PROBLEMS AND PROSPECTS OF JACKFRUIT CULTIVATORS - A STUDY WITH REFERENCE TO TAMILNADU

PROBLEMS AND PROSPECTS OF JACKFRUIT CULTIVATORS - A STUDY WITH REFERENCE TO TAMILNADU Mr.T.PANDIAN Research Scholar and Assistant Professor, Department of Business Administration, DDE, Annamalai University, Annamalainagar-608 002, Mobile-9486344976 Dr.K.SOUNDARARAJAN Associate Professor and Research Guide, Department of Business Administration, DDE, Annamalai University, Annamalainagar-608 002 ABSTRACT Jackfruits are soft and delicate, are more prone to damage and spoilage during handling and storage. Due to their high perishability, the postharvest management required is also high. It starts right from harvesting, field handling, transportation to pack house, pre-cooling and subsequent storage. Cold chains are essential component of horticultural postharvest infrastructure. It ensures maintenance of freshness of produce for extended period of storage. This article highlights problems and prospects of jackfruit cultivators-a study with reference to Tamilnadu. KEYWORDS Value-Added Food Industry, Jackfruit Cultivation, Harvesting Jackfruit, Problems and Prospects, Local Natural Resources, Fruit Producing. INTRODUCTION Jackfruit cultivation is one of the most important agricultural products in the country, which plays an important role in the economic development. The jackfruit cultivators are facing many problems in cultivation and harvesting season. During cultivation period the problem of rainfall, selection seed and financial assistance and harvest season the fruits losses due to lack of preservation. If the technique of manufacturing and preserving food subsistence in an effective manner with a view to enhance their shelf life, improve quality as well as make them functionally more useful. The jackfruit cultivation is based on local natural resources and indigenous knowledge and skill of the people. This sector directly contributing to income and employment generation and also induces output and employment growth indirectly through 63

its linkages with other sectors. Jackfruit processing can be done at home or in food processing industry. Besides reducing unnecessary wastage and losses of perishable items it helps in value addition, raising rural income by generating direct and indirect employment and diversifies the rural economy. The most important point in the jackfruit cultivation is that a substantial portion being rural based and it has very high employment potential with significantly lower investment. JACKFRUIT The scientific name of the jackfruit trees is Artocarpus heterophyllus, of the Moraceae family, which produces edible fruit. STATEMENT OF THE PROBLEM India is the one of the largest and most varied fruit producing nations in the world. Jackfruit is one of the most significant tropical fruit produced in India. The jackfruit cultivation is many centuries old and the farmers are unaware of the improved cultivation. They have many problems relating to cultivation, harvesting and marketing. In the cultivation stage they have problem with decrease in rainfall, natural calamities causes fluctuation in production and frequent drought conditions hampered the development of agriculture. In the harvesting stage perishable nature of fruits are wasted due to lack of storage facilities and lack of effective processing or preservation techniques, leads to high wastage. The pest and disease problem also results low output and poor quality of fruits. In the marketing stage they have many problems relating price fluctuation and lack of marketing problems. In Tamil Nadu is far from tapping the potential of processing and exporting dried jack fruits processors and exporters currently not available. Dried fruits have a large number of end-users including use in the dried fruit and nut industry. Besides, the inadequate rainfall of mansoon also causes fluctuation in production and frequent drought conditions hampered the development of jackfruit cultivation. In this backdrop this study is attempts to understand the problems and prospects of jackfruit cultivation in Tamil Nadu and to suggest suitable measures to improve this sector. OBJECTIVES OF THE STUDY- The objectives of the study are problems and prospects of jackfruit in select district of Tamilnadu. However, the following are the specific objectives of the study: 1. To identify the important problems faced by jackfruit cultivators in Tamil Nadu. 2. To ascertain the important prospects of jackfruit cultivators in Tamil Nadu. TESTING OF HYPOTHESES The following null hypothesis are framed and tested 1. Ho1: There is no significant difference between problems of Jackfruit cultivators on the basis of demographic profile of the respondents. 2. Ho2: There is no significant difference between prospects of Jackfruit cultivators on the basis of demographic profile of the respondents. METHODOLOGY The study is based on both primary and secondary data. The sources of secondary data are publications and seasonal crop report in Tamil Nadu and other Research Reports, Books, Journal articles and so on. Primary data are collected for understanding the problems of jackfruit cultivators in Tamil Nadu. In Tamil Nadu jackfruit cultivation are mainly concentrated in Cuddalore, Kanyakumari, Dindigul, Ariyalur and Pudukottai districts and they account for 73.21 per cent of area under jackfruit cultivation in 64

