Structural optimization and performance evaluation of a sugarcane leaf mulching machine
Existing sugarcane leaf mulching machines struggle to process high-fiber, tough sugarcane leaves, leading to incomplete mulching and uneven residue distribution. These limitations hinder subsequent farming operations and increase energy consumption. To address these challenges, this study presents a structural optimization and performance analysis of the 1GYF-150 sugarcane leaf mulching machine, introducing an enhanced, high-efficiency mulching mechanism. The operational principles of the machine were analyzed, and the effects of different blade types, including straight and hammer-shaped blades, on mulching performance were evaluated. Key parameters—such as blade structure, rotational speed, and arrangement—were optimized to improve mulching quality and pick-up efficiency. Further, a balance analysis of the cutter roller was conducted, incorporating MATLAB optimization algorithms and a fuzzy reliability function to enhance the roller’s structural integrity and reduce weight. Field tests under typical post-harvest conditions (leaf moisture content of 31.8%, representing the average humidity of sugarcane leaves in tropical regions) demonstrated that the optimized machine achieved a pick-up rate of 98.4% and a mulching rate of 94.4% (≤20 cm), reflecting improvements of 0.8% and 7.1% over the previous design, respectively. This study provides a valuable reference for advancing sugarcane leaf mulching machine performance and offers insights into more effective utilization of sugarcane leaf resources.
Authors
- Lijiao Wei (ORCID: https://orcid.org/0009-0001-5208-0204)
- Wei‐Hua Huang (ORCID: https://orcid.org/0000-0001-8951-075X)
- Ming Fu Li (ORCID: https://orcid.org/0000-0003-2963-9441)
- Shuo Wang (ORCID: https://orcid.org/0000-0003-0225-0612)
- Zhenhui Zheng (ORCID: https://orcid.org/0000-0002-0682-775X)
- Dongjie Du
- Chang Ge
- Zhaojun Niu
Institutions
- Chinese Academy of Tropical Agricultural Sciences (CN)
- Ministry of Agriculture (EE)
- Precision for Medicine (United States) (US)
- Ministry of Agriculture (CA)
- Ministry of Agriculture and Rural Affairs (CN)
Publication Details
- Journal
- Smart Agricultural Technology
- Published
- 2025-06-17
- DOI
- https://doi.org/10.1016/j.atech.2025.101116
- Citations
- 1
- Primary Topic
- Agricultural Engineering and Mechanization
- Type
- article
- Field-Weighted Citation Impact
- 0.71