Spectroscopy and Spectral Analysis, Volume. 42, Issue 3, 910(2022)
Effects of Orientation and Quality on Spatial Spectrum Characteristics of Fruits in Southern Xinjiang
Figures & Tables(16)
Fig. 3. Eliminating abnormal spectra of winter Jujube by Mahalanobis distance
Fig. 4. Eliminating abnormal sugar content samples of winter Jujube by concentration residual
Fig. 5. CARS method selects the characteristic wavelength of winter Jujube sugar
(a): Relationship between interation number and wavelength variable; (b): RMSECV value for different interations; (c): Variable PLS regression coefficient value
Fig. 6. Background spectra of winter jujube and results of con+1st modeling of sugar content
(a): Model sample regression; (b): Model sample error
Fig. 7. Comparison of inversion results of Roujean model
(a): Winter jujube; (b): Red grapes; (c): Fragrant pear
Fig. 8. Comparison of inversion results of Walthall model
(a): Winter jujube; (b): Red grapes; (c): Fragrant pear
Fig. 9. Error comparison of different fruits retrieved by Roujean model
(a): Winter jujube; (b): Red grapes; (c): Fragrant pear
Fig. 10. Error comparison of different fruits retrieved by Walthall model
(a): Winter jujube; (b): Red grapes; (c): Fragrant pear
Table 1. Results of background spectrum and sugar modeling of winter Jujube under different treatment methods
View tableView in ArticleTable 1. Results of background spectrum and sugar modeling of winter Jujube under different treatment methods
处理方法 r rmsec rmsep Con 0.549 93 2.40 2.72 MSC 0.814 82 1.67 2.43 SNV 0.827 29 1.62 2.34 Con+1st 0.853 31 1.50 2.29 MSC+1st 0.806 89 1.70 2.26 SNV+1st 0.803 86 1.71 2.28 Con+2st 0.723 36 2.00 2.26 MSC+2st 0.751 78 1.92 2.16 SNV+2st 0.746 10 1.91 2.42
Table 2. Modeling results of different winter jujube physicochemical values
View tableView in ArticleTable 2. Modeling results of different winter jujube physicochemical values
理化值 预处理方法 r rmsec rmsep 糖度 Con+1st 0.853 31 1.50 2.29 SNV 0.827 29 1.62 2.34 MSC 0.814 82 1.67 2.43 水分 Con 0.741 28 0.551 0.950 SNV 0.669 93 0.610 1.10 MSC 0.664 99 0.614 1.11 探测角 Con+2st 0.985 58 0.227 0.404 Con 0.975 40 0.296 0.260 Con+1st 0.974 72 0.300 0.323 方位角 Con+2st 0.941 83 2.84 5.72 MSC+1st 0.925 33 3.21 4.33 SNV+1st 0.914 64 3.42 4.35 相位角 MSC+2st 0.960 94 0.810 1.38 SNV+2st 0.960 42 0.804 1.48 Con+2st 0.957 55 0.860 1.45
Table 3. Modeling results of different Red grapes physicochemical values
View tableView in ArticleTable 3. Modeling results of different Red grapes physicochemical values
理化值 预处理方法 r rmsec rmsep 糖度 Con+2st 0.822 67 0.460 0.645 MSC+1st 0.818 21 0.465 1.05 SNV+1st 0.816 46 0.467 1.02 水分 Con+1st 0.784 74 0.577 0.955 Con+2st 0.721 79 0.644 1.09 MSC 0.616 77 0.733 1.11 探测角 Con+1st 0.992 73 0.463 0.633 Con 0.992 41 0.473 0.633 Con+2st 0.990 57 0.527 0.803 方位角 Con 0.910 45 2.50 3.99 MSC+1st 0.894 78 2.70 5.24 SNV+1st 0.890 70 2.75 4.70 相位角 Con 0.957 01 1.20 1.20 Con+1st 0.955 67 1.22 1.32 SNV+1st 0.950 29 1.29 1.77
