Econometric Estimation of Post Harvest Losses of Kinnow in

District Sargodha, Punjab

By

UMAR I JAZ AHMEDB.Sc. (Hons.) Agricultural and Resource Economics

A thesis submitted in partial fulfillment ofthe requirements for the degree of

MASTER OF SCIENCE (HONS)

IN

AGRICULTURAL ECONOMICS

Faculty of Agricultural Economics and Rural Sociology

University of AgricultureFaisalabad

2010

To,

The Controller Examinations,

University of Agriculture,

Faisalabad.

“We the Supervisory committee, certify that the contents and form of thesis submitted by

Mr. Umar Ijaz Ahmed, Regd. No. 2004-ag-1731, have been found satisfactory and

recommend that it be processed for evaluation, by the external Examiner (s) for the award of

degree”.

Supervisory Committee:

1. Chairman

(Dr. Khalid Mushtaq)

2. Member

(Dr. Maqsood Hussain)

3. Member

(Dr. Abedullah)

DEDICATED TO

My graceful and polite father

My most loving mother

My brothers and sisters

Whose love is more precious

Than pearls and diamonds

Who are those whom I say my own

Whose love will never change

Whose prayers will never die

&

Who are nearest, dearest and

deepest

to me

ACKNOWLEDGEMENTS

All praises and thanks for Almighty Allah who is the entire

source of knowledge and wisdom endowed to mankind. All

respects are for His Holy Prophet Muhammad (Peace be upon

Him) who is forever, a torch of guidance and source of

knowledge for entire humanity.

I owe a profound debt of gratitude and appreciation to my

supervisor Dr. Khalid Mushtaq, Assistant Professor,

Department of Agricultural Economics, University of Agriculture

Faisalabad, for his scholastic guidance, encouraging attitude

and constructive criticism during the course of these

investigations and under whose kind supervision the present

study was accomplished.

Luckily I had the rare opportunity to work under the

affectionate supervision of Dr. Abedullah, Assistant Professor,

Department of Environmental and Resource Economics. It was

his unwavering confidence in my capabilities and his

appreciation of my work which encouraged me keep on fighting

against all overwhelming odds till success was ensured.

I feel that without the valuable guidance of Mr. Maqsood

Hussain, Assistant Professor, Department of Agricultural

Economics and Dr. Abdul Ghafoor, Lecturer, Department of

Marketing and Agribusiness, this manuscript would not have

been completed.

I am thankful to my roommate (Arfan Saleem and Usman

Ishaq), all other friends (Asjad, Abid, Farhad, Amir, Hassan,

Irfan, Nasir, shahzad) and all Scouts of Agrivarsity Scouts

Group, UAF for their endless and nice cooperation and moral

support during my studies. I am also thankful to Mr. Umar

Hayat who helped me in data collection.

Finally, no acknowledgment could ever adequately express my

obligation to my affectionate parents whose hands always

raised in prayer for me and without whose moral and financial

support; the present destination would have merely been a

dream. I also owe immense feeling of love and respect for my

brothers and sisters for their humble prayers and good wishes.

(UMAR IJAZ AHMED)

TABLES OF CONTENTS

Chapter No.

Title Page No.

1 Introduction 1

2 Review of Literature 7

3 Material and Methods 23

4 Results and Discussion 28

5 Summary 64

Literature Cited 69

LIST OF TABLES

Table No.

TitlePage No.

Table 4.1 Area and Production of Citrus in Pakistan 31

Table 4.2 Area and Production of Citrus in Punjab Province 32

Table 4.3 Percentage shares of farm, market and retail level losses in total produce and total losses of kinnow

34

Table 4.4 Losses of kinnow incurred at farm level during picking, carrying, grading, packing and transportation

36

Table 4.5 Personal characteristics of Kinnow Producer/Contractors 37

Table 4.6 Orchard related characteristics 38

Table 4.7 Sale quantities and sale prices of kinnow 39

Table 4.8 Harvest Losses 40

Table 4.9 Post-harvest losses during carrying from picking to grading/packing place

42

Table 4.10 Post-Harvest losses of kinnow during grading and packing 44

Table 4.11 Post-Harvest losses of kinnow during loading and transportation 46

Table 4.12 Losses of kinnow incurred at wholesale market level during unloading and marketing and storage

47

Table 4.13 Personal characteristics of wholesaler 48

Table 4.14 Sale quantities and prices of kinnow 48

Table 4.15 Expenditures of Wholesalers 49

Table 4.16 Post-Harvest losses of kinnow at wholesale level 50

Table 4.17 Losses during storage at wholesale level 51

Table 4.18 Losses of kinnow incurred at retail level during retail marketing and unsold quantity

52

Table 4.19 Personal characteristics of retailers 53

Table 4.20 Purchase and Sale quantities and prices of kinnow 53

Table 4.21 Expenditures of Wholesalers 54

Table 4.22 Post-Harvest losses of kinnow at retail level 55

Table 4.23 Daily business volume 55

Table 4.24 Analysis of variance (ANOVA) 57

Table 4.25 Coefficients and t-test to check the significance of various factors 58

Table 4.26 Analysis of Variance (ANOVA) 59

Table 4.27 Coefficients and t-test to check the significance of various factors 60

Table 4.28 Analysis of Variance 61

Table 4.29 Coefficients and t-test to check the significance of various factors 62

LIST OF FIGURES

Figure No.

TitlePage No.

Figure 4.1 Area of Citrus in Pakistan from 1985-86 to 2007-08 33

Figure 4.2 Production of Citrus in Pakistan from 1985-86 to 2007-08 33

Figure 4.3 Percentage share of farm, market and retail level losses in total post harvest losses of kinnow

35

Declaration

I hereby declare that contents of the thesis, “Title of Thesis” are product of my

own research and no part has been copied from any published source (except the

references, some standard mathematical or genetic models/equations/protocols etc.). I

further declare that this work has not been submitted for award of any other

diploma/degree. The university may take action if

Signature of the Student Name: Umar Ijaz Ahmed Reg. No. 2004-ag-1731

ECONOMETRIC ESTIMATION OF POST HARVEST LOSSES OF KINNOW IN DISTRICT SARGODHA, PUNJAB

ABSTRACT

Post harvest losses are a great threat to productivity and exports of fruits from a developing country like Pakistan. The post harvest losses occur at various levels in the supply chain of Kinnow. The most important of these are the poor transportation and storage infrastructure, carrying and packing facilities and poor handling procedures. This study was conduct to quantify these losses at farm, wholesale market and retail levels. Three different multiple regression models were used for these three levels. A well designed farm questionnaire was used to collect post harvest losses data from 120 respondents from district Sargodha. Results shows that total post harvest losses at all three level were about 45 percent of the total produce. The losses at farm, wholesale market and retail levels were 72 percent, 25 percent and 3 percent of the total post harvest losses of kinnow respectively. Experience, picking time and picking method had significant effect on losses at farm level and experience, loading method, storage place also had significant effect on losses at transportation and wholesale market level. Similarly unsold quantity and type of retailers had significant effect on losses at retail level.

Key words: Kinnow, Post harvest losses, Transportation, Packaging

CHAPTER 1

INTRODUCTION

Pakistan is blessed with vast agricultural resources on account of its fertile land, well-

irrigated plains, extremes of weather, and centuries old tradition of farming. It is because of

its central importance in the economy that the government has identified agriculture as one of

the four major drivers of growth.

Regardless of the nature of the economy, agriculture sector assumes a pivotal role in

its economic development. Modern agriculture has always furnished the means to provide the

foundation for a developed industrial economy. Therefore, sustainable development in

agriculture sector in a country like Pakistan can stimulate growth and development in all

sectors of economy. In agriculture sector, food crops are always given prime importance, as

these are the main sources of food supply to human being. With its present contribution to

GDP at 21.8 percent, agriculture accounts for 42.1 percent of the total employed labor force

and is the largest source of foreign exchange earnings. Agriculture growth has been estimated

at 4.7 percent during 2008-09. Major crops (wheat, rice, cotton and sugarcane) accounting

for 33.4 percent of agricultural value added registered increasing growth of 7.7 percent as

against of negative 6.4 percent last year. Minor crops contributing 12.4 percent to overall

agriculture grew by 3.6 percent as against 10.9 percent last year (Government of Pakistan,

2009a).

The region of Pakistan has a rich topographic and climatic endowments and

variations in soil, on which a large range of horticultural crops, such as fruits, vegetables,

roots and tuber crops, ornamental, medicinal and aromatic plants, plantation crops, spices and

other are grown. A significant increase has been observed in the export earnings from the

horticultural crops during the recent years. This sector has the potential to provide

opportunities to increase income and alleviation of hunger and poverty and curve down

socio-economic problems of the region (Alam & Mujtaba, 2002).

Horticultural crops contribute about 6 percent of country's GDP and 22 percent of

national food production. Pakistan annually produces about 12000 thousands tonnes of fruits

and vegetables in which annul fruit production is about 5712.4 thousands tonnes. Citrus fruit

is leading in term of production followed by mango, dates and guava (Government of

Pakistan, 2008).

Citrus cultivars are grown in varying quantities in countries with tropical or sub

tropical climate. Citrus is a valued fruit of Pakistan and have number one position among all

fruits both for area and production in the country. Pakistan is among the top fifteen citrus

producing countries of the world (Mahmood and Sheikh, 2006). At present, total acreage

under citrus has recorded an increase to 199.4 thousand hectares in 2007-08 from 193.2

thousand hectares in 2006-07. Similarly production also went up to 2294.5 thousand tonnes

in 2007-08 from 1472.4 thousand tonnes in 2006-07. Punjab has major share of 96.7 percent

in total production of citrus in Pakistan (Government of Pakistan, 2008). Pakistani citrus

have huge demand in the international market due to its rich flavor and taste.

Pakistan is producing many varieties that are categorized into six major groups like

Sweet oranges, Mandarin, Grape fruit, Lemon and Lime. From these groups mandarin group

(Kinnow and Feutrells early) is very famous and good in taste. Kinnow is the major variety

and Pakistan is the largest producer of Kinnow (Citrus Reticulata). According to an estimate,

about 95 percent of world total production is produced in Pakistan (Mahmood and Sheikh,

2006).

Citrus fruit is grown in all four provinces of Pakistan. Punjab produces over 95

percent of the crop because of its favorable growing conditions and adequate water. The

main production areas of citrus in Pakistan are Sargodha, Toba Tek Singh, Rahim Yar Khan,

Multan, Sahiwal, Lahore, Sialkot, Jhang, Mianwali and Gujranwala in Punjab; Sukkhar,

Khairpur, and Nawabshah in Sindh; Makran, Sibbi and Kech in Baluchistan; Mardan,

Peshawar, Swat, Swabi and Noshera in Khyber Pakhtunkhan. Nearly 1.62 percent from

Sindh, 2.23 percent from Khyber Pakhtunkhan and 0.769 percent from Baluchistan

(Government of Pakistan, 2006).

Out of total production 2294.5 thousand tonnes in 2007-08, Pakistan exported about

215.061 thousand tonnes, which is the 9.37 percent of total production and rest of the

produce is either consumed domestically or wasted during post harvest handling

(Government of Pakistan, 2009b).

The act of growing and selling of citrus is no longer considered a simple activity. It

involves many factors as well as the interaction of many industries to make it possible for

selling. It involves labour directly in the field and packing facilities and indirectly in

transport-distribution. It involves supplies and services such as agricultural inputs,

transportation, grading, packaging, etc. (Guzman, 2004). Average yield of citrus in Pakistan

is about 12.78 tonnes per hectare (Government of Pakistan, 2006). While the potential yield

of citrus is 18-20 tonnes per hectare (PHDEB, 2006), so there is a big gap between its

average and potential yield. This yield gap may be attributed to a number of problems faced

by citrus growers, which need to be properly addressed. Amongst these problems regarding

information and inputs seem to have been playing an important role towards this big yield

gap. Although citrus is highly perishable crop and storage, packaging, transport and handling

technologies are practically non-existent; hence considerable produce is lost (FAO, 1989).

The post harvest losses in case of horticultural crops including citrus are estimated to range

between 30-50 percent of the total harvest (Lum, 2001).

Fresh fruits and vegetables are inherently perishable. During the process of handling,

transportation, storage, distribution and marketing, substantial losses are incurred which

range from a slight loss of quantity to spoilage. The primary causes are biological (chemical,

microbial, injuries, cuts, bruises, peeling and trimming etc.), environmental (overheating,

chilling, freezing and dehydration etc.) and physiological (sprouting, rooting and

transpiration etc.) and secondary causes includes inadequate curing, improper storage,

inappropriate transportation, inadequate production and harvest planning etc. These losses

have occurred at different stages like harvesting, processing, grading and packing, storage

and transportation (Shah and Farooq, 2006).

