NUTRITIONAL ASSESSMENT OF SOME NEGLECTED AND …prr.hec.gov.pk/jspui/bitstream/123456789/11237/1... · benish nawaz merani reg. no. 2k12-fst-34 institute of food sciences & technology

1

NUTRITIONAL ASSESSMENT OF SOME NEGLECTED AND

UNDERUTILIZED VEGETABLES WILDLY GROWN IN SINDH

Ph. D. THESIS

BY

BENISH NAWAZ MERANI

Reg. No. 2K12-FST-34

INSTITUTE OF FOOD SCIENCES & TECHNOLOGY

FACULTY OF CROP PRODUCTION,

SINDH AGRICULTURE UNIVERSITY

TANDOJAM, SINDH, PAKISTAN

2018

2



BY

BENISH NAWAZ MERANI

A THESIS SUBMITTED TO SINDH AGRICULTURE UNIVERSITY,

THROUGH THE INSTITUTE OF FOOD SCIENCES &

TECHNOLOGY, FACULTY OF CROP PRODUCTION, IN

CONNECTION WITH THE FULFILLMENT OF THE

REQUIREMENTS

FOR

THE DEGREE OF

DOCTOR OF PHILOSOPHY

IN

FOOD SCIENCE AND TECHNOLOGY

TANDOJAM, SINDH, PAKISTAN

2018

3

DEDICATION

I dedicate this thesis to my Parents and

Husband for their dedicated partnership for

success in my life

4

TABLE OF CONTENTS

CHAPTER PARTICULARS PAGE

APPROVAL CERTIFICATE BY SUPERVISORY

COMMITTEE i

RESEARCH CERTIFICATE ii

THESIS RELEASE FORM iii

HALF TITLE PAGE iv

ACKNOWLEDGEMENT v

LIST OF TABLES vi

LIST OF FIGURES ix

LIST OF APPENDICES xi

ABBREVIATIONS xiv

ABSTRACT xv

I INTRODUCTION 1

II REVIEW OF LITERATURE 14

III MATERIALS AND METHODS 40

IV RESULTS 74

V DISCUSSION 162

VI CONCLUSIONS AND RECOMMENDATIONS 187

VII REFERENCES 196

APPENDICES 227

i



BY

BENISH NAWAZ

APPROVAL CERTIFICATE BY SUPERVISORY COMMITTEE

I. SUPERVISOR DR. SAGHIR AHMED SHEIKH

Professor

Faculty of Crop Production

Sindh Agriculture University, Tando Jam.

II. CO-SUPERVISOR-I DR. SHAFI MUHAMMAD NIZAMANI

Professor

Faculty of Crop Protection

Sindh Agriculture University,

Tando Jam.

III CO-SUPERVISOR-II DR. AIJAZ HUSSAIN SOOMRO

Professor

Institute of Food Sciences & Technology,

Faculty of Crop Production

Sindh Agriculture University, Tando Jam.

DATE OF THE THESIS DEFENSE __________________________2017

ii

INSTITUTE OF FOOD SCIENCES & TECHNOLOGY

FACULTY OF CROP PRODUCTION

SINDH AGRICULTURE UNIVERSITY, TANDOJAM

RESEARCH CERTIFICATE

This is to certify that the present research work entitled “NUTRITIONAL

ASSESSMENT OF SOME NEGLECTED AND UNDERUTILIZED

VEGETABLES WILDLY GROWN IN SINDH” embodied in this thesis has been

carried out by Ms. Benish Nawaz under my supervision and guidance in connection with

fulfillment of the requirements for the degree of doctor of Philosophy in Food Sciences

and Technology and that the research work is original.

Date _______________2018

Prof. Dr. Saghir Ahmed Sheikh

Dean

&

Research Supervisor

iii

SINDH AGRICULTURE UNIVERSITY, TANDOJAM

THESES RELEASE FORM

I, Benish Nawaz Merani hereby authorize the Sindh Agriculture University, Tandojam

to supply copies of my thesis to libraries and individuals upon their request.

__________________

Signature

__________________

Dated

iv



BY

BENISH NAWAZ MERANI

v

ACKNOWLEDGEMENTS

I am grateful to Almighty Allah, the supreme, the merciful, the most gracious,

the compassionate, the beneficent, who is the entire and only source of every knowledge

and wisdom gifted to mankind and who blessed me with the ability to do this work.

I would like to convey my cordial gratitude and appreciation to my eminent

supervisors Dr. Saghir Ahmed Sheikh, Dean Faculty of Crop Prodcution, Dr. Shafi

Muhammad Nizamani, Professor National Center of Excellence in Analytical Chemistry

and Dr. Aijaz Hussain Soomro, Director Institute of Food Sciences and Technology. I

could not achieve this goal without their thought provoking guidance, cooperation and

moral support. They have always been a source of inspiration and a role model for me.

Their patience and generosity has enabled me to overcome all the hurdles coming in the

way of success. Their teachings have not only improved my research skills but also

refined me as human.

I am profoundly obliged to Dr. Aasia Akbar Panhwar for her unconditional

support and cooperation. Her brilliance in the field of research, knowledge, wisdom, love

and care helped me greatly to achieve my research goals. I would like to extend my

thanks to Prof. Dr. Shahabuddin Memon, Director National Center of Excellence in

Analytical Chemistry, University of Sindh Jamshoro for providing me an opportunity to

do part of my Ph.D. research and for providing good research facilities throughout the

course of research

I am also gratified to Ms. Nusrat Shahab Memon, Research Associate, IFST, SAU

Tandoja and all faculty members for their research consultancy and cooperation.

At last but not the least, I really acknowledge and offer my heartiest gratitude to

my beloved parents, husband, brothers and friend Mahvish Jabeen Channa for their great

sacrifice, moral support, cooperation, encouragement, patience, tolerance and prayers for

my health and success during this work.

Finally, I would acknowledge the Higher Education Commission Pakistan (HEC)

for providing me an opportunity and financial support to achieve this goal.

BENISH NAWAZ MERANI

vi

LIST OF TABLES

Table

No. PARTICULARS

Page

No.

1 Enumeration of selected vegetables 47

2 Percentage non-edible and edible parts of the selected vegetables 51

3 Cooking methodology of amaranthus, lambs quarter, gram leaves,

horse radish tree flowers and spinach 53

4 Coding of nontraditional and commercial vegetables 54

5 HPLC conditions for quantification of vitamins 65

6 Perception of non-traditional leafy vegetable use by selected

respondents (% frequency) 75

7 Moisture content (%) of different types of vegetables under the effect

of postharvest processing methods 76

8 Ash content (%) of different types of vegetables under the effect of

postharvest processing methods 78

9 Protein content (%) of different types of vegetables under the effect of


10 Fat (%) of different types of vegetables under the effect of postharvest

processing methods 82

11 Fiber content (%) of different types of vegetables under the effect of


12 Carbohydrate (%) of different types of vegetables under the effect of


13 Correlation matrix (r) of proximate composition of different

vegetables under the influence of processing treatments 87

14 Acetic acid (%) of different types of vegetables under the effect of


15 Citric acid (%) of different types of vegetables under the effect of


16 Oxalic acid (%) of different types of vegetables under the effect of


17 Tartaric acid (%) of different types of vegetables under the effect of


18 Correlation matrix (r) of organic acids of different vegetables under

the influence of processing treatments 94

19 Copper (mg 100g

-1) of different types of vegetables under the effect of


20 Iron (mg 100g



21 Zinc (mg 100g



22 Manganese (mg 100g

-1) of different types of vegetables under the

effect of postharvest processing methods 101

vii

23 Calcium (mg 100g

-1) of different types of vegetables under the effect


24 Magnesium (mg 100g



25 Sodium (mg 100g



26 Potassium (mg 100g



27 Correlation matrix (r) of mineral content of different vegetables under


28 Alkaloids (mg g



29 Saponins (mg g



30 Flavinoids (mg g



31 Phenol (mg g



32 Phenol (mg g



33 Correlation matrix (r) of phytochemical content of different vegetables

under the influence of processing treatments 121

34 Vitamin A (β-carotene) content (mg 100g

-1) of different types of

vegetables under the effect of postharvest processing methods 123

35 Vitamin C (mg 100g



36 Vitamin B1 (mg 100g









39 Correlation matrix (r) of vitamin content of different vegetables under


40 Total solids (%) of different types of vegetables under the effect of


41 Total soluble solids (°Brix) of different types of vegetables under the


42 Energy value (kcal 100g



43 pH level of different types of vegetables under the effect of


44 Nitrogen free extract (%) of different types of vegetables under the


45 Total fatty acids (%) of different types of vegetables under the effect 143

viii

of postharvest processing methods

46

Correlation matrix (r) of Nitrogen free extract, energy value, fatty

acid, pH, total solids and TSS of different vegetables under the

influence of processing treatments

145

47 Chlorophyll content of fresh vegetables selected in the present study 146

48 Five point scale sensory scores of raw or uncooked non-traditional

vegetables 147

49 Five point scale Sensory scores of non-traditional vegetables cooked

by traditional method 151

50 Extraction of components by using eigen values and variability

percentage 156

51 Analysis of component score coefficient matrix 159

52 Component correlation matrix 160

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LIST OF FIGURES

Table

No. PARTICULARS

Page

No.

1 Schematic representation of the methodology used in the present study 41

2 Map showing selected district of Sindh Province, Pakistan 43

3 Pictorial view of selected vegetables 48

4 Perception of nontraditional vegetable use 75

5 Graphical representation of the moisture content (%) of selected

vegetables 77

6 Graphical representation of the ash content (%) of selected vegetables 78

7 Graphical representation of the protein content (%) of selected vegetables 80

8 Graphical representation of the fat content (%) of selected vegetables 82

9 Graphical representation of the fiber content (%) of selected vegetables 84

10 Graphical representation of the carbohydrate content (%) of selected

vegetables 86

11 Graphical representation of the acetic acid (%) of selected vegetables 89

12 Graphical representation of the citric acid (%) of selected vegetables 90

13 Graphical representation of the oxalic acid (%) of selected vegetables 92

14 Graphical representation of the tartaric acid (%) of selected vegetables 93

15 Graphical representation of the copper content (mg 100g-1) of selected

vegetables 96

16 Graphical representation of the iron content (mg 100g

-1) of selected

vegetables 97

17 Graphical representation of the zinc content (mg 100g

-1) of selected

vegetables 99

18 Graphical representation of the manganese content (mg 100g

-1) of selected

vegetables 101

19 Graphical representation of the calcium content (mg 100g

-1) of selected

vegetables 103

20 Graphical representation of the magnesium content (mg 100g

-1) of

selected vegetables 105

21 Graphical representation of the sodium content (mg 100g

-1) of selected

vegetables 107

22 Graphical representation of the potassium content (mg 100g

-1) of selected

vegetables 109

23 Graphical representation of the alkaloids (mg g-1

) of selected vegetables 112

24 Graphical representation of the saponins (mg g-1


25 Graphical representation of the flavinoids (mg g-1


26 Graphical representation of the phenols (mg g-1


27 Graphical representation of the tanins (mg g-1


28 Graphical representation of the vitamin A (β-carotene) content (mg

100g-1


29 Graphical representation of the vitamin C (mg 100g

-1) of selected

vegetables 125

x

30 Graphical representation of the vitamin B1 (mg 100g

-1) of selected

vegetables 127


-1) of selected

vegetables 129


-1) of selected

vegetables 131

33 Graphical representation of the total solids (%) of selected vegetables 134

34 Graphical representation of the total soluble solids (°Brix) of selected

vegetables 136

35 Graphical representation of the energy value (kcal 100g

-1) of selected

vegetables 138

36 Graphical representation of the pH of selected vegetables 139

37 Graphical representation of the nitrogen free extract (%) of selected

vegetables 141

38 Graphical representation of the total fatty acid (%) of selected vegetables 143

39 Graphical representation of the total chlorophyll (%) of selected

vegetables 146

40 Spider chart showing five point scale sensory scores of uncooked

amaranthus vegetable 148

41 Spider chart showing five point scale sensory scores of uncooked lambs

quarter vegetable 148

42 Spider chart showing five point scale sensory scores of uncooked gram

leaves vegetable 149

43 Spider chart showing five point scale sensory scores of uncooked horse

radish tree flowers vegetable 149

44 Spider chart showing five point scale sensory scores of uncooked spinach

vegetable 150

45 Spider chart showing five point scale sensory scores of cooked

amaranthus vegetable 151

46 Spider chart showing five point scale sensory scores of cooked lambs

quarter vegetable 152

47 Spider chart showing five point scale sensory scores of cooked gram

leaves vegetable 152

48 Spider chart showing five point scale sensory scores of cooked horse

radish tree flowers vegetable 153

49 Spider chart showing five point scale sensory scores of cooked spinach

vegetable 153

50 Scree plot of the eigenvalues 157

51 3D component plot of the nutritional data of vegetables 161

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LIST OF APPENDICES

APPENDIX PARTICULARS PAGES

I

Best of fit curve of minerals standards (Calcium, Copper,

Iron, Zinc, Manganese, Magnesium, Sodium and

potassium)

227

II

Best of fit curve of vitamin standards (vitamin A (β-

carotene), vitamin C (Ascorbic acid), vitamin B1

(Thiamine), vitamin B2 (Ribofilavin) and vitamin B3

(Niacin))

229

III

Best of fit curve of chromatograms of vitamin standards

(vitamin B1 (Thiamine), vitamin B2 (Ribofilavin), vitamin

B3 (Niacin), vitamin A (β-carotene) and vitamin C

(Ascorbic acid)

230

IV Best of fit curve of phytochemical standards (total

flavonoids, total phenols and total tanins) 233

V Analysis of variance for moisture content of various

vegetables and processing methods 234

VI Analysis of variance for ash content of various vegetables

and processing methods 234

VII Analysis of variance for protein content of various


VIII Analysis of variance for fat content of various vegetables


IX Analysis of variance for fiber content of various


X Analysis of variance for carbohydrate content of various


XI Analysis of variance for acetic acid of various vegetables


XII Analysis of variance for citric acid of various vegetables


XIII Analysis of variance for oxalic acid of various vegetables


XIV Analysis of variance for tartaric acid of various vegetables


XV Analysis of variance for copper content of various


XVI Analysis of variance for iron content of various vegetables


XVII Analysis of variance for zinc content of various vegetables


xii

XVIII Analysis of variance for manganese content of various


XIX Analysis of variance for calcium content of various


XX Analysis of variance for magnesium content of various


XXI Analysis of variance for sodium content of various


XXII Analysis of variance for potassium content of various


XXIII Analysis of variance for alkaloids of various vegetables


XXIV Analysis of variance for saponins of various vegetables


XXV Analysis of variance for flavinoids of various vegetables


XXVI Analysis of variance for phenol of various vegetables and


XXVII Analysis of variance for tanins of various vegetables and


XXVIII Analysis of variance for vitamin A of various vegetables


XXIX Analysis of variance for vitamin C of various vegetables


XXX Analysis of variance for vitamin B1 of various vegetables


XXXI Analysis of variance for vitamin B2 of various vegetables


XXXII Analysis of variance for vitamin B3 of various vegetables


XXXIII Analysis of variance for total solids of various vegetables


XXXIV Analysis of variance for total soluble solids of various


XXXV Analysis of variance for energy value of various


XXXVI Analysis of variance for pH of various vegetables and


XXXVII Analysis of variance for nitrogen free extract of various


XXXVIII Analysis of variance for total fatty acids of various


xiii

XXXIX Analysis of variance for total chlorophyll of various

vegetables 242

XL Correlation matrix (r) of quality parameters of different

vegetables under the influence of processing treatments 243

XLI Analysis of variance for sensory analysis of uncooked

vegetables 244

XLII Analysis of variance for sensory analysis of cooked

vegetables 244

XLIII Informed consent 245

XLIV Questionnaire non-traditional vegetables 246

XLV Sensory evaluation form for cooked vegetables 247

XLVI Sensory evaluation form for raw or uncooked vegetables 248

xiv

ABBREVIATIONS

% Percent

< Less Than

µl Microliter

ANOVA Analysis of Variance

AOAC Association of The Analytical Chemists

Ca Calcium

CRD Complete Randomized Design

Cu Copper

Cv Coefficient of Variance

FAO Food and Agriculture Organization

Fe Iron

FW Fresh Weight

GOP Government of Pakistan

G Gram

GAE Gallic Acid Equivalent

HPLC High Performance Liquid Chromatography

IFST Institute of Food Sciences and Technology

K Potassium

Kcal Kilocalories

LDL Low Density Lipoprotein

LSD Least Significant Difference

M Mole

Mg Magnesium

Mg Milligram

mg kg-1

Milligram Per Kilogram

mg g-1

Milligram Per Gram

Min Minute

Ml Milliliter

Mn Manganese

Nm Nanometer

NS Nonsignificant ᴼC Degree Centigrade

Ppm Parts Per Million

Rpm Round Per Minute

SAU Sindh Agriculture University

SPSS Statistical Package for The Social Sciences

TSS Total Soluble Solids

UV–Vis Ultra Violet Visible

WHO World Health Organization

Zn Zinc

Μm Micrometer

xv

AN ABSTRACT OF THE THESIS OF

BENISH NAWAZ MERANI For Doctor of Philosophy in

Major Food Sciences & Technology

TITLE: NUTRITIONAL ASSESSMENT OF SOME NEGLECTED AND


The aim of this study was to investigate the utilization potential and

comparison of nutritional value of nontraditional with commercial vegetables in Sindh.

The questionnaire survey methodology was used to collect the data on the utilization and

consumption of nontraditional and commercial vegetables in Mirpurkhas of Sindh

province, Pakistan in 2014. On the basis of survey spinach, horse radish tree flowers,

lambs quarter and gram leaves were collected in January, 2014 whereas, amaranthus was

collected in the months of July-August, 2014 from district Mirpurkhas, packed with

proper labelling and brought to the Institute of Food Sciences and Technology, Sindh

Agriculture University Tandojam for processing and nutritional analysis. The edible parts

of vegetables were washed and divided into five sets namely control, boiled, cooked,

thermally dehydrated and shade dried.

The data of survey showed that gram leaves was the most popular non-

traditional vegetable eaten frequent or occasionally by 82% respondents only 18%

respondents never tasted or do not know this vegetable. Next vegetables which majority

of respondent never tasted or did not know included amaranthus and lambs quarter.

About 62% respondents never tasted or do not know horse radish tree flowers as

vegetable while 38% respondents answered they eat occasionally.

The nontraditional (lambs quarter, horse radish tree flowers, gram leaves,

amaranthus) and commercial (spinach) vegetables were analyzed for their nutritive,

mineral, vitamin, phytochemical and chlorophyll composition. The highest moisture

content (92.66%) was found in spinach under boiled method followed by 88.760%

moisture content in the same vegetable at fresh (control). Maximum ash content (16.15%)

in horse radish tree flowers followed by 10.56% ash content in amaranthus under

thermally dehydration. Protein content was found greater (7.56%) in gram leaves under

thermal dehydration method. However, minimum protein of 1.04% was found in spinach

under boiling method. The maximum value of 3.85% in horse radish tree flowers under

cooking method while minimum fat content i.e. 0.85 and 0.75% was found in spinach and

lambs quarter, respectively at boiling method. The highest value (13.35%) of fiber was

obtained in thermally dried sample of horse radish tree flowers whereas the lowest value

was recorded in boiled sample of spinach. However, higher carbohydrate (68.62%)

content was found in lambs quarter at shade drying. The nontraditional vegetables also

contain organic acids (e.g. lactic acid, citric acid, acetic acid, tartaric acid) in all the

selected vegetables. The nontraditional and commercial vegetables were also recorded

with significant amount of vitamins and phytochemicals. The energy value was found

lowest in fresh spinach (38.35 Kcal 100g-1

) hence was also detected lowered in other

processing methods as compared to nontraditional vegetables.

xvi

The results of the sensory evaluation of the uncooked and cooked samples

in present study revealed that in uncooked samples, horse radish tree flowers obtained

highest scores in appearance, color, odor, texture, taste, overall acceptability and

purchase i.e. 4.90, 4.70, 4.00, 3.90, 3.50, 3.80 and 3.80. While in traditionally cooked

samples lambs quarter and gram leaves retained original color and thus obtained the

highest scores in appearance and taste i.e. 3.70, 3.90 and 3.70, 3.50, respectively.

Acceptability study by hedonic scoring showed that nontraditional vegetables (horse

radish tree flowers, lambs quarter, and gram leaves and amaranthus) made by traditional

cooking were most acceptable as compared with commercial vegetable (spinach). These

nontraditional vegetables when consumed in cooked form could also be a good source of

nutrients.

Principal component analysis revealed that the first seven principal

components explained about 94.79% of the total variability in the observed parameters.

Moisture, total solid, ash, fiber, carbohydrate, nitrogen free extract, energy value, acetic

acid, citric acid, oxalic acid, tartaric acid, copper, iron, zinc, manganese, calcium, sodium

and potassium resulted the most effective variables for the first principal component.

Saponins, flavinoids, phenol and vitamin B3 were major contributors to second principal

component, while tannins content was useful to define the third principal component.

It was concluded that the nutrient and bioactive contents obtained from

selected vegetables seem to suggest that the vegetables have high potential to contribute

to the nutritional and health status of local as well as urban communities in Sindh

Pakistan. Their use in the communities should therefore, be promoted. Taking into

account the amount of nutrient and bioactive content in the selected nontraditional

vegetable, these plants could be valuable and important contributor to the diets of the

people in Sindh, Pakistan.

1

CHAPTER-I

INTRODUCTION

Background

Vegetables are the major part of daily food intake by human population all

over the world that plays an important role in the balanced diet. Green vegetables are

excellent sources of micronutrients, so the consumption of these may contribute to meet

the nutritional requirement and to overcome the micronutrient deficiency at minimum

cost (Saikia and Deka, 2013; Ebert, 2014). People living in rural areas harvest wide

variety of vegetables including fruits, leaves, tubers and roots from barren lands because

of their flavor and traditional uses to overcome shortage of food or as supplement.

Nontraditional vegetables are regarded as famine or hunger food due to their potential to

meet the income security and food demand as rural people cannot afford commercial

crops (Jayanti et al., 2013). There are 350,000 plant species throughout the globe and

around 80,000 are fit for human consumption (Fuleky, 2016). The vegetables contain

essential nutrients, mineral elements and anti-nutritional constituents with significant

biological roles at physiological concentrations (Atabo et al., 2017).

Dietary diversity and consumption pattern of nontraditional vegetables

In developing countries various types of wild edible plants are consumed

as sources of food. Due to the sharp increase in population, scarcity of fertile land for

cultivation and high prices of available staples, some people frequently collect wild

2

edible plants and other plants from natural habitats to meet their adequate level of

nutrition (Seal et al., 2017). Local people since long time consume nontraditional

vegetables on daily basis but there is no any systematic investigation has been carried

out. In resource-poor settings worldwide, low-quality, monotonous diets are common and

the risk of micronutrient deficiencies is high (Arimond et al., 2010; FAO, 2013b) because

only few known commercial species are used for global supply of food (Barucha and

Pretty, 2010; FAO, 2013a). The leafy vegetables contain appreciable amounts of minerals

and vitamins, thus may be included in diets to supplement daily dietary allowances

needed by the body, hence, improving nutritional status and curbing the problem of

micronutrient deficiency (Akpana et al., 2017).

In Pakistan, comparatively to other developing nations, an expected 80%

of the rural populace relies on nontraditional wild plants for their primary health care

needs (Khan, 2012). Several plants are utilized for medicinal and nutritional purposes.

Currently, there is an upsurge in the utilization of plants believed to possess high

nutritional and medicinal value by most locals especially those in developing countries.

The leaf part of vegetables is very rich source of essential minerals and amino acids that

are needed for proper function of the body system. Also, it is a rich source of energy and

relatively safe for consumption owing to its very low concentrations of antinutrients and

toxic elements (Ewere et al., 2017). In the course of the most recent decades, there has

been icreasing scientific and commercial concern in Pakistan for nontraditional

vegetables, mainly due to their economic potential and the wide spread cultural

acceptability of plant based products (Sher et al., 2014, 2015). In some regions of the

3

world, use of nontraditional vegetables and culinary herbs are wide spread, where these

nontraditional vegetables plant species are regarded as important healthy food (Afolayan

and Jimoh, 2009). These vegetables could be incorporated in food formulation as

therapeutic agent apart from its nutritional essence which could be explored to provide

affordable remedy to masses. Lesser known vegetables, has enormous nutritional

potentials and can favorably be used as a substitute for most of the commonly used

vegetables (Agarwal et al., 2017).

Today, there is evidence that edible nontraditional plants have been used

as vegetables since ancient times for their organoleptic, therapeutic and medicinal

properties (Guarrera and Savo, 2013) and are nutritionally important because of high

content of minerals, essential fatty acids, fibers and proteins (Jabeen et al., 2010; Ghani et

al., 2012). The nontraditional vegetables contain appreciable amounts of macro-minerals

like magnesium, calcium, potassium and phosphorus, which work synergistically to

maintain optimal health by keeping the body and tissue fluids from being either too acidic

or too alkaline; allowing for exchange of nutrients between body cells (Akpana et al.,

2017). Many nontraditional vegetables are also used with staple food in both urban and

rural areas. The nontraditional vegetables traditionally used as food that enhances the

taste and color of the diets but scientific data on the nutrients and chemical composition

of those nontraditional vegetables is still scarce (Satter et al., 2016). Therefore, the use of

edible nontraditional vegetables appears attractive for the reason that they are a source of

healthy compounds, but they are less understood than commercial vegetables (Guil-

Guerrero, 2014).

4

Nutritional and medicinal importance of nontraditional vegetables

Pakistan is rich in nontraditional vegetables plants and it incorporates just

about 6000 blossoming plants which have extraordinary dietary and therapeutic

significance. In Pakistan 200 distinctive plant species are utilized to treat diarrhea, skin

problems, kidney maladies, gastrointestinal ailments and urinary sicknesses (Hayat et al.,

2008). They are profitable in keeping up basic store in the body and are esteemed

principally for their high vitamin, dietary fiber and mineral substance. The wide variety

in texture, color and tastes of different vegetables has added an intriguing touch to meal

(Fasuyi, 2006). Vegetable leaves have appreciable amount of nutrients such as calcium,

potassium, iron, carbohydrate, fat, protein and anti-nutrients. This therefore, suggests that

the leafy vegetable could serve as a constituent of human diet, supplying the body with

micronutrients which are electrolytes proffering significant roles in humans (Atabo et al.,

2017).

There is now growing evidence that nontraditional vegetables have higher

nutritional value than several known common vegetables (Orech et al., 2007). These

vegetables present good nutritional sources with moderate energy values and rich sources

of macronutrients and micronutrients, exhibiting the least toxic risks regarding heavy

metals (Attaa et al., 2017) and are good source of nutrition of any food and rich source of

vitamins, phytonutrients and minerals which protect our eyes from age-related problems

(such as age-related muscular degeneration) and omega-3 fatty acids which protect us

5

from cardiovascular diseases. The nontraditional vegetables can therefore, provide

substantial nutritional and dietary benefits to tribal populations living in remote rural

areas and can prevent several chronic diseases caused by malnutrition (Geeta and

Sharma, 2015). The vegetables are rich sources of protein which can encourage their use

in human diets and might be helpful for protein energy malnutrition. Vegetables are rich

sources of fiber which is an important component in preventing overweight, constipation,

diabetes, cholesterol, cardiac diseases, colon and breast cancer, hypertension, etc (Koca et

al., 2015). Nontraditional vegetables have been recognized as a good source of vegetable

fiber and protein content and showed lower value for total phenols, flavonoids content

but higher free radical scavenging activity as compared to cultivated vegetables.

Therefore, both these vegetables possess strong anti antioxidative potential to manage

against metabolic disorders such as diabetes and cardiovascular diseases (Agarwal et al.,

2017).

The intake of nontraditional vegetable plants is important for human

health and vegetables play a critical nutritive part in such manner, particularly for country

populaces (Uusiku et al., 2010). Nontraditional vegetables provide the bulk of daily

calories and around 65% of the protein (Bennett, 2016). Interest in nontraditional

vegetables has significantly increased in light of the fact that they give high supplement

levels and potential medical advantages (Garcia-Herrera et al., 2014b). Consequently,

many people harvest nontraditional vegetables also because of their significant impact to

the diet in terms of healthy compounds for example, vitamins, minerals and antioxidants.

Consequently, the tradition of eating spontaneous plants is still alive as well as is

6

expanding since the nontraditional vegetables are regarded as healthy and natural foods

(Uusiku et al., 2010; Pereira et al., 2011; Renna and Gonnella, 2012; Sanchez-Mata et

al., 2012).

The utilization of green vegetables plays an important role in keeping a

balanced diet and turns away the diseases related to malnourishment. Epidemiological

studies show that an increased consumption of plant based products is related to lessened

danger of various chronic health dieases including cardiovascular, neurodegenerative and

cancer diseases (Yahia, 2010). The phytochemical composition revealed the presence of

considerable levels of phenolics, flavonoids, alkaloids, and tannins among all the

nontraditional vegetables (Attaa et al., 2017) with various biological activities (Dinda et

al., 2007a, 2007b; Podsedek, 2007). These phytochemicals are accounted for several

biological activities, such as anti-cancer, anti-inflammatory, antioxidant, and

antimicrobial activities. Particularly, phenolic compounds which have antioxidant

characteristics (Mertz et al., 2009) with free radical scavenging capacity and strong

chain-breaking which in turn provide defensive mechanism against reactive oxygen

species (ROS) (Podsedek, 2007; Attaa et al., 2017) that are responsible for tissue and

oxidative damage to proteins and nucleic acids (Middleton et al., 2008). The low sodium

make these plants healthy alternative dietary components in the management and

prevention of hypertension (Akpana et al., 2017).

7

Most of wild edible vegetable species have medicinal property and can be

used to keep people healthy and fit. Furthermore, phytochemical and nutraceutical studies

of these edible species may provide better nutritional source. Apart from the source for

food, human also utilize plants for dyes, ornaments and medicines. Wild edible plants are

source for nutrition but also possess higher medicinal property. These wild plants are

grown in forest region without chemical / fertilizer (Seema, 2015). Dietary guidelines

encouraged the supplementation of plant-derived nutraceuticals not only to provide an

insight regarding assuaging nature, nutritional worth, sustainability and safe status but

also to modulate the onset of chronic ailments (Atta et al., 2016). Despite their common

utilization, the wide selection of nontraditional vegetables either semi-cultivated or

cultivates in the wild (Shakirin et al., 2010). The major nutritional compounds that are

present in nontraditional vegetable plants are carbohydrates in the form of starch and

sugars, protein, lipid, in the form of oil, vitamins, minerals, etc. Apart from these

antioxidants, like ascorbic acid, phenols such as cholorogenic acid and its polymers are

available in plant because of these component, the wild vegetable most have potential to

improve physical as well as mental health, help in reduce the risk of disease. There is

therefore a need to explore the vast varieties of nontraditional vegetables as food by man

(Edogbanya, 2016). All thenontraditional vegetables have very good medicinal potentials,

meet the standard requirements for drug formulation and serve as good sources of energy

and nutrients (Attaa et al., 2017).

8

Role of nontraditional vegetables in food security

Nontraditional vegetables can contribute to food security in several ways.

Harvesting and trading nontraditional vegetables can result in rural employment and

income generation (Keller et al., 2005; Agea et al., 2007; Barucha and Pretty, 2010;

Legwaila et al., 2011). It has been observed from various reports that there is lack of

knowledge and intake of nontraditional vegetables (Hart and Vorster, 2006; Modi et al.,

2006; Van-Rensburg et al., 2007; Lewu and Mavengahama, 2010; Taleni et al., 2012).

Malnutrition has affected around nine hundred million individuals throughout the globe

and more than two billion are recorded with micronutrient deficiency related diseases

(Fan et al., 2012). Nevertheless, some authors (Berti et al., 2014) hypothesized that by

including nontraditional vegetable species in the diets, there is likely to be an

improvement in nutrient deficiencies.

Bvenura and Afolayan (2015) stated that the increased consumption of

nontraditional vegetables will help to reduce the malnutrition and food insecurity.

Moreover, if availability of the traditional and nontraditional vegetables is made

throughout the year will results in food stability. This can be done by encouraging people

to cultivate the nontraditional vegetables in their home gardens during their season and

preserve them for later use in offseason. The horticultural perspectives of nontraditional

vegetables despite of their long history have not been fully examined (Odhav et al.,

2007). Bvenura and Afolayan (2015) reported that nontraditional vegetables are clearly

underutilized although they potentially have a big role to play in food security.

9

Nontraditional vegetables are required to be revitalized and widely consumed in daily

diets to decease food insecurity. The knowledge about these species may soon be lost if

these species to continuous underappreciated and neglected. Therefore, there is a dire

need for systematic investigation and records of their bioactive and nutritive values in

emerging countries (Hervert-Hernandez et al., 2011).

Main characteristics and adaption of nontraditional vegetables to harsh climates

Nontraditional vegetables and nontraditional crops grow well during

drought periods and in areas with low or unreliable rainfall. Nontraditional vegetables

require fewer inputs (chemical fertilizers and pesticides) during production survive poor

soils as they are adapted to the local environmental conditions and are available when the

commercial vegetables are not (Modi et al., 2006; Van-Vuuren, 2006). These vegetables

are probably free of agricultural contaminants; but, their impacts on human heath are

minimal known (Pieroni et al., 2002; Luczaj, 2010). In different studies, it was reported

that nontraditional vegetables have increased agro-biodiversity, upgraded production and

minimized the effects of pests, diseases and environmental shocks where other species

could fail (Tilman et al., 2006; Venter et al., 2007; Bradford, 2010; Frison et al., 2011;

Mahapatra and Panda, 2012; Asif and Kamran, 2013).

On account of their strength, nontraditional vegetables can act as security

nets in times of food deficiency and starvation (Kebu and Fassil, 2006). They may also

add to dietary diversity and be essential components of an otherwise monotonous and

10

nutritionally poor diet (Fentahun and Hager, 2009). Together with the lack of food

composition data on nontraditional vegetables, this has led to a routine undervaluation of

wild edible plants in diets and to their neglect by researchers, policy makers and

nutritionists (Figueroa et al., 2009). Besides, post-harvest losses and quality deterioration

of vegetables are mostly caused by pests, microbial infection, natural ripening processes

and environmental conditions such as heat, drought and improper post-harvest handling

(Idah et al., 2007; Olayemi et al., 2010).

