Yan-de LIU, Mao-peng LI, Jun HU, Zhen XU, Hui-zhen CUI. Detection of Citrus Granulation Based on Near-Infrared Hyperspectral Data[J]. Spectroscopy and Spectral Analysis, 2022, 42(5): 1366
- Spectroscopy and Spectral Analysis
- Vol. 42, Issue 5, 1366 (2022)
Fig. 1. Three different granulation degrees of navel orange in southern Jiangxi
(a): None; (b): Mild; (c): Moderate
(a): None; (b): Mild; (c): Moderate
Fig. 2. Hyperspectral equipment imaging device
(a): Schematic diagram; (b): Picture
(a): Schematic diagram; (b): Picture
Fig. 3. Modeling flow chart of detection for navel oranges with different granulation degrees
Fig. 4. Original mean reflectance spectra of navel oranges with three granulation degrees
Fig. 5. Cumulative contribution rates of the first 20 principal components of citrus hyperspectral data
Fig. 6. SPA wavelength variable selection results
Fig. 7. UVE variable screening stability result graph
Fig. 8. Prediction results of UVE-LS-SVM model based on RBF-Kernel
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Table 1. Classification of training sets and prediction sets and sample codes of different coffee beans
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Table 2. Comparison of PLS-DA models based on different dimension reduction methods
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Table 3. Comparison of model performance between different dimension reduction methods and LS-SVM method
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