Experimentation is fundamental to advancements in science and technology, particularly for optimizing agricultural machinery. This research aims to demonstrate the efficacy of the Design of Experiments (DOE) as a robust methodology in improving the performance of postharvest processing equipment, such as shelling, threshing, and decorticating machines used for postharvest operations in pods, seeds and nuts processing. Using a case study on a melon seed shelling machine, the Response Surface Methodology (RSM) was employed to optimize two key operating parameters: seed moisture content and motor speed after full. A Box-Behnken Design was selected for its efficiency, requiring 13 experimental runs. Analysis of Variance (ANOVA) confirmed the high significance of the developed quadratic model (F-value = 50.03, p 0.001), which exhibited an excellent fit (adjusted R² = 95.33%). The results identified optimal parameters: a motor speed of approximately 1920 rpm and a moisture content of 24%, achieving a shelling efficiency of 93%. The second-best configuration yielded a motor speed of 2182 rpm and a moisture content of 22%, resulting in a shelling efficiency of 91%. Verification tests conducted at these optimal settings demonstrated an average relative error of only 0.65%, indicating strong alignment between the predicted and actual outcomes and thus validating the accuracy of the model. These findings confirm that RSM is an effective tool for optimizing the performance and productivity of agricultural machinery in the melon seed industry.
Kevin et al. (Fri,) studied this question.