Loss of indigenous knowledge and introduction of new commercial vegetables

The knowledge about nontraditional vegetables is decreasing which must

be documented (Aphane et al., 2003; Musinguzi et al., 2006; Lwoga et al., 2010).

Nontraditional plants, that are consumed as vegetables are actually part of the local

knowledge and production systems (Keller et al., 2004, 2005). Nontraditional vegetables

are those edible plants that are biologically indigenous to an area, while commercial

vegetables require various agricultural related inputs to grow. Indigenized vegetables are

local and adapted to the native environmental conditions (Laker, 2007). This loss in the

knowledge of nontraditional vegetables may contribute to decreased intake of plant

species which in turn results in micronutrient deficiency and food insecurity due to lack

of diet diversity (Flyman and Afolayan, 2008).

According to Keller et al. (2005) there are many factors that contribute to

the loss of knowledge about these species i.e. politics, lifestyle changes, introduction of

11

commercial crops and loss of habitat. The main reason for the loss of information about

nontraditional vegetables is the introduction and promotion of new commercial

vegetables by the agriculture extension and researchers, consequently leading to the

complete substitution of nontraditional vegetables (Jansen-van-Rensburg et al., 2007).

Commercial vegetables due to their popularity and market value are

keener about the farming of these commercial vegetables as compared with

nontraditional vegetables (Musinguzi et al., 2006). In many countries, nontraditional

vegetables have received negative attitude because of their primitiveness and poverty.

Thus, most of the population mainly youth, have stopped consumption of nontraditional

vegetables because they do not want to be labelled as backward (Jansen-van-Rensburg et

al., 2007).

Sensory (taste) and market potential

Earlier ethnobotanical surveys showed that value judgement can be done

on the basis of organoleptic qualities through which value of different species can be

judged (N’danikou et al., 2011). For example, if the respondents are given two species

and asked for their value, their response for one of the specie will be high because of its

taste. Kidane et al., (2015) carried out a survey to know which vegetable specie is most

preferred by the respondents on the basis of its taste. The chosen specie had the greater

market potential though marketability and was also influenced by other factors such as

quantity, accessibility and distribution.

12

Keeping in view, the present situation of ever increasing population,

urbanization and conversion of arable land in to residential areas, ultimately culminates

in the increased food demand leading to food in-security. The present study therefore, has

been designed to identify the wild vegetables suitable for human consumption. The study

planned would also indicate that the samples to be studied as good sources of macro and

micronutrients and to provide food security. There is always the need to explore every

possible source of nutrients for healthy living. The expected findings would also be

useful and helpful for nutritionists to formulate balance diets. The study shall also include

the effects of cooking and storage conditions on the nutrients of the vegetables

investigated and studied.

Problem statement and justification for the study

Literature review showed that extensive work has been done on the

nutritive components of various traditional in Pakistan; however, little attention has been

paid to the nutritive values of nontraditional vegetables. The findings obtained from

proposed study may guide researchers, scientists, health practitioners and above all, the

general public regarding wild vegetables that, these vegetables can not only contribute to

subsistence and nutritional requirement of the local people but can be a substantial

source of income generation against poverty alleviation particularly in rural areas of

Pakistan. Furthermore, identification of wild vegetables would help poor households to

have nutritive and affordable vegetables in comparison to other food items. The study

may provide valuable suggestions pertaining to other than formal sector in rural and peri-

13

urban areas because of their generally short labor intensive production systems, low

levels of investment and high yields. The present study may also help to identify the most

effective means of commercialization or best marketing and policy frameworks to

promote their use and maximize underutilized plant species having potentially economic

value.

Objectives of the study

The study shall be focused and attained through following objectives:

i. To assess the nutritional characteristics of selected wild vegetables

ii. To compare the nutritional characteristics of wild vegetables with other

commonly grown vegetables

iii. To determine the effect of processing and cooking on nutritional contents

of wild

vegetables

iv. To carry out the sensory attributes of cooked vegetables

v. To recommend the wild vegetables for human consumption, with

potentially

nutritive and health value

14

CHAPTER–II

REVIEW OF LITERATURE

Ethnobotanical information of nontraditional vegetables

Pakistan is bestowed with nontraditional vegetables plants with great

therapeutic importance. There are about 200 different plant species discovered having the

potential to treat urinary diseases, diarrhea, skin disorders, gastrointestinal diseases,

kidney diseases and dysentery (Sidhu et al., 2007; Hayat et al., 2008). Ethnobotany in

Pakistan is increasing with time and different studies have been recorded in various areas

(Qureshi and Bhatti, 2009; Qureshi et al., 2009a; Abbasi et al., 2010; Shinwari, 2010;

Bahadur, 2012; Farooq et al., 2012; Abbasi et al., 2013; Ahmad et al., 2014; Ullah et al.,

2014). Human consumption pattern for vegetables is limited to the introduced varieties

than wild habitats (Bussmann and Sharon, 2006; Cavender, 2006; Kunwar et al., 2006;

Pieroni et al., 2007).

Vegetables are considered most important in daily diet (Pandey, 2008).

The nontraditional vegetables despite of their medicinal values has been paid less

attention (Qureshi et al., 2006; Ahmad and Husain, 2008; Husain et al., 2008; Qureshi et

al., 2009; Mahmood et al., 2011c; Mahmood et al., 2012) and this field is regarded as

virgin (Mahmood et al., 2011a). The native individuals still prefer these wild plants as

medicines due to unaffordable costs of allopathic medicines, growing population,

15

incomplete health care systems and economic curbs (Mahmood et al., 2011b) but

unfortunately, this information is not documented properly on the ethno-medicinal

information from Pakistan (Mahmood et al., 2013). The nontraditional vegetables are

collected for home consumption by forest inhabitants, marginalized and tribal

communities or during indigenized festivals. None of the nontraditional vegetable plants

has been cultivated nor is the knowledge on nutritional properties still recorded or tapped.

These species are only consumed on the basis of their medicinal and taste values (Jayanti

et al., 2013).

Importance and utilization of nontraditional vegetables

Nontraditional vegetables are collected from both uncultivated and

cultivated lands and the information about nontraditional vegetables is passed on from

one generation to another generation as a part of the homegrown system of knowledge for

the local people (Lwoga et al., 2010). Throughout the most recent decades, there has been

an increasing commercial and scientific interest in Pakistan for nontraditional vegetables,

mostly because of their economic potential and the wide spread cultural acceptability of

plant based products (Sher et al., 2014, 2015). In Pakistan, comparatively to other

emerging countries, an expected 80% of the rural populace relies upon nontraditional

wild plants, for their essential health care needs (Khan, 2012). Today, there is proof that

edible nontraditional plant species have been used as vegetables since various decades

due to their medicinal and sensory attributes (Guarrera and Savo, 2013).

16

The use of edible nontraditional vegetables appears to be appealing in

light of the fact that they are appears to be appealing since they are a source of nutrients;

however, since they are less known than commercial vegetables (Guil-Guerrero, 2014).

Wild foods constitute an essential component of people's diets around the world

(Sanchez-Mata et al., 2012). However, apart from a handful of studies (Schunko and

Vogl, 2010; Schunko et al., 2012), quantitative data on wild food collection are scarce

and scattered. By wild edible plants we intend a food- centered subcategory of the

category utilized wild species (Maxted et al., 2011a, 2011b) that includes Crop Wild

Relatives (CWRs) and neglected crops that have the potential to diversify on-farm

production and regional diets. It mostly includes native species growing in their natural

habitat, but that may be managed, as well as introduced species that have been

domesticated (Hadjichambis et al., 2008; Menendez-Baceta et al., 2012). Despite the

wide spread use of nontraditional foods and their cultural importance, they lack

recognition as significant contributors to the human diet. Plant and animal domestication,

perhaps the most important cultural development of the past 13,000 years of human

history has resulted in the selection and use of a limited number of species for cultivation

and commercialization (Heinrich et al., 2006a, 2006b).

Scholars have shown that nontraditional vegetables often contain high

concentrations of minerals, proteins, vitamins A, C and significant percentages of fiber

than in cultivated vegetables (Alam et al., 2014). The nontraditional vegetables were

observed to be, relatively, good sources of vitamin B6 and ascorbic acid as they can

provide the recommended dietary allowance for daily healthy living (Akpana et al.,

17

2017). Nontraditional plants also generally contain a large spectrum of plant secondary

metabolic products like polyphenols, terpenoids, polysaccharides, nutraceuticals

(functional foods) which are potentially health-promoting agents. More than a simple

food, nontraditional vegetables may constitute proto-dietary supplements with

hypothetical cardio and chemo preventive properties (Visioli et al., 2004). Several plants

produce biologically active secondary metabolites mainly involved in plant defense

mechanisms (Visioli et al., 2011). Therefore, nontraditional plants are interesting sources

of potentially anti-bacterial products, which might theoretically be exploited in the

current search for novel antibiotics (Courvalin, 2016). The FAO (2010) reported that

nutrition and biodiversity converge to a common path leading to sustainable development

and food security and that wild species and intra species biodiversity have key roles in

global nutrition security. Accumulated evidence shows that wild edible plants provide

substantial health and economic benefits to developing countries (Shumsky et al., 2014).

The vegetables and their consumable parts differ from one area to another.

In many areas individuals eat leaves and in some they prefer the tubers, flowers and seeds

depending on the type of indigenous plant and the area or region. The edible parts are

mostly cooked as soups and stews. Concern has been communicated about the decrease

in the utilization of these vegetables. Nontraditional vegetables are at present neither

broadly consumed nor produced in vast amounts because people are not aware of their

nutritional quality and westernization prompted a negative impression of these vegetables

(Keith, 1992).

18

Policy makers and researchers have ignored nontraditional vegetables,

which resulted in too practically no data is accessible on their utilizations, cooking

techniques and healthful quality or bioavailability of their supplements. Recent research

shows that there are many nontraditional vegetables that could help to improve the

insufficient consumption of nutrients that has resulted from the inaccessibility of

commercial vegetables to marginal people (Modi et al., 2006; Van-Vuuren, 2006; Uusiku

et al., 2010). The decrease in the utilization of nontraditional vegetables can likewise be

ascribed to a reduction in the assortment of nontraditional vegetables and natural products

that are accessible. Moreover, there are various natural, political and financial reasons

that lie at the heart of indigenous learning misfortune with respect to nontraditional

vegetables (Adebooye and Opabode, 2004).

It is archived that nontraditional vegetables are utilized as nourishment

sources as well as therapeutic sources (Ezebilo, 2010). They are supposed to have

antiseptic properties and contain antioxidants, which helps in the prevention of cancer

and hypertension. They are not only used for dietary purpose but also therapeutic, as they

help to generate tissues and stimulate the immune system (Flyman and Afolayan, 2008).

The nontraditional vegetables also play an important role in income generation due to

low agricultural inputs during production (Adebooye and Opabode, 2004; Jansen-van-

Rensburg et al., 2007). In this context the analysis of wild edible plants is important to

identify the potential sources which could be exploited as alternative food (Seal et al.,

2017).

19

Nontraditional vegetables are likewise utilized as medicine. Adebooye and

Opabode (2004) recorded 24 nontraditional leafy vegetables that are utilized for

therapeutic purposes. These vegetables often contain low level of fat, hence, a staple food

for obese people. They are also rich in fiber, a feature that enhances them to decrease the

concentration of high cholesterol level in body (Tope et al., 2017). Lephole (2004)

carried out a survey in Lesotho and observed that 43.7% of the participants used

nontraditional vegetables for the treatment of diabetes and hypertension. The advantages

that nontraditional vegetables offer groups as a food source, income source and

therapeutic source to validate the need to decide current utilize and examine the

capability of future use. The protection of the related indigenous information is

fundamental for the handling and conservation of nontraditional vegetables. Moreover, it

is crucial to exchange the indigenous information to more youthful ladies to guarantee

that the use of nontraditional vegetables proceeds. The mentalities of particularly

youngsters towards nontraditional vegetables decide the potential for future utilization of

these vegetables as a nourishment source.

One reason that leads to lessened utilization of nontraditional vegetables is

unwillingness to walk long distances to assemble vegetables, as reported in the studies

headed by Viljoen et al. (2005) and Jansen-van-Rensburg et al. (2007). As far as parts

eaten, respondents reported that they eat for the most part the leaves except for some

nontraditional vegetables whose fruits are additionally eaten. Labadarios et al. (2005)

found in their study that individuals who grew their own nontraditional vegetables had a

higher consumption of minerals and vitamins. In this way, the production of

20

nontraditional vegetables is exceptionally prescribed as it gives dependable access to

nutritious foods. But, inferable from natural surroundings misfortune the accessibility of

nontraditional vegetables is not ensured (Keller et al., 2005; Viljoen et al., 2005).

The role of wild vegetables in household food security

Nontraditional vegetables are a typical and imperative source of food and

nourishment. These plant species which were at first essential sources of food in

numerous societies have been minimized. Micronutrient deficiencies, particularly in

youngsters, continue to be a worldwide concern and yet many reports have shown the

high nutritive value of nontraditional vegetables. If they are consolidated into the daily

diet, nontraditional vegetables can overcome some of the micronutrient related deficiency

diseases (Bvenura and Afolayan, 2015). The wild edible plants were rich in protein,

available carbohydrate, total dietary fibre and minerals, and it is believed that these plants

could be used for the nutritional purpose of human being due to their good nutritional

qualities, and adequate protection may be obtained against diseases arising from

malnutrition (Seal et al., 2017).

Undernourishment influences around 900 million individuals on the globe

and more than 2 billion experience the micronutrient deficiencies (Fan et al., 2012). As

indicated by the United Nations Department of Economic and Social Affairs (UN-

DESA), world populace which is at present around 7.2 billion is required to develop to

around 9.6 billion by 2050 and a lot of this development is relied upon to be amassed in

poor underdeveloped nations (DESA, 2013). The anticipated increase in worldwide

21

populace, poor management and lack of resources is expected to enhance food demand

and food insecurity in the coming decades (Rosegrant et al., 2008; Fan et al., 2012). The

cultivation of more food using fewer resources to meet a developing world populace and

guarantee food security becomes a topic that generates a lot of global interest. The latest

meaning of food security was coined at the 2006 World Food Summit: ‘a situation that

exists when all individuals, at all times, have economic, social and physical access to

nutritious, sufficient and safe food that meets their dietary needs and food preferences for

an active and healthy life’ (FAO, 2009).

In spite of the fact that an assortment of wild vegetables might be

accessible in an area, reports have demonstrated that reports have shown that only a few

selected ones are accessible for utilization as food (Hadjichambis et al., 2008). The

capacity of nontraditional vegetables to give the required supplements in human

physiology has been generally reported. They have been shown to keep superior

nutritional potentials than the commercial vegetables (Odhav et al., 2007; Flyman and

Afolayan, 2008; Lewu and Mavengahama, 2010; Kayode, 2012). Despite this, the

abundance of data accessible on the nutritional composition of commercial vegetables

alone is insufficient to fulfil nourishment demands.

It is usually believed that food security requires an interdisciplinary

method to solving, bringing the agriculturalists and nutritionists together (Maunder and

Meaker, 2007; Rocha, 2007; Ingram, 2011; Global Food Security, 2013). According to

Labadarios et al. (2008) the South African diet comprises predominantly of the staple

22

food plants and is deficient in differing qualities and thus prompts micronutrient

insufficiencies. These wild edible vegetables are the good source of nutrient for tribal

population, and in addition well comparable with various commercial vegetables. So, the

cultivation of these wild edible species needs to be adopted in large scale, which will

produce economic benefits for poor farmers (Seal et al., 2017). The World Health

Organization (WHO) prior reported that the utilization of fruits and vegetables is not as

much as half of the prescribed 400 g consumption for each day (WHO/FAO, 2003).

However, some authors (Uusiku et al., 2010; Berti et al., 2014) hypothesized that by

including nontraditional vegetable species in the diets will helps to decrease the

micronutrient deficiencies.

Bvenura and Afolayan (2015) stated that the increased consumption of

nontraditional vegetables will help to reduce the malnutrition and food insecurity.

Moreover, if availability of the traditional and nontraditional vegetables is made

throughout the year will results in food stability. This can be done by encouraging people

to cultivate the nontraditional vegetables in their home gardens during their season and

preserve them for later use in offseason. Bvenura and Afolayan (2015) further reported

that nontraditional vegetables are clearly underutilized although they potentially have a

big role to play in food security. Nontraditional vegetables are required to be revitalized

and widely consumed in daily diets to decease food insecurity. The knowledge about

these species may soon be lost if these species to continuous underappreciated and

neglected.

23

Conserving indigenous knowledge as the key to the current and future use of

nontraditional vegetables

Indigenous information includes knowledge about persistence that is

possessed by native people in their societies and is passed on from one generation to

another (Kaya and Masoga, 2005). This information is found in both urban and rural

societies and deals with problems regarding the survival of the community, protection,

use of the local environment and food security. Indigenized information is found in

various areas i.e. food technology, medicine, conflict resolution, peace building, social

welfare and agriculture (Odora-Hoppers, 2004). The knowledge about nontraditional

vegetables is decreasing which must be documented (Aphane et al., 2003).

Nontraditional vegetables are part of local knowledge and nontraditional

production systems. These vegetables are consumed locally over a number of years, but

did not cultivate (Keller et al., 2004, 2005). Nontraditional vegetables are those edible

plants that are biologically indigenous to an area, while commercial vegetables require

various agricultural related inputs to grow. Indigenized vegetables are local and adapted

to the native environmental conditions (Laker, 2007).

The significance of nontraditional vegetables lies in their high nutritional

quality and their capacity to flourish under unfriendly conditions. Nontraditional

vegetables and nontraditionally crops grow well during dry periods and in regions with

low rainfall. Nontraditional vegetables can survive poor soils, require less inputs,

24

chemical fertilizers (pesticides) and assets during production since they are adapted to the

local environmental conditions (Lephole, 2004; Modi et al., 2006; Van-Vuuren, 2006).

The utilization of nontraditional vegetables is diminishing even in the rural

areas for introduced vegetables and neglected by both researchers and policy makers

which in turn lead to the insufficiency of knowledge about nontraditional vegetables

(Jansen-van-Rensburg et al., 2007). Since documentation on nontraditional vegetables is

rare, elderly individuals remain the most important sources of data. The apprehension

exists that if nothing is done to monitor profitable data on nontraditional vegetables this

data may soon vanish from society, in light of the fact that the adolescent are generally

reluctant to increase such knowledge (Vorster et al., 2007). The exchange of indigenous

information on nontraditional vegetables will guarantee that the accessibility and use of

nontraditional vegetables will be kept up as an essential food sources for asset poor

country groups. Besides, the transfer of the indigenous learning connected with

nontraditional vegetables to the younger generation holds the way to the potential future

utilization of traditional vegetables.

Archiving the utilization of plants by ethnic minorities and tribal

individuals is not just a critical part in understanding and analyzing components of

conventional knowledge, additionally an approach to sustain information at danger of

being lost (De-Boer and Cotingting, 2014). Various research works have shown that

indigenous knowledge of nontraditional vegetables is vanishing in communities (Flyman

and Afolayan, 2008; Musinguzi et al., 2006; Jansen-van-Rensburg et al., 2007; Lwoga et

25

al., 2010). The loss of indigenous information results in less utilization of nontraditional

vegetables, which adds to the lack of diet diversity. This at last translates into food

instability and micronutrient deficiency, particularly among poor communities (Flyman

and Afolayan, 2008). Diverse factors have added to the loss of information about

nontraditional vegetables. These incorporate the introduction of new vegetables,

legislative issues, changes in way of life, habitat loss and the stigma connected with the

utilization of nontraditional vegetables (Keller et al., 2005).

Introduction of new commercial vegetables and Stigma attached to the use of

nontraditional vegetables

The introduction of new conventional vegetables has been referred to as

one of the reasons for the loss of information about nontraditional vegetables. The

conventional vegetables are broadly advanced by agricultural extension and research, in

this way prompting the complete substitution of nontraditional vegetables (Jansen-van-

Rensburg et al., 2007). Recently presented vegetables likewise give financial worth to the

farmers since they are exceptionally prominent and can be effectively promoted. Farmers

are accordingly more excited about the production of these new vegetables than

nontraditional vegetables that are difficult to market to vast (Musinguzi et al., 2006). An

absence of clear custodianship, little comprehension of sustainable management practices

and information of market sector prerequisites, place natural habitats, coupled with poor

social position and economic opportunities for gatherers and lacking institutional

structures and populaces of therapeutic plants at danger (Sher et al., 2010).

26

Negative attitudes towards the utilization of nontraditional vegetables have

additionally been referred to as one reason that adds to the loss of information. In many

ranges, nontraditional vegetables are connected with primitiveness and poverty.

Therefore, many people, particularly the young have stopped utilizing nontraditional

vegetables since they would prefer not to be marked as backwards (Jansen-van-Rensburg

et al., 2007).

Some nutritional challenges of nontraditional vegetables

Nontraditional vegetable plants play an important role in the health of

millions of people’s life in many villages ranging from 75– 80% of the world population,

mainly targeting primary health care in the developing countries because of better

cultural acceptability, compatibility with human body and lesser side effects (Kumar et

al., 2017). The incorporation of nontraditional vegetables into the diet has been ruined by

cultural and social issues in a few communities and a few authors have raised different

concerns over the suitability of these species to supply the required nourishing necessities

in the body. The nearness of antinutrients, for example, oxalate, phytic acid, saponins,

tannins and alkaloids in nontraditional vegetables has raised some serious concerns. In

the human body, oxalate ties to calcium to form calcium oxalate stones that prevent the

assimilation and usage of calcium leading to sicknesses, for example, osteomalacia and

rickets (Ladeji et al., 2004). Tannins can hasten certain proteins by joining with digestive

enzymes in this way making them inaccessible for absorption (Abara, 2003). Phytic acid

consolidates with some crucial components, for example, iron, zinc and phosphorus to

27

frame insoluble salts known as phytate. In Brazil, elevated amounts of tannins were

accounted for in the leaves of Talinum fruticosum (Leite et al., 2009). In spite of the fact

that Lola (2009) reported that some anti-nutrients, for example, tannins and oxalate are

health labile, heating T. fruticosum leaves did not change the composition of these anti-

nutrients. Though, in Nigeria, some common wild vegetables including Amaranthus,

Solanum and Corchorus species were found to contain low levels of these anti-nutrients.

(Agbaire, 2012). Despite the great advances observed in modern medicine in recent

decades, nontraditional vegetable plants still make an important contribution to health

care (Kumar et al., 2017).

In South Africa, Ndlovu and Afolayan (2008) found the leaves of C.

olitorius to contain different levels of phytate when compared with spinach and cabbage.

An investigation of Erythrina Americana in Mexico showed that the eatable flowers

contained noteworthy measures of alkaloids; whereas, these were disposed of by

discarding the water after boiling (Sotelo and Lopez-Garcia, 2007). The mineral content

while comparing with recommended dietary allowance, it reveals that the nontraditional

vegetables are good source of calcium, iron and zinc (Tope et al., 2017). Although some

nontraditional vegetables have been accounted for to contain some antinutrients, others

contain a few phytochemicals, for example, antioxidants that are valuable in human

physiology.

Antioxidant activities have been accounted for in an assortment of some

nontraditional vegetable species from different parts of the world (Afolayan and Jimoh,

2009; van-derWalt et al., 2009; Pereira et al., 2011; Morales et al., 2013; Garcia-Herrera

28

et al., 2014a and 2014b). These reports from different parts of the world demonstrate that

diverse nontraditional vegetables from various geological areas contain shifting measures

of phytochemicals including cancer prevention agents and antinutrients. The behavior of

phytochemicals, particularly antinutrients in nontraditional vegetables is a subject that is

not yet completely comprehended, thus needs more research. A comprehension of the

negative or positive effect nontraditional vegetables have on nutritional absorption in

human physiology will develop reasonable food security techniques.

Bvenura and Afolayan (2015) exhibited that the incorporation of

nontraditional vegetables in the eating routine could go far in handling malnutrition and

food insecurity particularly in children who are the most susceptible. Above all, there is a

need to educate the general population about the significance of nontraditional vegetables

so that their states of mind can change. The false and negative observations

encompassing the utilization of nontraditional vegetables, for example, poverty foods,

foods for women, children and the elderly and additionally drought foods should be

especially changed. The younger generation who are the future caretakers of this

information should be urged to welcome these assets while preservation of the current

species through exploration should be amended. Cultivation of the favored species

particularly those with positive organoleptic and healthful qualities should be supported.

Nutritional and Health Benefit information of nontraditional vegetables

Nontraditional vegetables are excellent sources of nutrients and energy,

besides they provide the bulk of daily calories and around 65% of the protein (Bennett,

29

2016). Interest in nontraditional vegetables has fundamentally expanded in Europe, and

somewhere else, in light of the fact that they give high nutrient levels and potential health

advantages (Garcia-Herrera et al., 2014b). The consumption of nontraditional vegetables

has generally assumed an essential part in supplementing staple farming foods in

numerous nations and their commitment to the Mediterranean diet is very much recorded

(Hadjichambis et al., 2008; Tardio, 2010). A few studies showed the essential role played

by nontraditional species as excellent source of macro and micronutrients in adding to

human dietary prerequisites (Flyman and Afolayan, 2008; Tardio et al., 2011). The

nutritional composition of nontraditional foods indicates that most of these foods are good

sources of carbohydrate, moderate sources of protein, fat, phosphorus, and iron and low sources

of dietary fibre, vitamin D, and calcium. Moreover, they provide substantial amounts of phytate

and smaller amounts of oxalate (Al-Faris, 2017).

Additionally, nontraditional vegetables may have part as functional foods

as they contain physiologically active foods and give health advantages beyond basic

nutrition, indicating potential biological activity of interest for the prevention of several

chronic diseases (Flyman and Afolayan, 2008). Therefore, these nontraditional plants

have been minimal concentrated as foods and are excluded in food composition databases

because of the lack of information on their composition in scientific writings (Garcia-

Herrera et al., 2014b). In this way, many individuals harvest nontraditional vegetables for

their substantial contribution to the diet as healthy components, for example, minerals,

cancer prevention agents and vitamins. In this way, the convention of eating

unconstrained plants is still alive as well as is expanding subsequent to the nontraditional

vegetables are viewed as healthy and natural foods (Pereira et al., 2011; Renna and

30

Gonnella, 2012; Sanchez-Mata et al., 2012). Nontraditional foods can be used in the

prevention and management of obesity, cardiovascular disease and diabetes mellitus.

Country dietary guidelines should take into consideration the nutritive value and health

aspects of these foods and encourage the consumption of healthy traditional foods (Al-

Faris, 2017).

Nontraditional vegetables are an imperative source of phytonutrients that

are fundamental for human body and can be incorporated into numerous vegetable salad

dishes to enrich dietary sources of health promoting compounds (Kaliora et al., 2015;

Kumar et al., 2015). Moreover, the utilization of wild edible nontraditional vegetables

has considerably decreased during the last few decades (Turner et al., 2011; Morales et

al., 2013). The worldwide interest for the supposed "health" or "super-foods" has revived

the market sector requirements for wild palatable species consumed as salad vegetables

and greens, subsequent to their expansion could supplement human eating routine and

supply human body with essential trace elements and vitamins (Barros et al., 2010).

Most of nontraditional edible vegetable species have medicinal property

and can be used to keep people healthy and fit. Further phytochemical and nutraceutical

studies of these edible species may provide better nutritional source. Apart from the

source for food, human also utilize plants for dyes, ornaments and medicines.

Nontraditional edible vegetable is source for nutrition but also possess higher medicinal

property. These nontraditional vegetable plants are grown in forest region without

chemical / fertilizer. Most of nontraditional vegetable are grown naturally without proper

31

cultivation technique in forest area; specifically, during monsoon season and collected by

tribal people. Tribes are part of nature; they fulfill their need through wild resources.

Their knowledge is based upon traditional sources (Seema, 2015).

Nutritional analysis of nontraditional vegetable demonstrates that the

nutritional quality of nontraditional vegetable is comparable and in some cases, they are

superiors to domesticated verities (Seema, 2015). Nontraditional foods have potentially

useful applications in planning normal and therapeutic diets (Al-Faris, 2017). The major

nutritional compounds that are present in nontraditional vegetable plants are

carbohydrates in the form of starch and sugars, protein, lipid, in the form of oil, vitamins,

minerals, etc. Apart from these antioxidants, like ascorbic acid, phenols such as

cholorogenic acid and its polymers are available in plant because of these component, the

wild vegetable most have potential to improve physical as well as mental health, help in

reduce the risk of disease. There is therefore a need to explore the vast varieties of

nontraditional vegetables as food by man (Edogbanya, 2016).

Factors affecting nutrient content of vegetables

The biosynthesis and concentration of nutrients differ generally among

nontraditional vegetables and on the effects of hereditary and environmental factors

(temperature and light), harvest practices, growing conditions and postharvest techniques

(Rouphael et al., 2012). Light also plays an important part in operating photosynthetic

and phytochemical activities (Bian et al., 2015) as the phytochemical synthesis and

32

accumulation in plants is highly related with photosynthates (Wu et al., 2007). Hence

therefore, to increase the phytochemical accumulation, the presence of optimal light is

very important (Bian et al., 2015). Post-harvest losses and quality deterioration of

vegetables are mostly caused by pests, microbial infection, during ripening and

environmental status (Idah et al., 2007; Olayemi et al., 2010). It occurs through all or at

least one of post-harvest activities such as harvesting, handling, storing, processing,

packaging, transporting and marketing (Mrema and Rolle, 2002).

The shelf life of vegetables is influenced by various means, for example,

growing strategies, post-harvest processes, processing and storage conditions. Among

these variables, the stage of ripeness at the season of harvest is one of the most important,

as it influences both the shelf life and the eating value of fresh cut vegetables and foods.

Specifically, fresh cut vegetables are harder to protect than other less processed items

since some of them must be totally ripened before processing (Gorny et al., 2000).

Effect of processing methods on nutrient loss

Traditional and nontraditional vegetables are compared by many authors

and found the later more nutritious (Odhav et al., 2007; Afolayan and Jimoh, 2009). The

processing of vegetables, for example, drying and cooking cannot be without impact on

their nutritional attributes. Cooking brings both chemical and physical changes to food

(Rehman et al., 2003). Additionally, food additives further change the nutritious

composition of vegetables. It is basic practice to utilize additives, for example, flavors

33

and spices to upgrade the taste of nontraditional vegetables in this way altering the

original nutritional state of the vegetables. Different processing techniques would

subsequently affect contrastingly on different particular nutrients. In Pakistan, it was

found that boiling decreased the fiber, fat and protein compositions. Ching (2010)

reported in his report that cooking these nontraditional vegetables for long at high

temperatures decreased greatly antinutrients, antioxidants and micronutrients. In his

study, stir frying declined phytate, oxalate, Zn, Fe, Mg and Ca whereas boiling essentially

decreased protein, fat and fiber contents.

Effect of cooking on vegetable processing

Ilelaboye et al. (2013) stated that blanching a variety of nontraditional

vegetables declined their Zn, Cu, Mn, Fe, Mg, Na, K and P contents while cooking the

unblanched samples enhanced the same minerals. Reports have demonstrated that

cooking blanched samples significantly decreased nitrite, nitrate, cyanide, tannin,

saponins, oxalate and phytate while the raw samples contained essentially large amounts

of these antinutrients. At the Virginia State University, raw samples of Urtica dioica

contained large quantities of vitamin A, vitamin C, protien, sugars, fiber and fats (Rutto

et al., 2013). While some nontraditional vegetables, for example, S. oleraceus can be

eaten raw as salads, some should be cooked before intake, for instance S. nigrum and

Urticaurens among others.

34

The nutritional composition of nontraditional vegetables differs after

introduction to heat subsequently; there is a need to treat each vegetable as a unique food.

In South Africa, the majority of nontraditional vegetables are cooked by boiling while

bicarbonate of pop, groundnuts, onions and tomatoes are incorporated as added

substances to upgrade the taste (Nesamvuni et al., 2001). This further increases the

nutritional value of the nontraditional vegetables and subsequently brings down

malnutrition ratio. Presenting nontraditional vegetables to cooking may lessen some

amount of nutrients yet cooking is utilized to upgrade their organoleptic attributes in this

way enhancing their adequacy and part in food security (Subhasree et al., 2009).

Cooking can be performed in different ways at the same time, for

nontraditional vegetables, most basic are microwaving, boiling and steaming. These

cooking procedures would bring about various changes in chemical composition and

physical qualities of the vegetables (Zhang and Hamauzu, 2004). Literature on the

impacts of cooking on the antioxidants in vegetables has been uncertain. There are

reports showing an upgrade or no change in antioxidants activity of vegetables (Turkman

et al., 2005) while others have shown a decline in antioxidant content after cooking

(Zhang and Hamazu, 2004). The diversity and presence of phytochemicals in

nontraditional vegetables are essential components for human wellbeing. Since a

substantial part of ingested nontraditional vegetables are generally thermally handled

before consumption, it is additionally important to investigate how the processing

influences the levels of these compounds (Volden et al., 2009).

35

Processing of nontraditional vegetables for consumption exposes the

phytochemicals present to detrimental factors that may lead to changes in their health

related quality. For instance, wet-thermal treatment causes denaturation of enzymes that

can catalyze breakdown of phytochemicals and nutrients. Then again, processing by heat

can bring about decrease of constituents by leaching or due to thermal destruction

(Rungapamestry et al., 2007). Turkmen et al. (2005) showed that distinctive cooking

strategies (microwaving, steaming and boiling) led to the reduction in phenolics from

leek, peas and squash. Watchtel-Galor et al. (2008) found that microwaving and steaming

brings losses in the total phenolic content of cabbage, choy-total and broccoli while

steaming showed less reduction as compared to microwaved samples. Similarly, Volden

et al. (2009) reported the loss of phytochemicals up to 19% in steamed cauliflower.

It is notable that handling of vegetables promotes a faster microbial

degradation, biochemical changes and physiological deterioration of the item even when

just slight preparing operations can be used (O’Beirne and Francis, 2003), which may

bring about degradation of the flavor, texture and color (Varoquaux and Wiley, 1994).

While traditional food processing strategies broaden the shelf life of vegetables and

fruits, the minimal processing to which fresh cut vegetables and fruits are subjected

renders items exceedingly perishable, requiring chilled capacity to guarantee a reasonable

shelf life (Garcia and Barret, 2002).