Pakistan’s citrus production is also subject to the post harvest losses during

harvesting, handling, transportation, storage and distribution. Besides resulting in low

per capita availability and huge monetary losses, these increase transport and market

costs also (Subrahmanyam, 1986). The quantum of loss is governed by factors like

perishable nature, method of harvesting and packaging, transportation etc. Citrus

(Kinnow) being a commercial fruit crop, the post harvest losses are significant in terms

of quantity as well as economic value (Gangwar et al., 2007).

Losses in quality of citrus are of particular importance as it is more susceptible to

injury than other fruits because of its constituents and structure, due to which, mechanical

injury in the case of this fruit causes rapid microbial deterioration, which may lead to total

rejection by the consumer (Tyler, 1978).

Due to inadequate handling, transport and storage facilities and further lack of

technical know-how about 10-15 percent of fruit are wasted from tree to table (Farooq

et al, 1978). As most of the post harvest losses occur at three level i.e. orchard,

transportation and wholesaler’s marketing and retailer’s levels. At orchard level losses

are due to harvesting injuries, culled, brushes, insect damage, button holes and

punchers. All the thrown away or discarded fruits at the orchards are treated as post

harvest loss (Gangwar et al., 2007).

As most of the transportation is done by roads and orchard to market, roads are

not in good condition or perhaps non-existent. Rugged and bad roads cause heavy

losses to fruits and vegetables and citrus is no exception. The fruit handling system

from farm to market is also complex therefore substantial amount of fruit is likely to be

wasted from time the crop is harvested till its consumption (PARC, 1986).

Diseases that occur after harvest can have a significant impact on keeping

quality of fresh citrus fruit. Levels of decay can often reach as much as 20-40 percent in

instances when fruits are treated with fungicides. To enhance sales and to develop new

market for fresh citrus decay must be controlled for periods of months. Losses occur

during post harvest handling represent economic losses in cost of production,

harvesting, packing, marketing and transportation. Decay also causes loss of consumer

confidence in fresh citrus quality and discourages repeat sales (Brown, 2003).

Research in the area of post harvest losses in fruits is of great importance to

minimize losses. This will help to (i) provide more produce available for domestic

consumption, (ii) increase exports and earn foreign exchange, (iii) provide the right

type of raw material for food processing industries, (iv) generate more employment

opportunities and (v) enhance value of products which ensues greater financial returns

to farmers and others involved in industry (Indian Agricultural Research Institute,

2003).

The goals of post harvest research and extension are to maintain quality and

safety and minimize losses of horticultural crops and their products between production

and consumption. Reduction of post harvest losses increases food availability to the

growing human population, decreases the area needed for production, and conserves

natural resources. Strategies for loss prevention include use of genotypes that have

longer post harvest life, use of an integrated crop management system that results in

good keeping quality, and use of proper post harvest handling systems that maintain

quality and safety of the products (Kader, 2003).

Trade and price policies revealed that the Kinnow producers were marginally

unprotected in Punjab. Hence there are good possibilities of substantial gains from free

trade, provided the infrastructure related to the WTO requirements is provided in the

area on priority basis. Farmers have a comparative advantage of producing world-class

citrus fruit for export as in the past they were unprotected from trade and pricing

policies of the Government. The only concern is the provision of necessary

infrastructure needed for international trade in the WTO perspective. Actually WTO

requirements are the opportunities, provided if institutional infrastructure is established.

After this, Pakistani products can earn name, then such barriers shall not affect exports.

Initially, the preparatory costs of compliance with the sanitary and phytosanitary (SPS)

measures will be high, but once such measures were adopted, the future benefits would

be much higher (Sharif and Ahmad, 2005).

In order to promote horticultural industry and to enhance foreign exchange earning to

the maximum extent, there is an urgent need to make a through scientific investigation into

the factors causing post harvest losses in citrus fruit and to adopt the technologies minimizing

these losses (Leghari, 2001). Post harvest losses in citrus take place at various levels, at the

farm level, transfer of citrus from producer to the consumer through the marketing system

involving various functions like exchange, storage, transportation and processing,

distribution and finally at the consumption stage (Chaudhry, 1980).

As most of the studies done on the estimation of post harvest losses was simply

calculates the averages, percentages, marketing margins and efficiency at different

levels. It is the need of the time to estimate the post harvest losses and find the major

determinants of post harvest losses at farm, transportation and wholesale market and

retail market level separately. So this study is planned to assess the quantitative post

harvest losses in citrus fruit, which occur at different levels and also to signify the

factors causing these losses.

Objectives

Specific objectives of this study are as follows:

To estimate losses in kinnow at farm, transportation and market and retail levels;

To quantify the factors contributing to the post harvest losses at different levels i.e.

farm, transportation and market and retail levels; and

To suggest policy measures for minimization of kinnow produce losses

CHAPTER 2

REVIEW OF LITERATURE

Irying (1965) studied the various type of losses occurred in agriculture like pre-

harvest, harvest, post harvest, marketing losses during different stages. He also noted that

once crops and livestock had been produced, they were subject to losses during storage,

marketing and processing activities. He estimated that losses for crops were at $ 1.04 billion.

Similarly losses in fruits and vegetables were put at $121.7 billion.

Khan (1965) reported that the total area under various types of fruits in 1964 was

302755 acres. All fruits were not available for human consumption due to a net loss of about

35 lacs mounds. About 10-15 percent waste of the total production was arising from

inadequate handling of fruits during the performance of various markets operations. It may

imply not only a great national loss but also non availability of an essential consumable

commodity in desired quantities for human consumption.

Bhat (1978) determine the quantitative food losses and their means, He said that the

major thrust in the past ten years had been directed towards determining food losses and

assessing the means by which these foods were lost. He argued that it should now be possible

to initiate some concrete action programs to minimize the quantitative and qualitative losses

that occur at various stages of food handling that starts from farm level to market and in the

house.

Dendy (1978) in his analysis of an FAO Survey of Post-harvest Crop Losses in

developing countries, emphasized that more decline of post harvest food losses in developing

countries should be undertaken as a matter of main concern, with a view to reaching at least a

50 percent reduction by 1985.

Parpia (1978) analyzed the nature and scale of the world hunger problem, and

recommended that the solution of this problem required not only increased production of

food but also maintenance of its quality through use of appropriate technologies for post

harvest conservation and processing including those for food manufacturing by-products.

United States National Academy of Science (1978) signified the problem of post

harvest food losses in developing countries and pointed out the need for giving consideration

to losses in food products other than the cereals, particularly fruits and vegetables.

Chaudhry (1980) concluded that the production and consumption stages of

agricultural produce were interlinked by an important section of the post harvest stage which

comprised a set of operations changing degree of loss-occurrence. A significant amount of

what a produced gets lost in one form or the other.

Greeley (1986) reported that the prevention of food loss in the farm level post harvest

system had become an objective of food policy in many developing countries. This objective

was founded on the allegations that the technology was available to avert or diminish these

losses and that as a result, hungry people will be less hungry. Facts on the levels of food loss

under conventional practices showed that at farm level cost reduction is the principal

influence on technological choice.

Khan (1988) said that fifty percent food losses could be reduced from harvesting to

food processing. He added that in order to overcome this situation there was a need for

evolving practical post harvest loss reduction policies and programs in developing countries.

The reserve stock could be build when post harvest loss could be restricted as much as by 50

percent for which all out efforts had to be intended at without which feeding 5 billion people

will become a serious problem. He reported that those developing countries whose

dependence is on exports will not be able to maintain a balance economy creating problem of

poverty and unemployment. He stated that even in Pakistan, in case of loss occurred, and

could have been avoided by saving agricultural products from pre and post harvest losses.

Asian Development Bank (1990) studied the major constraints in the export of fruits

and vegetables in Pakistan and reported that there are a lot of problems and constraints in the

production and export of fruits and vegetables in Pakistan especially in post harvest sector.

They concluded that lack of handling during harvesting and carrying, packaging, cold

storages and internal transport facilities were major sources of post harvest losses in fruits

especially in mango and citrus.

Liu (1990) studied the Taiwan’s experience of modernizing post harvest handling

technologies of fruits and vegetables. He said that post harvest handling had crucial effects

on post harvest losses. He argued that modern post harvest handling techniques applied in

grading, packing, precooling and transportation had minimized losses in developed countries.

He reported that the major form of losses were quantitative and its magnitude was 25 percent

or 28 to 42 percent worldwide and 15 to 60 percent or 15 to 50 percent in less industrialized

countries; however nobody knew the exact figure as it vary from country to country and time

to time. He described that major reasons of these losses were lack of market demand,

mechanical injury, physiological deterioration and parasitic diseases. Improved picking,

grading, packaging and transportation technologies could minimize these post harvest losses

in less developed countries.

Kader (1992) reported that losses during post harvest operations due to improper

storage and handling are enormous and could range from 10-40 percent. He further reported

that post harvest losses could occur in the field, in packing areas, in storage, during

transportation and in the wholesale and retail market as well as severe losses occurred

because of poor facilities, lack of know-how, poor management, market disfunction or

simply the carelessness of farmers.

Food and Fertilizer technology centre (1993) reported that post harvest losses of fruits

and vegetables were high in Asia, particularly in tropical countries. It further stated that fresh

fruits and vegetables were inherently perishable so during the process of distribution and

marketing, substantial losses were incurred. It generalized that causes of losses were many

including physical damage during handling and transport, physiological decay, water loss or

sometimes simply because there was a surplus in the marketplace and no buyer could be

found. It concluded that general picture of the rate of post harvest losses of horticultural

crops in each country could be obtained by calculating the difference between total

production and total consumption. According to this study post harvest losses of fresh

produce ranged from 20 to 50 percent.

Mohyuddin (1998) reported that the reasons for the occurrence of losses were almost

the same as were observed in mango fruit. Relatively more losses were observed due to

picking the fruit with stem, particularly in Kinnow variety as the skin of this variety is softer

which is easily injured by the stem of another fruit. The total marketing losses in various

marketing channels of citrus fruit ranged from 16.90 to 19.90 percent of the produce handled.

The results indicate that the losses occurring at post harvest levels are immense and recurring

which the developing economy of Pakistan can hardly afford to bear. These losses therefore,

must be minimized, if cannot be totally eliminated.

Bachmann and Earles (2000) reported some post harvest handling measures of fruits

and vegetables. Appropriate production practices, careful harvesting and proper packaging,

storage and transport all contribute to good quality produce. Production practices have a

tremendous effect on the quality of fruits and vegetables at harvest and post harvest quality

and shelf life. Environmental factors like soil type, temperature, frost and rainy weather at

harvest can have an adverse effect on storage life and quality. Management practices also

affect post harvest quality. Produce that has been stressed by too much or too little water,

high rates of nitrogen or mechanical injury (scrapes, bruises, abrasions) is particularly

susceptible to post harvest diseases. Temperature is the single most important factor in

maintaining quality after harvest. For maintaining temperature some of low cost structures

have created like pre-cooling, room cooling, forced air cooling, hydro cooling, top or liquid

icing, vacuum cooling and chilling injury.

Basappa et al. (2001) conducted study to estimate post harvest losses in Maize at

different stages of farm level. At farm level the post harvest losses were estimated to be 3.02

Kg per quintal. The share of harvesting loss was maximum. About 0.68 Kg per quintal of

maize was lost at the storage level. Whereas losses at transportation, threshing, packaging

and cleaning was 0.44, 0.34, 0.15 and 0.10 Kg per quintal respectively. There is a need for an

integrated effort to increase the productivity by evolving high yielding varieties hybrids in

maize. The improvement in storage facilities required immediate attention of the policy

makers for reducing post-harvest loss in maize.

Leghari (2001) reported that in Pakistan, the magnitude of post harvest losses of

vegetables and fruits were about 35 percent. He stated that in fruits and vegetables, the

quality of produce start deteriorating right after their harvest. According to him, primary

factors responsible for post harvest produce losses were: poor pre-harvest measures-adoption

of poor production techniques (varieties with low shelf life, imbalance use of nutrients, insect

pest and diseases infestation and a biotic stresses; low tech. harvesting procedures, non-

application of pre-harvest recommended treatments/practices, harvesting at improper stage

and improper care at harvest. In order to preserve the produce quality he recommended

different post harvest techniques for variety of produce. These techniques included hyper

cooling, refrigeration and freezing, modified atmosphere packaging, modified packaging

storage, control atmosphere storage, skin coating, hypo-baric or low pressure storage,

irradiation, dehydration, canning, high pressure processing and pulsed electric fields and

pulsed light applications.

