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GRADING AND PRICES GRAPE AND POMEGRANATEFRUITS A CAE OF BIJAPUR BAGALKOT MARKETS

Thesis submitted to theUniversity of Agricultural Sciences, Dharwad

in partial fulfi l lment of the requirements for theDegree of

MASTER OF BUSINESS ADMINISTRATION (AGRICULTURE)

By

AURN C. YAMBHATNAL

DEPARTMENT OF AGRICULTURAL MARKETING, CO-OPERATION

COLLEGE OF AGRICULTURE, DHARWADUNIVERSITY OF AGRICULTURAL SCIENCES,

DHARWAD 580005

SEPTEMBER, 2007

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ADVISORY COMMITTEE

Dharwad (B. BANAKAR)

SEPTEMBER, 2007 MAJOR ADVISOR

Approved by:

Chairman : ______________________

(B. BANAKAR)

Members : 1.____________________

(S.B. MAHAJANASHETTI)

2.____________________

(A.R.S. BHAT)

3.____________________

(S.G. ANGADI)

4.____________________

(N.F. UPPINAL)

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CONTENTS

Chapter

No.Title

Page

No.

I. INTRODUCTION

II. REVIEW OF LITERATURE

III. METHODOLOGY

IV. RESULTS

V. DISCUSSION

VI. SUMMARY AND POLICY IMPLICATIONS

VII. REFERENCES

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LIST OF TABLES

TableNo. Title

PageNo.

4.1 Influence of fruit quality characteristics on prices of grape and pomegranate

4.2 Non fruit quality characteristics influence on prices of grape andpomegranate

4.3 Scientific grade standards for Thompson Seedless variety of grape

4.4 Scientific grade standards for Sharad variety grape

4.5 Development of grade standards for Ganesh variety of pomegranate

4.6 Development of grade standards for Kesar variety of pomegranate

4.7 Fruit quality characteristics influence the Eye-Sight grade on price of grapeand pomegranate

4.8 Factors influencing Eye-Sight grade and Scientific grade of ThompsonSeedless grape

4.9 Deviations as explained by coefficients of variations in Scientific grade andEye-Sight grade for prices of grapes

4.10 Factors influencing Eye-Sight grade and Scientific grade of Kesar variety ofpomegranate

4.11 Deviations as explained by co-efficient of variations in Scientific grade andEye-Sight grade for prices of pomegranate

4.12 Impact of grading on price received for grape varieties

4.13 Impact of grading on price received for pomegranate varieties

4.14 Problems faced by the grape Traders

4.15 Problems faced by the pomegranate Traders

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I. INTRODUCTION

The improved technologies introduced in Indian Agriculture have brought anoverwhelming result in production levels. This has given rise to new problems in marketing,which have been overlooked inspite of the solutions for these problems are indispensable forthe agricultural prosperity. It is the disposal of the produce which is more important than theadaptation of new technologies, for higher profits. Unless and until the marketing systems are

improved no incentives to increase the production can attract the cultivators. It is a presentday fact that farmers are not getting the major share of consumers money which has to beovercome.

With the enormous increase in agricultural production, there has been a remarkableincrease in marketable surplus leading to inadequacies in execution of various marketingfunctions. These marketing functions have to cope up with the production levels to facilitatefarmers. This demands the development of sound marketing system on scientific grounds soas to enable farmers to get remunerative prices for their produce. Fruit grading plays a vitalrole in fetching higher prices for the producer and seller.

The quality of fruits produce brought to market differs much from lot to lot. This is dueto different varieties, management practices followed and varied agro-climatic conditions.Therefore, it is much essential to grade the produce brought to the market on scientificgrounds, so as to get remunerative prices. The producer-seller must be able to convince the

buyers with respect to the quality they are offering.

It is needless to emphasize the importance of grading. Grading and standardizationhas to be promoted on a large scale as it is much more important than the adoption ofimproved cultivation practices for high productivity. Grading promotes overseas trade as wellas saves time and energy of both buyer and seller in the process of marketing. The producewhich is graded assures quality to buyer and premium price to producer-seller.

In view of the above facts, serious efforts are being made to organize marketingsystem on scientific grounds by the enactment of agricultural produce (Grading and MarkingAct, 1937), which empowers the central government to set grade standards for agriculturalcommodities and livestock products, and to make stipulations to govern conditions of usingthese standards and lay down procedures regarding marking and packing.

Various studies have been conducted in the recent past to evaluate the present

grading norms and to establish the relationship between grade, price and quality. However,not much effort has been put into estimation of the relationship between grade and qualityfactors of commodities and also comparing the eye-sight grading with scientific grading.

As very less studies have been conducted throughout the country, the presentinvestigation was undertaken to develop grade standards for grape, pomegranate. It aims atfinding out comparing eyesight grading with scientific grading and thereby evaluatingefficiency.

1.1 IMPORTANCE OF FRUIT CROPS IN INDIAN ECONOMY

India is the second largest producer of fruits in the world next to China. The totalannual production is over 3.95 million tonnes in 2003-04, with a share of 11 per cent in theworld production.

The major fruits grown in India include, Mango, Banana, Papaya, Orange, Mosumbi,

Guava, Grapes, Apple, Pineapple, Sapota, Ber, Pomegranate, Strawberry, Litchi Etc.

India ranks first in the production of Mango, Banana, Sapota and acid limes in theworld. It is among the first 10 in the production of Apple, Papaya, Orange, Grapes AndPineapple. The five fruits namely mango, banana, citrus, guava and apple account for 75 percent of total fruit production in the country.

In Karnataka, the total cultivated area account for 2.61 lakh hectares with theproduction of 41.65 lakh tonnes.

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1.1.1 Importance of grape in Indian economy

Grape (Vitis vinifera L. cv. Thompson Seedless) belongs to family Vitaceae, isperhaps the most widely cultivated fruit crop of the world in varying climatic zones extendingfrom the temperate to the tropics. It is one of the most delicious, refreshing and nourishingsubtropical fruits. The berries are a good source of minerals and vitamins (B1, B2and C). Thefruits are consumed in fresh forms as a table fruit and in the processed form as wine, raisinand fresh juice.

Grape is cultivated over an area of 8.94 million ha in the world with an annualproduction of 64.87 million tonnes. Out of total production of grapes, 80 per cent is used forwine making, 10 per cent for raisin making and the rest for table purpose. In India, it iscultivated over an area of 40 thousand hectares with an annual production of 9.40 lakhtonnes. Grape cultivation in India has acquired greater significance due to its high productivitycompared to many other grape producing countries in the world.

Commercial viticulture in India is hardly a few decades old and major grape growingstates are Maharashtra, Karnataka, Tamil Nadu, Andhra Pradesh, Punjab and Haryana.Among all the grape growing states, Maharashtra occupies the largest area (16,000 ha)followed by Karnataka (8,500 ha). As far as productivity is concerned Karnataka stands firstfollowed by Maharashtra.

The popular grape varieties of South India are Anab-e-Shahi, Thompson Seedless,

Gulabi and Bangalore Blue. These grape varieties are becoming increasingly popular inpeninsular India.

In Karnataka, grape is commercially cultivated in southern parts of the state. Duringfifties, grape was introduced into North Karnataka, where conditions are quite different fromthat of South Karnataka. Thompson Seedless, Sharad, Tas-A-Ganesh, Sonaka and Arkavathiare the important seedless cultivars of grape under cultivation in the state. ThompsonSeedless is gaining more popularity both as table purpose and raisin making, because of itshigh total soluble solids and berries of amber colour thin skin and desired shape.

1.1.2 Importance of pomegranate in Indian economy

Pomegranate (Punica granatum L.) commonly known as Anar, Dalim, matulum is animportant fruit of tropical and subtropical regions of India. The wide adaptability, hardy nature,low maintenance cost, steady and high yields, fine table and therapeutic values, betterkeeping quality and possibilities to throw the plants into rest period when there is scarcity ofirrigation water are some of the qualities which make this fruit crop ideally suitable for semi-arid and arid regions. However, performance of the plant will be excellent, if maintained withprotective irrigation.

The centre of origin of this plant is thought to be Iran where it was first cultivated in2000 B.C. It is extensively cultivated in Spain, Morocco, Egypt, Iran, Afghanistan, China,Japan, USA, Russia, Pakistan, India and other Mediterranean countries. Pomegranateoccupies 18

thplace based on production among the worlds main fruit crops.

This fruit also has wide consumer preference, for its attractive, juicy sweet, acidic andrefreshing fruits. Fruits are used for both fresh consumption and processing.

The fresh fruit is of exquisite quality, while its processed products such as bottledjuice, syrups and jelly are highly appreciated and nourishing. The fruit is a good source ofcarbohydrates, minerals and vitamins. Pomegranate plant and fruit are prized over centuries

for their medicinal properties.The rind of the fruit has medicinal properties and is used in the indigenous system of

medicine for the prevention of intestinal disorders. It is also the source of dye which givesyellowish brown to khaki shades and has been used for dyeing wool and silk. Tannin occurson all parts of the tree, which is extracted and used as above or mixed with cystic tannins fortanning leather.

