Response Surface Methodology optimizes soil moisture content, rake angle, and forward speed for groundnut harvesting, suggesting efficiency improvements.
Efficient groundnut harvesting practices are essential for optimizing yield and reducing operational costs. This study optimizes the operational parameters of groundnut digging blades (V–blade and straight blade) using the Response Surface Methodology (RSM), under varying conditions. The effects of soil moisture content on wet basis (6%–9%, 9%–12%, 12%–15%), rake angle (15°, 20°, 25°) and forward speed (0.28, 0.35, 0.42 ms-1) on draft requirement (kgf) were examined for both blade geometries under the soil bin. The central composite rotatable design (CCRD) with a 2-factor interactions model was applied to correlate the independent parameters with the dependent parameter i.e., draft requirement. Ensuring statistical robustness, an analysis of variance (ANOVA) was performed on the model. The draft requirement for V–blade was lower as compared to that of straight blade. The soil moisture content, rake angle and forward speed, all had a significant effect on the draft requirement for both blade geometries. The draft requirement increased linearly with decreasing soil moisture content and increasing rake angle and forward speed. The optimized parameter for operating groundnut digger was V–blade working at 12%–15% soil moisture content, 15° rake angle and 0.28 m s-1 forward speed with 125.98 kgf draft requirement. This study establishes the groundwork for determining the optimal combination of digging blade parameters. These outcomes, translating to reduced time, energy consumption and costs, hold promise for field evaluations of the prototype digger.
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Kamendra et al. (2025) studied this question.
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