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Comparative study of volatile organic compound profiles in aromatic and non-aromatic rice cultivars using HS-GC-IMS and their correlation with sensory evaluation

文献类型： 外文期刊

作者： Xiong, Yin 1 ; Zheng, Xingfei 2 ; Tian, Xuhong 1 ; Wang, Chongrong 3 ; Chen, Junxiao 2 ; Zhou, Lei 2 ; Xu, Deze 2 ; Wang, Jingyi 4 ; Gilard, Veronique 5 ; Wu, Muci 1 ; You, Aiqing 2 ;

作者机构： 1.Wuhan Polytech Univ, Sch Modern Ind Selenium Sci & Engn, 36 Huanhu Middle Rd, Wuhan 430023, Peoples R China

2.Hubei Acad Agr Sci, Inst Food Crops, Key Lab Crop Mol Breeding, Hubei Key Lab Food Crop Germplasm & Genet Improvem, Wuhan 430064, Peoples R China

3.Guangdong Acad Agr Sci, Guangdong Key Lab New Technol Rice Breeding, Rice Res Inst,Minist Agr & Rural Affairs, Key Lab Genet & Breeding High Qual Rice Southern C, Guangzhou 510640, Peoples R China

4.Hubei Univ Technol, Sch food & Biol Engn, Wuhan 430068, Peoples R China

5.Univ Toulouse III Paul Sabatier, Lab Softmat, CNRS UMR 5623, 118 route Narbonne, F-31062 Toulouse, France

关键词： Aromatic rice; Non -aromatic rice; HS-GC -IMS; Sensory evaluation; Correlation analysis

期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：6.0； 五年影响因子：6.0 ）

ISSN： 0023-6438

年卷期： 2024 年 203 卷

页码：

收录情况： SCI

摘要： Analyzing of volatile organic compounds (VOCs) is important in rice quality control and breeding aromatic cultivars. This study utilized HS-GC -IMS, known for its simplicity, high sensitivity, and low cost, to analyze VOCs in 59 aromatic and 6 non -aromatic rice cultivars. The aromatic intensity of each rice cultivar was determined by artificial sensory evaluation, thus the correlation between sensory evaluation scores and VOC peak volumes was explored. A total of 77 VOCs were identified, with aromatic cultivars exhibiting prevalent short -chain aliphatic aldehydes, alcohols, and ketones, while non -aromatic samples contained higher concentrations of esters, furans, terpenes, and benzene derivatives. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) based on VOC data effectively distinguished the two rice types, and 35 VOCs were regarded as the marker VOCs contributing to the volatile variations. Furthermore, the correlation analysis between sensory evaluation and VOC markers revealed that most of these VOCs had a positive correlation with the sensory evaluation scores, with 1-pentanol, 2-acetyl-1-pyrroline (D), and 1-hexanol (M) exhibiting the highest correlation coefficients. Meanwhile, most VOC markers also exhibited positive correlations with other volatiles. The results confirm the suitability of HS-GC -IMS for VOC detection and rice category discrimination.

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