Frying is a typical prominent procedure used throughout the world to

generate products with good sensory and organoleptic attributes. In tropical nations, fried

items comprise for the most part of starchy foods (cassava, plantain, potatoes etc) which

36

are characterized by a high initial water content (60-80%) and low nutrient content. The

product during frying undergoes two correlated mass transfers i.e. oil uptake and water

loss. During broiling, the item experiences two associated mass exchanges: water loss

and oil uptake. The dietary value of last product is thus affected by the nature of the oil

used for frying. Since, frying oils differ from each other on the basis of fatty acid content

(saturated and unsaturated) and fat soluble nutrient (sterols, tocols, carotenoids and so

forth). Firstly, the degradation (oxidation or thermal) of fatty acids (mainly unsaturated)

and micronutrients is activated by the high temperatures involved during frying (Valdes

and Garcia, 2006).

The frying oil is used several times (10-15) before renewing and it must be

taken into account to limit the loss of nutrients in order to guarantee the economic and

nutritional sustainability of the process. Furthermore, an uncontrolled frying technique

(temperature more than 180°C, an excessive number of frying baths, inappropriate oil,

and so on.) can lead to the formation of lethal compounds in the final product

(acrylamide) or in the oil (oxidized triglycerides) (Bassama et al., 2012). At last, from a

dietetic point of view, fried products might be attractive or not and may contain varying

proportions of saturated fats. Every one of these viewpoints has incited concentrates on

enhancing the nutritional quality of final product by controlling the frying procedures.

The principle "degrees of freedom" for control of the nutritional value of an item during

frying was the temperature. However, decreasing the frying temperature (120-130°C)

resulted in reduced oil degradation and loss of nutrients as well. Indeed, unsaturated

37

(non-refined) oils bear interesting nutrients could be used with good frying practices

(Achir et al., 2010).

It is realized that cooking impels huge changes in chemical composition,

influencing the bio-accessibility and the concentration of nutrients, for example,

polyphenols, carotenoids and vitamin C (Pellegrini et al., 2010). Mazzeo et al. (2015)

reported that both steaming and boiling strategies could influence nutritional properties of

frozen vegetables in an alternate way.

Effect of drying methods on nutrient content

The fresh vegetables and fruits due to their high moisture content (upto

80%) are highly perishable and can deteriorate within short time if improperly handled

(Orsat et al., 2006). Drying is the procedure that involves the removal of water to stop or

reduce the growth of microbial contamination and enzymatic browning (Argyropoulos et

al., 2011; Kurozawa et al., 2012) which in turn help in preserving the nutritional value

and sensorial characteristics of the foods (Aguilera, 2003). There is the rapid growth rates

(3.3%) observed in the market value of dehydrated vegetables and fruits throughout the

world (Zhang et al., 2006). Drying of foods is the most common and oldest technique

involving the controlled transfer of heat (Mujumdar and Passos, 2000). Vegetables and

fruits are commonly dehydrated to reduce transport weight, minimize packaging

requirements, to enhance storage ability and to extend the shelf life (Ahmed, 2011). The

common methods used for drying the foods involve sun or hot air drying. Since solar

drying is the slow process which can be affected by birds, insects and rodent’s

38

infestation, Weather uncertainties, windblown debris high humidity (rain) and haze

(Ringeisen et al., 2013). Drying is amongst the most widely recognized food processing

strategies that can be utilized to extend the shelf life and to accomplish the required

qualities of a food items. Decreasing the water activity (aw) of food by means of this

procedure can reduce deterioration from microbial activity and chemical reactions

(Chiewchan et al., 2010).

According to Vorster et al. (2007) that preservation of nontraditional

vegetables helps to ensure food accessibility throughout the year, but Flyman and

Afolayan (2008) stated that it affects the nutritional quality of the foods like many other

processing treatments. Vorster et al. (2007) further surveyed that all the Xhosa

households dried vegetables without blanching them first which in turn largely affected

the nutritional content of vegetables. Flyman and Afolayan (2008) reported that when

vegetables are dried without prior blanching in direct sunlight leads to the destruction of

nutrients. Hassan et al. (2007) reported that the solar drying is hygienic, faster and have

no effect on the nutrients.

Sensory evaluation

The desireability of any food product is depend on its quality which can be

determined by objective and sensory methodologies. The psychometric, sensory,

organoleptic and subjective tests are taken by human organs to check the quality of food

(Srilakshmi, 1996). The senses used in sensory evaluation include tactile, taste, odor,

39

temperature, etc. Scientific methods of sensory analysis of foods are becoming

increasingly important in assessing the acceptability of food products (Jellinek, 1985).

Importance of sensory evaluation

The sophisticated food quality measuring instruments including nuclear

magnetic resonance spectrometers, gas chromatography, mass spectrometers, IR and UV

spectrophotometers, etc has increased the importance of sensory analysis. The optimal

information be obtained by the coordination of instrumental and sensory analysis. Even at

the limit of the instrumental sensitivity, e.g. where no signal appears, our biological

detector (our senses) may still perceive an odor, taste, etc. Furthermore, the instruments

will only analyze single components, whereas our senses give us a total impression of

flavor, odor, temperature and tactile components (Jellinek, 1985).

Conclusions

The literature review suggests that the awareness campaigns can help to

aware people’s knowledge about nutritional qualities of nontraditional vegetables.

Moreover, the loss of nurients occur during different cooking processes, hence therefore

there is a dire need to develop such cooking methodologies which ensure minimal loss of

nutrients in cooked vegetable. This will promote the confidence of users and general

utilization of nontraditional vegetables. It was also revealed that there is a lack of cooking

methods which in turn cause the taste of nontraditional vegetables less appealing and

boring. This would increase the interest of people to the consumption of nontraditional

vegetables which in turn also produce diet diversity for human being.

40

CHAPTER-III

MATERIALS AND METHODS

This section comprises the methodology used in the present research

study, i.e. location or description of the study area, type of the data, sources of the data,

sampling methods, data collection methods and analysis of collected samples.

Purpose of the study

The purpose of this study was to examine how rural residents of the lower

Sindh navigate their nutrition environment to obtain the foods they eat. The research was

aimed at selecting the inhabitant’s own perceptions about consumption and nutritional

quality of the selected nontraditional vegetables were explored. The selected

nontraditional vegetables were then also compared with the nutritional values of standard

commercial vegetable (Figure 1).

Description of research area

Perspective/ Status of vegetable production in Sindh

Agriculture is the backbone of the Pakistan’s economy, its development

and progress is therefore linked directly to the agriculture sector contributing 25% in the

Gross Domestic Product (GDP) of the Pakistan (GOP, 2011-12).

41

Figure 1. Schematic representation of the methodology used in the present study

NUTRITIONAL ASSESSMENT OF SOME NEGLECTED AND UNDERUTILIZED

VEGETABLES WILDLY GROWN IN SINDH

Survey of Mirpurkhas district

Collection, weight determination and transportation of nontraditional

vegetable samples

Identification of nontraitional vegetables grown in Mirpurkhas

district of Sindh province

Sample treatment and percentage non-edible and edible portions of

selected vegetables

Edible portion Non-Edible portion

Discarded

Thermally Dehydrated Shade Dried Fresh

(control)

Boiled

Nutritional Analysis

Statistical Analysis of obtained data

Cooked Curry

Data Analysis

Fresh

(control)

Chlorophyll content

Statistical Analysis

Curry

Sensory Analysis

Statistical Analysis

Fresh (raw)

42

On the basis of population and agriculture input, Sindh is regarded as

second biggest province of Pakistan, situated on the lower bank of river Indus. Sindh

represents about 23% (32 million) of the total population of Pakistan and on geographical

basis, it covers 18% of the area i.e. 140935 Km2

(14.09 million hectares). Sindh has 40%

of the total arable land with 5.88 million cultivated areas and 2.39 million hectares of

sown area. Hence, there are about 3.10 million hectares of total cultivated area, of which

0.71 million hectares of the land are used more than once for sowing purpose. The

climate of Sindh is an overall arid zone with rare monsoon rains that come in the rotation

of 4 to 5 years, leaving the canals as the only source for irrigating the crops. The hottest

months of the Sindh province are recorded from May to July i.e. above 40 ᴼC with

occasional frost (Development statistics of Sindh, 2011).

District Mirpurkhas

The description of selected district is according to agricultural statistics of

Sindh (Development statistics of Sindh, 2011) as shown in Figure 2.

The district Mirpurkhas is situated at the South-East corner of the

province. It lies from 25-9' to 29-17' North latitude and 69-3' to 69-26' East longitude.

It is bounded on the North by the district of Sanghar, in the East by the newly created

district Umerkot bordering the Bermet/Marwar and Jaisalmir districts of India, on the

West by the district of Hyderabad and in the West-South by the district Badin, in the

south by the district Thar bordering the Rann of Kutch. The Mirpurkhas District

comprises 2991 km2 (2.10%) of the total geographical area of Sindh, with the total

population of 1.4 million souls accounted in 2012. The highest and lowest recorded

43

temperatures of the district are 41C and 9 C, respectively. June and September are the

monsoon months and there is insignificant rainfall recorded in the winter season

(Wikipedia).

Figure 2. Map showing selected district of Sindh Province, Pakistan

44

Survey of Mirpurkhas district

Identification of wild vegetables grown in Mirpurkhas district of Sindh province

The questionnaire survey methodology was used to collect the data on the

utilization and consumption of nontraditional and commercial vegetables in culturally

and ecologically diverse area, Mirpurkhas of Sindh province, Pakistan in 2014.

All relevant farmers were informed at first about the study, its objectives

and how the study would be conducted then a consent letter (Appendix XLIII) was signed

by each participant farmer after explanation in Sindhi (local language) showing that they

were agreed to participate in this research project conducted by PhD scholar and her

consulted supervisor / advisor of IFST, SAU, Tandojam.

Each respondent agreed that their participation was strictly voluntary. The

farmer’s response to every question was written in the structured questionnaire form

(Appendix XLIV), recorded and kept for in a locked file cabinet. The questions were at

first explained in Sindhi (Local language) to each participant and the information was

documented. The process was very extractive in the beginning, but as trust and respect

between community members and research team developed participation grew.

Design of the questionnaire

The questionnaire was designed according to the problem tree methods

proposed by Fink (1995), with mainly closed questions that were based on the opinions

of key informants. The information that was gathered through these activities was used to

help develop the questionnaire. A problem tree was developed that addressed all of the

45

objectives that needed to be answered by questionnaire. These objectives were broken

down into questions that needed to be answered to address these specific objectives. The

questions were discussed with experts (sociologist, extension, personnel and researchers)

to ensure that they measured the objectives accurately. The questions were very specific

to minimize possible misunderstanding between enumerator and respondent. Open

questions were used in areas where answers were expected to be variable. The local

experts, villagers and reference books on local plants were extensively used as sources

for plant identification and distribution. Census data were used to help understand the

community and population better. As early as 1937, Sletto found that respondents would

rather agree as disagree (Mounton and Marais, 1993), thus such questions were avoided.

The question asked of respondents to describe certain aspects and the enumerators ticked

off what was mentioned.

Sample size or sampling of farmers from Mirpurkhas district of Sindh

Systematic sampling (Fink, 2003) was used to identify the respondents in

the selected District, as sampling frames were difficult to obtain and not very complete.

The farmers were randomly selected for the face to face interviews. Determination of

minimum sample size of 100 respondents district Mirpurkhas was done according to the

method of Bartlett et al. (2001), so as to achieve a maximum error of 5 % at a 95 %

confidence level. In this way every element in the population has the same chance of

being selected. Therefore, sampling was done “without replacement”.

46

Methods of data analyses for survey

The data of survey was coded and analyzed by using descriptive statistics

module of SPSS-16 for presenting in frequencies and percentage counts.

Selected agricultural locations and vegetable production

District Mirpurkhas was surveyed in this study. The vegetables that were

focused to be cultivated were spinach whereas there were other vegetables too, which

were not cultivated and even without any agricultural input, i.e. Amaranthus, Horse

radish tree flowers and Lambs quarter. The Gram crop is cultivated as pulse crop purpose

but its leaves are consumed in rural villages as nontraditional vegetable. These

nontraditional vegetables are considered as weeds growing in the fields without any labor

and farm inputs. At present these nontraditional vegetables are discarded by the growers

because of lack of awareness. These vegetables have also a great importance because

these grow in commercial crops (such as sugarcane, cotton, wheat, rice, etc).

Nontraditional vegetable specimens were recognized with the help of flora of Pakistan by

using the Nomenclature of Nasir and Ali (2005) (Table 1, Figure 3).

47

Table 1. Enumeration of selected vegetables

Plant Name English

name

Local

name Family Position

Parts

Used Status

Amaranthus

viridis L. Amaranthus Mariro Amaranthaceae

Leafy

vegetable Leaves Wild

Cicer

arietinum L. Gram Channa Fabaceae

Leafy

vegetable Leaves

Cultivated as

pulse crop,

leaves under-

utilized as

vegetable

Chenopodium

album L.

Lambs

quarter Jhil Chenopodiaceae

Leafy

vegetable Leaves Wild

Moringa

oleifera L

Horse radish

tree flowers Suhanjhro Moringaceae

Flower

vegetable Flowers Wild

Spinasia

oleraceae L. Spinach Palak Chenopodiaceae

Leafy

vegetable Leaves Cultivated

48

English name: Amaranthus English name: Gram leaves

English name: Horse radish tree flowers English name: Lambs quarter

English name: Spinach

Figure 3. Pictorial view of selected vegetables

49

Analysis of uncooked vegetables

Collection of vegetable samples

Sampling was conducted according to the international standard guideline

(SAC, 2008). Spinach, Horse radish tree flowers, Gram leaves and Lambs quarter were

collected in January, 2014; whereas, Amaranthus was collected in the months of July-

August, 2014 from Mirpurkhas district. The vegetables (Spinach, Amaranthus, Gram

leaves and Lambs quarter) were collected by cutting the stem approximately 3 cm from

the soil surface. Whereas, the Horse radish tree flowers were plucked from tree with care.

At each sample location, fresh, non- infested and un-damaged vegetable samples were

collected from three different sites to provide replicate samples of each plant.

Weight determination and transportation of veteable samples

The weight of the vegetables was obtained by placing the vegetables on

pre-weighed pan digital top loading balance and the reading was noted carefully. Sample

size for each vegetable was at least 10 kg and was taken among commodities considering

high consumption rate. Samples were transferred aseptically into sterile Nasco Easy-to-

Close Whirl-Pak sample bags (Fisher Scientific) without washing. Sample bags were

marked on the exterior surface with the following information: product type, sample

number, sample location, date of collection and placed in an ice chest box and transported

to the laboratory of IFST, SAU, Tandojam on the same day. Samples were stored in

refrigerator at 4°C for 1-2 days until traditionally processed.

50

Treatment of uncooked vegetable samples

The edible parts were separated from their respective non-edible parts.

The samples were washed, removed nonedible portion, cut according to the nature of

vegetable. Edible parts of the plants are those which intended for cooking or eating as

raw, for example leaves, shoots, flowers, etc., whereas non-edible parts of the plants are

those which we do not eat such as seeds, stem, roots etc. Edible parts were washed with

mild rubbing under running tap water for 25-30 seconds to remove unwanted materials

(dirt and debris) and placed in a hung strainer in the air to drain away extra water. The

remaining moisture was evaporated by spreading samples on a stainless steel tray at

room temperature for 30 minutes. Blanching treatment was avoided due to increased

losses of nutrients as well as unwanted color change (Arya et al., 1979; Baloch et al.,

1997).

Non-edible and edible portions were weighed and the percentage of non-

edible portion (skin, seeds, etc.) of selected vegetables was calculated by the following

formula:

The percentage of edible portion of selected vegetable was calculated by the formula

For each selected vegetable the percentage of non-edible and edible portions are given in

the Table 2.

51

Table 2. Percentage non-edible and edible parts of the selected vegetables

Vegetable names Total

weight

Weight

of edible

part

Weight of

non-

edible

part

Percentage

edible

portion

Percentage

non-edible

portion

Spinach (Spinacia

oleracea)

10 kg 6.9 kg 3.1 kg 69% 31%

Amaranthus

(Amaranth Virdis)

10 kg 6.7 kg 3.3 kg 67% 33%

Horse radish tree

flowers (Moringa

oleifera)

10 kg 6.3 kg 3.7 kg 63% 37%

Lambs quarter

(Chenopodium

album)

10 kg 6.8 kg 3.2 kg 68% 32%

Gram leaves (Cicer

arietinum)

10 kg 6.1 kg 3.9 kg 61% 39%

Treatment for fresh uncooked samples (Control)

The first set of all the vegetables was cut into smaller pieces with a sharp

stainless steel knife and packed in properly labeled polyethylene bags and kept in a deep

freezer at -20± 1°C until analyses was performed within twenty four hours.

Sample preparation for processing methods

Six kilograms (6 kg) of each vegetable sample were separated for further

analyses. The samples were divided into five (5) sets. 1st set was (1 kg) and packed in

properly labeled polyethylene bags to serve as control. 2nd

set (1 kg for each) was

subjected to boiling. The boiled sample was divided into two equal portions, out of which

one portion was packed as it is while other was subjected to cooking with standard

52

ingredients. The 3rd

and 4th

set was subjected to thermal dehydration and shade drying.

The details of each set treatment are given below:

Treatment for fresh samples (Control)

The first set of all the vegetables was cut into smaller pieces with a sharp

stainless steel knife and packed in properly labeled polyethylene bags and kept in a deep

freezer at -20± 1°C until analyses was performed within twenty four hours.

Treatment for boiled samples

The second set of vegetable samples was cut into evenly sized chunks.

The water was added to boiling pan and allowed to boil before addition of vegetables.

The amount of water was kept minimum just to cover the vegetable samples in order to

reduce the nutrient loss in water. The vegetable samples were boiled for 5 minutes and

then the water was drained. The samples were allowed to cool at room temperature and

then packed properly in pre-labelled polythene bags. The packed samples were then

placed in deep freezer at -20± 1°C until analyses.

Treatment for making vegetable powder

The 3rd

and 4th

set of all the vegetables was subjected to thermal

dehydration and shade drying. The leaves and flowers were kept in a butter paper

envelope and dried in an oven (Model: FPM-05-0401, GLSC equipment’s Pakistan) at

55ºC for 24 hours (Abuye et al., 2003). Similarly, for shade drying the samples were kept

on stainless steel tray lined with butter paper at room temperature for 24 hours. The dried

53

samples were pounded into fine powder using a laboratory pestle and mortar. The powder

obtained was passed through 2.0 mm sieve prior to analyses (Fasakin, 2004) and kept in

airtight pre-washed sterilized glass bottles in dry and cool place until nutritional analyses.

Treatment for vegetable cooking

The equal half of boiled vegetable sample was subjected to cooking with

standard ingredients, allowed to cool at room temperature and displayed for sensory

evaluation.

Development of different cooking methods for selected vegetables and their

organoleptic evaluation

Cooking of food is the use of heat to bring about desirable changes in

foods since it improves the flavor of the cooked food to enhance the human palate

(Mudambi and Rajagopal, 1981). The standard cooking methodology used for each

vegetable is given in the Table 3. The saucepan was placed on medium flame with canola

oil. The sliced onions were added and stirred till golden brown color appeared. Next the

chopped garlic, tomatoes with all other ingredients were added and stirred for 30 seconds.

The edible portion of vegetable samples (leaves cut into chunks and flowers) were then

added to the saucepan and stirred for 5 minutes. The vegetable samples were left till

water evaporated at low flame. The cooked vegetable was stirred and taken out into

prewashed bowl.

54

Table 3. Cooking methodology of amaranthus, lambs quarter, gram leaves, horse

radish tree flowers and spinach

Ingredients

Amaranthus Lambs

quarter

Gram

leaves Spinach

Horse radish

tree flowers

Weight (g)

Total vegetable 500 500 500 500 500

Salt 2 2 2 2 3

Red chili powder 2 2 2 2 3

Turmeric powder 0.5 0.5 0.5 0.5 0.5

Onion (chopped) 10 10 10 10 10

Tomato 20 20 20 20 20

Garlic 5 5 5 5 5

Chilli green 10 10 10 10 10

Oil 30 ml 30 ml 30 ml 30 ml 30 ml

Final product 511 519 513 508 570

No of servings 4 persons 4 persons 4 persons 4 persons 5 persons

Sensory evaluation of cooked and uncooked vegetables

Coding of vegetable samples

All the dishes filled with prepared vegetables were coded at first in order

to know the liking of experts. It would also help to know that the prepared nontraditonal

vegetables are acceptable as a food or not at all. Therefore, all the cooked and uncooked

nontraditional and local vegetables were served with the coded form as shown in Table 4.

55

Table 4. Coding of nontraditional and commercial vegetables

Coding pattern Cooked vegetables (Common names)

A Amaranthus

B Horse radish tree flowers

C Lambs quarter

D Gram leaves

E Spinach

Coding pattern Uncooked vegetables (Common names)

F Amaranthus

G Horse radish tree flowers

H Lambs quarter

I Gram leaves

J Spinach

Selection of trained panel of judges for sensory evaluation

The uncooked and prepared recipes of all nontraditional and local

vegetables were subjected to sensory evaluation. The evaluation was done by a trained

panel consisting of ten members using five point hedonic scales. The panel was given a

sufficient amount of coded samples at room temperature in a white glass bowl of the

same size and shape. The evaluation was carried out in a quiet, odor-free room

maintaining ideal conditions for testing. Each panelist was given a proforma of cooked

and uncooked vegetables (Appendix XLV and XLVI) and asked to evaluate the samples

for different attributes viz. color, odor, texture, taste and overall acceptability. Following

measures were taken to reduce the potential bias:

The dishes were presented on separate tables to look attractive.

56

Panels of judges were requested not to communicate during assessment and were

positioned so that they could not see reactions of each other.

All the judges were asked to drink a sip of water after tasting each prepared dish

to minimize the influence of previously tasted dish on another dish.

All the dishes were coded and kept confidential.

Determination of nutritional characteristics of uncooked and cooked vegetables

Nutrients are needed for body building, energy, maintenance and/or

regulation of body processes therefore, it is necessary to determine the nutritional

characteristics of food which will be consumed as a part of the meal. The food is then

sealed hermetically in an oxygen and moisture proof, easy close bags and stored at -20 °C

until nutritional analyses.

The fresh cut (control), powdered (thermally dehydrated and shade dried),

boiled and curry samples were subjected for the nutrient analyses as follows:

Proximate analysis

The fresh, boiled, curry, thermally dehydrated (powdered) and shade dried

(powdered) samples were extracted and processed for proximate analyses (Proteins,

crude fibers, fats, carbohydrates, ash and moisture) according to the standard methods.

57

Percentage moisture content (%)

The AOAC (2000) method was used to determine moisture content of the

samples. The 5g sample was taken in a pre-weighed, flat-bottom dish and placed in an oven

at 60± 2°C for 24 hours. The sample was then on the next day placed in a desiccator for 1

hour and then the loss in weight was recorded and results were obtained by using the

formula given below:

Percentage ash content (%)

The procedure of AOAC (2000) was followed to determine ash content (%).

The sample of 5g was taken in pre-weighed silica crucible and placed in a muffle furnace at

550 °C for 5 hours or until grayish-white ash appears. Next, the sample was cooled in a

desiccator for1 hour and weighed. To confirm the result the crucible was re-heated for 1

more hour, cooled and weighed. The procedure was repeated till a constant weight was

achieved. The ash weight was calculated with the given formula:

Pecentage fat content (%)

The weight of the extraction flask of soxhlet apparatus was noted. The

sample of 5 g was taken in a thimble with the help of a pair of tongs and closed it with fat

free cotton swab. The thimble was then placed carefully in the extraction unit. About 150

58

ml of the petroleum ether was added to the extraction flask and fitted with condenser

connected to the tap water for cooling. The soxhlation assembly was then fitted with the

stand over a hot plate and heated at 60 °C for six hours (AOAC, 2000).

Next, the flask was removed and transferred to the desiccator to cool for

30 minutes. The ether was evaporated by rotavapor and the flask containing fat was

weighed and reading was noted carefully and calculated by the given formula:

Where, W1 = empty flask weight

W2 = weight of the flask containing fat

W3 = sample weight

Percentage crude fiber (%)

The sample for crude fiber anysis was taken after removal of fat in

soxhlation and was estimated by acid and alkali method (Khalil and Durrani, 1990). 2 g

of the sample was placed in a beaker and 100 ml of HCl (2.5%) was added. The mixture

was boiled with stirring for about half an hour. The sample was then allowed to cool and

filtered with a linen cloth into a conical flask. The filtrate was rinsed with the warm

distilled water. The residue left was then added to another beaker for alkali digestion. The

fiber residues were again digested with 100 ml of 2.5% of caustic soda in a similar way

as it was done in acid digestion. The sample was dried overnight. The fiber residues were

then carefully transferred to the pre-weighed dry crucible. The crucible was then placed

in a muffle furnace at 550 °C for 5 hours till a grayish-white ash formed. Next, the

59

crucible was transferred to the desiccator, allowed to cool and weighed again. The loss in

weight of the dried residues upon ignition was noted as amount of crude fiber. Percentage

of crude fiber was calculated as follows:

Where, W2 = weight of the ash

W1 = weight of the sample

Percentage protein content (%)

Micro-Kjeldhl method of AOAC (1990) was used to determine the nitrogen

content. For this, 2g of sample was placed in a micro Kjeldahl flask and added 20ml of

concentrated H2SO4 (sulfuric acid), 10 g of NaSo4 (sodium sulfate) and 1 g of CuSo4

(copper sulfate). The mixture was warmed slightly at first and then increased when frothing

reduced from 8 hours till a bluish green translucent solution appeared and organic matter

was oxidized to inorganic form. The hot plate turned off when the required digestion of the

material was obtained. The digested material was allowed to cool and filtered with

whatman filter No. 42 paper and taken into a volumetric flask and made the final volume

up to 250 ml.

The distillation of the digest sample was performed by Markam still distilled

apparatus (Khalil and Durrani, 1990). About 5 ml of the digest samples along with 5 ml of

40% caustic soda (NaOH) solution and a few drops of distilled water was added through

the distillation tube into the flask. The distillation continued for 15-20 minutes and the

ammonia gas (NH3) produce was kept in a flask along with 20 ml boric acid (4%) and 3-5

60

drops of methyl red indicator. The distillation was stopped when the pink color in the flask

converted into yellow. The flask was removed and titrated against the 0.1M H2SO4 till pink

color appeared. The titrated value at which pink color appeared was recorded and nitrogen

content was calculated by the following formula:

Where, 100 = Conversion to percent

0.0014 = Constant which means that 0.0014 is liberated by 1ml of 0.100 H2SO4

6.25 = Factor for vegetables

Percentage carbohydrate content (%)

The difference method was applied to calculate the carbohydrate (%)

(AOAC, 1990).

Organic acids (%)

Organic acids were determined by calculating titratable acidity of the

sample. The titratable acidity was evaluated due to the method of AOAC (2000). 10 gram

sample was mashed into pestle and mortar with 30 ml distilled water. The sample was

stirred and filtered through whatman filter paper No.4. The 10 ml of filtred sample were

61

taken into a prewashed conical flask and added 3-5 drops of phenolphthalein. Next the

sample was titrated against 0.1 N NaOH (sodium hydroxide).

Equivalent weight of citric acid = 70 g

Equivalent weight of tartaric acid = 75 g

Equivalent weight of oxalic acid = 45 g

Equivalent weight of acetic acid = 60 g

Mineral analysis (mg 100g-1

)

Sample preparation/digestion and analyses of mineral elements

100 ppm stock solution of the micro minerals such as copper (cu),

iron (Fe), zinc (Zn), magnese (Mn) and macro minerals, including magnesium

(Mg), calcium (Ca), potassium (K) and sodium (Na) were prepared. Perchloric-acid

digestion method with a slight modification was used for elemental analyses (Allen,

1974). 0.25 g sample was added to 6.5 ml of mixed acid solution, i.e. nitric acid,

sulfuric acid and perchloric acid (5:1:0.1) and digested in a flask (50 ml) on a

hot plate in a fume hood till the digestion was completed. Digested samples were

allowed to cool, fil t ered (Whatmann No. 42) and transferred in a 20 ml volumetric

flask, by rising volume with 0.2N HNO3. The sample was then collected into

prewashed, sterile, acid friendly plastic bottle and the concentration of each element

was determined on Shimadzu AA-670 atomic absorption spectrophotometer. The

atomic absorption instrument was calibrated intermittently during analyses and the

62

minerals of the given sample were estimated. The blank solutions were used in between

each run in order to minimize the interferences. Concentration of each element was

calculated by using a formula:

Where;

A=Total volume of extract (ml)

W=Weight of dry plant

Vitamin assay

Chemicals and Reagents

HPLC-grade solvents were used for analyses. Acetonitrile and methanol

were procured from Lab-Scan, USA. The water used for HPLC and sampling was

prepared with Millipore, Molsheim (France). All vitamin standards were of HPLC grade

and were obtained from Sigma Chemical Company.

Standard preparation

The stock solution of vitamins was prepared before vitamin analyses in

order to achieve accuracy of the sample results. The stock solutions of respective

standards of water soluble vitamins were prepared as follows:

Vitamin B1 (Thiamine): Dissolve 25 ml of distilled water with 26.7 mg of thiamine

hydrochloride.

Vitamin B2 (riboflavin): Dissolve 100 ml of extraction solution with 6.9 mg of

riboflavin (extraction solution has limit to dissolve 7 mg of riboflavin).

63

Vitamin B3 (Nicotinamide): Dissolve 25 ml of double distilled water with 41.5 mg of

nicotinamide.

Vitamin β-carotene: weigh 1.0 mg of β-carotene into a 25 ml volumetric flask,

dissolve with hexane until all β-carotene is dissolve, and then dilutes to mark with

hexane.

Vitamin C: add 100 mg of ascorbic acid in 100 ml volumetric flask and make the

final volume with 3% (50:50) solution of metaphosphoric acid (0.3 M) and acetic acid

(1.4 M).

All the stock solutions prepared were stored in dark at -20 ∘C. The

standard curves from the peak areas were prepared by injecting the 20 µl of standard

solution (Aslam et al., 2008).

Determination of vitamin B1 and B2 (mg 100g-1

)

Five gram sample was taken into a conical flask with 0.1N HCl, covered

with aluminum foil, mixed and placed in autoclave (121°C) for 30min. Sample was taken

out from autoclave and then cooled to below room temperature. The solution was

adjusted to pH 4.0 with 4.0 M sodium acetate buffer (pH 6.1) and then added 5 ml of

10% takadiastase solution, flask caped, mixed and placed in a water bath (45-50 °C) for 4

hours with time to time mixing. Flasks were allowed to cool and the solution was

transferred to the volumetric flask (100 ml) making the final volume with deionized

water. The solution was filtered through filtration assembly (0.45μm sized pores) into

amber glass bottle for HPLC analysis (Fernando and Murphy, 1990).

64

Determination of vitamin B3 (mg 100g-1

)

One gram of sample was taken into a centrifuge tube with 0.75g Ca (OH)2

and 20 ml of de-ionized water, mixed well and placed into preheated autoclave (121 °C)

for 2 hours. The sample was taken out, allowed to cool at room temperature, transferred

to the volumetric flask (50 ml) and made the final volume with deionized water. The

digested sample was then centrifuged (2500 rpm) at 5 °C for 15 mins. The tube was

taken out, allowed to cool and pipetted 15 ml of supernatant into another centrifuge tube.

The pH was adjusted up to 7 with 10 % oxalic acid (care and patience is required if pH

drops to less than pH 7, slowly add a drop of saturated Ca (OH)2 solution until pH 7 is

reached). The final volume was made with de-ionized water up to 25 ml, capped, mixed

well and again centrifuged (2500 rpm) at 5 ᵒC for 15 min.

The C18 Sep-Pak cartridge (500 mg) was connected with 500 mg SCX

cartridge in series (C18 cartridge on top) using a column adaptor. The conditioning of the

cartridges was done by passing the methanol (10 ml) followed by deionized water

(10 ml). The 10 ml supernatant of the digested sample was loaded onto the column and

the eluent was collected into test tube. The eluent was evaporated with a stream of

nitrogen and re-dissolved the residue with 2 ml of de-ionized water (Ward and Trenerry,

1997).

Determination of vitamin C (mg 100g-1

)

The 2.5 g sample was homogenized with 3% metaphosphoric acid,

transferred to the 100 ml volumetric flask and made the final volume with 3%

metaphosphoric acid. The sample was shacked vigorously for 5 minutes and placed into

65

ultrasonic bath for 10 minutes. The solution was passed through membrane filter

0.45 μm by using filtration assembly (Lakshanasomya, 1998).

Determination of β- Carotene (mg 100g-1

)

One gram of sample was taken into round bottom brown flask (250ml) and

added with 10 ml of the ascorbic acid, 40 ml ethanol and 10 ml of KOH. The sample was

mixed thoroughly after adding each reagent. Three glass beads were added into the flask,

placed in water bath (80 °C) for 30 minutes and stir continuously (using magnetic stirrer).

The flasks were cooled at room temperature, added 50 ml of the hexane and shake

vigorously. Place the flasks untouched until two layers appeared, and then transferred the

upper layer into 250 ml brown separating funnel.

The sample was extracted again in saponification flask 2 times with 40 ml

each of extraction solvent and combined the upper layers into the separating funnel.

Shake the separating funnel and allowed the layers to be separated and discarded the

lower layer. The sample was dried by means of a rotary vacuum evaporator (<30 °C) and

flushed with nitrogen gas. The dried sample was dissolved immediately with 10 ml

methanol, filtered through a 0.45 μm membrane using solvent filtration apparatus and

collected into brown vials for HPLC analysis (Horwitz, 2000 and Thaifoods, 2002).

66

Table 5. HPLC conditions for quantification of vitamins

Thiamine Riboflavin Niacin β- Carotene Ascorbic

Acid

Column

Supelco LC-18

column

(250mm×

4.6mm ID,

5μm) (Supelco

Park,

Bellefonte,

USA)

Supelco LC-

18 column

(250mm×

4.6mm ID,

5μm)

(Supelco

Park,

Bellefonte,

USA)

Supelco

LC-18

column

(250mm×

4.6mm ID,

5μm)

(Supelco

Park,

Bellefonte,

USA)

Supelco LC-

18 column

(250mm×

4.6mm ID,

5μm)

(Supelco

Park,

Bellefonte,

USA)

Supelco

LC-18

column

(250mm×

4.6mm ID,

5μm)

(Supelco

Park,

Bellefonte,

USA)

Mobile

Phase

Ratio: Methanol

and de-ionized

water

50:50

Ratio:

Methanol

and de-

ionized water

85:15

Ratio:

Methanol

and de-

ionized

water

50:50

Ratio:

Acetonitrile:

Methanol:

Chloroform

89:9:2

Ratio: 0.3

M

potassium

dihydrogen

phosphate

in

0.35% (v/v)

ortho-

phosphoric

acid

Detector Fluorescencedet

ector

Fluorescence

detector

Ultraviolet

detector

Ultraviolet

detector

Ultraviolet

detector

Wavelengt

h 440nm 360 nm 254 nm 450 nm 248 nm

Injection

Volume

10 μl

10 μl

10 μl

20 μl

20 μl

Flow Rate 1.3 ml/min 1.3 ml/min 0.5 ml/min 1.5 ml/min 3.11

ml/min

Phytochemical analysis

The phytochemical samples were estimated by using the standard methods

of composition.