A number of varieties of pomegranate are cultivated and are distinguished by shapeof the fruit, colour of the rind, thickness of the rind, taste and colour of the aril. In Indiapomegranate was previously grown in kitchen gardens but commercial plantations have comeup in recent years with the introduction of some improved cultivars like Ganesh, Araktha,

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Sindhur and Jyothi With the recent developments in dryland horticulture, the production of thisfruit has increased with increased demand in internal trade and export market.

Although, the fruit is grown all over India, it is commercially exploited only inMaharashtra and North Karnataka.

Pomegranate has attracted many growers especially those in Karnataka andMaharashtra for its wider adaptability, relatively low cultivation costs, drought tolerance, good

yields, excellent shelf life and export potential.In Karnataka, pomegranate occupies an area of 10803 hectares (Anon., 2003) with

the production of 12466 tonnes. The predominant pomegranate growing districts areBagalkot, Bijapur, Raichur, Belgaum, Bellary, Chitradurga and Dharwad.

In Northern Karnataka, Bagalkot district is the largest pomegranate producer with anarea of 1702 hectares. The other important horticultural crops grown in the district areGrapes, Sapota, Mango, Lime and Ber.

However, most of the research conducted on grading and price quality aspects arefound in foreign countries. Studies on this vital subject within the country are seldomavailable. Hence, the present study was undertaken to examine the physical properties andqualitative characteristics of grape and pomegranate samples and establish price-qualityrelationship for grape and pomegranate.

More precisely the present study proposes to examine the following specificobjectives in the fruit crop in Bijapur and Bagalkot districts. The specific objectives of thestudy are as follows.

1. To determine the fruit quality and non-fruit quality factors influencing the price of selectedfruits.

2. To develop the grade standards for selected fruits.

3. To determine the extent of deviation between eyesight grading and scientific grading.

4. To analyse the impact of grading on price received by producer-seller

5. To identify the problems faced by the traders

1.2 PLAN OF CHAPTERS

The importance and significance of the present study along with the specification ofthe objectives to be analysed are presented in the first chapter. The Chapter II deals with thereviews of some of the earlier studies. The Chapter III describes the identification of variablesand analytical framework adopted for the study. In Chapter IV, the results of the study arepresented, the Chapter V deals with interpretation and discussion of the results. The ChapterVI contains the summary of the main findings and policy implications emerging from thefindings of the present study and the Chapter VII contains the literature cited.

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II. REVIEW OF LITERATURE

Review of literature provides information to the researchers regarding the previousworks done in their area of research and thereby helps them in identifying the theoreticalframework and methodological issues relevant to the study. It provides the researchers aproper direction to carryout their research work and enables them to arrive at meaningfulresults. Keeping these facts in view, the available literature relevant to the objectives of the

present study was reviewed and they are presented herein under the following headings.

The quality of the agricultural commodities is considered to be one of the importantfactors in determining the prices. Very few studies have tried to establish the relationshipbetween the quality of the produce and its price. Such of the studies which may throw light onthe quality, grading and prices of agricultural commodities, are reviewed in this chapter.These studies have been grouped into five sections. They are as follows.

2.1 Quality factors in relation to prices of various commodities

2.2 Development of grade standards for important commodities

2.3 Deviation between eye-sight grade and scientific grade

2.4 Problems faced by the traders

2.1 QUALITY FACTORS IN RELATION TO PRICES OF

VARIOUS COMMODITIESLuhtala (1986) reported that a new system of producer prices for milk in Finland no

longer uses the methylene blue test but is based solely on bacterial count and somatic cellcount.

Bockstael et al. (1987) studied the economic efficiency of grading and standards isdiscussed. The general agricultural literature on minimum quality standards and grading isreviewed, and the apparent controversies highlighted. Several strains in the literature arepulled together and an analysis of grading and standards is presented for the case in whichproduct quality is known with certainty and in which there exists uncertainty about quality. Anattempt is made to integrate relevant analyses from both the agricultural and mainstreameconomic literature and to determine what, if any, decisive theoretical results exist. Thepossibility is explored that industry structure may affect the evaluation of grades andstandards as potentially efficient practices. It is concluded that grades have a place in themarketing system and that socially optimal grading schemes can be devised. Additionally,minimum standards established under marketing orders, while generally either undesirable orinnocuous, can potentially be justified on economic efficiency grounds when quality isunobservable. However, grading and standards although potentially beneficial, can also beused to accomplish socially undesirable ends. It may be that if left to well-organized,cooperating bodies of growers and handlers, standards and grades will be set sub-optimallyand may screen collusive type behaviour. Alternatively, if provisions for grading and setting ofstandards are granted to unorganized, highly competitive growers, they may serve to improveinformation flow and combat marketing power of the middlemen. The paper is discussed byJ.C. Nichols.

Chen (1988) revealed that in retail markets for fresh agricultural commodities, productcharacteristics are heterogeneous and consumers have less-than-perfect information aboutproduct quality. Consequently, sorting schemes such as grading and branding occur. The

study investigates how the degree of grading and branding for agricultural commodities at theconsumer level is determined. A Lancaster type demand function involving quantity andquality was derived, based on Dixit's iso-elastic utility function. The models developed areapplied to the following propositions: (1) in a market with a majority of uninformed consumers,branding may not provide higher quality. When branding provides lower quality, grading maylose market share; and (2) in a market with a majority of informed consumers, branding mayprovide higher quality. When grading provides a lower quality, it may gain market share.Empirical observations from retail markets are examined to lend further support to thesepropositions.

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Halinen (1988) observed the systems used in Iceland, Norway, Sweden, Denmarkand Finland for sampling, testing and grading farm milk for payment purposes are describedin detail.

Kalloli et al. (1988) reported that using groundnuts as an example, this studyexamined the relationship between grade and quality, and between price and quality of aproduct. Data were collected from three regulated markets (Gokak, Hubli and Dharwad) inKarnataka State, India. A grade response model was fitted for each of the selected markets

with grade value of the sample as dependent variable. To test these models multiple linearregression analysis and step-wise linear regression analysis were used. The study revealedthat the grade value and price are closely related. The main variables affecting price are,dryness of the pods, maturity, soil content of the pods, shelling percentage, oil percentageand moisture percentage. The existing grading systems in the regulated markets were farfrom satisfactory.

Srinivasan and Mani (1989) reported the Commercial Grading Scheme that wasestablished to help farmers obtain a fair price for their produce operates in 102 centerslocated in regulated markets in Tamil Nadu State, India. This paper assesses theperformance of the scheme, which has been in operation for two decades. Among the samplefarmers studied, 62.5% were aware of the scheme but only 38% graded their produce underthe scheme. The quantity of graded produce accounted for 21% of the total quantity marketedby the sample farmers, on an average. The increase in price obtained was, on an average,

Rs 3.33 per Rs 100 worth of graded produce marketed.Kondo and Shibata (1989) studied the factors stimulating the organization of

strawberry growers in Japan are discussed, and the behavior of members of a producergroup was studied in relation to whether they conformed to the group norm or not. A survey ofgrowers showed that most was highly conscious of the need to grade their strawberries.Growers who conformed to the group norm obtained yields per unit area that were markedlyhigher than growers who did not, and they tended to have a strong interest in improving theirgrowing techniques. Important organizational factors that could be intensified are: (1)fulfillment of the members' desire to improve, sales power and growing techniques, and anincrease in cohesiveness; (2) advancement of the grading techniques of the non-conformingmembers to the level of the conformers, so increasing profitable sales; and (3) theachievement of more profitable sales than other groups.

Kutumbarao (1990) observed 'Agmark grading' is the term commonly applied to theAgricultural Produce (Grading and Marking) Act implemented by the Directorate of Marketingand Inspection (DMI), in India, since 1937. This survey traces the history of such grading withspecial reference to oilseeds intended for the domestic and international market. Widely usedas cooking medium, edible oils are particularly prone to adulteration by products such asartificial essence, mineral oils and banned anti-oxidants, which can cause serious diseases,hence the great need for regulation in this area. Conclusions reveal that grading and qualitycontrol of agricultural products according to identifiable and standard parameters serves asan essential prerequisite for ensuring consumer satisfaction and payment in line with qualityfor the producer. Statistical evidence collected from a series of surveys conducted by the DMIis used to verify conclusions.

Gopalan and Gopalan (1991) established that the agricultural marketing system inIndia suffers from severe constraints like high costs, the existence of middlemen, storage andtransport bottlenecks and a lack of market information among farmers. This article uses acase study of the Nilgiri Cooperative Marketing Society in the potato-growing region of Tamil

Nadu to evaluate various methods of raising marketing efficiency. The analysis suggests thatthe cooperative has weakened the many small monopolies and malpractices of middlemen,and has led to a considerable improvement in marketing efficiency. However, there is needfor more timely and adequate application of farm inputs, better coverage of potato growers,grading schemes and more efficient dispersal of information, among other requirements.

Vyakaranahal et al. (1992) studied the grading of seeds (collected in Dharwad,Karnataka) by size indicated that the best germination and seedling vigour were obtainedfrom the largest seeds (those retained by a sieve size of 11.2-12.9 mm). However, seedrecovery in these larger size classes was low so use of 8.8-9.2 mm seeds is recommended.

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Mohammed Ali (1992) reported that based on his analytical study on the private andthe public fruit processing units situated at Bangalore came to the conclusion that the annualprocurements of raw material was more in case of private sector units over the public sectorunits by 744.55 tonnes.