Lum (2001) reported the post harvest losses in the range of 40-60% of the perishable

commodities in most of countries as a great concern. He argued that a valuable amount of

food, which could be used, is being wasted annually. He concluded that these countries

continue to suffer as consequences of food shortages, malnutrition and loss of export

revenue.

Studman (2001) studied that computers and electronics have made a

particular impact on the postharvest industry. These include environmental control

and storage, quality monitoring, quality management, grading systems, inventory

control, and management of product. It is likely that consumer demand for

improved quality, longer storage life, and guaranteed product safety will continue

to grow. In a highly competitive market the industry will need to meet these

demands, and electronic technology will play an increasingly important role.

Improved sensors to assess quality are still needed, and handling and storage

systems are likely to become increasingly sophisticated. In the latter half of the

twentieth century technology has contributed much to improve the world's food

supply, but it has also generated problems for the wider society, which will require

attention in the next millennium.

Martinez and Davis (2002) suggest that farmers must become more interdependent

participants in the food supply chain, perhaps giving rise to more contracting and other forms

of organizations in agriculture. They believe that, a food company’s growth will depend on

lowering production costs, differentiating its products, producing higher quality products at

economical prices or expanding international trade. Coordination between agricultural

production and processing will be essential to providing consumers with products that meet

their demands for quality and variety.

Post harvest Horticulture Training and Research Centre (2002) in its collaboration

with Department of Agriculture on a program to cut post harvest losses in agricultural

commodities and to assure the quality supply of horticultural produce, reported that

government statistics currently showed post harvest losses in banana up to 40 percent, papaya

48 percent, mango 70 percent and cauliflower and ornamental plants 40 percent. According

to their research, these losses were due to the inherent perishable quantity of horticultural

crops, adverse condition in post harvest environment, poor handling and lack of access to

post harvest facilities, and distribution inefficiency from production to consumption areas.

They have concluded that post harvest losses from major crops pose a big problem to local

farmers as it cut back on their ability to compete against cheap imports coming into the

country under liberalized farm gate. They emphasized the need for government and the

private sector to fortify research, development and extension efforts on post harvest issue.

Ragni and Berardinelli (2002) said that in sorting and packaging lines,

fruits are submitted to impacts that can involve alterations to the flesh. For this

study, impact measurements were taken at critical points on Italian machines at a

domestic packing house. These impacts were then reproduced in the laboratory to

analyse the damage and the mechanical behaviour of apples of four cultivars

(Golden Delicious, Stark Delicious, Granny Smith and Rome Beauty). Using multiple

linear regressions, correlations were determined between the characteristics of the

apples, impact levels, subsequent damage and parameters describing the

mechanical behaviour of the fruits. The deterioration of the flesh observed on the

impacted apples does not represent serious commercial damage to the product,

excluding the deterioration due to an accessory feeding line that employs a dry bin

dumper. In this last case, damage can consist of darkening of the flesh and

fractures having a depth of 4–5 mm and a diameter of 12–15 mm. The research

emphasized the need to consider characteristics such as the impact radius, the flesh

firmness and the sugary content of the flesh when studying the effects of dynamic

stresses on apples. The sample of Stark Delicious showed the highest susceptibility

to impacts.

Srivastava (2002) stated that post harvest losses estimated around 10 percent in food

grains and 25-40 percent in fruits and vegetables constitute a national waste in terms of food

as well as money. He said that agricultural produce sold in market was not standardized,

scientifically packed, graded and labeled. He emphasized that there is a pressing need to

establish such post harvest technology systems which reduce losses and in order to reduce

these losses post harvest management systems must include mechanism to ensure that food

products meet all required national and international standards set by SPS under WTO.

Admassu (2003) reported that losses after harvest were a major source of food loss.

Farmers growing horticultural crops were facing high economic loss, because they had no

means of increasing the shelf life of these crops. He further reported that the country

(Ethopia) was not getting foreign exchange from horticultural crops due to the low levels of

post harvest technology, which made the product of inferior quality and has no chance of

competing in the world market.

ASET (2003) estimated the loss of horticultural produce due to non-availability of

post harvest and food processing facilities in Bihar and Uttarpradesh. The study attempted to

analyze various aspects of post harvest losses as well as to quantify the exact losses of

horticulture produce due to lack of post harvest storage and processing facilities. The study

concluded that post harvest loss of horticulture produce vary between 5-40 percent of total

production.

Ram (2003) said that India suffered a loss of around $20 billion annually, due to

uncontrolled ripening and inadequate post harvest management of fruits and vegetables. He

suggested that a reduction in post harvest losses by extending the shelf life of fruits and

vegetables through genetic engineering by only one percent would save the country losses

over Rs. 200 crore.

Yuen and Teng (2003) had derived the post harvest losses of fruits using expert

judgement, sampling of storage facilities and analysis of trade documents. According to their

research post harvest losses in tropical fruits have been estimated to average between 15-25

percent of production. They reported that these losses were caused by physical, mechanical,

biological and social factors. According to their study, biological events leading to post

harvest losses started in the field and efficient control measures might involve manipulation

of the production system. They concluded that a distinction had to be made between quantity

loss and the real, biological versus artificially set social losses. They further concluded that

biological losses were lower than social losses and in the context of current concerns about

pesticides: social losses may be unacceptably high in developed countries.

Bari (2004) estimated the post harvest losses of mango in district Rahim Yar Khan

and Multan, Punjab Pakistan. Descriptive and analytical analysis was used to estimates the

losses. Linear multiple regression model was used at farm level only. She reported that total

post harvest losses of mango at farm, market and consumption levels were almost 31 percent

of the total production and maximum losses were occurred at farm level that is 38.6 percent

of the total post harvest losses. Market and consumption level losses were 35.9 and 25.5

percent of the total losses respectively. Major reasons of these losses were inadequate

picking, packing, transportation and marketing procedures.

Dhatt (2004) gave the significance of the course on “Maintenance of post harvest

quality during storage and exports horticultural crops” organized by The Punjab Horticultural

Post Harvest Technology Centre of Punjab Agricultural University. He reported that India

produced more than 142 million tonnes of fruits and vegetables yearly but processed and

exported less than 2 percent of its produce, mainly because of improper post harvest

treatment, which lead to 20-40 percent wastage, thus leaving little actual surpluses for

exports and processing. He further stated that the major factor for these massive losses was

lack of awareness of knowledge and skills on the part of handlers and inappropriate

infrastructural facilities.

Hussain et al. (2004) conducted a 45 days storage experiment to investigate the effect

of Uni-Packaging treatments on the shelf life of citrus fruits. Different treatments were

polyethylene bags of 0.0254mm, 0.0508mm thickness and control. The result showed that the

uni-packaging had no significant effect on the pH of citrus fruit. Weight loss increased

significantly as storage increased. Maximum weight loss observed in control and minimum

weight loss in thick packaging (0.0508mm). The T.S.S increased during storage but

individual packaging had non-significant effect on the T.S.S. Ascorbic acid decreased from

1.59-0.63% during storage. The organoleptic properties evaluation revealed that individual

packaging had significant effect on the external appearance, taste and texture. Thick

packaging performs significant effect in prolonging the shelf life of citrus fruit.

Karunananthun (2004) reported that in India post harvest losses of fruits and

vegetables range between 20 to 40 percent, while losses in pulses, oilseeds and cereals range

between 10 to 30 percent. This represented a market value of approximately $15 billion US

per year, causing a serious dent in the economic wealth of the farm producers.

Henson and Reardon (2005) have argued that the emergence of private food safety

and quality standards mainly in developed countries is now a well-established fact. These

standards operate alongside regulatory systems but in terms of market access and access to

the shelves of the leading supermarkets in the rich countries, it become almost mandatory.

With these standards becoming a global phenomenon, countries in the developing world (the

South) faces increasing constraints in exporting their food products to markets in Europe and

the USA.

Jarimopas et al. (2005) measured the vibration levels in two of the most commonly

used truck types to ship packaged goods as a function of road condition and vehicle speed.

The suspension type on the trailers studied was leaf-spring. The results of damage to

packaged tangerine fruit as a function of location in the payload are also presented. The data

presented in this study will assist product and package designers to reduce damage in transit.

The results showed that vibration levels increased with speed and as a result of road

condition. Analysis of variance indicated that three controlling factors, road surface, truck

speed and truck type. Fruit damage was found to be greatest in the uppermost container for

every combination of road, truck type and travelling speed, which also corresponded to the

highest vibration levels recorded. The results showed that a significant amount of damage

can occur on unpaved roads (laterite), while the packages are transported from farms and

harvesting areas to regional truck terminals. Damage on asphalt road conditions was

minimal. This paper provides an updated history of measured and quantified levels of

vibration for these specific trucks and road conditions.

Kader (2005) stated that reduction of quantitative losses is a higher priority than

qualitative losses in developing countries, while this thing is opposite in developed countries

where consumer dissatisfaction with produce quality results in a larger proportion of the total

post harvest losses. Development of new cultivars with better taste and dietetic value plus

adequate productivity should be given high priority in all countries. Strategies for reducing

postharvest losses in developing countries include, application of current knowledge to

improve the handling systems, especially packaging and cold chain maintenance of

horticultural perishables and assure their quality and safety; overcoming the socioeconomic

constraints, such as inadequacies of infrastructure, poor marketing systems, and weak R&D

capacity; and encouraging consolidation and vertical addition among producers and

marketers of horticultural crops.

Spinardi (2005) studied on effect of harvest date and storage on antioxidant systems

in pears. Pears (Pyrus communis ‘Passa Crassana’) were picked at 3 different stages of

ripening: immature, commercial ripe and fully ripe. Commercially ripe fruits were stored for

3 and 4 months at normal atmosphere (T: 1.5°C; R.H.: 95%). Ethylene production rates were

measured and the activity of the scavenging enzyme ascorbate peroxidase (APX) was

evaluated. The levels of the antioxidant ascorbic acid (AA) and of malondialdehyde (MDA),

a marker of lipid peroxidation, were also determined. Ethylene levels were barely detectable

at all 3 harvest dates and increase progressively during storage. APX activity was positively

affected by the ripening stage, whereas decreased significantly during cold storage. AA

reached the highest level in commercial ripe fruits. Furthermore, storage had a negative

effect on AA content and caused a gradual, marked decrease. MDA did not change in fruits

of different ripening stages, while after storage the levels were significantly higher. These

results suggest that, during cold storage of pears, defense mechanisms against AOS fail to

provide adequate protection, thus oxidative stress occurs.

Udas et al. (2005) studied on post harvest handling of four major vegetables namely

cauliflower, cabbage, radish and tomato. Information was collected on harvesting time and

methods, timing and availability of transport, grading, pre-cooling, packaging and storage.

The study found that the postharvest losses of cauliflower, cabbage, radish and tomatoes

from the farmer’s field to the collection centers were 6 percent, 9 percent, 6 percent and 3

percent respectively. The losses were mainly due to spoilage, bruising and trimmings in

cauliflower and cabbage, breaking in radish and rupturing and spoilage in tomatoes. The

losses incurred in above four vegetables at retailer’s level were 41 percent, 34 percent, 4.5

percent and 7 percent respectively for the four vegetables. Physically damaged, sorted

vegetables and trimmed parts were sold at a lower price to feed livestock. The main factors

responsible for postharvest losses were inappropriate packaging, transportation and grading

systems. 

Watkins and Ekman (2005) stated that temperature control is the main technology

underpinning storage of horticultural crops. However, the effects of cooling can vary.

Although low temperatures generally reduce ethylene sensitivity, ethylene production can be

either stimulated or inhibited. The consequences of changes in ethylene production/

sensitivity may be either positive or negative for product quality. Responses to the ethylene

inhibitor 1-MCP are mediated by such reactions, as well as according to how the fumigant

interacts with plant tissues at different temperatures. Low temperatures generally maintain

desirable levels of sugar, acid, and other flavor compounds in horticultural products.

However, storage at too low a temperature or for too long can permanently suppress volatile

production or cause “off” odors and flavors to accumulate. The effects of temperature on

vitamins, flavonoids, phenolics, and other plant anti-oxidants are more difficult to quantify.

Some of these compounds increase as products ripen, so treatments that maintain commercial

quality can negatively influence nutritional quality. The storage temperature therefore often

represents a compromise between the product qualities preferred by consumers and the

economic realities and product quality requirements of those involved in the produce supply

chain.

