食品与发酵工业 >

2022 , Vol. 48 >Issue 13: 268 - 276

DOI: https://doi.org/10.13995/j.cnki.11-1802/ts.029667

分析与检测

基于GC-MS结合化学计量学方法鉴定四川郫县豆瓣酱

  • 张蕾蕾 ,
  • 吴剑荣 ,
  • 张洪涛 ,
  • 高敏杰 ,
  • 詹晓北
展开
  • (江南大学 生物工程学院,江苏 无锡,214122)
第一作者：硕士研究生(吴剑荣副教授为通信作者,E-mail:kinwu@jiangnan.edu.cn)

收稿日期: 2021-10-11

  修回日期: 2021-12-06

  网络出版日期: 2022-08-03

基金资助

国家重点研发计划项目(2018YFC1604105-5)

收起

Discrimination of broad bean paste from Pixian Sichuan and other origins using GC-MS combined with chemometrics

  • ZHANG Leilei ,
  • WU Jianrong ,
  • ZHANG Hongtao ,
  • GAO Minjie ,
  • ZHAN Xiaobei
Expand
  • (School of Biotechnology, Jiangnan University, Wuxi 214122, China)

Received date: 2021-10-11

  Revised date: 2021-12-06

  Online published: 2022-08-03

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摘要

四川郫县豆瓣酱是我国著名的地理标志产品,溯源与鉴别检测技术对保证其产地和品质真实性具有重要意义。为构建郫县豆瓣酱产地辨析模型,以不同产地豆瓣酱为研究对象,初步探讨了挥发性物质指纹分析对郫县豆瓣酱产地溯源的可行性。采用顶空固相微萃取结合气相色谱-质谱联用仪在105份不同产地来源的豆瓣酱样品中检测出87种挥发性物质,应用化学计量学工具对数据进行筛选和分析,成功构建基于挥发性物质的产地鉴别模型。采用正交-偏最小二乘法判别分析确定45种变量权重系数大于1的物质,再通过Fisher判别分析进一步确定15种挥发性物质为豆瓣酱的有效溯源指标,Fisher判别模型的整体正确判别率为95.9%,对验证集样本均实现正确的分类。GC-MS技术结合化学计量学方法不仅能准确鉴定豆瓣酱的关键香气组分,而且可应用于豆瓣酱的产地区分。

关键词： 郫县豆瓣酱; 挥发性成分; Fisher判别分析; 正交-偏最小二乘判别分析; 气相色谱-质谱法(GC-MS)

本文引用格式

张蕾蕾 , 吴剑荣 , 张洪涛 , 高敏杰 , 詹晓北 . 基于GC-MS结合化学计量学方法鉴定四川郫县豆瓣酱[J]. 食品与发酵工业, 2022 , 48(13) : 268 -276 . DOI: 10.13995/j.cnki.11-1802/ts.029667

Abstract

The traceability and identification is very important for the protection of geographical origin and authenticity of Pixian broad bean paste, which is a famous geographical indication product in China.In order to establish the origin discrimination model of Pixian broad bean paste, the feasibility of tracing the origin of Pixian broad bean paste by analyzing its volatile compounds was investigated. Eighty-seven volatile compounds were detected in 105 bean sauce samples from different manufacturing origins by headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). Using chemometrics software to filter and analyze the data, the identification model based on volatile compounds was successfully constructed. Orthogonal partial least squares discriminant analysis (OPLS-DA) revealed 45 compounds with variable importance for the projection greater than 1. Using Fisher discriminant analysis, 15 volatile compounds were further identified as effective traceability indexes. The overall correct discriminant rates of Fisher discriminating models were 95.9%, and all the samples in the validation set were correctly classified. GC-MS combined with chemometric methods could not only accurately identify the key volatile compound of broad bean paste, but also have certain ability to identify the origin of broad bean paste.

Key words： Pixian broad-bean paste; volatile compounds; Fisher discriminant analysis; orthogonal partial least squares discriminant analysis; GC-MS

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