67

Alkaloids Determination (mg g-1

)

The 5 g sample was taken into a beaker (250 ml) with acetic acid (10% in

200 ml ethanol), covered and left for four hours. The sample was filtered and the filtrate

was concentrated by placing the sample in a water bath at 60 °C until it remained ¼ of its

previously taken volume. The ammonium hydroxide (conc.) was drop wise included to

the extracted material till precipitates appeared. The precipitated sample was rinsed with

a diluted ammonium hydroxide solution and passed through Whatman No. 42 (Harborne,

1993). The residue of filtrate was the alkaloids were calculated as percentage of the

dried fraction by using the formula;

Where;

W1= weight of the sample

W2= Weight of the filter paper

W3= Weight of the filter paper with precipitate

Flavonoid determination (mg g-1

)

The 10 g sample was placed in a mixture of ethanol (95%, 3 ml),

aluminium chloride (10%, 0.2 ml), potassium acetate (1 M, 0.2 ml) and distilled water

(5.6 ml) for 30 minutes at ambient temperature till the color development. The

absorbance of the sample solutions was determined at 415 nm on a UV–Vis

spectrophotometer and the concentration of flavonoids determined using a standard

curve of quercetin. The quercetin working standard solutions (1, 5, 10, 25, 50, 75 and

68

100 ppm in 80% ethanol) were prepared from the quercetin stock standard solution. A

1mL of each of the working standard solutions was mixed with ethanol (95%, 3 ml),

aluminium chloride (10%, 0.2 ml), potassium acetate (5%, 0.2 ml) and distilled water

(5.6 ml), left for 30 minutes at room temperature for full colour development and

absorbance read on a UV–Vis spectrophotometer at 415 nm. A blank was run

together with the working standard solutions with distilled water replacing the extracts

or the wine as per method reported by Humadi and Istudor (2008). The final

concentration of the sample was determined using the equation

Saponin determination (mg g-1

)

The sample of 5 g was placed in a beaker and added 200 ml of the ethanol

(20%). The sample was transferred to the water bath with the continuous magnetic stirrer

for four hours at 55 °C. The sample was passed by whatman 42 number paper and

residues were extracted again with ethanol if about 200 ml (20%). The solution was then

again placed over a water bath at 90 °C making the final volume of about 40 ml. The

solution was put into the separating funnel of 250 ml capacity and added 20 ml of diethyl

ether to it. The separating funnel was then covered and shacked vigorously for 2 minutes.

The layer of ether was discarded, whereas the aqueous layer was collected into a conical

flask. The process repeated again and the purification process was repeated and then

added with n-butanol (60 ml). The extracts of n-butanol were rinsed twice with NaCl

(5%) solution for twice. The sample remained was warmed to evaporate the solution to a

69

persistent weight and calculated for the saponin (Obadoni and Ochuko, 2001) by the

given formula;

Where;

W1= weight of the sample

W2= Weight of the empty flask

W3= Weight of the flask with evaporated sample

Determination of total phenols (mg g-1

GAE)

The sample of 10 g was taken into a beaker, included ether (50 ml) and

boiled for 5 minutes. 5 ml of the solution was then taken into a volumetric flask (50 ml)

and added 10 ml of de-ionized water, amyl alcohol (5 ml) and 2 ml ammonium

hydroxide. The solution was made up to the mark with the help of deionized water and

allowed to stand untouched for 30 minutes for the development of colored solution. The

sample was then read at wavelength of 765 nm on UV-spectrophotometer (Ebrahimzadeh

et al., 2008).

Simultaneously 1, 5, 10, 25, 50, 75 and 100 ppm gallic acid working

standards were prepared from the gallic acid standard stock solution in separate 100

mL volumetric flasks. A 1 mL aliquot of each of the working standard solutions was

treated in the same way as the sample. A calibration curve was plotted from the

absorbance of the working standards and their concentrations. The concentrations of the

sample reported as gallic acid equivalent (GAE) was calculated from the equation

(Lee, 2004).

70

Tannin determination (mg g-1

)

The sample of 10 g was taken into plastic bottle of 100 ml, then de-

ionized water (50 ml) was added and subjected to shaking for an hour on a power-driven

shaker. The sample was passed by filtration into a volumetric flask of 50 ml and

prepared the volume de-ionized water. About 5 ml of the filtrate was pipetted into a 25

ml test tube and added 3 ml of each Fe Cl3 (0.1 M), HCl (0.1 N) and potassium

ferrocyanide (0.008 M), 30 minutes was allowed for full color development. The

spectrophotometer equipped with UV spectra was used to measure the absorbance of the

sample at 760 nm within 10 minutes against a blank sample (Boham and Kocipai,

1994). The standard tannic acid solutions (1, 5, 10, 25, 50, 75 and 100 ppm) were

prepared. Concentrations of the samples were calculated from standard curve using

an equation:

Where;

A1= Absorbance of the std.

A2= Sample absorbance

C= Standard concentration

M= Mass of the sample

71

Total solids, total soluble solids, energy value, pH, nitrogen free extract and fatty

acid analyses

Total solids determination (%)

The total solids of given sample were calculated by subtracting its

moisture percentage from hundred (James, 1995).

Total soluble solids determination (ᵒBrix)

Total soluble solid (TSS) was determined according to the method of

Mazumdar and Majumder (2003). First of all machine was cleaned and calibrated to zero

with the help of distilled water. Vegetable samples were mashed into pestle and mortar

and the sample was placed on the prism of the refractometer with the help of spatula.

Next the lid of refractometer was closed and results were noted in terms of ᵒBrix. For

each sample of vegetable same technique was applied. The results were obtained in

triplicate to reduce the error.

Energy value determination (Kcal 100g-1

)

The calorific value in the form of Kcal 100g-1

of a given sample was

obtained by the formula of Asibey-Berko and Taiye (1999).

72

Determination of pH

The pH is the hydrogen ion concentration of any given sample, determined

by using a digital pH meter (AOAC, 2000). Solutions with buffer tablets of pH 4 and 10

were prepared in order to ensure accuracy of digital pH apparatus. The probe of the

apparatus was rinsed with de-ionized water, dried with tissue paper and then inserted into

the buffer solution when accurate results obtained the electrode was rinsed again with

distilled water, dried and inserted into the sample and recorded its pH concentration.

Percentage nitrogen free extracts (%)

The percentage Nitrogen free extract (NFE) was obtained by the procedure

of Owolabi et al. (2012).

Percentage total fatty acid content (%)

Total fatty acids were determined by multiplying conversion factor of 0.80

with the crude fat (%) of a given sample (Greenfield and Southgate, 2003; Akinyeye et

al., 2010, 2011).

Extraction and estimation of chlorophyll pigments (mg g-1

)

Chlorophyll estimation was carried out according to Arnon (1949). This

procedure was carried out in dim light in order to reduce photo-destruction of the

pigments. Healthy, fresh samples of the above mentioned species were collected and 1

73

gram of each was weighed and crushed to make its pulp with 20 ml acetone (80 %) in the

lab scale grinder.

The paste was transferred to the centrifuge tube and the pestle and mortar

were rinsed with acetone and added to the tube. The sample was then centrifuged with 10

ml of acetone (80% freshly prepared) at 5000 rpm for 5 minutes and the supernatant was

collected in a beaker of 50 ml. The solution was transferred to the 100 ml volumetric

flask and made the final volume with de-ionized water. The sample was then recorded at

the wavelengths of 645 and 663 nm against the acetone (80%) as a blank solution through

a spectrophotometer of UV spectra. The quantification of factor in order to get

chlorophyll content in mg/g was obtained as follows:

Where, V= final volume made = 100 ml

W= fresh weight of sample = 1 g.

The equations for the calculation of the total chlorophyll, chlorophyll a and chlorophyll b

were obtained by following the formulas given below:

Where, A663 = absorbance at 663 nm

A645 = absorbance at 645 nm

74

Statistical analyses

Data was analyzed from analysis of variance (ANOVA) using two factor

factorial along with Complete Randomised Design (CRD) to find out levels of

significance among various treatments and their interactions. The levels of significance

between means were estimated by the least significant difference (LSD) method at <

0.05 was considered statistically significant following the procedures of Steel and Torrie

(1980). Correlation analysis was performed to determine the relationship between each

quality parameter of vegetables. Principal component analysis was performed to study the

relationships between nutritional content of selected vegetables using SPSS 16.

75

CHAPTER-IV

RESULTS

The main purpose of current research work was to assess the nutritional

quality of nontraditional vegetables wildly grown in Sindh. The content of the present

study includes field survey in Mirpurkhas district of Sindh and laboratory tests for quality

characteristics of vegetables. The data generated from the present study was statistically

analyzed and the results are interpreted in the following sections.

Perception of non-traditional vegetable use by selected of respondents

Percent frequency data in Table 6 (Figure 4) shows respondents perception

about utilization of non-traditional vegetables. It has been observed from the survey that

gram leaves vegetable was the most popular non-traditional vegetable eaten frequently or

occasionally by 82% respondents only 18% respondents never tasted or do not know this

vegetable. Next popular vegetables which majority of respondent never tasted or did not

know included amaranthus and lamb's quarter. About 62% respondents never tasted or do

not know horse radish tree flowers as vegetable while 38% respondents answered they

eat frequent or occasionally.

76

Table 6. Perception of non-traditional leafy vegetable use by selected respondents

(% frequency)

Vegetable Name

Do not

know

Never

tasted

Eat

occasionally

Eat

frequently Total

1 2 3 4

Lamb's quarter 38 21 16 25 100

Amaranthus 34 19 29 18 100

Gram leaves 10 08 34 48 100

Horse radish tree

flowers 27 35 30 08 100

Figure 4. Perception of nontraditional vegetable use

Proximate composition of vegetables

Determination of percent moisture in selected vegetables

Statistical ANOVA for processing methods, type of vegetables and their

interaction showed significant differences for moisture content (Appendix V). Spinach

had higher moisture content (54.46%), which was followed by 51.29% moisture content

in horse radish tree flowers. The least moisture content (48.36%) was detected in samples

77

of amaranthus (Table 7). Moisture content as influenced by processing methods revealed

significant differences. The maximum (86.51%) moisture content was observed in boiled

vegetables, followed by 83.61% moisture content in fresh vegetables (control). Whereas,

minimum moisture content (6.277%) was noted in thermally dehydrated vegetables

(Table 7). Interactive effect of processing methods and vegetable types showed

significant effect on moisture content. The highest moisture content (92.66%) was found

in spinach under boiled method followed by 88.76% moisture content in the same

vegetable at fresh (control), whereas least i.e. 4.93% was observed in horse radish tree

flowers at thermal dehydration method (Table 7, Figure 5).

Table 7. Moisture content (%) of different types of vegetables under the effect of

postharvest processing methods

Vegetables

Processing methods

Mean Fresh

(control) Boiled Curry

Thermally

dehydrated

Shade

dried

Amaranthus 81.96

ef

±0.33

83.05ef

±0.31

65.50j

±3.3

5.407m

±1.13

5.883m

±0.11 48.36

D

Lambs quarter 84.08

de

±0.72

85.46cd

±0.64

71.42h

±0.25

6.417lm

±0.31

7.180lm

±0.45 50.91

B

Gram leaves 82.28

ef

±0.10

84.13de

±0.89

68.76i

±0.91

6.00m

±0.36

6.22m

±0.63 49.47

C

Horse radish tree

flowers

80.98f

±0.24

87.26bc

±0.34

77.46g

±0.42

4.933m

±0.79

5.840m

±0.22 51.29

B

Spinach 88.76

b

±0.41

92.66a

±0.08

72.46h

±1.13

8.627kl

±0.18

9.833k

±0.12 54.46

A

Mean 83.61B 86.51

A 71.12

C 6.277

D 6.991

D

`Means within columns and rows followed by same letters are not significantly different

at 5% probability level

78

Figure 5. Graphical representation of the moisture content (%) of selected

vegetables

Determination of percent ash in selected vegetables

ANOVA for ash content is shown in Appendix VI. Analysis indicated

significant differences for processing methods, vegetables and interaction of processing ×

vegetables. Among the vegetables, horse radish tree flowers had maximum (7.23%) ash

content followed by amaranthus (5.489%). The minimum (3.965%) ash content was

noted in spinach (Table 8). Processing methods had significant effect on ash content and

the highest value of ash content (11.06%) was recorded under thermall dehydration

method followed by 9.915% ash content in shade dried vegetables. While, lowest value

(0.996%) of ash content was observed in boiled samples of vegetables (Table 8). Ash

content under the interactive effect of vegetable type x processing method showed

maximum ash content (16.15%) in horse radish tree flowers under thermall dehydration

followed by 14.82% ash content in the same vegetable under shade dry method.

However, lower (0.507%) ash content was noted in spinach at boiling (Table 8, Figure 6).

79

Table 8. Ash content (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 2.353

j

±0.19

1.227l

±0.05

3.813h

±0.18

10.56c

±0.25

9.493d

±0.94 5.489

B

Lambs quarter 2.013

jk

±0.06

1.187l

±0.03

2.127jk

±0.06

9.507d

±0.05

8.287e

±0.07 4.624

D

Gram leaves 2.233

jk

±0.12

1.213l

±0.06

3.227i

±0.07

10.43c

±0.27

9.220d

±0.06 5.264

C

Horse radish tree

flowers

4.873g

±0.11

0.847lm

±0.08

1.927k

±0.07

16.15a

±0.07

14.82b

±0.08 7.23

A

Spinach 0.887

lm

±0.05

0.507m

±0.09

2.00jk

±0.09

8.680e

±0.08

7.753f

±0.06 3.965

E

Mean 2.472C 0.996

D 2.619

C 11.06

A 9.915

B

Means within columns and rows followed by same letters are not significantly different at

5% probability level

Figure 6. Graphical representation of the ash content (%) of selected vegetables

80

Determination of percent protein in selected vegetables

ANOVA for protein content is revealed in Appendix VII. The results for

protein content represented significant differences (P≤0.01) among types of vegetable,

types of processing and their interaction. Protein content was highest (5.90%) in gram

leaves, while the horse radish tree flowers ranked second with 4.62%. Whereas, the

minimum protein content 2.37% was recorded from samples of spinach (Table 9).

Processing methods displayed significant differences for protein content. The maximum

protein content (5.412%) was noted in thermally dehydrated vegetables followed by

4.890% in shade dried. Whereas, the lowest protein content (2.883%) was detected from

boiled vegetable samples (Table 9). Interactive effect of vegetable type and processing

type showed significantly greater protein content (7.56%) in gram leaves under thermal

dehydration method. However, minimum protein of 1.04% was found in spinach under

boiling method (Table 9, Figure 7).

81

Table 9. Protein content (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 3.273

j

±0.06

2.293k

±0.05

3.073j

±0.70

5.183def

±0.06

4.833efg

±0.03 3.73

D

Lambs quarter 4.306

hi

±0.86

3.170j

±0.05

4.043i

±0.03

4.303de

±0.03

4.76fgh

±0.03 4.13

C

Gram leaves 5.916

c

±0.05

4.570gh

±0.08

4.916efg

±0.03

7.560a

±0.07

6.55b

±0.03 5.90

A

Horse radish tree

flowers

4.746fgh

±0.005

3.342j

±0.105

4.250hi

±0.008

5.530cd

±0.05

5.226def

±0.005 4.62

B

Spinach 2.170

k

±0.51

1.040l

±0.019

2.086k

±0.42

3.483j

±0.31

3.08j

±0.37 2.37

E

Mean 4.082C 2.883

E 3.674

D 5.412

A 4.890

B



Figure 7. Graphical representation of the protein content (%) of selected vegetables

82

Determination of percent fat in selected vegetables

Statistical ANOVA for vegetables, processing methods and interaction of

vegetables and processing methods revealed significant differences (P≤0.01) for fat

content (Appendix VIII). Fat content in various types of vegetables revealed significant

differences. The higher fat content of 2.73 and 2.62% was observed in horse radish tree

flowers and spinach, respectively. Whereas, the lowest fat content (1.62%) was found in

lambs quarter (Table 10). Fat content under the effect of processing methods represented

significant differences. Fat content had higher value of 3.30% in curry or cooked

vegetables which was followed by 2.37% detected in thermally dehydrated vegetables.

However, minimum fat content (1.29%) was found in boiled vegetables (Table 10). The

results for fat content under the interactive effect of vegetables and processing methods

indicated maximum value of 3.85% in horse radish tree flowers under cooking method

while minimum fat content i.e. 0.85% and 0.75% was found in gram leaves and lambs

quarter, respectively at boiling method (Table 10, Figure 8).

Table 10. Fat (%) of different types of vegetables under the effect of postharvest

processing methods

83

Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 2.15

defghi

±0.18

1.10kl

±0.22

3.40ab

±0.26

2.55cde

±0.42

2.31cdefgh

±0.39 2.30

B

Lambs quarter 1.25

jkl

±0.27

0.75l

±0.18

2.85bc

±0.27

1.70hijk

±0.21

1.57ijk

±0.45 1.62

C

Gram leaves 1.60

ijk

±0.31

0.85l

±0.25

2.75cd

±0.82

2.01efghi

±0.21

1.99efghi

±0.47 1.84

C

Horse radish tree

flowers

2.40cdefg

±0.13

1.90fghi

±0.26

3.85a

±0.27

2.85bc

±0.45

2.65cd

±0.68 2.73

A

Spinach 2.35

cdefg

±0.35

1.850ghij

±0.42

3.65a

±0.52

2.75cd

±0.21

2.50cdef

±0.25 2.62

A

Mean 1.95C 1.29

D 3.30

A 2.37

B 2.203

BC



Figure 8. Graphical representation of the fat content (%) of selected vegetables

84

Determination of percent fiber in selected vegetables

Fiber content was significantly (P≤0.01) affected by processing methods.

However, type of vegetables and interaction of vegetables × processing methods showed

non-significant effect on fiber content (Appendix IX). The results for fiber content in

different vegetables revealed significant differences and ranged from 5.163% to 6.67%

(Table 11). Processing methods had significant effect on fiber content. The thermally

dried vegetables had higher fiber content i.e. 10.83%, while the lowest (1.817%) fiber

content was noted in boiled vegetables (Table 11). The results for fiber content under the

interactive effect of vegetables and processing methods showed the highest value

(13.35%) in thermally dried sample of horse radish tree flowers whereas the lowest value

was recorded in boiled sample of spinach (Table 11, Figure 9).

85

Table 11. Fiber content (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 2.60

efgh

±0.45

2.350ghi

±1.34

4.250d

±0.15

10.383bc

±0.37

10.10c

±2.52 5.936

B

Lambs quarter 2.167

ghi

±0.10

1.550hi

±0.49

3.950de

±0.10

10.15bc

±0.44

9.583c

±0.37 5.48

BC

Gram leaves 2.550

fgh

±0.18

1.700hi

±0.104

3.13d

±0.18

10.50bc

±0.18

9.80c

±0.57 5.736

BC

Horse radish tree

flowers

2.70efgh

±0.21

2.450fgh

±0.95

3.367defg

±0.15

13.35a

±0.32

11.48b

±0.60 6.67

A

Spinach 2.083

ghi

±0.27

1.033i

±0.13

3.750def

±0.02

9.750c

±0.22

9.200c

±0.25 5.163

C

Mean 2.420D 1.817

D 3.890

C 10.83

A 10.03

B



Figure 9. Graphical representation of the fiber content (%) of selected vegetables

86

Determination of percent carbohydrate in selected vegetables

Statistical analysis showed a significant effect of type of vegetables, processing

methods and their interaction on carbohydrate content as shown in Appendix X. The

higher (34.18%) carbohydrate content was noted in amaranthus whereas the minimum

carbohydrate of 26.96% was recorded in horse radish tree flowers (Table 12).

Carbohydrate content was influenced by processing methods and displayed significantly

highest carbohydrate content of 65.96 and 64.02% in shade dried and thermally

dehydrated vegetables, respectively followed by 15.42% carbohydrate content in curry.

However, least carbohydrate content was obtained in fresh (5.463%) and boiled (6.503%)

vegetables (Table 12). Interactive effect of vegetable types × processing methods

produced significantly higher carbohydrate (698.62%) in lambs quarter at shade drying.

However, lesser carbohydrate (2.91%) was noted in spinach at boiling (Table 12, Figure

10).

87

Table 12. Carbohydrate (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 7.660

efg

±0.66

9.980e

±0.74

20.08d

±0.56

65.80a

±9.62

67.38a

±2.07 34.18

A

Lambs quarter 6.183

efg

±0.61

7.887efg

±0.50

15.61d

±0.28

66.92a

±0.19

68.62a

±0.63 33.04

AB

Gram leaves 5.423

efg

±0.35

7.537efg

±0.30

16.21d

±0.78

63.50ab

±0.42

66.22a

±0.42 31.77

B

Horse radish tree

flowers

4.300fg

±0.17

4.200fg

±0.56

9.150ef

±1.02

57.19c

±0.19

59.96bc

±0.34 26.96

C

Spinach 3.747

g

±0.49

2.910g

±0.27

16.05d

±0.98

66.71a

±0.33

67.63a

±0.51 31.41

B

Mean 5.463C 6.503

C 15.42

B 64.02

A 65.96

A



Figure 10. Graphical representation of the carbohydrate content (%) of selected

vegetables

88

Correlation matrix (r) of proximate composition of different vegetables

The data on correlation study of proximate composition of different

vegetables under the influence of various processing treatments are presented in Table

13. Moisture content exhibited a significant (P≤0.01) negative association with ash (r= -

0.922), fiber (r = -0.968), carbohydrate (r = -0.990) and protein (r = -0.557) of different

vegetables whilst a non-significant negative correlation was observed with fat (r = -

0.152). Likewise, ash showed a significant positive relationship with fiber (r = 0.949),

carbohydrate (r = 0.875) and protein (r = 0.600) while a non-significant positive

correspondence was observed with fat (r = 0.185). There was observed a non-significant

positive correlation for fiber with respect to fat (r = 0.211) and significant (P≤0.01)

positive correlation was noticed with protein (r = 0.558) and carbohydrate (r = 0.939). Fat

showed non significant negative correlation with protein (r = -0.055) whereas a non-

significant positive association was found in carbohydrate (r = 0.118). Carbohydrate

showed a significant (P≤0.05) positive correlation with protein (r = 0.503).

Table 13. Correlation matrix (r) of proximate composition of different vegetables

under the influence of processing treatments

Moisture Ash Fiber Fat Carbohydrate Protein

Moisture 1

Ash -0.922** 1

Fiber -0.968** 0.949** 1

Fat -0.152 0.185 0.211 1

Carbohydrate -0.990** 0.875** 0.939** 0.118 1

Protein -0.557** 0.600** 0.558** -0.055 0.503* 1

** = P<0.01; * = P<0.05, levels of significance.

89

Organic acids of different vegetables

Determination of percent acetic acid in selected vegetables

Type of vegetables, processing methods and their interaction showed a

significant effect on acetic acid content (Appendix XI). The acetic acid content in

amaranthus, lambs quarter, gram leaves, horse radish tree flowers and spinach was in

order of 0.08, 0.048, 0.058, 0.067 and 0.054%, respectively (Table 14). Acetic acid as

influenced by processing methods revealed significant differences and showed higher

value of 0.118% in thermally dehydrated samples of vegetables whereas the lowest value

of 0.017% acetic acid was found in boiled vegetables (Table 14). Interactive effect of

processing methods × vegetables represented highest acetic acid i.e. 0.143% in

amaranthus at thermal dehydration method (Table 14, Figure 11).

Table 14. Acetic acid (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.05

f

±0.003

0.03gh

±0.003

0.04fg

±0.003

0.143a

±0.009

0.136a

±0.003 0.08

A

Lambs quarter 0.016

hij

±0.006

0.01j

±0.003

0.02hij

±0.007

0.103de

±0.006

0.09e

±0.029 0.048

D

Gram leaves 0.023

hij

±0.002

0.013ij

±0.001

0.026ghi

±0.003

0.120bc

±0.002

0.11cd

±0.001 0.058

C

Horse radish tree

flowers

0.040fg

±0.003

0.02hij

±0.006

0.030gh

±0.003

0.113cd

±0.021

0.133ab

±0.015 0.067

B

Spinach 0.020

hij

±0.003

0.013ij

±0.003

0.020hij

±0.002

0.113cd

±0.021

0.103de

±0.021 0.054

CD

Mean 0.030B 0.017

D 0.027

B 0.118

A 0.114

A



90

Figure 11. Graphical representation of the acetic acid (%) of selected vegetables

Determination of percent citric acid in selected vegetables

ANOVA results for citric acid showed significant differences (P≤0.01)

among vegetable types, processing methods and interaction of vegetables × processing

(Appendix XII). Citric acid was higher (0.117%) in gram leaves as compared to horse

radish tree flowers (0.087%), amaranthus (0.071%), lambs quarter (0.066%) and spinach

(0.056%) and as shown in Table 15. The samples from thermally dehydrated vegetables

had highest citric acid of 0.182% whereas the lowest value of 0.022% citric acid was

found from boiled vegetables (Table 15). Citric acid under the interactive effect of

processing methods and vegetables showed highest value i.e. 0.26% in gram leaves under

thermal dehydration method (Table 15, Figure 12).

91

Table 15. Citric acid (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.026

jkl

±0.003

0.016kl

±0.004

0.026jkl

±0.003

0.170cd

±0.01

0.116f

±0.003 0.071

C

Lambs quarter 0.023

jkl

±0.007

0.013l

±0.003

0.023jkl

±0.008

0.153de

±0.007

0.116f

±0.034 0.066

B

Gram leaves 0.053

h

±0.002

0.036hij

±0.002

0.040hij

±0.003

0.260a

±0.003

0.196b

±0.002 0.117

A

Horse radish tree

flowers

0.046hi

±0.003

0.030ijkl

±0.007

0.033ijk

±0.004

0.183bc

±0.024

0.143e

±0.018 0.087

B

Spinach 0.023

jkl

±0.003

0.013l

±0.003

0.023jkl

±0.002

0.146e

±0.025

0.073g

±0.025 0.056

D

Mean 0.034C 0.022

D 0.029

CD 0.182

A 0.129

B



Figure 12. Graphical representation of the citric acid (%) of selected vegetables

92

Determination of percent oxalic acid in selected vegetables

Statistical analysis of variance (ANOVA) for vegetable types, processing

types and their interaction showed significant differences for oxalic acid (Appendix XIII).

The maximum oxalic acid (0.058%) was noted in samples of spinach whereas the rest of

the vegetables had lower values of oxalic acid i.e. from 0.029 to 0.043% (Table 16).

Among the processing methods, the oxalic acid was maximum i.e. 0.076% in thermally

dehydrated vegetables while the minimum (0.014%) oxalic acid was found from samples

of boiled vegetables (Table 16). Oxalic acid under the interactive effect of processing

methods and vegetables indicated significantly highest value of 0.113% in spinach at

thermal dehydration method (Table 16, Figure 13).

Table 16. Oxalic acid (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean

Fresh (control) Boiled Curry Thermally

dehydrated

Shade

dried

Amaranthus 0.016

fghi

±0.002

0.010hi

±0.002

0.020fgh

±0.002

0.06d

±0.006

0.053d

±0.002 0.032

C

Lambs quarter 0.013

ghi

±0.004

0.006i

±0.002

0.013ghi

±0.005

0.053d

±0.004

0.050d

±0.022 0.029

D

Gram leaves 0.026

e

±0.001

0.016fghi

±0.001

0.020fgh

±0.002

0.073c

±0.002

0.056d

±0.001 0.038

B

Horse radish tree

flowers

0.033e

±0.002

0.016fghi

±0.002

0.023efg

±0.002

0.083c

±0.015

0.060d

±0.011 0.043

B

Spinach 0.034

e

±0.002

0.020fgh

±0.002

0.024efg

±0.001

0.113a

±0.016

0.100b

±0.016 0.058

A

Mean 0.024C 0.014

D 0.020

CD 0.076

A 0.064

B



93

Figure 13. Graphical representation of the oxalic acid (%) of selected vegetables

Determination of percent tartaric acid in selected vegetables

Vegetable types, processing methods and their interaction had a significant

effect (P≤0.01) on tartaric acid content (Appendix XIV). Tartaric acid in amaranthus,

lambs quarter, gram leaves, horse radish tree flowers and spinach was in order of 0.076,

0.073, 0.128, 0.049 and 0.011%, respectively (Table 17). Tartaric acid was highest

(0.206%) in thermally dehydrated vegetables. However, the lowest (0.024%) tartaric acid

was found in boiled vegetables (Table 17). Interactive effect of processing methods ×

vegetables showed significantly maximum tartaric acid of 0.273% in gram leaves at

thermal dehydration process (Table 17, Figure 14).

94

Table 17. Tartaric acid (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh (control) Boiled Curry

Thermally

dehydrated

Shade

dried

Amaranthus 0.027

ijk

±0.004

0.020jk

±0.004

0.023jk

±0.003

0.186d

±0.011

0.126ef

±0.003 0.076

C

Lambs quarter 0.026

ijk

±0.008

0.016jk

±0.003

0.023jk

±0.008

0.183d

±0.007

0.120f

±0.037 0.073

C

Gram leaves 0.060

g

±0.003

0.046ghi

±0.002

0.050gh

±0.003

0.273a

±0.003

0.240b

±0.002 0.128

A

Horse radish tree

flowers

0.016jk

±0.003

0.008k

±0.007

0.013k

±0.004

0.146e

±0.026

0.063g

±0.019 0.049

D

Spinach 0.050

gh

±0.004

0.030hijk

±0.004

0.036hij

±0.002

0.240b

±0.027

0.183d

±0.027 0.011

B

Mean 0.035C 0.024

C 0.029

C 0.206

A 0.141

B



Figure 14. Graphical representation of the tartaric acid (%) of selected vegetables

95

Correlation matrix (r) of organic acids of different vegetables

Results on correlation analysis of organic acids of selected vegetables

under the influence of processing treatments are given in Table 18. The relationship

showed a significant (P<0.01) positive correlation for acetic acid with citric acid (r =

0.865), oxalic acid (r = 0.792) and tartaric acid (r = 0.808). The citric acid was found to

be significantly (P<0.01) positively correlated with oxalic acid (r = 0.738) and tartaric

acid (r = 0.885). A significant and positive correlation was also observed between oxalic

acid and tartaric acid (r = 0.839).

Table 18. Correlation matrix (r) of organic acids of different vegetables under the


Acetic acid Citric acid Oxalic acid Tartaric acid

Acetic acid 1

Citric acid 0.865** 1

Oxalic acid 0.792** 0.738** 1

Tartaric acid 0.808** 0.885** 0.839** 1


Mineral content of different vegetables

Determination of copper content (mg 100g-1

) in selected vegetables

Copper content under the effect of vegetable types, processing methods

and their interaction showed significant differences (P≤0.01) as indicated in Appendix

XV. Copper content in different vegetables displayed significantly maximum copper

content (1.95 mg 100g-1

) in gram leaves followed by 1.89 mg 100g-1

copper in lambs

quarter. The minimum copper of 6.07 mg 100g-1

and 1.22 mg 100g-1

was noticed in

spinach and horse radish tree flowers (Table 19). Among the processing methods, highest

96

copper content (2.19 mg 100g-1

) was observed in thermally dehydrated vegetables

followed by shade dried (1.88 mg 100g-1

). However, lowest (1.01 mg 100g-1

) copper

content was found in boiled vegetables (Table 19). Interactive effect of processing

methods × vegetables indicated highest copper content of 2.99 mg 100g-1

in gram leaves

at dehydration process whereas the lowest copper content (1.01 mg 100g-1

) was detected

from spinach under boiling (Table 19, Figure 15).

Table 19. Copper (mg 100g-1

) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh (control) Boiled Curry

Thermally

dehydrated

Shade

dried

Amaranthus 1.143

ghi

±0.002

0.99ijk

±0.003

1.090hij

±0.001

3.026a

±0.03

1.940cd

±0.04 1.63

B

Lambs quarter 1.860

cd

±0.02

1.660e

±0.02

1.790de

±0.04

2.150b

±0.02

1.990bc

±0.02 1.89

A

Gram leaves 1.35

f

±0.02

1.21fgh

±0.04

1.30fg

±0.02

2.990a

±0.03

2.900a

±0.04 1.95

A

Horse radish tree

flowers

0.950jkl

±0.03

0.803l

±0.04

0.890kl

±0.002

1.820cde

±0.002

1.660e

±0.004 1.22

C

Spinach 0.560

m

±0.002

0.390m

±0.01

0.480m

±0.004

1.010ijk

±0.002

0.910jkl

±0.01 0.67

D

Mean 1.172C 1.01

D 1.11

C 2.19

A 1.88

B



97

Figure 15. Graphical representation of the copper content (mg 100g

-1) of selected

vegetables

Determination of iron content (mg 100g-1


Analysis of variance for iron content showed significant differences

(P≤0.01) under the effect of vegetable types, processing methods and their interaction

(Appendix XVI). Vegetable type displayed significantly higher iron content (4.394 mg

100g-1

) in gram leaves followed by 2.906 mg 100g-1

in amaranthus, while the lowest iron


) was noted in horse radish tree flowers (Table 20). Processing

methods showed significantly maximum iron content of 2.87 mg 100g-1

in thermally

dehydrated samples of vegetables, while shade dried method ranked second with 2.748

mg 100g-1

, whereas lowest iron content (1.932 mg 100g-1

) observed in boiled vegetables

(Table 20). Interactive effect of processing methods × vegetables showed greater iron

content i.e. 4.810 mg 100g-1

in gram leaves at thermal dehydration process. However,

98

lower iron content of 0.77 mg 100g-1

was detected in spinach after boiling process (Table

20, Figure 16).

