Original Articles

Effects of operating factors on branch chipping performance and parameter optimization based on an orthogonal experimental design

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Published: 16 April 2026
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A typical blade-type branch chipper was used to study the effects of rotor speed, feed mass and branch diameter class on chipping performance. Chipping efficiency and the qualified particlesize rate (percentage of output particles ≤30 mm) were adopted as evaluation indices. Singlefactor tests and an L9(3^3) orthogonal experiment were carried out to analyze the influence of each factor on these performance indices. The results showed that branch diameter class had the most significant impact on performance: small-diameter branches significantly improved both chipping efficiency and the qualified particle-size rate. Rotor speed and feed mass exhibited positive effects within appropriate ranges, each with an optimal interval. The orthogonal test confirmed a significant synergistic effect among the three factors, and the optimal parameter combination was determined to be a rotor speed of 2500 r/min, a feed mass of 6.5 kg per batch, and small branch material. These results provide a theoretical reference for improving the performance of branch chippers.

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CRediT authorship contribution

Chen Feng, study concept, experiments design. Peilin Wu, experiments performing, data collection. Taotao Nie, data analysis, figures preparation. Xiaodong Xu supervision, writing – review & editing. All authors read and approved the final manuscript.

Supporting Agencies

China Machinery Industry Education Association, Jiangsu Provincial Basic Science Natural Science Research Program for Universities, Jiangsu Provincial Higher Education Teaching Reform Research Program

Data Availability Statement

The datasets generated or analysed during the current study are available from the corresponding author on reasonable request.

How to Cite



“Effects of operating factors on branch chipping performance and parameter optimization based on an orthogonal experimental design” (2026) Journal of Agricultural Engineering [Preprint]. doi:10.4081/jae.2026.2163.