식물병연구 (Research in Plant Disease)

한국식물병리학회 (The Korean Society of Plant Pathology)
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Artificial Intelligence Plant Doctor: Plant Disease Diagnosis Using GPT4-vision

  • Yoeguang Hue (Department of Plant Medicine, Sunchon National University) ;
  • Jea Hyeoung Kim (Department of Plant Medicine, Sunchon National University) ;
  • Gang Lee (Department of Computer Engineering, Sunchon National University) ;
  • Byungheon Choi (Department of Multimedia Engineering, Sunchon National University) ;
  • Hyun Sim (Department of Industry Academic Collaboration Foundation, Sunchon National University) ;
  • Jongbum Jeon (Korea Bioinformation Center (KOBIC), Korea Research Institute of Bioscience and Biotechnology (KRIBB)) ;
  • Mun-Il Ahn (EPINET Co., Ltd.) ;
  • Yong Kyu Han (EPINET Co., Ltd.) ;
  • Ki-Tae Kim (Department of Plant Medicine, Sunchon National University)
  • 투고 : 2024.02.05
  • 심사 : 2024.03.06
  • 발행 : 2024.03.31
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초록

Integrated pest management is essential for controlling plant diseases that reduce crop yields. Rapid diagnosis is crucial for effective management in the event of an outbreak to identify the cause and minimize damage. Diagnosis methods range from indirect visual observation, which can be subjective and inaccurate, to machine learning and deep learning predictions that may suffer from biased data. Direct molecular-based methods, while accurate, are complex and time-consuming. However, the development of large multimodal models, like GPT-4, combines image recognition with natural language processing for more accurate diagnostic information. This study introduces GPT-4-based system for diagnosing plant diseases utilizing a detailed knowledge base with 1,420 host plants, 2,462 pathogens, and 37,467 pesticide instances from the official plant disease and pesticide registries of Korea. The AI plant doctor offers interactive advice on diagnosis, control methods, and pesticide use for diseases in Korea and is accessible at https://pdoc.scnu.ac.kr/.

키워드

과제정보

This research was supported by the MSIT (Ministry of Science and ICT), Korea, under the National Program for Excellence in SW) supervised by the IITP (Institute of Information & Communications Technology Planning & Evaluation) in 2024 (2023-0-00028).

참고문헌

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