of

both products, lesser peel removal in this area than at top points for higher speeds

could be explained in different ways. The most likely reason is reduction in

coverage area of the concave points at top side areas for higher p. speed. The higher

radius of rotation for those points compared with smaller radius at the top points

caused higher circumferential speed and decreased the access to the grooves by the

abrasive-cutter brushes.

7.5.2 The effect of coarseness on LnP.rate

The comparison mean of LnP.rate as one transformed type of peeling rate for

different coarseness levels of brush revealed an almost linear relationship (Figure

7.6). The increasing trend of LnP.rate was found for both products in the same order

for very coarse, mild, coarse, and fine respectively. The Jarrahdale variety showed

significantly higher LnP.rate than the Jap in all types of coarseness of brush. The

lower rate of peeling rate for the Jap variety again emphasized the greater toughness

of skin that demands higher cutting, shearing, and rupture forces compared with the

Jarrahdale. Although the results showed that all types of brushes with different

coarseness levels have toughness greater than skin toughness of the two products,

the production of peel losses per unit time becomes higher for the finest skin of

Jarrahdale. In addition fine and coarse brushes with lower toughness showed a

higher LnP.rate. This was mainly because of the oblique position of the teeth in

these types of brushes. More comparison of the results also revealed higher output

of the fine than the mild brush and also of the coarse than the very coarse brush. It

means the size of protrusions is effective on the LnP.rate. The smaller size could

increase the LnP.rate for both varieties. The mean of LnP.rate for the fine type of

brush was significantly (p < 0.05) bigger than for the coarse type (Appendix 4) and

this was in agreement with the previous obtained results (Chapter 6). The reasons

for this result could be explained as more flexibility and capability of penetration

into concave areas by smaller sizes such as the fine brush. Despite those acceptable

results the coarse brush type revealed significantly (p < 0.05) higher LnP.rate than

the mild type of brush. The results of applying the mild brush showed expected non

significant higher peel removal compared to the very coarse type of brush. Results

127

generally showed the increase of the peeling rate when reducing the coarseness of

brush, irrespective of the position of the coarse type of brush.

0

0.2

0.4

0.6

0.8

1

1.2

Very coarse Mild Coarse FineCoarseness

LnP.

rate

(gr/

min

)

JapJarrahdale

Fig.7.6. The effect of mean coarseness on LnP.rate

7.5.2.1 The effect of coarseness on LnP.rate at different p. speed

The general form of an increasing trend of different p. speed levels for both

varieties of pumpkin except at 550 rpm for the Jarrahdale variety was observed

(Figure 7.7). The mild brush at 550 rpm did show the opposite trend. The curvature

change of increasing trend at this point to concave for the Jarrahdale revealed lesser

peel removal than the expected LnP.rate. Higher mean value of the LnP.rate than

expected normal growth of trend at 550 rpm was easily revealed except for the mild

brush on the Jarrahdale. The mean of LnP.rate at 400 rpm was similar for different

brushes for both varieties of pumpkin. That means this speed is not sufficient to

impose necessary cutting force for notable penetration and peel removal on

different product. The idea was proved by the revelation of a big difference between

the results at 400 rpm and the other higher angular velocities of every type of brush.

The increase of the p. speed above 400 rpm led to higher peel removal in the

Jarrahdale compared to the Jap. Both products showed a sharp increase of peel

removal from course to mild at 400 and 850 rpm. It means considerable reduction

128

of coarseness and increasing p. speed can significantly affect the peeling rate in the

form of the LnP.rate.

FineCoarseMildVery coarseCoarseness

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00

Mea

n Ln

P.ra

te

850.00700.00550.00400.00

Pspeed

FineCoarseMildVery coarse

Coarseness

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00

Mea

n Ln

P.ra

te

850.00700.00550.00400.00

Pspeed

Jarrahdale Jap

Fig.7.7. The effect of coarseness on LnP.rate at different speeds of abrasive-cutter

brush

7.5.2.2 The effect of coarseness on LnP.rate at different locations of pumpkin

The reduction of the coarseness of brush generally caused an increase of the

LnP.rate as the peeling rate at different areas of both products. The form of

increasing trend was different between the two varieties at different areas except the

top. All types of brushes revealed higher peel removal at the top areas compared to

the bottom except the very coarse brush for the Jap variety (Figure 7.8). This is

because of the existence of grooves (deep and thin in some products) at top areas

compared with a flat surface at the bottom. Therefore, the interaction area for each

removal impact of brush and the peel removal in total was higher at top areas. For

the same reason the removal rate of coarse and very coarse grades at top areas was

lower. This reduction clearly can be seen for the Jap variety because of the tougher

skin of the Jap compared with the Jarrahdale. Higher mean of LnP.rate at the top-

side areas than the bottom-side can be explained by considering the larger depth of

grooves at the top side areas. It means the possibility of more effective peeling for

129

each impact of all types of brushes at top side areas. The mean LnP.rate at the

bottom side areas of the Jap was higher than at the top side for coarse and fine types

of brush.

FineCoarseMildVery coarseCoarseness

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

Mea

n Ln

P.ra

te

Top-sideBottom-sideTopBottom

Location

FineCoarseMildVery coarseCoarseness

1.25

1.00

0.75

0.50

0.25

0.00

-0.25

Mea

n Ln

P.ra

te

Top-sideBottom-sideTopBottom

Location

Jarrahdale Jap

Fig.7.8. The effect of coarseness on LnP.rate at different locations of product

7.5.3 The effect of location of product’s surface on LnP.rate

The mean of LnP.rate of the Jarrahdale variety was higher than that of the Jap

variety at different locations on the product. The difference was significantly bigger

(more than two times) at top and bottom areas (Figure 7.9). The results of the post-

hoc test (Appendix 4) showed significant difference (p < 0.05) between the bottom

and side areas. The results revealed no difference between the top and other areas of

product. Study of the range of change between the maximum and minimum mean of

LnP.rate at all areas for each variety showed a small difference. The difference for

the Jarrahdale (0.63 g/min) was higher than for the Jap (0.58 g/min). This can be

attributed to generally lesser skin toughness of the Jarrahdale variety that results in

more peel removal per unit time compared with the Jap. Comparison of two

products did show also two other important differences.

130

00.20.40.60.8

11.2

Bottom Top Bottom-side

Top-side

Location

LnP

. rat

e (g

r/m

in) Jap

Jarrahdale

Fig.7.9. The effect of mean location on LnP.rate

The existence of a concave area at the top of the Jap variety and also the small

difference of mean LnP.rate between the top and bottom side areas of Jap could be

identified in Figuere 7.9. It means the Jap variety of pumpkin has more similarity in

curvature at side areas and also between top and bottom areas.

7.5.3.1 The effect of location on LnP.rate in different coarsenesses of brush

Higher peel removal rate as LnP.rate for the Jarrahdale variety compared with the

Jap can be seen in Figure 7.10. While both products showed the largest difference at

the top area for different coarseness of brush, the smallest difference of the

Jarrahdale and Jap was observed at the bottom-side and top-side areas respectively.

The effect of the mild brush could only produce similar form of increasing trend for

both products. In other words, the variation of the effect of different types of

brushes on peel removal at different locations of both varieties was considerable.

While the very coarse brush, as a less effective brush, produced more LnP.rate at

the top area of the Jarrahdale than bottom, the results for the Jap variety were

opposite with small difference. The fine type of brush, as a more effective brush,

produced higher peeling rate at side areas. The LnP.rate was high at the top side

area for the Jarrahdale and at the bottom side area for the Jap. Although there was

no significant difference between sides areas in both varieties (Appendix 4), side

131

areas of products were found to be similar especially for fine and mild brushes on

the Jarrahdale and mild and coarse on the Jap.

Top-sideBottom-sideTopBottomLocation

1.40

1.20

1.00

0.80

0.60

0.40

0.20

0.00

Mea

n Ln

P.ra

te

FineCoarseMildVery coarse

Coarseness

Top-sideBottom-sideTopBottomLocation

1.25

1.00

0.75

0.50

0.25

0.00

-0.25M

ean

LnP.

rate

FineCoarseMildVery coarse

Coarseness

Jarrahdale Jap

Fig.7.10. The effect of location on LnP.rate in different coarseness

7.5.3.2 The effect of location of product’s surface on LnP.rate at different

p. speed

The increase of p. speed showed a higher LnP.rate for both varieties (Figure 7.11).

The peel losses as LnP.rate appeared to be higher for the Jarrahdale compared with

the Jap. Peeling at different speeds of abrasive-cutter brush revealed that higher and

lower values of mean LnP.rate difference take place at the bottom-side and top

areas for both products respectively. All p. speed levels showed a lower LnP.rate at

the bottom area and a maximum in one of the side areas. The biggest LnP.rate at the

bottom side area was for the Jap variety at 850 rpm.

132

Top-sideBottom-sideTopBottomLocation

2.00

1.50

1.00

0.50

0.00

-0.50

-1.00

Mea

n Ln

P.ra

te

850.00700.00550.00400.00

Pspeed

Top-sideBottom-sideTopBottomLocation

1.50

1.00

0.50

0.00

-0.50

Mea

n Ln

P.ra

te

850.00700.00550.00400.00

Pspeed

Jarrahdale Jap

Fig.7.11. The effect of location on LnP.rate at different p. speeds

7.6 Conclusions and discussion

Mechanical peeling of two varieties of pumpkin including Jarrahdale and Jap was

experimentally investigated by using an abrasive-cutter brush. The tests were

carried out using full factorial design. The effect of three independent variables,

namely, the angular velocity of brushes (four levels), coarseness of brushes (four

levels), and location of peeling on product (four levels) on LnP.rate was

investigated as the transformed dependent variable of peeling rate (g/min).

The increase of mean p. speed led to a linear increase of the mean LnP.rate (g/min).

This result was expected because increasing the p. speed leads to higher energy and

frequency of the impacts of brushes on the surface of product. The results of multi

comparisons of the LnP.rate among different levels of p. speed showed high

significant difference (p < 0.05) between each two levels of p. speed for both

products. The comparison of the two products showed higher LnP.rate of the

Jarrahdale compared with the Jap. This could be attributed to lower effective cutting

parameters including cutting force, rupture force, and shear force of the Jarrahdale

133

skin. It might also be because of higher skin toughness of the Jap and these aspects

were already discussed in Chapter 3. The increase of p. speed supplies the same

amount of impact force for both varieties but the Jarrahdale did show more response

with increases of the curve slope at higher levels of p. speed. It means the resistance

of skin tissues against elastic and plastic deformation for the Jarrahdale decreases

more at higher levels of p. speed compared to the Jap.

The mean comparison of LnP.rate as one transformed type of peeling rate for

different coarseness of brush revealed an almost linear relationship. The increasing

trend of LnP.rate was observed for both products in the same order including very

coarse, mild, coarse, and fine brushes respectively. The Jarrahdale variety showed

significantly higher LnP.rate than the Jap in all types of coarseness of brush. The

lower rate of peeling rate of the Jap variety again emphasized the greater toughness

of skin that requires higher cutting, shearing, and rupture forces compared with the

Jarrahdale. Fine and coarse brushes with lower toughness showed a higher LnP.rate.

This was mostly because of the oblique position of teeth in these types of brushes.

More comparison of the results also revealed higher output of the fine than mild

brushes and also of the coarse than the very coarse brush. It means the size of

protrusions impacts on the LnP.rate. The smaller size could increase the LnP.rate

for both varieties. The mean of LnP.rate for the fine type of brush was significantly

(p < 0.05) bigger than the coarse type and this was in agreement with the previously

obtained results. This could be attributed to higher flexibility and capability of

penetration into concave areas by smaller sizes of protrusions such as in the fine

brush. Results generally showed that with the increase of peeling rate the coarseness

of brush is reduced, ignoring the position of the coarse type of brush.

The mean of LnP.rate of the Jarrahdale was higher than the Jap at different

locations on the product. The difference was significant (more than two times) at

the top and bottom areas. The results of the post-hoc test showed significant

difference (p < 0.05) between bottom and side areas. The results revealed no

difference between the top and other areas of product. Study of the range of change

between the maximum and minimum mean of LnP.rate in all areas for each variety

showed a small difference. The difference for Jarrahdale (0.63 g/min) was higher

than for the Jap (0.58 g/min). It can be explained by the generally less tough skin of

134

the Jarrahdale producing more peel removal per unit time compared with the Jap.

The existence of a concave zone at the top area of the curve of the Jap variety and

also small difference of mean LnP.rates between the top and bottom-side areas of

the Jap showed that this variety of pumpkin has more similarity in curvature at side

areas and also between top and bottom areas.

7.7 Summary

Abrasive-cutter brush as the best peeling method of tough-skinned vegetables was

comprehensively investigated. Full factorial experiment design was applied in

peeling experiments of two varieties of pumpkin (Jap and Jarrahdale). The

experiments were carried out in 128 runs (64 runs for each variety of pumpkin).

Three effective independent variables related to either the peeling tool (p. speed and

the roughness of brush) or product (the location of peeling on product) were

selected for investigation. The influence of these significant parameters on LnP.rate

as logarithmic transform of peeling rate was studied. The results showed that

LnP.rate is increasing continuously with the increase of p. speed. The effect of the

brush roughness as a categorical variable on peeling rate was investigated in four

levels. The response variable, LnP.rate, increased in order of coarse, mild, coarse

and fine. Another categorical variable was location. The surface of the whole

pumpkin was divided into four sections named “Top”, “Top-side”, “Bottom-side”

and “Bottom”. These areas were selected as four levels of location of peeling. It was

revealed that the LnP.rate increases in order of bottom, top, bottom-side and top-

side. The difference was attributed to the number and size of grooves in these areas.

