Optimal Cropping Pattern for Economic Sustainability Using Linear Programming Model

Abstract

Agriculture remains the backbone of rural livelihoods, yet farmers often face challenges in maximizing income due to traditional cropping patterns and resource limitations. This study focuses on Optimal Cropping Pattern for Economic Sustainability through the lens of Profit optimization, using Piplav village in Anand district as a case study. Linear Programming (LP) Model methodology was applied to select an optimal cropping pattern that enhances farm profitability while considering constraints such as land availability, labour, and input costs. Primary data were collected through field surveys and the LP model was designed to identify the most economically viable crop combinations. Results demonstrate that by adopting the optimized cropping pattern, farmers can significantly increase their net income compared to existing practices. The study highlights the potential of mathematical programming as a practical decision-making tool for rural farmers, encouraging a shift toward more sustainable and profitable agricultural systems. These findings offer valuable insights for policymakers, extension workers, and farming communities aiming to strengthen economic resilience in the agricultural sector. In future research, methods such as multi-objective programming and advanced computational models could be employed to address a broader range of variables, including environmental sustainability, rainfall variability, and changing market trends. Additionally, optimization techniques based on artificial intelligence will be explored to enhance the accuracy and adaptability of solutions under real-world field conditions. These approaches aim to develop more robust and practical strategies for crop planning, thereby supporting sustainable agricultural development.