Analysis Method for Freshness of Stored Paddy Rice Based on Volatile Components and Multivariate Statistical Analysis
By using paddy rice harvested between 2019 and 2023 as the research object,the volatile components of rice grains were detected by headspace solid-phase microextraction coupled with gas chromatography-triple quadrupole mass spectrometry.Qualitative analysis of the compounds was complemented by a standard mass spectrometry database and retention index,while a selected ion monitoring approach was established to quantify the contents of each component through the internal standard method.Multivariate statistical analyses including principal component analysis and orthogonal partial least squares discriminant analysis were employed to identify differential compounds related to freshness of the paddy rice.Subsequently,a classification model for identifying stored paddy rice based on volatile component analysis was developed.A total of 44 kinds of volatile compounds were identified across different harvest years,including aldehydes,alcohols,ketones,acids,esters,phenols and furans.The results of the multivariate statistical analysis revealed that the content-based orthogonal partial least squares discriminant analysis model could effectively distinguish 2023 harvested paddy rice from those harvested between 2019 and 2022 into two distinct categories.Notably,compounds such as hexanoic acid and nonanoic acid along with twelve others were identified as differential compounds based on variable improtance in projection(VIP)values exceeding 1 and p values less than 0.05.The classification model established through volatile component analysis was expected to provide a theoretical foundation for assessing the freshness of stored paddy rice.
Paddy riceVolatile componentGas chromatography-triple quadrupole mass spectrometryMultivariate statistical analysisClassification model
国家科技期刊平台
NSTL
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