135

Chapter 8

Modelling of mechanical peeling as sum of

consumed energy in the peeling process

8.1 Introduction

Modelling of the results can be illustrated in different ways. Mechanical peeling is

carried out mostly on the basis of cutting forces. The simulation of mechanical

peeling on the basis of the cutting process helps to better understand the effective

forces of peeling and the role of different influence parameters of product and peeling

tool. Mechanical peeling using an abrasive-cutter brush was simulated on the basis of

the cutting process. Choosing the input and output variables which would be

industrially applicable was attempted. Three variables, namely, angular velocity of

abrasive-cutter brush (ωp), the degree of unevenness of product surface (φ), and the

shape of the abrasive-cutter brush (λ), were chosen as independent variables and the

peel losses per unit time were chosen as the output of the model. The developed

model was verified using the experimental results of peeling for two varieties of

pumpkin including Jarrahdale and Jap. In this chapter the theory of a mathematical

model based on the cutting procedure of the fibrous material is discussed. This model

is developed and investigated for the first time.

136

8.2 Theory of the model

8.2.1 The assumptions

The following assumptions were applied:

1. Removing peel is assumed to occur in layers and in the form of chips.

2. Peeling rate is in linear proportion to peeling energy.

3. The angular velocity of product is assumed to be zero.

4. The size and the weight of products are assumed to be the same and constant for

products of each variety.

8.2.2 Development of the model

The cutting procedure and removing the peel can be split into two main stages

including fracture of the skin and scratching along removing the peel as formed chips.

The total energy spent on cutting and removing the skin can be written as given

below:

)(121 PPP

ct +=

η, (8-1)

where, Pt is the total required power of peeling in N. mm/min; P1 and P2 are the

required power for cutting and forming removed skin, respectively, in N. mm/min;

and ηc is total peeling efficiency.

The energy consumed at the fracture stage itself is spent to penetrate the abrasive-

cutter brush (teeth) inside the skin (Figure 8.1). The penetration depth depends on the

stroke force developed by the rotational kinetic energy of the brush and neglecting

the air resistance. The total penetration energy can be calculated as given below:

)(1 dpp EEnP += ω , (8-2)

137

where, P1 is the total fractural power per unit time in N. mm/min; n is the installed

number of brushes on the peeler head; ωp is the angular velocity of the brush in rpm;

Ep and Ed are the necessary penetration and deflection energy of one brush in N. mm

respectively.

Fig.8.1.The view of abrasive-cutter brush after penetration into the skin

The energy required for penetration of one brush through the skin, Ep, is given below:

2111 ).( δδ ×−= tVKE ipp , (8-3)

where, K1 is the average shearing resistance per unit length of stroke in N.mm-1; Vip is

the linear penetration velocity of brush teeth inside the skin in mm/s; t1 is the time of

stroke in s; δ1 is the deflection of product in mm; and δ2 is the average penetration

depth of teeth inside the skin in mm. The deflection of the product in reaction of

stroke, δ1, is neglected because of rigid support of the vegetable holder which allows

the simplifying of equations. The penetration depth of the teeth of the brush inside the

skin also depends on the linear velocity of the teeth through skin and the time of

stroke as given below:

Without deflection

After deflection

Rotation centre of brush

δ2 δ3

Product

138

21 δ=⋅ tVip , (8-4)

The coefficient K1 is considerably affected by the ratio of the material’s toughness

and other stated parameters according to the following equation:

2

122111

sin4δ

θτπγα lddlK = , (8-5)

where, γ is the ratio of product toughness (Tp) to the toughness of tool (Tt) as follows:

t

p

TT

=γ (8-6)

α is the density of protrusions on a brush in number/mm2; l1 is the effective length

(covered by abrasive strip) of the brush in mm; d1 is the diameter of the brush in mm;

τ is the shear strength of the product in N/mm2; d2 is the diameter of the protrusion’s

hole in mm; l2 is the length of each tooth on protrusion in mm; and θ1 is the angle of

the teeth in protrusion in degrees (Figure 8.2).

Fig.8.2. The cross-sectional view of one protrusion (two out of four teeth are shown)

Each brush stroke is accompanied by its deflection. In ideal conditions, the end of the

brush will show a deflection of δ3 because of reaction to the stroke. The average

expenditure energy for this deflection when considering a brush as a cantilever beam

can be written as follows:

l2

θ1

d2

139

3333δ

δL

EIEd = , (8-7)

where, Ed is the expenditure energy of one brush due to deflection in N. mm; E is the

modulus of elasticity of the brush in N.mm-2; I is the geometric moment of inertia of

the brush in mm4; L is the whole length of the brush in mm; and δ3 is the average

deflection of the brush at the fracture stage in mm. As the deflection of the brush

varies from zero at the root to the maximum at the end of brush and the resistance of

the brush against bending is linearly proportional to deflection, the average deflection

is considered as estimated below:

20 max3

3δδ +

= , (8-8)

where, δ3max is the maximum deflection of the brush in the fracture stage in mm.

Therefore, replacing coefficients in 8-2 leads to the final form of required power in

the fractural stage of peeling as given below:

)34( 3

23

1221211 LEISinddllnP pδθτδπγαω += , (8-9)

The second stage of energy is spent after fracture of the peel. This energy is required

to scratch and remove the skin in chip form. The total power expenditure at this stage

can be written as follows:

opc VFP ⋅=2 , (8-10)

where, P2 is the total power required at the second stage of peeling in N. mm/min; Vop

is the linear velocity of scratching teeth inside the skin in mm/s; and Fc is the cutting

force in N. The cutting force of fibrous material such as pumpkin is comprised of

three effective forces (Dowgiallo, 2005) as given below:

defc FFFF ++= , (8-11)

140

where, Fc is the total cutting force in N; Ff is friction force in N; Fe is force spent for

elastic and plastic deformation in N; and Fd is disintegration force exerted by brush

teeth on the product structure in N. Ff and Fe as two important effective forces will be

included in detail in the model. The expenditure energy due to Fd is released mostly

as heat and depends significantly on some parameters such as the geometrical

dimensions of teeth, the cutting speed, and resistance of product to cutting. Fd will be

included in the model as part of the efficiency of cutting in this stage. The energy

spent by Ff for one brush can be written using the law of friction as given below:

hFKE ff ××= 2 , (8-12)

where, Ef is the energy spent on friction in N. mm; Ff is the friction force in N; h is

the length of removed peel in mm; and K2 is the friction coefficient related to the

properties of the product and geometrical parameters of brush. This coefficient can be

written on the basis of the most significant parameters as follows:

2

2112 d

dlK αδπϕ= , (8-13)

where, K2 is the friction coefficient; α is the density of protrusion in number/mm2;

and φ is the degree of unevenness of the product surface. The degree of unevenness

increases in order of bottom, top, bottom-side, and top-side for both products. The

force required to overcome friction is estimated using the following relationship:

vdf RF ⋅= μ , (8-14)

where, Ff is the friction force in N; μd is the dynamic coefficient of friction between

the brush’s tooth and product; and Rv is the total normal reaction in N, that is

complimented from two main important forces as follows:

dev FNR += , (8-15)

141

where, Fde is the deflection force of brush in N; and N is the normal reaction force to

the weight of the brush in N, that can be calculated as:

21 cosθWN = , (8-16)

where, W1 is the weight of one brush in gr; and θ2 is the angle between direction of

the weight and direction of the line that passes through the gravity centre of brush and

is perpendicular to the surface of product at the contact point. With the replacing of

8-15 and 8-16 into 8-14 the total friction force can be obtained as follows:

)3cos( 34

21 LEIWF dfδθμ += , (8-17)

where, δ4 is the average deflection of brush at the second stage of cutting in mm. This

deflection should be bigger than the deflection at the previous stage, δ3, due to

passing of the product by the brush.

The total energy expenditure of one brush by friction force can be written as:

)3cos( 34

212 LEIWhKE dfδθμ += (8-18)

The force spent on elastic and plastic deformation is another effective force at the

second stage of cutting. As fibrous materials are not less stiff than friable or

crystalline materials (Dowgiallo, 2005), this force forms a considerable part of

cutting force at the second stage. The elastic and plastic deformation force can be

determined as the equation given below:

33 lhKFe ×××= τ , (8-19)

where, Fe is the total elastic and plastic deformation forces of one brush in N; τ is the

shear strength of product in N/mm2; h is the length of removed peel in mm; and l3 is

the total projected lengths of the protrusion’s teeth engaged in cutting in mm. Figure

8.2 shows the top view of protrusion (in direction of cutting). As the direction of

movement and cutting are not the same (because of angle θ1) then the projected

142

length (l3) should be considered in the above equation to calculate the work done by

this force. With consideration of Figure 8.2 the length of l3 can be replaced with:

123 cos2 θll = (8-20)

The coefficient of K3 depends on some geometrical parameters of the brush as stated

below:

απ 113 dlK = (8-21)

Therefore, the total elastic and plastic deformation energy can be given as follows:

122

11 cos2 θταπ lhdlEe ⋅⋅⋅⋅⋅⋅= (8-22)

With consideration of the disintegration force as a coefficient for both Ef and Ee and

adding up 8-18 and 8-22, the total energy expenditure at the second stage of cutting

could be represented as given below:

⎥⎦

⎤⎢⎣

⎡+⎟

⎠⎞

⎜⎝⎛ += 123

421

2

21142 cos..23cos θτδθϕμδαπ hl

LEIW

ddlhKE d , (8-23)

where, E2 is the total required energy of peeling in the second stage in N. mm; and K4

is the coefficient of disintegration force of the product structure.

The equation 8-10 of required power for scratching and removing peel at the

second stage of cutting can be rewritten as given below:

252 EKP = , (8-24)

where, P2 is the total required power for one brush in the second stage of peeling in N.

mm/min; and K5 as the scratching coefficient at the second stage of peeling could be

expressed as:

143

βωω nK

p

v=5 , (8-25)

where, K5 is the scratching coefficient in the second stage in number/min; ωv is the

angular velocity of the vegetable holder in rpm; and β is the number of scratches in

number/min. The length of scratching or efficiency is dependent on ωv/ωp. Also, β is

considered due to the reason that a stroke of brush does not necessarily lead to

scratching. Therefore, the total required power of peeling at the second stage of

cutting will be given as follows:

⎥⎦

⎤⎢⎣

⎡⋅⋅+⎟

⎠⎞

⎜⎝⎛ += 123

421

2

21142 cos23cos θτδθϕμδαπβ

ωω hl

LEIW

ddlhnKP d

p

v (8-26)

The energy required for the abrasive-cutter brush could be obtained by integrating the

component models stated by the above equations. The integration gives the final

equation as follows:

)34(13

23

122121 LEISinddllnP p

ct

δθτδπγαωη

+= +

⎥⎦

⎤⎢⎣

⎡⋅⋅+⎟

⎠⎞

⎜⎝⎛ + 123

421

2

211

4 cos23cos θτδθϕμδαπβωω

ηhl

LEIW

ddlhnK d

p

v

c

, (8-27)

where, Pt is the total required power of peeling in N. mm/min.

As the cutting force of fibrous material is directly in relation to the resulted

deformation during cutting (Dowgiallo, 2005), it can be assumed that the peeling rate

also should be in direct relation to the required power of cutting. Assuming a linear

relationship between the peeling rate and the required power of peeling leads to the

following equation:

tPKrateP ⋅= 6. , (8.28)

144

where, P. rate is the peeling rate during peeling in gr/min; and K6 is the transform

coefficient of Pt to p. rate in g/N. mm. The integration of 8.27 and 8.28 will show the

final equation of peeling rate during peeling as given below:

)34(1. 3

23

1221216 LEISinddllnKrateP p

c

δθτδπγαωη

+= +

⎥⎦

⎤⎢⎣

⎡⋅⋅+⎟

⎠⎞

⎜⎝⎛ + 123

421

2

211

46 cos23cos θτδθϕμδαπβωω

ηhl

LEIW

ddlhnKK d

p

v

c

(8.29)

The input of the obtained model includes many parameters related to the product and

the abrasive-cutting brush. As determination of all effective parameters is impossible

at this stage, it was attempted to rewrite and arrange the above model using

industrially applicable input and output variables. The review of effective parameters

regarding the results of the previous chapter showed three likely independent

variables. They are the angular velocity of brush (ωp), the unevenness of product

surface (φ), and cosθ1 that represents the shape of the brush and actual protrusion of

the brush and it is denoted as (λ). The output of model is kept as p. rate and rewriting

equation 8.29 by using factorial technique on the basis of these three independent

variables will show the general format of model as given below:

λϕω 3210. CCCCrateP p +++= , (8.30)

where, the model coefficients C0 to C3 are as follows:

34

1146031

LEIdlhnKKC

p

v

c

δωω

ηαπβ= ; (8.31)

)3sin4(13

23

12212161 LEIddllnKC

c

δθτδπγαη

+= ; (8.32)

)3cos(13

421

2

211462 L

EIWddlhnKKC d

p

v

c

δθμαδπβωω

η+= ; (8.33)

145

22

1146312 lhdlhnKKC

p

v

c

ατπβωω

η= . (8.34)

8.2.3 Determination of the model coefficients

The accuracy of prediction of the model depends significantly on the accuracy of

model’s parameters. Some of the parameters are known (e.g. l1, l2, d1, d2, etc.) and

some of them could be determined from specially designed experiments. A few

mechanical properties from the latter part (e.g. Tp, τ, etc.) and some related

parameters that did not appear directly in the model have been determined earlier by

this research and the others need to be determined using special experiments (e.g. β,

δ3 ). Direct measurement of all appeared parameters in the model would result in

accurate estimation of the abrasive-cutter brush operation. Due to the impossibility of

carrying out separate direct measurements, coefficients of the model were determined

indirectly using experimental data and based on the multiple regression analysis

technique. The obtained data from full factorial experiments on the peeling of two

varieties of pumpkin, Jarrahdale and Jap, by abrasive-cutter brush were used (Chapter

7). The dependent variable as p. rate was selected to be a function of angular velocity

of brushes (ωp), type of brush (λ), and unevenness of product surface (φ) as three

independent variables.

