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Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods

Crataegi Fructus (CF) is widely used as a medicinal and edible material around the world. Currently, different types of processed CF products are commonly found in the market. Quality evaluation of them mainly relies on chemical content determination, which is time and money consuming. To rapidly an...

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Detalles Bibliográficos
Autores principales: Fei, Chenghao, Ren, Chenchen, Wang, Yulin, Li, Lin, Li, Weidong, Yin, Fangzhou, Lu, Tulin, Yin, Wu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817683/
https://www.ncbi.nlm.nih.gov/pubmed/33473146
http://dx.doi.org/10.1038/s41598-020-79717-w
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author Fei, Chenghao
Ren, Chenchen
Wang, Yulin
Li, Lin
Li, Weidong
Yin, Fangzhou
Lu, Tulin
Yin, Wu
author_facet Fei, Chenghao
Ren, Chenchen
Wang, Yulin
Li, Lin
Li, Weidong
Yin, Fangzhou
Lu, Tulin
Yin, Wu
author_sort Fei, Chenghao
collection PubMed
description Crataegi Fructus (CF) is widely used as a medicinal and edible material around the world. Currently, different types of processed CF products are commonly found in the market. Quality evaluation of them mainly relies on chemical content determination, which is time and money consuming. To rapidly and nondestructively discriminate different types of processed CF products, an electronic nose coupled with chemometrics was developed. The odour detection method of CF was first established by single-factor investigation. Then, the sensor array was optimised by a stepwise discriminant analysis (SDA) and analysis of variance (ANOVA). Based on the best-optimised sensor array, the digital and mode standard were established, realizing the odour quality control of samples. Meanwhile, mathematical prediction models including the discriminant formula and back-propagation neural network (BPNN) model exhibited good evaluation with a high accuracy rate. These results suggest that the developed electronic nose system could be an alternative way for evaluating the odour of different types of processed CF products.
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spelling pubmed-78176832021-01-22 Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods Fei, Chenghao Ren, Chenchen Wang, Yulin Li, Lin Li, Weidong Yin, Fangzhou Lu, Tulin Yin, Wu Sci Rep Article Crataegi Fructus (CF) is widely used as a medicinal and edible material around the world. Currently, different types of processed CF products are commonly found in the market. Quality evaluation of them mainly relies on chemical content determination, which is time and money consuming. To rapidly and nondestructively discriminate different types of processed CF products, an electronic nose coupled with chemometrics was developed. The odour detection method of CF was first established by single-factor investigation. Then, the sensor array was optimised by a stepwise discriminant analysis (SDA) and analysis of variance (ANOVA). Based on the best-optimised sensor array, the digital and mode standard were established, realizing the odour quality control of samples. Meanwhile, mathematical prediction models including the discriminant formula and back-propagation neural network (BPNN) model exhibited good evaluation with a high accuracy rate. These results suggest that the developed electronic nose system could be an alternative way for evaluating the odour of different types of processed CF products. Nature Publishing Group UK 2021-01-20 /pmc/articles/PMC7817683/ /pubmed/33473146 http://dx.doi.org/10.1038/s41598-020-79717-w Text en © The Author(s) 2021 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Fei, Chenghao
Ren, Chenchen
Wang, Yulin
Li, Lin
Li, Weidong
Yin, Fangzhou
Lu, Tulin
Yin, Wu
Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods
title Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods
title_full Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods
title_fullStr Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods
title_full_unstemmed Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods
title_short Identification of the raw and processed Crataegi Fructus based on the electronic nose coupled with chemometric methods
title_sort identification of the raw and processed crataegi fructus based on the electronic nose coupled with chemometric methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7817683/
https://www.ncbi.nlm.nih.gov/pubmed/33473146
http://dx.doi.org/10.1038/s41598-020-79717-w
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