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Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling

In order to investigate the flavour characteristics of aromatic, glutinous, and nonaromatic rice, gas chromatography–ion mobility spectrometry (GC-IMS) was used to analyse the differences in volatile organic compounds (VOCs) amongst different rice varieties. The results showed that 103 signal peaks...

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Autores principales: Chen, Jin, Liu, Ying, Yang, Mi, Shi, Xinmin, Mei, Yuqin, Li, Juan, Yang, Chunqi, Pu, Shihuang, Wen, Jiancheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673298/
https://www.ncbi.nlm.nih.gov/pubmed/38005287
http://dx.doi.org/10.3390/molecules28227566
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author Chen, Jin
Liu, Ying
Yang, Mi
Shi, Xinmin
Mei, Yuqin
Li, Juan
Yang, Chunqi
Pu, Shihuang
Wen, Jiancheng
author_facet Chen, Jin
Liu, Ying
Yang, Mi
Shi, Xinmin
Mei, Yuqin
Li, Juan
Yang, Chunqi
Pu, Shihuang
Wen, Jiancheng
author_sort Chen, Jin
collection PubMed
description In order to investigate the flavour characteristics of aromatic, glutinous, and nonaromatic rice, gas chromatography–ion mobility spectrometry (GC-IMS) was used to analyse the differences in volatile organic compounds (VOCs) amongst different rice varieties. The results showed that 103 signal peaks were detected in these rice varieties, and 91 volatile flavour substances were identified. Amongst them, 28 aldehydes (28.89~31.17%), 24 alcohols (34.85~40.52%), 14 ketones (12.26~14.74%), 12 esters (2.30~4.15%), 5 acids (7.80~10.85%), 3 furans (0.30~0.68%), 3 terpenes (0.34~0.64%), and 2 species of ethers (0.80~1.78%) were detected. SIMCA14.1 was used to perform principal component analysis (PCA) and orthogonal partial least squares discriminant analysis, and some potential character markers (VIP > 1) were further screened out of the 91 flavour substances identified based on the variable important projections, including ethanol, 1-hexanol, hexanal, heptanal, nonanal, (E)-2-heptenal, octanal, trans-2-octenal, pentanal, acetone, 6-methyl-5-hepten-2-one, ethyl acetate, propyl acetate, acetic acid, and dimethyl sulphide. Based on the established fingerprint information, combined with principal component analysis and orthogonal partial least squares discriminant analysis, different rice varieties were also effectively classified, and the results of this study provide data references for the improvement in aromatic rice varieties.
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spelling pubmed-106732982023-11-13 Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling Chen, Jin Liu, Ying Yang, Mi Shi, Xinmin Mei, Yuqin Li, Juan Yang, Chunqi Pu, Shihuang Wen, Jiancheng Molecules Article In order to investigate the flavour characteristics of aromatic, glutinous, and nonaromatic rice, gas chromatography–ion mobility spectrometry (GC-IMS) was used to analyse the differences in volatile organic compounds (VOCs) amongst different rice varieties. The results showed that 103 signal peaks were detected in these rice varieties, and 91 volatile flavour substances were identified. Amongst them, 28 aldehydes (28.89~31.17%), 24 alcohols (34.85~40.52%), 14 ketones (12.26~14.74%), 12 esters (2.30~4.15%), 5 acids (7.80~10.85%), 3 furans (0.30~0.68%), 3 terpenes (0.34~0.64%), and 2 species of ethers (0.80~1.78%) were detected. SIMCA14.1 was used to perform principal component analysis (PCA) and orthogonal partial least squares discriminant analysis, and some potential character markers (VIP > 1) were further screened out of the 91 flavour substances identified based on the variable important projections, including ethanol, 1-hexanol, hexanal, heptanal, nonanal, (E)-2-heptenal, octanal, trans-2-octenal, pentanal, acetone, 6-methyl-5-hepten-2-one, ethyl acetate, propyl acetate, acetic acid, and dimethyl sulphide. Based on the established fingerprint information, combined with principal component analysis and orthogonal partial least squares discriminant analysis, different rice varieties were also effectively classified, and the results of this study provide data references for the improvement in aromatic rice varieties. MDPI 2023-11-13 /pmc/articles/PMC10673298/ /pubmed/38005287 http://dx.doi.org/10.3390/molecules28227566 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
Chen, Jin
Liu, Ying
Yang, Mi
Shi, Xinmin
Mei, Yuqin
Li, Juan
Yang, Chunqi
Pu, Shihuang
Wen, Jiancheng
Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling
title Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling
title_full Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling
title_fullStr Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling
title_full_unstemmed Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling
title_short Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling
title_sort analysis of the differences in volatile organic compounds in different rice varieties based on gc-ims technology combined with multivariate statistical modelling
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10673298/
https://www.ncbi.nlm.nih.gov/pubmed/38005287
http://dx.doi.org/10.3390/molecules28227566
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