Regarding the general linear function of the model, a multiple regression analysis was

carried out for both varieties of pumpkin to determine four coefficients. The SPSS

software package (version 13) was used for the analysis.

8.2.4 Model validation

A portion of the data for each experiment (12.7% for Jarrahdale and 12.9% for Jap)

was not used for determination of the model’s coefficients. Those randomly selected

data were used for model validation. The experimental data of p. rate were compared

with the corresponding predicted p. rate for each variety of pumpkin using a scattered

plot. The models were considered validated if the following criteria were satisfied:

146

1. The intercept of the linear regression analysis between the modelled and

experimental values should be close to zero.

2. The coefficient of linear regression analysis between the modelled and

experimental values should be close to unity.

3. The correlation coefficient between the modelled and experimental values

should be statistically significant.

8.3 Results and discussion

The proposed mathematical model for mechanical peeling of tough-skinned

vegetables, using abrasive-cutter brushes, is a linear type and has four coefficients.

There are three independent variables, including, ωp, unevenness of product surface

(φ), and the type of brush (λ). The coefficients of those variables include parameters

related to the properties of the product and the brush as a peeler. The coefficients

were determined indirectly by using experimental data on peeling two different

varieties of pumpkin namely Jarrahdale and Jap. The experiments were carried out

strictly under the same conditions for both products. Multiple regression analysis was

used for determination of coefficients and the results are presented below.

8.3.1 Model coefficients

The estimated values of model coefficients along with other results of multiple

regression analysis are shown in Table 8-1 and the complete results are reported in

Appendix 8-1. The results revealed that those three coefficients of the model for both

varieties of pumpkin are highly significant (p < 0.0001). Despite the highly

significant effect of these independent variables still they could explain 88% (R2 =

0.881) of the variation in dependent variables for the Jarrahdale and about 89% (R2 =

0.894) for the Jap. Regarding the relatively small number of variables (three

independent variables), the R square is sufficiently satisfied. But the difference

between the full value of R square showed there are still some other effective

variables on peeling rate resulting from peeling by an abrasive-cutter brush. Their

significance varies with their number. If remaining variables are more than one, then

their effectiveness would be smaller. However, the obtained value (almost 0.90) of

147

coefficient of determination (R2) can provide a realistic estimation of effective

parameters on the mechanical peeling of both products.

Table8-1.The results of multiple regression analysis for coefficients of two

mechanical peeling models

Model coefficients

Product C0 C1 C2 C3

R2

F

Sig.

Jarrahdale -4.239 0.007 0.487 0.506 0.881 106.559 0.000

Jap -3.088 0.005 0.405 0.410 0.894 123.867 0.000

The results also showed the significance of each independent variable in the model

for both products. As all variables are highly significant (p < 0.0001), it means that

all inserted parameters as coefficients to the model can significantly affect the peeling

rate. The general comparison of all coefficients revealed that all coefficients (except

the coefficients C0) are higher for the Jarrahdale than for the Jap. The existence of a

positive linear function between each independent variable and output showed that

the increase of ωp, φ, and λ leads to higher values of peeling rate.

The value of C1 was higher for the Jarrahdale (0.007) than for the Jap (0.005). This

indicates that the energy requirement for the penetration of the brush’s teeth into the

skin of the Jarrahdale was greater than that for Jap at the first stage of the cutting

process. Due to identical conditions of experiments, the reason could be related to the

two important mechanical properties of pumpkin, γ, which appeared in this

coefficient. Considering the same toughness of the abrasive-cutter brush for both

varieties, the cause of difference should be found at the numerator of the ratio of

toughness (γ). Although the skin toughness of the Jarrahdale (13.87 N.mm) is less

than the skin toughness of the Jap (33.10 N.mm), the higher unpeeled toughness of

the Jarrahdale (719.72 N.mm) than that of the Jap (702.73 N.mm) could affect the

required power of peeling at that stage.

The comparison of the coefficient C2 showed that this coefficient for the Jap (0.405)

is smaller than that for the Jarrahdale (0.487). Again, considering the same conditions

of peeling for both varieties, the cause of difference should be found in properties of

148

the product. The most significant parameters in this coefficient are μd, h, and β.

Although the value of dynamic coefficient of friction (μd) has not been reported for

those varieties, the values of static coefficient of friction have been measured in this

research. Although the static coefficient of friction of the Jap on stainless steel in the

unpeeled state (0.63) and in the state of being without periderm (0.76) are higher than

that of the Jarrahdale in the unpeeled state (0.30) and without periderm state (0.61),

the dynamic coefficient of friction has not been measured. The length of removed

peel for each scratch (h) appeared in coefficient C2. The direct effect of h on peeling

rate means producing bigger h needs more required energy of peeling or the tissue

structure of product is looser. The comparison of mechanical properties supports this

relationship. Lower value of properties of the Jarrahdale such as skin thickness (13.87

N.mm), shear strength of skin (2.72 N/mm2) and unpeeled (1.78 N/mm2), cutting

force of skin (2.82 N) and unpeeled (5.15 N) and also rupture force of skin (40.68 N)

and unpeeled (248 N) compared with the Jap with skin toughness (33.10 N. mm),

shear strength of skin (3.29 N/mm2) and unpeeled (2.42 N/mm2), cutting force of skin

(2.41 N) and unpeeled (10.99 N) and rupture force of skin (98.30 N) and unpeeled

(249 N) are already revealed (Chapter 3). As φ appeared at the second stage of

peeling, the skin properties make a heavier impact than unpeeled properties. One of

the effective forces at the second stage that can affect peeling production by

scratching was rupture force. Lower resistance of the Jarrahdale skin to rupture force

allowed for production of longer h. The loose tissue structure of the Jarrahdale also

could be significantly effective in increasing the value of β. The loose tissue has

higher ability to absorb the strokes of brushes. The lower value of skin toughness of

the Jarrahdale was an obvious reason for the increased ability to transform more

strokes to scratches (β).

The type of brush that appeared in the model as λ had coefficient C3. The value of

coefficient C3 was also revealed to be smaller for the Jap (0.410) than that value for

the Jarrahdale (0.506). The related properties of product that can explain the

difference in this coefficient were shear strength (τ) and the cubic value of the length

of removed peel (h). The shear strength of the Jap in the states of skin (3.29 N/mm2)

and unpeeled (2.42 N/mm2) are significantly bigger than the shear strength of the

Jarrahdale in skin (2.72 N/mm2) and unpeeled (1.78 N/mm2) states. The effect of h on

coefficient C2 is another cause of higher value of C3 for the Jap. This influence

149

because of cubic value of h can significantly affect the peeling rate more than the

shear strength can.

The comparison of coefficients C0 showed the value for the Jarrahdale (-4.239) is

significantly smaller than that coefficient value for the Jap (-3.088). The related

parameters to the product that appeared in this coefficient were β and h. They could

not explain this behaviour. This difference could be attributed to some parameters

that are not represented in the model.

8.3.2 Model validation

The validation of the model was assessed using scattered plots between experimental

and predicted values (Figure 8.3). The values of the regression coefficients showed

about ±0.14 difference with unity (not parallel trade lines). It was 0.85 for the Jap and

1.14 for the Jarrahdale. The intercepts of the regression lines were nearly close to

zero. The values of -0.05 and 0.01 were obtained in this case for the Jap and

Jarrahdale respectively. Also the correlation coefficients between predicted and

experimental values of the Jap (0.98) and Jarrahdale (0.96) were revealed to be

statistically significant. Therefore, all assumed criteria for meeting validity were

satisfied.

Jarrahdaley = 1.1411x + 0.0121R2 = 0.9372, R=0.96

Japy = 0.8589x - 0.0581R2 = 0.9669, R=0.98

0

1

2

3

4

5

6

7

8

0 2 4 6

Predicted values of p. rate

Exp

erim

enta

l val

ues o

f p. r

ate

Jarrahdale

Jap

Fig.8.3. Experimental versus predicted values of p. rate (gr/min)

150

8.3.3 Applicability of the model

For the first time a generalised model was developed for mechanical peeling using

abrasive-cutter brushes. The model was developed for the peeling of tough-skinned

vegetables and its validity was assessed for two varieties of pumpkin, namely, Jap

and Jarrahdale. For the first time the model was developed on the basis of the cutting

process of mechanical peeling. The determined coefficients of models are valid only

for the same conditions of experiments that were carried out in this research. The

general effects of different parameters of the product and peeler on power

requirement of peeling or peel losses can be extended to other tough-skinned

vegetables especially those with the same shape. The behaviour of different

parameters that were shown in the model as part of the cutting process could be

applied in the design of peelers in different aspects. The range of application of

angular velocity of brushes is from 400 to 850 rpm. The application range for the

shape of brush is in four groups, namely, fine, mild, coarse, and very coarse with

regard to the given toughness (90-170 N. mm) and geometrical parameters described

in the experiment conditions. The model can show the effect and predict the value of

peel losses at different places of pumpkin. Those places as described already are top,

bottom, top-side, and bottom-sides of the pumpkin.

Some mechanical properties of product such as toughness, shear stress, and dynamic

friction coefficient were considered in the model. As these properties vary even for

products of one variety due to different growing conditions (e.g. soil, water,

sunshine) and as this variation is not necessarily linear, the mean values of those

parameters were considered in the model. However, the suggested values of

coefficients are valid for the Jap and Jarrahdale varieties that are grown in Australia.

The relationship among different parameters of the product and abrasive-cutter brush

and their effect on the peeling rate could be used in industrial design of this

innovative peeler and development of other peelers with similar operation.

151

8.4 Conclusions

Mechanical peeling of two varieties of pumpkin (Jap and Jarrahdale) was simulated

and results were shown as two mathematical models. The output of modelling was

peeling rate (p. rate) and the input arranged with three main independent variables,

namely, the angular velocity of brushes (ωp), the degree of unevenness of product’s

surface (φ), and the shape of brush (λ). The results showed all three independent

variables can significantly affect the peeling rate. The relationship was revealed as

linear. The results revealed that the lower value of mechanical properties of the

Jarrahdale such as shear strength, cutting force, rupture force and skin toughness,

caused higher values of model coefficients involving C1, C2, and C3 for the same

conditions of experiments. The constant C0 was unexpectedly higher for the Jap than

for the Jarrahdale.

8.5 Summary

Mechanical peeling using an abrasive-cutter brush was simulated for the first time by

analysing the cutting process. The energy requirement of peeling was integrated for

two stages including penetration of the brush’s teeth into the peel and scratching

along the skin removing skin. Assuming a linear relationship of peeling rate with

total power required for peeling led to the final shape of the output for the model. A

large number of related parameters to the product and abrasive-cutter brush that

appeared in the model were arranged on the basis of three independent variables

using factorial technique. Those three industrially applicable factors were the angular

velocity of brushes (ωp), the degree of unevenness of product surface (φ), and the

shape of the brush (λ).The other variables that appeared in coefficients were assessed

indirectly for two different varieties of pumpkin (the Jap and Jarrahdale). The results

showed all considered parameters significantly affect the peeling rate. It was revealed

that for the same conditions of experiments, mechanical properties of the product can

significantly influence the results. Those effective parameters of the model related to

the product were shear strength (τ), the ratio of toughness for product and brush (γ),

the length of removed chip (h), and the dynamic coefficient of friction (μd). The

results were in good agreement with the measured mechanical properties such as

152

toughness, shear strength, cutting force, and rupture force in different states of the

two varieties.

Two derived mathematical models for both products were validated with

experimental results. Those models could be used for the same conditions of

experiments for these two varieties of pumpkin grown in Australia. The relationship

among different parameters of the product and abrasive-cutter brush and their effect

on the peeling rate can be used in industrial design of this innovative peeler and

development of other peelers with similar operation.

153

Chapter 9

Conclusions and perspectives

In this chapter, the thesis is concluded by providing a summary of the thesis and the

major findings of the research. Research related to this project which would require

more investigation is identified.

9.1 Thesis summary and conclusions

The main purpose of this thesis was to develop innovative mechanical peeling methods

for tough-skinned vegetables, using pumpkin as a case study, and modelling the

influence of parameters related to the product and peeling tool. Through the course of

this study the objectives set in section 1.2 have all been achieved.

An innovative mechanical peeling method, named as the abrasive-cutter brush, was

developed and the role of significant related parameters on the operation of this method

was shown in a mathematical model. The model has been developed on the basis of the

cutting process for the first time and has industrial application in the design of peeling

equipment.