Table 20. Iron (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 2.990

fg

±0.04

2.580h

±0.04

2.760gh

±0.004

3.190ef

±0.02

3.010fg

±0.02 2.906

B

Lambs quarter 2.120

i

±0.02

1.800j

±0.02

1.990ij

±0.002

3.460d

±0.02

3.360de

±0.04 2.546

C

Gram leaves 4.520

ab

±0.05

3.830c

±0.02

4.050c

±0.04

4.810a

±0.02

4.760ab

±0.05 4.394

A

Horse radish tree

flowers

1.040mn

±0.02

0.680p

±2.00

0.870nop

±0.02

1.390kl

±0.03

1.230lm

±0.04 1.042

E

Spinach 1.210

l,

±0.002

0.770op

±0.005

0.980mno

±0.02

1.500k

±0.04

1.380kl

±0.04 1.168

D

Mean 2.376C 1.932

E 2.130

D 2.870

A 2.748

B



Figure 16. Graphical representation of the iron content (mg 100g

-1) of selected

vegetables

99

Determination of zinc content (mg 100g-1


The zinc content indicated significant variations (P≤0.01) under the

influence of vegetable types, processing methods and their interaction (Appendix XVII).

The results for zinc content in different vegetables represented maximum value of 4.918

mg 100g-1

in amaranthus, while the lambs quarter ranked second which was observed as

4.45 mg 100g-1

. The least zinc content (2.94 mg 100g-1

) was found in horse radish tree

flowers (Table 21). Zinc content under the effect of processing methods showed

maximum value of 5.96 mg 100g-1

in thermally dehydrated vegetables followed by shade

dried method (5.48 mg 100g-1

) as compared to minimum (2.02 mg 100g-1

) zinc content in

boiled vegetables (Table 21). Interactive effect of processing methods and vegetables

exhibited significantly lowest zinc content of 1.04 mg 100g-1

in horse radish tree flowers

after boiling process whereas the highest zinc content i.e. 7.240 mg 100g-1

was noted

from amaranthus after thermal dehydration process (Table 21, Figure 17).

100

Table 21. Zinc (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 4.66

gh

±0.02

2.68lm

±0.02

3.16j

±0.01

7.240a

±0.02

6.85b

±0.02 4.918

A

Lambs quarter 3.46

i

±0.03

2.86kl

±0.02

2.96jk

±0.002

6.86b

±0.02

6.11c

±0.04 4.45

B

Gram leaves 2.86

kl

±0.04

2.15o

±0.02

2.36no

±0.04

5.58d

±0.02

5.01ef

±0.06 3.59

C

Horse radish tree

flowers

2.35no

±0.03

1.04r

±0.02

1.75p

±0.02

5.02ef

±0.02

4.56h

±0.02 2.94

E

Spinach 2.55

mn

±0.03

1.37q

±0.04

1.85p

±0.04

5.13e

±0.004

4.88fg

±0.005 3.15

D

Mean 3.17C 2.02

E 2.41

D 5.96

A 5.48

B



Figure 17. Graphical representation of the zinc content (mg 100g

-1) of selected

vegetables

101

Determination of manganese content (mg 100g-1


Analysis of variance for manganese content indicated significant

differences (P≤0.01) for vegetable types, processing methods and their interaction

(Appendix XVIII). Manganese content showed highest value of 1.608 mg 100g-1

in gram

leaves followed by 1.177 mg 100g-1

in amaranthus. The minimum manganese of 0.788

mg 100g-1

was recorded in spinach (Table 22). Among processing methods, manganese

content the maximum manganese content (1.336 mg 100g-1

) was detected in thermally

dehydrated vegetables followed by 1.187 mg 100g-1

in shade dried vegetables, whereas

the minimum manganese of 0.868 mg 100g-1

found in boiled vegetables (Table 22).

Manganese content under the effect of processing methods × vegetables exhibited

maximum value of 1.950 mg 100g-1

in gram leaves at thermal dehydration method,

whereas least manganese (0.490 mg 100g-1

) was determined in gram leaves at boiling

process (Table 22, Figure 18).

102

Table 22. Manganese (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 1.190

def

±0.02

1.036ghi

±0.04

1.073fgh

±0.02

1.310d

±0.02

1.276d

±0.02 1.177

B

Lambs quarter 0.896

jkl

±0.02

0.836klm

±0.02

0.910ijkl

±0.002

1.110efg

±0.004

1.010ghij

±0.002 0.952

C

Gram leaves 1.670

b

±0.03

1.230de

±0.02

1.510c

±0.02

1.950a

±0.04

1.680bc

±0.04 1.608

A

Horse radish tree

flowers

0.960hijk

±0.02

0.750m

±0.04

0.810lm

±0.03

1.240de

±0.04

1.080fgh

±0.04 0.968

C

Spinach 0.783

lm

±0.02

0.490n

±0.04

0.710m

±0.003

1.070fgh

±0.004

0.890jkl

±0.004 0.788

D

Mean 1.100C 0.868

E 1.002

D 1.336

A 1.187

B



Figure 18. Graphical representation of the manganese content (mg 100g-1

) of

selected vegetables

103

Determination of calcium content (mg 100g-1


Calcium content showed significant differences (P≤0.01) under the effect

of vegetable types, processing methods and their interaction (Appendix XIX). Among the

vegetables, calcium content was higher (424 mg 100g-1

) in horse radish tree flowers,

while the lambs quarter ranked second with 391.8 mg 100g-1

. Whereas, lower calcium

content of 206.3 mg 100g-1

was found in gram leaves (Table 23). Processing methods had

significant effect on calcium content and showed maximum calcium content (437.5 mg

100g-1

) in thermally dehydrated vegetables followed by shade dried (401.7 mg 100g-1

) as

compared to 215.5 mg 100g-1

calcium content from boiled vegetables (Table 23).

Interaction of processing methods and vegetables represented highest calcium content

(568.8 mg 100g-1

) in lambs quarter after dehydration process. However, the lower

calcium content (120.8 mg 100g-1

) was found in gram leaves after boiling (Table 23,

Figure 19).

104

Table 23. Calcium (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 275.8

j

±0.002

247.5m

±0.02

263.2l

±0.04

501.1c

±0.03

476.8d

±0.02 352.8

C

Lambs quarter 309.6

h

±0.43

268.7k

±0.06

288.3i

±0.04

568.8a

±0.03

523.7b

±0.05 391.8

B

Gram leaves 181.4

o

±0.26

120.8s

±0.02

156.1q

±0.04

308.4h

±0.02

265.1l

±0.02 206.3

E

Horse radish tree

flowers

448.1f

±0.03

309.4h

±0.02

412.6g

±0.26

497.6c

±0.04

453.7e

±0.02 424.2

A

Spinach 199.5

n

±0.26

131.2r

±0.26

167.4p

±0.02

311.8h

±0.04

289.3i

±0.06 219.8

D

Mean 282.8C 215.5

E 257.5

D 437.5

A 401.7

B



Figure 19. Graphical representation of the calcium content (mg 100g

-1) of selected

vegetables

105

Determination of magnesium content (mg 100g-1


Analysis of variance showed that magnesium content was significantly

affected by vegetable types, processing methods and their interaction (Appendix XX).

The maximum magnesium content (78.66 mg 100g-1

) was noted in lambs quarter

followed by amaranthus (73.46 mg 100g-1

), while the minimum value (33.42 mg 100g-1

)

of magnesium was observed in spinach (Table 24). Magnesium content as influenced by

processing methods revealed significantly highest value of 79.83 mg 100g-1

in thermally

dehydrated vegetables while the shade dried vegetables ranked second with 73.63 mg

100g-1

, whereas the minimum magnesium content (31.34 mg 100g-1

) noted in boiled

vegetables (Table 24). The greater magnesium content (108.4 mg 100g-1

) under the

interactive effect of processing methods × vegetables was observed from lambs quarter

after thermal dehydration treatment. The minimum magnesium content (11.34 mg 100g-1

)

was detected in spinach after boiling (Table 24, Figure 20).

106

Table 24. Magnesium (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 72.60

g

±0.004

41.85s

±0.02

57.12l

±0.04

101.3b

±0.02

94.43d

±0.02 73.46

B

Lambs quarter 79.03

e

±0.02

46.13q

±0.02

62.26j

±0.04

108.4a

±2.00

97.43c

±1.00 78.66

A

Gram leaves 68.23

i

±0.43

38.23t

±2.00

52.53n

±0.04

77.45f

±2.00

71.53h

±1.00 61.59

C

Horse radish tree

flowers

44.38r

±1.00

19.18x

±0.07

32.75v

±0.02

61.81k

±0.36

56.50m

±1.00 42.92

D

Spinach 35.95

u

±0.06

11.34y

±0.04

21.17w

±0.06

50.16o

±1.00

48.50p

±0.28 33.42

E

Mean 60.04C 31.34

E 45.16

D 79.83

A 73.67

B



Figure 20. Graphical representation of the magnesium content (mg 100g

-1) of

selected vegetables

107

Determination of sodium content (mg 100g-1


Analysis of variance indicated that vegetable types, processing methods

and their interaction had a significant effect on sodium content (Appendix XXI). The

results for sodium content revealed maximum (806.1 mg 100g-1

) value in lambs quarter

followed by 771.5 mg 100g-1

sodium content in spinach, whereas the lowest (650.2 mg

100g-1

) sodium content was noted in horse radish tree flowers (Table 25). Thermally

dehydrated vegetables had higher sodium content i.e. 1137.1 mg 100g-1

followed by

1067.9 mg 100g-1

sodium content in shade dried vegetables. The minimum sodium


) was found in boiled vegetables (Table 25). Interaction of

processing methods × vegetables resulted highest sodium content i.e. 1211.5 mg 100g-1

from lambs quarter at thermal dehydration treatment, while minimum sodium content

(391.3 mg 100g-1

) was observed in horse radish tree flowers after boiling process (Table

25, Figure 21).

108

Table 25. Sodium (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 491.60

q

±0.43

479.60t

±0.06

554.4m

±0.04

1114.5e

±0.03

1043.5h

±0.05 736.7

D

Lambs quarter 511.40

n

±0.43

501.1o

±0.06

654.6k

±0.04

1211.5a

±0.03

1151.5d

±0.05 806.1

A

Gram leaves 499.6

p

±0.43

489.6s

±0.006

584.4l

±0.02

1153.5c

±0.03

1065.7g

±0.05 758.5

C

Horse radish tree

flowers

401.6v

±0.43

391.3w

±0.06

454.6u

±0.04

1008.5i

±0.036

995.4j

±0.05 650.2

E

Spinach 501.6

o

±0.43

490.6r

±0.06

584.6l

±0.04

1197.5b

±0.03

1083.5f

±0.05 771.5

B

Mean 481.2D 470.5

E 566.5

C 1137.1

A 1067.9

B



Figure 21. Graphical representation of the sodium content (mg 100g

-1) of selected

vegetables

109

Determination of potassium content (mg 100g-1


Statistical ANOVA for vegetable types, processing methods and their

interaction revealed significant differences (P≤0.01) for K (Appendix XXII). Lambs

quarter had the higher potassium content (924.10 mg 100g-1

) followed by 904.1 mg 100g-

1 in lambs quarter. However, the minimum (845.2 mg 100g

-1) potassium content observed

in horse radish tree flowers (Table 26). Potassium content was significantly highest

(1059.6 mg 100g-1

) in thermally dehydrated samples of vegetables. However, the lowest

potassium content (758.5 mg 100g-1

) was found in boiled vegetables (Table 26).

Interactive effect of processing methods × vegetables showed highest potassium content

of 1081.40 mg 100g-1

in lambs quarter after thermal dehydration process. The lowest

potassium content (734.4 mg 100g-1

) was noted from horse radish tree flowers after

boiling treatment (Table 26, Figure 22).

110

Table 26. Potassium (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 779.8

q

±0.04

744.3w

±0.03

768.3r

±0.03

1066.5c

±0.02

988.5h

±0.03 869.4

C

Lambs quarter 828.5

k

±0.02

795.0n

±0.01

817.5l

±0.02

1081.4a

±0.02

998.4f

±0.03 904.1

A

Gram leaves 764.7

s

±0.02

738.7x

±0.03

753.5u

±0.26

1040.3d

±0.02

967.3i

±0.04 852.9

D

Horse radish tree

flowers

762.4t

±0.02

734.4y

±0.02

751.5v

±0.02

1035.4e

±0.02

942.4j

±0.04 845.2

E

Spinach 796.1

m

±0.05

780.1p

±0.04

785.6o

±1.00

1074.5b

±0.03

992.5g

±0.26 885.7

B

Mean 786.3C 758.5

E 775.3

C 1059.6

A 977.8

B



Figure 22. Graphical representation of the potassium content (mg 100g

-1) of selected

vegetables

111

Correlation matrix (r) of mineral content of different vegetables

The results of correlation analysis of mineral content of different

vegetables under the effect of postharvest processing are shown in Table 27. The

relationship showed that Cu, Zn, Ca, Mg, Na and K were significantly (P≤0.01) and

positively correlated with each other. The relationship of Ca with Fe and Mn showed

nonsignificant relationship with each other. Fe and Ca showed negative whereas Mn and

Ca showed positive relation with each other.

Table 27. Correlation matrix (r) of mineral content of different vegetables under the


Cu Fe Zn Mn Ca Mg Na K

Cu 1

Fe 0.647**

1

Zn 0.730**

0.432**

1

Mn 0.666**

0.847**

0.455**

1

Ca 0.481**

-0.059

0.681**

0.055

1

Mg 0.797**

0.626**

0.835**

0.540**

0.628**

1

Na 0.642**

0.313**

0.883**

0.402**

0.582**

0.599**

1

K 0.646**

0.227*

0.896**

0.348**

0.644**

0.615**

0.973**

1


112

Phytochemical content of different vegetables

Determination of alkaloids content (mg g-1


The results for alkaloids represented significant differences (P≤0.01)

among vegetable types, processing methods and their interaction (Appendix XXIII).

Amaranthus had maximum alkaloids (2.94 mg g-1

), while the lamb quarter ranked second

which was observed to be 0.69 mg g-1

. The minimum alkaloids content of 0.27 mg g-1

was noted in horse radish tree flowers whereas no alkaloids presence was found in

spinach (Table 28). Processing methods indicated significant differences for alkaloids

and showed maximum value of 1.14 mg g-1

in fresh or control vegetables followed by

0.96 mg g-1

in shade dried vegetables. While, minimum value (0.65 mg g-1

) of alkaloids

was observed in curry or cooked vegetables (Table 28). Interaction of processing

methods × vegetables showed highest alkaloids i.e. 3.56 mg g-1

in amaranthus at fresh

condition whereas least (0.07 mg g-1

) was found in horse radish tree flowers after cooking

treatment (Table 28, Figure 23).

113

Table 28. Alkaloids (mg g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 3.56

a

±0.04

2.85c

±0.004

2.36d

±0.05

2.97b

±0.05

2.98b

±0.03 2.94

A

Lambs quarter 0.96

e

±0.04

0.59hi

±0.004

0.46kl

±0.03

0.65h

±0.04

0.80f

±0.004 0.69

B

Gram leaves 0.74

g

±0.04

0.50jk

±0.006

0.36m

±0.05

0.55ij

±0.04

0.62h

±0.004 0.55

C

Horse radish tree

flowers

0.46kl

±0.04

0.19o

±0.006

0.07p

±0.04

0.25n

±0.04

0.40lm

±0.005 0.27

D

Spinach 0.00

q

±0.00

0.00q

±0.00

0.00q

±0.00

0.00q

±0.00

0.00q

±0.00 0.00

E

Mean 1.14A 0.83

D 0.65

E 0.88

C 0.96

B



Figure 23. Graphical representation of the alkaloids (mg g

-1) of selected vegetables

114

Determination of saponins content (mg g-1


The statistical analysis of variance showed a significant (P≤0.01) effect of

vegetable types, processing methods and their interaction on saponins content (Appendix

XXIV). Saponins in lambs quarter revealed higher value of 2.81 mg g-1

followed by 2.19

mg g-1

in gram leaves, while minimum saponins (1.11 mg g-1

) was noted in amaranthus.

There was no presence of saponins in spinach (Table 29). Saponins under the effect of

processing methods displayed highest value of 1.74 mg g-1

in fresh or control vegetables,

followed by 1.58 mg g-1

in shade dried vegetables. The saponins content was lower (0.94

mg g-1

) in curry or cooked vegetables (Table 29). Interaction of processing methods and

vegetables indicated highest saponins of 3.51 mg g-1

in lambs quarter at fresh condition

(control). The lowest saponins i.e. 0.75 mg g-1

was noted from amaranthus after cooking

or curry process (Table 29, Figure 24).

115

Table 29. Saponins (mg g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 1.650j

±0.05

0.953o

±0.004

0.750p

±0.04

1.050n

±0.03

1.146m

±0.006 1.11

C

Lambs quarter 3.510

a

±0.04

2.516f

±0.004

2.070h

±0.06

2.850c

±0.04

3.110b

±0.002 2.81

A

Gram leaves 2.600

e

±0.04

1.935i

±0.004

1.476k

±0.05

2.68d

±0.03

2.28g

±0.005 2.19

B

Horse radish tree

flowers

0.953o

±0.03

0.413q

±0.005

0.420q

±0.04

1.510k

±0.03

1.390l

±0.005 0.93

C

Spinach 0.00

p

±0.00

0.00p

±0.00

0.00p

±0.00

0.00p

±0.00

0.00p

±0.00 0.00

E

Mean 1.74A 1.16

D 0.94

E 1.61

B 1.58

C



Figure 24. Graphical representation of the saponins (mg g


116

Determination of flavinoids content (mg g-1


Statistical analysis of variance (ANOVA) revealed significant (P≤0.01)

differences in flavinoids under the effect of vegetable types, processing methods and their

interaction (Appendix XXV). The higher flavinoids content (1.21 mg g-1

) was found in

lambs quarter whereas the least flavinoids value was recorded in spinach i.e. 0.07 mg g-1

(Table 30). Among the processing methods, curry or cooked vegetables had minimum

(0.42 mg g-1

) flavinoids. The maximum (0.98 mg g-1

) flavinoids content was recorded in

fresh or control vegetables (Table 30). Interaction of processing methods and vegetables

resulted a maximum value of flavinoids i.e. 1.75 mg g-1

in lambs quarter at fresh

condition. However, the lower flavinoids content (0.02 mg g-1

) was observed from

spinach after curry or cooking process (Table 30, Figure 25).

117

Table 30. Flavinoids (mg g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.85

i

±0.002

0.53o

±0.002

0.24q

±0.002

0.55n

±0.004

0.82j

±0.002 0.60

D

Lambs quarter 1.75

a

±0.002

1.07d

±0.002

0.85i

±0.004

1.14c

±0.02

1.27b

±0.002 1.21

A

Gram leaves 1.27

b

±0.004

0.94g

±0.002

0.66k

±0.002

0.95f

±0.002

1.02e

±0.002 0.96

B

Horse radish tree

flowers

0.95f

±0.95

0.62m

±0.002

0.33p

±0.003

0.64l

±0.003

0.91h

±0.002 0.69

C

Spinach 0.11

r

±0.004

0.05u

±0.001

0.02v

±0.002

0.07t

±0.002

0.10s

±0.004 0.07

E

Mean 0.98A 0.64

D 0.42

E 0.67

C 0.82

B



Figure 25. Graphical representation of the flavinoids (mg g


118

Determination of phenols content (mg g-1


ANOVA for phenol indicated significant differences among vegetable

types, processing methods and their interaction (Appendix XXVI). Lambs quarter had

maximum value (4.29 mg g-1

) of phenol followed by 3.69 mg g-1

in gram leaves.

However, minimum (0.05 mg g-1

) phenol was observed in spinach (Table 31). Phenol as

influenced by processing methods showed minimum value of 1.58 mg g-1

in curry or

cooked vegetables followed by 1.84 mg g-1

detected in boiled vegetables. However, the

highest phenol (2.66 mg g-1

) was noted from fresh or control vegetables (Table 31).

Phenol content under the interaction of processing methods and vegetables varied

significantly and it was observed that highest value (5.56 mg g-1

) of phenol was in lambs

quarter at fresh condition. However, lowest phenol i.e. 0.012 mg g-1

, 0.01 mg g-1

and 0.02

mg g-1

was obtained from spinach after boiling, cooking and thermal dehydration process,

respectively (Table 31, Figure 26).

119

Table 31. Phenol (mg g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.35

o

±0.002

0.10s

±0.04

0.05t

±0.004

0.15q

±0.002

0.30p

±0.001 0.19

D

Lambs quarter 5.56

a

±0.003

3.51g

±0.003

3.25h

±0.002

3.92e

±0.003

5.22b

±0.002 4.29

A

Gram leaves 4.14

c

±0.004

3.54f

±0.002

2.85k

±0.002

3.93e

±0.004

3.98d

±0.002 3.69

B

Horse radish tree

flowers

3.15i

±0.002

2.07m

±0.002

1.75n

±0.002

2.28l

±0.002

2.97j

±0.002 2.44

C

Spinach 0.11

r

±0.004

0.012u

±0.002

0.01u

±0.002

0.02u

±0.0003

0.10rs

±0.009 0.05

E

Mean 2.66A 1.84

D 1.58

E 2.06

C 2.51

B



Figure 26. Graphical representation of the phenols (mg g


120

Determination of tanins content (mg g-1


Analysis of variance for tanins revealed significant differences under the

effect of vegetable types, processing methods and their interaction (Appendix XXVII).

Tanins content was higher (0.30 mg g-1

) in amaranthus, while the lambs quarter ranked

second with 0.28 mg g-1

. However, the tanins was lower (0.08 mg g-1

) in horse radish tree

flowers (Table 32). Processing methods indicated lowest value of tanins (0.08 mg g-1

) in

curry/ cooked vegetables followed by 0.14 mg g-1

found from boiled vegetables, whereas

highest (0.31 mg g-1

) tanins was noted from control or fresh vegetables (Table 32).

Interaction of processing methods and vegetables showed significantly maximum tanins

content of 0.48 mg g-1

from amaranthus at fresh condition (control). However, minimum

tanins content i.e. 0.04 mg g-1

was established from horse radish tree flowers after

cooking process (Table 32, Figure 27).

121

Table 32. Tanins (mg g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.48

a

±0.004

0.22de

±0.005

0.11hi

±0.003

0.25d

±0.002

0.44b

±0.004 0.30

A

Lambs quarter 0.45

b

±0.04

0.21e

±0.003

0.09ijk

±0.003

0.23de

±0.002

0.43b

±0.006 0.28

B

Gram leaves 0.18

f

±0.003

0.09ij

±0.0004

0.07jkl

±0.002

0.10i

±0.001

0.13gh

±0.0004 0.11

D

Horse radish tree

flowers

0.14g

±0.002

0.06kl

±0.003

0.04l

±0.003

0.09ijk

±0.02

0.10hi

±0.003 0.09

E

Spinach 0.34

c

±0.003

0.10hi

±0.10

0.08ijk

±0.004

0.11hi

±0.002

0.22e

±0.07 0.17

C

Mean 0.31A 0.14

D 0.08

E 0.15

C 0.26

B



Figure 27. Graphical representation of the tanins (mg g


122

Correlation matrix (r) of phytochemical content of different vegetables

The relationships among phytochemicals of different vegetables under the

effect of postharvest processing are presented in Table 33. It is obvious from the results

that alkaloids showed a non-significant (P ≥ 0.05) positive relationship with saponins (r =

0.118) and flavinoids (r = 0.147) while a significant negative correlation with phenol (r =

-0.30) and a significant positive association with tannins (r = 0.547) was noted. Similarly,

saponins had a significant and positive correlation with flavinoids (r = 0.932), phenol (r =

0.868) and tannins (r = 0.330). Flavinoids showed a positive and significant correlation

with phenol (r = 0.871) and tannins (r = 0.384). However, phenol and tannins had a non-

significant association.

Table 33. Correlation matrix (r) of phytochemical content of different vegetables

under the influence of processing treatments

Alkaloids Saponins Flavinoids Phenol Tanins

Alkaloids 1

Saponins 0.118

1

Flavinoids 0.147

0.932**

1

Phenol -0.300*

0.868**

0.871**

1

Tanins 0.547** 0.330**

0.384**

0.043

1


123

Vitamin content of different vegetables

Determination of β-carotene content (mg 100g-1


Analysis of variance for β-carotene is given in Appendix XXVIII.

Analysis indicated a significant effect of vegetable types, processing methods and their

interaction on β-carotene content. The maximum β-carotene content (2.93 mg 100g-1

)

was observed in spinach, while the lambs quarter ranked second with 2.98 mg 100g-1

.

However, the lowest β-carotene of 0.02 mg 100g-1

was recorded in gram leaves (Table

34). β-carotene content as influenced by processing methods showed lowest value of 0.82

mg 100g-1

from curry or cooked vegetables followed by 1.40 mg 100g-1

from boiled

vegetables, while highest β-carotene of 2.73 mg 100g-1

observed from control/ fresh

vegetables (Table 34). Interactive effect of processing methods × vegetables showed

highest β-carotene (4.93 mg 100g-1

) from spinach at fresh condition. The lowest β-

carotene content i.e. 0.009 mg 100g-1

and 0.008 mg 100g-1

was noted from gram leaves

after boiling and curry process, respectively (Table 34, Figure 28).

124

Table 34. β-carotene content (mg 100g-1

) of different types of vegetables under the

effect of postharvest processing methods

Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 3.28

b

±0.004

0.97h

±0.004

0.54ij

±0.004

1.01h

±0.005

1.09h

±0.004 1.38

B

Lambs quarter 3.46

b

±0.04

3.07c

±0.004

1.77f

±0.04

3.28b

±0.005

3.33b

±0.02 2.98

A

Gram leaves 0.04

k

±0.005

0.009k

±0.002

0.008k

±0.002

0.02k

±0.005

0.03k

±0.003 0.02

D

Horse radish tree

flowers

2.26e

±0.04

0.55ij

±0.003

0.37j

±0.004

0.73i

±0.04

1.45g

±0.005 1.07

C

Spinach 4.60

a

±0.006

2.40e

±0.003

1.40g

±0.004

2.81d

±0.004

3.46b

±0.005 2.93

A

Mean 2.73A 1.40

D 0.82

E 1.57

C 1.87

B



Figure 28. Graphical representation of the vitamin A (β-carotene) content (mg

100g-1

) of selected vegetables

125

Determination of vitamin C content (mg 100g-1


Vitamin C content was significantly (P≤0.01) affected by vegetable types,

processing methods and their interaction as shown Appendix XXIX. The results for

vitamin C indicated maximum value of 37.33 mg 100g-1

in gram leaves followed by

35.62 mg 100g-1

in amaranthus as compared to lower vitamin C of 3.42 mg 100g-1

in

horse radish tree flowers (Table 35). Processing methods represented lowest (15.42 mg

100g-1

) vitamin C from curry/cooked vegetables followed by 16.91 mg 100g-1

from

boiled vegetables. However, highest vitamin C content (41.11 mg 100g-1

) was noted from

fresh vegetable samples (Table 35). Interaction of processing methods × vegetables

showed significantly higher vitamin C i.e. 60.74 mg 100g-1

in gram leaves at fresh

condition, while minimum vitamin C of 1.31 mg 100g-1

was recorded from horse radish

tree flowers after curry or cooking process (Table 35, Figure 29).

126

Table 35. Vitamin C (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 56.34

b

±0.04

25.98k

±0.005

23.55m

±0.005

34.67h

±0.004

37.57f

±0.05 35.62

B

Lambs quarter 43.79

c

±0.007

18.11q

±0.004

17.42r

±0.005

22.13n

±0.005

27.41i

±0.005 25.77

C

Gram leaves 60.74

a

±0.004

26.33j

±0.004

24.08l

±0.003

35.50g

±0.004

39.99d

±0.004 37.33

A

Horse radish tree

flowers

6.727u

±0.004

1.977x

±0.005

1.313y

±0.003

3.337w

±0.002

3.793v

±0.005 3.429

E

Spinach 37.95

e

±0.006

12.14s

±0.004

10.75t

±0.004

19.90p

±0.004

21.04o

±0.026 20.36

D

Mean 41.11A 16.91

D 15.42

E 23.11

C 25.96

B



Figure 29. Graphical representation of the vitamin C (mg 100g

-1) of selected

vegetables

127

Determination of vitamin B1 content (mg 100g-1


ANOVA for vitamin B1 showed significant differences (P≤0.01) among

vegetable types, processing methods and their interaction (Appendix XXX). Gram leaves

had higher vitamin B1 of 0.159 mg 100g-1

followed by 0.126 mg 100g-1

in lambs quarter,

while the lowest vitamin B1 (0.019 mg 100g-1

) was noted in amaranthus (Table 36).

Vitamin B1 content revealed the lowest (0.054 mg 100g-1

) from curry/ cooked vegetables

whereas the highest vitamin B1 (0.126 mg 100g-1

) was found from fresh vegetables

(Table 36). Interactive effect processing methods × vegetables showed significantly

maximum vitamin B1 content of 0.216 mg 100g-1

in gram leaves at fresh or control

condition (Table 36, Figure 30).

128

Table 36. Vitamin B1 (mg 100g-1



Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.026

jkl

±0.005

0.017kl

±0.0005

0.013l

±0.0004

0.018kl

±0.0003

0.024kl

±0.0004 0.019

E

Lambs quarter 0.170

b

±0.04

0.120de

±0.004

0.086fg

±0.004

0.120de

±0.002

0.133cde

±0.006 0.126

B

Gram leaves 0.216

a

±0.004

0.123de

±0.005

0.106ef

±0.003

0.143bcd

±0.004

0.206a

±0.003

0.159A

Horse radish tree

flowers

0.060ghi

±0.04

0.038ijk

±0.004

0.033ijkl

±0.03

0.039ijk

±0.004

0.050hij

±0.03 0.044

D

Spinach 0.156

bc

±0.004

0.038ijk

±0.0005

0.037ijkl

±0.003

0.054hij

±0.004

0.071gh

±0.0005 0.071

C

Mean 0.126A 0.068

C 0.054

D 0.075

C 0.096

B



Figure 30. Graphical representation of the vitamin B1 (mg 100g

-1) of selected

vegetables

129



Statistical analysis showed significant differences (P≤0.01) in vitamin B2

under the influence of vegetable types, processing methods and their interaction

(Appendix XXXI). The maximum vitamin B2 (0.317 mg 100g-1

) was recorded in lambs

quarter while minimum of 0.014 mg 100g-1

vitamin B2 was observed in amaranthus

(Table 37). Among processing methods, the lowest value of 0.096 mg 100g-1

vitamin B2

content was observed from curry or cooked vegetables followed by 0.106 mg 100g-1

from

boiled vegetables whereas, high vitamin B2 content (0.184 mg 100g-1

) was found from

fresh vegetables (Table 37). Interaction of processing methods and vegetables

represented highest vitamin B2 content (0.46 mg 100g-1

) in lambs quarter at fresh or

control condition. However, lower vitamin B2 content i.e. 0.008 mg 100g-1

was

determined from amaranthus after curry or cooking (Table 37, Figure 31).

130




Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.016

lm

±0.003

0.011m

±0.0005

0.008m

±0.002

0.013lm

±0.004

0.016klm

±0.0006 0.014

D

Lambs quarter 0.460

a

±0.04

0.276cd

±0.004

0.250d

±0.04

0.290bc

±0.04

0.310b

±0.005 0.317

A

Gram leaves 0.076

hi

±0.004

0.038kl

±0.0004

0.036klm

±0.005

0.046jk

±0.005

0.068ij

±0.0007 0.054

C

Horse radish tree

flowers

0.180e

±0.03

0.101fgh

±0.005

0.086ghi

±0.005

0.113fg

±0.003

0.176e

±0.004

0.132B

Spinach 0.186

e

±0.004

0.103fgh

±0.003

0.096ghi

±0.005

0.126f

±0.004

0.173e

±0.004 0.137

B

Mean 0.184A 0.106

CD 0.096

D 0.118

C 0.150

B




-1) of selected

vegetables

131



ANOVA for vitamin B3 content showed significant differences (P≤0.01)

under the effect of vegetable types, processing methods and their interaction (Appendix

XXXII). The results for vitamin B3 represented highest value (0.962 mg 100g-1

) in lambs

quarter, followed by horse radish tree flowers (0.672 mg 100g-1

), spinach (0.54 mg 100g-

1), amaranthus (0.523 mg 100g

-1) and then gram leaves (0.502 mg 100g

-1) as shown in

Table 38. Different processing methods revealed the lowest vitamin B3 (0.434 mg 100g-1

)

from cooked vegetables whereas the highest value (0.901 mg 100g-1

) of vitamin B3 was

noted from fresh vegetables (Table 38). Vitamin B3 under the interactive effect of

processing methods and vegetables displayed highest value i.e. 1.500 mg 100g-1

in lambs

quarter at fresh or control (Table 38, Figure 32).

132




Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 0.736

cde

±0.003

0.396h

±0.005

0.366h

±0.004

0.416h

±0.003

0.698de

±0.002 0.523

C

Lambs quarter 1.500

a

±0.45

0.696de

±0.005

0.650e

±0.04

0.850cd

±0.03

1.116b

±0.003 0.962

A

Gram leaves 0.666

e

±0.004

0.426h

±0.004

0.336h

±0.005

0.450h

±0.04

0.629ef

±0.003 0.502

C

Horse radish tree

flowers

0.880c

±0.03

0.619efg

±0.005

0.450h

±0.04

0.640e

±0.04

0.768cde

±0.002 0.672

B

Spinach 0.723

de

±0.005

0.466gh

±0.005

0.366h

±0.004

0.483fgh

±0.005

0.669e

±0.006 0.542

C

Mean 0.901A 0.521

C 0.434

D 0.568

C 0.777

B




-1) of selected

vegetables

133

Correlation matrix (r) of vitamin content of different vegetables

Table 39 indicates relationship among vitamin contents of different

vegetables under the effect of postharvest processing. β-carotene showed a significant

positive relationship with vitamin B2 (r = 0.646) and vitamin B3 (r = 0.553) whereas a

non-significant correlation was obtained with vitamin C (r = 0.091) and vitamin B1 (r =

0.056). Vitamin C also showed a non-significant association with vitamin B2 (r = -0.088)

and vitamin B3 (r = 0.213) whereas a significant correlation was found with vitamin B1 (r

= 0.498). The vitamin B1, vitamin B2 and vitamin B3 were significantly positive

associated with each other as indicated by “r” value which is ranging from 0.342 to

0.766.

