#6206. Grading method of soybean mosaic disease based on hyperspectral imaging technology

September 2026publication date
Proposal available till 14-05-2025
4 total number of authors per manuscript0 $

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Journal’s subject area:
Animal Science and Zoology;
Agronomy and Crop Science;
Forestry;
Aquatic Science;
Computer Science Applications;
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Abstract:
Soybean is a crop with a long cultivation history that occupies an important position in agricultural production. Soybean mosaic virus disease (SMV) has caused a rapid decline in soybean yields, causing huge losses to the soybean industry, wherefrom its early detection is particularly important. This study proposes a new classification method for the early SMV, dividing its severity into grades 0, 1 and 2. In the case of a small number of experimental samples of soybeans, this study proposes a combined convolutional neural network and support vector machine (CNN-SVM) method for the early detection of SMV.
Keywords:
CNN-SVM; Grading method; Hyperspectral imaging technology; Soybean mosaic virus disease

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