基于挥发性成分和多元统计分析法鉴别稻谷新陈度
Analysis Method for Freshness of Stored Paddy Rice Based on Volatile Components and Multivariate Statistical Analysis
郭瑞 1李盼盼 2张炜 1王楠希 1杨永坛1
作者信息
- 1. 国家粮食和物资储备局科学研究院,北京 100037
- 2. 国家粮食和物资储备局科学研究院,北京 100037;河南工业大学粮油食品学院,郑州 450001
- 折叠
摘要
本研究以2019～2023年份收获的稻谷为研究对象,采用顶空固相微萃取-气相色谱-三重四极杆质谱联用方法对稻谷的挥发性成分进行检测,结合标准质谱数据库及保留指数建立选择离子监测方法,通过内标法计算各个组分的含量.采用主成分分析和正交偏最小二乘法判别分析对挥发性化合物进行多元统计分析,筛选出与稻谷新鲜度相关的差异化合物,建立了基于挥发性成分分析的储藏稻谷鉴别模型.在不同年份收获的稻谷样本中共检出44种挥发性化合物,包括醛类、醇类、酮类、酸类、酯类、酚类和呋喃等.多元统计分析结果表明,根据挥发性化合物含量建立的正交偏最小二乘法判别分析模型,2023年收获的稻谷与2019～2022年收获的稻谷可显著区分为两类,进一步基于变量重要性投影(VIP)值大于1和单因素分析p值小于0.05,确定己酸和壬酸等12种化合物为差异化合物.本研究提出的基于挥发性成分分析的储藏稻谷分类模型可为稻谷新陈度判定提供理论依据.
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.
关键词
稻谷/挥发性成分/气相色谱-三重四极杆质谱/多元统计分析/分类模型Key words
Paddy rice/Volatile component/Gas chromatography-triple quadrupole mass spectrometry/Multivariate statistical analysis/Classification model引用本文复制引用
基金项目
中央级公益性科研院所基本科研业务费专项项目(ZX2407)
出版年
2024
国家科技期刊平台
NSTL
万方数据