Key Technologies of Intelligent Weeding for Vegetables: A Review

Author:

Jiao Jinkang1234,Zang Ying1345,Chen Chaowen134

Affiliation:

1. College of Engineering, South China Agricultural University, Guangzhou 510642, China

2. School of Intelligent Engineering, Shaoguan University, Shaoguan 512005, China

3. Key Laboratory of Key Technology on Agricultural Machine and Equipment (South China Agricultural University), Ministry of Education, Guangzhou 510642, China

4. State Key Laboratory of Agricultural Equipment Technology, Guangzhou 510642, China

5. Guangdong Provincial Key Laboratory of Agricultural Artificial Intelligence (GDKL-AAI), Guangzhou 510642, China

Abstract

Vegetables are an essential part of people’s daily diet, and weeds can cause serious losses in vegetable yield and quality. Intelligent weeding technology for vegetables will be one of the mainstream technologies in modern agricultural development. This article reviews the current research status of intelligent weeding technology for vegetables, including vegetable and weed detection technology, weeding actuators, and weeding robots. Firstly, the vegetable and weed detection technology was introduced in detail from three aspects: global weed detection, crop-rows detection, and vegetable/weed precise recognition technology. The research results of some researchers were summarised, and the vegetable/weed precise recognition technology, including machine learning and proximal sensor technology, was introduced. Secondly, the weeding actuators and robots were introduced, including intelligent chemical weeding, mechanical weeding, physical weeding, and integrated weed management methods. Some weeding actuators and robots developed by researchers and agricultural companies were showcased. Finally, the challenges and future development directions of intelligent weeding technology were discussed and analysed. Intelligent weeding technology for vegetables is still mainly limited by natural conditions and a lack of technology. In the future, it will be possible to develop in the direction of multi-algorithm and multi-sensor fusion technologies. It is necessary to improve the applicability of intelligent weeding equipment for various environments, crops, and weeds. This article can provide a reference for future research in the field of intelligent weeding for vegetables.

Funder

The Earmarked Fund for CARS

Key Realm R&D Program of Guangdong Province

Publisher

MDPI AG

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