Mahmood & Sheikh (2006) conducted a study on citrus export system in Pakistan.

They reported that harvested Kinnow is exported through three different channels. Produce

was brought to processing units in 20 to 40 Kg plastic boxes. After unloading the produce is

washed, dried, waxed, again dried, graded, packed, labelled and then transported to Karachi

port in open top trucks or refrigerated containers. Majority of exporters (66.7 percent) use

refrigerated containers. They concluded that problems with Kinnow exports include low

quality, lack of storage facilities, non-availability of quality packing, poor transportation

facilities, high freights charges, weak role of export promoting agencies and inconsistent

government policies.

Singh and Jain (2006) studied on Post harvest microbial losses in distant marketing of

Kinnow. A field experiment was conducted to find out the losses of Kinnow mandarin due to

mycoflora in long distance marketing. The fruits were packed in CFB boxes (24 to 84 fruits

per box) with 2-3 layers and in wooden boxes (36 to 132 fruits per box) with 3-4 layers and

loaded 850 boxes of CFB and 550 wooden boxes in different trucks and transported from

NAFED, Maujgarh, Abohar (Punjab) and Shri Ganganagar area (Rajasthan) to Bangalore

(Karnataka) 2500 km away. Among the fruits, 31.1 and 22.9 percent got infected due to fungi

in CFB boxes and wooden boxes, respectively. Alternaria alternata had the highest incidence

(81.1 percent) in CFB boxes followed by Penicillium digitatum and P. italicum. Among the

fruits discarded due to mycoflora decay, 64-70 percent was infected by P. digitatum. It is

concluded that injured fruits (due to mechanical or frost injury), if packed, are bound to spoil

and spread infection to other sound fruits. To save packaging and transportation cost and

reduce the losses, injured fruits should be sorted and removed at the initial stage of packing.

Aujla et al. (2007) reported that scarcity in storage and transportation infrastructure

resulted in 25-40 percent post-harvest losses that shrinks supply and put pressure on prices.

The prevention of such losses would further improve exportable surplus and their

international competitiveness. Farmers just receive one-fourth of consumers’ price, whereas

lion’s share goes to other market traders. In order to lower the shares of middlemen in

consumer’s rupee, access to credit and market information, control over the output losses,

improvements in market infrastructure and cheaper availability of transport and packing

material is needed. Fruit markets are not perfectly competitive. There is a need to improve

efficiency and effectiveness to promote export of fruits. A product-specific market

development strategy needs to be initiated with the active participation from the production

and marketing systems.

Basavaraja et al. (2007) use tabular analysis to estimate the post-harvest losses at

different stages, and functional analysis has been used to assess the influence of socio-

economic factors on postharvest losses at the farm level. It has been found that about 75 per

cent of the total post-harvest losses occur at the farm level and about 25 per cent at the

market level. The post-harvest losses at farm level have been observed as 1.68 q/ha in rice

and 0.45 q/ha wheat. On per farm basis, these have been estimated to be 4.20 quintals in rice

and 1.01 quintals in wheat. The storage losses at different stages have added up to about

35.80 per cent of the total post-harvest losses in rice and 33.52 per cent in wheat, while

harvesting and threshing operations together have accounted for about 17 per cent of total

losses in both the crops. Transit losses at different levels have been important component of

post-harvest losses, contributing to about 20 per cent of the total losses. The functional

analysis has revealed that education level of farmers and bad weather conditions influence

the post-harvest losses significantly at farm level in both the food grains, while inadequate

availability of labour and faulty storage method influence the post-harvest losses positively

and significantly in rice and wheat, respectively.

Gangwar et al. (2007) reported that the aggregate post harvest losses from orchard to

consumers in Kinnow in two different and distant markets ranges from 14.84 percent in

Delhi market to 21.91 percent in Bangalore market. They estimates the post harvest losses

using a modified formula and said that inclusion of marketing loss in the estimation of

marketing margins, price spread and efficiency indicated that the old estimation methods

unduly overstates the farmer’s net price and profit margins to the market middle man. The

results had emphasized that efforts should be made to adopt improved packaging techniques,

cushioning material and cold storage facilities at retail level.

Ilyas et al. (2007) said that apples and banana are transported from localities of

production to far off places for marketing and consumption. Both fruit being succulent are

liable to damage and deterioration during harvesting, transportation, marketing, storage and

consumption, if not properly handled. Total losses in the apples transported from Quetta,

Swat and Murree to Faisalabad market during the months of August, September and

November were found to be 23, 20 25 percent respectively. In apples kept under the

conditions of cold storage for 22 weeks losses were found to be 28 percent. The fungi

isolated from rotten apples were Aspergillus niger, A. fumigatus, Alternaria tenuis, A.

tenuissima,Cladosporiums herbarum, Helminthosporium tetramera, Mucor racemosus,

Penicillium expansum, Pencillium italicum and Rhizopus nigricans. The pathogenecity test

revealed that Alternaria tenuis,Aspergillus niger and Rhizopus nigricans were pathogenic to

both injury inoculated and non injured inoculated apple fruits. Total losses in banana

transported from Nawabshah, Mirpur Khas and Hyderabad to Faisalabad market in the

months of December, February and March amounted to 37, 39 and 43 percent respectively.

The fungi isolated from rotten banana were Aspergillus fumigatus, Alternaria

tenuis,Botryodiplodia theobromae, Colletotrichum musae, and Verticillium theobromae. All

these fungi expect A.fumigatus were found to be pathogenic both to injury and non injury

inoculated banana fruits.

Murthy et al. (2007) reported the post-harvest losses at different stages of marketing

and their impact on farmers’ net price, marketing costs, margins and efficiency. The post-

harvest losses were as high as 28.84 percent in the wholesale channel; comprising 5.53

percent at the field and assembly level, 6.65 percent at the wholesale level and 16.66 percent

at the retail level. These losses in the co-operative marketing channel were 18.31 percent

with 7.82, 1.77 and 8.72 percent in the corresponding stages. The losses in co-operative

channel were higher in the first stage of handling, i.e. assembly level and lower in the later

stages of marketing. The losses at the field and assembly levels accounted for as high as 42

percent of the total loss in the cooperative channel compared to about 19 percent in the

wholesale channel. Losses at wholesale and retail stages in the wholesale channel accounted

for 23 percent and 58 percent, respectively, compared to 10 percent and 48 percent in co-

operative channel. Better loading and transportation, less handling and acceptance of good

quality produce at the time of procurement contributed to the lower losses at the later stages

of marketing in the co-operative channel. Further, market-wise analysis revealed that the

losses were higher during retailing than in other stages of marketing. In the cooperative

channel, postharvest losses at the retail level accounted for 48 percent, while it was 58

percent in the wholesale channel. By separating out marketing loss at each stage of

marketing, the actual margins of intermediaries have been estimated. It has been observed

that the existing methods tend to overstate the farmers’ net price and margins of the

intermediaries. In fact, the margin of the retailers’ after accounting for the physical losses

during retailing has been found to be negative (loss), which was otherwise positive (profit) in

the conventional estimation.

Chohan and Ahmad (2008) studied the use of post harvest technologies by the tomato

growers in AJK. They reported that tomato growers in the study area were not following post

harvest technologies that include; grading, packaging, pre-cooling, storage and

transportation. The major reason being is that the growers are not well conversant with these

technologies. They are more familiar and inclined towards traditional methods post harvest

handling of the produce. It is envisaged that growers could improve their returns in case they

avoid post harvest losses to a greater degree by adopting these technologies. Bulk of tomato

surplus produce was marketed through local market (75 percent). A small quantity (25

percent) was marketed through wholesale market. The market margin tends to be lower in the

local as compared to the wholesale market.

Gajanana et al. (2008) reported that Papaya cv. Taiwan 786 was introduced in Andhra

Pradesh, India some 10 years ago which is now spread to different parts of the country. Most

of the papaya produced from this region is marketed at Bangalore and during this process,

heavy post harvest loss occurs. Lack of information on post harvest handling and marketing

practices; associated losses occurring at different stages of handling and their implications on

marketing efficiency and availability necessitated the genesis of this study. The results

revealed that the total post harvest loss (PHL) in papaya produced in Ananthpur district of

Andhra Pradesh and marketed in Bangalore of Karnataka state worked out to 25.49 percent

consisting of 1.66 percent at filed level, transit loss of 4.12 percent and ripening loss of 8.22

percent at the market level and 11.49 percent at the retail level. At the field level, the losses

were mainly due to immature and small size of fruits, malformation and harvesting injury. At

the market level, bruises and pressing injury caused transit loss. Anthracnose and fruit rot due

to Alternaria and Phytophthora were the main causes of loss during ripening. Rotting of

fruits was the main reason for loss during retailing. Marketing system for papaya was not

found to be efficient as the efficiency index was less than 1.00. The producer’s share was as

low as 26 percent and the inclusion of PHL as another component of marketing cost would

add to inefficiency of the marketing system as it reduced the efficiency index further and the

price spread would have been just 57 percent without the PHL. There is a need to reduce the

PHL and improve the availability through the recommended pre and post harvest treatments

and better handling and storage to improve the marketing efficiency in papaya.

Jabir and Sanjeev (2008) studied the perceptions of farmers about risks in production

of fruits and vegetables have been analyzed using structured survey method. The study is

based on the survey of a total of 634 farmers, comprising 188 fruit farmers and 446 vegetable

farmers, covering six districts of Uttar Pradesh, namely, Lucknow, Allahabad, Gorakhpur,

Moradabad, Jhansi and Agra. The perceived priorities of farmers about major sources of risks

in production of fruits and vegetables have been reported under ‘investment risks’, ‘socio-

economic risks’, ‘environmental risks’, ‘production risks’ and ‘market risks’. In general, the

price and production risks have been perceived as the most important sources of risk in

production of fruits and vegetables in the area. The study has argued that public intervention

can facilitate better risk management through improved information system, development of

financial markets and promotion of market-based price and yield insurance schemes, thus

ensuring that the marginal farmers are able to benefit from these interventions as well as

participate in the emerging systems.

Adeoye et al. (2009) reported that more men were involved in wholesaling of tomato

while more women were involved in retailing of tomato. Most of the respondents have been

in the business for more than 10 years. The major causes of economic losses to tomatoes

were physiological, pathological and mechanical damages. In the UC82B variety,

pathological damage constituted the greater percentage (44 percent) of losses; while the

greatest cause of damage in Roma and VT563/JM94/47 was physiological and was put at 44

percent and 36 percent respectively. Ibadan local suffered the highest kind of damage traced

to mechanical factors to the tune of 39 percent. There was a significant difference (p<0.05) in

the mean percentage damage of UC82B compared to the three other tomatoes varieties

(P<0.05), while there was no significant (p>0.05) difference between mean percentage

damage of VT563/JM94/47 and Ibadan local varieties. Based on the losses in the marketing

margin, there was reduction of 34% in marketing margin of UC82B, Roma 85 percent,

VT563/JM94/47, 94 percent and Ibadan local 79 percent at the retail level. Provision of

improved mode of transportation and storage, is thereby recommended to minimize losses in

tomatoes.

Ayandiji et al. (2009) explained the reasons of post harvest losses in their study of

gross margin analysis of post harvest losses of citrus in Nigeria. Losses from harvest, market

and transportation constituted 14.4 percent of the possible total revenue. The result of the

gross margin analysis shown that 7.8 percent of the respondents had a negative gross margin

without taking into account losses, while 36.7 percent of the respondents had a negative gross

margin when losses was considered. It had been observed that a lot of citrus fruits are wasted

annually due to poor harvesting, high cost of carrying, inappropriate treatment, poor

marketing facilities and too little processing factories as well as poor processing services

among others. Respondents did not have high-quality packaging and handling culture during

movement of the citrus fruits. They also load the citrus fruits in bags or pour them by baskets

into the vehicles and this is responsible for high loss.

CHAPTER 3

MATERIALS AND METHODS

Approximately 95 percent of the total citrus fruit in Pakistan is produced by Punjab

province. The citrus (Kinnow) production belt in Punjab province comprises of districts

Sargodha, Toba Tek Singh, Multan, Rahim Yar Khan, Sahiwal, Lahore, Sialkot, Jhang,

Mianwali and Gujranwala. The main reason behind this is the natural climatic conditions and

soil that is more suitable for kinnow production than any other crop. Government policies to

facilitate water supply and pesticide technology have encouraged the growers to expand area

under orchard. Relatively more cash income as compared to other crops and inherited

occupation were however, the major reasons to grow kinnow orchard.

