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Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning

INTRODUCTION: The cultivation and sale of medicinal plants are some of the main ways to meet the increased market demand for plant-based drugs. Panax notoginseng is a widely used Chinese medicinal material. The growth and accumulation of bioactive constituents mainly depend on a satisfactory growing...

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Autores principales: Liu, Chunlu, Zuo, Zhitian, Xu, Furong, Wang, Yuanzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941628/
https://www.ncbi.nlm.nih.gov/pubmed/36825249
http://dx.doi.org/10.3389/fpls.2022.1009727
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author Liu, Chunlu
Zuo, Zhitian
Xu, Furong
Wang, Yuanzhong
author_facet Liu, Chunlu
Zuo, Zhitian
Xu, Furong
Wang, Yuanzhong
author_sort Liu, Chunlu
collection PubMed
description INTRODUCTION: The cultivation and sale of medicinal plants are some of the main ways to meet the increased market demand for plant-based drugs. Panax notoginseng is a widely used Chinese medicinal material. The growth and accumulation of bioactive constituents mainly depend on a satisfactory growing environment. Additionally, the occurrence of market fraud means that care should be taken when purchasing. METHODS: In this study, we report the correlation between saponins and climate factors based on high performance liquid chromatography (HPLC), and evaluate the influence of climate factors on the quality of P. notoginseng. In addition, the synchronous two-dimensional correlation spectroscopy (2D-COS) images of near infrared (NIR) data combined with the deep learning model were applied to traceability of geographic origins of P. notoginseng at two different levels (district and town levels). RESULTS: The results indicated that the contents of saponins in P. notoginseng are negatively related to the annual mean temperature and the temperature annual range. A lower annual mean temperature and temperature annual range are favorable for the content accumulation of saponins. Additionally, high annual precipitation and high humidity are conducive to the content accumulation of Notoginsenoside R1 (NG-R1), Ginsenosides Rg1 (G-Rg1), and Ginsenosides Rb1 (G-Rb1), while Ginsenosides Rd (G-Rd), this is not the case. Regarding geographic origins, classifications at two different levels could be successfully distinguished through synchronous 2D-COS images combined with the residual convolutional neural network (ResNet) model. The model accuracy of the training set, test set, and external validation is achieved at 100%, and the cross-entropy loss function curves are lower. This demonstrated the potential feasibility of the proposed method for P. notoginseng geographic origin traceability, even if the distance between sampling points is small. DISCUSSION: The findings of this study could improve the quality of P. notoginseng, provide a reference for cultivating P. notoginseng in the future and alleviate the occurrence of market fraud.
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spelling pubmed-99416282023-02-22 Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning Liu, Chunlu Zuo, Zhitian Xu, Furong Wang, Yuanzhong Front Plant Sci Plant Science INTRODUCTION: The cultivation and sale of medicinal plants are some of the main ways to meet the increased market demand for plant-based drugs. Panax notoginseng is a widely used Chinese medicinal material. The growth and accumulation of bioactive constituents mainly depend on a satisfactory growing environment. Additionally, the occurrence of market fraud means that care should be taken when purchasing. METHODS: In this study, we report the correlation between saponins and climate factors based on high performance liquid chromatography (HPLC), and evaluate the influence of climate factors on the quality of P. notoginseng. In addition, the synchronous two-dimensional correlation spectroscopy (2D-COS) images of near infrared (NIR) data combined with the deep learning model were applied to traceability of geographic origins of P. notoginseng at two different levels (district and town levels). RESULTS: The results indicated that the contents of saponins in P. notoginseng are negatively related to the annual mean temperature and the temperature annual range. A lower annual mean temperature and temperature annual range are favorable for the content accumulation of saponins. Additionally, high annual precipitation and high humidity are conducive to the content accumulation of Notoginsenoside R1 (NG-R1), Ginsenosides Rg1 (G-Rg1), and Ginsenosides Rb1 (G-Rb1), while Ginsenosides Rd (G-Rd), this is not the case. Regarding geographic origins, classifications at two different levels could be successfully distinguished through synchronous 2D-COS images combined with the residual convolutional neural network (ResNet) model. The model accuracy of the training set, test set, and external validation is achieved at 100%, and the cross-entropy loss function curves are lower. This demonstrated the potential feasibility of the proposed method for P. notoginseng geographic origin traceability, even if the distance between sampling points is small. DISCUSSION: The findings of this study could improve the quality of P. notoginseng, provide a reference for cultivating P. notoginseng in the future and alleviate the occurrence of market fraud. Frontiers Media S.A. 2023-02-07 /pmc/articles/PMC9941628/ /pubmed/36825249 http://dx.doi.org/10.3389/fpls.2022.1009727 Text en Copyright © 2023 Liu, Zuo, Xu and Wang https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Plant Science
Liu, Chunlu
Zuo, Zhitian
Xu, Furong
Wang, Yuanzhong
Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning
title Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning
title_full Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning
title_fullStr Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning
title_full_unstemmed Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning
title_short Study of the suitable climate factors and geographical origins traceability of Panax notoginseng based on correlation analysis and spectral images combined with machine learning
title_sort study of the suitable climate factors and geographical origins traceability of panax notoginseng based on correlation analysis and spectral images combined with machine learning
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9941628/
https://www.ncbi.nlm.nih.gov/pubmed/36825249
http://dx.doi.org/10.3389/fpls.2022.1009727
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