Comparative study of volatile organic compound profiles in aromatic and non-aromatic rice cultivars using HS-GC–IMS and their correlation with sensory evaluation
Yin Xiong, Xingfei Zheng, Xuhong Tian, Chongrong Wang, Junxiao Chen, Lei Zhou, Deze Xu, Jingyi Wang, Véronique Gilard, Muci Wu, Aiqing You
Abstract
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.