3.1 Selection of the Study Area

The study was confined to the one of the major kinnow producing district of Punjab

i.e. Sargodha on the basis of its higher share in acreage, production and taste in Punjab. Study

conducted in this district can be fairly representative for the Punjab province. Only Sargodha

district have a lion share of kinnow in area and production in Punjab.

3.2 Selection of the Basic Sampling Unit

For the present study, two tehsils of Sargodha i.e. Bhalwal and Kot Moman were

selected. These two tehsils were selected on the basis of their importance in kinnow

production and easy accessibility.

3.3 Selection of the Producers/Contractors

Twenty kinnow producers/contractor) were selected from each tehsils randomly. The

orchards of producers/contractors were stratified into small, medium and large size based on

the criteria followed by Ahmad, 1989.

a) Small size orchard < 8 acres

b) Medium size orchard 8-16 acres

c) Large size orchard >16 acres

In total forty kinnow orchards were selected from selected tehsils at random in such a way

that:

a) No. of producers/contractors having small size orchards 17

b) No. of producers/contractors having medium size orchard 12

c) No. of producers/contractors having large size orchard 11

Total 40

3.4 Selection of the Wholesalers

Twenty wholesalers from each tehsil fruit and vegetable market were selected at

random. There were almost 50 wholesalers dealing with kinnow in each of tehsil fruit and

vegetable market, out of which 20 wholesalers were selected from each market randomly.

3.5 Selection of the Retailers

Two types of retailers were found i.e. stallholders (shopkeepers) and hawkers. A

sample of 10 stallholders and 10 hawkers were selected from each district at random for

collection information. In total 20 hawkers and 20 stall holders were selected at random from

both the tehsils.

3.6 Data Collection

Separate questionnaires were prepared for each category of respondents and personal

interview method was used to collect relevant information and to identify variables on pre-

tested questionnaire.

3.7 Analysis of Data

a) Descriptive Statistics

The data thus collected was tabulated in the form of tables and percentage and

average method was used to explain the 1st objective of the study i.e. to estimate the post

harvest losses of kinnow at farm, transportation and market, and retail level.

(a) Simple arithmetic mean, A.M. = X/N

Where: - X = summation of all values

N = total number of items

(b) Percentage losses at different stages of handling at each respondent category

= {(Kg/40Kg)/40} * 100

Where: - Kg/40Kg = losses in Kgs at the specified handling stage in 40 Kg

(mound) of produce. These stages include picking, carrying from

orchard to grading/packing place, grading and packing etc.

(c) Percentage losses at each respondent category = ∑ Li

Where: - ∑ Li = summation of percentage losses at all handling stages of

specified respondents category. These respondent categories included

producer/contractor, wholesaler and retailers.

b) Analytical Model

To study the impact of different determinants involved in citrus post harvest losses,

multiple linear regression model will be used. As most of the past studies only use

descriptive analysis like Ayandiji et al., 2009, Gangwar et al., 2007, Murthy et al., 2007 etc.

Only a couple of studies are conducted so far in which econometric model was used to

estimate post harvest losses in fruits at producer/contractor level i.e. Bari, 2004 and

Basavaraja et al., 2007. In this study we will develop three different multiple linear

regression models for three different levels of post harvest losses (farm, transportation and

wholesale market and retail levels) with descriptive analysis.

So, the three models for three different levels are as under:

At Farm Level

The general form of the function at farm level is as follows:

Losses = f (Edu, Exp, Os, Pt, Pm)

Double log model was used for analysis because it gives direct elasticities and results of this

functional form were more reliable than simple one. So the specific model used was

LnL1 = β0 + β1 LnEdu + β2 LnExp + β3 LnOs + β4 Pt + β5 Pm + ε

Where;

L1 = Quantity of post harvest losses in Kgs at farm level;

Edu = Education of respondent in years;

Exp = Experience of respondents in years;

Os = Orchard size of the respondent in acres;

Pt = Picking Time (Dummy variable);

Character assigned value

Morning 1

Evening 0

Pm = Picking method (Dummy variable)

Character assigned value

With Scissor 1

Manual 0

ε = Disturbance term

t-statistics was used to test the significance of these factors in post harvest losses of kinnow

at farm level.

At Transportation and Market Level

The general form of the function at transportation and market level is as follows:

Losses = f (Edu, Exp, Ttrans, Itrans, Lm, Sp)

So the specific model used was

LnL2 = β0 + β1 LnEdu + β2 LnExp + β3 Ttrans + β4 Itrans + β5 Lm+ β6 Sp + ε

Where;

L2 = Quantity of post harvest losses in Kgs at transportation and market level;

Edu = Education of respondent in years;

Exp = Experience of respondents in years;

Ttrans = Type of transportation (Dummy variable);

Character assigned value

Truck/Mazda 1

Other 0

Itrans = Infrastructure of transportation (Dummy variable);

Character assigned value

Metallic Road 1

Non-metallic Road 0

Lm = Loading method (Dummy variable);

Character assigned value

Stacking of boxes 1

Open loading 0

Sp = Storage place (Dummy variable);

Character assigned value

Cold storage 1

Normal storage 0

ε = Disturbance term

At Retail Level

The general form of the function at retail level is as follows:

Losses = f (Exp, USqt, Tr)

So the specific model used was

LnL3 = β0 + β1 LnExp + β2 LnUSqt + β3 Tr + ε

Where;

L3 = Post harvest losses in Kgs at retail level;

Exp = Experience of respondent in years;

USqt = Unsold quantity on daily basis in Mds;

Tr = Type of retailer (Dummy variable);

Character assigned value

Shopkeeper 1

Hawker 0

ε = Disturbance term

CHAPTER 4

RESULTS AND DISCUSSION

This chapter mainly deals with the post harvest losses occurring at production,

marketing and retail levels of kinnow. Kinnow production involves picking, cleaning,

standardization, grading, packing, transportation and loading/unloading. Kinnow marketing

and retailing also involves loading/unloading, transportation, cleaning, grading, storage etc.

Kinnow post harvest losses take place at all these stages and have been quantified and

discussed in this chapter. The various factors contributing to these losses have been discussed

with their significance. A regression function has been used to show major factors causing

kinnow post harvest losses and to calculate the level of significance of these factors on

kinnow post harvest losses. Lay out of the chapter on results and discussion is as follows;

1. Marketing channel of Kinnow

2. Past trend in Area and Production of Citrus in Pakistan

3. Quantitative post harvest losses of kinnow at farm, transportation and market, and

retail levels

4. Factors causing post harvest losses of kinnow at farm, transportation and market,

and retail levels

5. Conclusion

4.1 Marketing channel of kinnow

The most common kinnow-marketing channel through which kinnow fruit passes

from producer to consumer in the study area was as under:

Producer Contractor Wholesaler Retailer Consumer

4.1.1 Producer/Pre-harvest Contractor

(a) Producer

The process of kinnow production and marketing starts with the producer/grower.

Producer undertakes the primary grading or selection, first handling and packaging, performs

the first transportation to the marketing and bears all the losses taking place at these stages.

But a large majority of the kinnow growers i.e. 90 percent sold the harvesting rights of their

orchards to contractors at the flowering stage. Only 10 percent sold their produce directly to

market themselves, mainly in the hope of getting better prices.

(b) Reasons of pre-harvest sale

The main reason for sale of pre-harvest contractor was lack of time, labour,

transportation problems and to avoid risk and uncertainties. Kinnow orchard owners were

growing crops in addition to kinnow. Therefore, they didn’t spare time and labour for

marketing of kinnow fruit and preferred to sell an orchard to a contractor. Moreover, the

labour they had is not trained specifically for picking and packing of fruit and lack of

transportation facilities also compelled them to sell standing orchard to contractor. Another

reason for pre-harvest sale was that, the kinnow producers did not want to be involved in the

complications of marketing system and avoided the risk of price and income variation,

uncertainties in production and post harvest losses inherent with this marketing system.

(c) Pre-harvest Contractor

Pre-harvest contractor purchases the fruit crop from the producer, in advance of the

majority stage and sells in the market at maturity. He has more information about the

marketing conditions and prices than the producer. While contracting an orchard the

contractor estimates its yield and considers the expected cost to be incurred for supervision,

labour, transportation and marketing.

Contractor after purchasing the standing orchards engaged in same activities like

picking, packing, storage, transport and marketing activities and bear losses at all these stages

as done by the producer if he had not sold to the contractor. So the same pattern was

followed for the producer and contractor with regard to post harvest losses occurring during

all these stages at farm level.

4.1.2 Wholesaler

Wholesaler buys and sells large quantities of farm products. He deals in several

commodities within interregional markets and also supplies produce to processing industries,

exporters and retailers according to their demand. Wholesaler usually purchases fruit from

the commission agents at auction floor and sells in smaller quantities to retailers and

consumers. He generally occupies a site or a place where buying and selling takes place at

market place, does some grading, standardization and cleaning and then sells to buyer.

4.1.3 Retailers

Retailers usually indicate a final link between producer and consumers. They buy

and sell small quantities according to the demand of consumers in the area. Two types of

retailers were generally found in case of kinnow fruit. The shopkeeper occupied their own or

hired fixed small shops in the main market or in the town. While hawkers were selling fruits

in baskets or hand carts and were usually mobile.

4.2 Past trend in area and production of citrus in Pakistan

In Table 4.1, area and production of citrus in Pakistan is shown from 1985-86 to

2007-08 and in Table 4.2, area and production of citrus in Punjab province is shown from

1997-98 to 2007-08.

The trend in area and production of citrus in Pakistan has been shown in the graphs

that 24 percent area increased from 1985-86 to 2000-01 and production is increased by 28

percent from 1985-86 to 1996-97.

Table 4.1: Area and Production of Citrus in Pakistan

Year Area (' 000' hectares) Production (' 000' tonnes)

1985-86 149.7 1434.4

1986-87 153.5 1467.1

1987-88 158.8 1411.3

1988-89 170.2 1565.1

1989-90 171.1 1576.3

1990-91 173.3 1609.1

1991-92 176.2 1629.8

1992-93 176.2 1665.3

1993-94 185 1849.4

1994-95 190.7 1932.8

1995-96 193.6 1959.5

1996-97 194.4 2002.6

1997-98 196.1 2037

1998-99 197 1861.5

1999-2000 197.7 1943.2

2000-01 198.7 1897.7

2001-02 194.2 1830.3

2002-03 181.6 1702.3

2003-04 176.5 1760.3

2004-05 183.8 1943.7

2005-06 192.3 2458.4

2006-07 193.2 1472.5

2007-08 199.4 2294.5

Source: Government of Pakistan, 2007-08

Table 4.2: Area and Production of Citrus in Punjab Province

Year Area in '000 hectares Production in '000 tonnes

1997-98 185.4 1946.5

1998-99 186.1 1769.2

1999-2000 186.8 1859.2

2000-01 187.6 1812.9

2001-02 183.2 1751.0

2002-03 170.8 1623.6

2003-04 166.6 1688.7

2004-05 173.9 1872.2

2005-06 182.1 2385.1

2006-07 183.3 1400.7

2007-08 189.2 2219.3

Source: Government of Pakistan, 2007-08

Figure 4.1: Area of Citrus in Pakistan from 1985-86 to 2007-08

Figure 4.2: Production of Citrus in Pakistan from 1985-86 to 2007-08

4.3 Quantitative post harvest losses of kinnow

Kinnow post harvest losses have been divided in three categories in this study which are as

under;

1) Losses at farm level

2) Loses at wholesale market level

3) Losses at retail level

4.3.1 Total post harvest losses of kinnow in the marketing channel

Total post harvest losses of kinnow at farm, wholesale market and retail level were 45

percent of the total produce. Losses at farm level were maximum i.e. 32.4 percent of the total

produce and 72 percent in total losses in kinnow. Table 4.3 and fig. 4.3 shows the percentage

share of losses in total produce and in total post harvest losses of kinnow. These results are

similar like Adeoye, et al., 2009, Admassu, 2003, ASET, 2003, Bari, 2004, Bassapa, et al.,

2007, Basavaraja, et al., 2007, Chaudry, 1980, FAO, 1989, Gajanana, et al., 2008, Gangwar,

et al. Al., Ilyas et al., 2007, IARI, 2003, Leghari, 2001, Liu, 1990, Mohyuddin, 1998,

Murthay et al., 2007, Yuen and Teng, 2003.

