Identification of Official Rhubarb Samples by Using PLS and Terahertz Time-Domain Spectroscopy
The development of terahertz technology is attracting broad intention in recent years. The quality identification is important for the quality control of Chinese medicine production. In the present work, terahertz time-domain spectroscopy (THz-TDS) combined with partial least squares (PLS) were used for the identification model building and studied based on 41 official and unofficial rhubarb samples. First, the THz-TDS spectra of rhubarb samples were collected and were preprocessed by using chemometrics methods rather than transformed to absorption spectra. The identification models were then established based on the processed terahertz time domain spectra. The spectral preprocessing methods include Savitzky-Golay (S-G) first derivative, detrending, standard normal transformation (SNV), autoscaling, and mean centering. The identification accuracy of 90% was accomplished by using proper pretreatment methods, which was higher than the classified accuracy of 80% without any preprocessing for the time domain spectra. The component number of the PLS model was evaluated by leave-one-out cross-validation (LOOCV). The minimum values of the root-mean squared error of cross-validation (RMSECV) and root-mean squared error of prediction (RMSEP) were 0.076 6 and 0.169 0 by using mean centering method, respectively. The results of this work showed that the combination of terahertz time domain spectroscopy technology with chemometrics methods, as well as PLS can be applied for the recognition of genuine and counterfeit Chinese herbal medicines, as well as official and unofficial rhubarbs. The advantage of using terahertz time domain spectra directly with no transformation into absorption spectra is: (1) the thickness of samples could not be considered in the model establishment, and (2) the spectral processing was simplified. The proposed method based on the combination of THz-TDS and chemometrics proved to be rapid, simple, non-pollution and solvent free, suitable to be developed as a promising tool for quality control of many other Chinese herbal medicines.
| Medienart: |
Artikel |
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| Erscheinungsjahr: |
2016 |
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| Erschienen: |
2016 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:36 |
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| Enthalten in: |
Guang pu xue yu guang pu fen xi = Guang pu - 36(2016), 2 vom: 20. Feb., Seite 316-21 |
| Sprache: |
Chinesisch |
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| Beteiligte Personen: |
Wang, Jing-rong [VerfasserIn] |
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| Themen: |
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| Anmerkungen: |
Date Completed 10.06.2016 Date Revised 02.12.2018 published: Print Citation Status MEDLINE |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM260611638 |
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| 245 | 1 | 0 | |a Identification of Official Rhubarb Samples by Using PLS and Terahertz Time-Domain Spectroscopy |
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| 520 | |a The development of terahertz technology is attracting broad intention in recent years. The quality identification is important for the quality control of Chinese medicine production. In the present work, terahertz time-domain spectroscopy (THz-TDS) combined with partial least squares (PLS) were used for the identification model building and studied based on 41 official and unofficial rhubarb samples. First, the THz-TDS spectra of rhubarb samples were collected and were preprocessed by using chemometrics methods rather than transformed to absorption spectra. The identification models were then established based on the processed terahertz time domain spectra. The spectral preprocessing methods include Savitzky-Golay (S-G) first derivative, detrending, standard normal transformation (SNV), autoscaling, and mean centering. The identification accuracy of 90% was accomplished by using proper pretreatment methods, which was higher than the classified accuracy of 80% without any preprocessing for the time domain spectra. The component number of the PLS model was evaluated by leave-one-out cross-validation (LOOCV). The minimum values of the root-mean squared error of cross-validation (RMSECV) and root-mean squared error of prediction (RMSEP) were 0.076 6 and 0.169 0 by using mean centering method, respectively. The results of this work showed that the combination of terahertz time domain spectroscopy technology with chemometrics methods, as well as PLS can be applied for the recognition of genuine and counterfeit Chinese herbal medicines, as well as official and unofficial rhubarbs. The advantage of using terahertz time domain spectra directly with no transformation into absorption spectra is: (1) the thickness of samples could not be considered in the model establishment, and (2) the spectral processing was simplified. The proposed method based on the combination of THz-TDS and chemometrics proved to be rapid, simple, non-pollution and solvent free, suitable to be developed as a promising tool for quality control of many other Chinese herbal medicines | ||
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