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投稿时间：2021-10-20
投稿时间：2021-10-20
中文摘要: 为实现对霉变香米快速、简便、准确地判别分析，以自然霉变香米中分离出的6种主要霉菌为研究对象，借助气相离子迁移谱（gas chromatography-ion mobility spectrometry，GC-IMS）技术分析其自身代谢过程中产生的微生物挥发性有机化合物（microbial volatile organic compounds，mVOCs），结合统计分析，筛选出具有表征霉变信息的mVOCs物质，并结合化学计量学方法建立霉变香米的判别模型。结果表明：6种霉菌产生的mVOCs物质主要为醇类、醛类、酮类以及酯类等；霉菌侵染的香米样品与正常样品在主成分得分图中呈现2个簇类聚集，k近邻判别模型显示测试集样品平均识别率达到95.25%，从而证实mVOCs具有表征香米霉变能力的可靠性，GC-IMS结合化学计量学方法对香米霉变无损判别有效分析的可行性，在大米品质分析与贮藏监控等领域具有广泛的应用价值。
Abstract:In order to perform a rapid，simple and accurate discriminant analysis of moldy fragrant rice，six main molds isolated from naturally moldy fragrant rice were studied.The microbial volatile organic compounds（mVOCs）produced by their own metabolism were analyzed by gas chromatography-ion mobility spectrometry（GC-IMS）.Combined with statistical analysis，mVOCs with mildew information were selected，and the discrimination model of moldy fragrant rice was established using chemometrics.The results showed that the main mVOCs produced by six molds were mainly alcohols，aldehydes，ketones and esters；the fragrant rice samples infected by moldy and normal fragrant rice samples were divided into two clusters in the principal component score diagram；the k nearest neighbor discriminant model showed that the average recognition rate of the test sample set was 95.25%.Therefore，it was proved that mVOCs had the reliability of characterizing mildew ability of rice，and GC-IMS combined with chemometrics was feasible for nondestructive discriminant and effective analysis of mildew of rice，which had a wide application value in rice quality analysis and storage monitoring.
keywords: gas chromatography-ion mobility spectrometry （GC-IMS） moldy fragrant rice microbial volatile organic components（mVOCs） k nearest neighbor（kNN） fingerprint
文章编号：202304027 中图分类号： 文献标志码：
基金项目:国家自然科学基金项目（32202150）；广西自然科学基金项目（2021GXNSFBA075019、2022GXNSFAA035256）；广西高校中青年教师科研基础能力提升项目（2021KY0352）；江苏农牧科技职业学院校级科研项目（NSF2021ZR07）
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