Table 39. Correlation matrix (r) of vitamin content of different vegetables under the


β-carotene Vitamin C Vitamin B1 Vitamin B2 Vitamin B3

β-carotene 1

Vitamin C 0.091

1

Vitamin B1 0.056

0.498**

1

Vitamin B2 0.646**

-0.088

0.408**

1

Vitamin B3 0.553**

0.213

0.342**

0.766**

1


134

Total solids, total soluble solids, energy value, pH, nitrogen free extract and fatty

acid contents of different vegetables

Determination of total solids (%) in selected vegetables

The total solids content was significantly (P≤0.01) affected by different

types of processing methods, vegetable types and their interaction (Appendix XXXIII).

The values of total solids in amaranthus, lambs quarter, gram leaves, horse radish tree

flowers and spinach were in order of 51.63, 49.08, 50.52, 48.70 and 45.53%, respectively

(Table 40). Among the processing methods, the highest value (93.72%) of total solids

was noted in thermally dehydrated vegetables followed by shade dried (93.01%).

However, minimum of 13.48% total solids was detected in boiled vegetables (Table 40).

Interactive effect of vegetables × processing methods showed greater value of total solids

(95.06%) in horse radish tree flowers under thermal dehydration process, while the least

value of total solids (7.34%) was found in spinach under boiling method (Table 40,

Figure 33).

135

Table 40. Total solids (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 18.03

hi

±0.33

16.95hi

±0.31

34.50d

±0.3

94.59a

±0.11

94.11a

±0.15 51.63

A

Lambs quarter 15.92

ij

±0.72

14.54jk

±0.64

28.58f

±0.25

93.58ab

±0.10

92.82ab

±0.11 49.08

C

Gram leaves 17.72

hi

±0.10

15.86ij

±0.13

31.24e

±0.92

94.00a

±0.36

93.78a

±0.13 50.52

B

Horse radish tree

flowers

19.02h

±0.24

12.74kl

±0.54

22.54g

±1.21

95.06a

±0.27

94.16a

±0.22 48.70

C

Spinach 11.24

l

±0.41

7.34m

±0.08

27.53f

±1.13

91.37bc

±0.18

90.16c

±0.12 45.53

D

Mean 16.38C 13.48

D 28.87

B 93.72

A 93.01

A



Figure 33. Graphical representation of the total solids (%) of selected vegetables

136

Determination of total soluble solids (°Brix) in selected vegetables

Statistical analysis of variance (ANOVA) indicated a significant effect of

vegetable types, processing types and interaction of vegetables × processing (Appendix

XXXIV). The results indicated maximum (2.017°Brix) total soluble solids in spinach

followed by gram leaves (1.971°Brix), amaranthus (1.472°Brix), lambs quarter

(1.05°Brix) and horse radish tree flowers (0.936°Brix) as shown in Table 41. Vegetables

treated with different processing methods displayed significant differences for total

soluble solids. Maximum value of total soluble solids (2.094°Brix) was found in

thermally dehydrated vegetables, while the shade drying method ranked second with

1.828°Brix, whereas lower value of 0.94°Brix total soluble solids was observed in boiled

method (Table 41). Total soluble solids under the interactive effect of vegetable type and

processing type showed higher value of 2.68, 2.66 and 1.963°Brix in gram leaves,

spinach and amaranthus, respectively under thermall dehydration method (Table 41,

Figure 34).

137

Table 41. Total soluble solids (°Brix) of different types of vegetables under the effect


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 1.936

e

±0.06

0.936l

±0.05

0.990kl

±0.06

1.963de

±0.02

1.536g

±0.35 1.472

C

Lambs quarter 1.040

k

±0.07

0.550m

±0.02

0.580m

±0.02

1.660f

±0.04

1.420ij

±0.02 1.050

D

Gram leaves 2.030

d

±0.07

1.420ij

±0.03

1.446hij

±0.04

2.680a

±0.06

2.280c

±0.05 1.971

B

Horse radish tree

flowers

0.953l

±0.03

0.413n

±0.03

0.416n

±0.04

1.510gh

±0.05

1.386j

±0.03 0.936

E

Spinach 2.020

d

±0.07

1.420ij

±0.02

1.470ghi

±0.04

2.660a

±0.03

2.516b

±0.05 2.017

A

Mean 1.596C 0.948

D 0.981

D 2.094

A 1.828

B



Figure 34. Graphical representation of the total soluble solids (°Brix) of selected

vegetables

138

Determination of energy value (Kcal 100g-1


Analysis of variance represented a significant (P≤0.01) effect of

processing methods, vegetable types and their interaction on energy value as indicated in

Appendix XXXV. Energy value in amaranthus, gram leaves, lambs quarter, spinach and

horse radish tree flowers was in order of 150.3, 143.2, 142.1, 139.8 and 130.3 Kcal 100g-

1, respectively (Table 42). Among the processing methods, maximum energy value

(265.8 Kcal 100g-1

) was noted in shade dried vegetables followed by thermally dehdrated

vegetables (261.63 Kcal 100g-1

). However, minimum energy value (41.04 Kcal 100g-1

)

was exhibited in boiled vegetables (Table 42). Interactive effect of vegetables and

processing methods showed lowest energy value (28.41 Kcal 100g-1

) in spinach under

boiling method (Table 42, Figure 35).

Table 42. Energy value (Kcal 100g-1

) of different types of vegetables under the effect


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 53.32

f

±0.32

50.43f

±0.75

107.6d

±0.51

268.9ab

±2.10

271.6a

±1.18 150.3

A

Lambs quarter 43.05

fg

±0.92

42.16fg

±0.74

89.45de

±0.89

266.1ab

±0.3

269.7a

±0.51 142.1

AB

Gram leaves 47.21

fg

±0.28

45.16fg

±0.32

92.90de

±1.59

261.98ab

±0.54

269.0a

±0.93 143.2

AB

Horse radish

tree flowers

47.02fg

±0.26

39.06fg

±1.27

75.25e

±1.98

241.5c

±0.46

249.0bc

±1.04 130.3

C

Spinach 38.35

fg

±0.78

28.41g

±0.43

92.93de

±1.36

269.6a

±0.51

269.8a

±0.21 139.8

B

Mean 45.79C 41.04

C 91.63

B 261.63

A 265.8

A



139

Figure 35. Graphical representation of the energy value (Kcal 100g

-1) of selected

vegetables

Determination of pH value in selected vegetables

Statistical analysis of variance for pH value showed significant differences

(P≤0.01) among vegetable types, processing types and their interaction (Appendix

XXXVI). The higher pH of 7.26 and 7.13 was recorded in lambs quarter and amaranthus,

respectively while the minimum pH of 6.64 was detected in gram leaves (Table 43).

Among the processing methods, boiled vegetables had maximum pH value of 7.202

while the cooked vegetables ranked second with 7.134. The minimum pH (6.827) was

found in samples of thermally dehydrated vegetables (Table 43). Interactive effect of

vegetable type × processing type showed highest pH value of 7.446 in lambs quarter

under boiling process (Table 43, Figure 36).

140

Table 43. pH level of different types of vegetables under the effect of postharvest

processing methods

Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 7.150

f

±0.04

7.330bc

±0.04

7.240de

±0.04

6.946hi

±0.05

7.026gh

±0.06 7.138

B

Lambs quarter 7.260

cd

±0.02

7.446a

±0.26

7.373ab

±0.014

7.083fg

±0.04

7.156ef

±0.04 7.264

A

Gram leaves 6.660

kl

±0.04

6.820j

±0.04

6.710k

±0.06

6.460m

±0.02

6.580l

±0.04 6.646

D

Horse radish tree

flowers

6.980h

±0.02

7.130f

±0.06

7.010gh

±0.08

6.810j

±0.06

6.880ij

±0.05 6.962

C

Spinach 7.076

fg

±0.07

7.286cd

±0.06

7.340bc

±0.04

6.836j

±0.04

6.973h

±0.03 7.102

B

Mean 7.025C 7.202

A 7.134

B 6.827

E 6.923

D



Figure 36. Graphical representation of the pH of selected vegetables

141

Determination of nitrogen free extracts (%) in selected vegetables

Analysis of variance for nitrogen free extracts is given in Appendix

XXXVII. Analysis indicated significant differences (P≤0.01) for vegetable types,

processing methods and their interaction. The higher nitrogen free extract was recorded

in amaranthus (28.24%), lambs quarter (27.56%), spinach (26.24%) and gram leaves

(26.04%) as compared to lower nitrogen free extract of 20.28% in horse radish tree

flowers (Table 44). Samples had the highest nitrogen free extract of 55.92 and 53.17% in

shade dried and thermally dehydrated vegetables, respectively. However, the minimum

values of 3.043 and 4.686% nitrogen free extract were noted in fresh and boiled

vegetables, respectively (Table 44). Interactive effect of vegetable type and processing

methods indicated maximum value of nitrogen free extract i.e. 59.03% in lambs quarter

under shade drying process (Table 44, Figure 37).

142

Table 44. Nitrogen free extract (%) of different types of vegetables under the effect


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 5.060

efg

±0.76

7.630defg

±1.03

15.94d

±0.68

55.30ab

±1.25

57.28ab

±2.51 28.24

A

Lambs quarter 4.017

efg

±0.51

6.337defg

±1.37

11.66def

±0.28

56.77ab

±0.26

59.03a

±1.07 27.56

A

Gram leaves 2.873

efg

±0.52

5.837efg

±0.37

12.08de

±0.96

53.00abc

±0.27

56.42ab

±0.94 26.04

A

Horse radish tree

flowers

1.600g

±0.38

1.750fg

±0.72

5.783efg

±1.17

43.84c

±0.26

48.46bc

±0.93 20.28

B

Spinach 1.663

g

±0.44

1.877fg

±0.17

12.29de

±0.95

56.96ab

±0.51

58.43ab

±0.75 26.24

A

Mean 3.043C 4.686

C 11.55

B 53.17

A 55.92

A



Figure 37. Graphical representation of the nitrogen free extract (%) of selected

vegetables

143

Determination of total fatty acids (%) in selected vegetables

Statistical analysis showed that total fatty acids were significantly

(P≤0.01) affected by vegetable types, processing methods and interaction of vegetables x

processing (Appendix XXXVIII). Total fatty acids were higher (2.184%) in horse radish

tree flowers, while the spinach ranked second with 2.096% total fatty acids. However, the

lowest (1.319%) total fatty acids were observed in lambs quarter (Table 45). Total fatty

acids under the effect of processing methods indicated significant differences and showed

a maximum value of total fatty acids (2.640%) in curry or cooked vegetables followed by

thermally dehydrated (1.898%), while minimum value (1.052%) of total fatty acids was

recorded from boiled samples of vegetables (Table 45). Interactive effect of vegetables

and processing type resulted highest total fatty acids (3.08%) in horse radish tree flowers

at cooking or curry process. However, least value (0.68%) of total fatty acids was

observed in gram leaves under boiling method (Table 45, Figure 38).

144

Table 45. Total fatty acids (%) of different types of vegetables under the effect of


Vegetables

Processing methods

Mean Fresh


Thermally

dehydrated

Shade

dried

Amaranthus 1.720

defghi

±0.14

0.880kl

±0.18

2.720ab

±0.21

2.040cde

±0.22

1.846cdefgh

±0.24 1.841

B

Lambs quarter 1.00

jkl

±0.22

0.700l

±0.17

2.280bc

±0.22

1.360hijk

±0.14

1.256ijk

±0.2 1.319

C

Gram leaves 1.280

ijk

±0.12

0.680l

±0.2

2.200cd

±0.18

1.610efghi

±0.14

1.593efghi

±0.16 1.472

C

Horse radish tree

flowers

1.920cdefg

±0.11

1.520fghi

±0.21

3.080a

±0.22

2.280bc

±0.18

2.120cd

±0.18 2.184

A

Spinach 1.880

cdefg

±0.1

1.480ghij

±0.22

2.920a

±0.14

2.200cd

±0.14

2.00cdf

±0.14 2.096

A

Mean 1.560C 1.052

D 2.640

A 1.898

B 1.763

BC



Figure 38. Graphical representation of the total fatty acid (%) of selected vegetables

145

Correlation matrix (r) of Nitrogen free extract, energy value, fatty acid, pH, total

solids and TSS of different vegetables

The relationships among nitrogen free extract, energy value, fatty acid,

pH, total solids and total soluble solids of vegetables under the influence of postharvest

processing are shown in Table 46. The relationship showed that total solids was

significantly and positively correlated with total soluble solids (r = 0.561), energy (r =

0.992) and nitrogen free extract (r = 0.968) whereas a significant negative correlation was

observed with pH (r = -0.469). Fatty acid imparted a non-significant correlation with total

solids (r = 0.149), pH (r = -0.040), total soluble solids (r = -0.004), energy (r = 0.178) and

nitrogen free extract (r = -0.103). Nitrogen free extract showed a significant positive

association with total soluble solids (r = 0.572) and energy (r = 0.998) while non-

significantly and negatively associated with pH (r = -0.403). Energy value indicated

significant negative association with pH (r = -0.442) and positive association with total

soluble solids (r = 0.570). However, pH showed significant relationship with total soluble

solids (r = -0.620).

146

Table 46. Correlation matrix (r) of Nitrogen free extract, energy value, fatty acid,

pH, total solids and TSS of different vegetables under the influence of

processing treatments

Total solids PH TSS Energy NFE Fatty acid

Total solids 1

PH -0.469**

1

TSS 0.561**

-0.620**

1

Energy 0.992**

-0.442**

0.570**

1

NFE 0.968**

-0.403**

0.572**

0.988**

1

Fatty acid 0.149

-0.040

-0.004

0.178

0.103

1


Determination of total chlorophyll content (mg g-1


Analysis of variance for total chlorophyll content is given in Appendix

XXXIX. The results in Table 47 (Figure 39) show the chlorophyll content of amaranthus,

gram leaves, horse radish tree flower, lambs quarter and spinach leaves. The purpose of

chlorophyll determination was to ensure the quality of the vegetable. The highest total

chlorophyll content (a + b) was detected in lambs quarter (3.19 mg g-1

), followed by

spinach (1.88 mg g-1

), amaranthus (1.850 mg g-1

), gram leaves (1.504 mg g-1

) and horse

radish tree flowers (0.048 mg g-1

).

147

Table 47. Chlorophyll content of fresh vegetables selected in the present study

Vegetables Chlorophyll a

(mg g-1

)

Chlorophyll b

(mg g-1

)

Total chlorophyll

(mg g-1

)

Amaranthus 1.306b ± 0.005 0.543

c ± 0.009 1.850

c ± 0.006

Lambs quarter 1.548a ± 0.003 1.650

a ± 0.008 3.199

a ± 0.004

Gram leaves 1.147c ± 0.004 0.357

d ± 0.002 1.504

d ± 0.007

Horse radish tree

flowers 0.027

d ± 0.005 0.021

e ± 0.009 0.048

e ± 0.004

Spinach 1.311b ± 0.005 0.577

b ± 0.007 1.888

b ± 0.008

Mean values ± SD triplicate determinations. Mean values within a column with different

superscripts are significantly different at P<0.05

Figure 39. Graphical representation of the total chlorophyll (%) of selected

vegetables

148

Sensory evaluation of selected vegetables

Sensory evaluation of uncooked vegetables

The data presented in table 48 (Figure 40- 44) shows the five point scale

of 5 raw or uncooked non-traditional vegetables, in which different parameters were

studied including appearance, color, odor, texture, taste and overall acceptability. Horse

radish tree flowers obtained highest scores in appearance, color, odor, texture, taste,

overall acceptability and purchase i.e. 4.90, 4.70, 4.00, 3.90, 3.50, 3.80 and 3.80. The

second vegetable securing highest scores was gram leaves followed by amaranthus,

lambs quarter and spinach. The analysis of variance for sensory analysis of uncooked

vegetables is given in Appendix XLI.

Table 48. Five point scale sensory scores of raw or uncooked vegetables

Parameters Amaranthus

Lambs

quarter

Gram

leaves

Horse

radish tree

flowers

Spinach

Appearance 3.90a ±0.73 3.70

a ±0.82 4.10

a ±0.87 4.90

b ±0.31 3.60

a ±1.17

Color 4.00ab

±0.81 3.60a ±0.84 4.00

ab ±0.81 4.70

b ±0.48 3.60

a ±1.07

Odor /

Aroma 3.70

a ±0.67 3.20

a ±0.91 3.60

a ±1.26 4.00

a ±0.47 3.30

a ±0.94

Texture

rating 3.60

ab ±0.69 3.10

a ±0.73 3.80

ab ±0.78 3.90

b ±0.56 3.30

ab ±0.94

Taste/ flavor 2.90a ±1.10 3.00

a ±0.94 3.20

a ±1.13 3.50

a ±0.85 3.20

a ±1.13

Overall

acceptability 3.50

a ±0.85 3.40

a ±0.84 3.50

a ±0.97 3.80

a ±0.78 3.60

a ±0.96

Purchase 3.20a ±1.31 3.10

a ±0.87 3.60

a ±1.17 3.80

a ±0.91 3.50

a ±1.19

Values are expressed as mean (n=10); Values with different superscripts down the rows

are significantly different from each other at p<0.05

149

Figure 40. Spider chart showing five point scale sensory scores of uncooked

amaranthus vegetable

Figure 41. Spider chart showing five point scale sensory scores of uncooked lambs

quarter vegetable

150

Figure 42. Spider chart showing five point scale sensory scores of uncooked gram

leaves vegetable

Figure 43. Spider chart showing five point scale sensory scores of uncooked horse

radish tree flowers vegetable

151

Figure 44. Spider chart showing five point scale sensory scores of uncooked spinach

vegetable

Sensory evaluation of cooked vegetables

The scores of all the attributes showed that samples cooked by different

methods were highly acceptable (Table 49, Figure 45-49). Analysis of variance for total

chlorophyll content is given in Appendix XLII. Traditionally cooked lambs quarter and

gram leaves retained original color and thus obtained the highest scores in appearance i.e.

3.70 and 3.90, respectively. The lambs quarter vegetable retained pleasant odor with the

score of 3.50, as compared with horse radish tree flowers, gram leaves, amaranthus and

spinach (3.30, 3.20, 3.10 and 3.10, respectively). Gram leaves and horse radish tree

flowers secured the same rating for texture (3.70), purchase (4.20) and overall

acceptability (3.40).

152

Table 49. Five point scale sensory scores of cooked vegetables

Parameters Amaranthus Lambs

quarter

Gram

leaves

Horse

radish tree

flowers

Spinach

Appearance 3.60a ±1.07 3.70

a ±1.25 3.70

a ±0.94 3.60

a ± 1.26 3.40

a ±1.07

Taste 3.20a ±0.91 3.90

ab ±0.99 3.50

ab±0.52 3.50

ab ±0.97 4.10

b ±0.56

Odor/ Aroma 3.10a ±0.73 3.50

a ±0.70 3.20

a ±0.91 3.30

a ±0.94 3.10

a ±0.73

Texture

rating 3.50

a ±0.85 3.00

a ±1.05 3.70

a ±0.67 3.70

a ±0.82 3.00

a ±0.94

Overall

acceptability 3.30

a ±1.25 3.80

a ±1.22 3.40

a ±

0.84 3.40

a ±0.69 3.00

a ±1.24

Purchase 3.90a ±0.99 4.10

a ±0.87 4.20

a ±0.91 4.20

a ±1.13 3.90

a ±0.99

Values are expressed as mean (n=10); Values with different superscripts down the rows

are significantly different from each other at p<0.05

Figure 45. Spider chart showing five point scale sensory scores of cooked

amaranthus vegetable

153

Figure 46. Spider chart showing five point scale sensory scores of cooked lambs

quarter vegetable

Figure 47. Spider chart showing five point scale sensory scores of cooked gram

leaves vegetable

154

Figure 48. Spider chart showing five point scale sensory scores of cooked horse

radish tree flowers vegetable

Figure 49. Spider chart showing five point scale sensory scores of cooked spinach

vegetable

155

Principal component analysis of nutritional characteristics of different vegetables

Quality of vegetables can be affected by several factors (pre-harvest &

post-harvest factors) and the nutritional characteristics of different vegetables vary

differently. This situation leads to search for linear combinations which are optimal in

some sense. These linear combinations are computed by the methods called “Principle

Component Analysis”. The principal component analysis transforms the original

variables into new axes, or principal components, which are orthogonal, so that the data

presented in those axes are uncorrelated with each other; therefore, PCA provides

information for interpretation and better understanding of the most meaningful

parameters which describes the whole data set through data reduction with a minimum

loss of the original information (Berrueta et al., 2007; Cam et al., 2009). The first

principal component covers as much of the variation in the data as possible. The second

principal component is orthogonal to the first and covers as much of the remaining

variation as possible, and so on. The results obtained in PCA are interpreted in the

following sections:

Component analysis

Table 50 shows the eigenvalue and total variance explained for our factor

solution. There are thirty-four variables used in the sample. It is quite clear from the table

that the first seven components has their eigenvalues over 1 and are large enough to be

retained. This is based on Chatfield and Collin (1980) assumption which stated that

components with an eigenvalue of less than 1 should be eliminated. The result further

156

revealed that the first seven components contributed 94.79% (that is their cumulative

variance) of the variability among the observed variables. This indicates that the variance

of the 34 observed variables had been accounted for by these 7 extracted components

(principle components). Component 1, 2, 3, 4, 5, 6 and 7 explained 46.98, 14.39, 11.65,

8.31, 5.91, 4.31 and 3.24% of the total variation, respectively. It can also be seen from the

table that the initial eigenvalues and the extracted eigenvalues are exactly same which is

evident of the validity of the principal component analysis.

157

Table 50. Extraction of components by using eigen values and variability percentage

Component

Initial Eigenvalues Extraction Sums of Squared Loadings

Total % of

Variance Cumulative % Total

% of

Variance

Cumulative

%

1 15.97 46.97 46.97 15.97 46.96 46.97

2 4.89 14.38 61.36 4.89 14.36 61.32

3 3.96 11.65 73.01 3.96 11.64 73.01

4 2.82 8.31 81.32 2.82 8.31 81.39

5 2.01 5.91 87.24 2.01 5.91 87.22

6 1.46 4.30 91.54 1.46 4.30 91.59

7 1.10 3.24 94.79 1.10 3.24 94.70

8 0.41 1.21 96.00

9 0.31 0.93 96.94

10 0.21 0.62 97.56

11 0.17 0.50 98.07

12 0.15 0.46 98.53

13 0.13 0.40 98.94

14 0.09 0.28 99.22

15 0.07 0.21 99.43

16 0.05 0.17 99.60

17 0.03 0.10 99.70

18 0.03 0.08 99.79

19 0.02 0.08 99.87

20 0.01 0.04 99.92

21 0.01 0.03 99.95

22 0.007 0.02 99.97

23 0.005 0.01 99.98

24 0.002 0.007 99.99

25 0.001 0.004 99.99

26 0.001 0.002 99.99

27 0.00 0.00 100.00

28 0.00 0.00 100.00

29 9.067E-16 2.667E-15 100.00

30 3.683E-16 1.083E-15 100.00

31 4.244E-17 1.248E-16 100.00

32 -3.010E-16 -8.854E-16 100.00

33 -6.149E-16 -1.809E-15 100.00

34 -8.781E-16 -2.583E-15 100.00

158

Scree plot

The scree plot of the eignvalues of observed components is depicted in

Figure 50. The horizontal axis shows the number of total components (34) while on

vertical axis, the eigenvalues are plotted. It can be clearly seen from the figure that first

seven eigenvalues are greater in magnitude whereas after these seven values the change

in eigenvalue is very small i.e., less than one. Based on the large magnitude of the first

seven eigenvalues it can be easily concluded that seven factors are well enough to

account for the data variability.

Figure 50. Scree plot of the eigenvalues

159

Principal component loadings

The calculated component loadings are shown in Table 51. The

component loading is a matrix of correlation between components and variables. Factor

scores or “factor loadings” indicate how each “hidden” factor is associated with the

“observable” variables used in the analysis. The first column is the correlation between

the first component and each variable, the second column is the correlation between the

second component and each variable and so on.

Classifying the component loading according to Liu et al. (2003) the

loading values greater 0.75 signifies “strong”, the loading with absolute values between

0.75 and 0.50 indicate “moderate” while loading values between 0.50 and 0.30 denote as

“weak”. Using this classification, the first principal component axis had strong loading

for moisture, total solid, ash, fiber, carbohydrate, nitrogen free extract, energy value,

acetic acid, citric acid, oxalic acid, tartaric acid, copper, iron, zinc, manganese, calcium,

sodium and potassium. The second principal component axis weighed strong saponins,

flavinoids, phenol and vitamin B3 while tannins content had strong loadings in the third

principal component axis. All variables in component 4, 5, 6 and 7 explained weak and

moderate loadings. It can be seen that as these correlations become weak as the number

of principal component increases.

160

Table 51. Analysis of component score coefficient matrix

Parameters Component

1 2 3 4 5 6 7

Moisture -0.97 -0.007 0.173 -0.013 0.09 0.05 -0.01

Total solid 0.97 0.007 -0.173 0.013 -0.09 -0.05 0.01

Ash 0.94 -0.04 0.181 0.154 -0.07 0.006 0.03

pH -0.14 0.24 0.624 0.032 -0.09 0.28 -0.60

Total soluble solids 0.65 0.04 0.106 0.146 -0.13 0.31 0.55

Fiber 0.84 -0.01 -0.118 0.026 -0.08 -0.16 0.16

Fat 0.09 -0.25 -0.514 0.305 0.56 0.38 0.20

Total fatty acids -0.02 -0.11 -0.422 0.223 0.69 0.41 -0.13

Protein 0.24 0.28 -0.544 0.656 -0.004 0.11 0.06

Carbohydrate 0.95 0.01 -0.181 -0.060 -0.12 -0.06 -0.02

Nitrogen free extract 0.94 0.02 -0.185 -0.072 -0.12 -0.04 -0.05

Energy value 0.95 -0.002 -0.253 -0.002 -0.05 -0.01 -0.00

Acetic acid 0.93 -0.03 -0.098 -0.135 -0.20 0.06 -0.06

Citric acid 0.93 -0.03 -0.098 -0.135 -0.20 0.06 -0.06

Oxalic acid 0.93 -0.03 -0.098 -0.135 -0.20 0.06 -0.06

Tartaric acid 0.93 -0.03 -0.098 -0.135 -0.20 0.06 -0.06

Copper 0.79 0.09 0.311 -0.206 0.36 0.13 -0.17

Iron 0.82 -0.14 0.433 -0.059 0.30 -0.007 -0.07

Zinc 0.88 0.03 0.228 0.297 0.17 0.08 -0.06

Manganese 0.81 -0.08 0.417 -0.031 0.36 -0.03 -0.06

Calcium 0.86 0.11 0.045 -0.133 0.33 -0.25 0.00

Magnesium 0.51 -0.35 0.399 0.558 0.02 -0.23 0.13

Sodium 0.96 -0.007 -0.162 -0.033 0.001 0.06 -0.06

Potassium 0.96 -0.008 -0.140 -0.069 0.05 0.06 -0.12

Alkaloids 0.12 -0.08 0.716 0.630 0.05 -0.11 0.02

Saponins 0.05 0.89 -0.129 0.295 0.12 -0.19 -0.08

Flavinoids 0.04 0.91 -0.034 0.332 0.02 -0.19 -0.03

Phenol 0.00 0.87 -0.433 0.111 0.02 -0.11 -0.09

Tanins 0.22 0.48 0.767 0.076 0.09 0.02 0.16

Vitamin A 0.04 0.11 0.421 -0.717 0.05 0.35 0.28

Vitamin C 0.03 0.42 0.491 0.393 -0.33 0.51 0.06

Vitamin B1 -0.05 0.74 -0.243 -0.056 -0.31 0.45 -0.05

Vitamin B2 0.04 0.69 -0.033 -0.545 0.40 -0.04 0.03

Vitamin B3 0.09 0.79 0.217 -0.269 0.14 -0.21 0.31

161

Component correlation analysis

Correlation coefficients between the seven components of the PCA are

shown in the Table 52. It could be observed from this table that mostly correlation

between any two components is very weak and even for some components these values

are found fairly close to zero which show that components are uncorrelated. The

uncorelatedness of components is one of the basic assumptions of PCA. There are

negative correlations between component-II and component-III. Likewise, component-I

is negatively correlated with component-VI and VII. The observed correlation of

component-II with components III, V and VII is nearly 0. Among all the observed

correlations, the highest value was reported between component-I and component-III.

Table 52. Component correlation matrix

Components 1 2 3 4 5 6 7

1 1

2 0.07 1

3 0.27 -0.04 1

4 0.19 0.17 0.23 1

5 0.20 0.06 0.17 0.004 1

6 -0.07 0.15 -0.13 -0.22 -0.18 1

7 -0.09 0.03 0.21 0.25 -0.05 -0.18 1

162

3D component plot

The following figure shows the 3D plot of components in rotated space. It

can be inferred from the Figure 51 that three variables that had high loading were

assumed to belong with component-I i.e., alkaloid, moisture and vitamin C. It can be seen

that most of the variables (29) belong to component-II with the exception of TSS and

vitamin A which belong to component-III.

Figure 51. 3D component plot of the nutritional data of selected vegetables

163

CHAPTER-V

DISCUSSION

The consumption of nontraditional vegetables in the form of food was

investigated in three locations of district Mirpurkhas and studied the nutritional

composition of selected wildly grown nontraditional and commercial vegetables after

subjecting to boiling, cooking curry, shade drying and thermal dehydration treatments in

order to know the effect of processing on the nutrient content of vegetables as compared

to raw (uncooked). The results obtained are discussed in the following sections:

Perception of non-traditional vegetable use by selected respondents

Percent frequency data in Table 6 (Figure 4) shows respondent’s

perception about utilization of nontraditional leafy vegetables. It has been observed from

the survey that gram leaves were the most popular non-traditional vegetable eaten

frequent or occasionally by 82% respondents only 18% respondents never tasted or do

not know this vegetable. Next popular vegetables which majority of respondent never

tasted or did not know included amaranthus and lambs quarter. About 62% respondents

never tasted or do not know horse radish tree flowers as vegetable while 38% respondents

answered they eat frequent or occasionally.

The survey was meant to highlight the abundant nontraditional

underutilized vegetables in Sindh province of Pakistan and its environments and also to

164

serve as a tool for alleviating the difficulty in getting these nontraditional vegetables for

their required usage. In addition, the survey was also for the transfer of knowledge on

food security, health and poverty alleviation, as nontraditional vegetables play a crucial

role in food security due to high nutritional value of urban and rural communities

(Seema, 2015). These nontraditional vegetables are also valuable sources of energy and

micronutrients in the diets of the communities (Grivetti and Ogle, 2000). Further, they

serve as income sources to the small farmers and may be marketed locally, provincially

and even globally (Hoeschle-Zeledon and Bordoni, 2003). The range of these species

covered is wide, including plants that provide stimulants, spices, medicines, fibers,

tubers, roots, oils, nuts, leaves, grains and fruits (Sheikh and Javed, 2007). Some of these

species might be broadly distributed all around, however are confined to a more local

production and consumption. Many nontraditional vegetables are grown for oil, grain,

fiber, food and as source of medicine play a major role in the subsistence of local people

and frequently are of special medicinal, cultural and social value (Jain and Gupta, 2013).

Nontraditional vegetables typically do not meet modern standards for

uniformity and other characteristics as they have been neglected by breeders from the

private, public sectors (Stamp et al., 2012) and less competitive in marketplace compared

with commercial crops (Jackson et al., 2007; Frison et al., 2011; McCouch, 2013). Apart

from their medicinal, cultural and commercial value, nontraditional vegetables are also

considered significant for sustainable food production as they decrease the influence of

production systems on the environment (De-la-Pena et al., 2011; Hughes and Ebert,

2013). These plants can be incorporated in commercial crop plants in future and will tend

165

to minimize food scarcity as well as economy in tribal areas for their livelihood and help

in regeneration of barren lands. These plants can be incorporated in commercial crop

plants in future and will tend to minimize food scarcity as well as economy in tribal areas

for their livelihood and help in regeneration of barren lands (Bello et al., 2015).

Effect of processing methods on nutritional composition of vegetables

The proximate composition of fresh, thermally dehydrated, curry, shade

dried and boiled amaranthus, gram leaves, horse radish tree flowers and spinach using

different methods revealed variations in the composition (Table 7-12, Figure 5-10). The

overall results differed for each processing treatment. It was observed that moisture

content was maximum in boiled samples of spinach, horse radish tree flowers, lambs

quarter, gram leaves and amaranthus (92.66, 87.26, 85.46, 84.13 and 83.05%). However,

in fresh samples the maximum moisture ontent was found in spinach followed by lambs

quarter, gram leaves, amaranthus and hors radish tree flowers (88.76, 84.08, 82.28, 81.96

and 80.98%) and minimum moisture was observed in thermally dehydrated samples

(Table 5, Figure 4). The spinach vegetable was recorded with highest moisture content

which means that spinach is highly perishable which cannot be stored for long time

duration. Generally, variations observed in proximate composition could be caused by

variations in the used ingredients or preparation methods (Al-Faris, 2017).

The present results are in agreement with the results of Satter et al. (2016)

who reported the moisture contents of the nontraditional vegetables like Dhekishak,

166

Helencha, Kalmishak, Patshak and Shapla stem to be 90.37, 87.60, 90.12, 86.81 and

94.36%, respectively. These results were very close to the moisture contents of some wild

edible and commonly used vegetables in Pakistan (Imran et al., 2007; Hussain et al.,

2011). Hussain et al. (2010) also stated that moisture contents varied in different wild

vegetables investigated by them. Hanif et al. (2006) and Das et al. (2009) concluded that

green leafy vegetables had higher moisture content and were in line with the findings of

Saidu and Jideobi (2009) who recorded highest moisture contents at reproductive stages

in leaves. Hussain et al. (2009b) also reported high moisture contents in Allium sativum

(67.66 %) and Valeriana officinalis (6.82 %) which were lower than observed in the

findings. Adnan et al. (2010) reported high moisture contents in Bupleurum falcatum,

Forsskalea tenacissima, Lavendula angustifolia, Valeriana officinalis and Otostegia

limbata and their results are in conformity with the present results. According to AOAC

(1995) low moisture content signifies high food value. The high moisture levels in the

polluted vegetables suggest that the vegetables analyzed may not be stored for a long

time due to high water activity (Gbadamosi, 2011). Water also provide medium for

water-soluble enzymes and co-enzymes required during metabolism of vegetables

(Ihenacho, 2009). However, increased moisture may add and cause quality deterioration

as the samples studied may be prone to bacterial attack during storage (Onyeike et al.,

2003). It has also been reported which microorganisms that cause spoilage are known to

thrive in foods containing high moisture content (Emebu and Anyika, 2011).

