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Vision-Based a Seedling Selective Planting Control System for Vegetable Transplanter

Author

Listed:
  • Mingyong Li

    (College of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China
    Science & Technology Innovation Center for Completed Set Equipment, Longmen Laboratory, Luoyang 471000, China)

  • Liqiang Xiao

    (Science & Technology Innovation Center for Completed Set Equipment, Longmen Laboratory, Luoyang 471000, China)

  • Xiqiang Ma

    (Science & Technology Innovation Center for Completed Set Equipment, Longmen Laboratory, Luoyang 471000, China)

  • Fang Yang

    (Science & Technology Innovation Center for Completed Set Equipment, Longmen Laboratory, Luoyang 471000, China)

  • Xin Jin

    (Science & Technology Innovation Center for Completed Set Equipment, Longmen Laboratory, Luoyang 471000, China
    Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province, Luoyang 471003, China)

  • Jiangtao Ji

    (Science & Technology Innovation Center for Completed Set Equipment, Longmen Laboratory, Luoyang 471000, China
    Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing of Henan Province, Luoyang 471003, China)

Abstract

Seedling transplanting is an important part of vegetable mechanized production in modern agriculture. After the seedlings are cultivated on a large scale by the nursery tray, they are planted into the field by the transplanter. However, unlike manual transplanting, transplanter is unable to judge the status of seedlings in the hole during seedling planting, which leads to problems such as damaged seedlings and empty holes being picked in the same order and planted into the field, resulting in yield reduction and missed planting. Aiming at this problem, we designed a seedling selective planting control system for vegetable transplanter which includes vision unit, seedling picking mechanism, seedling feeding mechanism, planting mechanism, pneumatic push rod unit, limit sensor, industrial computer and logic controller. We used asymmetrical light to construct visual identification scenes for planting conditions, which suppresses environmental disturbances. Based on the intersection operation of mask and image, a fast framework of tray hole location and seedling identification (FHLSI) was proposed combined with FCM segmentation algorithm. The vision unit provides the transplanting system with information on the status of the holes to be transplanted. Based on the information, planting system chooses the healthy seedlings for transplanting, improving the survival rate and quality of transplanting. The results show that the proposed visual method has an average accuracy of 92.35% for identification with the selective planting control system of seedlings and improves the transplanting quality by 15.4%.

Suggested Citation

  • Mingyong Li & Liqiang Xiao & Xiqiang Ma & Fang Yang & Xin Jin & Jiangtao Ji, 2022. "Vision-Based a Seedling Selective Planting Control System for Vegetable Transplanter," Agriculture, MDPI, vol. 12(12), pages 1-14, December.
  • Handle: RePEc:gam:jagris:v:12:y:2022:i:12:p:2064-:d:990328
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    Cited by:

    1. Kaikang Chen & Bo Zhao & Haiyan Zhou & Liming Zhou & Kang Niu & Xin Jin & Ruoshi Li & Yanwei Yuan & Yongjun Zheng, 2023. "Digital Twins in Plant Factory: A Five-Dimensional Modeling Method for Plant Factory Transplanter Digital Twins," Agriculture, MDPI, vol. 13(7), pages 1-18, June.

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