Md. Kalimuddin et al. (1994) studied four different combinations of vegetables ingardens of 3 small farms in Bangladesh in 1990-91 for improving household nutrition and togenerate income. The combinations were: okra, red amaranthus, Brinjal and Spinach; stem

amaranthus, kang Kong, tomato; Indian spinach, stem amaranthus, radish; and redamaranthus, Indian spinach and cabbage. Total vegetable production was 233.9 and 228.54kg/m2 and net return was 455.67 and 595.96 taka/10 m2 in 1990 and 1991, respectively. Thefamilies consumed most of the vegetables. The vitamin A contribution from the gardenexceeded the requirement of a family of 5 for 250 and 260 days in 1990 and 1991. Vitamin Cfrom the crops also exceeded the family requirement for 280 and 300 days in 1990 and 1991,respectively. The crops also contributed calcium and iron.

Viswanath and Narappanavar (1994) discussed the grading of arecanuts at theproducer, wholesale and distribution level, based on information collected at Mangalore,Shimoga, Sagar and Sirsi markets in India. Producers stratify arecanuts by sorting, andtraders vertically differentiate produce by means of twelve factors. It is concluded that thegrading system needs to be made more effective.

Omotesho et al. (1995) the study examines the relevance of standardization and

grading as a facilitating function in marketing of grains. The various measurement units, theiracceptability and adoption by the consumers and traders along with the relationship of pricesto different grades of grains are critically assessed. It is revealed that there is no uniformity inany of the units and no rigid basis for sorting products into lots. Fifty-three percent of therespondents complained of frequent changes in the volume of a particular unit ofmeasurement and 83% of the consumer respondents indicated their willingness to pay more ifgrade of choice were available. Often consumers are given a lesser quantity than they hadbargained for and this constitutes a major problem for collection of accurate price data. Tostandardize the marketing provision of grain containers that cannot be easily altered in size orvolume is imperative.

Bon and Bon (1996) reported that in recent years, various activities have beenconducted in the vegetable subsector, with the aim of supplying products that meetconsumers' quality expectations, as defined in market surveys on tomatoes, onions andpotatoes. Cultivation techniques were improved to ensure that the quality (shapes andcolours) of these vegetable products is regular throughout the year. However, sellers'constraints were not taken into account in these surveys. Despite the fact that quality hasbeen somewhat improved, there are still no interprofessional policies on quality that are in linewith both consumers' needs and farmers' supply.

Dharmadhikari and Jite (1996) revealed the ponderosa infection induceddevelopment of large galls on the stem, leaves and fruits of A. leucophloea, studied the levelsof total sugars and ascorbic acid in healthy plants and in galls. Sucrose concentration waslower in the galls and fructose concentration was higher. The ascorbic acid content was lowerin galls compared with healthy plants. Ascorbic acid oxidase activity was higher in the galls.

Srivastava and Arora (1996) observed the data are presented for the diurnal pricevariation of 15 vegetables in Haldwani vegetable market, Kumaon division, Uttar Pradesh,India, surveyed over the period 7 June 1987 to 6 July 1987. The vegetables are: potato,onion, ginger, tomato, brinjal (aubergines), bottle gourd, pumpkin, bean, edible arum, ridgegourd, jack fruit, capsicum, okra, bitter gourd, and squash melon.

Oguri et al.(1997) examined the situation of egg product usage by egg grading andpacking plants in Japan. A survey of 58 grading and packing plants were conducted duringOctober to December 1996. The main results are: (1) about 30% of plants stored eggs atambient temperature, whereas they should be stored at less than 8C; (2) 87% of productswere raw whole eggs and 13% were frozen whole eggs. There were no separated eggs suchas liquid yolk and albumen. 93% of products at grading and packing centers were notsterilized but specialized egg breakers' eggs are sterilized; (3) most of the grading andpacking centers liquid eggs were sold to bread and cake making industries whilst most of thespecialized egg breakers' eggs were directed to the mayonnaise industry; (4) pricing of egg

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products is dependent on the price of shell eggs (Tokyo-Zennoh price); and (5) it isconsidered important to establish egg product standards and price formation.

Retnowati et al.(1997) reported that in Indonesia, production of salted fish of variablequality causes some difficulties in marketing. The quality grading performed by the processorsand its possible role in pricing of the commodity at the production level is investigated.Products prepared from brown anchovies, white anchovies and scads were chosen for thestudy. Several fish processing centers along the North Coast of Java were surveyed. The

results indicate that quality grading at the processors' level was carried out based on physicalcharacteristics, especially appearance (colour, size and physical damage), odour, taste(saltiness) and dryness. There were different criteria in the grading systems among theprocessors, as they did not use quality standards. In addition each quality grade has adifferent market region. In general, lower quality causes lower prices. Less salty productswere priced higher.

Combris et al. (1999) studied the significance of quality in fixing the prices ofBordeaux and Burgundy wines are examined. While at wholesale wine auctions therelationship between quality and price is a strong one, due to the information held by theexperts involved in it, among lay buyers the situation is more complicated. The papertherefore ask to what extent information on the label is more significant than sensory, moresubjective experience of the wine by consumers. The first part considers how differencesbetween prices for wines in a market can be accounted for. The second part stresses the

strategies open to consumers in making a choice, one constraint being that tasting theproduct directly will not normally be possible, meaning that more attention will be paid to thelabel and any expert assessments it contains. The conclusion argues that these subjectiveaspects of quality-evaluation are less significant than objectively determinable characteristicssuch as jury opinions. The labelling of Burgundies is more flexible than that of Bordeaux, dueto the rigidity of the characteristics of the latter.

Chalfant et al.(2000) studied the economic effects of errors in pure grading, focusingin particular on the implications of one-way (asymmetric) grading errors, namely when small,low-quality product is erroneously classified as high quality, but not vice versa, are discussed.In an application to the prune industry in California, the extent to which large prunes areundervalued and small prunes are overvalued is estimated. It is concluded that grading errorsmean that prunes graded, as high quality may not be high quality. The presence of theseincorrectly graded prunes depresses the prices that growers are paid for high-quality prunesand increases the net returns for small prunes. As a result, growers face reduced incentives

to produce larger prunes.

Judd (2000) reported that the relationship between price and objective quality isimportant for consumers who perceive that high prices signal high quality. Several studies inthe past have attempted to measure the relationship. This study focuses on brands of foodproducts in a variety of categories in an attempt to measure the correlation between price andquality, and to report the outcomes if the highest and lowest priced brand in category areselected. This study also considers the findings of earlier food product studies, as well asearlier studies of non-food products. Data from the USA are used in the study.

Jaiswal (2000) reported an overview of how grading and standardization of foodproducts is done is presented. Also described are the mandatory and voluntarystandardization systems in India.

An experiment was conducted by Babu (2002) to study the influence of gradingcustard apple fruits immediately after harvesting on the market price and level of return.Grading of the fruits according to weight resulted in better acceptability to consumers.Tabulated data on the comparative market value of custard apple fruits and costs incurred bygrader/trader for 1000 fruits and economic analysis are presented.

Chiorescu and Gronlund (2003) reported that presorting logs in the sawmills log yardis one of the strategies used by the Swedish sawmilling industry in order to maximse profits.Approximately 96% of Swedish sawmills perform the presorting of logs according to theirdimensions, most commonly by the diameter .only a small number of sawmills use log gradeinformation as a sorting criterion. However, the grade information at individual log level,together with the estimated volume, is always used for the calculation of the log payment. Thequality assessment of the log is done on a visual basis, that is the measurer grades the log on

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what he or she sees on the outside of the log. This judging should correspond to the expectedquality of the center boards produced after sawing current studies have only related thecenterboards quality to the grade arrived at by visual inspection. In view economic importanceof the sideboards in the lumber yield and in the entire functioning of a sawmill ,a real need forinformation on the recovery of side boards in relation to log and centerboards quality is nowarising and becoming a key issue. In this industry, with the help of the entire Swedish pinestem bank material, the relation ship between the side boards quality and the logs quality and

the relation ship between the quality of side boards and of center boards were studied. Theresults show that side board quality cannot be predicted from the visual quality assessment ofthe logs. Never the less, fairly good correlation exists between the side board quality and thequality of the corresponding quality. A financial analysis focusing on the relation ship betweencommercial values of the saw logs and the corresponding lumber out put for the Swedish pinestem bank material is also included in the study. The study shows that the actual log pricingsystem should be improved because the commercial values of the log are not in accord withthe real values of the lumber produced.

Wader and Kumar (1995) made an attempt to determine deviation between scientificgrading and eye-sight grading of cotton. The data for this study was generated by analyzing194 cotton samples collected from Raichur and Hubli markets. No variable was negativelycorrelated with scientific grade whereas ginning percentage, strength and trash content werenegatively correlated with eye-sight grades. A large number of variables were highlysignificant in determining scientific grades, whereas very few variables were significant in the

case of eye-sight grade. Further colour, 50 per cent span length and trash content were theonly factors which have highly significant relationship with eye-sight grades. With regard toscientific grades except mirconaire and maturity all the other measurable factors were foundto have significant effect upon scientific grade.

