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Research Article Open access CC BY 4.0

Growth and Instability Analysis of Vegetable Crops in Chhattisgarh Plains: A Production Function Approach

Prachi Jaiswal, Sweta Ramole, Ankur Gupta

Journal of Scientific Research and Reports · pp. 10–19 · Published 29 Sep 2025

10.9734/jsrr/2025/v31i103544

Abstract

This study analyzes the production dynamics of five major vegetable crops—Brinjal, Okra, Cauliflower, Potato, and Tomato—in Chhattisgarh, India, using district-level data from 2004–05 to 2021–22. Secondary data from 17 districts were compiled into a relational database and examined through stepwise regression-based production function models, incorporating both annual and periodic effects to capture structural changes in crop performance. The models demonstrated high explanatory power, with R² values of 98.12% for Brinjal in Rajnandgaon, 98.98% for Okra in Bilaspur, 98.32% for Cauliflower in Koriya, 98.39% for Potato in Kabirdham, and 98.9% for Tomato in Rajnandgaon. Decomposition of results revealed significant heterogeneity across districts: in Jagdalpur, Bastar, Koriya, and Kabirdham, production was primarily area-driven, whereas in Bilaspur, Jashpur, and Mahasamund, productivity gains played the dominant role. These findings highlight the dual pathways of agricultural growth—through area expansion and productivity enhancement—and provide critical insights for policy formulation. For sustainable vegetable development, district-specific interventions are essential: improved seeds, irrigation, and nutrient management in productivity-led regions, and land-use optimization in area-driven regions. The research underscores the value of econometric modeling and database-driven analysis in guiding evidence-based agricultural planning and enhancing predictive accuracy for future crop performance.

Production function modeling area and productivity analysis growth and instability econometric modeling relational database spatio-temporal dynamics stepwise regression policy implications

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