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. 2023 Nov 13;28(22):7566.
doi: 10.3390/molecules28227566.

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

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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

Jin Chen et al. Molecules. .

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.

Keywords: gas chromatography–ion mobility spectrometry (GC-IMS); orthogonal partial least squares discriminant analysis; principal component analysis; rice; volatile components.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
(left,right) GC-IMS 3D spectra (a~f: DG163, DG1839, DG1938, DG1946, DG2029, DG2030) and GC-IMS 2D spectra of volatile substances in different rice varieties.
Figure 2
Figure 2
GC-IMS two-dimensional spectra of volatile substances in different rice varieties (difference comparison map).
Figure 3
Figure 3
Qualitative analysis spectrum of volatile substances in rice variety DG163 via GC-IMS.
Figure 4
Figure 4
Fingerprints of volatile components in different rice varieties. Note: rows represent all signal peaks selected in the samples, and columns represent signal peaks of volatile components in different samples.
Figure 5
Figure 5
Relative contents of volatile substances in different rice varieties.
Figure 6
Figure 6
PCA diagram (left) and OPLS-DA model (right) of volatile substances of different rice varieties.
Figure 7
Figure 7
OPLS-DA model validation and VIP values of different rice varieties (Compounds highlighted in red are potential signature markers for VIP > 1).
Figure 8
Figure 8
PCR analysis of aromatic gene badh2 locus of aromatic rice Diantun502 and its improved lines. Note: M: DNA ladder marker; 1: DT502; 2: DG163; 3: DG1839; 4: DG1946; 5: DG1938; 6: DG2029; 7: DG2030.

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