Peeling is one of the most important preliminary stages of fruit and vegetable

processing. Tough-skinned vegetables such as pumpkin and melon currently are peeled

either semi-automatically or automatically. Circular shapes of rotating graters are

applied in semi-automatic method. Segments of the product are brought into contact

with the grater by an operator. This process is tedious and time consuming. In the latter

method, whole pumpkins are passed through automatic machines where the floor is

covered by many rotator disks (carborundum or blade). The main limitation of both

methods especially for varieties with an uneven surface is high peeling losses.

154

A detailed literature review has been conducted and showed that current peeling

methods include mechanical, thermal, and chemical methods and among these, the

mechanical peeling methods are preferred as they possess some important features of

the “ideal” method such as the maintenance of the freshness and integrity of the peeled

product. The literature review revealed that no systematic research has been undertaken

on mechanical peeling of tough-skinned vegetables. Generally the main cause of

unsuccessful attempts to investigate peeling, including mechanical methods, was the

low amount of attention paid to the properties of the product to be peeled. Therefore, to

introduce a successful mechanical peeling method, the development of the peeling

method in this research was carried out in four steps which were the study of

mechanical properties of tough-skinned vegetables, trial of possible mechanical peeling

tools, development of an innovative mechanical peeling method, and modelling of the

influence of parameters of the product and peeling tool in the proposed method.

In the first step, some mechanical properties of tough-skinned vegetables were studied.

There was no scientific definition of tough-skinned vegetables. Pumpkin and melon

(three varieties each) were chosen as the case studies. The selected varieties were

Jarrahdale, Jap, and Butternut for pumpkin; and Watermelon, Rockmelon, and

Honeydew for melon. The values of toughness, rupture force, cutting force, shear

strength force, shear strength, and static coefficient of friction of each variety were

determined for the first time in different states of product including skin, flesh and

unpeeled. Further, the contribution (%) of skin to different unpeeled properties was

determined. The results were statistically compared to find the similarities and

differences. The necessary range of different applied forces to peel vegetables was

specified. It was also found that tough-skinned vegetables can be defined by the ratio of

the skin’s shear strength to the same property of the unpeeled state.

In the second step, preliminary trials of different mechanical peeling methods (15

methods) were conducted. The results of the study of mechanical properties did help to

formulate better ideas for different tools for the trials. The test rig that enabled testing

of different mechanical peeling methods for different sized vegetables was designed

and manufactured for the first time. Four methods involving abrasive pads, abrasive

foams, a milling cutter, and an abrasive-cutter brush were developed for the first time

and found to have potential industrial application as mechanical peeling methods.

155

Those four methods were compared for peeling the Jap variety of pumpkin using a

fractural factorial design (Taguchi method). The criteria of comparison were higher and

more even peeling efficiencies in different areas of vegetable with lower peel losses.

The abrasive-cutter brush was found to be the best method compared to the other

methods. Estimated results for the optimum combination of the variables were

determined.

In the third step, further investigation was conducted to reveal the effects of different

parameters on peeling by the abrasive-cutter brush. The experiments were carried out

on two varieties of pumpkin, namely the Jap and Jarrahdale, using a full factorial

design. Results showed that the peeling rate (gr/min) as the dependent variable is

significantly affected by three independent variables which are the angular velocity of

brushes, the coarseness of brushes, and the location of peeling on the pumpkin. The

effects were discussed in detail in Chapter 7.

In the final step, mechanical peeling of the pumpkin using the abrasive-cutter brush

was simulated. This was the first simulation that has been carried out on mechanical

peeling of fruits and vegetables. The simulation was conducted on the basis of power

required in different steps of cutting and removing peel. The results were modelled

mathematically. The type and effect of different parameters related to the product and

abrasive-cutter brush on the peeling rate were determined. The model was verified by

experimental data of pumpkin varieties including Jap and Jarrahdale. The parameters

were estimated indirectly for each variety and their effect was discussed in Chapter 8.

The measured coefficients of the model proved the results of mechanical properties of

the Jap and Jarrahdale that were obtained in step one. The model showed it has the

ability to be used on the design of an abrasive-cutter brush for industrial application.

9.2 Directions for future research

Despite achieving the defined objectives in this thesis, there are still topics related to

this research that could be further investigated. Among them, the following areas are

emphasised:

156

• Determination of some other related mechanical properties of tough-

skinned vegetables

Further research is needed to determine values of other mechanical properties

that were not studied such as the dynamic coefficient of friction. Those

properties may be applied directly in the model or may indirectly affect the

peeling process. Furthermore, that investigation would be applied to develop the

classification of products on the basis of mechanical properties. It could also be

useful for determination of the range of applications for the proposed peeler and

lead to other new ideas for mechanical peeling.

• Investigation of the effects of environmental parameters on mechanical

properties of tough-skinned vegetables

In this research the mean values of mechanical properties in defined

environmental conditions (temperature and humidity) were determined and used.

As maintenance of these conditions is not always easy, it would be helpful to

investigate the relationship between environmental conditions and the

mechanical properties of tough-skinned vegetables.

• Investigation of the relationship between peeling rate and energy required

for mechanical peeling

This relationship was assumed to be linear in the developed model. It is

necessary to investigate this relationship and to determine the coefficient of this

function. This research can be conducted on different vegetables and on

different varieties. It would be useful to investigate whether there is any

relationship between the proposed coefficient and the mechanical properties for

different products.

• Development of the proposed mathematical model

157

The model can be extended in different ways. As discussed, there are still other

influencing parameters in the proposed model. The type and their effect should

be investigated to increase the accuracy and application ability of the model.

Further investigation is also needed to reveal any interaction between the

current determined variables. Some parameters, such as angular velocity of

vegetable holder, were assumed to be fixed. Increasing the accuracy of the

extended model can be achieved by considering such variables.

• Design and manufacture of an industrial peeler of tough-skinned

vegetables on the basis of the abrasive-cutter brush method

This research focused on revealing the best mechanical peeling method and

determination of the type and effects of the related parameters on the function

of the proposed method. As the ability of the method was proved in different

aspects, the manufactured peeler on the basis of the abrasive-cutter brush has

potential for wide application in the food processing industry. This is

emphasised because of the current lack of any satisfactory peeler for tough-

skinned vegetables especially those with uneven surface.

158

Appendices Appendix 1 1.1 Multiple comparisons of the mean of the mechanical properties 1.1.1 Multiple Comparisons of the mean of the unpeeled rupture force among varieties of pumpkin and melon Dependent Variable: Rupture force (N) of unpeeled

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale .83571 14.54 .954 -28.36 30.04 Butternut -15.99429 18.01 .379 -52.17 20.18 Rockmelon 149.48238(*) 16.31 .000 116.70 182.25 Honeydew 66.30196(*) 16.75 .000 32.64 99.95 Watermelon 77.18349(*) 16.31 .000 44.41 109.95

Jarrahdale Jap -.83571 14.54 .954 -30.04 28.36 Butternut -16.83000 15.37 .279 -47.71 14.05 Rockmelon 148.64667(*) 13.34 .000 121.83 175.45 Honeydew 65.46625(*) 13.88 .000 37.58 93.34 Watermelon 76.34778(*) 13.34 .000 49.53 103.15

Butternut Jap 15.99429 18.01 .379 -20.18 52.17 Jarrahdale 16.83000 15.37 .279 -14.05 47.71 Rockmelon 165.47667(*) 17.06 .000 131.20 199.75 Honeydew 82.29625(*) 17.48 .000 47.17 117.41 Watermelon 93.17778(*) 17.06 .000 58.90 127.45

Rockmelon Jap -149.48238(*) 16.31 .000 -182.25 -116.70 Jarrahdale -148.64667(*) 13.34 .000 -175.45 -121.83 Butternut -165.47667(*) 17.06 .000 -199.75 -131.20 Honeydew -83.18042(*) 15.73 .000 -114.78 -51.58 Watermelon -72.29889(*) 15.26 .000 -102.95 -41.64

Honeydew Jap -66.30196(*) 16.75 .000 -99.95 -32.64 Jarrahdale -65.46625(*) 13.88 .000 -93.34 -37.58 Butternut -82.29625(*) 17.48 .000 -117.41 -47.17 Rockmelon 83.18042(*) 15.73 .000 51.58 114.78 Watermelon 10.88153 15.73 .492 -20.71 42.48

Watermelon Jap -77.18349(*) 16.31 .000 -109.95 -44.41 Jarrahdale -76.34778(*) 13.34 .000 -103.15 -49.53 Butternut -93.17778(*) 17.06 .000 -127.45 -58.90 Rockmelon 72.29889(*) 15.26 .000 41.64 102.95 Honeydew -10.88153 15.73 .492 -42.48 20.71

* The mean difference is significant at the .05 level.

159

1.1.2 Multiple Comparisons of the mean of the skin rupture force among varieties of pumpkin and melon Dependent Variable: Rupture force (N) of skin

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 57.62015(*) 10.60 .000 36.41 78.82 Butternut -91.07467(*) 15.72 .000 -122.52 -59.62 Rockmelon 6.99242 12.33 .573 -17.67 31.65 Honeydew -56.72667(*) 15.72 .001 -88.17 -25.27 Watermelon -77.33167(*) 12.06 .000 -101.45 -53.20 Jarrahdale Jap -57.62015(*) 10.60 .000 -78.82 -36.41 Butternut -148.69482(*) 14.64 .000 -177.96 -119.42 Rockmelon -50.62773(*) 10.91 .000 -72.44 -28.80 Honeydew -114.34682(*) 14.64 .000 -143.62 -85.07 Watermelon -134.95182(*) 10.60 .000 -156.15 -113.74Butternut Jap 91.07467(*) 15.72 .000 59.62 122.52 Jarrahdale 148.69482(*) 14.64 .000 119.42 177.96 Rockmelon 98.06709(*) 15.93 .000 66.19 129.93 Honeydew 34.34800 18.68 .071 -3.02 71.71 Watermelon 13.74300 15.72 .386 -17.70 45.19 Rockmelon Jap -6.99242 12.33 .573 -31.65 17.67 Jarrahdale 50.62773(*) 10.91 .000 28.80 72.44 Butternut -98.06709(*) 15.93 .000 -129.93 -66.19 Honeydew -63.71909(*) 15.93 .000 -95.58 -31.84 Watermelon -84.32409(*) 12.33 .000 -108.98 -59.65 Honeydew Jap 56.72667(*) 15.72 .001 25.27 88.17 Jarrahdale 114.34682(*) 14.64 .000 85.07 143.62 Butternut -34.34800 18.68 .071 -71.71 3.02 Rockmelon 63.71909(*) 15.93 .000 31.84 95.58 Watermelon -20.60500 15.72 .195 -52.05 10.84 Watermelon Jap 77.33167(*) 12.06 .000 53.20 101.45 Jarrahdale 134.95182(*) 10.60 .000 113.74 156.15 Butternut -13.74300 15.72 .386 -45.19 17.70 Rockmelon 84.32409(*) 12.33 .000 59.65 108.98 Honeydew 20.60500 15.72 .195 -10.84 52.05

* The mean difference is significant at the .05 level.

160

1.1.3 Multiple Comparisons of the mean of the unpeeled toughness among varieties of pumpkin and melon Dependent Variable: toughness of unpeeled product

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale -16.988 108.69 .876 -235.31 201.33 Butternut 101.470 134.65 .455 -168.99 371.93 Rockmelon 99.482 121.97 .419 -145.51 344.47 Honeydew -376.92(*) 125.26 .004 -628.53 -125.31 Watermelon -300.56(*) 121.97 .017 -545.56 -55.57 Jarrahdale Jap 16.988 108.69 .876 -201.33 235.31 Butternut 118.45 114.93 .308 -112.39 349.31 Rockmelon 116.47 99.77 .249 -83.93 316.87 Honeydew -359.93(*) 103.77 .001 -568.37 -151.50 Watermelon -283.58(*) 99.77 .006 -483.98 -83.17 Butternut Jap -101.47 134.65 .455 -371.93 168.99 Jarrahdale -118.45 114.93 .308 -349.31 112.39 Rockmelon -1.98 127.56 .988 -258.21 254.23 Honeydew -478.39(*) 130.71 .001 -740.94 -215.84 Watermelon -402.04(*) 127.56 .003 -658.26 -145.81Rockmelon Jap -99.48 121.97 .419 -344.47 145.51 Jarrahdale -116.47 99.77 .249 -316.87 83.93 Butternut 1.98 127.56 .988 -254.23 258.21 Honeydew -476.40(*) 117.61 .000 -712.63 -240.18 Watermelon -400.05(*) 114.09 .001 -629.22 -170.87Honeydew Jap 376.92(*) 125.26 .004 125.31 628.53 Jarrahdale 359.93(*) 103.77 .001 151.50 568.37 Butternut 478.39(*) 130.71 .001 215.84 740.94 Rockmelon 476.40(*) 117.61 .000 240.18 712.63 Watermelon 76.35 117.61 .519 -159.82 312.58 Watermelon Jap 300.56(*) 121.97 .017 55.57 545.56 Jarrahdale 283.58(*) 99.77 .006 83.17 483.98 Butternut 402.04(*) 127.56 .003 145.81 658.26 Rockmelon 400.05(*) 114.09 .001 170.87 629.22 Honeydew -76.35 117.61 .519 -312.58 159.87

* The mean difference is significant at the .05 level.

