Status and drivers of crop diversification in the Eastern Gangetic Plains of South Asia: Across borders and communities

Abstract

Crop diversification is indispensable for the development of Agriculture in the Eastern Gangetic Plains (EGP) of South Asia. Given policy imperatives encouraging crop diversification, significant evidence, and knowledge gaps remain, with a lack of integrative studies that quantitatively and qualitatively assess the diverse and intricate dimensions of crop diversification within the broader context of the EGP. The study assesses the spatiotemporal patterns of crop diversification, aiming to elucidate the nuanced challenges associated with transitioning to more diversified cropping systems and identifying country-specific determinants within the EGP. Uses cross-sectional data from 1397 farm households across 72 communities in India, Nepal, and Bangladesh. Combine descriptive and quantitative analysis to explore seasonal and regional aspects of crop diversification. Besides, the Herfindahl-Hirschman Index (HHI) to assess current crop diversification levels. A Tobit Regression Model is used to identify the country-specific determinants of crop diversification. Results revealed significant variation in crop diversification across the EGP, with notable seasonal and regional differences. Family size influences diversification in all three countries, while factors such as joint decision-making with a spouse, solar-powered irrigation, and orchard ownership vary regionally. Rice remains dominant during the summer monsoon (kharif) season, but there is a shift towards greater diversification in the winter (rabi) season, suggesting potential for further diversification. This study provides a comprehensive overview of diversification patterns and their drivers in the EGP, capturing broad trends and local nuances. It offers valuable baseline information for promoting crop diversification and underscores the need for tailored approaches to enhance sustainability in this poverty-dense and agriculturally dependent region.