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Special Issue:
智慧植保合辑Smart Plant Protection
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| Development of an automatic monitoring system for rice light-trap pests based on machine vision |
YAO Qing1, FENG Jin1, TANG Jian2, XU Wei-gen3, ZHU Xu-hua4, YANG Bao-jun2, LÜ Jun1, XIE Yi-ze5, YAO Bo1, WU Shu-zhen1, KUAI Nai-yang1, WANG Li-jun6 |
1 School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, P.R.China
2 State Key Laboratory of Rice Biology, China National Rice Research Institute, Hangzhou 310006, P.R.China
3 Plant Protection, Quarantine and Pesticide Management Station of Zhejiang, Hangzhou 310020, P.R.China
4 Zhejiang Top Cloud-agri Technology Co., Ltd., Hangzhou 310015, P.R.China
5 Agricultural Technology Extension Center of Shangyu, Shaoxing 312300, P.R.China
6 Agricultural Technology Extension Center of Keerqin, Keerqin 137713, P.R.China |
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Abstract Monitoring pest populations in paddy fields is important to effectively implement integrated pest management. Light traps are widely used to monitor field pests all over the world. Most conventional light traps still involve manual identification of target pests from lots of trapped insects, which is time-consuming, labor-intensive and error-prone, especially in pest peak periods. In this paper, we developed an automatic monitoring system for rice light-trap pests based on machine vision. This system is composed of an intelligent light trap, a computer or mobile phone client platform and a cloud server. The light trap firstly traps, kills and disperses insects, then collects images of trapped insects and sends each image to the cloud server. Five target pests in images are automatically identified and counted by pest identification models loaded in the server. To avoid light-trap insects piling up, a vibration plate and a moving rotation conveyor belt are adopted to disperse these trapped insects. There was a close correlation (r=0.92) between our automatic and manual identification methods based on the daily pest number of one-year images from one light trap. Field experiments demonstrated the effectiveness and accuracy of our automatic light trap monitoring system.
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Received: 11 November 2019
Accepted:
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| Fund: This work was supported by the Fundamental Public Welfare Research Program of Zhejiang Provincial Natural Science Foundation, China (LGN18C140007 and Y20C140024), the National High Technology Research and Development Program of China (863 Program; 2013AA102402) and the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences. |
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Corresponding Authors:
Correspondence YAO Qing, E-mail: q-yao@zstu.edu.cn; TANG Jian, E-mail: tangjian@caas.cn
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Cite this article:
YAO Qing, FENG Jin, TANG Jian, XU Wei-gen, ZHU Xu-hua, YANG Bao-jun, Lü Jun, XIE Yi-ze, YAO Bo, WU Shu-zhen, KUAI Nai-yang, WANG Li-jun.
2020.
Development of an automatic monitoring system for rice light-trap pests based on machine vision. Journal of Integrative Agriculture, 19(10): 2500-2513.
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