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Key Technologies in Intelligent Seeding Machinery for Cereals: Recent Advances and Future Perspectives

Author

Listed:
  • Wei Liu

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Jinhao Zhou

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Tengfei Zhang

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Pengcheng Zhang

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Mengjiao Yao

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Jinhong Li

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Zitong Sun

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Guoxin Ma

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Xinxin Chen

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

  • Jianping Hu

    (School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
    Jiangsu Provincial Key Laboratory of Hi-Tech Research for Intelligent Agricultural Equipment, Jiangsu University, Zhenjiang 212013, China)

Abstract

The operational performance of cereal seeding machinery influences the yield and quality of cereals. In this article, we review the existing literature on intelligent technologies for cereal seeding machinery, encompassing active controllable seeding actuators, intelligent seeding rate control, and intelligent seed position control systems. In this manuscript, (1) the characteristics and innovative structures of existing motor-driven seed-metering devices and ground surface profiling mechanisms are expounded; (2) state-of-the-art detection principles and applications for soil property sensors are described based on different soil properties; (3) optimal seeding rate decision approaches based on soil properties are summarized; (4) the research state of seeding rate measuring and control technologies is expounded in detail; (5) trajectory control methods for seeding machinery and seeding depth control systems are described based on measurement and control principles; and (6) the present state, limitations, and future development directions of intelligent cereal seeding machinery are described. In the future, more advanced multi-algorithm and multi-sensor fusion technologies for soil property detection, optimal seeding rate decisions, seeding rates, and seed position control are likely to evolve. This review not only expounds the latest studies on intelligent actuating, sensing, and control technologies for intelligent cereal seeding machinery, but also discusses the shortcomings of existing intelligent seeding technologies and future developing trends in detail. This review, therefore, offers a reference for future research in the domain of intelligent seeding machinery for cereals.

Suggested Citation

  • Wei Liu & Jinhao Zhou & Tengfei Zhang & Pengcheng Zhang & Mengjiao Yao & Jinhong Li & Zitong Sun & Guoxin Ma & Xinxin Chen & Jianping Hu, 2024. "Key Technologies in Intelligent Seeding Machinery for Cereals: Recent Advances and Future Perspectives," Agriculture, MDPI, vol. 15(1), pages 1-38, December.
    • Handle: RePEc:gam:jagris:v:15:y:2024:i:1:p:8-:d:1551618
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    References listed on IDEAS

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    1. Yecheng Wang & Xueqi Kang & Guoqing Wang & Wenyi Ji, 2023. "Numerical Analysis of Friction-Filling Performance of Friction-Type Vertical Disc Precision Seed-Metering Device Based on EDEM," Agriculture, MDPI, vol. 13(12), pages 1-17, November.
    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. Yanqing Zhang & Yaocheng Tang & Ding He & Jie Shi & Lirong Hao & Jiabao Li & Deng Sun & Hongbo Li & Zhiyong Zhang & Shaobo Ye & Yongqiang He & Qingliang Cui, 2024. "Design and Test of Electromagnetic Vibration Type Fine and Small-Amount Seeder for Millet," Agriculture, MDPI, vol. 14(9), pages 1-22, September.
    4. Baocheng Zhou & Xin Su & Hongjun Yu & Wentian Guo & Qing Zhang, 2023. "Research on Path Tracking of Articulated Steering Tractor Based on Modified Model Predictive Control," Agriculture, MDPI, vol. 13(4), pages 1-21, April.
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