Analysis Method for Freshness of Stored Paddy Rice Based on Volatile Components and Multivariate Statistical Analysis
10.19756/j.issn.0253-3820.241233
- VernacularTitle:基于挥发性成分和多元统计分析法鉴别稻谷新陈度
- Author:
Rui GUO
1
;
Pan-Pan LI
;
Wei ZHANG
;
Nan-Xi WANG
;
Yong-Tan YANG
Author Information
1. 国家粮食和物资储备局科学研究院,北京 100037
- Keywords:
Paddy rice;
Volatile component;
Gas chromatography-triple quadrupole mass spectrometry;
Multivariate statistical analysis;
Classification model
- From:
Chinese Journal of Analytical Chemistry
2024;52(9):1244-1253
- CountryChina
- Language:Chinese
-
Abstract:
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.
