IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i4p843-d1119297.html
   My bibliography  Save this article

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

Author

Listed:
  • Meixiang Chen

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Liping Chen

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Tongchuan Yi

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Ruirui Zhang

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Lang Xia

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Cheng Qu

    (Institute of Plant Protection, Beijing Academy of Agriculture and Forestry Sciences, Beijing 100097, China)

  • Gang Xu

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Weijia Wang

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Chenchen Ding

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Qing Tang

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, Beijing 100097, China)

  • Mingqi Wu

    (National Research Center of Intelligent Equipment for Agriculture, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    Research Center for Intelligent Equipment, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
    National Center for International Research on Agricultural Aerial Application Technology, 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.

Suggested Citation

  • Meixiang Chen & Liping Chen & Tongchuan Yi & Ruirui Zhang & Lang Xia & Cheng Qu & Gang Xu & Weijia Wang & Chenchen Ding & Qing Tang & Mingqi Wu, 2023. "Development of a Low-Power Automatic Monitoring System for Spodoptera frugiperda (J. E. Smith)," Agriculture, MDPI, vol. 13(4), pages 1-19, April.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:4:p:843-:d:1119297
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/4/843/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/4/843/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jozsef Suto, 2022. "Codling Moth Monitoring with Camera-Equipped Automated Traps: A Review," Agriculture, MDPI, vol. 12(10), pages 1-18, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jozsef Suto, 2023. "Hardware and Software Support for Insect Pest Management," Agriculture, MDPI, vol. 13(9), pages 1-2, September.
    2. Dana Čirjak & Ivan Aleksi & Darija Lemic & Ivana Pajač Živković, 2023. "EfficientDet-4 Deep Neural Network-Based Remote Monitoring of Codling Moth Population for Early Damage Detection in Apple Orchard," Agriculture, MDPI, vol. 13(5), pages 1-20, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:4:p:843-:d:1119297. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.