Development of a Low-Power Automatic Monitoring System for Spodoptera frugiperda (J. E. Smith)

Author:

Chen Meixiang123,Chen Liping123,Yi Tongchuan123,Zhang Ruirui123ORCID,Xia Lang123,Qu Cheng4,Xu Gang123,Wang Weijia123,Ding Chenchen123,Tang Qing123,Wu Mingqi123

Affiliation:

1. National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China

2. Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China

3. National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China

4. Institute of Plant Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China

Abstract

Traditional traps for Spodoptera frugiperda (J. E. Smith) monitoring require manual counting, which is time-consuming and laborious. Automatic monitoring devices based on machine vision for pests captured by sex pheromone lures have the problems of large size, high power consumption, and high cost. In this study, we developed a micro- and low-power pest monitoring device based on machine vision, in which the pest image was acquired timely and processed using the MATLAB algorithm. The minimum and maximum power consumption of an image was 6.68 mWh and 78.93 mWh, respectively. The minimum and maximum days of monitoring device captured image at different resolutions were 7 and 1486, respectively. The optimal image resolutions and capture periods could be determined according to field application requirements, and a micro-solar panel for battery charging was added to further extend the field life of the device. The results of the automatic counting showed that the counting accuracy of S. frugiperda was 94.10%. The automatic monitoring device had the advantages of low-power consumption and high recognition accuracy, and real-time information on S. frugiperda could be obtained. It is suitable for large-scale and long-term pest monitoring and provides an important reference for pest control.

Funder

the National Natural Science Foundation of China

the Promotion and Innovation of Beijing Academy of Agriculture and Forestry Sciences

Publisher

MDPI AG

Subject

Plant Science,Agronomy and Crop Science,Food Science

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1. Detecção da Praga Spodoptera frugiperda no Cultivo de Milho usando Armadilhas Inteligentes e Visão Computacional;Anais do XV Workshop de Computação Aplicada à Gestão do Meio Ambiente e Recursos Naturais (WCAMA 2024);2024-07-21

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