Cotton stalk management after harvest remains a critical challenge in Indian agriculture due to high labour requirements and environmental concerns associated with residue burning. This study presents a novel optimisation-driven design approach for a cotton stalk harvesting machine by integrating a laboratory-scale prototype with response surface methodology (RSM) to systematically evaluate and optimise key operational parameters. Unlike conventional approaches, this work establishes a quantitative relationship between machine design variables and performance indicators, enabling predictive optimisation for field applicability. The effects of peripheral speed, forward speed and blade type were investigated through 26 experimental runs, focusing on the bulk density and machine output of chopped cotton stalks. Results demonstrated that blade type and operational speeds significantly influenced performance, with strong interaction effects between peripheral speed and blade type at the 1 % significance level. Bulk density ranged from 143.85 to 249.38 kg m-3, while machine output varied between 211.3 and 573.5 kg hr-1. The optimised parameter combination, consisting of a peripheral speed of 57.95 m s-1, a forward speed of 2.21 km hr-1 and L-type blade, yielded a predicted output of 573.67 kg hr-1 and a bulk density of 255.27 kg m-3. Importantly, these optimised conditions provide practical operational benchmarks for field-scale implementation, demonstrating the potential to enhance chopping efficiency, reduce manual labour dependency and minimise environmental impacts. The study thus contributes a scalable and performance-validated framework for improving cotton residue management under real agricultural conditions.