Table 4.3: Percentage shares of farm, market and retail level losses in total produce and total losses of kinnow

LevelsPercentage share in total

produce of kinnow

Percentage share in total

losses of kinnow

At Farm Level Losses 32.4 72

At Wholesale Market Level

Losses11.2 24.9

At Retail Level Losses 1.4 3.1

Total 45 100

Farm Level Losses, 72%

Wholesale Market Level Losses, 25%

Retail Level Losses, 3%

Figure 4.3 Percentage share of farm, market and retail level losses in total post harvest

losses of kinnow

4.3.2 Losses at Farm Level

Table 4.4 shows that total losses of kinnow during picking, carrying, packing and

grading and transportation stages were estimated as 32.4 percent of the total produce. From

these losses at farm level, picking losses 60.5 percent of the total losses at farm level.

Similarly losses of carrying from picking place to grading/packing place and during grading

and packing were 10.8 and 6.8 percent of the total losses at farm level respectively. 21.9

percent kinnow of the total losses at farm level were lost during loading and transportation as

shown in the Table 4.4. Results also similar like Udas, et al., 2005, Subrahmanyam, 1986,

Sing and Jain, 2006, Parpia, 1978, PARC, 1986, Hussain, et al., 2004, FFTC, 1993, Dendy,

1978, Ayandiji et al., 2009.

Table 4.4: Losses of kinnow incurred at farm level during picking, carrying, grading, packing and transportation

ItemDuring

Picking

During grading

and packing

During

carrying

During loading

and

transportation

Total

% age share of

Losses in total

produce

19.55 3.5 2.2 7.1 32.4

%age share of

losses in total losses

at farm level

60.5 10.8 6.8 21.9 100

(a) Personal characteristics of kinnow producer/contractor

Table 4.5 shows the personal characteristics of producers/contractor. Average age of

the respondents is 44 years and education has about 8 years. Respondents have about 16

years of orchard experience in the study area. 55 percent of the growers belong from business

family background and 35 percent from agriculture. 60 percent of the growers have no

partnership for orchard business.

Table 4.5: Personal characteristics of kinnow producer/contractors

Sr. No. Characteristics Mean Std. Deviation

1 Respondent's Age 44.3 12.4

2 Education (Schooling Years) 8.7 3.3

3 Orchard Experience (Years) 16.2 8.2

4 Family Background (Percent)

Agriculture 35.0 -

Business 55.0 -

Service 10.0 -

5 Partnership (Percent)

Yes 40.0 -

No 60.0 -

(b) Orchard related characteristics

Table 4.6 shows that total orchard size in the study area was about 179 acres. Number

of plants per acre was about 94 and yield per tree was about 3 mounds. Growers had

production cost of Rs. 14412 per acre. About 97 percent contactors had contract duration of

one year. About 63 percent of the respondents had started the contract at fruit formation stage

and only 5 percent at harvesting stage.

Table 4.6: Orchard related characteristics

Sr. No. Characteristics Mean Std. Deviation

1 Total Orchard Size (Acre) 178.7 117.4

2 No. of Plants / Acre 93.8 5.8

3 Yield/Tree (Mds) 3.3 0.99

4 Production Cost (Rs/Acre) 14412.5 1705.5

5 Contract duration (percent)

One year 97.5 -

Two year 2.5 -

6 Contract stage (percent)

Flowering 32.5 -

Fruit formation 62.5 -

Harvesting 5.0 -

(c) Sale quantities and Sale prices

Table 4.7 gives an insight about the sale quantities and sale prices of kinnow. Sale

quantity in mid season was high i.e. about 16350 mounds than early season (8697 mds) and

late season (6791 mds). Growers were get more returns in late season sales i.e. sale price in

late season was about Rs. 642 per mound higher than the sale prices in early and mid season.

Table 4.7: Sale quantities and sale prices of kinnow

Sr. No. Items Mean Std. Deviation

1Early Season Sale (Qty) in Mds for

Kinnow8696.9 6426.7

2Early Season Sale Price in Rs/Md for

Kinnow603.2 147.0

3Mid Season Sale (Qty) in Mds for

Kinnow16350.2 14442.8

4Mid Season Sale Price in Rs/Md for

Kinnow527.9 110.9

5Late Season Sale (Qty) in Mds for

Kinnow6791.0 5669.3

6Late Season Sale Price in Rs/Md for

Kinnow642.4 135.1

(d) Harvest losses

Table 4.8 shows the harvest (picking) losses. On an average 195 mounds quantity

picked at one time lot and from which 10 mounds were discarded during picking. There is

about 1.9 mounds kinnow that were lost completely and 7.5 mounds partially lost. So the

total loss during picking was about 9.5 mounds and the value of this total loss was about Rs.

5615. Most of the kinnow lost due to cuts and bruise i.e. 30.0 and 22.5 percent. About 95

percent of the growers used scissor for picking of kinnow fruit as scissor cause less injuries

and cuts to fruit and losses was minimized. 90 percent skilled labour was used for picking of

the fruit from tree, grading and packaging.

Table 4.8 Harvest Losses

Sr. No. Items Mean Std. Deviation

1 Qty. Picked One Time lot (Mds) 195.4 87.2

2 Quantity Discarded (Mds) 10.1 5.7

3 Complete Loss (Mds) 1.9 1.9

4 Partial Loss (Mds) 7.5 6.6

5 Total Loss (Mds) 9.5 6.4

6If partial Loss, decrease in Value

(percent)50.6 10.4

7 Sale Price (Rs/ Mds) 591

8 Value of complete loss (Rs) 1122.9

9 Value of partial loss (Rs) 4432.5

10 Total value of loss (Rs) 5614.5

11 Type of losses (percent)

Cuts 30.0 -

Bruise 22.5 -

Pressed 17.5 -

Injury 17.5 -

Latex 5.0 -

Other 7.5 -

12 Method of Picking (percent)

Scissor 95.0 -

Hand 5.0

13 Labour used for picking (Percent)

Skilled 90.0 -

Ordinary 10.0 -

(e) Post harvest losses during carrying from picking to grading/packing place

Total post harvest losses during carrying from picking to grading/packing place were

about 3.5 mounds, in which 0.61 mounds were completely lost and 1.7 mounds of kinnow

lost partially as depicted in Table 4.9. 37 percent decrease in value due to partial loss. In

short total value of loss was about Rs. 2068. About 47 and 27 percent kinnow was pressed

and injured respectively during carrying. About 70 percent of the respondents had used

plastic crates for carrying of fruit and 15 and 12 percent use wooden baskets and palli for

carrying. About 75 percent skilled labour used for carrying the produce from field to

grading/packing place.

Table 4.9 Post-harvest losses during carrying from picking to grading/packing place

Sr. No. Items Mean Std. Deviation

1 Qty. Picked One Time lot (Mds) 195.4 87.2

3 Complete Loss (Mds) 0.6 0.9

4 Partial Loss (Mds) 1.8 1.1

5 Total Loss (Mds) 3.5 4.0

6 if Partial loss, decrease in Value (Percent) 36.9 17.2

7 Sale Price (Rs/ Mds) 591 -

8 Value of complete loss (Rs) 360.5 -

9 Value of partial loss (Rs) 1063.8 -

10 Total value of loss (Rs) 2068.5 -

11 Type of losses (Percent)

Cuts 7.5 -

Bruise 10.0

Pressed 47.5

Injury 27.5 -

Latex 7.5 -

12 Type of material used for packing (Percent)

Wooden Basket 15.0 -

Plastic Crates 70.0

Palli 12.5 -

Other 2.5 -

13 Labour used for carrying (Percent)

Skilled 75.0 -

Ordinary 25.0 -

(f) Post harvest losses during grading and packing

Table 4.10 reported the post harvest losses during grading and packing. Total loss

was about 2.2 (0.6 mds complete loss and 1.7 mds partial loss) mounds during grading and

packing and 35 percent value was decreased due to partial loss. So the total value of loss was

about Rs. 1300. About 45 and 33 percent produce lost due to pressing and bruise during

grading and packing. As size, shape and quality of fruit greatly depended on the packaging

method and packaging material. So fine wooden basket is the best material for packing.

Results shows that 35 percent respondents were used fine wooden basket for packing and

about 32.5 and 27.5 percent respondents used palli and plastic crates for packing of fruit. As

proper and good packing had a great role in the quality of fruit. So, 85 percent skilled labour

was used for packing so that standard of quality packing should be achieved.

Table 4.10 Post-Harvest losses of kinnow during grading and packing

Sr. No. Items Mean Std. Deviation

1 Qty. Picked One Time lot (Mds) 195.4 87.2

2 Complete loss (Mds) 0.6 0.5

3 Partial Loss (Mds) 1.7 0.9

4 Total Loss (Mds) 2.2 1.2

5 If Partial loss, decrease in Value (Percent) 35.2 16.2

6 Sale Price (Rs/ Mds) 591

7 Value of complete loss (Rs) 362.0

8 Value of partial loss (Rs) 1004.7

9 Total value of loss (Rs) 1300.2

10 Type of losses (Percent)

Cuts 12.5 -

Bruise 32.5 -

Pressed 45.0

Injury 7.5 -

Latex 2.5 -

11 Packing material used (Percent)

Fine wooden basket 35.0 -

Plastic crate 27.5 -

Palli 32.5

Other 5.0 -

12 Labour used for grading/packing (Percent)

Skilled 85.0 -

Ordinary 15.0 -

(g) Post harvest losses of kinnow during loading and transportation

Total losses during loading and transportation were about 7.1 mounds as depicted in

Table 4.11. Total value of loss was about Rs. 4196 and 42 percent value decreased due to

partial loss. About 35, 25 and 22.5 percent fruit was lost due to injury, pressed and bruise

respectively. About 37.5 percent respondents used mazda for the transportation of kinnow

while 45 percent used other type of vehicle for transportation. About 68 percent respondents

used stacking of boxes method for loading of kinnow and about 73 percent roads of the study

area were metallic.

Table 4.11:Post-Harvest losses of kinnow during loading and transportation

Sr. No. Items Mean Std. Deviation

1 Complete Loss (Mds) 1.9 2.6

2 Partial Loss (Mds) 5.1 5.4

3 Total Loss (Mds) 7.1 7.4

4 If Partial loss, decrease in Value (Percent) 42.6 16.9

5 Sale Price (Rs/ Mds) 591 -

6 Value of complete loss (Rs) 1122.9 -

7 Value of partial loss (Rs) 3014.1 -

8 Total value of loss (Rs) 4196.1 -

9 Type of losses (Percent)

Cuts 12.5 -

Bruise 22.5 -

Pressed 25.0 -

Injury 35.0 -

Latex 5.0 -

10 Type of transport used (Percent)

Truck 12.5 -

Mazda 37.5 -

Pick Up 5.0 -

Other 45.0 -

11 Loading Methods used (Percent)

Stacking of boxes 67.5 -

Open loading 25.0 -

Other 7.5 -

12 Infrastructure of transportation (Percent)

Metallic Road 72.5 -

Non-Metallic Road 27.5 -

4.3.3 Losses at Wholesale Market Level

Total losses at wholesale market level were about 11.2 percent of the total produce.

During unloading and marketing 55.4 percent of the total losses at market level was occurred

and 44.6 percent during storage as shown in Table 4.12.

Table 4.12: Losses of kinnow incurred at wholesale market level during unloading and marketing and storage

ItemsDuring Unloading

and MarketingDuring Storage Total

% age share of Losses in total

produce6.2 5.0 11.2

%age share of losses in total

losses at farm level55.4 44.6 100

(a) Personal characteristics of Wholesalers

Table 4.13 shows that most of the respondents had in age bracket of about 40 years.

Education level of the respondent was about 8 years of schooling. Business experience of

respondents was about 18 years. About 55 percent of the respondents had belongs from

business background and 45 percent from agriculture. About 74 percent of the wholesalers

had no partnership.

Table 4.13: Personal characteristics of wholesaler

Sr. No. Characteristics Mean Std. deviation

1. Age (years) 39.8 9.5

2. Education (years) 7.6 3.7

3. Business experience (years) 17.7 7.6

4. Family background (Percent)

Agriculture 45.0 -

Business 55.0 -

Other - -

5. Partnership (Percent)

Yes 26.2 -

No 73.8 -

(b) Sale quantities and prices of kinnow

As Table 4.14 indicates that mid season sales and prices were very high i.e. about 271

mounds Rs. 655 respectively. Early season and late season sale quantities were about 120 and

141 mounds respectively. Also early and late season sale price was about Rs. 610 and Rs.

654 respectively.