161

1.1.4 Multiple Comparisons of the mean of the skin toughness among varieties of pumpkin and melon Dependent Variable: Toughness of skin

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 19.23 24.88 .442 -30.50 68.97 Butternut -96.05(*) 37.19 .012 -170.39 -21.70 Rockmelon -146.84(*) 29.16 .000 -205.14 -88.54 Honeydew -186.80(*) 37.19 .000 -261.15 -112.45 Watermelon -403.25(*) 28.52 .000 -460.27 -346.23 Jarrahdale Jap -19.237 24.88 .442 -68.97 30.50 Butternut -115.28(*) 34.47 .001 -184.20 -46.36 Rockmelon -166.08(*) 25.61 .000 -217.28 -114.87 Honeydew -206.04(*) 34.47 .000 -274.96 -137.12 Watermelon -422.49(*) 24.88 .000 -472.23 -372.75 Butternut Jap 96.05(*) 37.19 .012 21.70 170.39 Jarrahdale 115.28(*) 34.47 .001 46.36 184.20 Rockmelon -50.79 37.68 .183 -126.12 24.54 Honeydew -90.75(*) 44.19 .044 -179.09 -2.41 Watermelon -307.20(*) 37.19 .000 -381.55 -232.85 Rockmelon Jap 146.84(*) 29.16 .000 88.54 205.14 Jarrahdale 166.08(*) 25.61 .000 114.87 217.28 Butternut 50.79 37.68 .183 -24.54 126.12 Honeydew -39.95 37.68 .293 -115.29 35.37 Watermelon -256.41(*) 29.16 .000 -314.71 -198.10 Honeydew Jap 186.80(*) 37.19 .000 112.45 261.15 Jarrahdale 206.04(*) 34.47 .000 137.12 274.96 Butternut 90.75(*) 44.19 .044 2.41 179.09 Rockmelon 39.95 37.68 .293 -35.37 115.29 Watermelon -216.45(*) 37.19 .000 -290.79 -142.16 Watermelon Jap 403.25(*) 28.52 .000 346.23 460.27 Jarrahdale 422.49(*) 24.88 .000 372.75 472.23 Butternut 307.20(*) 37.19 .000 232.85 381.55 Rockmelon 256.41(*) 29.16 .000 198.10 314.71 Honeydew 216.45(*) 37.19 .000 142.10 290.79

* The mean difference is significant at the .05 level.

162

1.1.5 Multiple Comparisons of the mean of the unpeeled cutting force among varieties of pumpkin and melon Dependent Variable: Cutting force (N) of unpeeled product

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 5.83600(*) .85222 .000 4.11 7.55 Butternut -9.49200(*) 1.03455 .000 -11.57 -7.40 Rockmelon -1.20000 .85222 .166 -2.91 .51 Honeydew 1.44000 .97756 .148 -.53 3.41 Watermelon .82500 .85222 .338 -.89 2.54 Jarrahdale Jap -5.83600(*) .85222 .000 -7.55 -4.11 Butternut -15.32800(*) 1.01591 .000 -17.37 -13.28 Rockmelon -7.03600(*) .82949 .000 -8.70 -5.36 Honeydew -4.39600(*) .95781 .000 -6.32 -2.46 Watermelon -5.01100(*) .82949 .000 -6.68 -3.33 Butternut Jap 9.49200(*) 1.03455 .000 7.40 11.57 Jarrahdale 15.32800(*) 1.01591 .000 13.28 17.37 Rockmelon 8.29200(*) 1.01591 .000 6.24 10.33 Honeydew 10.93200(*) 1.12313 .000 8.66 13.19 Watermelon 10.31700(*) 1.01591 .000 8.26 12.36 Rockmelon Jap 1.20000 .85222 .166 -.51 2.91 Jarrahdale 7.03600(*) .82949 .000 5.36 8.70 Butternut -8.29200(*) 1.01591 .000 -10.33 -6.24 Honeydew 2.64000(*) .95781 .008 .70 4.57 Watermelon 2.02500(*) .82949 .019 .35 3.69 Honeydew Jap -1.44000 .97756 .148 -3.41 .53 Jarrahdale 4.39600(*) .95781 .000 2.46 6.32 Butternut -10.93200(*) 1.12313 .000 -13.19 -8.66 Rockmelon -2.64000(*) .95781 .008 -4.57 -.70 Watermelon -.61500 .95781 .524 -2.54 1.31 Watermelon Jap -.82500 .85222 .338 -2.54 .89 Jarrahdale 5.01100(*) .82949 .000 3.33 6.68 Butternut -10.31700(*) 1.01591 .000 -12.36 -8.26 Rockmelon -2.02500(*) .82949 .019 -3.69 -.35 Honeydew .61500 .95781 .524 -1.31 2.54

* The mean difference is significant at the .05 level.

163

1.1.6 Multiple Comparisons of the mean of the skin cutting force among varieties of pumpkin and melon Dependent Variable: Cutting force (N) of skin

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 6.59111(*) 1.09249 .000 4.39 8.78 Butternut -7.90111(*) 1.09249 .000 -10.09 -5.70 Rockmelon -3.23778(*) 1.06483 .004 -5.37 -1.09 Honeydew -.55528 1.39266 .692 -3.35 2.24 Watermelon -.71944 1.02193 .485 -2.77 1.33 Jarrahdale Jap -6.59111(*) 1.09249 .000 -8.78 -4.39 Butternut -14.49222(*) 1.09249 .000 -16.69 -12.29 Rockmelon -9.82889(*) 1.06483 .000 -11.97 -7.68 Honeydew -7.14639(*) 1.39266 .000 -9.94 -4.34 Watermelon -7.31056(*) 1.02193 .000 -9.36 -5.25 Butternut Jap 7.90111(*) 1.09249 .000 5.70 10.09 Jarrahdale 14.49222(*) 1.09249 .000 12.29 16.69 Rockmelon 4.66333(*) 1.06483 .000 2.52 6.80 Honeydew 7.34583(*) 1.39266 .000 4.54 10.14 Watermelon 7.18167(*) 1.02193 .000 5.12 9.23 Rockmelon Jap 3.23778(*) 1.06483 .004 1.09 5.37 Jarrahdale 9.82889(*) 1.06483 .000 7.68 11.97 Butternut -4.66333(*) 1.06483 .000 -6.80 -2.52 Honeydew 2.68250 1.37107 .056 -.07 5.44 Watermelon 2.51833(*) .99231 .015 .52 4.51 Honeydew Jap .55528 1.39266 .692 -2.24 3.35 Jarrahdale 7.14639(*) 1.39266 .000 4.34 9.94 Butternut -7.34583(*) 1.39266 .000 -10.14 -4.54 Rockmelon -2.68250 1.37107 .056 -5.44 .075 Watermelon -.16417 1.33802 .903 -2.85 2.52 Watermelon Jap .71944 1.02193 .485 -1.33 2.77 Jarrahdale 7.31056(*) 1.02193 .000 5.25 9.36 Butternut -7.18167(*) 1.02193 .000 -9.23 -5.15 Rockmelon -2.51833(*) .99231 .015 -4.51 -.52 Honeydew .16417 1.33802 .903 -2.52 2.85

* The mean difference is significant at the .05 level.

164

1.1.6 Multiple Comparisons of the mean of the flesh cutting force among varieties of pumpkin and melon Dependent Variable: Cutting force (N) of flesh

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale .94643(*) .20648 .000 .5277 1.3652 Butternut -3.06500(*) .22949 .000 -3.5304 -2.5996 Rockmelon 1.85214(*) .20648 .000 1.4334 2.2709 Honeydew 2.08643(*) .20648 .000 1.6677 2.5052 Watermelon 1.95833(*) .21637 .000 1.5195 2.3971 Jarrahdale Jap -.94643(*) .20648 .000 -1.3652 -.5277 Butternut -4.01143(*) .24534 .000 -4.5090 -3.5139 Rockmelon .90571(*) .22396 .000 .4515 1.3599 Honeydew 1.14000(*) .22396 .000 .6858 1.5942 Watermelon 1.01190(*) .23311 .000 .5391 1.4847 Butternut Jap 3.06500(*) .22949 .000 2.5996 3.5304 Jarrahdale 4.01143(*) .24534 .000 3.5139 4.5090 Rockmelon 4.91714(*) .24534 .000 4.4196 5.4147 Honeydew 5.15143(*) .24534 .000 4.6539 5.6490 Watermelon 5.02333(*) .25372 .000 4.5088 5.5379 Rockmelon Jap -1.85214(*) .20648 .000 -2.2709 -1.4334 Jarrahdale -.90571(*) .22396 .000 -1.3599 -.4515 Butternut -4.91714(*) .24534 .000 -5.4147 -4.4196 Honeydew .23429 .22396 .302 -.2199 .6885 Watermelon .10619 .23311 .651 -.3666 .5790 Honeydew Jap -2.08643(*) .20648 .000 -2.5052 -1.6677 Jarrahdale -1.14000(*) .22396 .000 -1.5942 -.6858 Butternut -5.15143(*) .24534 .000 -5.6490 -4.6539 Rockmelon -.23429 .22396 .302 -.6885 .2199 Watermelon -.12810 .23311 .586 -.6009 .3447 Watermelon Jap -1.95833(*) .21637 .000 -2.3971 -1.5195 Jarrahdale -1.01190(*) .23311 .000 -1.4847 -.5391 Butternut -5.02333(*) .25372 .000 -5.5379 -4.5088 Rockmelon -.10619 .23311 .651 -.5790 .3666 Honeydew .12810 .23311 .586 -.3447 .6009

* The mean difference is significant at the .05 level.

165

1.1.7 Multiple Comparisons of the mean of the unpeeled shear strength force among varieties of pumpkin and melon Dependent Variable: Shear strength force of unpeeled product

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 29.526 15.51 .063 -1.61 60.66 Butternut -2.831 22.40 .900 -47.78 42.12 Rockmelon 148.016(*) 20.01 .000 107.84 188.18 Honeydew 99.233(*) 20.01 .000 59.06 139.40 Watermelon 109.162(*) 19.21 .000 70.61 147.71 Jarrahdale Jap -29.526 15.51 .063 -60.65 1.61 Butternut -32.357 21.15 .132 -74.80 10.09 Rockmelon 118.489(*) 18.60 .000 81.14 155.83 Honeydew 69.707(*) 18.60 .000 32.36 107.04 Watermelon 79.635(*) 17.73 .000 44.03 115.23 Butternut Jap 2.831 22.40 .900 -42.12 47.78 Jarrahdale 32.357 21.15 .132 -10.09 74.80 Rockmelon 150.847(*) 24.64 .000 101.39 200.30 Honeydew 102.064(*) 24.64 .000 52.61 151.51 Watermelon 111.993(*) 23.99 .000 63.84 160.14 Rockmelon Jap -148.016(*) 20.01 .000 -188.18 -107.84 Jarrahdale -118.489(*) 18.60 .000 -155.83 -81.14 Butternut -150.847(*) 24.64 .000 -200.30 -101.39 Honeydew -48.782(*) 22.49 .035 -93.92 -3.63 Watermelon -38.854 21.78 .080 -82.56 4.85 Honeydew Jap -99.233(*) 20.01 .000 -139.40 -59.06 Jarrahdale -69.707(*) 18.60 .000 -107.04 -32.36 Butternut -102.064(*) 24.64 .000 -151.51 -52.61 Rockmelon 48.782(*) 22.49 .035 3.63 93.92 Watermelon 9.928 21.78 .650 -33.78 53.64 Watermelon Jap -109.162(*) 19.21 .000 -147.71 -70.61 Jarrahdale -79.635(*) 17.73 .000 -115.23 -44.03 Butternut -111.993(*) 23.99 .000 -160.14 -63.84 Rockmelon 38.854 21.78 .080 -4.85 82.56 Honeydew -9.928 21.78 .650 -53.64 33.78

* The mean difference is significant at the .05 level.

166

1.1.8 Multiple Comparisons of the mean of the skin shear strength force among varieties of pumpkin and melon Dependent Variable: Shear strength force of skin

(I) Vegetable

(J) Vegetable

Mean Difference (I-J)

Std. Error Sig.

95% Confidence Interval

Lower Bound

Upper Bound

Jap Jarrahdale 33.82658(*) 10.60 .002 12.64 55.01 Butternut -77.01300(*) 16.30 .000 -109.57 -44.45 Rockmelon -2.51667 12.01 .835 -26.52 21.48 Honeydew -38.92700(*) 16.30 .020 -71.48 -6.36 Watermelon -43.04000(*) 12.01 .001 -67.04 -19.03Jarrahdale Jap -33.82658(*) 10.60 .002 -55.01 -12.64 Butternut -110.83958(*) 16.21 .000 -143.21 -78.46 Rockmelon -36.34325(*) 11.89 .003 -60.09 -12.59 Honeydew -72.75358(*) 16.21 .000 -105.12 -40.37 Watermelon -76.86658(*) 11.89 .000 -100.61 -53.11Butternut Jap 77.01300(*) 16.30 .000 44.45 109.57 Jarrahdale 110.83958(*) 16.21 .000 78.46 143.21 Rockmelon 74.49633(*) 17.16 .000 40.21 108.78 Honeydew 38.08600 20.39 .066 -2.65 78.82 Watermelon 33.97300 17.16 .052 -.31 68.25Rockmelon Jap 2.51667 12.01 .835 -21.48 26.52 Jarrahdale 36.34325(*) 11.89 .003 12.59 60.09 Butternut -74.49633(*) 17.16 .000 -108.78 -40.21 Honeydew -36.41033(*) 17.16 .038 -70.69 -2.12 Watermelon -40.52333(*) 13.16 .003 -66.81 -14.22Honeydew Jap 38.92700(*) 16.30 .020 6.36 71.48 Jarrahdale 72.75358(*) 16.21 .000 40.37 105.12 Butternut -38.08600 20.39 .066 -78.82 2.65 Rockmelon 36.41033(*) 17.16 .038 2.12 70.69 Watermelon -4.11300 17.16 .811 -38.39 30.17Watermelon Jap 43.04000(*) 12.01 .001 19.03 67.04 Jarrahdale 76.86658(*) 11.89 .000 53.11 100.61 Butternut -33.97300 17.16 .052 -68.25 .31 Rockmelon 40.52333(*) 13.16 .003 14.22 66.81 Honeydew 4.11300 17.16 .811 -30.17 38.39

* The mean difference is significant at the .05 level.