Tamil Nadu. In which Cuddalore account 27.22 per cent, Kanyakumari account 23.79 per cent and Dindigul account 13.81 per cent of the total jackfruit cultivation area of Tamil Nadu. Therefore Primary data were collected from these three districts. Here the study, based on primary survey, concentrates only on large area of jackfruit cultivation in Tami Nadu. SAMPLING DESIGN The Proportionate Stratified Sampling Method was used to select the respondents in jackfruit cultivators in Tamilnadu. This sampling involved in drawing sample from each stratum in proportion to the latter s share in the total jackfruit cultivators. 2 per cent of each category of jackfruit cultivators selected for districts namely Cuddalore, Kanyakumari and Dindigul were selected for the study. The sample size constituted 2 per cent of the universe i.e., 540 entrepreneurs. The universe constituting 27,000 jackfruit cultivators, were classified as shown in the following Table 1. Table 1 Selection of Sample Respondents S. No Name of the Districts Total Jackfruit Cultivators Selection of Sample Size (2%) 1. Cuddalore 12,450 249 2. Kanyakumari 9,910 198 3. Dindigul 4,640 93 Total 27,000 540 Source: Office Records for Committees -2014. ANALYSIS OF PROBLEMS AND PROSPECTS OF JACKFRUIT CULTIVATORS The collected data were summarised and scrutinized carefully for statistical analysis using SPSS package, is computer software for analyzing social science data. In order to achieve the meaningful conclusions, tabular technique of analysis was intensively used because of its simplicity. Finally, relevant Tables were prepared according to the requirement of data presentation to meet the objectives of the study. FACTOR ANALYSIS FOR PROBLEMS OF JACKFRUIT Analyses were done with the main objectives to find out the underlying common factors among 9 variables included in this study. Principal component factoring method with variance rotation was used for factor extraction. A two factors solution was derived using a score test. Table shows the results of the factor analysis. Name of all the 9 variables and their respective loadings in all the two factors are given in the table. An arbitrary value of 0.38 and above is considered significant loading. A positive loading indicates that greater the value of the variable greater is the contribution to the factor. On the other hand, a negative loading implies that greater the value, lesser its contribution to the factor or vice versa. Keeping these in mind, a study of the loadings indicates the presence of some significant pattern. Effort is made to fix the size of correlation that is meaningful, club together the variables with loadings in excess of the criteria and search for a concept that unifies them, with greater attention to variables having higher loadings. Variables have been ordered and grouped by the size of loadings to facilitate interpretation and shown in table. Factor analysis was done among 9 variables used in the study. The principal component analysis with varimax rotation was used to find out the percentage of variance of each factor, which can be grouped together from the total pool of 9 variables considered in the study. The results are given in table and column 1 shows the serial number, 2 shows the name given for each factor, 3 shows variables loaded in each factor, 4 gives the loadings, 5 gives the communality for each variables, 6 gives the Eigen value for each factor and 7 gives the percentage of variance found out through the analysis. 65

Table 2 Communalities Variables Initial Extraction Choosing the seedlings 1.000.827 Purchase of seedlings 1.000.429 Financial Problem 1.000.514 Maintenance Problem 1.000.722 Reasons for low yield in Jackfruit 1.000.572 Labour Problems 1.000.496 Selling problem 1.000.726 Problems in Direct selling of regulated markets/ Mundy 1.000.627 Selling problems with brokers 1.000.881 Extraction Method: Principal Component Analysis. Source: Computed from the primary data From the Table 2 shows that in the data interpretation on problems of jackfruit cultivators through factor analysis, out of nine variables, selling problems with brokers, variable got high communality value (0.881). It means extracted factors are able to explain low variance in that the variable more effectives than other variables and purchase of seedlings variable got lowest communality value (0.429). It means that the extracted factors are not able to explain much variance in that variable. Such variable may be dropped from the analysis. Table 2(a) Total Variance Explained Initial Eigen values Extraction Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % 1 3.478 38.641 38.641 3.478 38.641 38.641 2 1.240 13.780 52.421 1.240 13.780 52.421 3 1.076 11.953 64.374 1.076 11.953 64.374 4.903 10.029 74.402 5.709 7.877 82.279 6.621 6.895 89.174 7.455 5.056 94.230 8.307 3.414 97.644 9.212 2.356 100.000 Extraction Method: Principal Component Analysis. Source: Computed from the primary data Table 2 (a) shows that percentage of variance in respect of 9 variables in problems in jackfruit cultivation. These variables have been rotated to ascertain cumulative percentage of variance. The factor 1 causes 38.641 per cent of variance factor 2 causes 13.780 per cent of variance and factor 3 causes 11.953 per cent of variance in problems in jackfruit cultivators. The overall three factors cumulatively contribute 64.374 per cent. 66

