ArticleMolecules (Basel, Switzerland)2023
Analysis of the Differences in Volatile Organic Compounds in Different Rice Varieties Based on GC-IMS Technology Combined with Multivariate Statistical Modelling.
Article in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- Review
- A comprehensive map of key aroma-active compounds in cigar tobacco via GC-IMS and GC-O-MS.Frontiers in plant science · 2026Article
- Chemometric Approach for Discriminating the Volatile Profile of Cooked Glutinous and Normal-Amylose Rice Cultivars from Representative Japanese Production Areas Using GC × GC-TOFMS.Foods (Basel, Switzerland) · 2025Article
- Discrimination of different varieties of rice in Wuchang area based onFood chemistry: X · 2025Article
- Analysis of volatile organic compounds in ten types of tribute Rice based on headspace-gas chromatography-ion mobility spectrometry technology.Food chemistry: X · 2025Article
- Comparative transcriptome and genome analysis between susceptible Zhefang rice variety Diantun 502 and its resistance variety Diantun 506 upon Magnaporthe oryzae infection.BMC plant biology · 2025Article
- Identification of characteristic flavor compounds ofFood chemistry: X · 2024Article
- Analysis of rice characteristic volatiles and their influence on rice aroma.Current research in food science · 2024Article
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9 authors.
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Abstract
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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