2.2 DEVELOPMENT OF GRADE STANDARDS FORIMPORTANT COMMODITIES

Sedky et al.(1972) evaluated pineapple grading at farm level. They found that fruitsharvested for canning were not uniform either in weight or in size. The average weight of thefruits was 2.33 pound ranging between 1.25 to 4.0 pounds. The average diameter of the fruitswas 4.48 inches with a range between 2.33 and 5.75 inches. The average length was 6.19inches with a range between 4.75 and 8.5 inches.

Yamanaka and Tsuchiya (1978) evaluated the grading methods of fresh fruits,

currently used in the marketing system in Japan, by employing econometric analysis. Theyapplied quantification theory, using the data obtained through the survey of the marketingprocess of mandarin oranges. Their findings indicated the necessity of simplifying the gradingsystem so as to improve its efficiency.

Agillion and Sardido (1979) studied grading and standarisation of fruits in philippines.Grading of fruits involved the classification by size and each class was graded according to itsgeneral appearance, quality and conditions. They found that grading practices in localmarkets were not uniform and the farmers and traders were not fully enlightened about theobjectives and procedures of the existing methods and grading standards, which counted tothe existing practices, should be implemented to assist farmers and to improve marketingefficiency.

Gholba (1982) evaluated the present prospects of grading or testing of wool oninternal basis. In his study the general complaint from the manufacturing was that raw wool

purchased by them did not come to their expectation inspite of paying high rate and it lackedconsiderably in quality. Gholba opined that the Directorate of Marketing and inspection, whichsuccessfully implemented the grading of wool for export, could easily handle the presentsituation without much difficulty. For wool samples received from the parties could facilitateand enable department officials to know the pattern of business, to collect the statistical dataon all the quality factors for framing specifications for grading wool under AGMARK and alsoto infuse confidence in the trade circle in respect of all those necessary facilities it would notbe difficult for the central agency like AGMARK to meet the present challenge.

Humbarwadi et al. (1981) found that grades had no relevance on prices in the field ofmarketing of agricultural produce even with the existence of competition.

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Wit (1984) evaluated the current practice of grading of fruits, vegetables, meat, eggs,poultry and fish, in the context of the existing Dutch quality control regulations. He concludedthat the present agricultural act afforded an opportunity to make the quality control marks, notonly completely reliable but also clearer for the consumer.

Takavarsha (1984) in his study on marketing of agricultural products, the economicsof statutory grading systems and produces, acceptance standards in the agriculturalmarketing process, using aggregated time series data for cotton and maize delivered to the

respective marketing boards in Zimbabwe by percentage grade composition. During 1973-87,he evaluated the trend and relationship between grade prices, quality grades, inter-gradeprice differential and the per unit weighed mean volume of the grades delivered during theperiod. He made a comparison between the rate of increase in grade prices and thecorresponding changes in the aggregated weighted, mean value of grades delivered and theimpact of inter grade price differential and percentage grade comparisons on the market valueof the products concerned. The second changes in the value of the products attributable forquality changes were also examined. He concluded that there were no signif icantly noticeablegains in returns to producers resulting from quality changes, due to fluctuations in thecompositions of grades delivered, and relatively small price differential for superior grades.The grading system had however, been significantly effective in discouraging marketing ofpoor grade and in maintaining quality standards and improving the marketing efficiency on thewhole.

Golou and Shalit (1985) developed an econometric model for grape pricing in Israel,based on the hypotheses that the market value of wine was positively correlated with thequality of grapes. The model included a set of producer pricing rules bases on the quality ofgrapes. They concluded that price differentiation by grape quality was necessary to ensurethe supply of quality wine in a regulated industry.

Murthy et al. (1996) made an attempt to develop grade standards for groundnut inChitradurga district of Karnataka. Appropriate weights were assigned to different qualitativevariables based on the opinion of different market functionaries. Using these weights acomposite index was developed by scoring method, which was the basis for determiningscientific grades. Groundnut is classified into 9 grades based on the composite index number.

Wader and Kumar (1996) studied the quality and non-quality characteristicsinfluencing price of cotton in Hubli and Raichur during the year 1990-91. A large number ofvariables were found to be not only insignificant statistically but were also associated withsign contrary to the expectation which suggests that prices were not paid according to thescientific evaluation of quality characters.

Tripathi (1997) studied the role of grading in marketing of apple fruits in chamba-mussoorie belt of Uttar Pradesh Hills. The factors determining the quality of apples were size,shape, stage of maturity, colour, free from injuries, blemishes, disease spots, brushes etc. Hetook diameter of the fruits into consideration while grading and graded the fruits into supersize (87 mm), extra large (81 mm), large (75 mm), medium (69 mm), small (63 mm), extrasmall (57 mm), piltoo (including culls) - (51 mm).

Wader and Murthy (1998) made an attempt to develop grade standards for cotton inRaichur and Hubli cotton markets of Karnataka. To develop grade standards weights wereassigned to different qualitative variables like ginning percentage, 50 per cent span length, 25per cent span length mean length, uniformity ratio, strength, fineness, maturity co-efficient,trash content, colour and feel based on the opinion of different market functionaries. Usingthese weights a composite index was developed by scoring method and cotton was classifiedinto 8 grades.

2.3 DEVIATION BETWEEN EYE-SIGHT GRADE ANDSCIENTIFIC GRADE

Sekhon et al. (1972) noticed reciprocal relationship between palmitic acid (p) andlinolic acid (l) content in groundnut. The greatest variation was observed in olecic acid content(41.10 to 66.80 per cent) and the lowest variation in linolic acid content (18.10 to 38.10 percent)

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Nichols (1972) compared the US combination grade of grape fruit with US Number 1grade of grape fruit. Data were collected from retail stores in two cities and analysed using a10 variance analysis model. He observed that the extent of relationship between grade andper customer sales depends on the degree of competition from the grape fruit supply areas. Achange in the grade from US combination to US No. 1 Resulted in a significant increase inper customer sale of grape fruit in the markets with high competitive supply and with theestablished standards of quality. He found no significant change in sale in the area where no

such competition existed.Petry and Anderson (1974) compared the wheat grades of United States with those

of Canada. They found that the change in Canadian wheat standards brought them into amore parallel position with United States wheat standards, especially with respect to themarketing of wheat with guaranteed protein contents.

Traylor and kiow (1978) compared the official government grades for rough rice withthe grades assigned by the trade in Louisiana. In general, they observed that trade assigneda lower quality numerical grade to a given sample of rice than grade turned out to be slightlybetter indicator of quality as measured by prices paid than the government grade.

Trapp (1981) studied the economic homogeneity of grade classifications under thenew and old feeder cattle grading system. He developed a methodology to determine thedegree of economic homogeneity of a given grade classes and opined that a morehomogeneous grade grouping was desirable. It was found that the new feeder cattle grading

system provided 12.50 per cent less homogeneous basic grade group classes than the oldsystem.

Kleijn (1991) observed that in the marketing process, onion were sorted into gradesaccording to quality characteristics such as size, appearance, shape and firmness. Until now,grading and sorting in the Dutch onion industry as a method for quality segmentation has notbeen optional. Better regrouping of onion would increase profits despite higher cost. Thehigher profits were achieved by cleaner markets, which facilitate purchasing, and by better-standardized products, which generate market efficiency. Gross price flexibility coefficients fordifferent grades derived using multiple regression analysis with time series data arecalculated to obtain the criterion for effective quality segmentation.

Gowda et al. (1994) compared the physico-chemical characteristics and processingquality of two IIHR tomato varieties with six commercial cultivars of different regions. Theyfound that juice yield was maximum in IIHR varieties Arka Ashish (71%). The total soluble

solids of IIHR variety (Arka Ashish and Anka Ahuti) were better (5.20

B, 5.60

B), while Acidity(0.55%)

and Ascorbic acid (5.2, 6.7mg/100g) were similar to other cultivars. Lycopene content

was maximum in Arka Ashish (7 mg/100g) followed by pusa Gaurav (16 mg/100g) and ArkaAhuti (5.2 mg/100 g). In viscosity, the IIHR varieties were better than Pusa Ruby, Roma andPusa gaurav. The viscosity of IIHR varieties was 188-270.

Thakur and Lal Kaushal (1995) studied the physico-chemical characteristics of sixcommercial varities and F1 hybrids of tomato grown in Himachal Pradesh. Tomatoes ofvarities like Punjab chuhara, Roma, Vaishali, Rajani and MTH-15 were determinate type.While remaining were indeterminate. All the varieties/hybrids had red surface colour whilesolan Golan, yashwant, Punjab chuhara, Roma, MTH-6 and MTH-15 had deep red colour.The varieties/hybrids with higher fruit weight had bigger fruit also. Oval shapedvarieties/hybrids had lower number of locules and their pericarp thickness was higher than theothers. Seed and waste matter were lowest in Punjab chuhara and juice percentage and totalsolids were highest in it. MTH-6 had recorded highest total soluble solids (5.47

0brix) and total

sugars of 3.55 per cent and reducing sugars 3.12 per cent. Oval shaped varities like Punjabchuhara and Roma had lower acidity (0.45 per cent, 0.48 per cent) and higher pH (4.3) thanspherical or round shaped varieties/hybrids. Spherical shaped varieties had lower pH (3.9-4.2) and higher acidity (0.56-0.68 per cent). Ascorbic acid content was found to be highest inVaishali (30.06 mg/100 g) while pectin was recorded higher in Rajani (0.198 per cent).

