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

Wei Liu, Jinhao Zhou, Tengfei Zhang, Pengcheng Zhang, Mengjiao Yao, Jinhong Li, Zitong Sun, Guoxin Ma, Xinxin Chen and Jianping Hu ()
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Wei Liu: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Jinhao Zhou: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Tengfei Zhang: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Pengcheng Zhang: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Mengjiao Yao: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Jinhong Li: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Zitong Sun: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Guoxin Ma: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Xinxin Chen: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China
Jianping Hu: School of Agricultural Engineering, Jiangsu University, Zhenjiang 212013, China

Agriculture, 2024, vol. 15, issue 1, 1-38

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.

Keywords: seeding machinery; intelligent seeding; cereal; precision agriculture; seeding rate control; seeding depth control; soil property measurement (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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