Ash content is the index of the total mineral content of any sample. The

nontraditional vegetables represented in Table 8 (Figure 6) contained high amounts of ash

167

that indicated the vegetables were rich in minerals and could provide a considerable

amount of mineral elements in our diet. The ash content (total minerals) in respective

vegetables ranged from 1.227 – 10.56% for amaranthus, 1.187 – 9.507% for lambs

quarter, 1.213 – 10.43% for gram leaves and 0.487 – 16.15% for horse radish tree

flowers. However, the ash content for spinach vegetable was noted 0.507 to 8.680%. The

results of the present study showed that nontraditional vegetables are rich in total mineral

content as compared with commercial vegetable (spinach). In earlier studies, ash content

of nontraditional edible plants has been reported between 0.65 and 26.70% (Demir 2006;

Kagale and Sabale, 2014; Kalita et al., 2014; Tuncturk and Ozgokce, 2015). However,

Roe et al. (2013) reported that the ash content of the wild plants examined were

considerably higher than the commercial vegetables (0.4 - 2.0%). The higher ash content

as compared to commonly available vegetables like lettuce (0.4% DM) and spinach

(0.7% DM) were also reported by Salazar et al. (2006). The high ash content of leaves

may be due to its mineral content (Shukla et al., 2001). Gafar et al. (2011) reported the

ash content of chancapiedra plant to be up-to 5.55% but Nwaogu et al. (2000) revealed

19.61% in Amaranthus hybridus. P. mildbraedii had the highest ash (19.72%) content

(Okon and James, 2015). Orhuamen et al. (2012) found 10.4% for Telfairia occidentalis

while in Talinum triangulare, they reported as ash percentage to be 8.85%.

Protein contents vary according to climatic and habitat conditions

(Cheema et al., 2011). The protein content in Table 9 (Figure 7) was observed greater in

thermally dehydrated gram leaves (7.56%) as compared to other nontraditional

vegetables and in spinach low protein content was observed (1.04% in boiled sample).

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The data of Satter et al. (2016) also showed that the vegetables are rich sources of protein

which can encourage their use in human diets and might be helpful to contain protein

energy malnutrition. As for as crude protein is concerned, Hanif et al. (2006) recorded

0.9% to 2.1 % protein contents in the selected vegetables. Cheema et al. (2011) reported

high concentration of crude protein in leaves of Morus alba, which happened to be best

source of protein in ruminant feeding. They also stated that differences in crude protein

were due to differences of capability of plants to accumulate protein. This is also true in

this study whereby there were differences in amount of protein among the plants.

Yao et al. (2000) also stated that Morus alba is a best source of protein for

ruminants. Adenipekun and Oyetunji (2010) observed little differences between Vigna

unguiculata (23%) and Arachis hypogea (24%) and this agrees with the findings in some

cases, in this study. Hussain et al. (2010) also found that Sonchus asper and Melia

azadrichta had the highest concentration of protein. Barua et al. (2015) observed the

crude protein content of different plant species in descending order in Drymaria cordata

(20.57%) followed by Homalomena aromatica (20.5%), Elsholtzia communis (16.19%),

Zanthoxylum alatum (10.94%), Clerodendrum indicum (7.88%) and Gnetum gnemon

(6.7%). Hussain et al. (2009a) also noted 6.4% protein in ginger. Shah et al. (2009) stated

that protein rich plants had 23- 33% protein, whereas the present investigation reported

moderate level of protein in analyzed nontraditional plants. The results also differ of from

those of other workers (Hameed et al., 2008; Adnan et al., 2010; Hussain et al., 2010). It

was noted that the local nontraditional plant species consumed as leafy vegetables

169

contained significantly higher amounts of protein than the commercially cultivated leafy

vegetables (Geeta and Sharma, 2015).

Umar et al. (2007) reported protein content of water spinach up to 6.30 %.

Van Wyk (2005) and Odhav et al. (2007) determined the values of protein for Lambs

quarter (4.4%), Amaranthus hybridus (3.5%) and Galinsoga parviflora (3.29%). The

protein contents of the wild plants in this study are relatively comparable to those

obtained by El-Amier and Ejgholi (2014) on Atriplex halimus (14.79%), Limonium

pruinosum (12.38%) and Limoniastrum monopetalum (14.15%), but lower than values

reported by Zahran and El-Amier (2013) on Bassia indica (9.25%), Arthrocnemum

macrostachyum (5.34%) and Halocnemum strobilaceum (9.44%) and Stanacev et al.

(2010) on Medicago sativa and Trifolium alexandrinum. The presence of high protein

indicates nutritional superiority over other consumable crops (Gopalan et al., 2004). Very

high protein content in nontraditional vegetables indicated that the species can be a very

good source of protein as well (Barua et al., 2015). The high protein content of seeds

makes it a good body building food for growth and repair of worn out cells and tissues

specially in children (Chadare et al., 2009).

Fat in food including essential fatty acids and vitamins is considered as a

main source of energy. The crude fat content of the curry samples of horse radish tree

flowers (3.85%) vegetable was higher than other selected vegetables. While in fresh

samples the fat content was found 2.15, 1.25, 1.60 and 2.40% for amaranthus, lambs

quarter, gram leaves and horse radish tree flowers. The fat content of fresh spinach was

170

recorded 2.35% (Table 10, Figure 8). The fatty acid content was recorded higher in curry

samples of horse radish tree flowers (3.08%) followed by spinach (2.92%), amaranthus

(2.720%), lambs quarter (2.280%) and gram leaves (2.200%). The results revealed that

nontraditional vegetables are rich sources of energy as compared with cultivated

vegetable spinach (Table 45, Figure 38). The values of the present study are much higher

as compared with the fat content (0.21- 0.45%) of some leafy vegetables in Nigeria

(Onwordi et al., 2009) and are similar to the fat content (2.00 and 3.01%) of some wild

vegetables in Nigeria and Pakistan (Nkafamiya et al., 2010; Hussain et al., 2011; Khan et

al., 2013).

Crude fats and oils are the part of a complex organic material that is

soluble in ether. It chiefly consists of fats and fatty acids. It is a measure of the fat or oil

(lipid) of plant which is considered as medicinal or nutritious feed and extremely rich

sources of energy. Oils usually impede microbial fermentation. Ruminant diets usually

contain to about 4% fat. The results of this study are in line with Coskun et al. (2004),

Cherney and Cherney (2005) and Hussain and Durrani (2009). Ayuba et al. (2011) who

reported crude lipid content as 6% in roots and 15.52% in the seed of Datura innoxia, as

in the present study. The low level of fats contents may be of benefit to individuals

suffering from hyper lipidaemia because of the role of fat in potentiating risk of

developing certain kinds of cancer, heart disease and diseases associated with damage of

coronary artery (Onunogbu, 2002). Fat also is major determinant of palatability of food

(Antia et al., 2006). The leaves of Leptadenia hastata contain 5.0% crude fat

(Yirankinyuki et al., 2015) which is the same with that of Indigofera astragalina (Gafar

171

et al., 2011). The crude fat content ranges in plants in between 0.31- 1.27% and crude

fiber 7.31- 20.0%. Presence of low fat can be recommended for individuals suffering

from obesity (Barua et al., 2015).

Vegetables are also rich sources of fiber which is an important component

in preventing overweight, constipation, diabetes, increase of serum cholesterol, risk of

heart diseases, breast/colon cancers and hypertension, etc. (Koca et al., 2015). The crude

fiber of the nontraditional vegetables represented in Table 11 (Figure 9) was highest in

thermally dried samples of horse radish tree flowers (13.35%) followed by gram leaves

(10.50%), amaranthus (10.383%), lambs quarter (10.15%) and spinach (9.750%).

Whereas, the fiber content in spinach was noted lowest as compared with nontraditional

vegetables. The findings are closely similar to the other nontraditional edible plants and

commonly consumed vegetables in Pakistan (Hussain et al., 2011; Shad et al., 2013).

Fiber is a nutrient of diet that is necessary for digestion and promoting soft stools for

effective elimination (Vadivel and Janardhanan, 2005). The content of fiber in the wild

vegetables used in the study can encourage their use in the human diet to fulfill the RDA

of fiber. The crude fiber is the organic residue remaining after digestion with acid and

base residues. The fibrous elements are an important constituent of balanced diet that

decreases blood cholesterol level, heart risks, colon cancer and diabetes (Ishida et al.,

2000). Belewu and Babalola (2009) stated that crude fibers can be used for useful

purposes if treated with microorganisms.

172

Hussain et al. (2010) estimated fibers varied from 9.5 to 12.12% in

selected nontraditional plants. This range is similar to the findings in this study. Hameed

et al. (2008) reported moisture, ash, crude fiber, proteins, fats and oils, and carbohydrates

contents in Rumex hastatus, R. dentatus and R. nepalensis (Polygonaceae). Their findings

also support the findings in the study. Aberoumand (2012) reported that Solanum indicum

contained 8.00% crude fiber showing the variation from the present study which may

have been due to different soil and environmental factors. Fiber is known to decrease the

risk of obesity (Maki et al., 2012) and plays an important role in the body, to help

maintain a healthy digestive tract, remove potential carcinogens from the body and keep

blood sugar levels under control (Emebu and Anyika, 2011). The crude fiber content of

9.33% obtained by Yirankinyuki et al. (2015) were higher than 2.67 % in Indigofera

astragalina (Gafar et al., 2011) and lower (13 %) in Tribulus terrestris leaves and 29.00

% in Balsam apple leaves (Hassan and Umar, 2006).

The value was within the range of 0.70- 12.0 % for most leafy vegetables

except Balsam leaves (Gafar et al., 2011). The presence of high crude fiber in food

material is reported to decrease dry matter digestibility in animals. Fiber is useful for

maintaining bulk, motility, increase intestinal peristaltic movement and prevent colon

cancer (Omale et al., 2010). There is a variation in the value of crude fiber and it range

from 7.31% (E. communis) to 20% (H. aromatica) which is much higher than the

reported value (8.54%) in H. aromatica (Seal and Chaudhuri, 2015). Barua et al. (2015)

stated that there may be a variety of many reasons for such changes due to climate, soil

173

composition and season of collection as the samples were usually collected during winter

season when the fiber content was very high.

Carbohydrates are the principal source of energy. The carbohydrate

content was found highest in shade dried sample of lambs quarter (68.62%) as compared

to other vegetables (Table 12, Figure 10). While, the spinach vegetable was noted with

lower carbohydrate values as compared with nontraditional vegetables. Imran et al.

(2007) reported the closely related results of some wild edible leaves such as spinach,

sweet potato and triden which were 54.20, 75.00 and 82.80%, respectively. On the other

hand, the results were considerably higher than the reported values when compared to

some nontraditional edible plants (3%) of Pakistan (Khan et al., 2013) and commonly

consumed vegetables (29.40 - 32.80%) in Nigeria (Onwordi et al., 2009). Due to the

carbohydrate content, the vegetables can be a good food source of carbohydrate for

human consumption. Carbohydrate is a group of organic compounds that includes sugars,

starches, cellulose, and gums. It serves as a major energy source in the diet of humans

and animals. These compounds are produced in the photosynthetic plants and contain

only carbon, hydrogen and oxygen in the ratio of 1:2:1. Carbohydrates perform numerous

important functions in human and animal bodies. Lee and Lim (2006) isolated new

glycoprotein (150 KDa) from Solanum nigrum, which also contained carbohydrate

component (69.74%) and protein content (30.26%).

Audu et al. (2007) reported carbohydrate from leaves of Lophira

lanceolata. Hameed et al. (2008) found carbohydrates contents in R. hastatus, R. dentatus

and R. nepalensis. Folarin and Igbon (2010) noticed carbohydrate from Enterolobium

174

cyclocarpum seed. Aberoumand (2012) also revealed that Solanum indicum contained

40.67% carbohydrate. All these studies are in agreement with the present findings. The

high levels of carbohydrate in nontraditional vegetables indicate that they contribute

significantly to the energy content of the food materials (Sidibe and Williams, 2002;

Yirankinyuki et al., 2015). The most important function of carbohydrates is to fulfil the

body’s energy requirement (Igwe et al., 2015). High content of carbohydrates suggests

the rich source of energy supply and may be a veritable tool for the rural people as a

source of body nourishment (Antia et al., 2006).

The nontraditional vegetables also contain organic acids (e.g. oxalic acid,

citric acid, acetic acid, tartaric acid) in all the selected vegetables (Table 14-17, Figure

11-14) which have ability to prevent or kill microbes in vegetables and fruits (Bari et al.,

2003). Organic acids are primary metabolites known to exhibit antimicrobial, antioxidant,

and anti-tumorous effect and plays important role in plant metabolism as they are

involved in several fundamental pathways (Kathirvel et al., 2014). Organic acids are

mainly used in preparation of juices and beverages as food additives because they greatly

influence the aroma, taste, and color of the food (Kumari et al., 2017). Beside, this, the

identified organic acids also used in food processin and preservation owing to their

antimicrobial, antiviral, and high antioxidant properties (Sivasubramanian and Brindha,

2013).

175

It has been demonstrated that the edible vegetables are capable of

accumulating high levels of minerals from the soil (Cobb et al., 2000). The results of the

present study showed that (Table 19- 26, Figure 15- 22) the thermally dehydrated

samples retained the highest mineral content followed by shade dried, cooked, fresh and

boiled samples. The highest calcium, magnesium, sodium and potassium content were

found in thermally dehydrated samples of lambs quarter (568.8, 108.4, 1211.5 and 1081.4

mg 100g-1

). The copper and zinc were found highest in amarathus (3.026 and 7.240 mg

100g-1

) whereas the fe and manganese contents were maximum in gram leaves (4.810 and

1.950 mg 100g-1

). The lower values of mineral content of spinach vegetable were

recorded when comparing with nontraditional vegetables. Horo and Topno (2015)

reported that the nontraditional leafy vegetables are delicious, refreshing and rich in

minerals.

The copper content was recorded greater in thermally dehydrated sample

of amaranthus that is up to 3.026 mg 100 g-1

. The present results are also in line with

Gupta et al. (2005) who recorded the highest amount of copper content in some wild

vegetable Cocculus hirsutus, Boerhaavia diffusa, Centella asiatica and Delonix elata and

lowest in Amaranthus tricolor and Commelina benghalensis.

Iron content of the fresh samples of studied nontraditional wild vegetables

compared favorably to most of the results reported from other studies that the range of fe

content was recorded from 6.97 to 22.73 mg 100g-1

for some wild green leafy vegetables

in North-East India and from 21.30 to 33.40 mg 100g-1

for some commonly and wildly

grown and consumed leafy vegetables in Kano, Nigeria (Saikia and Deka, 2013).

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Consumption of these nontraditional vegetables may help to overcome iron deficiency

anemia.

Zn as an integral part of many enzymes in human body plays catalytic,

structural and regulatory roles. It is essential for normal growth, mental ability, immune

system, reproduction and healthy function of the heart (Afolayan and Jimoh, 2009). The

zinc content of fresh Amaranthus (4.66 mg 100 g-1

) in present study compares favorably

to Dhekishak (2.29 mg 100 g-1

) as reported by Satter et al. (2016).

The highest Mn value was found in the dried leaves of gram leaves (1.950

mg 100g-1

). This element plays a significant role in the metabolism of fat, carbohydrate

and protein and boost the production of steroid sexual hormones (Saikia and Deka, 2013).

The result of mineral analysis reveals that the leaves of lambs quarter

contain high amount of calcium content (568.8 mg 100 g-1) in thermally dried sample.

The results are in agreement with the Gupta et al. (2005) who reported that the

Amaranthus tricolor, Cucurbita maxima, Boerhaavia diffusa and Digera arvensis had

high content of calcium content of 239, 302, 330 and 506 mg 100 g-1

, respectively.

Calcium has various functions in the body as it is present in extracellular fluid, blood and

bone in large proportions and also regulates normal functioning of cell permeability, milk

clotting, blood coagulation and cardiac muscles (Indrayan et al., 2005).

Magnesium is a mineral element important for circulatory diseases like

metabolism of calcium in bones and ischemic heart disease (Hassan and Umar, 2006).

177

The magnesium content was found highest in Lambs quarter (108.4 mg 100-1

) followed

by Amaranthus (101.3 mg 100-1

), gram leaves (77.45 mg 100-1

), horse radish tree flowers

(61.81 mg 100-1

) and spinach (50.16 mg 100-1

) treated with thermal dehydration. It has

also reported that Mg in some wild plants Echinops giganteus, Capsicum frutescens,

Piper guineense and Piper umbellatum of Cameroon was found 89, 254, 296 and 490 mg

100g-1

, respectively (Bouba et al., 2012). Magnesium plays major function in maintaining

the normal functioning of muscle and nerve, support healthy immune system and control

blood glucose levels (Saikia and Deka, 2013).

Noteworthy sodium concentration was recorded 491.6, 511.6, 499.6, 401.6

and 501.6 mg 100g-1

in fresh leaves of amaranthus, lambs quarter, gram leaves, horse

radish tree flowers and spinach are very much compared with the values observed by

Odhav et al. (2007) in the leaves of Oxygonum sinuatum (1460 mg 100g-1

) while C.

asiatica (16 mg 100g-1

) contained the lowest amount. Hence, the consumption of these

vegetables may control the high blood pressure. The potassium (828.54 mg 100 g-1

) in

fresh sample of Lambs quarter in the present study was higher than 14.55 mg 100 g-1

found in Indigofera astragelina leaves (Gafar et al., 2011) and also that of

Mucunasloanei. Similarly, Seal et al. (2017) also reported that the P. acinosa leaves had

highest potassium content (75.72 mg g-1

) and minimum in M. khasianus fruit (13.74 mg

g-1

). Potassium has diuretic nature and Na helps in transport of metabolites. The Na/K

ratio helps in preventing high blood pressure in human body (Saupi et al., 2009).

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The recorded difference is may be due to variation in agronomic, climatic,

seasonal, and genetic background. Regular intake of these nontraditional vegetables may

help in inhibiting cardiovascular and hypertension diseases (He and MacGregor, 2008).

Sun drying is the gradual loss of water through evaporation and cannot

support leaching. It has to be noted that minerals are not volatile (Hailu and Addis, 2016).

The statistically significant ( < 0.05) reduction of iron and zinc concentration upon

cooking and peeling of the tuber may be because of the presence of minerals in the outer

non edible part of the tuber which was removed by peeling after boiling the tuber (Hailu

and Addis, 2016). The same reason may apply to the minerals which showed enormous

reduction in the boiled and peeled D. abyssinica. Reduction in zinc content was also

reported in peeled and boiled tubers of Dioscorea cayenensis (Akin-Idowu et al., 2009).

The presence of phytochemicals is an indication that the leaves could be

used for medicinal purposes (Offor et al., 2017). The medicinal relevancy of these leafy

vegetables is manifested in their usage by local people in the preparation of pot herb for

curing of various ailments (Olujobi, 2015). Table 28- 32 (Figure 23- 27) shows the

presence of phytochemicals (alkaloids, saponins, flavonoids, phenols and tanins) in

amaranthus, lambs quarter, gram leaves and horse radish tree flowers vegetables.

However, spinach vegetable was detected with only three phytochemicals namely,

flavonoids, phenols and tanins. This assertion is in consonance with the opinion of Musa

et al. (2000), who noted that extract from Acalypha species could be used as anti-biotics.

Saponin has been reported to suppress cholesterol build up in the body, while tannin has

been used in the treatment of common pathogenic strains in the body (Kubmarawa et al.,

179

2007). Though, phytate have been implicated with some nutritional diseases such as bio-

availability of mineral elements, and inhibitions of some metabolic activities, the values

obtained in this study were below the established toxic level of 6% (Sobowale et al.,

2011).

Phytochemicals are natural bioactive compounds found in plants that work

in close association with nutrients and dietary fiber for disease protection (Oteng-Gang

and Mbachu, 1990). Tannins are regarded as agents for toning of vital organs such as

kidney and liver. The phytochemical composition determines the medicinal values of

these edible nontraditional vegetables and also could serve as a starting material for the

synthesis of new drugs in pharmaceutical industries (Okerulu and Onyema, 2015). Plant

tannins have a variety of health benefits and intake of tannin containing diet could help in

good health maintenance. Tannins are a unique phytochemical, particularly in terms of

their vast potential health benefit. Analysis of tannins composition in different plant

foods including ethnic plant foods would encourage their consumption for maintenance

of good health (Tuli et al., 2017).

Each of these phytochemicals is known for various protective and

therapeutic effects (Asaolu et al., 2009). Tannins impose an astringent taste in foods

thereby affecting palatability (Ogbede et al., 2015). However, tannin compounds have

been reported to possess antibacterial (Akiyama et al., 2001), antiviral and antiparasitic

effects (Kolodziej et al., 2005). The phenolic content of these nontraditional vegetables

was significantly higher in comparison to Brassica juncea, the commercialized vegetable

180

(Ng et al., 2012). The results are also relatively higher than the commonly consumed

food plants from India (0.0-1.2 mg GAE/g raw foodstuff) as reported by Saxena et al.

(2007). Phenolics are nonnutritive secondary metabolites found in plants that promote

significant health benefit and prevent various diseases. Study by Stagos et al. (2012) and

Delgado et al. (2009) stated that phenolic compunds can prevent cardiac and

neurodegerative diseases.

The total flavinoid content of the studied plants is comparable to some of

the medicinal plants (1.6-13.12 mg RE/g DW) and vegetables (0.9- 4.9 mg RE/g DW)

reported in the previous studies (Djeridane et al., 2006). Oxalates are known to combine

with and isolate some useful metallic elements thus causing them to be deposited in solid

forms. This, in effect, makes them unavailable for adsorption in human system (Alamu et

al., 2013). The oxalate contents were 1.31± 0.020 and 0.36± 0.02%, while the tannin

values were 0.04± 0.00 and 0.03± 0.00% respectively. The saponin contents the other

hand were 2.53± 0.02 and 1.13± 0.00% (Ndamitso et al., 2015). Alkaloids have immense

physiological activities in the living systems hence they are widely used in medicine

(Olaofe and Sanni, 2007).

The alkaloid contents of these samples were 0.65±0.02 and 0.68±0.02%

for the leaves and stems respectively (Olaofe and Sanni, 2007). The respective flavonoid

contents of the samples were 0.52± 0.03 and 0.34± 0.02% for the leaves and stems

respectively (Ndamitso et al., 2015). However, anti-nutritional factors encountered in

fruits, vegetables and grains which do not have nutritional values but they do affect

181

various body processes and reduce the risk of many diseases such as cancer, heart

diseases, stroke, high blood pressure, cataracts and urinary tract infection (Okwu and

Ndu, 2006). Appropriate processing methods are known to reduce the antinutritional

activity of these factors (Hailu and Addis, 2016). According to Yadav and Sehgal (2003),

the oxalate content was equal to 3.05 mg 100g-1

, value lower than that is reported (14.9 g

100g-1

) in common green leafy vegetable spinach (Spinacia oleracia).

The value obtained for vitamins from the amaranthus, lambs quarter, gram

leaves and horse radish tree flowers and spinach vegetables in fresh, thermally

dehydrated, curry, shade dried and boiled samples (Table 34- 38, Figure 28- 32) revealed

that the nontraditional and commercial vegetables have almost similar pattern of vitamin

content and are rich in vitamins and the values shows a close agreement with those

obtained by Adeniyi et al. (2011). In some selected leafy vegetables, vitamins B1, B2 and

B3, have been reported to be highly essential for micronutrient metabolism whereas

vitamin C is used for protein metabolism and collagen synthesis (Vunchi et al., 2011).

Vitamin A and beta-carotene are essential for good vision (Adeyeye, 2014). Results

available reviewed and current study demonstrated that the wild species contained

valuable amount of vitamins such as riboflavin and ascorbic acid (Ng et al., 2012). The

riboflavin content was the highest in Limnophila aromaticoides (13.7 μg g-1

FW)

followed by Crassocephalum crepidioides (12.4 μg g-1

FW) and were of the same

magnitude as that generally found in dairy product. Therefore, daily consumption of these

vegetables might help to alleviate riboflavin deficiency, which gives negative impact on

the metabolism of other nutrients, especially B-group vitamins, through flavin coenzyme

182

activity. The sufficient intake of riboflavin on the other hand had proven to have

protective effect against proximal colon cancer (De-Vogel et al., 2008).

The amount of thiamine in Limnophila aromaticoides (16.6 μg g-1

FW),

Ceratopetris thalictroides (9.0 μg g-1

FW) and Etlingera elatoir (3.24 μg g-1

FW) were

high as compared to the uncommon vegetables studied by Raghuvanshi et al. (2001).

Nevertheless, plants or vegetables usually contain great amount of heat-stable anti-

thiamine compounds such as tannic acid and thiaminase I, which usually affect the

bioavailability of thiamine in plants (Lonsdale, 2006). According to the findings of Lui et

al. (2008), high concentration of ascorbic acid in plant samples might be associated with

attractive free radical scavenging capacity and health benefit like anti-carcinogenic and

anti-atherogenic.

The β-carotene content of the indigenous vegetables in this study were 2-

5 times lower than that of other vegetables, such as carrots (Daucus carota; 18,300 g

100g-1

), sweet potato (Ipomea batatas; 9500 g 100g-1

), and pumpkin (Cucurbita maxima;

6900 g 100g-1

). All of these vegetable varieties are excellent sources of β-carotene

(Krinsky and Johnson, 2005). The vitamin acts as an antioxidant to prevent free radicals

from damaging tissues and to inhibit LDL oxidation that can lead to atherosclerosis

(Osganian et al., 2003). Because humans are incapable of synthesizing vitamin C due to

the absence of L. gluconolactone oxidase, this vitamin must be obtained from the diet

(Kongkachuichai et al., 2015) with cashew apple pulp (ripe) and Spanish joint fir having

the highest quantities and the lowest content in turmeric. Puwastein et al. (1999) reported

183

that vegetables including horse radish tree (Moringa oleifera; 239 mg 100g-1

), green chili

pepper (Capsicum annuum; 175 mg 100g-1

), coriander (Coriandrum sativum; 127 mg

100g-1

), and kale (Brassica oleracea; 117 mg 100g-1

) had equivalent or higher amounts of

vitamin C.

The total solids were highest in thermally dehydrated samples of all the

vegetables than other treatments (Table 40, Figure 33). The total soluble solids in Table

41 (Figure 34) were observed highest in thermally dried sample of gram leaves (2.680

°Brix).

The results of the present study revealed that the nontraditional vegetables

have the potential to provide essential nutrients needed in human diet for maintaining the

normal body function. Table 42 (Figure 35) shows that amaranthus had maximum energy

value (271.6 Kcal 100g-1

) than spinach (269.8 Kcal 100g-1

), lambs quarter (268.7 Kcal

100g-1

), gram leaves (269.0 Kcal 100g-1

) and horse radish tree flowers (249.0 Kcal 100g-

1). Hussain et al. (2011), Mohammed and Sharif (2011), Khan et al. (2013) reported that

the nontraditional vegetables were a good nutritional source and in some cases, they were

better than those of some organized green cultivated vegetables. Thus, they are capable of

providing energy to the consumer and sufficient to fulfill the RDA by FAO/WHO (Satter

et al., 2016). The caloric values recorded in this study ranged between 246.39 Kcal to

313.94 Kcal with U. urens having the lowest.

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Nonetheless, these three vegetable species can be considered a good

source of energy for both human and livestock whosoever has access to eat. These values

compared favorably with 285.02 Kcal and 260.93 Kcal reported for Argemone

subfusiformis and U. urens, respectively (Jimoh et al., 2010). Leptadenia hastata leaves

provided 286.32 Kcal of energy on dry weight basis which is within the range of 248.8-

307.1 Kcal 100g-1

reported in some Nigerian leafy vegetables (Isong et al., 1999). It

therefore, suggests that Leptadenia hastata can serve as a good source of energy

supplement for the body (Yirankinyuki et al., 2015). Chionyedua et al. (2009) reported

the energy values of C. olitorius (177.55 Kcal 100g-1

), A. cruentus (176.67 Kcal 100g-1

)

and C. argenta (174.93 Kcal 100g-1

). The energy value of plant tubers was estimated

within the range of 272.4- 266.04 Kcal 100g-1

(Deshmukh and Rathod, 2013). Senna

occidentalis and Wahlenbergia undulata yielded the highest energy levels of 84 and 75

Kcal 100g-1

, respectively. These results also indicate that 50% of the vegetables have

significant energy values ranging from 50 to 70 Kcal 100g-1

(Odhav et al., 2007).

The pH content was found highest in boiled, curry and fresh samples of

lambs quarter (7.446, 7.373 and 7.260, respectively) as compared to other vegetables

(Table 43, Figure 36). Ndamitso et al. (2015) studied the pH value of leaves and stems of

Ipomoea Aquatic (water spinach) and noted that the respective pH values of 5.83± 0.015

and 5.80± 0.020 for the leaves and stems were relatively the same indicating that both

parts of the plant were only slightly acidic in nature.

185

Chlorophyll is a natural dye derived from green plants and it absorbs

energy from the sun that is used to synthesize carbohydrates from CO2 via photosynthesis

(Raven et al., 2005). The higher plants in their chloroplast contain two types of

chlorophyll i.e. chlorophyll a (blue-green) and chlorophyll b (yellow-green), which differ

in the substituent of a pyrrole ring II. In addition, it’s photosynthetic role it has other

applications and is used as a natural pigment in food and cosmetics (Humphery, 2004).

The results of the a, b and total chorophyll (Table 47, Figure 39) revealed that lambs

quarter had the highest total chlorophyll content (3.199 mg g-1

) followed by spinach

(1.888 mg g-1

), amaranthus (1.850 mg g-1

), gram leaves (1.504 mg g-1

) and horse radish

tree flowers (0.048 mg g-1

).

The leaf chlorophyll content provides important information about growth,

production, physiological status of the plant and ensure the quality of of crop and yield

(Menesatti et al., 2010; Riccardi et al., 2014; Zhang et al., 2016). This practice has an

important significance for the modern precision agriculture (Zhang et al., 2016). The

content of pigments in plants is important, not only for coloration and physiological

function, but also because of their acknowledged roles in health (Niizu and Rodriguez-

Amaya 2005; Liu et al. 2007,). Highest total chlorophyll was found in Rumex nepalensis

(1.58 mg g-1

), followed by Justicia adhatoda (1.53 mg g-1

) while the lowest total

chlorophyll content was recorded in Basella rubra (0.57 mg g-1

). The total chlorophyll

was also found to be high in Passiflora edulis (1.39 mg g-1

), Spilanthes acemella (1.37

mg g-1

), Piper longum (1.21 mg g-1

) and Amaranthus viridis (1.20 mg g-1

) (Buragohain et

al., 2013).

186

Sensory evaluation of cooked and uncooked vegetables

The desireability of any food product is depend on its quality which can be

determined by objective and sensory methodologies. The psychometric, sensory,

organoleptic and subjective tests are taken by human organs to check the quality of food

(Srilakshmi, 1996). Sensory analysis of food relies upon evaluation through the use of

our senses (odor, taste, tactile, temperature, etc.). Only by applying exact scientific

testing methods can lead to reproducible results. Scientific methods of sensory analysis of

foods are becoming increasingly important in assessing the acceptability of food products

(Jellinek, 1985). According to Vaid (2008) that sensory quality is composed of various

wisdoms of sensitivity during selecting and eating a food. Physical appearance, mouth

feel and flavor decide the recognition of food. By using senses (odour, taste, tactile,

temperature, etc.) sensory analysis of a food could be carried out. However, statistical

analysis and reproducible results could be obtained only by applying exact scientific

testing methods.


in present study revealed that all samples had good taste (Table 48 and 49, Figure 40-

49). In uncooked samples horse radish tree flowers obtained highest scores in appearance,

color, odor, texture, taste, overall acceptability and purchase i.e. 4.90, 4.70, 4.00, 3.90,

3.50, 3.80 and 3.80, respectively. While in traditionally cooked samples cooked lambs

quarter and gram leaves retained original color and thus obtained the highest scores in

appearance and taste i.e. 3.70, 3.90 and 3.70, 3.50, respectively. The lambs quarter

187

vegetable retained pleasant odor with the score of 3.50, as compared with horse radish

tree flowers, gram leaves, amaranthus and spinach (3.30, 3.20, 3.10 and 3.10,

respectively). Acceptability study by hedonic scoring showed that nontraditional

vegetables (horse radish tree flowers, lambs quarter, gram leaves and amaranthus) made

by traditional cooking were most acceptable as compared with commercial vegetable

(spinach).

The findings of the present study are in line with the study of

Umuhozariho et al. (2013), who carried out sensory evaluation of cooked cassava

species. According to them cassava species do not considerably effect aroma, colour and

taste. Similar results were obtained by Tarkergari et al. (2013) who found significant

differences in a few of the recipes fortified with purslane that of control. Ward et al.

(2009) based on selective chemical and physical properties studied patties containing 5

and 10% purslane for sensory evaluation for colour, juiciness tenderness texture and

flavour and rated 5% incorporation to be significantly better than 10% incorporation. It

has been experienced that only those foods are acceptable to the human palate, which are

cooked properly and the criterion of the desirability of any food product depends on its

ultimate quality. The quality of a food could be assessed by sensory and scientific

methods.

188

CHAPTER-VI

SUMMARY

The present study was conducted to observe the impact of traditional

processing methods on nutritional composition and bioactive constituents of non-

traditional (lambs quarter, amaranthus, gram leaves and horse radish tree flowers) and

commercial (spinach) vegetables of Sindh, Pakistan. The nutritional values of

nontraditional vegetables were also compared with the standard vegetable spinach. The

findings of the study are summarized as under:

Nontraditional vegetables play a vital role in the diet of the people

throughout the world. The increasing populations of the world coupled with urbanization

have increased food demands and have not only increased overwhelmed pressure on

available land resources for more productivity but have also accentuated the post-harvest

losses. This has also created a demand for better and increased yields of vegetables, their

appropriate storage and preservation. But due to lack of adequate resource availability

ultimately leads to malnutrition caused by insufficient nutrients which are needed to

maintain healthy body/ functional ability. There is great potential for a number of

currently nontraditional vegetables to play a major role in a more diversified and

sustainable food production system. It has been observed from the survey that Gram

leaves was the most popular non-traditional vegetable eaten frequent or occasionally by

82% respondents only 18% respondents never tasted or do not know this vegetable. Next

popular vegetables which majority of respondent never tasted or did not know included

amaranthus and lambs quarter. About 62% respondents never tasted or do not know

189

Horse radish tree flowers as vegetable while 38% respondents answered they eat frequent

or occasionally.

