Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy
Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopam...
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| Autor*in: |
Zhao, J. H. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Anmerkung: |
© Springer Science+Business Media New York 2017 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of applied spectroscopy - Springer US, 1966, 84(2017), 1 vom: März, Seite 76-81 |
|---|---|
| Übergeordnetes Werk: |
volume:84 ; year:2017 ; number:1 ; month:03 ; pages:76-81 |
| Links: |
|---|
| DOI / URN: |
10.1007/s10812-017-0430-6 |
|---|
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OLC2034687221 |
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| 520 | |a Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. | ||
| 650 | 4 | |a ractopamine | |
| 650 | 4 | |a clenbuterol hydrochloride | |
| 650 | 4 | |a surface enhanced Raman spectroscopy | |
| 650 | 4 | |a pork | |
| 650 | 4 | |a rapid detection and identification | |
| 700 | 1 | |a Yuan, H. C. |4 aut | |
| 700 | 1 | |a Peng, Y. J. |4 aut | |
| 700 | 1 | |a Hong, Q. |4 aut | |
| 700 | 1 | |a Liu, M. H. |4 aut | |
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10.1007/s10812-017-0430-6 doi (DE-627)OLC2034687221 (DE-He213)s10812-017-0430-6-p DE-627 ger DE-627 rakwb eng 530 VZ 11 ssgn Zhao, J. H. verfasserin aut Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2017 Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. ractopamine clenbuterol hydrochloride surface enhanced Raman spectroscopy pork rapid detection and identification Yuan, H. C. aut Peng, Y. J. aut Hong, Q. aut Liu, M. H. aut Enthalten in Journal of applied spectroscopy Springer US, 1966 84(2017), 1 vom: März, Seite 76-81 (DE-627)129972495 (DE-600)410515-1 (DE-576)015535800 0021-9037 nnns volume:84 year:2017 number:1 month:03 pages:76-81 https://doi.org/10.1007/s10812-017-0430-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_70 AR 84 2017 1 03 76-81 |
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10.1007/s10812-017-0430-6 doi (DE-627)OLC2034687221 (DE-He213)s10812-017-0430-6-p DE-627 ger DE-627 rakwb eng 530 VZ 11 ssgn Zhao, J. H. verfasserin aut Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2017 Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. ractopamine clenbuterol hydrochloride surface enhanced Raman spectroscopy pork rapid detection and identification Yuan, H. C. aut Peng, Y. J. aut Hong, Q. aut Liu, M. H. aut Enthalten in Journal of applied spectroscopy Springer US, 1966 84(2017), 1 vom: März, Seite 76-81 (DE-627)129972495 (DE-600)410515-1 (DE-576)015535800 0021-9037 nnns volume:84 year:2017 number:1 month:03 pages:76-81 https://doi.org/10.1007/s10812-017-0430-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_70 AR 84 2017 1 03 76-81 |
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10.1007/s10812-017-0430-6 doi (DE-627)OLC2034687221 (DE-He213)s10812-017-0430-6-p DE-627 ger DE-627 rakwb eng 530 VZ 11 ssgn Zhao, J. H. verfasserin aut Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2017 Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. ractopamine clenbuterol hydrochloride surface enhanced Raman spectroscopy pork rapid detection and identification Yuan, H. C. aut Peng, Y. J. aut Hong, Q. aut Liu, M. H. aut Enthalten in Journal of applied spectroscopy Springer US, 1966 84(2017), 1 vom: März, Seite 76-81 (DE-627)129972495 (DE-600)410515-1 (DE-576)015535800 0021-9037 nnns volume:84 year:2017 number:1 month:03 pages:76-81 https://doi.org/10.1007/s10812-017-0430-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_70 AR 84 2017 1 03 76-81 |
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10.1007/s10812-017-0430-6 doi (DE-627)OLC2034687221 (DE-He213)s10812-017-0430-6-p DE-627 ger DE-627 rakwb eng 530 VZ 11 ssgn Zhao, J. H. verfasserin aut Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2017 Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. ractopamine clenbuterol hydrochloride surface enhanced Raman spectroscopy pork rapid detection and identification Yuan, H. C. aut Peng, Y. J. aut Hong, Q. aut Liu, M. H. aut Enthalten in Journal of applied spectroscopy Springer US, 1966 84(2017), 1 vom: März, Seite 76-81 (DE-627)129972495 (DE-600)410515-1 (DE-576)015535800 0021-9037 nnns volume:84 year:2017 number:1 month:03 pages:76-81 https://doi.org/10.1007/s10812-017-0430-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_70 AR 84 2017 1 03 76-81 |
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10.1007/s10812-017-0430-6 doi (DE-627)OLC2034687221 (DE-He213)s10812-017-0430-6-p DE-627 ger DE-627 rakwb eng 530 VZ 11 ssgn Zhao, J. H. verfasserin aut Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media New York 2017 Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. ractopamine clenbuterol hydrochloride surface enhanced Raman spectroscopy pork rapid detection and identification Yuan, H. C. aut Peng, Y. J. aut Hong, Q. aut Liu, M. H. aut Enthalten in Journal of applied spectroscopy Springer US, 1966 84(2017), 1 vom: März, Seite 76-81 (DE-627)129972495 (DE-600)410515-1 (DE-576)015535800 0021-9037 nnns volume:84 year:2017 number:1 month:03 pages:76-81 https://doi.org/10.1007/s10812-017-0430-6 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-PHY SSG-OLC-CHE GBV_ILN_70 AR 84 2017 1 03 76-81 |
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Zhao, J. H. Yuan, H. C. Peng, Y. J. Hong, Q. Liu, M. H. |
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detection of ractopamine and clenbuterol hydrochloride residues in pork using surface enhanced raman spectroscopy |
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Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy |
| abstract |
Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. © Springer Science+Business Media New York 2017 |
| abstractGer |
Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. © Springer Science+Business Media New York 2017 |
| abstract_unstemmed |
Surface enhanced Raman spectroscopy (SERS) coupled with chemometric methods, such as adaptive iteratively reweighted penalized least squares (AIR-PLS), wavelet transform, and least squares support vector machine (LSSVM), was investigated to realize the rapid detection and identifi cation of ractopamine (RAC) and clenbuterol hydrochloride (CL) residues in pork. First-level wavelet detail signal intensities at 1168 $ cm^{–1} $ were used to establish a standard curve of the RAC residues in pork, and the linear regression equation and the correlation coefficient were y = –4. 3683x – 11.059 and –0.9726. Second-level wavelet detail signal intensities at 1258 $ cm^{–1} $ were used to establish a standard curve of the CL residues in pork, and the linear regression equation and the correlation coeffi cient were y=33.595x + 36.538 and 0.9842. The second-level wavelet detail signals of the SERS spectra were selected as the inputs of the LSSVM classifi cation model for the identifi cation of the RAC and CL residues in pork, with a total accuracy rate reaching 100%. The experimental results demonstrate that the proposed method based on SERS is a good detection scheme for the rapid detection and identifi cation of RAC and CL residues in pork. © Springer Science+Business Media New York 2017 |
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Detection of Ractopamine and Clenbuterol Hydrochloride Residues in Pork Using Surface Enhanced Raman Spectroscopy |
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