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- W4320527924 abstract "Drought stress is an important environmental factor that restricts the quality and high yield of the soybean. Rapid and nondestructive monitoring of canopy traits under drought stress is very critical to the cultivation and quality improvement of for the soybean plants. To solve the problems of traditional artificial chemical tests in determining soybean wilt index, such as cumbersome, time-consuming, and laborious, a method for calculating wilting index was proposed based on the fractal dimension of multispectral images for the soybean canopy. First, the soybean variety of Suinong 26 was chosen as the experimental subject, the multispectral images of five channels (RGB, GRE, NIR, RED and REG) of the soybean canopy were acquired. Second, the soybean canopy image was extracted by K-means clustering algorithm from the original multispectral image, with an effective segmentation rate (ESR) of 0.9729. Third, on the base of the multispectral image enhanced by the gamma transform for the soybean canopy, a method for calculating wilting index (LBC,LDBC, LDB) was constructed for the soybean canopy by using fractal dimension algorithms including box-counting (BC) dimension, differential box-counting (DBC) dimension and double blanket (DB) dimension. Finally, the proposed method was proved by using the average leaf inclination (LI) and the projected leaf area (PLA). The experimental results showed that the determination coefficients R2 were all above 0.85. The LBC got the highest correlation with LI and PLA in the RGB channel with coefficient determination R2 above 0.8729. The LDB got the highest correlation with LI and PLA in the GRE, NIR, and REG channels with determination coefficient R2 above 0.8824. The LDBC got the highest correlation with LI and PLA in the RED channel with determination coefficient R2 above 0.8857. This achievement presented that the proposed wilting index could characterize the change degree for the ecology and morphology when soybeans were affected by drought stress, which can provide the technical support to scientifically monitor the phenotypic traits in the process of variety breeding, field cultivation for the soybean plant." @default.
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- W4320527924 date "2023-03-01" @default.
- W4320527924 modified "2023-10-17" @default.
- W4320527924 title "Calculation method of wilting index based on fractal dimension of multispectral images for the soybean canopy" @default.
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- W4320527924 doi "https://doi.org/10.1016/j.compag.2023.107656" @default.
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