Murthy and Wader (1999) conducted a study on evaluation of eye-sight grading onprice of different varieties of groundnut at different markets of Chitradurga district ofKarnataka.

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From the studies reviewed, it is clear that there are studies conducted mostly inforeign countries and very few studies are available in our country also the studies conductedwithin India have dealt with evaluation of existing grading practices like working out ofpercentage of farmers knowing, prices of graded produce and time and labour saving due tograding etc. but none of the above studies have taken chemical and physical qualitativecharacteristics and non qualitative characteristics into consideration for eye sight grading andno studies have attempted to develop standards for scientific grading. Further, very few

studies are available in this regard in Karnataka. Therefore, an attempt is made here todevelop standards for scientific grading. An attempt is also made to study the effect of gradingon prices received by farmers. In brief, the present study was aimed at a study of quality,grading and prices of important fruit crop marketed in Karnataka by taking both qualitativecharacteristics and non qualitative characteristics simultaneously into account whiledeveloping scientific grading and to assess the impact of eye sight grading on prices of fruitmarkets in Karnataka.

2.4 PROBLEMS FACED BY THE TRADERS

Jagannathan (1995) identified the constraints encountered by sericulture farmers inCoimbatore district of Tamil Nadu. The study revealed that inadequate market facilities (80%),lack of control measures for silkworm disease (74%), non-availability of labour for picking ofleaves (70%), high wage rates of labour (64%), non-availability of disease free layings (52%)and disinfection chemicals in time (48%) and lack of skilled labour for rearing silkworms (60%)

were the major problems.

Das et al.(1997) examined difficulties encountered by farmers in adopting improvedtechnologies and suggestions made by the farmers in improving the sericulture industry. Dataare presented from 3 sericulture districts (Malda, Murshidabad and Birbhum) in West Bengal,India conducted during 1992-93, when 650 farmers in 25 villages were surveyed. Each farmerwas asked for five important problems relating to the extent and nature of hardship and tosuggest three measures to improve the sericulture situation. Thirteen problems are identifiedin the development of sericulture : non-availability of leaf; non-availability of DFLs; lack ofsuitable silkworm races; unfavourable climate; high incidence of disease and pest; lowcocoon production; poor quality cocoons; non-availability of markets; lack of technicalknowledge; existence of alternative crops; lack of government assistance; lack of skilledlabour and lack of finance. Fourteen measures were suggested : arrangements for subsidy;availability of irrigation water; supplying of rearing appliances; establishment of regulatedmarkets; supply of DFLs in time; arrangement for post-cocoon services; imparting training;financial assistance; supply of various input materials; supply of quality DFLs supply of HYVmulberry plants; controlling and monitoring input prices; regular vigilance by the office staff(both central and state) and strict maintenance of a crop schedule.

Kunt et al. (2001) studied the details of the problems faced by mango growers inreference to its marketing. They reported that majority of mango growers (59.72%) felt theproblem of higher marketing costs in marketing of this fruits. About 73 per cent growersexperienced the dominant role of traders are a major problem in its marketing non-availabilityof cold storage was also identified as a problem by 65.28 per cent mango growers more than50 per cent mango growers felt the transpiration problems in terms of non-availability oftransportation facility, lack of proper road and higher transportation cost.

Pagire (2001) concluded grade I quality grapes, marketing the grapes in the statelevel markets, selling the grapes to exporter traders and the period I were found to beimportant in receiving the higher prices.

Chauhan and Mehta (2004) reported that unremunerative prices during the peakseason and lack of storage facilities were reported to be the important constraints byvegetable growers. Besides all weather pucca roads. Costly grading and packing inadequateskilled labour and lack of information about arrivals and sizes prices in the major concerningmarkets were others problems reported by vegetable produces.

Gupta and Prashant (2004) analyzed the constraints in cashewnut production andmarketing. They reported that lack of money and essential

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Experiments needed for cashewnut production is a big constraint. About 91 per centproducers were facing this problem. Other important constraints are the lack of soil testingfacilities from which about 90 per cent cashew nut growers are affected.

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III. METHODOLOGY

This chapter deals with the selection of the study area and its description, the natureand source of data, various tools and techniques employed. This chapter is further dividedinto five sub-sections. They are;

3.1 Brief description of the study area

3.2 Data and sampling procedure

3.3 Measurement of characteristics of the samples by different instruments

3.4 Analytical techniques

3.5 Definitions and concepts of the terms used

3.1 BRIEF DESCRIPTION OF THE STUDY AREA

3.1.1 Bijapur district

Bijapur is one of the largest districts in Karnataka and has an area of 10541 sq. kmconsisting of 5.49 percent of the area of the state. It lies between 15

050

and 17

028 north

latitude and 74054 and 76

028 east longitude. The district is surrounded by Sholapur district

on the north and Sangli on the North West (both of Maharashtra state), by the district of

Belgaum on the west, Bagalkot on the south, Gulbarga on the east and by Raichur on thesouth east. Thus, it is a land locked district on the northern boundary of Karnataka. TheBijapur district consists of five talukas viz., Bijapur, Basavana Bagewadi, Indi, Sindigi andMuddebihal.

The climate of the district is generally dry, the large variation the rainfall, from year toyear, both in quantum and its distribution through the seasons. This makes the district moreprone to drought and famine. The average annual rainfall of the district is 668.2 mm. Thetemperature ranges from 14.8

0C to 43

0C. There are two main types of soil s namely black

soil and red soil. The main food crops are Jowar, Bajra, wheat and gram. Among thecommercial crops groundnut, Sesamum, linseed, cotton, safflower and sunflower are morepopular.

The medium rainfall, dry and healthy weather are considered to be the idealconditions for grape cultivation. Bijapur district in Karnataka has all these ideal conditions for

successful grape cultivation which is the major grape cultivating district in the northernKarnataka. It ranks first in the area under grape cultivation in Karnataka with 4390 hectareand with a production of 65805 tonnes during the year 2002-03. Grape cultivation is practicedthroughout the district. Almost all the produce in the study area, grape is known for quality.Hence, Bijapur was specially selected for the study.

Demographical features

According to 2001 census the total population of the district was 18.10 lakhs

Population of the district

Total : 18.10 lakhs (18.06918 inhabitants)

Male : 9.07 lakh

Female : 9.02 lakh

Density : The population density of Bijapur district is approximately 172 persons per sq km

Sex ratio : the sex ratio of the district 977/1000males

Literacy rate

According to 2001 census the literacy rate of the district is at 56 percent stoodmarginally above the state figure. The literacy rate among male is 57.95 whereas amongfemale it is only 39.14 percent.

Climate

The climate is warm and dry throughout the year and rainfall is scarce. The averageannual rainfall for the district is 552.8 mm with 37.2 rainy days. The monsoon generally

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breaks in the district during june and lasts till October. The highest mean monthly rain fall149.2 mm in the month of September and lowest is 3.5 mm in February. The annual rainfallvariation in the district is marginal from place to place

Soil type

The major soil types of the district are black soil and red soil Bijapur is very rich in redsoil which is conducive to the cultivation of horticultural crops.

Major crops

The major crops grown in this area are, Jowar, Bajra, groundnut, linseed, cotton,safflower, Sesamum and sunflower are more popular.

Horticultural crops

Grape, Pomegranate, Ber, Sapota and Papaya are the main fruit crops grown.Whereas Onion, Lemon, Cabbage, Cauliflower, Tomato and Brinjal are the importantvegetables grown in the district.

Sources of irrigation

The main source of irrigation are Canals, Bore wells and Tanks.

Land utilization

The total geographical area of the district is 10541 sq km which accounts for 8.9percent of the state geographical area.

3.1.2 Bagalkot district

The district of Bagalkot is situated entirely on the northern Karnataka plateau, whichis a part of larger Deccan plateau. Located in north central Karnataka, Bagalkot is surroundedby Belgaum district to the west, Bijapur district and Gulbarga district to the north andnortheast, Raichur district to the east and koppal district, Gadag and Dharwad districts to thesoutheast, south and southwest respectively. It is positioned at 16

012 N, 75

045E and covers

an area of 6593 sq km.

Bagalkot district is one of the major pomegranate growing districts occupying fourthposition in area and production next to Koppal, Bijapur and Bellary in the state. Whereas, withrespect to productivity Bagalkot occupies first position (13.50 t/ha) followed by Koppal (13t/ha), Bijapur (10 t/ha) and Bellary (7 t/ha). In addition to the considerable increase in the areaunder pomegranate crop in Bagalkot district (1016 ha in 2002-03 to 1702 ha in 2004-05) andalso as per the familiarity of the researcher with the study area forms the basis for selection ofthe study area.

Demographical features

According to 2001 census, the total population of the district was 16.52 lakh personswith 51 per cent males and 49 per cent females.

Population of the district

Total : 16.52 lakh

Male : 8.36 lakh

Female : 8.17 lakh

Density/sq. km. : 251Sex ratio : 977/1000

Literacy rate

According to 2001 census, the literacy rate of Bagalkot district was 57.81 per cent,higher than national levels (52 percent) but lowers the mean literacy rate of the state (66.6percent), the male literacy was at 71.31 per cent and female literacy was at 44.10 per cent.

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Climate

Climate is very warm and dry throughout the year and rainfall is scarce. Climate isvery hot in summer (April-may), the average temperature is 32 degree Celsius and duringwinter (November-January) 15 degree Celsius. Bagalkot district receives the lowest rainfallannually in Karnataka.

