ArticleData in brief2024
Dataset on the status of crop diversification in the Eastern Indo Gangetic Plains of South Asia.
Article in Data in brief, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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3 authors.
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Abstract
South Asia's Eastern Indo-Gangetic Plains (EIGP) is home to approximately 450 million people. This region is characterized by the highest global concentration of rural poverty and a predominant reliance on agriculture for nutritional sustenance and economic livelihoods. Agriculture in the EIGP is highly cereal-centric, making crop diversification indispensable for its development. This data article is part of the research conducted by an interdisciplinary team of researchers analysing the status and determinants of crop diversification in South Asia's EIGP. The data presented here were collected from 1,400 farm households across 72 communities in eight locations within the EIGP of India, Nepal, and Bangladesh during the year 2023. The research employed a simple random sampling method for empirical data collection. The primary agricultural decision-makers were given a tailored questionnaire comprising seven modules. These modules sought comprehensive data on livelihood practices, changes in agriculture, aspirations, diet, food security, mechanization, demographics, and asset ownership. The questionnaire was translated from English into Nepali and Bangla to facilitate a thorough understanding of the farmers' livelihoods in the study areas. The survey successfully ended with 1400 properly filled and captured questionnaires, which was quite representative. The cross-sectional data presented here describe location-specific farm-level crop distribution, enabling the analysis of geographic variations in crop diversification. The generation of this dataset addresses a significant gap in the availability of information on the current state of crop diversification in the EIGP, offering a foundational baseline for future research and interventions by regional governments and development partners. We employed the Herfindahl-Hirschman Index (HHI) to calculate crop diversification and a Tobit Regression Model to identify the region-specific determinants of crop diversification. The dataset is hereby made available as it is considered vital for regional policy and practical recommendations.
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