167

1.1.9 Multiple Comparisons of the mean of the flesh shear strength force among varieties of pumpkin and melon Dependent Variable: Shear strength force of flesh

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 20.15977(*) 4.51 .000 11.07 29.24 Butternut -.13150 5.53 .981 -11.27 11.01 Rockmelon 55.20167(*) 4.43 .000 46.27 64.12 Honeydew 48.07650(*) 5.53 .000 36.93 59.22 Watermelon 54.14705(*) 4.51 .000 45.06 63.23 Jarrahdale Jap -20.15977(*) 4.51 .000 -29.24 -11.07 Butternut -20.29127(*) 5.23 .000 -30.83 -9.74 Rockmelon 35.04189(*) 4.05 .000 26.88 43.20 Honeydew 27.91673(*) 5.23 .000 17.37 38.46 Watermelon 33.98727(*) 4.14 .000 25.65 42.32 Butternut Jap .13150 5.53 .981 -11.01 11.27 Jarrahdale 20.29127(*) 5.23 .000 9.74 30.83 Rockmelon 55.33317(*) 5.16 .000 44.92 65.73 Honeydew 48.20800(*) 6.14 .000 35.84 60.57 Watermelon 54.27855(*) 5.23 .000 43.73 64.82 Rockmelon Jap -55.20167(*) 4.43 .000 -64.12 -46.27 Jarrahdale -35.04189(*) 4.05 .000 -43.20 -26.88 Butternut -55.33317(*) 5.16 .000 -65.73 -44.92 Honeydew -7.12517 5.16 .175 -17.53 3.28 Watermelon -1.05462 4.05 .796 -9.21 7.10 Honeydew Jap -48.07650(*) 5.53 .000 -59.22 -36.93 Jarrahdale -27.91673(*) 5.23 .000 -38.46 -17.37 Butternut -48.20800(*) 6.14 .000 -60.57 -35.84 Rockmelon 7.12517 5.16 .175 -3.28 17.53 Watermelon 6.07055 5.23 .252 -4.47 16.61 Watermelon Jap -54.14705(*) 4.51 .000 -63.23 -45.06 Jarrahdale -33.98727(*) 4.14 .000 -42.32 -25.65 Butternut -54.27855(*) 5.23 .000 -64.82 -43.73 Rockmelon 1.05462 4.05 .796 -7.10 9.21 Honeydew -6.07055 5.23 .252 -16.61 4.47

* The mean difference is significant at the .05 level.

168

1.1.10 Multiple Comparisons of the mean of the unpeeled shear strength among varieties of pumpkin and melon Dependent Variable: Shear strength of unpeeled product

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale .64250(*) .11424 .000 .4135 .8715 Butternut .13450 .16653 .423 -.1994 .4684 Rockmelon 1.91250(*) .14880 .000 1.6142 2.2108 Honeydew 1.77875(*) .14280 .000 1.4924 2.0651 Watermelon 1.88750(*) .14280 .000 1.6012 2.1738 Jarrahdale Jap -.64250(*) .11424 .000 -.8715 -.4135 Butternut -.50800(*) .15643 .002 -.8216 -.1944 Rockmelon 1.27000(*) .13740 .000 .9945 1.5455 Honeydew 1.13625(*) .13088 .000 .8739 1.3986 Watermelon 1.24500(*) .13088 .000 .9826 1.5074 Butternut Jap -.13450 .16653 .423 -.4684 .1994 Jarrahdale .50800(*) .15643 .002 .1944 .8216 Rockmelon 1.77800(*) .18319 .000 1.4107 2.1453 Honeydew 1.64425(*) .17836 .000 1.2867 2.0018 Watermelon 1.75300(*) .17836 .000 1.3954 2.1106 Rockmelon Jap -1.91250(*) .14880 .000 -2.2108 -1.6142 Jarrahdale -1.27000(*) .13740 .000 -1.5455 -.9945 Butternut -1.77800(*) .18319 .000 -2.1453 -1.4107 Honeydew -.13375 .16192 .412 -.4584 .1909 Watermelon -.02500 .16192 .878 -.3496 .2996 Honeydew Jap -1.77875(*) .14280 .000 -2.0651 -1.4924 Jarrahdale -1.13625(*) .13088 .000 -1.3986 -.8739 Butternut -1.64425(*) .17836 .000 -2.0018 -1.2867 Rockmelon .13375 .16192 .412 -.1909 .4584 Watermelon .10875 .15643 .490 -.2049 .4224 Watermelon Jap -1.88750(*) .14280 .000 -2.1738 -1.6012 Jarrahdale -1.24500(*) .13088 .000 -1.5074 -.9826 Butternut -1.75300(*) .17836 .000 -2.1106 -1.3954 Rockmelon .02500 .16192 .878 -.2996 .3496 Honeydew -.10875 .15643 .490 -.4224 .2049

* The mean difference is significant at the .05 level.

169

1.1.11 Multiple Comparisons of the mean of the skin shear strength among varieties of pumpkin and melon Dependent Variable: Shear strength of skin

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig. 95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale .57389(*) .25 .029 .05 1.08 Butternut .98389(*) .39 .016 .19 1.77 Rockmelon 2.58306(*) .29 .000 2.00 3.16 Honeydew 1.04389(*) .39 .010 .25 1.83 Watermelon 2.28556(*) .29 .000 1.70 2.86 Jarrahdale Jap -.57389(*) .25 .029 -1.08 -.05 Butternut .41000 .39 .301 -.37 1.19 Rockmelon 2.00917(*) .28 .000 1.43 2.58 Honeydew .47000 .39 .237 -.31 1.25 Watermelon 1.71167(*) .28 .000 1.13 2.28 Butternut Jap -.98389(*) .39 .016 -1.77 -.19 Jarrahdale -.41000 .39 .301 -1.19 .37 Rockmelon 1.59917(*) .41 .000 .76 2.43 Honeydew .06000 .49 .904 -.92 1.04 Watermelon 1.30167(*) .41 .003 .46 2.13 Rockmelon Jap -2.58306(*) .29 .000 -3.16 -2.00 Jarrahdale -2.00917(*) .28 .000 -2.58 -1.43 Butternut -1.59917(*) .41 .000 -2.43 -.76 Honeydew -1.53917(*) .41 .000 -2.37 -.70 Watermelon -.29750 .31 .356 -.93 .34 Honeydew Jap -1.04389(*) .39 .010 -1.83 -.25 Jarrahdale -.47000 .39 .237 -1.25 .31 Butternut -.06000 .49 .904 -1.04 .92 Rockmelon 1.53917(*) .41 .000 .70 2.37 Watermelon 1.24167(*) .41 .004 .40 2.07 Watermelon Jap -2.28556(*) .29 .000 -2.86 -1.70 Jarrahdale -1.71167(*) .28 .000 -2.28 -1.13 Butternut -1.30167(*) .41 .003 -2.13 -.46 Rockmelon .29750 .31 .356 -.34 .93 Honeydew -1.24167(*) .41 .004 -2.07 -.40

* The mean difference is significant at the .05 level.

170

1.1.12 Multiple Comparisons of the mean of the flesh shear strength among varieties of pumpkin and melon Dependent Variable: Shear strength of flesh

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale -.09920(*) .04333 .027 -.1864 -.0120 Butternut -.23575(*) .05316 .000 -.3428 -.1287 Rockmelon .21125(*) .04256 .000 .1256 .2969 Honeydew .22425(*) .05316 .000 .1172 .3313 Watermelon .20261(*) .04333 .000 .1154 .2898 Jarrahdale Jap .09920(*) .04333 .027 .0120 .1864 Butternut -.13655(*) .05029 .009 -.2378 -.0353 Rockmelon .31045(*) .03892 .000 .2321 .3888 Honeydew .32345(*) .05029 .000 .2222 .4247 Watermelon .30182(*) .03976 .000 .2218 .3819 Butternut Jap .23575(*) .05316 .000 .1287 .3428 Jarrahdale .13655(*) .05029 .009 .0353 .2378 Rockmelon .44700(*) .04963 .000 .3471 .5469 Honeydew .46000(*) .05897 .000 .3413 .5787 Watermelon .43836(*) .05029 .000 .3371 .5396 Rockmelon Jap -.21125(*) .04256 .000 -.2969 -.1256 Jarrahdale -.31045(*) .03892 .000 -.3888 -.2321 Butternut -.44700(*) .04963 .000 -.5469 -.3471 Honeydew .01300 .04963 .795 -.0869 .1129 Watermelon -.00864 .03892 .825 -.0870 .0697 Honeydew Jap -.22425(*) .05316 .000 -.3313 -.1172 Jarrahdale -.32345(*) .05029 .000 -.4247 -.2222 Butternut -.46000(*) .05897 .000 -.5787 -.3413 Rockmelon -.01300 .04963 .795 -.1129 .0869 Watermelon -.02164 .05029 .669 -.1229 .0796 Watermelon Jap -.20261(*) .04333 .000 -.2898 -.1154 Jarrahdale -.30182(*) .03976 .000 -.3819 -.2218 Butternut -.43836(*) .05029 .000 -.5396 -.3371 Rockmelon .00864 .03892 .825 -.0697 .0870 Honeydew .02164 .05029 .669 -.0796 .1229

* The mean difference is significant at the .05 level.

171

1.2 Multiple Comparisons of contribution of skin to the mechanical properties 1.2.1. Multiple Comparisons of contribution of skin to the unpeeled rupture force among varieties of pumpkin and melon Dependent Variable: Rupture force contribution (%)

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 6.66034 3.819 .088 -1.0321 14.3528 Butternut -50.02543(*) 4.979 .000 -60.0552 -39.9957 Rockmelon -66.76518(*) 4.401 .000 -75.6303 -57.9000 Honeydew -59.17743(*) 4.979 .000 -69.2072 -49.1477 Watermelon -74.42587(*) 4.285 .000 -83.0581 -65.7936Jarrahdale Jap -6.66034 3.819 .088 -14.3528 1.0321 Butternut -56.68576(*) 4.326 .000 -65.4001 -47.9714 Rockmelon -73.42551(*) 3.646 .000 -80.7695 -66.0815 Honeydew -65.83776(*) 4.326 .000 -74.5521 -57.1234 Watermelon -81.08621(*) 3.505 .000 -88.1473 -74.0251Butternut Jap 50.02543(*) 4.979 .000 39.9957 60.0552 Jarrahdale 56.68576(*) 4.326 .000 47.9714 65.4001 Rockmelon -16.73975(*) 4.848 .001 -26.5048 -6.9747 Honeydew -9.15200 5.378 .096 -19.9854 1.6814 Watermelon -24.40044(*) 4.743 .000 -33.9546 -14.8463Rockmelon Jap 66.76518(*) 4.401 .000 57.9000 75.6303 Jarrahdale 73.42551(*) 3.646 .000 66.0815 80.7695 Butternut 16.73975(*) 4.848 .001 6.9747 26.5048 Honeydew 7.58775 4.848 .125 -2.1773 17.3528 Watermelon -7.66069 4.132 .070 -15.9839 .6625 Honeydew Jap 59.17743(*) 4.979 .000 49.1477 69.2072 Jarrahdale 65.83776(*) 4.326 .000 57.1234 74.5521 Butternut 9.15200 5.378 .096 -1.6814 19.9854 Rockmelon -7.58775 4.848 .125 -17.3528 2.1773 Watermelon -15.24844(*) 4.743 .002 -24.8026 -5.6943Watermelon Jap 74.42587(*) 4.285 .000 65.7936 83.0581 Jarrahdale 81.08621(*) 3.505 .000 74.0251 88.1473 Butternut 24.40044(*) 4.743 .000 14.8463 33.9546 Rockmelon 7.66069 4.132 .070 -.6625 15.9839 Honeydew 15.24844(*) 4.743 .002 5.6943 24.8026

* The mean difference is significant at the .05 level.

