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Design and Performance Evaluation of a Self-Propelled Mugwort Harvester for Hilly and Mountainous Regions

Author

Listed:
  • Yi Li

    (School of Mechanical Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Yongsheng He

    (School of Mechanical Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Kai Zhang

    (School of Mechanical Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Siqi Wang

    (School of Mechanical Engineering, Hubei University of Technology, Wuhan 430070, China
    School of Mechanical Engineering, Hubei Engineering University, Xiaogan 432000, China)

  • Xinyu Hu

    (School of Mechanical Engineering, Hubei University of Technology, Wuhan 430070, China)

  • Junnan Chen

    (School of Mechanical Engineering, Hubei University of Technology, Wuhan 430070, China)

Abstract

There are extensive areas of mugwort cultivation in China, making efficient harvesting crucial for the industry’s economic performance. However, the lack of specialized harvesting machinery for hilly and mountainous regions leads to reliance on manual operations, characterized by high labor intensity and low efficiency. To address these issues, a self-propelled mugwort harvester is designed based on mugwort planting patterns and the physical characteristics of mugwort during the harvesting period. Key structural components, such as drum dimensions, tooth shapes, and tine arrangements, are developed, and a defoliation force model is established to identify factors influencing the net rate of mugwort leaf harvesting, impurity rate, and mugwort leaf usability. The harvester employs a fully hydraulic drive system, for which the hydraulic system is designed and components are selected. A quadratic regression orthogonal rotary test determines the optimal parameters: a forward speed of 0.8 m/s, drum speed of 200 r/min, and cutting table height of 50 mm. Field tests show that the harvester achieves a net rate of mugwort leaf harvesting of 93.78%, an impurity rate of 13.96%, a mugwort leaf usability of 86.23%, and an operational efficiency of 0.155 hm 2 /h, while maintaining stable operation under field conditions. Beyond these performance metrics, the harvester reduces dependency on manual labor, lowers operational costs, and increases profitability for farmers. By improving the sustainability and mechanization of mugwort harvesting, this study provides an efficient solution for mugwort cultivation in hilly and mountainous regions and contributes to the sustainable development of the industry.

Suggested Citation

  • Yi Li & Yongsheng He & Kai Zhang & Siqi Wang & Xinyu Hu & Junnan Chen, 2025. "Design and Performance Evaluation of a Self-Propelled Mugwort Harvester for Hilly and Mountainous Regions," Agriculture, MDPI, vol. 15(1), pages 1-32, January.
  • Handle: RePEc:gam:jagris:v:15:y:2025:i:1:p:111-:d:1560899
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    References listed on IDEAS

    as
    1. Jiaxuan Yang & Xinyan Qin & Jin Lei & Lijian Lu & Jianglong Zhang & Zhi Wang, 2024. "Design and Experiment of a Crawler-Type Harvester for Red Cluster Peppers in Hilly and Mountainous Regions," Agriculture, MDPI, vol. 14(10), pages 1-22, October.
    2. En Lu & Jialin Xue & Tiaotiao Chen & Song Jiang, 2023. "Robust Trajectory Tracking Control of an Autonomous Tractor-Trailer Considering Model Parameter Uncertainties and Disturbances," Agriculture, MDPI, vol. 13(4), pages 1-17, April.
    3. Lihe Wang & Fei Liu & Qiang Wang & Jiaqi Zhou & Xiaoyu Fan & Junru Li & Xuan Zhao & Shengshi Xie, 2023. "Design of a Spring-Finger Potato Picker and an Experimental Study of Its Picking Performance," Agriculture, MDPI, vol. 13(5), pages 1-19, April.
    4. Jie Ling & Haiyang Shen & Man Gu & Zhichao Hu & Sheng Zhao & Feng Wu & Hongbo Xu & Fengwei Gu & Peng Zhang, 2024. "The Design and Optimization of a Peanut-Picking System for a Fresh-Peanut-Picking Crawler Combine Harvester," Agriculture, MDPI, vol. 14(8), pages 1-20, August.
    5. Zhenlong Wang & Fanting Kong & Qing Xie & Yuanyuan Zhang & Yongfei Sun & Teng Wu & Changlin Chen, 2024. "Design and Testing of a Crawler Chassis for Brush-Roller Cotton Harvesters," Agriculture, MDPI, vol. 14(10), pages 1-21, October.
    6. Siqi Wang & Daode Zhang & Xinyu Hu & Rui Lu, 2024. "Finite Element Simulations and Experimental Analysis for Efficient Mugwort Harvesting," Agriculture, MDPI, vol. 14(11), pages 1-13, October.
    7. Dianlei Han & He Zhang & Guoyu Li & Gaoliang Wang & Xinzhong Wang & Yongcheng Chen & Xuegeng Chen & Xiangyu Wen & Qizhi Yang & Rongqiang Zhao, 2024. "Development of a Bionic Picking Device for High Harvest and Low Loss Rate Pod Pepper Harvesting and Related Working Parameter Optimization Details," Agriculture, MDPI, vol. 14(6), pages 1-18, May.
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