Design and experiment of reciprocating herbaceous mulberry harvesting tester

• A prototype herbaceous mulberry harvester was developed with sensor-based monitoring. • Real-time torque and speed data enabled in situ measurement of power consumption. • Response surface methodology quantified effects of speed factors on energy and stubble. • Cutting power was 3.7 times conveying power; cutter speed had the strongest influence. • Optimal parameters reduced power use and improved stubble quality with <5% deviation. Efficient harvesting of herbaceous mulberry is essential for reducing labor costs and ensuring high-quality stubble for rapid regrowth in sericulture production. However, existing mechanized harvesters rarely enable in situ measurement of cutting and conveying power under field conditions, and the influence of operational parameters on both energy consumption and stubble quality remains insufficiently quantified. In this study, a crawler-type prototype harvester equipped with three independently driven AC servo motors and real-time torque sensors was developed to monitor cutting, conveying, and baling processes. A Central Composite Design (CCD) combined with response surface methodology was employed to investigate the effects of forward speed, conveying speed, and average cutting speed on average cutting power per branch, average conveying power per branch, and stubble quality score. Field trials were conducted in Rizhao, Shandong Province, China, using the mulberry cultivar ‘Guishangyou 12’. The regression models exhibited high goodness of fit (R² = 0.9546∼0.9946) and non-significant lack of fit (p > 0.05). Results indicated that cutting power consumption was on average 3.7 times higher than conveying power, with cutting speed exerting the most significant influence on energy use (p < 0.01) and stubble quality (p < 0.01). The optimal parameter combination—forward speed of 0.55 m/s, conveying speed of 0.96 m/s, and cutting speed of 0.95 m/s—reduced cutting power to 26.91 J·branch⁻¹, minimized conveying power to 6.64 J·branch⁻¹, and achieved a stubble quality score of 9.43. Validation experiments confirmed that deviations from predicted values were <5%. These findings provide a quantitative basis for operational optimization and energy efficiency improvement in herbaceous mulberry harvesting machinery.