172

1.2.2 Multiple Comparisons of contribution of skin to the unpeeled toughness among varieties of pumpkin and melon Dependent Variable: Toughness contribution (%)

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale -.3214 4.738 .946 -9.8602 9.2174 Butternut -20.2054(*) 6.178 .002 -32.6425 -7.7684 Rockmelon -26.8392(*) 5.317 .000 -37.5433 -16.1351 Honeydew -19.5534(*) 6.178 .003 -31.9905 -7.1164 Watermelon -48.2414(*) 5.317 .000 -58.9456 -37.5373Jarrahdale Jap .3214 4.738 .946 -9.2174 9.8602 Butternut -19.8840(*) 5.368 .001 -30.6900 -9.0780 Rockmelon -26.5177(*) 4.349 .000 -35.2737 -17.7618 Honeydew -19.2320(*) 5.368 .001 -30.0380 -8.4260 Watermelon -47.9200(*) 4.349 .000 -56.6759 -39.1641Butternut Jap 20.2054(*) 6.178 .002 7.7684 32.6425 Jarrahdale 19.8840(*) 5.368 .001 9.0780 30.6900 Rockmelon -6.6337 5.885 .266 -18.4811 5.2135 Honeydew .6520 6.673 .923 -12.7816 14.0856 Watermelon -28.0360(*) 5.885 .000 -39.8833 -16.1887Rockmelon Jap 26.8392(*) 5.317 .000 16.1351 37.5433 Jarrahdale 26.5177(*) 4.349 .000 17.7618 35.2737 Butternut 6.6337 5.885 .266 -5.2135 18.4811 Honeydew 7.2857 5.885 .222 -4.5615 19.1331 Watermelon -21.4022(*) 4.974 .000 -31.4150 -11.3894Honeydew Jap 19.5534(*) 6.178 .003 7.1164 31.9905 Jarrahdale 19.2320(*) 5.368 .001 8.4260 30.0380 Butternut -.6520 6.673 .923 -14.0856 12.7816 Rockmelon -7.2857 5.885 .222 -19.1331 4.5615 Watermelon -28.6880(*) 5.885 .000 -40.5353 -16.8407Watermelon Jap 48.2414(*) 5.317 .000 37.5373 58.9456 Jarrahdale 47.9200(*) 4.349 .000 39.1641 56.6759 Butternut 28.0360(*) 5.885 .000 16.1887 39.8833 Rockmelon 21.4022(*) 4.974 .000 11.3894 31.4150 Honeydew 28.6880(*) 5.885 .000 16.8407 40.5353

* The mean difference is significant at the .05 level.

173

1.2.3 Multiple Comparisons of contribution of skin to the unpeeled cutting force among varieties of pumpkin and melon Dependent Variable: Cutting force contribution (%)

(I) vegetable (J) vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 31.3144(*) 9.436 .002 12.2268 50.4021 Butternut .2444 9.986 .981 -19.9561 20.4450 Rockmelon -17.6205(*) 8.226 .039 -34.2608 -.9803 Honeydew -17.0935 9.986 .095 -37.2941 3.1070 Watermelon -14.8145 8.226 .079 -31.4548 1.8257 Jarrahdale Jap -31.3144(*) 9.436 .002 -50.4021 -12.2268 Butternut -31.0700(*) 10.842 .007 -53.0001 -9.1399 Rockmelon -48.9350(*) 9.246 .000 -67.6370 -30.2330 Honeydew -48.4080(*) 10.842 .000 -70.3381 -26.4779 Watermelon -46.1290(*) 9.246 .000 -64.8310 -27.4270Butternut Jap -.2444 9.986 .981 -20.4450 19.9561 Jarrahdale 31.0700(*) 10.842 .007 9.1399 53.0001 Rockmelon -17.8650 9.806 .076 -37.7015 1.9715 Honeydew -17.3380 11.324 .134 -40.2432 5.5672 Watermelon -15.0590 9.806 .133 -34.8955 4.7775 Rockmelon Jap 17.6205(*) 8.226 .039 .9803 34.2608 Jarrahdale 48.9350(*) 9.246 .000 30.2330 67.6370 Butternut 17.8650 9.806 .076 -1.9715 37.7015 Honeydew .5270 9.806 .957 -19.3095 20.3635 Watermelon 2.8060 8.007 .728 -13.3904 19.0024Honeydew Jap 17.0935 9.986 .095 -3.1070 37.2941 Jarrahdale 48.4080(*) 10.842 .000 26.4779 70.3381 Butternut 17.3380 11.324 .134 -5.5672 40.2432 Rockmelon -.5270 9.806 .957 -20.3635 19.3095 Watermelon 2.2790 9.806 .817 -17.5575 22.1155Watermelon Jap 14.8145 8.226 .079 -1.8257 31.4548 Jarrahdale 46.1290(*) 9.246 .000 27.4270 64.8310 Butternut 15.0590 9.806 .133 -4.7775 34.8955 Rockmelon -2.8060 8.007 .728 -19.0024 13.3904 Honeydew -2.2790 9.806 .817 -22.1155 17.5575

* The mean difference is significant at the .05 level.

174

1.2.4 Multiple Comparisons of contribution of skin to the unpeeled maximum shearing strength force among varieties of pumpkin and melon Dependent Variable: Maximum shearing strength force contribution (%)

(I) Vegetable

(J) Vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale 14.72430(*) 5.743 .013 3.1873 26.2613 butternut -24.87433(*) 8.291 .004 -41.5287 -8.2200 Rockmelon -52.72976(*) 7.408 .000 -67.6102 -37.8493 Honeydew -46.91033(*) 8.291 .000 -63.5647 -30.2560 Watermelon -54.83583(*) 7.110 .000 -69.1168 -40.5549Jarrahdale Jap -14.72430(*) 5.743 .013 -26.2613 -3.1873 butternut -39.59863(*) 7.829 .000 -55.3248 -23.8725 Rockmelon -67.45406(*) 6.887 .000 -81.2878 -53.6203 Honeydew -61.63463(*) 7.829 .000 -77.3608 -45.9085 Watermelon -69.56013(*) 6.565 .000 -82.7469 -56.3734butternut Jap 24.87433(*) 8.291 .004 8.2200 41.5287 Jarrahdale 39.59863(*) 7.829 .000 23.8725 55.3248 Rockmelon -27.85543(*) 9.121 .004 -46.1758 -9.5350 Honeydew -22.03600(*) 9.851 .030 -41.8243 -2.2477 Watermelon -29.96150(*) 8.880 .001 -47.7984 -12.1246Rockmelon Jap 52.72976(*) 7.408 .000 37.8493 67.6102 Jarrahdale 67.45406(*) 6.887 .000 53.6203 81.2878 butternut 27.85543(*) 9.121 .004 9.5350 46.1758 Honeydew 5.81943 9.121 .526 -12.5010 24.1398 Watermelon -2.10607 8.062 .795 -18.2992 14.0870 Honeydew Jap 46.91033(*) 8.291 .000 30.2560 63.5647 Jarrahdale 61.63463(*) 7.829 .000 45.9085 77.3608 butternut 22.03600(*) 9.851 .030 2.2477 41.8243 Rockmelon -5.81943 9.121 .526 -24.1398 12.5010 Watermelon -7.92550 8.880 .376 -25.7624 9.9114 Watermelon jap 54.83583(*) 7.110 .000 40.5549 69.1168 Jarrahdale 69.56013(*) 6.565 .000 56.3734 82.7469 butternut 29.96150(*) 8.880 .001 12.1246 47.7984 Rockmelon 2.10607 8.062 .795 -14.0870 18.2992 Honeydew 7.92550 8.880 .376 -9.9114 25.7624

* The mean difference is significant at the .05 level.

175

1.2.5 Multiple Comparisons of contribution of skin to the unpeeled shearing strength among varieties of pumpkin and melon Dependent Variable: Shear strength contribution (%)

(I) vegetable(J)

vegetable

Mean Difference

(I-J) Std.

Error Sig.95% Confidence

Interval

Lower Bound

Upper Bound

Jap Jarrahdale -7.9733 18.440 .667 -45.012 29.065 Butternut 43.0586 26.620 .112 -10.409 96.526 Rockmelon 3.9481 23.784 .869 -43.824 51.721 Honeydew -191.1873(*) 26.620 .000 -244.655 -137.719 Watermelon -33.5558 22.826 .148 -79.404 12.292 Jarrahdale Jap 7.9733 18.440 .667 -29.065 45.012 Butternut 51.0320(*) 25.136 .048 .544 101.520 Rockmelon 11.9214 22.111 .592 -32.491 56.334 Honeydew -183.2140(*) 25.136 .000 -233.702 -132.726 Watermelon -25.5825 21.077 .231 -67.918 16.753 Butternut Jap -43.0586 26.620 .112 -96.526 10.409 Jarrahdale -51.0320(*) 25.136 .048 -101.520 -.544 Rockmelon -39.1105 29.283 .188 -97.927 19.706 Honeydew -234.2460(*) 31.629 .000 -297.775 -170.716 Watermelon -76.6145(*) 28.510 .010 -133.879 -19.349Rockmelon Jap -3.9481 23.784 .869 -51.721 43.824 Jarrahdale -11.9214 22.111 .592 -56.334 32.491 Butternut 39.1105 29.283 .188 -19.706 97.927 Honeydew -195.1354(*) 29.283 .000 -253.952 -136.318 Watermelon -37.5039 25.882 .154 -89.491 14.483 Honeydew Jap 191.1873(*) 26.620 .000 137.719 244.655 Jarrahdale 183.2140(*) 25.136 .000 132.726 233.702 Butternut 234.2460(*) 31.629 .000 170.716 297.775 Rockmelon 195.1354(*) 29.283 .000 136.318 253.952 Watermelon 157.6315(*) 28.510 .000 100.366 214.896Watermelon Jap 33.5558 22.826 .148 -12.292 79.404 Jarrahdale 25.5825 21.077 .231 -16.753 67.918 Butternut 76.6145(*) 28.510 .010 19.349 133.879 Rockmelon 37.5039 25.882 .154 -14.483 89.491 Honeydew -157.6315(*) 28.510 .000 -214.896 -100.366

* The mean difference is significant at the .05 level.

176

1.3 Mechanical properties of varieties of melon and pumpkin

in three different states including skin, unpeeled, and flesh

(Mean ± Standard Deviation)

Properties

Varieties Cases Rupture forc

(N)

Toughness

(N. mm)

Cutting forc

(N)

Max. Shear

Strength force

(N)

Shear

strength

(N.mm-2)

Skin 40.68±19 13.87±7 2.82±0.34 57.84±16 2.72±1.06

Flesh 1.41±0.51 43.86±13 0.41±0.08

Jarrahdale

Unpeeled 248.66±45 719.72±293 5.15±0.84 218.18±61 1.78±0.40

Skin 98.30±54 33.10±29 9.41±3 91.67±55 3.29 ±0.99

Flesh 2.36±0.51 64.02±5 0.31±0.07

Jap

Unpeeled 249.49±27 702.73±146 10.99±2 247.71±34 2.42±0.31

Skin 189.37±14 129.16±34 17.31±0.62 168.68±19 2.31±0.22

Flesh 5.43±0.64 64.15±22 0.55±0.24

Butternut

Unpeeled 265.49±18 601.26±141 20.48±1 250.54±10 2.28±0.21

Skin 91.31±16 179.95±85 12.65±3 94.19±7 0.71±0.13

Flesh 0.51±0.29 8.82±2 0.10±0.05

Rockmelon

Unpeeled 100.01±14 603.25±168 12.19±1 99.69±16 0.51±0.16

Skin 155.03±33 219.91±176 9.96±4 130.60±24 2.25±0.63

Flesh 0.27±0.09 15.94±1 0.09±0.03

Honeydew

Unpeeled 183.19±36 1079.66±137 9.55±2 148.47±27 0.64±0.28

Skin 175.63±20 436.36±89 10.13±1 134.71±23 1.00±0.21

Flesh 0.40±0.12 9.87±3 0.11±0.03

Watermelon

Unpeeled 172.31±15 1003.306±34 10.16±1 138.54±25 0.53±0.13

177

1.4 Relative contribution (%) of skin to different mechanical

properties for three pumpkin varieties including Jarrahdale,

Jap, and Butternut (Mean ± Standard Deviation)

Properties

Varieties

Rupture

force

N

Toughness

N. mm

Cutting

force

N

Max. shear

Strength force

N

Shear

strength

N.mm-2

Jarrahdale 16.17±9 2.13±1 53.88±12 27.83±7 153.03±55

Jap 22.83±7 1.80±0.74 85.19±23 42.56±27 145.05±41

Butternut 72.86±6 22.01±9 84.95±8 67.43±8 101.99±16

Melon 89.60±6 28.64±14 102.81±17 95.29±8 141.10±30

Honeydew 82.01±16 21.36±18 102.28±25 89.47±17 336.24±86

Watermelon 97.26±2 50.05±15 100.00±14 97.39±8 178.61±43

178

1.5 Drawings of instrumentations 1.5.1 The cutting indentor

179

1.5.2 The skin holder

180

1.5.3 The skin holder (details)

181

1.5.4 The skin holder (details)

182

1.5.5 The cutter of unpeeled sample

183

1.5.6 Spherical end indentor

184

Appendix 2 2.1 Test rig

185

2.1.1 Table of test rig

186

2.1.2 The chassis of test rig

187

2.1.3 The plate of test rig (N.10 in appendix 4.2)

188

2.1.4 The chamber of test rig

189

2.1.5 The vegetable holder

190

2.1.6 The vegetable holder (shaft)

191

2.1.7 The pyramid of knifes

192

2.1.8 The peeler head

193

2.1.9 The peeler head (details)

2.1.10 The peeler head (shaft)

194

2.1.11 The peeler head (flap)

195

2.1.12.1 The peeler head (frame)

196

Appendix 3 3.1 Experimental results of using milling cutter

Exp.no. Peel losses %/min

Peeling efficiency %/min

Concave area

Peeling efficiency %/min

Convex area 1 0.4 25 25 2 0.1675 16.25 25 3 0.26 17.5 25 4 0.48 25 25 5 0.4425 17.5 25 6 0.2875 23.75 25 7 0.9725 22.5 25 8 0.1725 11.25 20 9 0.1725 12.5 22.5