Soil type

The major soil types of the districts are medium black, red and sandy soils. Like mostof north Karnataka, Bagalkot is very rich in black soil which is conducive to the cultivation ofcotton.

Major crops

Major crops grown are Jowar, maize, wheat, red gram, soybean, sunflower,groundnut, cotton and sugarcane.

Horticultural crops

Pomegranate, Grapes, Mango, Sapota, Guava, Pappaya are the main fruit crops,whereas Tomato, Brinjal, Cabbage, Cauliflower and Onion are the important vegetablesgrown in the district.

Sources of irrigation

The main sources of the irrigation are canals, bore wells and tanks with net irrigatedarea of 2, 00,241 hectares.

Land utilization

The total geographical area of the district is 6593 sq. km which accounts for 5.49 percent of the states geographical area. The total cultivable area is 8, 63,395 hectares. Theaverage annual rainfall of the district is 610 mm.

The Agricultural Research Station and Krishi Vigyan Kendra are situated in Bagalkot districtwhich provides strong research and extension support as well as guidance to the farmers.There are two fruit co-operative societies.

3.2 DATA AND SAMPLING PROCEDURE

Bijapur and Bagalkot markets are the terminal producers market for grape, and

pomegranate in the state.

Samples were collected during the crop year 2005-06 from Bijapur and Bagalkotmarkets. The total sample size of 120 was considered. For each fruit crop two leadingvarieties were selected for gape fruits, 30 samples Thompson seedless and 30 samples ofSharad varieties were considered from Bijapur grape market. Similarly in case ofpomegranate 30 samples from Ganesh and 30 samples from Kesar varieties from Bagalkotmarket were collected in peak period of the respective fruit season of a respective fruit crop.Samples were selected randomly from the market.

The primary information was collected for the year 2005-06, the data were collectedfor these selected fruit crops through personnel interview from the traders with the help of wellstructured and pre-tested schedule.

Varieties selected

Grape : In grapes two varieties were selected namely Thompson Seedless and Sharad

Thompson seedless : 15 bunches were randomly picked from both farmers and traders. Foreye sight grading, the whole bunches were considered for the study but where as, in the caseof scientific grading, 10 berries were randomly selected and plucked from these bunches(total 30 bunches).

Sharad : 15 bunches were randomly picked from both farmers and traders. For eye sightgrading, the whole bunches were considered for the study but where as, in the case ofscientific grading, 10 berries were randomly selected and plucked from these bunches (total30 bunches).

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Pomegranate : In pomegranate two varieties were selected.

Ganesh : 15 fruits were randomly picked from both farmers and traders. Here, for both eyesight and scientific grading methods the same fruits were used.

Kesar : 15 fruits were randomly picked from both farmers and traders. Here, for both eye sightand scientific grading methods the same fruits were used.

3.3 MEASUREMENT OF CHARACTERISTICS OF THESAMPLES BY DIFFERENT INSTRUMENTS

The qualitative characteristics viz., Total soluble solids (brix), Total sugar (%), Acidcontent (percent), Weight of the pulp (gms), Juice content (ml/gms) and Seed content (no)were analysed chemically for scientific grading of grape and pomegranate fruits.

Total soluble solids

Total soluble solids of grape and pomegranate are determined by using ERMArefractometer. A drop of fresh fruit juice is put on the refractometer, and then recorded theTSS content

Acid content

The percent of any of a group compounds that give a sour or sharp taste in fruits.

Reducing sugar

The per cent reducing sugar in the juice was determined by Dinitro-salicylic acid(DNSA) method (Miller, 1972). A known volume of alcohol extract was taken and allowed toevaporate the alcohol completely. Clear solution was taken for estimation of reducing sugarusing DNSA-reagent by following the above method and results were expressed in per cent.

Non-reducing sugar

The per cent of non-reducing sugar was determined by substracting the per centreducing sugar from the per cent total sugar and multiplying the same with 0.95 as givenbelow (Somogyi, 1952).

Non-reducing sugar (%) = Per cent total sugar per cent reducing sugar 0.95

Weight of the pulp

The weight of the pulp is determined by peeling off of the outer skin of grape orpomegranate and weighed and it is expressed in terms of gms.

Weight of the skin

The weight of the skin is determined by peeling of the outer layer of the fruit andweighed to know the weight of the skin which is expressed in terms of gms.

Juice content

Five grams of grape berries are grinded and squeezed to estimate the juice content,expressed in terms of ml.

Seed Content

A pomegranate fruit from both varieties were picked at random and number of seedsper fruit is counted.

Visual observations of grapes

Visual observations such as colour, size, appearance, were observed and recorded.

The quality factors, which were analysed by observation method for grape that iscolour, size and appearance.

Colour

Colour is the visual sensation produced when light of different wave lengths isabsorbed by the fruit and relayed back to the eyes. This colour is also a parameter to check

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the quality of the fruit, there were three types of colour observed by naked eye they are lightgreen to yellow, yellow and green.

Size

The dimensions of the fruits in consideration which may be length, breadth, weight ofvolume or a combination of these characterstics.it also means largeness or magnitude. Threetypes of sizes observed by naked eye, these three types are small, medium and large.

Appearance

The outward or superficial look of fruits is known as appearance. There were twotypes of appearance observed clean and uncleaned.

By visual observation of Pomegranate

The quality factors, which were analysed by observation method for pomegranateare; 1) colour 2) size and 3) appearance.

Colour

Colour is the visual sensation produced when light of different wave lengths isabsorbed by the fruit and relayed back to the eyes. This colour is also a parameter to checkthe quality of the fruit. There were three types of colour observed by naked eye they are lightyellow to Red, Red and maroon.

Size

The dimensions of the fruits in consideration which may be length, breadth, weight ofvolume or a combination of this characterstics.it also means largeness or magnitude. Threetypes of sizes observed by naked eye, these three types are small, medium and large.

Appearance

The outward or superficial look of fruits is known as appearance. There were twotypes of appearance observed Bruise and unbruised

Chemical quality characteristics of important fruit crops

Thirty samples from each variety were selected for chemical analysis.

Analysis quality characteristics by chemical method were carried out in the gradinglaboratory of the Department of Agril. Marketing and Co-operation, Department of Soil

Sciences and Department of Biochemistry, at agriculture college Dharwad. They arediscussed below.

Total soluble solids

Total soluble solids of grape and pomegranate are determined by using Ermarefractometer. A drop of fresh fruit juice is put on the refractometer, and then TSS content.

Reducing sugar

Procedure for estimation of reducing sugars by Nelson Somogyis method for grapeand pomegranate fruit crops

Sugar by virtue of the presence of free or potentially free aldehyde (CHO) orketo (>C=0) group in them, reduce certain metallic ions such as copper, bismuth, mercury,iron and silver in alkaline solution. The colour change is quantified based on the amount of

sugar present. The following reagents were usedReagents

I. Alkaline copper reagent

Solution A

Dissolve 25 g of anhydrous sodium carbonate, 25 g of sodium potassium tarterate 20g sodium bicarbonate and 200 grams of sodium sulphate in about 800 ml of distilled water.Dilute to 1 litre

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Solution B

Dissolve 15 g copper sulphate in distilled water, add one or two drops of concentratedsulphuric acid and make up the volume to 100 ml with distilled water.

Mix solution A and B in 24:1 (v/v) proportion just before use.

II. Arsenomolybdate reagentDissolve 25 g of ammonium molybdate in 450 ml of distilled water. Add 21 ml of

concentrated sulphuric acid and mix. Dissolve 3 g of sodium orthoarsenate in 25 ml water.Mix the two solutions with stirring and place in an incubator at 37C for 24-48 hrs. Thereagent should be stored in brown bottle, which remains stable for a few months.

III. Stock standard solution

Dissolve 100 mg of D-glucose in distilled water in a volumetric flask. This solutioncontains 1 mg of glucose per ml. Prepare fresh on the day of work.

IV. Working standard solution

Dilute 10 ml of stock standard solution to 100 ml with distilled water in a volumetric

flask. This solution contains 100 g of glucose per ml and prepare fresh on the day of work.

Procedure1. Pipette out into a series of labelled test tubes suitable aliquots of working standard

(10-100 g) and make up the volume to 1 ml with distilled water in all the tests.Maintain a reagent blank with 1 ml distilled water.

2. Add 1 ml of freshly prepared alkaline copper reagent to all the tubes includingreagent blank and place them in boiling water bath for exactly 20 minutes. Cool underthe tap without shaking and add 1 ml of arsenomolybdate reagent with immediatemixing till effervescence subside.

3. Make up the volume to 20 ml with distilled water and read the % T of standard andthe sample against reagent blank which is set to 100 % T at 510 nm.

4. Calculate mg of reducing sugar present per g or 100 g of the sample with the help ofstandard graph.

Note: alcohol interferes in the sugar estimation. Evaporate alcohol from 1 ml ofalcoholic extract on a boiling water bath. Cool and make upto a known volume withwater and draw suitable aliquots for the estimation of reducing sugar.

