Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy
This study attempted to measure the total polyphenols contents in Fuzhuan tea by near-infrared (NIR) spectroscopy coupled with an appropriate multivariate calibration method. Partial least squares (PLS), synergy interval PLS (si-PLS), and genetic algorithm-based PLS (ga-PLS) were carried out compara...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2022-12-01
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| Series: | CyTA - Journal of Food |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19476337.2022.2128429 |
| _version_ | 1811241289898786816 |
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| author | Jing-Xue Liu Jia-Ying Xin Ting-Ting Gao Feng-Lin Li Xie Tian |
| author_facet | Jing-Xue Liu Jia-Ying Xin Ting-Ting Gao Feng-Lin Li Xie Tian |
| author_sort | Jing-Xue Liu |
| collection | DOAJ |
| description | This study attempted to measure the total polyphenols contents in Fuzhuan tea by near-infrared (NIR) spectroscopy coupled with an appropriate multivariate calibration method. Partial least squares (PLS), synergy interval PLS (si-PLS), and genetic algorithm-based PLS (ga-PLS) were carried out comparatively to calibrate regression models. The root mean square error of prediction (RMSEP), determination coefficient (Rp2), and P-value between the true and predicted values of prediction set were used to evaluate the performance of the final model. The ga-PLS model showed the best performance compared with the PLS and si-PLS models. The optimal model obtained Rp2 = 0.9996 and RMSEP = 0.0488 for the prediction set using only 37 spectral data points. No significant difference was observed between the true and predicted tea polyphenol contents in the prediction set (P > 0.05). NIR spectroscopy together with the ga-PLS algorithm can be used to rapidly predict the total polyphenol contents in Fuzhuan tea. |
| first_indexed | 2024-04-12T13:34:14Z |
| format | Article |
| id | doaj.art-e73ba76f4d18499d9b089c4abb8de3a5 |
| institution | Directory Open Access Journal |
| issn | 1947-6337 1947-6345 |
| language | English |
| last_indexed | 2024-04-12T13:34:14Z |
| publishDate | 2022-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | CyTA - Journal of Food |
| spelling | doaj.art-e73ba76f4d18499d9b089c4abb8de3a52022-12-22T03:31:05ZengTaylor & Francis GroupCyTA - Journal of Food1947-63371947-63452022-12-0120123624310.1080/19476337.2022.2128429Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopyJing-Xue Liu0Jia-Ying Xin1Ting-Ting Gao2Feng-Lin Li3Xie Tian4Key Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, Heilongjiang, ChinaKey Laboratory for Food Science & Engineering, Harbin University of Commerce, Harbin, Heilongjiang, ChinaCollege of Food Engineering, Jilin Agricultural Science and Technology University, Jilin, Jilin, ChinaCollege of Food Engineering, Jilin Agricultural Science and Technology University, Jilin, Jilin, ChinaCollege of Food Engineering, Jilin Agricultural Science and Technology University, Jilin, Jilin, ChinaThis study attempted to measure the total polyphenols contents in Fuzhuan tea by near-infrared (NIR) spectroscopy coupled with an appropriate multivariate calibration method. Partial least squares (PLS), synergy interval PLS (si-PLS), and genetic algorithm-based PLS (ga-PLS) were carried out comparatively to calibrate regression models. The root mean square error of prediction (RMSEP), determination coefficient (Rp2), and P-value between the true and predicted values of prediction set were used to evaluate the performance of the final model. The ga-PLS model showed the best performance compared with the PLS and si-PLS models. The optimal model obtained Rp2 = 0.9996 and RMSEP = 0.0488 for the prediction set using only 37 spectral data points. No significant difference was observed between the true and predicted tea polyphenol contents in the prediction set (P > 0.05). NIR spectroscopy together with the ga-PLS algorithm can be used to rapidly predict the total polyphenol contents in Fuzhuan tea.https://www.tandfonline.com/doi/10.1080/19476337.2022.2128429Fuzhuan teatea polyphenolsnear-infrared spectroscopypartial least squaresgenetic algorithmTé Fuzhuan |
| spellingShingle | Jing-Xue Liu Jia-Ying Xin Ting-Ting Gao Feng-Lin Li Xie Tian Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy CyTA - Journal of Food Fuzhuan tea tea polyphenols near-infrared spectroscopy partial least squares genetic algorithm Té Fuzhuan |
| title | Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy |
| title_full | Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy |
| title_fullStr | Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy |
| title_full_unstemmed | Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy |
| title_short | Effect of variable selection and rapid determination of total tea polyphenols contents in Fuzhuan tea by near-infrared spectroscopy |
| title_sort | effect of variable selection and rapid determination of total tea polyphenols contents in fuzhuan tea by near infrared spectroscopy |
| topic | Fuzhuan tea tea polyphenols near-infrared spectroscopy partial least squares genetic algorithm Té Fuzhuan |
| url | https://www.tandfonline.com/doi/10.1080/19476337.2022.2128429 |
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