Linear Programming-Based Crop Planning for Farm Profit Improvement in Jagdishpur Block, Bihar

Improving farm income in smallholder agriculture requires crop plans that reflect both local resource constraints and realistic economic opportunities. This paper presents a linear programming model for crop planning in Jagdishpur Block, Bhagalpur district, Bihar. Using block-level data on cultivable area, labor availability, crop yields, production costs, and output prices, the model identifies the land allocation that maximizes annual net return. The optimized solution raises estimated net profit from Rs 40.92 crore under the observed crop pattern to Rs 72.33 crore, mainly through expanded allocation to sugarcane and pulse crops. The results also reveal a marked gap between the mathematical optimum and actual farmer practice. This paper argues that the gap is explained less by farmer irrationality than by missing infrastructure in processing, aggregation, procurement, and market support. The analysis illustrates how optimization can guide local agricultural planning while also showing that profitable crop recommendations must be interpreted together with value-chain capacity and implementation constraints.