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Research on UAV Remote Sensing Method of Mold Detection Suitable for Pericarp of Citri Reticulatae ‘Chachi’ Warehouses

Author

Listed:
  • Guoqi Yan

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Maoming Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Maoming 525000, China)

  • Jialei Qu

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Wei Li

    (School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi 214122, China)

  • Dongyi Chen

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Chumin Zhong

    (Jiangmen Palace International Food Inc., Jiangmen 529100, China)

  • Hao Luo

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China)

  • Guoliang Ou

    (Jiangmen Palace International Food Inc., Jiangmen 529100, China)

  • Jiasi Mo

    (College of Engineering, South China Agricultural University, Guangzhou 510642, China
    Maoming Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Maoming 525000, China)

Abstract

Once the Pericarp of Citri Reticulata ‘Chachi’ (PCRC) develops mildew while in storage, the rapid spread of the flora after the occurrence of mold can cause huge losses. As such, inspecting whether the PCRC is moldy is important. In this paper, we propose an alternative inspection method, namely that of utilizing a small UAV with a camera to inspect the PCRC mildew in the top stacks under consideration. Specifically, we first address the light problem in the collected images with different lights via a multi-spectral method, and find that 625–740 nm of lighting has a significant effect on mildew. Second, we utilize the ultrared 1.4R-G method to extract the features of mildew with Otus binarization. We can see that the mold-free area is less than 95% in an image categorized as having mildew. The proposed mildew inspection method achieved 93.3% accuracy. Our method could send the inspection information to a control system, achieving rapid closed-loop automatic control and reducing the mildew-related loss.

Suggested Citation

  • Guoqi Yan & Jialei Qu & Wei Li & Dongyi Chen & Chumin Zhong & Hao Luo & Guoliang Ou & Jiasi Mo, 2023. "Research on UAV Remote Sensing Method of Mold Detection Suitable for Pericarp of Citri Reticulatae ‘Chachi’ Warehouses," Agriculture, MDPI, vol. 13(3), pages 1-15, February.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:3:p:528-:d:1077317
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    Citations

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    Cited by:

    1. Zongru Liu & Jiyu Li, 2023. "Application of Unmanned Aerial Vehicles in Precision Agriculture," Agriculture, MDPI, vol. 13(7), pages 1-4, July.

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