Thesis by Umar Ijaz, Econometric Estimation of Post Harvest Losses of Kinnow in District Sargodha

Econometric Estimation of Post Harvest Losses of Kinnow in District Sargodha, Punjab

By

UMAR IJAZ AHMED

B.Sc. (Hons.) Agricultural and Resource Economics

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

MASTER OF SCIENCE (HONS) IN AGRICULTURAL ECONOMICS

Faculty of Agricultural Economics and Rural Sociology

University of Agriculture Faisalabad

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.

Title

Page 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

36

Table 4.5

Losses of kinnow incurred at farm level during picking, carrying, grading, packing and transportation Personal characteristics of Kinnow Producer/Contractors

Table 4.6

Orchard related characteristics

38

Table 4.7

Sale quantities and sale prices of kinnow

39

Table 4.8 Table 4.9

Harvest Losses Post-harvest losses during carrying from picking to grading/packing place Post-Harvest losses of kinnow during grading and packing

40 42

46 47

Table 4.13 Table 4.14

Post-Harvest losses of kinnow during loading and transportation Losses of kinnow incurred at wholesale market level during unloading and marketing and storage Personal characteristics of wholesaler Sale quantities and prices of kinnow

Table 4.15

Expenditures of Wholesalers

49

Table 4.16

Post-Harvest losses of kinnow at wholesale level

50

Table 4.17 Table 4.18

51 52

Table 4.19 Table 4.20 Table 4.21

Losses during storage at wholesale level Losses of kinnow incurred at retail level during retail marketing and unsold quantity Personal characteristics of retailers Purchase and Sale quantities and prices of kinnow Expenditures of Wholesalers

Table 4.22

Post-Harvest losses of kinnow at retail level

55

Table 4.23 Table 4.24

Daily business volume Analysis of variance (ANOVA)

Table 4.10 Table 4.11 Table 4.12

37

44

48 48

53 53 54 55 57

Table 4.25

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

58

Table 4.26 Table 4.27 Table 4.28

Analysis of Variance (ANOVA) Coefficients and t-test to check the significance of various factors

59 60

Analysis of Variance

61

Table 4.29

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

62

LIST OF FIGURES Figure No.

Title

Page 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, wellirrigated 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 preharvest, 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, nonapplication 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

sophisticated.

systems In

the

are

likely

latter

half

to of

become the

increasingly

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

regressions,

correlations

Beauty). were

Using

determined

multiple

linear

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 socioeconomic 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 postharvest 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’, ‘socioeconomic 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 (p16 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 pretested 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 Morning

assigned value 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 Percentage share in total

Percentage share in total

produce of kinnow

losses of kinnow

32.4

72

11.2

24.9

At Retail Level Losses

1.4

3.1

Total

45

100

Levels

At Farm Level Losses At Wholesale Market Level Losses

Retail Level Losses, 3% Wholesale Market Level Losses, 25%

Farm Level Losses, 72%

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

Item

During loading

During

During grading

During

Picking

and packing

carrying

19.55

3.5

2.2

7.1

32.4

60.5

10.8

6.8

21.9

100

and

Total

transportation

% age share of Losses in total produce %age share of losses in total losses at farm level (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

-

40.0 60.0

-

5

Partnership (Percent) Yes No

(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

-

Flowering

32.5

-

Fruit formation

62.5

-

Harvesting

5.0

-

6

Contract stage (percent)

(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. 1 2 3 4 5 6

Items Early Season Sale (Qty) in Mds for Kinnow Early Season Sale Price in Rs/Md for Kinnow Mid Season Sale (Qty) in Mds for Kinnow Mid Season Sale Price in Rs/Md for Kinnow Late Season Sale (Qty) in Mds for Kinnow Late Season Sale Price in Rs/Md for Kinnow

Mean

Std. Deviation

8696.9

6426.7

603.2

147.0

16350.2

14442.8

527.9

110.9

6791.0

5669.3

642.4

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) If partial Loss, decrease in Value

9.5

6.4

50.6

10.4

6

(percent)

7

Sale Price (Rs/ Mds)

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)

12

13

Cuts Bruise Pressed Injury Latex Other Method of Picking (percent) Scissor Hand Labour used for picking (Percent) Skilled Ordinary

591

30.0 22.5 17.5 17.5 5.0 7.5

-

95.0 5.0

-

90.0 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

195.4

87.2

1

Qty. Picked One Time lot (Mds)

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

-

Wooden Basket

15.0

-

Plastic Crates

70.0

Palli

12.5

-

Other

2.5

-

Skilled

75.0

-

Ordinary

25.0

-

12

13

Type of material used for packing (Percent)

Labour used for carrying (Percent)

(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

195.4

87.2

1

Qty. Picked One Time lot (Mds)

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)

11

12

Cuts

12.5

-

Bruise

32.5

-

Pressed Injury

45.0 7.5

-

Latex

2.5

-

Fine wooden basket

35.0

-

Plastic crate

27.5

-

Palli

32.5

Other

5.0

-

Skilled

85.0

-

Ordinary

15.0

-

Packing material used (Percent)

Labour used for grading/packing (Percent)

(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

-

Truck

12.5

-

Mazda

37.5

-

Pick Up

5.0

-

Other

45.0

-

Stacking of boxes

67.5

-

Open loading

25.0

-

Other

7.5

-

Metallic Road

72.5

-

Non-Metallic Road

27.5

-

10

11

12

Type of transport used (Percent)

Loading Methods used (Percent)

Infrastructure of transportation (Percent)

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

Items % age share of Losses in total produce %age share of losses in total losses at farm level

During Unloading

During Storage

Total

6.2

5.0

11.2

55.4

44.6

100

and Marketing

(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 Other

55.0 -

-

Yes

26.2

-

No

73.8

-

5.

Partnership (Percent)

(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. 1.

Items Carrying Charges from Auction Floor to Own Floor (Rs/Mds)

2.

Auction Charges if (Rs/Mds)

3.

Monthly Rent of the Floor (Rs)

4.

Daily expenditures

Mean

Std. Deviation

5.4

3.6

9.4

1.8

10975.0

4410.0

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)

9.

Cold

31.0

Normal

69.0

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

Items

During retail

Unsold

Marketing

Quantity

0.67

0.69

1.4

49.6

50.4

100

% age share of Losses in total produce %age share of losses in total losses at farm level

Total

(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) 75.0 25.0

-

Yes

12.5

-

No

87.5

-

Shop keeper

60.0

-

Hawker

40.0

-

Business Other 5.

Partnership (Percent)

6

Type of retailer (Percent)

(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. 1.

Items Carrying Charges from market to own

Mean

Std. Deviation

25.9

16.9

3.

shop (Rs/Mds) 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 level Sr. 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 volume Sr. 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

-0.276

0.143

-1.936

0.061

Time Dummy for Picking

-0.477

0.218

-2.187

0.036

Method 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

-0.593

0.390

-1.521

0.137

-0.555

0.273

-2.031

0.050

-0.562

0.293

-1.916

0.064

Dummy for Infrastructure of transportation Dummy for Loading Method Storage Place 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

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

(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 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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