Intelligent pesticide application system for intercropping: development, challenges, and solutions based on monoculture machinery
Year: 2025
Type: article
Abstract: Intercropping is an efficient cultivation model that maximizes the utilization of land resources, and the intelligentization of plant protection machinery is a crucial aspect in promoting its widespread adoption. This paper analyzes the development direction of intelligent pesticide application system for intercropping based on advancements in monoculture systems. Based on the characteristics of intercropping systems, this study proposes solutions such as multi-sensor data fusion, lightweight recognition algorithms, and field management robot to reduce data fusion time and minimize algorithmic redundancy. Two major development directions are highlighted: (1) The design of field management robots that integrate multi-source data fusion and high performance algorithms to recognize complex field information and achieve precision operations requiring the establishment of large datasets, efficient lightweight algorithms, and integrated models for perception, decision making, and execution; and (2) The genetic enhancement of crops by introducing herbicide resistance genes to simplify pesticide application and reduce the complexity of intelligent machinery in intercropping systems. In summary, the intelligentization of pesticide application machinery for intercropping should be achieved through the integration of agronomic practices and agricultural machinery, addressing intercropping specific challenges based on the technological foundation established for monoculture intelligent spraying systems.
Source: Cogent Food & Agriculture
Authors: Wei Zhong, Wanting Yang, Yunfei Wang, Xiang Dong, Xiaowen Wang, Weidong Jia, Mingxiong Ou
Institutions: Jiangsu University, Taizhou University, Taizhou University
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: diamond
Awards: G3923509137, G5193329631
OpenAlex ID: W4417026376
