Classification of Mango Farmers in Malda District for better Developmental Policies: A Multivariate Clustering Approach

Mango is a bulky and nutritious fruit crop and it had high demand for it’s delicious taste, soothing aroma, varietal diversity and wide adoptability to meet food and nutritional security. India is the largest producer of mango among that West Bengal is one of the contributors in the Indian mango basket. Malda district alone contributes more than 50 per cent of the mango production of the state from thirty one thousand hectares out of total eighty one thousand hectare mango area in West Bengal. In the present study an attempt has been made to critically analyse the status of mango farming by taking a random sample of 110 mango farmers from five selected blocks of Malda district adopting two stage sampling method with a specific objective to group the farmers in homogenous clusters to facilitate the developmental policy for different group of mango farmers. Among the parameters under study operational cost per unit of area under mango orchard is contributing maximum 26.67 per cent in cluster discrimination using Euclidian distance measure. Salient feature of the clustering analysis is the formation of five different groups by five farmers, thereby indicating the need for in depth study of these farmers so as to unearth the speciality of forming separate groups by these farmers. The present study thus, recommends for formation of cluster wise developmental policies for the betterment of the age-old mango farming in the district.

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Journal
Journal of Scientific Research and Reports
Published
2024-12-16
DOI
https://doi.org/10.9734/jsrr/2024/v30i122679
Primary Topic
Agricultural Economics and Practices
Type
article
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article

Classification of Mango Farmers in Malda District for better Developmental Policies: A Multivariate Clustering Approach

Pradeep Mishra, Abdullah Mohammad Ghazi Al khatib, P. K. Sahu, Mrittika Das et al.
Journal of Scientific Research and Reports
Agricultural Economics and Practices
article

Classification of Mango Farmers in Malda District for better Developmental Policies: A Multivariate Clustering Approach

Pradeep Mishra, Abdullah Mohammad Ghazi Al khatib, P. K. Sahu, Mrittika Das, Bankim Sarkar
article en

Abstract

Mango is a bulky and nutritious fruit crop and it had high demand for it’s delicious taste, soothing aroma, varietal diversity and wide adoptability to meet food and nutritional security. India is the largest producer of mango among that West Bengal is one of the contributors in the Indian mango basket. Malda district alone contributes more than 50 per cent of the mango production of the state from thirty one thousand hectares out of total eighty one thousand hectare mango area in West Bengal. In the present study an attempt has been made to critically analyse the status of mango farming by taking a random sample of 110 mango farmers from five selected blocks of Malda district adopting two stage sampling method with a specific objective to group the farmers in homogenous clusters to facilitate the developmental policy for different group of mango farmers. Among the parameters under study operational cost per unit of area under mango orchard is contributing maximum 26.67 per cent in cluster discrimination using Euclidian distance measure. Salient feature of the clustering analysis is the formation of five different groups by five farmers, thereby indicating the need for in depth study of these farmers so as to unearth the speciality of forming separate groups by these farmers. The present study thus, recommends for formation of cluster wise developmental policies for the betterment of the age-old mango farming in the district.

Journal of Scientific Research and ReportsVol. 30(12)
Bidhan Chandra Krishi Viswavidyalaya (IN), Damascus University (SY)
Openalex Percentile: Top 59%
Agricultural Economics and Practices
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Classification of Mango Farmers in Malda District for better Developmental Policies: A Multivariate Clustering Approach — Pradeep Mishra, Abdullah Mohammad Ghazi Al khatib, et al. · Journal of Scientific Research and Reports (2024) | TGRS Research Map | TGRS