Table 4. Modeling results of different Fragrant Pear physicochemical values
View tableView in ArticleTable 4. Modeling results of different Fragrant Pear physicochemical values
理化值 预处理方法 r rmsec rmsep 糖度 Con+2st 0.913 34 0.505 1.02 MSC+2st 0.909 23 0.524 0.982 SNV+2st 0.904 02 0.530 0.965 水分 SNV+2st 0.891 33 0.412 0.885 MSC+1st 0.868 04 0.451 1.02 SNV 0.720 12 0.631 1.09 探测角 Con 0.974 69 0.588 0.692 Con+2st 0.966 59 0.674 0.661 SNV 0.964 62 0.694 0.666 方位角 MSC 0.936 88 3.76 5.55 SNV 0.934 54 3.82 5.56 MSC+1st 0.900 14 4.69 6.30 相位角 Con 0.956 27 1.25 1.91 SNV 0.950 56 1.33 1.70 MSC 0.946 25 1.38 1.71
Table 5. Comparison of inversion results of roujean model
View tableView in ArticleTable 5. Comparison of inversion results of roujean model
样品
编号冬枣 红提 香梨 R2 r rmsep 误差/% R2 r rmsep 误差/% R2 r rmsep 误差/% 1 0.968 8 0.992 6 0.028 0 4.41 0.975 0 0.989 4 0.031 6 9.12 0.981 5 0.982 1 0.041 2 2.92 2 0.932 8 0.989 7 0.042 8 8.84 0.952 6 0.984 1 0.038 8 9.27 0.756 2 0.986 5 0.076 0 12.65 3 0.925 0 0.989 6 0.044 4 7.20 0.897 8 0.988 4 0.058 2 14.32 0.876 5 0.957 4 0.046 9 4.70 4 0.853 2 0.979 5 0.065 2 9.89 0.834 0 0.977 0 0.073 7 16.60 0.746 2 0.967 1 0.075 0 11.03 5 0.958 4 0.996 7 0.033 8 7.54 0.918 8 0.966 1 0.062 0 8.36 0.814 8 0.962 1 0.069 4 10.57 6 0.989 8 0.996 6 0.017 1 2.80 0.975 9 0.988 7 0.029 2 7.03 0.892 9 0.964 5 0.046 9 4.65 7 0.971 6 0.991 7 0.027 6 3.92 0.900 0 0.991 2 0.062 9 14.31 0.814 9 0.963 7 0.066 7 9.53 8 0.875 6 0.985 3 0.059 7 13.55 0.971 0 0.985 9 0.033 2 9.13 0.762 1 0.969 6 0.079 6 12.88
Table 6. Comparison of inversion results of Walthall model
View tableView in ArticleTable 6. Comparison of inversion results of Walthall model
样品
编号冬枣 红提 香梨 R2 r rmsep 误差/% R2 r rmsep 误差/% R2 r rmsep 误差/% 1 0.977 6 0.992 5 0.024 0 2.62 0.909 2 0.977 3 0.056 5 13.89 0.767 7 0.975 3 0.079 7 7.62 2 0.912 7 0.995 4 0.047 3 8.92 0.883 1 0.961 5 0.064 2 10.94 0.912 0 0.988 4 0.050 6 3.73 3 0.931 5 0.998 6 0.042 9 8.51 0.685 9 0.963 6 0.105 2 29.63 0.849 4 0.985 0 0.067 4 7.89 4 0.964 6 0.997 5 0.030 9 5.83 0.796 0 0.957 6 0.084 7 17.19 0.790 7 0.970 8 0.081 3 9.99 5 0.873 7 0.971 5 0.058 4 8.51 0.752 7 0.949 7 0.094 8 20.09 0.889 0 0.955 6 0.059 0 6.76 6 0.985 8 0.992 9 0.019 6 3.38 0.964 6 0.988 1 0.035 9 8.47 0.913 0 0.975 1 0.052 1 6.00 7 0.979 0 0.996 0 0.023 8 4.25 0.911 5 0.988 2 0.056 7 14.41 0.820 2 0.988 0 0.074 9 10.67 8 0.921 6 0.990 2 0.045 9 7.52 0.974 6 0.988 3 0.030 4 8.59 0.770 3 0.923 0 0.084 6 10.07
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Jia-yi XU, Xue HUANG, Hua-ping LUO, Jin-xiu LIU, Yu-ting SUO, Chang-xu WANG. Effects of Orientation and Quality on Spatial Spectrum Characteristics of Fruits in Southern Xinjiang[J]. Spectroscopy and Spectral Analysis, 2022, 42(3): 910
Paper Information
Category: Orginal Article
Received: Feb. 2, 2021
Accepted: Mar. 15, 2021
Published Online: Apr. 19, 2022
The Author Email: XU Jia-yi (1056939585@qq.com)
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