Table 2 (b) Component Matrix a Factors Components 1 2 3 Choosing the seedlings.193.448.767 Purchase of seedlings.652 -.055 -.028 Financial Problem.666.206 -.167 Maintenance Problem.785.315 -.076 Reasons for low yield in Jackfruit.500 -.185.536 Labour Problems.616.000 -.342 Selling problem.825 -.212 -.004 Problems in Direct selling of regulated markets/ Mundy.789 -.041 -.056 Selling problems with brokers -.150.902 -.211 Extraction Method: Principal Component Analysis, a. 3 components extracted. Source: Computed from the primary data The factors are arranged based on the Eigen value viz F1 (Eigen value 3.478) F2 (Eigen value 1.240) F3 (Eigen value 1.076) These three factors are described as this model has a strong statistical support and the Kaiser-Maya- Olkin (KMO) test of sampling adequacy concurs that the sample taken to process the factor analysis is statistically sufficient (KMO value = 0.9241). CORRELATION ANALYSIS Correlation analysis deals with the relationship between two or more variables. Correlation analysis significantly related to prospects of jackfruit cultivation and Sub Factors. Table 3 Correlation Analysis Factors Prospects in Cultivation Financial Prospects Marketing Prospects Technical Prospects Prospects in.273 **.404 **.162 ** Cultivation Financial Prospects.273 **.313 **.282 ** Marketing Prospects.404 **.313 **.250 ** Technical Prospects.162 **.282 **.250 ** Source: Computed from Primary data It is noted from the Table 3 shows that the prospects jackfruit cultivation and marketing indicates significantly and positively correlated to all sub factors. It indicates the relationship between the prospects in cultivation and significantly correlated to prospects in cultivation, financial prospects, marketing prospects and technical prospects. 67

FACTOR ANALYSIS FOR PROSPECTS OF JACKFRUIT Analysis was done with the main objectives to find out the underlying common factors among 4 variables included in this study. Principal component factoring method with variance rotation was used for factor extraction. Any two factors solution was derived using a score test. Table shows the results of the factor analysis. Name of all the 4 variables and their respective loadings in all the two factors are given in the table. An arbitrary value of 0.42 and above is considered significant loading. A positive loading indicates that greater the value of the variable greater is the contribution to the factor. On the other hand, a negative loading implies that greater the value, lesser its contribution to the factor or vice versa. Keeping these in mind, a study of the loadings indicates the presence of some significant pattern. Effort is made to fix the size of correlation that is meaningful, club together the variables with loadings in excess of the criteria and search for a concept that unifies them, with greater attention to variables having higher loadings. Variables have been ordered and grouped by the size of loadings to facilitate interpretation and shown in table. Factor analysis was done among four variables used in the study. The principal component analysis with varimax rotation was used to find out the percentage of variance of each factor, which can be grouped together from the total pool of 9 variables considered in the study. The results are given in table and column 1 shows the serial number, 2 shows the name given for each factor, 3 shows variables loaded in each factor, 4 gives the loadings, 5 gives the communality for each variables, 6 gives the Eigen value for each factor and 7 gives the percentage of variance found out through the analysis. Table 4 Communalities Variables Initial Extraction Prospects in cultivation 1.000.474 Financial Prospects 1.000.476 Marketing Prospects 1.000.564 Technical Prospects 1.000.337 Source: Computed from Primary data, Extraction Method: Principal Component Analysis. From the Table 4 shows that the data interpretation on prospects of jackfruit cultivators through factor analysis, out of four variables, marketing prospects, variable got high communality value (0.564). It means extracted factors are able to explain low variance in that the variable more effectives than other variables and technical prospects variable got lowest communality value (0.337). It means that the extracted factors are not able to explain much variance in that variable. Such variable may be dropped from the analysis. Table 4 (a) Total Variance Explained Initial Eigenvalues Extraction Sums of Squared Loadings Component Total % of Variance Cumulative % Total % of Variance Cumulative % 1 1.851 46.267 46.267 1.851 46.267 46.267 2.873 21.837 68.103 3.692 17.308 85.412 4.584 14.588 100.000 Source: Computed from primary data Extraction Method: Principal Component Analysis. 68

