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| Application of image analysis technology in crop pollution damage identification |
| Received:October 27, 2023 |
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| KeyWord:crop damage;support vector machine;neural network;deep learning;judicial appraisal |
| Author Name | Affiliation | E-mail | | QIANG Liwen | Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China | | | JIA Guanghui | Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China
College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China | | | WANG Wei | Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China | | | ZHOU Li | Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China | lily_621@163.com |
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| Abstract: |
| The rapid identification of crop damage is essential in preventing crop damage, improving crop yield, responding to instructions in agricultural production accidents, identifying potential crop pollution damage behavior, and reducing the threat of pollution to crop growth and the quality and safety of agricultural products. With the development of image processing technology, analysis methods based on image processing technology have achieved rapid and accurate non-destructive detection and identification of crop damage. This article provides a brief overview of the research and application of this method under crop diseases, pests, grass pests, pollution stress, meteorological disasters, and nutrient deficiency. Developing a recognition system for crop pollution stress based on image analysis has promising applications in the judicial identification of agricultural environmental damage and requires further exploration and research. |
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