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A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea
To investigate different contents of pu-erh tea polyphenol affected by abiotic stress, this research determined the contents of tea polyphenol in teas produced by Yuecheng, a Xishuangbanna-based tea producer in Yunnan Province. The study drew a preliminary conclusion that eight factors, namely, alti...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252623/ https://www.ncbi.nlm.nih.gov/pubmed/37297373 http://dx.doi.org/10.3390/foods12112128 |
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author | Zhang, Shihao Yang, Chunhua Sheng, Yubo Liu, Xiaohui Yuan, Wenxia Deng, Xiujuan Li, Xinghui Huang, Wei Zhang, Yinsong Li, Lei Lv, Yuan Wang, Yuefei Wang, Baijuan |
author_facet | Zhang, Shihao Yang, Chunhua Sheng, Yubo Liu, Xiaohui Yuan, Wenxia Deng, Xiujuan Li, Xinghui Huang, Wei Zhang, Yinsong Li, Lei Lv, Yuan Wang, Yuefei Wang, Baijuan |
author_sort | Zhang, Shihao |
collection | PubMed |
description | To investigate different contents of pu-erh tea polyphenol affected by abiotic stress, this research determined the contents of tea polyphenol in teas produced by Yuecheng, a Xishuangbanna-based tea producer in Yunnan Province. The study drew a preliminary conclusion that eight factors, namely, altitude, nickel, available cadmium, organic matter, N, P, K, and alkaline hydrolysis nitrogen, had a considerable influence on tea polyphenol content with a combined analysis of specific altitudes and soil composition. The nomogram model constructed with three variables, altitude, organic matter, and P, screened by LASSO regression showed that the AUC of the training group and the validation group were respectively 0.839 and 0.750, and calibration curves were consistent. A visualized prediction system for the content of pu-erh tea polyphenol based on the nomogram model was developed and its accuracy rate, supported by measured data, reached 80.95%. This research explored the change of tea polyphenol content under abiotic stress, laying a solid foundation for further predictions for and studies on the quality of pu-erh tea and providing some theoretical scientific basis. |
format | Online Article Text |
id | pubmed-10252623 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102526232023-06-10 A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea Zhang, Shihao Yang, Chunhua Sheng, Yubo Liu, Xiaohui Yuan, Wenxia Deng, Xiujuan Li, Xinghui Huang, Wei Zhang, Yinsong Li, Lei Lv, Yuan Wang, Yuefei Wang, Baijuan Foods Article To investigate different contents of pu-erh tea polyphenol affected by abiotic stress, this research determined the contents of tea polyphenol in teas produced by Yuecheng, a Xishuangbanna-based tea producer in Yunnan Province. The study drew a preliminary conclusion that eight factors, namely, altitude, nickel, available cadmium, organic matter, N, P, K, and alkaline hydrolysis nitrogen, had a considerable influence on tea polyphenol content with a combined analysis of specific altitudes and soil composition. The nomogram model constructed with three variables, altitude, organic matter, and P, screened by LASSO regression showed that the AUC of the training group and the validation group were respectively 0.839 and 0.750, and calibration curves were consistent. A visualized prediction system for the content of pu-erh tea polyphenol based on the nomogram model was developed and its accuracy rate, supported by measured data, reached 80.95%. This research explored the change of tea polyphenol content under abiotic stress, laying a solid foundation for further predictions for and studies on the quality of pu-erh tea and providing some theoretical scientific basis. MDPI 2023-05-25 /pmc/articles/PMC10252623/ /pubmed/37297373 http://dx.doi.org/10.3390/foods12112128 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Zhang, Shihao Yang, Chunhua Sheng, Yubo Liu, Xiaohui Yuan, Wenxia Deng, Xiujuan Li, Xinghui Huang, Wei Zhang, Yinsong Li, Lei Lv, Yuan Wang, Yuefei Wang, Baijuan A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea |
title | A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea |
title_full | A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea |
title_fullStr | A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea |
title_full_unstemmed | A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea |
title_short | A Nomogram Model for Predicting the Polyphenol Content of Pu-Erh Tea |
title_sort | nomogram model for predicting the polyphenol content of pu-erh tea |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10252623/ https://www.ncbi.nlm.nih.gov/pubmed/37297373 http://dx.doi.org/10.3390/foods12112128 |
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