Table 4.14: Sale quantities and prices of kinnow

Sr. No. Items Mean Std. Deviation

1. Early season sale (Mds) 120.2 223.2

2. Early season price (Rs/ Mds) 609.8 86.2

3. Mid season sale (Mds) 270.9 718.2

4. Mid season price (Rs/ Mds) 655.4 94.8

5. Late season sale (Mds) 141.2 286.8

6. Late season price (Rs/ Mds) 653.9 188.1

(c) Expenditures of Wholesalers

Table 4.15 tells us about the expenditures of wholesaler. Results show that carrying

charges from auction floor to own floor was about Rs. 5.4 per mound. Auction charges were

about Rs. 9.4 per mounds. Monthly rent of the floor was about 10975 Rs. Daily expenditure

of the wholesaler was about Rs. 390.

Table 4.15: Expenditures of Wholesalers

Sr. No. Items Mean Std. Deviation

1.Carrying Charges from Auction Floor

to Own Floor (Rs/Mds)5.4 3.6

2. Auction Charges if (Rs/Mds) 9.4 1.8

3. Monthly Rent of the Floor (Rs) 10975.0 4410.0

4. Daily expenditures 390.0 92.8

(d) Post harvest losses of kinnow at wholesale level

Table 4.16 shows the post harvest losses of kinnow at wholesale level. About 6.2

mounds of kinnow lost during marketing in which 3.7 and 3.8 mounds were complete and

partial loss. 47 percent value of produce decreased due to partial loss. Total value of loss was

about Rs. 3681. About 62 and 21 percent of the produce was lost due to pressed and injury.

Table 4.16: Post-Harvest losses of kinnow at wholesale level

Sr. No. Items Mean Std. deviation

1. Complete loss (Mds) 3.7 8.9

2. Partial loss (Mds) 3.8 3.2

3. Total loss (Mds) 6.2 5.7

4. If partial loss, decrease in value (Percent) 47.4 13.4

5. Sale price (Rs/ Mds) 591 -

6. Value of complete loss (Rs.) 2186.7 -

7. Value of partial loss (Rs.) 2245.8 -

8. Total value of loss (Rs.) 3681.9 -

9. Type of losses (Percent)

Cuts 9.5

Bruise 7.2

Pressed 61.9 -

Injury 21.4 -

(e) Losses of kinnow during storage at wholesale level

Wholesalers sometimes store the fruit for future sale. The storage duration may be for

some days or some weeks. There are two methods of storage, one is cold storage and second

is normal storage. Table 4.17 shows the losses during storage. About 9 mounds of the fruit

were lost during storage. There was 18 percent decrease in value due to partial loss. Total

value of loss was about Rs. 5319. Duration of storage was about 2 days. About 69 percent

fruit was stored at normal conditions and 31 percent stored at cold conditions. During storage

about 38 and 37 percent losses were due to spot and rotening and 26 percent remain unripe.

Table 4.17: Losses during storage at wholesale level

Sr. No. Items Mean Std. deviation

1. Complete loss (Mds) 3.8 5.9

2. Partial loss (Mds) 5.2 10.0

3. Total loss (Mds) 9.0 14.5

4. If partial loss, decrease in value (Percent) 18.0 25.4

5. Sale price (Rs/ Mds) 591 -

6. Value of complete loss (Rs.) 2245.8 -

7. Value of partial loss (Rs.) 3073.2 -

8. Total value of loss (Rs.) 5319.0 -

9. Duration of storage (Days) 1.8 1.7

10. Storage Place (Percent)

Cold 31.0

Normal 69.0

9. Type of losses (Percent)

Spot 37.8

Rotening 36.0

Un Ripe 26.2 -

4.3.4 Losses at Retail Level

Total losses at retail level were about 1.4 percent of the total produce. About 50

percent share in total retail level losses was of unsold quantity as shown in Table 4.18.

Table 4.18: Losses of kinnow incurred at retail level during retail marketing and unsold quantity

ItemsDuring retail

Marketing

Unsold

QuantityTotal

% age share of Losses in total

produce0.67 0.69 1.4

%age share of losses in total

losses at farm level49.6 50.4 100

(a) Personal characteristics of Retailers

Age bracket of the retailers in study area was about 35 years and had schooling of

about 6 years as depicted in Table 4.19. About 75 percent of the retailers had family

background of business. About 88 percent retailers had no partnership in their business. 60

percent of the retailers run their business in shop while 40 percent were hawkers.

Table 4.19: Personal characteristics of retailers

Sr. No. Characteristics Mean Std. deviation

1. Age (years) 34.9 11.4

2. Education (years) 6.2 3.8

3. Business experience (years) 10.3 8.2

4. Family background (Percent)

Business 75.0 -

Other 25.0 -

5. Partnership (Percent)

Yes 12.5 -

No 87.5 -

6 Type of retailer (Percent)

Shop keeper 60.0 -

Hawker 40.0 -

(b) Purchase and sale quantities and prices

Retailers on an average purchase quantity of 6 mounds at purchase price of Rs. 353

per mound while quantity sell was about 5.7 mounds at price of Rs. 416 per mound as shown

in Table 4.20.

Table 4.20: Purchase and Sale quantities and prices of kinnow

Sr. No. Items Mean Std. Deviation

1. Purchase Quantity in mds 6.0 3.0

2. Purchase Price in Rs/md 352.9 114.6

3. Sale quantity in mds 5.7 2.6

4. Sale price in Rs/md 416.1 136.1

(c) Expenditures of retailers

Table 4.21 tells us about the general expenditure during process. Carrying charges

from market to shop were about Rs. 26 per mound. Monthly rent of the shop was about Rs.

4490 and daily expenditures were about Rs.163.

Table 4.21: Expenditures of Wholesalers

Sr. No. Items Mean Std. Deviation

1.Carrying Charges from market to own

shop (Rs/Mds)25.9 16.9

3. Monthly Rent of the shop (Rs) 4490.0 3844.8

4. Daily expenditures 163.3 136.4

(d) Post harvest losses of kinnow at retail level

In Table 4.22 shows that total losses at retail level were about 1 mounds which

comprises of 0.46 mounds complete loss and 0.66 mounds partial loss. About 44 percent fruit

value decreased due to partial loss. Fruit was spoiled during retail process due to pressing,

rotening, spot, unripe and other factors and share of these were about 25, 17.5, 12.5, 7.5 and

37.5 percent respectively.

Table 4.22: Post-Harvest losses of kinnow at retail levelSr. No. Items Mean Std. deviation

1. Complete loss (Mds) 0.5 0.5

2. Partial loss (Mds) 0.7 0.8

3. Total loss (Mds) 1.1 0.8

4. If partial loss, decrease in value (Percent) 43.9 22.3

5. Sale price (Rs/ Mds) 591 -

6. Value of complete loss (Rs.) 271.7 -

7. Value of partial loss (Rs.) 390.0 -

8. Total value of loss (Rs.) 661.9 -

9. Type of losses (Percent)

Spot 12.5

Pressed 25.0

Rotening 17.5 -

Un ripped 7.5 -

Other 37.5

(e) Daily business volume

On an average about 7.6 mounds volume handled on daily basis by most of the

retailers and about 0.7 mounds quantity remains unsold daily as reported in Table 4.23.

About 75 percent of the retailers had done grading after opening of fruit from packing.

Table 4.23: Daily business volumeSr. No. Items Mean Std. Deviation

1. Volume Handled on daily basis in mds 7.6 8.8

3. Unsold Quantity on daily basis in mds 0.7 0.8

4. Grading after opening

Yes 75.0 -

No 25.0 -

4.4 Factors causing post harvest losses of kinnow at different

levels

Second objective of the study was to identify various factors causing post harvest

losses of kinnow at farm, transportation ad wholesale market and retail levels. Above

statistics shows that post harvest losses were greatest at farm level i.e. about 32 percent of the

total produce. These losses were about 72 percent of total kinnow post harvest losses. It

indicated that major factors causing post harvest losses of kinnow could be identified at the

farm level but the factors at other levels are also have significant impact on post harvest

losses so in this study an effort is made to identify the factors causing post harvest losses at

farm, transportation and wholesale market and retail levels.

4.4.1 At Farm Level

(a) Overall Significance of Model

According to Table 4.25, 40.6 percent of the model was explained by independent

variables i.e. the overall fitness of the model was about 40 percent at farm level. Standard

error of the estimate was about 29 percent. The reason of low R square value was natural and

unexpected events occurred time to time during peak season. Adjusted R square was 31.5

percent.

(b) Analysis of Variance (ANOVA)

ANOVA in Table 4.24 shows that the total sum of squares of model was about 4.65

and regression and residual sum of squares were about 1.88 and 2.76 respectively. F value of

the model at 5 degree of freedom was 4.5 and it is significant at 0.3 percent. So the model is

significant at 0.3 percent.

Table 4.24: Analysis of variance (ANOVA)

Model Sum of Squares df Mean Square F Sig.

Regression 1.887 5 0.377 4.503 0.003a

Residual 2.766 33 0.084

Total 4.653 38

(c) Significance of various factors in post harvest losses of kinnow at farm level

According to the regression results (Table 4.25) the model can be explained in the

following form

LnL1 = 3.839 - 0.211 LnEdu – 0.222 LnExp + 0.214 LnOsize – 0.276 Ptime – 0.477 Pmethod

+ ε

Table 4.25 shows that the post harvest losses at farm level did not significantly

depend upon the education status (significant level of 0.137) of producer or contractor.

Producer or contractor whether illiterate or educated had the almost same level of losses.

Elasticity of education had value of -0.211. Coefficient of experience of producer or

contractor has a value of -0.222 and a significance level of 0.048 showing significant effect

on post harvest losses of kinnow at farm level. Producers or contractor having more

experience in production and harvesting had less losses i.e. one percent experience increased

caused 0.222 percent decrease in post harvest losses at farm level. Orchard area has a

coefficient value of 0.214 and significant level of 0.007 showing significant effect on losses.

As orchard size increases the post harvest losses also increases because the sign of coefficient

was positive. This negative effect of orchard size was due to management problems on the

farm. Picking time is the most important factor. As fruit that are picked at morning is fresher

and have good quality then that is picked on other day round. Picking time had a significant

level of 0.061 and coefficient value of -0.276. This means that picking time is significantly

effecting kinnow losses at farm level i.e. its makes differences that the fruit is picked in

morning or evening. When fruit is picked at morning then the losses are 0.276 times less then

the losses occurred when fruit was picked at evening. Picking method had a significant level

of 0.036 and coefficient value of -0.477 as shown in table 4.26. If the fruit was picked with

scissor, the losses are 0.477 times less than the losses with manual picking. So the picking

method had significant effect on post harvest losses of kinnow at farm level. Picking with

scissor caused less post harvest losses than manual picking. These results are similar like

Bari, 2004, Gangwar, et al., 2007, Murthay, et al., 2007.

Table 4.25: Coefficients and t-test to check the significance of various factors

Model Coefficients Std. Error t-value Sig.

(Constant) 3.839 0.590 6.507 0.000

Education (Years) -0.211 0.138 -1.526 0.137

Experience (Years) -0.222 0.108 -2.057 0.048

Orchard size (Acres) 0.214 0.074 2.878 0.007

Dummy for Picking

Time

-0.276 0.143 -1.936 0.061

Dummy for Picking

Method

-0.477 0.218 -2.187 0.036

R2 = 0.41, Adjusted R2 = 0.32

4.4.2 At transportation and Wholesale Market Level

(a) Overall significance of the model

Overall fitness of the model was 68 percent with standard error of the estimate 52

percent. Table 4.27 shows that 68 percent of the model was explained by the independent

variables like education, experience, type of transportation, infrastructure of transportation,

loading method and storage place.

(b) Analysis of Variance (ANOVA)

Analysis of variance or ANOVA of F test are used to check the overall performance

of the model i.e. how much the model reliable. Regression, residual and total sum of square

of the model was 19.87, 9.33 and 29.20 respectively. F value of the model was about 14.48 at

a significance level of 0.000. So according to this the model is appropriate.

Table 4.26: Analysis of Variance (ANOVA)

Model Sum of Squares df Mean Square F Sig.

