Spectroscopy and Spectral Analysis, Volume. 42, Issue 4, 1129(2022)
Nondestructive Identification of Different Chrysanthemum Varieties Based on Near-Infrared Spectroscopy and Pattern Recognition Methods
Figures & Tables(4)
Fig. 1. Original spectra of the complete (a) and powdered samples (b)
Fig. 2. PCA results of the original spectra of complete (a) and powdered sample (b)
Fig. 3. CWT-FLD result of the complete samples (a), FLD result of original spectra of the powdered samples (b)
Table 1. Identification accuracies obtained by SIMCA/FLD and pretreatment methods
View tableView in ArticleTable 1. Identification accuracies obtained by SIMCA/FLD and pretreatment methods
Dataset Pretreatment SIMCA/% FLD/% Chu Gong Hang Bo Whole Chu Gong Hang Bo Whole Complete Original 100 50 60 70 70 60 100 100 90 87.5 De-bias 100 0 70 50 55 70 100 90 80 85 DT 90 10 60 60 55 70 100 90 90 87.5 SNV 90 10 60 70 57.5 80 100 80 90 87.5 Min-Max 80 60 60 100 75 60 100 90 90 85 MSC 90 10 60 40 50 70 100 90 90 87.5 1st 100 80 70 60 77.5 80 100 100 100 95 2nd 100 0 60 40 50 60 100 100 90 87.5 CWT 100 70 70 50 72.5 90 100 100 100 97.5 1st-DT 100 80 70 50 75 70 100 100 100 92.5 1st-SNV 100 90 100 60 87.5 90 100 100 70 90 1st-MSC 100 90 100 90 95 80 90 100 90 90 CWT-MSC 100 90 90 90 92.5 70 90 100 90 87.5 CWT-SNV 90 90 100 90 92.5 80 90 100 80 87.5 Powdered Original 70 100 100 100 92.5 100 100 100 100 100 De-bias 70 80 100 100 87.5 100 100 100 100 100 DT 70 70 100 80 80 100 100 100 100 100 SNV 70 90 20 70 62.5 100 100 100 90 97.5 Min-Max 60 80 80 90 77.5 100 100 100 90 97.5 MSC 70 90 20 70 62.5 100 100 100 90 97.5 1st 60 100 100 100 90 100 100 100 100 100 2nd 70 30 60 50 52.5 80 80 70 50 70 CWT 60 90 90 90 82.5 90 100 100 100 97.5 1st-DT 50 90 90 100 82.5 100 100 100 90 97.5 1st-SNV 70 50 20 70 52.5 70 80 80 80 77.5 1st-MSC 70 60 20 80 57.5 70 80 80 70 75 CWT-MSC 80 60 20 60 55 70 80 80 90 80 CWT-SNV 70 60 10 60 50 60 80 80 80 75
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Jia-yi LI, Mei YU, Mai-quan LI, Yu ZHENG, Pao LI. Nondestructive Identification of Different Chrysanthemum Varieties Based on Near-Infrared Spectroscopy and Pattern Recognition Methods[J]. Spectroscopy and Spectral Analysis, 2022, 42(4): 1129
Paper Information
Category: Research Articles
Received: Mar. 1, 2021
Accepted: --
Published Online: Jul. 25, 2023
The Author Email: LI Jia-yi (lijy_li@yeah.net)
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