Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing
In order to explore spectral standardization methods for spectra collected by different NIR spectrometers, to reduce spectral differences, and to realize model sharing among different instruments, the crude protein content of 154 wheat flour samples was measured using one grating and three Fabry-Per...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Journal of Food Quality |
| Online Access: | http://dx.doi.org/10.1155/2022/9009756 |
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| author | Jing Tian Xinyu Chen Zhennan Liang Wenliang Qi Xiaohuan Zheng Daoli Lu Bin Chen |
| author_facet | Jing Tian Xinyu Chen Zhennan Liang Wenliang Qi Xiaohuan Zheng Daoli Lu Bin Chen |
| author_sort | Jing Tian |
| collection | DOAJ |
| description | In order to explore spectral standardization methods for spectra collected by different NIR spectrometers, to reduce spectral differences, and to realize model sharing among different instruments, the crude protein content of 154 wheat flour samples was measured using one grating and three Fabry-Perot tunable filter NIR spectrometers in wavelength. At the same wavelength range and wavelength interval, three algorithms, namely, direct standardization (DS), piecewise direct standardization (PDS), and simple linear regression direct standardization (SLRDS), were used to standardize spectra collected by different instruments from the same samples. Spectral standardization error rate (SSER), principal component score error rate (PCSER), and other indicators were employed to analyze the spectral differences between the master and the target spectra, and the effect of model sharing was evaluated using parameters including prediction correlation coefficient (Rp), root mean square error of prediction (RMSEP), and relative prediction deviation (RPD). The results show the following: (1) The difference between spectra can be quantitatively evaluated through analyzing SSER and PCSER. (2) After standardization by the three algorithms, the spectral difference between the three target and the master spectrometers is significantly reduced and the prediction effect of the master model is greatly improved. (3) Among the three algorithms, DS algorithm had the smallest error rate in standardizing spectra from three target spectrometers. After standardization by the DS algorithm, the master model had the best effect. Its prediction accuracy was greatly improved compared with that before standardization. (4) The standard model established based on the S450 spectrometer can be applied to the same spectrometer as the N500 spectrometer with the same resolution and different wavelength ranges, so as to achieve model sharing. Therefore, DS, PDS, and SLRDS algorithms can effectively reduce the spectral differences between different instruments and realize the sharing of NIR calibration models for wheat flour crude protein measurement. |
| format | Article |
| id | doaj-art-e42e48f0a79b467eb3cfdef4bbd1d853 |
| institution | OA Journals |
| issn | 1745-4557 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Food Quality |
| spelling | doaj-art-e42e48f0a79b467eb3cfdef4bbd1d8532025-08-20T02:21:34ZengWileyJournal of Food Quality1745-45572022-01-01202210.1155/2022/9009756Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model SharingJing Tian0Xinyu Chen1Zhennan Liang2Wenliang Qi3Xiaohuan Zheng4Daoli Lu5Bin Chen6School of Food and Biological EngineeringDepartment of Physical ChemistrySchool of Mechanical EngineeringSchool of Food and Biological EngineeringSchool of Food and Biological EngineeringSchool of Food and Biological EngineeringSchool of Food and Biological EngineeringIn order to explore spectral standardization methods for spectra collected by different NIR spectrometers, to reduce spectral differences, and to realize model sharing among different instruments, the crude protein content of 154 wheat flour samples was measured using one grating and three Fabry-Perot tunable filter NIR spectrometers in wavelength. At the same wavelength range and wavelength interval, three algorithms, namely, direct standardization (DS), piecewise direct standardization (PDS), and simple linear regression direct standardization (SLRDS), were used to standardize spectra collected by different instruments from the same samples. Spectral standardization error rate (SSER), principal component score error rate (PCSER), and other indicators were employed to analyze the spectral differences between the master and the target spectra, and the effect of model sharing was evaluated using parameters including prediction correlation coefficient (Rp), root mean square error of prediction (RMSEP), and relative prediction deviation (RPD). The results show the following: (1) The difference between spectra can be quantitatively evaluated through analyzing SSER and PCSER. (2) After standardization by the three algorithms, the spectral difference between the three target and the master spectrometers is significantly reduced and the prediction effect of the master model is greatly improved. (3) Among the three algorithms, DS algorithm had the smallest error rate in standardizing spectra from three target spectrometers. After standardization by the DS algorithm, the master model had the best effect. Its prediction accuracy was greatly improved compared with that before standardization. (4) The standard model established based on the S450 spectrometer can be applied to the same spectrometer as the N500 spectrometer with the same resolution and different wavelength ranges, so as to achieve model sharing. Therefore, DS, PDS, and SLRDS algorithms can effectively reduce the spectral differences between different instruments and realize the sharing of NIR calibration models for wheat flour crude protein measurement.http://dx.doi.org/10.1155/2022/9009756 |
| spellingShingle | Jing Tian Xinyu Chen Zhennan Liang Wenliang Qi Xiaohuan Zheng Daoli Lu Bin Chen Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing Journal of Food Quality |
| title | Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing |
| title_full | Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing |
| title_fullStr | Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing |
| title_full_unstemmed | Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing |
| title_short | Application of NIR Spectral Standardization Based on Principal Component Score Evaluation in Wheat Flour Crude Protein Model Sharing |
| title_sort | application of nir spectral standardization based on principal component score evaluation in wheat flour crude protein model sharing |
| url | http://dx.doi.org/10.1155/2022/9009756 |
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