Regression 19.876 5 3.975 14.487 0.000(a)

Residual 9.330 34 0.274

Total 29.205 39

(c) Significance of various factors of post harvest losses of kinnow

According to the regression results (table 4.27) the model can be explained in the

following form

LnL2 = 4.808 – 0.154 Education – 0.272 Experience – 0.593 Infrastructure of transport –

0.555 Loading method – 0.562 storage place

Education had not significantly effecting post harvest losses of kinnow at

transportation and wholesale market level. Experience had a significant effect at a

significance level of 0.060. As one percent increase in the experience causes 0.272 percent

decrease in post harvest losses. Infrastructure of transport has non significant impact on post

harvest losses during transportation. Use of metallic road for transportation of fruit causes

losses 0.593 times less losses used for non-metallic road. Loading method is also an

important determinant in post harvest losses of kinnow. Chances of losses during open

loading are more because of pressing, injury etc. Loading method had a coefficient value of -

0.555 at significance level of 0.05. As stacking of boxes had 0.555 times less losses than

open loading. Storage place also an important determinant in post harvest losses. As cold

storage has less losses then normal storage. Storage place had coefficient value of -0.562 at

0.064 level of significance. Cold storage had 0.562 times less losses than the normal storage.

Table 4.27: Coefficients and t-test to check the significance of various factors

Model Coefficients Std. Error T value Sig.

(Constant) 4.808 0.461 10.437 0.000

Education (Years) -0.154 0.115 -1.335 0.191

Experience (Years) -0.272 0.140 -1.944 0.060

Dummy for

Infrastructure of

transportation

-0.593 0.390 -1.521 0.137

Dummy for Loading

Method-0.555 0.273 -2.031 0.050

Storage Place -0.562 0.293 -1.916 0.064

R2 = 0.68, Adjusted R2 = 0.63

4.4.3 Losses at Retail Level

(a) Overall significance of the model

Overall fitness of the model i.e. R square of the model is 62.3 percent as shown in

Table 4.29. Adjusted R square is 59 percent and standard error of the estimate is 59.22

percent. Results show that 62 percent model is explained by the independent variables.

(b) Analysis of Variance (ANOVA)

Table 4.28 shows the results of analysis of variance (F test). The results show that

model had 31.64 sums of squares. Regression and residual mean square values are 19.718

and 11.925 respectively. Overall F value of the model is high i.e. 18.739 at significance level

of 0.000. So model is appropriate.

Table 4.28: Analysis of Variance

(c) Significance of various factors causing post harvest losses of kinnow

Table 4.32 shows the factors that are causing post harvest losses of kinnow at retail

level with their coefficient value and significance levels.

LnL3 = 0.453 – 0.080 LnExp + 0.259 LnUSqt – 1.32 Tr + ε

Experience of retailer had coefficient value of -0.08 which mean that one percent increase in

experience cause 0.08 percent decrease in post harvest losses but this value is not significant

as significant level is 0.46. So experience is non significant at retailer level.

Retailers purchase and sale the fruit on daily basis. So the unsold quantity on daily basis

cause great post harvest losses to retailers. Results shows that when there is one percent

increase in unsold quantity causes 0.26 percent increase in post harvest losses. And this

coefficient has significant at 6 percent level of significant. Type of retailer is also an

important factor causing post harvest losses. There are two types of retailers one are small

Model Sum of Squares df Mean Square F Sig.

Regression 19.718 3 6.573 18.739 0.000a

Residual 11.925 34 0.351

Total 31.643 37

shopkeepers and second are hawkers. Post harvest losses were high in case of hawker than

shopkeepers. When the retailer type is shopkeeper the losses are 1.32 times less than that of

hawker retailer type. And this variable is significant at 0.000 level of significant.

Table 4.29: Coefficients and t-test to check the significance of various factors

Model Coefficients Std. Error t value Sig.

(Constant) 0.453 0.317 1.429 0.162

LnExp -0.080 0.108 -.738 0.466

LnUnsoldqt 0.259 0.135 1.921 0.063

Type of retailer -1.320 0.266 -4.959 0.000

R2 = 0.62, Adjusted R2 = 0.59

4.4 Conclusion

In view of foregoing discussion, the following conclusions can be derived:

1. Total post harvest losses of kinnow at farm level, wholesale market level and retail

level were about 45 percent of the total production of kinnow in study area.

2. Farm level losses were maximum i.e. 72 percent of the total post harvest losses in the

marketing channel of kinnow. Major reasons of these losses were inadequate picking,

packing, transportation and marketing procedures. While factors contributing these

losses were little education and experience, orchard size of the producer/contractor,

picking time and picking method/technique. Losses were also high due to low level of

management in the orchards.

3. Wholesale market level losses were about 25 percent of the total losses in the

marketing channel of kinnow. These losses were caused mainly due to marketing

inefficiencies, lack of infrastructure, delayed marketing and improper handling of

kinnow at farm and market level.

4. Retail level losses were about 3.1 percent of the total post harvest losses of kinnow in

the marketing channel. The reasons of losses at retail level were experience, unsold

quantity on daily basis and type of retailer that is shopkeeper or hawker.

CHAPTER 5

SUMMARY

Citrus is the major fruit crop of Pakistan. Kinnow is most produced variety of citrus

in Pakistan. At present total acreage under citrus in Pakistan is 199.4 thousand hectares and

its production is 2294.5 thousand tonnes. Pakistani kinnow have high demand in world

market due to its rich flavor and taste. Pakistani kinnow has a unique value in world market

due to its unique taste and quality. Kinnow production, marketing and exports have been

subjective to qualitative and quantitative post harvest losses due to improper production,

marketing, packaging, transportation and storage procedures. Thid study was aimed to assess

and quantify losses of kinnow which starts accuring from harvesting till its consumption, to

find out the factors causing losses and to give suggestion to minimize such losses.

District Sargodha was selected for the study on the basis of their highest area and

production. A total number of 120 respondents were selected from two tehsils of Sargodha

i.e. Bhalwal and Kot Moman randomly out of which were 40 producers/contractors, 40

wholesalers and 40 retailers. Percentage losses of kinnow have been calculated at each of this

category by percentage method. Post harvest losses were presented in the functional form to

study the significant of various factors in post harvest losses of kinnow.

Main Findings

Main findings of the study were as follows:

1. About 90 percent of producers have sold standing fruit trees to contractors at

flowering stage or before fruit maturity. So further picking, packing, marketing was

done by the contractors. Only 10 percent producers marketed their produce

themselves.

2. Total post harvest losses in the marketing channel of kinnow were 32.4 percent at

farm level, 11.2 percent at wholesale market level and 1.4 percent at retail level.

3. At farm level, losses during picking were about 60.5 percent, packing and grading

losses were 10.8, carrying losses were 6.8 percent and loading and transportation

losses were about 22 percent of the total post harvest losses accuring to

producer/contracotrs respectively. Major reasons of picking losses were fruit fallen on

ground, knocking with sticks, clipping shaking and pulling with hands. Packing losses

were mainly due to tight packing and unskilled labour. Transportation losses were

due to loading/unloading, bad handling and defective roads. Losses of kinnow at

market entry level were mainly due to rotten fruits.

4. Post harvest losses at wholesale market level were about 11.2 percent of the total

business volume. Major reasons of these losses were loading/unloading and

marketing and storage losses which caused 55 and 45 percent of total losses at

wholesale market level.

5. Losses at retail level were about 1.4 percent of the total business volume. Major

reasons of these losses at retailer level were cleaning, transportation, left over, over

ripe and fruit taken for home consumption by the retailers.

6. The model used to identify the significance of various factors involved in post harvest

losses of kinnow at farm level had an overall significance of (R2) 41 percnet.

Experience, picking time and picking method had significant effect on post harvest

losses of kinnow at farm level while education and orchard size had non significant

effect on losses.

7. The model used to identify factors involved in post harvest losses of kinnow at

transportation and wholesale market had an overall significance of (R2) 68 percent.

Experience, loading method and storage place had significant effect of post harvest

losses of kinnow at transportation and wholesale market level and education and

infrastructure of transportation had non significant effect on post harvest losses.

8. The model used to identify the significance of the various factors involved in post

harvest losses of kinnow at retail level had an overall significance of (R2) 62.3

percent. Unsold quantity of kinnow on daily basis and type of retailer had significant

effect on post harvest losses and expereince had non significant effect on losses.

Recommendations

Like other developing countries, Pakistan needs to increase the quantity of food

available for its rapidly growing population. There are various ways to approach these

problems. One is to produce more food; another is to conserve whatever is produced. In the

past, much emphasis has been put on growing more food, while the post harvest aspect

(conservation of food after harvest) has been generally ignored. Careless post harvest

handling of kinnow causes damage of fruit; reduce its quality and market price. Such

damaged produce fails to attract the international buyer and bring the exporting countryless

porfit and a bad name. This ultimately results in huge economic loss to the country.

Following measures can be adopted to reduce post harvest losses of kinnow.

Fruit should be picked at least once in a week. This will make 5 to 7 harvests for any given

tree, allowing a better quality of fruit to be transported to the market as well as harvesting

more fruit, with fewer losses due to fruit drop. When kinnow fruit is being picked, efforts

should be made not to knock them off the tree and onto the ground. If fruit falls, it gets

bruised or wounded, becomes more susceptable to disease and insects attack and spoil

qiackly. It may be hard to prevent fruits from falling, but if the numbers of fruits falling on

the ground have been reduced, we will have high quality produce to sell. The fruit should be

picked in the coolest daylight hours i.e. in the morning and immediately placed in buckets or

containers out of direct sunlight. Although it does not have immediate effect on post harvest

losses of kinnow even then the fruit that has been harvested in the morning will look better

and last longer. On the other hand if harvesting or picking is done in the day the fruit may be

wilted or limp and will also have more disease and insect problems. Fruit should be picked

with scissor and hand while standing on the ground cutting the stem 6-10 cms from the fruit.

For the fruits located high on the tree, a fruit picking pole having blade on it to cut the stem

and a small basket to collect the fruit immediately after cutting. Good care should be taken in

the handling of the fruit. Significant losses due to improper handling have been reported. In

the packing place, the fruit should have the stem cut, washed, graded and packed and

immediately refrigerated to slow down the ripening process. Even for domestic marketing,

the simple process of providing a cool-water wash (immediate precooling) after harvest

should be employed even if refrigeration is not being used. This will extend the life of the

fruit somewhat and its appeal to to buyers. Before taking to the markets, fruit should be

graded and sized into two or more grades according to trade standards. Efficient marketing

system require precise grading standards for each kind of product so a comprehensive

commidity grading systemshould be implemented to reduce losses. Good quality packaging

material must be made available within the country as packaging of fresh fruit has a great

significance in reducing the wastage. Packaging provides protection from physical demage

during storage, transportation and marketing. Kinnow fruit should be packed in clean,

moderate dimension, easy to handle, inexpensive and easly degradable or recyclable wooden

crates or in Corrugated Fine Wooden Boxes (CFB ). Filling should be recommended with

papers or a similar material, over packing should be avoided that can also cause damage.

Good packaging maintains but does not improve the quality of fruits packed in it; therefore

the best possible produce should be packaged to avoid further losses. The fruit should be

transported immediately after packing. Transportation of kinnow fruit should be in vehicles

that provide leasr shaking, movement and vibration. Transport difficulties and absence of

link roads between farms and market, pumpy, bad road cause accidents and mechanical

iinjury to fruit. Overall efficient roads and transportaation system should be adopted.

Reasonable amount of fruit should be transported at a time. At retail level, the losses of

hawker has more than shopkeeper and this is due to instability between shopkeeper and

hawkers. So Government should take steps to overcome the instability condition between

shopkeepers and hawkers. Hawkers remains unsold quantity more than shopkeepers and that

cause more losses to hawkers.

To improve post harvest situation, it is essential to create awareness among growers, farm

workers, managers, traders and exporters about the extent of the losses being incurred and

their economic consequences. Also there is need for extension services to farmers, including

information on price, grading and standardization, packaging and labeling, storage and

warehousing, sanitary and phyto sanitary (SPS) measures. Research in the area of food

control and post harvest management in the country tends to be inadequate, due to limited

resources and often poor management. Laboratories are frequently poorly equipped and

suitable trained analytical staff. Post harvest management system also suffers from poorly or

inadequately developed policies. So there is an urgent need to carry out research and

development in the area of post harvest management. There is need to provide basic

infrastructure like storage, handling, grading, packing, transport and marketing facilities and

technical expertise. This could be carried out by the public and private sectors. Trade

libralization and WTO agreement also demands to produce kinnow of inetrnational,

nationaland private sector standards with respect to quality, safety, environment and labor

employed in post harvest activities. To enable the country to meet Sanitary and Phyto

Sanitary Measures (SPS) or Technical Barriers to Trade (TBT) obligations to international

food trade, technical assistance in the food control and post harvest management area should

be obtained through the World Bank, other development banks and from bilateral donor

agencies.

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