Acid hydrolysis of non-reducing Sugar

Sucrose, the non-reducing sugar, does not exhibit reducing property. Since the activecarboxyl groups of its components, namely D-glucose and D-fructose are locked up ina glycosidic linkage. Sucrose, is therefore, first hydrolysed with the help of dilute mineral acidlike hydrochloric or sulphuric acid. The hydrolysate is neutralised and the reducing sugar areestimated by any of the suitable methods.

Reagents

1. Sucrose solution

1. Dissolve 80 mg of sucrose in distilled water and make up to 50 ml in a volumetricflask.

2. 0.1 and 1 N HCl and 1 N NaOH.

3. Phenolphthalein indicator in alcohol

Procedure

1. Place in a test tube 0.5 ml of sucrose solution. Add 0.5 ml of water followed by 1 ml of1N HCl and place on a water bath at 50C for 20 minutes. Cool, add a drop ofindicator solution and mix well.

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2. Add drop wise 1N NaoH till the solution turns pink due to excess alkali, reneutralisethe excess alkali with 0.1 N HCl which is added drop wise till the solution becomescolourless and make upto known volume (5 or 10 ml).

3. Draw suitable aliquots i.e., (0.5 ml or more) and estimate reducing sugar present inthe hydrolyate by Nelson Somogyis method.

4. Estimate the amount of reducing sugar in the alcoholic extract before and after

hydrolysis by any one of the method.5. The reducing sugar in the hydrolysate is a measure of total sugar. Subtract the

quantity of reducing sugar from this value, multiply by a conversion factor 0.95 to getreducing sugar.

3.4 ANALYTICAL TECHNIQUES

The analytical techniques employed in the study are

1. Tabular presentation

2. Step-wise multiple regression analysis

3. Correlation analysis and coefficient of variance

4. Composite Indexing

1. Tabular presentation

The techniques of tabular presentation was followed for identifying and comparing thequalitative variables like colour, weight of the pulp, reducing sugar, total soluble solids(TSS),colour, size, acids, juice content grade values and price per kg.

2. Step-wise multiple regression analysis

Step wise multiple regression function was employed in order to asses the influenceof fruit quality characteristics on the price of grape and pomegranate.

The stepwise multiple regression procedures involves relating one or moreindependent variables to a dependent variable where in the solution excludes those variablesthat do not make a minimum contribution to total explained variation. The test of significancefor variables is based on p values obtained from regression equation.

The most influential independent variable may be determined by selecting thatindependent variable which has the highest correlation coefficient with the dependentvariable. There were three models included; in first model price as dependent variable andqualitative characteristics as independent variables. In second model, price as dependentvariable and non-qualitative characteristics as independent variables and in third model, eye-sight grade as a dependent variable and qualitative characteristics as independent variables.

There are total 16 qualitative and non-qualitative variables included in the study. Inorder to include qualitative and non-qualitative variables such as size, colour, weight of thepulp, total soluble solids, acids, total sugars, juice content, seed content, appearance, weightof the skin and eye-sight grade. The non qualitative characteristics such as time of sale, timeof harvest, type of soil, variety and area under crop were considered under the study. Certainnon quantifiable (that could not be measured) variables were assigned dummy they werecolour, appearance, time of sale, time of harvest, type of soil and variety.

The qualitative characteristics that were in the study are size, colour, weight of thepulp, total soluble solids, acids, Total sugars, Juice content, Seed content, Appearance,weight of the skin and eye sight grade.

The non qualitative characteristics that were selected for the study are time of sale,time of harvest, soil type, variety, and area under crop.

The measurement unit for the qualitative and non fruit qualitative characteristics is asfollows.

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Fruit quality characteristics

1. Size (mm)

2. Colour - Grape light green to yellow, Yellow and green (Dummy). Pomegranate Lightyellow to red, red and maroon (Dummy)

3. Weight of the pulp (Grams)

4. Total soluble solids (Brix)5. Acids (Percentages)

6. Total Sugars (%)

7. Juice contents (ml)

8. Seed Contents (No)

9. Appearance (Grape-Clean and uncleaned) Dummy

(Pomegranate- Bruise and un bruised) Dummy

10. Weight of the skin (Grams)

11. Eye sight grade (dummy)

Non fruit qualitative characteristics

1. Time of sale (Soon after harvest, later) Dummy

2. Time of harvest (As and when ripens, high market price) Dummy

3. Variety (Grape- Thomson seedless, Sharad) Dummy

(Pomegranate- Ganesh, Kesar) Dummy

4. Area under crop (Acres)

5. Soil type (Black, Red loamy, Latertic soil) Dummy

There were totally six dummy variables included in the study among which two werequalitative dummies and the remaining four were non qualitative dummy variables.

The two qualitative dummy variables that were included in the study are

A. Colour for grapes light green to yellow (1), yellow (0) and Green(0) colours wereselected. for pomegranate light yellow to red (0), Red (0) and maroon (1) colourswere selected.

B. Appearance for grapes and pomegranates are clean (1) and uncleaned (0) andbruise (0) and unbruised (1) were selected respectively.

The four non qualitative dummy variables that were selected in the study are.

A. Time of sale for both grape and pomegranate units were soon after harvest (0) later(1).

B. Time of Harvest for both grapes and pomegranates the units were as and whenripens (0), High market price (1)

C. Soil type: the soil type necessary for both grape and pomegranate to achieve goodyields is red loamy soils (1), Black soil (0) and lateratic soil (0).

D. Variety for grapes Thompson seedless (1) and Sharad (0), for pomegranate Kesar (1)and Ganesh (0)

Following are the qualitative and non-qualitative variables included in the study.

Y = + 1X1+ 2X2+ 3X3+ 4X4+ 5X5+ 6X6+ 7X7+ 8X8+ 9X9+ 10X10+ 11X11+

12X12+ 13X13+ 14X14+ 15X15+ e

Where Y= dependent variable.

X1, X2, X3.......................................X 15 are independent variables.

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, 1,2,3................................... ..15 are Regression coefficients and,

e is random error.

Qualitative characteristics

X1 : Size (small, medium and large) (mm)

X2 : Colour (light green to yellow, yellow and green colour) dummy.Pomegranate (Light yellow to red, red, maroon) dummy

X3 : Weight of the pulp (gms)

X4 : Total soluble solids (brix)

X5 : Acids (%)

X6 : Total sugars (%)

X7 : Juice content (ml)

X8 : Seed content (Nos)

X9 : Appearance (Grape: Clean and uncleaned) Dummy

(Pomegranate: Bruise and unbruised) Dummy

X10 : Weight of the skin (Grams)

X11 : Eye sight grade

Non-fruit quality characteristics

X12 : Time of sale (Soon after harvest, later) Dummy

X13 : Time of harvest (As when ripens, High market price)Dummy

X14 : Soil type (red, black and lateritic soil) Dummy

X15 : Variety (Grape: Thompson Seedless, Sharad), Dummy

(Pomegranate: Ganesh and Kesar) Dummy

X16 : Area under crop (Acre.)

3. Correlation and co-efficient of variation

Correlation is used to identify the relation between price of eye sight grade andscientific grades in the case of grape and pomegranate fruit samples.

Similarly, coefficient of variations (C.V) is used to measure the extent of variation inthe eyesight grade and scientific grades. The coefficient of variation was calculated as follows

c.v = 100

4. Composite Indexing

For the Important quality characteristics of grape and pomegranate, appropriateweights were assigned. These weights were given based on the opinions of different marketfunctionaries such as, trader and merchants, and correlation coefficient attached to differentqualitative variables. The following weights were assigned to each variety included in thestudy.

Standard deviation

Mean

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Composite Index for grapes

Sl No. Characteristics Weights used (%)

1 Total sugars 0.30 (30%)

2 Total soluble solids 0.20 (20%)

3 Juice contents 0.20 (20%)

4 Size 0.08 (8%)

5 Appearance 0.06 (6%)

6 Eye sight grade 0.06 (6%)

7 Acids 0.05 (5%)

8 Colour 0.05 (5%)

Composite index for pomegranates

Sl No. Characteristics Weights used (%)

1 Seed content 0.25 (25%)

2 Total sugars 0.20 (20%)

3 Total soluble solids 0.15 (15%)

4 Size 0.10 (10%)

5 Eye sight grade 0.10 (10%)

6 Acids 0.05 (5%)

7 Appearance 0.05 (5%)

8 Colour 0.05 (5%)

9 Weight of the pulp 0.05 (5%)

Thus, a composite index for each sample of grape and pomegranate included in thestudy was worked out. Using these weights, a composite index was developed, which was thebasis for determining the standard for various grades. This in turn was the basis for scientific

grade.

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3.5 DEFINITION AND CONCEPTS OF THE TERMS USED

Grading

Grading is the process of sorting into different lots of a given product according to thestandards prescribed for the purpose. In other words, grading was considered as the processof dividing the produce of fruits in uniform groups according to certain standards specified forthe particular fruit crops in question.

Eye-sight grading

It is eye-sight (visual) inspection of qualitative characters such as appearance,cleanliness, scars, shape, size, ripeness, weight, colour and grade the products and bid theprice.

Scientific grading

In this case, the qualitative characteristics of the fruit crops such as total solublesolids, total sugars, acid content, juice content, seed content and weight of the pulp aremeasured in the laboratory and classified according to the grade specifications.

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IV. RESULTSThis section is devoted to present the results of those factors that were found to be

instrumental in price and grade determination, both qualitative and non-fruit quality factorsincluded in this analysis.