Table 4 (a) shows the percentage of variance in respect of four variables in prospects of jackfruit cultivation. These variables have been rotated to ascertain cumulative percentage of variance. The factor causes 42.267 per cent of variance in problems in jackfruit cultivators. Table 4 (b) Component Matrix a Variables Component 1 Prospects in cultivation.688 Financial Prospects.690 Marketing Prospects.751 Technical Prospects.580 Extraction Method: Principal Component Analysis. Source: Computed from primary data, a.1 components extracted. The factor is arranged based on the Eigen value viz F1 (Eigen value 1.851) These three factors are described as this model has a strong statistical support and the Kaiser-Maya- Olkin (KMO) test of sampling adequacy concurs that the sample taken to process the factor analysis is statistically sufficient (KMO value = 0.8729). Table 5 Descriptive Statistics and Rank Analysis Variables N Mean Ranks SD SE Skewness Kurtosis Prospects in Cultivation 540 48.67 A 5.87 0.25 0.45 0.05 Financial Prospects 540 14.54 C 2.80 0.12 0.96 0.28 Marketing Prospects 540 21.74 B 3.99 0.17 0.09 0.33 Technical Prospects 540 11.08 D 2.03 0.09 0.11 0.07 Source: Computed from Primary data It is noted from the Table 5 shows that prospects in cultivation (48.67) scored higher mean value than other groups. It indicates prospects in cultivation groups have high level of mean score than other groups and Skewness value is 0.45 and Kurtosis value is 0.05. In the case of Prospects in cultivation rank is A, Marketing Prospects rank is B, Financial Prospects rank is C and Technical Prospects rank is D. SUGGESTIONS 1. To distribute various machineries like Hand operated Jackfruit cutter, Jackfruit cutter machine, Electric Cabinet dryer, Sealing machine, Wet grinder are essential for processing the fruits into various value added products of good demand. 2. More importance is needed to provide adequate and timeliness of credit availability to the cultivators. 3. Enhancing awareness on improved production and postharvest handling techniques can be made possible through training activities. 4. To enhance the poor infrastructure facilities like multipurpose cold storage facility, packaging and transportation. 5. Educating the farmers about the improved cultivation and marketing practices through an integrated extension network. 6. The horticulture department has to educate the farm cultivation and support to farm investment. 7. Development of farmer organizations to the help manage village-level investment and to enable farmers to have a greater voice in national and local policy. 69

8. The government has to encourage corporate sectors to install food processing factory at the major production districts of Cuddalore, Kanyakumrai and Dindigul. 9. The horticulture department has to educate the farm cultivation and support to farm investment. 10. Organize linkages between entrepreneurs and financial institutions for financing Jackfruit processing. 11. The government has to encourage corporate sectors to install food processing factory at the major production districts of Cuddalore, Kanyakumrai and Dindigul. 12. To encourage the processing of value added products in commercial scale for their livelihood enhancement. 13. There is a need to strengthen the market capacities of the cultivators, including their access to good-quality roads and an efficient transport system, as well as to market information. Strengthening market capacities of the cultivators can be achieved through more investments in education and technical training. CONCLUSION The present study concluded that, the major problem in jackfruit cultivation is inefficient handling and transportation; poor technologies for storage, processing, and packaging; involvement of too many diverse actors; and poor infrastructure. Jackfruits are soft and delicate, are more prone to damage and spoilage during handling and storage. Due to their high perishability, the postharvest management required is also high. It starts right from harvesting, field handling, transportation to pack house, precooling and subsequent storage. Cold chains are essential component of horticultural postharvest infrastructure. It ensures maintenance of freshness of produce for extended period of storage. The cultivation requires linking operations more closely and systematically, modernizing marketing infrastructure and technologies, capacity building of the cultivators, and strengthening the policy for better marketing. REFERENCES 1. Azad, A.K., Jones, J.G. and Haq, N. (2007), Assessing morphological and isozyme variation of jackfruit in Bangladesh, Agroforestry System, 71, pp. 109-125. 2. Azam, F.M.S., Rahmatullah, M. and Ather-uz-Zaman (2009), Tissue culture of a year-round fruiting variety of Artocarpus heterophyllus, Bangladesh, Acta Horticulture, 806(1): 269-276. 3. Bhatia, S., Siddappa, G.S. and Lal, Giridhari (1956), Product development from the fruits, Indian journal agriculture, 25: 408. 4. Bose, T.K., (1985), Jackfruit. In B. K. Mitra (Ed.), Fruits of India: Tropical and subtropical naya prokas, Calcutta, India. 5. Datta, S.C. and Biswas, S.C. (1972), Utilization of fruits for dietary purposes, Indian Farming, 3: pp.527-553. 6. Guruprasad, T.R., (1981), Studies on systematic selection of jackfruit types, M.Sc.(Hort.) Thesis, University Agriculture Science, Bangalore, India. 7. Jinsu Varghese and M. Haridas (2007), Prospects of Jackfruit Blend Yoghurt Whey, World Journal of Dairy & Food Sciences 2 (1), pp. 35-37, 2007. 8. Konhar, T., Murmu, S. and Maharan, T. (1990), a study on the budding methods of propagation of jackfruit, Orissa journal of agricultural research 3(2), pp. 115-119. 9. N.K. Halder, A.T.M. Farid and M. A. Siddiky (2008), Effect of Boron for Correcting the Deformed Shape and Size of Jackfruit, Journal of Agriculture & Rural Development, 6 (1&2), pp. 37-42. 70

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