The nontraditional namely, lambs quarter, horse radish tree flowers, gram

leaves, amaranthus and commercial (spinach) vegetables were analyzed for their

nutritive, mineral, vitamin, phytochemical and chlorophyll composition. The results from

nutritional analysis showed that all the nontraditional vegetables used in this study had

low moisture content as compared with spinach. It was observed that moisture content

was high in boiled samples of horse radish tree flowers, lambs quarter, gram leaves and

amaranthus (87.26, 85.46, 84.13 and 83.05%). However, the moisture content in

cultivated spinach vegetable was recorded highest in boiled (92.66%) and fresh (88.76%)

samples which means that spinach is highly perishable which cannot be stored for long

time duration.

The ash content (total minerals) in respective vegetables ranged from

1.227 – 10.56% for amaranthus, 1.187 – 9.507% for lambs quarter, 1.213 – 10.43% for

gram leaves and 0.487 – 16.15% for horse radish tree flowers. However, the ash content

for spinach vegetable was noted 0.507 to 8.680%. The results of the present study

showed that nontraditional vegetables are rich in total mineral content as compared with

commercial vegetable (spinach). The protein content in Table 9 (Figure 7) was observed

greater in thermally dehydrated gram leaves (7.56%) as compared to other nontraditional

vegetables and in spinach low protein content was observed (1.04% in boiled sample).

The crude fat and fatty acid content was recorded highest in curry samples whereas crude

190

fiber was found maximum in thermally dehydrated samples of the selected vegetables.

The carbohydrate content was found highest in shade dried sample of lambs quarter

(68.62%) as compared to other vegetables. The results revealed that nontraditional

vegetables are rich sources of energy as compared with spinach.

The thermally dehydrated samples retained the highest mineral and

organic acid content followed by shade dried, cooked, fresh and boiled samples. The

highest calcium, magnesium, sodium and potassium content were found in thermally

dehydrated samples of lambs quarter (568.8, 108.4, 1211.5 and 1081.4 mg 100g-1

). The

copper and zinc were found highest in amarathus (3.026 and 7.240 mg 100g-1

) whereas

the fe and manganese contents were maximum in gram leaves (4.810 and 1.950 mg 100g-

1). The lower values of mineral content of spinach vegetable were recorded when

comparing with nontraditional vegetables.

The presence of phytochemicals (alkaloids, saponins, flavonoids, phenols

and tanins) in amaranthus, lambs quarter, gram leaves and horse radish tree flowers

vegetables. However, spinach vegetable was detected with only three phytochemicals

namely, flavonoids, phenols and tanins. The presence of phytochemicals is an indication

that the leaves could be used for medicinal purposes. The value obtained for vitamins

from the amaranthus, lambs quarter, gram leaves and horse radish tree flowers and

spinach vegetables in fresh, thermally dehydrated, curry, shade dried and boiled samples

revealed that the nontraditional and commercial vegetables have almost similar pattern of

vitamin content and are rich in vitamins.

191

The total solids were highest in thermally dehydrated samples of all the

vegetables than other treatments. The total soluble solids in were observed highest in

thermally dried sample of gram leaves (2.680 °Brix). The results of the present study

revealed that the nontraditional vegetables have the potential to provide essential

nutrients needed in human diet for maintaining the normal body function. The

amaranthus had maximum energy value (271.6 Kcal 100g-1

) than spinach (269.8 Kcal

100g-1

), lambs quarter (268.7 Kcal 100g-1

), gram leaves (269.0 Kcal 100g-1

) and horse

radish tree flowers (249.0 Kcal 100g-1

). The pH content was found highest in boiled,

curry and fresh samples of lambs quarter (7.446, 7.373 and 7.260, respectively) as

compared to other vegetables.

Ideally, the prevalence of macro and micronutrient related disorders can

be addressed by fortification and supplementation, but this has to be subsidized because it

can be expensive and hence financially inaccessible to the rural population who form the

majority of the macro and micronutrient deficiency victims. Taking into account the

amount of available nutrients and bioactive compounds in the selected nontraditional and

commercial vegetables it was observed that nontraditional vegetables are also valuable

and important contributor to the diets of the people as commercial vegetables and also

these nontraditional vegetables grow without any agricultural input are available at lower

prices affordable to rural masses. Therefore, among alternatives available to meet the

food demands nontraditional vegetables are regarded as cheap source of food for the

marginal communities in Sindh, Pakistan

192


in present study revealed that all samples had good taste. In uncooked samples horse

radish tree flowers obtained highest scores in appearance, color, odor, texture, taste,

overall acceptability and purchase i.e. 4.90, 4.70, 4.00, 3.90, 3.50, 3.80 and 3.80. While

in traditionally cooked samples cooked lambs quarter and gram leaves retained original

color and thus obtained the highest scores in appearance and taste i.e. 3.70, 3.90 and 3.70,

3.50, respectively. Acceptability study by hedonic scoring showed that nontraditional

vegetables (horse radish tree flowers, lambs quarter, and gram leaves and amaranthus)

made by traditional cooking were most acceptable as compared with commercial

vegetable (spinach). Therefore, these nontraditional vegetables can be consumed in

cooked form like other commercial crops. To alleviate the situation, efforts need to be

focused on exploring possibility of the under exploited and lesser known vegetables as a

source of nutrients as food items and supplements.

To epitomize, from the present results and detailed quoted literature it was

observed that assuring food supply to the rural areas, particularly in developing countries

is one of the biggest challenges. Use of nontraditional vegetables is important but ignored

facet for food supply in such areas. The present study revealed that nontraditional

vegetables form good quality food to rural communities thus play important role in

nutritional security to rural areas. However, they need proper focus in policies and

conservation. Perhaps a proper documentation of traditional knowledge related to the

utilization of such resource is an urgent need in Pakistan. Subsequently it is

recommended that, since these nontraditional vegetable species provide food security,

193

thus can play significant role in uplifting socio-economic status of rural people as well as

save the natural habitats. It could be safely said that promoting nontraditional vegetables

would certainly strengthen multifunctional agricultural policies for securing food and

livelihood security and environmental sustainability in urban and peri-urban areas of

Pakistan. Increasing the production of nontraditional vegetables and informing people

how to cook vegetables to gain maximum nutritional value will help ensure low cost

nutrients reach vulnerable populations and enhance food and nutritional security. At the

same time it would also facilitate in sustaining rural landscapes, biodiversity, cultural

heritage and increase life expectancy in Sindh, Pakistan.

194

CHAPTER-VII

CONCLUSIONS AND RECOMMENDATIONS

Conclusions

In conclusion, it was observed that the nontraditional vegetables naturally

grown in district Mirpurkhas of Sindh Pakistan are rich with their nutritive values when

comparing to standard commercial vegetable spinach. These nontraditional vegetables

have higher concentrations of the carbohydrate, protein, fiber, minerals, vitamins,

phytochemicals, greater energy values and lower amount of fat and fatty acids. The

processing treatments showed significant effects on the nutritional values of the selected

vegetables out of which boiling and cooking showed the adverse effects. In sensory

evaluation, the panelists preferred the nontraditional vegetables to commercial vegetable

(spinach).

Moreover, the nutrient and bioactive compounds obtained from selected

nontraditional vegetables studied have high potential to contribute to the nutritional and

health status of local as well as urban communities in Sindh, Pakistan. Their use in the

communities should therefore be promoted. These nontraditional vegetables can be

consumed together with starchy staples as part of a balanced diet and help to alleviate

some nutritional deficiencies.

By studying the bioavailability of the nutrient and minerals content of

nontraditional vegetables together with the optimization of their properties and nutritional

195

values in the daily food of the population will ultimately lead to their higher demand,

wider cultivation and increased supply. The projection of population in Pakistan as

regards life expectancy and food security are quite depressing and challenging aspects of

the moment. Obtaining information and promoting knowledge about high functional

value of selected nutrient rich nontraditional vegetables could potentially address some of

these challenges. Increasing the production of nontraditional vegetables and making the

people aware, how to prepare vegetables to gain maximum nutritional value will help

ensure low cost nutrients availability to reach vulnerable populations to enhance food and

nutritional security as well as life expectancy.

Recommendations

Since the nontraditional vegetables investigated in this study contained

considerable amount of important nutrients it is suggested that:

1) They should be taken as food or added to food as condiments to supplement variety

of nutrients in human diet especially among the rural dwellers with low income.

2) It is also recommended that Government and corporate bodies should embark on

plantation establishment of these species for sustainable production.

3) The study can be extended on more recipes to study the effect of different cooking

methods.

4) In order to expand utilization and conservation of the two indigenous vegetables,

farmers and people at large should be informed about nutritional importance and

health benefits of these nontraditional vegetables.

196

5) The Ministry of Agriculture and partners in the agriculture sector should explore

domestication of these vegetables through agronomic studies.

6) Further research is needed to determine the anti-microbial activities of nontraditional

vegetables to establish medicinal properties of the plant in the treatment of diarrhea/

dysentery and fresh wounds.

7) The optimum conditions and technologies may be established for the retention of

compounds with nutritional value and non-nutrient health promoting benefits in the

nontraditional vegetables.

8) The research and extension services should focus on these nontraditional vegetables

in order to harness their potentials for the enhancement of the livelihoods of farmers

that are dependent on it.

9) Farmers should also organize themselves as niche group for the marketing of

nontraditional vegetables such that they may have better returns.

197

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APPENDICES

Appendix I. Best of fit curve of minerals standards (Calcium, Copper, Iron,

Zinc, Manganese, Magnesium, Sodium and potassium)

229

230

Appendix II. Best of fit curve of vitamin standards (vitamin A (β-carotene),

vitamin C (Ascorbic acid), vitamin B1 (Thiamine), vitamin B2

(Ribofilavin) and vitamin B3 (Niacin))

231

Appendix III. Best of fit curve of chromatograms of vitamin standards

(vitamin B1 (Thiamine), vitamin B2 (Ribofilavin), vitamin B3

(Niacin), vitamin A (β-carotene) and vitamin C (Ascorbic acid)

232

233

234

Appendix IV. Best of fit curve of phytochemical standards (total flavonoids,

total phenols and total tanins)

235

Appendix V. Analysis of variance for moisture content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 2 1.1

Vegetable 4 320 80.1 38.68 0.000

Processing 4 99998 24999.5 12071.7 0.000

Vegetable × Processing 16 261 16.3 7.89 0.000

Error 48 99 2.1

Total 74 100682

CV 2.83

Appendix VI. Analysis of variance for ash content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.10 0.050

Vegetable 4 131.21 30.303 498.77 0.00

Processing 4 1322.50 330.624 5441.88 0.00

Vegetable × Processing 16 114.31 7.144 117.59 0.00

Error 48 2.92 0.061

Total 74 1561.03

CV 4.55

Appendix VII. Analysis of variance for protein content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.029 0.0146

Vegetable 4 99.771 24.9426 243.79 0.000

Processing 4 59.540 14.8851 145.49 0.000


Error 48 4.911 0.1023

Total 74 168.081

CV 7.64

Appendix VIII. Analysis of variance for fat content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.0533 0.02663

Vegetable 4 13.8945 3.47364 23.40 0.000

Processing 4 31.9105 7.97764 53.74 0.000


Error 48 7.1251 0.14844

Total 74 53.7673

CV 17.33

236

Appendix IX. Analysis of variance for fiber content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 2.55 1.277

Vegetable 4 19.31 4.827 7.10 0.000

Processing 4 1111.92 277.980 408.68 0.000


Error 48 32.65 0.680

Total 74 1187.68

CV 14.23

Appendix X. Analysis of variance for carbohydrate content of various vegetables

and processing methods

Source DF SS MS F P

Rep 2 11.9 6.0

Vegetable 4 454.0 113.5 10.67 0.000

Processing 4 57105.5 14276.4 1342.33 0.000


Error 48 510.5 10.6

Total 74 58284.0

CV 10.36

Appendix XI. Analysis of variance for acetic acid of various vegetables and

processing methods Source DF SS MS F P

Rep 2 0.00049 0.00024

Vegetable 4 0.00934 0.00234 24.84 0.00

Processing 4 0.15307 0.03827 407.11 0.00


Error 48 0.00451 0.00009

Total 74 0.16961

CV 15.74

Appendix XII. Analysis of variance for citric acid of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00022 0.00011

Vegetable 4 0.03441 0.00860 82.98 0.000

Processing 4 0.31439 0.07860 758.19 0.000


Error 48 0.00498 0.00010

Total 74 0.37349

CV 12.79

237

Appendix XIII. Analysis of variance for oxalic acid of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00011 0.00006

Vegetable 4 0.00867 0.00217 44.26 0.000

Processing 4 0.04774 0.01194 243.58 0.000


Error 48 0.00235 0.00005

Total 74 0.06399

CV 17.62

Appendix XIV. Analysis of variance for tartaric acid of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00027 0.00014

Vegetable 4 0.05706 0.01427 81.48 0.000

Processing 4 0.40432 0.10108 577.30 0.000


Error 48 0.00840 0.00018

Total 74 0.49215

CV 15.18

Appendix XV. Analysis of variance for copper content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.0119 0.00594

Vegetable 4 17.0266 4.25666 347.88 0.000

Processing 4 16.9338 4.23344 345.98 0.000


Error 48 0.5873 0.01224

Total 74 40.5723

CV 7.50

Appendix XVI. Analysis of variance for iron content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.132 0.0659

Vegetable 4 114.221 28.5553 1164.12 0.000

Processing 4 9.508 2.3770 96.91 0.000


Error 48 1.177 0.0245

Total 74 128.125

CV 6.50

238

Appendix XVII. Analysis of variance for zinc content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.072 0.0362

Vegetable 4 42.949 10.7373 522.16 0.000

Processing 4 194.862 48.7155 2369.03 0.000


Error 48 0.987 0.0206

Total 74 242.380

CV 3.76

Appendix XVIII. Analysis of variance for manganese content of various vegetables


Source DF SS MS F P

Rep 2 0.01277 0.00639

Vegetable 4 6.00147 1.50037 218.22 0.000

Processing 4 1.89459 0.47365 68.89 0.000


Error 48 0.33003 0.00688

Total 74 8.52551

CV 7.55

Appendix XIX. Analysis of variance for calcium content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 4 0.00011

Vegetable 4 600797 0.00860 82.98 0.000

Processing 4 550279 0.07860 758.19 0.000


Error 48 0.00498 0.00010

Total 74 0.37349

CV 0.68

Appendix XX. Analysis of variance for magnesium content of various vegetables


Source DF SS MS F P

Rep 2 0.2 0.11

Vegetable 4 22653.1 5663.28 156628 0.000

Processing 4 24029.5 6007.37 166145 0.000


Error 48 1.7 0.04

Total 74 47957.2

CV 0.33

239

Appendix XXI. Analysis of variance for sodium content of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 1 0.36629

Vegetable 4 204964 51240.9 1589327 0.000

Processing 4 6522075 1630519 5.1E+07 0.000


Error 48 2 0.03224

Total 74 6752685

CV 0.02

Appendix XXII. Analysis of variance for potassium content of various vegetables


Source DF SS MS F P

Rep 2 0.02981 0.01491

Vegetable 4 34677.3 8669.33 627591 0.000

Processing 4 1139705 284926 2.1E+07 0.000


Error 48 0.66306 0.01381

Total 74 1177920

CV 0.01

Appendix XXIII. Analysis of variance for alkaloids of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.0030 0.0015

Vegetable 4 83.146 20.786 18533.3 0.00

Processing 4 1.9670 0.4917 438.45 0.00


Error 48 0.0538 0.0011

Total 74 86.385

CV 3.74

Appendix XXIV. Analysis of variance for saponins of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.0003 0.0001

Vegetable 4 73.2142 18.3036 13943.8 0.000

Processing 4 6.9445 1.7361 1322.59 0.000


Error 48 0.0630 0.0013

Total 74 84.4689

CV 2.57

240

Appendix XXV. Analysis of variance for flavinoids of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.0004 0.00018

Vegetable 4 11.1299 2.78248 75089.5 0.000

Processing 4 2.6877 0.67192 18132.7 0.000


Error 48 0.0018 0.00004

Total 74 14.5657

CV 0.86

Appendix XXVI. Analysis of variance for phenol of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.001 0.0003

Vegetable 4 229.610 57.4024 664893 0.000

Processing 4 12.314 3.0784 35657.7 0.000


Error 48 0.004 0.0001

Total 74 250.324

CV 0.44

Appendix XXVII. Analysis of variance for tanins of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00112 0.00056

Vegetable 4 0.56007 0.14002 477.43 0.000

Processing 4 0.57245 0.14311 487.97 0.000


Error 48 0.01408 0.00029

Total 74 1.33615

CV 8.88

Appendix XXVIII. Analysis of variance for vitamin A of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.017 0.0086

Vegetable 4 97.278 24.3194 1764.41 0.000

Processing 4 29.479 7.3697 534.68 0.000


Error 48 0.662 0.0138

Total 74 142.195

CV 6.98

241

Appendix XXIX. Analysis of variance for vitamin C of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 3.920E-04 1.960E-04

Vegetable 4 11266.9 2816.73 1.1E+07 0.000

Processing 4 6298.58 1574.64 6437338 0.000

Vegetable × Processing 16 1152.90 72.0562 294575 0.000

Error 48 0.01174 2.446E-04

Total 74 18718.4

CV 0.06

Appendix XXX. Analysis of variance for vitamin B1 of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00064 0.00032

Vegetable 4 0.19993 0.04998 182.34 0.000

Processing 4 0.04618 0.01154 42.12 0.000


Error 48 0.01316 0.00027

Total 74 0.28522

CV 19.68

Appendix XXXI. Analysis of variance for vitamin B2 of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00211 0.00106

Vegetable 4 0.81569 0.20392 694.93 0.000

Processing 4 0.07734 0.01934 65.89 0.000


Error 48 0.01409 0.00029

Total 74 0.96063

CV 13.08

Appendix XXXII. Analysis of variance for vitamin B3 of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 0.00211 0.00106

Vegetable 4 0.81569 0.20392 694.93 0.000

Processing 4 0.07734 0.01934 65.89 0.000


Error 48 0.01409 0.00029

Total 74 0.96063

CV 14.79

242

Appendix XXXIII. Analysis of variance for total solids of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 2 1.1

Vegetable 4 320 80.1 38.68 0.000

Processing 4 99998 24999.5 12071.7 0.000


Error 48 99 2.1

Total 74 100682

CV 2.93

Appendix XXXIV. Analysis of variance for total soluble solids of various vegetables


Source DF SS MS F P

Rep 2 0.0021 0.00105

Vegetable 4 15.1587 3.78966 1790.96 0.000

Processing 4 15.6643 3.91607 1850.69 0.000


Error 48 0.1016 0.00212

Total 74 31.8676

CV 3.09

Appendix XXXV. Analysis of variance for energy value of various vegetables and

processing methods

Source DF SS MS F P

Rep 2 197 98

Vegetable 4 3129 782 5.29 0.001

Processing 4 774551 193638 1310.25 0.000

Vegetable × Processing 16 2351 147 0.99 0.478

Error 48 7094 148

Total 74 787322

CV 8.61

Appendix XXXVI. Analysis of variance for pH of various vegetables and processing

methods

Source DF SS MS F P

Rep 2 0.00948 0.00474

Vegetable 4 3.35484 0.83871 323.66 0.000

Processing 4 1.39460 0.34865 134.54 0.000


Error 48 0.12438 0.00259

Total 74 4.98407

CV 0.72

243

Appendix XXXVII. Analysis of variance for nitrogen free extract of various

vegetables and processing methods

Source DF SS MS F P

Rep 2 69.6 34.8

Vegetable 4 594.9 148.7 4.03 0.006

Processing 4 42355.4 10588.8 286.65 0.000


Error 48 1773.1 36.9

Total 74 45051.3

CV 23.67

Appendix XXXVIII. Analysis of variance for total fatty acids of various vegetables


Source DF SS MS F P

Rep 2 0.0004 0.00018

Vegetable 4 11.1299 2.78248 75089.5 0.000

Processing 4 2.6877 0.67192 18132.7 0.000


Error 48 0.0018 0.00004

Total 74 14.5657

CV 17.25

Appendix XXXIX. Analysis of variance for total chlorophyll of various vegetables

Source DF SS MS F P

Rep 2 0.0001 0.00005

Vegetable 4 15.2128 3.80319 107477 0.000

Error 8 0.0003 0.00004

Total 14 15.2131

CV 0.35

244

Appendix XL. Correlation matrix (r) of quality parameters of different vegetables under the influence of processing

treatments

MC TS A PH TSS CF F FA Pro CH NFE E AA CA OA TA Cu Fe Zn Mn Ca Mg Na K Alk Sap Fla Phe Tan VA VC VB1 VB2 VB3

MC 1

TS -0.95 1

A -0.90 0.91 1

PH 0.24 -0.24 -0.04 1

TSS -0.63 0.63 0.67 -0.19 1

CF -0.87 0.87 0.79 -0.27 0.63 1

F -0.11 0.11 0.01 -0.49 0.14 0.03 1

FA 0.02 -0.01 -0.10 -0.11 -0.04 -0.06 0.78 1

Pro -0.31 0.31 0.21 -0.27 0.25 0.24 0.47 0.35 1

CH -0.99 0.99 0.87 -0.23 0.59 0.83 0.06 -0.05 0.26 1

NFE -0.98 0.98 0.85 -0.21 0.56 0.78 0.06 -0.04 0.25 0.99 1

E -0.99 0.99 0.85 -0.29 0.60 0.83 0.18 0.04 0.34 0.99 0.98 1

AA -0.92 0.92 0.84 -0.14 0.57 0.76 0.01 -0.11 0.22 0.92 0.92 0.91 1

CA -0.92 0.92 0.84 -0.14 0.57 0.76 0.01 -0.11 0.22 0.92 0.92 0.91 0.97 1

OA -0.92 0.92 0.84 -0.14 0.57 0.76 0.01 -0.11 0.22 0.92 0.92 0.91 0.98 0.95 1

TA -0.92 0.92 0.84 -0.14 0.57 0.76 0.01 -0.11 0.22 0.92 0.92 0.91 0.96 0.97 0.98 1

Cu -0.67 0.67 0.73 0.17 0.42 0.55 0.06 0.09 -0.09 0.66 0.66 0.65 0.67 0.67 0.67 0.67 1

Fe -0.68 0.68 0.82 0.11 0.48 0.60 0.02 0.01 -0.12 0.66 0.65 0.65 0.67 0.67 0.67 0.67 0.92 1

Zn -0.79 0.79 0.9 0.06 0.61 0.68 0.16 0.11 0.31 0.75 0.74 0.76 0.74 0.74 0.74 0.74 0.81 0.86 1

Mn -0.68 0.68 0.81 0.10 0.47 0.61 0.05 0.05 -0.07 0.65 0.64 0.64 0.65 0.65 0.65 0.65 0.92 0.99 0.87 1

Ca -0.81 0.81 0.76 -0.17 0.46 0.74 0.07 0.03 0.09 0.81 0.79 0.80 0.72 0.72 0.72 0.72 0.83 0.82 0.77 0.85 1

Mg -0.43 0.43 0.67 -0.02 0.43 0.46 0.01 -0.09 0.19 0.37 0.34 0.37 0.35 0.35 0.35 0.35 0.31 0.61 0.68 0.61 0.41 1

Na -0.97 0.97 0.87 -0.17 0.61 0.83 0.18 0.06 0.27 0.96 0.96 0.97 0.91 0.91 0.91 0.91 0.75 0.73 0.81 0.72 0.82 0.36 1

K -0.94 0.94 0.85 -0.14 0.53 0.78 0.18 0.09 0.27 0.94 0.94 0.95 0.92 0.92 0.92 0.92 0.77 0.75 0.81 0.75 0.83 0.37 0.97 1

Alk -0.01 0.01 0.31 0.35 0.21 0.04 -0.13 -0.17 0.01 -0.03 -0.05 -0.05 -0.03 -0.03 -0.03 -0.03 0.18 0.39 0.45 0.40 0.09 0.74 -0.02 -0.02 1

Sap -0.08 0.08 0.01 0.11 0.01 0.06 -0.09 0.04 0.48 0.07 0.07 0.07 -0.03 -0.03 -0.03 -0.03 0.06 -0.11 0.15 -0.03 0.21 -0.14 0.05 0.03 0.07 1

Fla -0.06 0.06 0.03 0.16 0.03 0.04 -0.17 -0.06 0.46 0.05 0.05 0.04 -0.04 -0.04 -0.04 -0.04 0.02 -0.12 0.14 -0.05 0.14 -0.08 0.01 0.00 0.14 0.97 1

Phe -0.08 0.01 -0.09 -0.03 -0.07 0.05 -0.01 0.08 0.52 0.09 0.09 0.11 -0.01 -0.01 -0.01 -0.01 -0.05 -0.31 -0.02 -0.23 0.10 -0.40 0.06 0.03 -0.30 0.91 0.87 1

Tan -0.09 0.09 0.34 0.45 0.29 0.08 -0.34 -0.31 -0.15 0.07 0.07 0.03 0.07 0.07 0.07 0.07 0.44 0.44 0.39 0.46 0.27 0.28 0.07 0.08 0.58 0.34 0.43 0.07 1

VA 0.06 -0.06 0.00 0.19 0.21 -0.05 -0.25 -0.18 -0.55 -0.03 -0.03 -0.08 0.09 0.09 0.09 0.09 0.31 0.21 -0.03 0.20 0.09 -0.26 -0.02 0.02 -0.16 -0.22 -0.21 -0.22 0.38 1

VC 0.03 -0.03 0.19 0.52 0.37 -0.08 -0.18 -0.22 0.16 -0.06 -0.05 -0.07 0.01 0.01 0.01 0.01 0.09 0.05 0.25 0.04 -0.19 0.13 -0.01 -0.04 0.51 0.28 0.39 0.12 0.61 0.12 1

VB1 -0.01 0.01 -0.08 0.20 0.11 -0.05 -0.11 -0.03 0.30 0.01 0.03 0.01 0.02 0.02 0.02 0.02 -0.06 -0.32 -0.09 -0.31 -0.17 -0.51 0.02 -0.01 -0.35 0.54 0.56 0.69 0.11 0.13 0.50 1

VB2 -0.01 0.00 -0.11 0.05 -0.07 -0.01 -0.11 0.06 -0.11 0.03 0.03 0.01 0.01 0.01 0.01 0.01 0.32 0.07 -0.04 0.13 0.32 -0.49 0.04 0.10 -0.38 0.52 0.47 0.56 0.32 0.46 -0.08 0.40 1

VB3 -0.05 0.05 0.05 0.05 0.14 0.07 -0.30 -0.26 -0.02 0.06 0.06 0.02 0.02 0.02 0.02 0.02 0.23 0.09 0.06 0.14 0.29 -0.19 0.01 0.04 -0.04 0.61 0.65 0.55 0.61 0.37 0.21 0.34 0.76 1

Bold font: NS (the P values are greater than 0.01)

Abbreviations used in correlation matrix

MC: Moisture content TS: Total solids A: Ash TSS: Total soluble solids CF: Crude fiber F: Fat

FA: fatty acids Pro: Protein CH: Carbohydrate NFE: Nitrogen free extract E: Energy value AA:

Acetic acid

CA: Citric acid OA: Oxalic acid TA: Tartaric acid Cu: Copper Fe: Iron Zn:

Zinc

Mn: Manganese Ca: Calcium Mg: Magnesium Na: Sodium K: Potassium Alk:

Alkaloids

Sap: Saponins Fla: Flavinoids Phe: Phenol Tan: Tanins V: Vitamin

245

Appendix XLI. Analysis of variance for sensory analysis of uncooked vegetables

Parameters DF SS MS F P

Appearance 4 10.720 2.680 3.865 0.009

Color 4 8.080 2.020 2.942 0.030

Odor 4 4.120 1.030 1.280 0.292

Texture 4 4.520 1.130 1.963 0.116

Taste 4 2.120 0.530 0.491 0.742

Acceptability 4 0.920 0.230 0.292 0.881

Purchase 4 3.320 0.830 0.679 0.610

Appendix XLII. Analysis of variance for sensory analysis of cooked vegetables

Parameter DF SS MS F P

Appearance 4 0.600 0.150 0.118 0.976

Taste 4 5.120 1.280 1.895 0.128

Aroma 4 1.120 0.280 0.420 0.793

Texture 4 5.080 1.270 1.647 0.179

Purchase 4 0.920 0.230 0.236 0.917

Acceptability 4 3.280 0.820 0.703 0.594

246

Appendix XLIII. Informed Consent

From: Benish Nawaz Mirani

Subject: Consent to Participate

Dear Sir:

I (participant), agree to participate in this research project conducted by Benish Nawaz

Mirani, Student at Institute of Food Sciences and Technology, Sindh Agriculture

University Tandojam. I understand the purpose of this study is to examine how Lower

Sindh residents of District Mirpurkhas navigate their nutrition environment to obtain the

foods they eat. I understand my participation is strictly voluntary and may refuse to

answer any question without penalty. I am also informed that my participation will last

approximately 30 minutes.

I understand that my response to the questions will be written, and that these forms will

be transcribed/stores and kept in a locked file cabinet. Afterward, these forms will be

destroyed. I understand questions or concerns about this study are to be directed Benish

Nawaz Mirani, or her advisor Dr. Saghir Ahmed Sheikh, Institute of Food Sciences and

Technology, Sindh Agriculture University Tandojam.

Miss Benish Nawaz has explained in Sindhi the information above and any questions I

asked have been answered to my satisfaction. I agree to participate in this activity and

know my responses will be recorded. I understand a copy of this form will be made

available to me for the relevant information and phone numbers.

“I agree ______ I disagree______to have my responses recorded on audio/video tape.”

“I agree ______I disagree______that (researcher name) may quote me in his/her paper”

________________________________________________________________________

Participant signature and date

This survey has been reviewed and approved by the IFST, SAU Tandojam. Questions

concerning your rights as a participant in this research may be addressed to the Director

IFST, SAU Tandojam. Thank you for taking the time to assist me in this research.

247

Appendix XLIV:

Questionnaire non-traditional vegetables

Name of respondent: _____________________________________ S.No.

Education level: _____________ Age (yrs): Gender: M F

Village: ________________________ District: __________________

Farming experience (yrs): __________ Land holding (acres): _______

Interviewer Name: __________________ Interview date: ____________

S# Vegetable

Name

Eat

frequently

Eat

occasionally

Never

tasted

Do not

know

4 3 2 1

1

2

3

4

5

8. If never tasted, then

Name of

vegetable

Dislike Can’t get

(not available)

Can’t cook Other

(Specify)

248

Appendix XLV:

Sensory evaluation form

(For cooked vegetables)

Name of Expert age; Gender M F

Recipe Name: Category:

Directions: Tick one rating in the boxes for each of the following: Appearance,

taste/flavor, texture/consistency, aroma/smell, and overall acceptability

Parameter Point scores (on five point scale 1-5)

5 4 3 2 1

Appearance Extremely

Attractive

Moderately

Attractive

Attractive

Unappealing Fair

Taste/Flavor Tasted great Flavorful Acceptable Off flavor Flavor did not

appeal to me

Texture

rating

Wonderful

texture

Good texture Acceptable

texture

Off texture Inappropriate

texture/flat/runny

Aroma/

Smell rating

Wonderful

aroma

Appealing

aroma

Acceptable

aroma

Aroma is not

appealing

Unappetizing

aroma

Overall

acceptability

Extremely

Acceptable

Moderately

Acceptable

Acceptable Moderately

Unacceptable

Unacceptable

Purchase Definitely

would

Probably

would

Might or

might not

Probably would

not

Definitely would not

249

Appendix XLVI:

Sensory evaluation form

(For raw or uncooked vegetables)

Name of Expert: age: Gender: M F

Vegetable Name: Date:

Directions: Tick one rating in the boxes for each of the following: Appearance, color,

odor, texture/consistency, taste, and overall acceptability

Parameter Point scores (on five point scale 1-5)

5 4 3 2 1

Appearance Extremely

attractive

Moderately

attractive

Attractive

Fair

Unappealing

Color Typical green Green (typical) with

scarce dark-green or

light-green

spots

Green with

numerous

spots

Yellow-

green or

mostly dark-

green

Dark-green

or yellow

Odor Very intrinsic

very intensive

Intrinsic

intensive

Medium

intrinsic

medium

intensive

Rather

extrinsic

weakly

intensive

Off-odor

undetectable

Texture

consistency

– leaf

tenderness

– moisture

Very crisp,

firm

dry leaves

Crisp, firm

slightly moist leaves

Medium firm,

slightly soft

moist leaves

Not firm,

soft,

slightly

gummy

moist,

slightly

sticky leaves

Gummy or

sticky

very wet,

strongly

stuck leaves

Taste Very intrinsic,

desirable

Intrinsic, desirable Medium

intrinsic,

rather desirable

Not intrinsic Off-flavor

Overall

acceptable

Extremely

acceptable

Moderately

acceptable

Acceptable Moderately

unacceptable

Unacceptable

Purchase Definitely

would

Probably would Might or might

not

Probably

would not

Definitely

would not

250

PLACE OF WORK Sindh Agriculture University, Tandojam.

DURATION OF WORK Three years

EDUCATIONAL UNIT INVOLVED Institute of Food Sciences & Technology Faculty of Crop Production

Sindh Agriculture University, Tandojam. And

National Center of Excellence in Analytical Chemistry, University of Sindh, Jamshoro.

SUPERVISOR PROF. DR. SAGHIR AHMED SHEIKH

Professor


Faculty of Crop Production,

Sindh Agriculture University, Tandojam.

CO-SUPERVISOR-I PROF. DR. SHAFI MUHAMMAD

NIZAMANI

Professor

National Center of Excellence in Analytical Chemistry, University of Sindh, Jamshoro.

CO- SUPERVISOR-II PROF. DR. AIJAZ HUSSAIN SOOMRO

Professor


Faculty of Crop Production,

Sindh Agriculture University, Tandojam.

STUDENT Benish Nawaz

Documents

NUTRITIONAL ASSESSMENT OF SOME NEGLECTED AND …prr.hec.gov.pk/jspui/bitstream/123456789/11237/1... · benish nawaz merani reg. no. 2k12-fst-34 institute of food sciences & technology