3.2 Experimental results of using abrasive pads

Exp.no. Peel losses %/min

Peeling efficiency %/min

Concave area

Peeling efficiency %/min

Convex area 1 0.0615 3.25 5 2 0.042 4.5 4.75 3 0.015 0.5 3.25 4 0.0195 1.5 3.5 5 0.049 2.25 4.75 6 0.0355 4 4.25 7 0.2345 5 5 8 0.027 0.75 3.5 9 0.006 0.25 0.5

197

3.3 Experimental results of using abrasive foams

Exp.no. Peel losses %/min

Peeling efficiency %/min

Concave area

Peeling efficiency %/min

Convex area 1 0.26025 22.5 25 2 0.244 22.5 22.5 3 0.37575 25 25 4 0.3405 22.5 22.5 5 0.30925 22.5 22.5 6 1.09575 12.5 17.5 7 0.70325 25 25 8 0.58075 23.75 23.75 9 0.395 25 25 10 0.1555 15 15 11 1.24 15 17.5 12 0.10625 12.5 13.75 13 0.22925 15 17.5 14 0.38425 21.25 21.25 15 0.19725 13.75 16.25 16 0.66125 25 25 17 0.805 25 25 18 0.752 25 25 19 0.41225 20 17.5 20 0.199 25 17.5 21 0.081 3.75 5 22 0.61475 25 25 23 0.13975 12.5 13.75 24 0.058 6.25 8.75 25 1.89125 25 25 26 1.9975 25 25 27 0.5085 25 25

198

3.4 Experimental results of using abrasive-cutter brush

Exp.no. Peel losses %/min

Peeling efficiency %/min

Concave area

Peeling efficiency %/min

Convex area 1 0.455 42.5 42.5 2 1.4975 57.5 80 3 0.6075 48.75 48.75 4 2.3625 82.5 82.5 5 1.4675 78.75 78.75 6 1.2975 57.5 70 7 0.6075 50 65 8 1.6025 68.75 68.75 9 1.17 71.25 75

199

Appendix 4 4.1 Normality assessment of peeling rate (g/min) of Jap and Jarrahdale varieties 4.1.1 Jarrahdale variety before transformation

Kolmogorov-Smirnov(a) Shapiro-Wilk Statistic df Sig. Statistic df Sig.

Peeling rate .117 64 .029 .881 64 .000

a Lilliefors Significance Correction Plosses Stem-and-Leaf Plot Frequency Stem & Leaf 6.00 0 . 345777 22.00 1 . 0000122333444556667899 13.00 2 . 0123444788899 12.00 3 . 022355556899 4.00 4 . 2247 1.00 5 . 2 2.00 6 . 23 4.00 Extremes (>=7.3) Stem width: 1.00 Each leaf: 1 case(s)

-2 0 2 4 6 8 10

Observed Value

-4

-2

0

2

4

Expe

cted

Nor

mal

Normal Q-Q Plot of Plosses

0 2 4 6 8 10

Observed Value

-0.4

-0.2

0.0

0.2

0.4

0.6

0.8

1.0

Dev

from

Nor

mal

Detrended Normal Q-Q Plot of Plosses

200

Plosses

0.00

2.00

4.00

6.00

8.00

10.00

481532

13

0.00 2.00 4.00 6.00 8.00 10.00

Plosses

0

2

4

6

8

10

12

14

Freq

uenc

y

Mean = 2.7356Std. Dev. = 1.88944N = 64

Histogram

201

4.1.2 Jap variety before transformation

Kolmogorov-Smirnov(a) Shapiro-Wilk Statistic df Sig. Statistic df Sig.

Peeling rate .169 64 .000 .807 64 .000

a Lilliefors Significance Correction Plosses Stem-and-Leaf Plot Frequency Stem & Leaf 2.00 0 . 34 12.00 0 . 556777889999 14.00 1 . 01112222233344 10.00 1 . 6667788899 8.00 2 . 00134444 8.00 2 . 55556778 2.00 3 . 24 2.00 3 . 67 2.00 4 . 24 4.00 Extremes (>=5.3) Stem width: 1.00 Each leaf: 1 case(s)

-2 0 2 4 6 8

Observed Value

-4

-2

0

2

4

Expe

cted

Nor

mal

Normal Q-Q Plot of Plosses

0 2 4 6 8

Observed Value

-0.5

0.0

0.5

1.0

1.5

2.0

Dev

from

Nor

mal

Detrended Normal Q-Q Plot of Plosses

202

0.00 2.00 4.00 6.00 8.00

Plosses

0

5

10

15

20

25Fr

eque

ncy

Mean = 2.062Std. Dev. = 1.53827N = 64

Histogram

Plosses

0.00

2.00

4.00

6.00

8.00

1348

3116

203

4.1.3 Jarrahdale variety after transformation LnP.rate Stem-and-Leaf Plot Frequency Stem & Leaf 1.00 Extremes (=<-1.2) 2.00 -0 . 69 3.00 -0 . 333 18.00 0 . 000001122233344444 12.00 0 . 556667788889 20.00 1 . 00000011122222333444 5.00 1 . 56889 3.00 2 . 001 Stem width: 1.00 Each leaf: 1 case(s)

-1 0 1 2

Observed Value

-0.6

-0.4

-0.2

0.0

0.2

Dev

from

Nor

mal

Detrended Normal Q-Q Plot of LnPlosses

-1 0 1 2

Observed Value

-4

-2

0

2

4Ex

pect

ed N

orm

al

Normal Q-Q Plot of LnPlosses

LnPlosses

-1.00

0.00

1.00

2.00

51

-2.00 -1.00 0.00 1.00 2.00 3.00

LnPlosses

0

5

10

15

20

Freq

uenc

y

Mean = 0.7703Std. Dev. = 0.72508N = 64

Histogram

204

4.1.4 Jap variety after transformation LnP.rate Stem-and-Leaf Plot Frequency Stem & Leaf 1.00 Extremes (=<-1.2) 4.00 -0 . 5669 9.00 -0 . 111122333 17.00 0 . 00001111122233444 22.00 0 . 5555666667888889999999 7.00 1 . 0122344 2.00 1 . 67 2.00 2 . 00 Stem width: 1.00 Each leaf: 1 case(s)

-1 0 1 2

Observed Value

-4

-2

0

2

4

Expe

cted

Nor

mal

Normal Q-Q Plot of LnPlosses

-1 0 1 2

Observed Value

-0.4

-0.2

0.0

0.2

0.4

Dev

from

Nor

mal

Detrended Normal Q-Q Plot of LnPlosses

LnPlosses

-1.00

0.00

1.00

2.00

50

-2.00 -1.00 0.00 1.00 2.00 3.00

LnPlosses

0

5

10

15

20

25

Freq

uenc

y

Mean = 0.4965Std. Dev. = 0.68195N = 64

Histogram

205

4.2 Multi comparisons of the mean of LnP.rate among different levels of independent variables 4.2.1 P. speed a. Jarrahdale Dependent Variable: LnP.rate

(I) Pspeed (J) Pspeed

Mean Difference

(I-J) Std. Error Sig. 95% Confidence

Interval

Lower Bound

Upper Bound

400.00 550.00 -.78455(*) .14258 .000 -1.0698 -.4993 700.00 -1.17661(*) .14258 .000 -1.4618 -.8914 850.00 -1.64859(*) .14258 .000 -1.9338 -1.3634

550.00 400.00 .78455(*) .14258 .000 .4993 1.0698 700.00 -.39206(*) .14258 .008 -.6773 -.1069 850.00 -.86404(*) .14258 .000 -1.1492 -.5788

700.00 400.00 1.17661(*) .14258 .000 .8914 1.4618 550.00 .39206(*) .14258 .008 .1069 .6773 850.00 -.47197(*) .14258 .002 -.7572 -.1868

850.00 400.00 1.64859(*) .14258 .000 1.3634 1.9338 550.00 .86404(*) .14258 .000 .5788 1.1492 700.00 .47197(*) .14258 .002 .1868 .7572

* The mean difference is significant at the .05 level. b. Jap Dependent Variable: LnP.rate

(I) Pspeed (J) Pspeed

Mean Difference

(I-J) Std. Error Sig. 95% Confidence

Interval

Lower Bound

Upper Bound

400.00 550.00 -.52862(*) .14849 .001 -.8256 -.2316 700.00 -.96187(*) .14849 .000 -1.2589 -.6649 850.00 -1.46678(*) .14849 .000 -1.7638 -1.1698

550.00 400.00 .52862(*) .14849 .001 .2316 .8256 700.00 -.43325(*) .14849 .005 -.7303 -.1362 850.00 -.93816(*) .14849 .000 -1.2352 -.6411

700.00 400.00 .96187(*) .14849 .000 .6649 1.2589 550.00 .43325(*) .14849 .005 .1362 .7303 850.00 -.50491(*) .14849 .001 -.8019 -.2079

850.00 400.00 1.46678(*) .14849 .000 1.1698 1.7638 550.00 .93816(*) .14849 .000 .6411 1.2352 700.00 .50491(*) .14849 .001 .2079 .8019

* The mean difference is significant at the .05 level.

206

4.2.2 Coarseness a. Jarrahdale Dependent Variable: LnP.rate

(I) Coarseness (J) Coarseness

Mean Difference

(I-J) Std. Error Sig. 95% Confidence

Interval

Lower Bound

Upper Bound

Very coarse Mild -.31821 .24559 .200 -.8095 .1731 Coarse -.50041(*) .24559 .046 -.9917 -.0092 Fine -.69295(*) .24559 .006 -1.1842 -.2017

Mild Very coarse .31821 .24559 .200 -.1731 .8095 Coarse -.18221 .24559 .461 -.6735 .3090 Fine -.37475 .24559 .132 -.8660 .1165

Coarse Very coarse .50041(*) .24559 .046 .0092 .9917 Mild .18221 .24559 .461 -.3090 .6735 Fine -.19254 .24559 .436 -.6838 .2987

Fine Very coarse .69295(*) .24559 .006 .2017 1.1842 Mild .37475 .24559 .132 -.1165 .8660 Coarse .19254 .24559 .436 -.2987 .6838

* The mean difference is significant at the .05 level. b. Jap Dependent Variable: LnP.rate

(I) Coarseness (J) Coarseness

Mean Difference

(I-J) Std. Error Sig. 95% Confidence

Interval

Lower Bound

Upper Bound

Very coarse Mild -.31671 .22779 .170 -.7724 .1389 Coarse -.48892(*) .22779 .036 -.9446 -.0333 Fine -.71804(*) .22779 .003 -1.1737 -.2624

Mild Very coarse .31671 .22779 .170 -.1389 .7724 Coarse -.17221 .22779 .453 -.6279 .2834 Fine -.40133 .22779 .083 -.8570 .0543

Coarse Very coarse .48892(*) .22779 .036 .0333 .9446 Mild .17221 .22779 .453 -.2834 .6279 Fine -.22912 .22779 .319 -.6848 .2265

Fine Very coarse .71804(*) .22779 .003 .2624 1.1737 Mild .40133 .22779 .083 -.0543 .8570 Coarse .22912 .22779 .319 -.2265 .6848

* The mean difference is significant at the .05 level.

207

4.2.3 Location a. Jarrahdale Dependent Variable: LnP.rate

(I) Location (J) Location

Mean Difference

(I-J) Std. Error Sig. 95% Confidence Interval

Lower Bound

Upper Bound

Bottom Top -.29541 .24717 .237 -.7898 .1990 Bottom side -.52613(*) .24717 .037 -1.0205 -.0317 Top side -.63579(*) .24717 .013 -1.1302 -.1414

Top Bottom .29541 .24717 .237 -.1990 .7898 Bottom side -.23072 .24717 .354 -.7251 .2637 Top side -.34038 .24717 .174 -.8348 .1540

Bottom side Bottom .52613(*) .24717 .037 .0317 1.0205 Top .23072 .24717 .354 -.2637 .7251 Top side -.10966 .24717 .659 -.6041 .3847

Top side Bottom .63579(*) .24717 .013 .1414 1.1302 Top .34038 .24717 .174 -.1540 .8348 Bottom side .10966 .24717 .659 -.3847 .6041

* The mean difference is significant at the .05 level. b. Jap Dependent Variable: LnP.rate

(I) Location (J) Location

Mean Difference

(I-J) Std. Error Sig. 95% Confidence Interval

Lower Bound

Upper Bound

Bottom Top -.18371 .22916 .426 -.6421 .2747 Bottom side -.57259(*) .22916 .015 -1.0310 -.1142 Top side -.58830(*) .22916 .013 -1.0467 -.1299

Top Bottom .18371 .22916 .426 -.2747 .6421 Bottom side -.38888 .22916 .095 -.8473 .0695 Top side -.40459 .22916 .083 -.8630 .0538

Bottom side Bottom .57259(*) .22916 .015 .1142 1.0310 Top .38888 .22916 .095 -.0695 .8473 Top side -.01570 .22916 .946 -.4741 .4427

Top side Bottom .58830(*) .22916 .013 .1299 1.0467 Top .40459 .22916 .083 -.0538 .8630 Bottom side .01570 .22916 .946 -.4427 .4741

* The mean difference is significant at the .05 level.

208

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