The results were presented in the following heads.

4.1 Fruit quality characteristic factors and non fruit qualitative characteristic factorsaffecting the prices

4.1.1 Fruit quality characteristics influence the price of grape and pomegranate

4.1.2 Non-fruit quality characters influence the price of grape and pomegranate

4.2 Development of grade standards for grapes and pomegranate

4.2.1 Development of grade standards for grape

4.2.1.1 Development of grade standards for Thompson Seedless variety of grape

4.2.1.2 Development of grape standards for Sharad variety of grape

4.2.2 Development of grade standards for pomegranate

4.2.2.1 Development of grade standards for Ganesh variety of pomegranate fruit

4.2.2.2 Development of grade standards for Kesar variety in pomegranate fruit

4.3 Determine the extent of deviation between eye-sight grading and scientific grading

4.3.1 Quality characteristics influence the eye sight grade prices of grape and pomegranatefruits

4.3.2 Deviation between eye-sight grade and scientific grade of Thompson variety of grape

4.3.3 Deviation between eye-sight grade and scientific grade of pomegranate

4.4 Impact of grading on price received by producer-seller

4.4.1 Impact of grading on price received by grape producer-seller

4.4.2 Impact of grading on price received by pomegranate producer-seller

4.5 Problems faced by the grape and pomegranate traders

4.5.1 Problems faced by the grape traders

4.5.2 Problems faced by the pomegranate traders

4.1 FRUIT QUALITY CHARACTERISTICS FACTORS ONFRUIT AND QUALITATIVE CHARACTER FACTORSAFFECTING THE PRICES

4.1.1 Fruit quality characteristics influence the price of grape andpomegranate

Step-wise multiple regression functions was employed in order to assess theinfluence of fruit quality characteristics factor influence the price of grape and pomegranate

and presented the results in Table 4.1.

There were ten fruit quality characteristics factors which were included in the step-wise multiple regression model taking price as dependent variable, however only two factorsin each fruit found significant in the model.

In the case of grape fruits, only two factors that is total sugars and medium sized fruitregression coefficient found to be significant in the model all other variables are deleted in thestep-wise regression model because the remaining variables were not contributed to theprice. The R

2value found to be 0.88 indicating 88 per cent of the total variation in the price of

grape was explained by explanatory variables.

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Table 4.1. Influence of fruit quality characteristics on prices of grape and pomegranate

Grape PomegranateSl.No.

VariablesRegressioncoefficients

R2

Regressioncoefficients

R2

0.88 0.79

1. Total sugars6.05** (0.009)

-

2. Size 2.904** (0.173) -

3. Weight of the skin - -6.236**(0.022)

4. Juice content - 0.76** (0.012)

Figures in the parentheses indicate the standard error (SE) value** - Significant at 1%

Table 4.2. Non fruit quality characteristics influence on prices of grape and pomegranate

Grape Pomegranate

Sl. No. VariablesRegressioncoefficients

R2 Regression

coefficientsR

2

0.58 0.64

1. Area under crop 1.792**(0.600)

3.725**(0.705)

2. Black soil (dummy) -4.79**(0.623)

-

3. Time of sale (dummy) - 0.332**(0.332)

4. Kesar variety (dummy) - 7.125**(0.414)

Figures in the parentheses indicate the standard error (SE) value** Significant at 1%

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In the case of pomegranate fruits, regression coefficients of weight of the skin andjuice content (6.23 and 0.76), respectively were found to be significant. The R

2value is 0.79

indicating 79 per cent of the total variation in the price of pomegranate fruit is explained byexplanatory variables.

4.1.2 Non-fruit quality characteristics influencing on prices of grape andpomegranate fruit

The non-fruit quality characteristics influence on prices of grape and pomegranatefruit is presented in Table 4.2. There were fruit quality characteristics influence the price ofgrape or pomegranate was considered. However, only two factors in grape fruit and threefactors in pomegranate fruit were found to be significant.

In grape fruit, regression coefficient of area under the crop (1.79) and type of soil (-4.79) are significant at 1 per cent level. The R

2value found to be 0.58 indicating 58 per cent

of total variation in prices as explained by non-fruit quality factors.

Similarly, in the pomegranate fruit crop, regression coefficients of time of sale (0.33),area under crop (3.72) and variety (7.13) were found to be significant at 1 per cent level. TheR

2value was found to be 0.64 indicating 64 per cent of the total variation in price explained by

these non-fruit quality factors.

4.2 DEVELOPMENT OF GRADE STANDARDS FOR GRAPES

AND POMEGRANATE4.2.1 Development of grade standards for grapes

4.2.1.1 Development of grade standards for Thompson Seedless variety ofgrape

The results of the analysis are present in table 4.3 the composite index wasdeveloped taking all qualitative characteristics by measuring and scoring for thecharacteristics considered for scientific grading.

In case of Thompson variety, the score of composite index ranges from 16.19 to17.07 was considered as grade I, the scores ranges from 15.32 to 16.18 considered as gradeII, the scores of composite index ranges from 14.45 to 15.31 considered as grade III and thescores of composite index ranges from 13.5 to 14.44 is considered as grade IV.

4.2.1.2 Development of grade standards for Sharad variety grape

The result of analysis are presented in the table 4.4, the composite index as could beclear in the table, the Sharad variety of grape scores ranges from 13.07 to 13.87 consideredas grade I, score ranges from 12.27 to 13.06 considered as grade II, the scores ranges from11.47 to 12.26 considered as grade III and the scores ranges from 10.67 to 11.46 consideredas grade IV.

4.2.2 Development of grade standards for pomegranate

4.2.2.1 Development of grade standards for Ganesh variety of pomegranatefruits

The composite index worked out to develop scientific grade were presented in thetable 4.5. The Ganesh variety got the composite index ranges from 48.95 to 52.24 (grade I),

40.67 to 48.94 (grade II), 42.38 to 45.66 (grade III) and 39.10 to 42.37 (grade IV).

4.2.2.2 Development of grade standards for Kesar variety of pomegranate fruits

The results of the analysis are presented in the table 4.6. it could be seen from thetable that, the Kesar variety got the scores ranges from 38.48 to 40.35 (grade I), 36.61 to38.47 (grade II), 34.74 to 36.60 (grade III) and 32.87 to 34.73 (grade IV).

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Table 4.3. Scientific grade standards for Thompson Seedless variety of grape

Sl. No. Grade standardsComposite index number of different

grades

1. I 16.19 17.07

2. II 15.32 16.18

3. III 14.45 15.31

4. IV 13.58 14.44

Table 4.4. Scientific grade standards for Sharad variety grape

Sl. No. Grade standardsComposite index number of different

grades

1. I 13.07 13.87

2. II 12.27 13.06

3. III 11.47 12.26

4. IV 10.67 11.46

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4.3 DETERMINE THE EXTENT OF DEVIATION BETWEENEYE-SIGHT GRADE AND SCIENTIFIC GRADE

It was hypothesized that eye sight grades deviate from scientific grades quitesignificantly and that they do not reflect actual quality of the grape. In order to test thishypothesis, it was necessary to determine scientific grades. This was accomplished on thebasis of the instrument. Measurements for all quality variables used in this study.

The quality of agriculture produce brought to be market by the farmers varied(considerably from lot to lot). This variation in quality is mainly due to the differences inmanagement practices like insect pest control methods and time of harvesting and agro-climatic factors etc. It is therefore highly essential to grade the produce on scientific gradingwhich should be based on objective evaluation of quality aspects. So, that the sellers could beable to describe the quality that they are offering and the buyers should understand what isbeing offered.

4.3.1 Quality characteristics influence the eye sight grade price of grape andpomegranate fruits

The step-wise multiple regression function was estimated separately for each fruit tostudy the effect of quality characteristics of prices on eye sight grade. In this model, eye sightgrade price was taken as dependent variable and qualitative factors as independent

variables. The regression coefficients are presented in Table 4.7. Out of 10 qualitativevariables considered in this model, but only six variables were found to be highly significant.

In grape fruit, regression coefficients of colour, appearance and size were 0.80, 0.23and 0.15, respectively and found to be highly significant. Other variables did not contributemuch to the eye sight grade determination. The colour and appearance is significant at 1 percent level whereas size was significant at 5 per cent level. The R

2value was found to be 0.80

indicating 80 per cent of total variation in the eye sight grade of grape explained byexplanatory variables.

In pomegranate fruit, regression coefficients for colour, acid content, total sugars andjuice content were found to be 0.45, -0.35, 2.45 and 0.28, respectively were highlysignificant. The colour, acid and total sugar content were significant at 1 per cent level andjuice content significant at 5 per cent level. The R

2value is 0.72 indicating 72 per cent of the

total variation in eye sight grade of pomegranate.

4.3.2 Deviation between eye sight grade and scientific grade of Thompsonseed less variety of grape

Table 4.8 shows that the results of deviation analysis of eye sight grade and scientificgrade. In eye sight grade the factors influencing the eye sight grade are total sugars, variety,size and appearance found to be significant. However, total sugars found to be negative.Similarly, in scientific grade total sugars, juice content and total soluble solids is highlysignificant at 1 per cent level. In scientific grade, juice content and total soluble solids (TSS) ishighly significant at 1 per cent level. The R

2value of eye sight grade w