Characterization and classification of the aroma of beer samples by means of an MS e-nose and chemometric tools

被引:57
|
作者
Vera, L. [1 ]
Acena, L. [1 ]
Guasch, J. [1 ]
Boque, R. [2 ]
Mestres, M. [1 ]
Busto, O. [1 ]
机构
[1] Univ Rovira & Virgili, Fac Enol Tarragona, Dept Analyt Chem & Organ Chem, Analyt Chem Wine & Food Res Grp, Tarragona 43007, Spain
[2] Univ Rovira & Virgili, Fac Enol Tarragona, Dept Analyt Chem & Organ Chem, Chemometr Qualimetr & Nanosensors Res Grp, Tarragona 43007, Spain
关键词
MS e-nose; Beer; Volatile compounds; Classification; Characterization; LDA; SOLID-PHASE MICROEXTRACTION; HEADSPACE-MASS-SPECTROMETRY; ELECTRONIC NOSE; WINE DISCRIMINATION; GAS-CHROMATOGRAPHY; SENSORS; ARRAY;
D O I
10.1007/s00216-010-4343-y
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
An electronic nose based on coupling of headspace (HS) with a mass spectrometer (MS) has been used in this study to classify and characterize a series of beers according to their production site and chemical composition. With this objective, we analyzed 67 beers of the same brand and preparation process but produced in different factories. The samples were also subjected to sensory evaluation by a panel of experts. Linear discriminant analysis (LDA) was used as the classification technique and stepwise LDA based on Wilk's lambda criterion was used to select the most discriminating variables. To interpret the aroma characteristics of the beers from the m/z ions obtained, score and loading bi-plots were obtained by applying canonical variables. Because the beers analyzed were marketed with the same name and brand, we expected to be working with the same product irrespective of its origin. However, results from both sensory evaluation and use of the e-nose revealed differences between factories. With the e-nose it was possible to relate these differences to the presence (and abundance) of characteristic ions of different compounds typically found in beer. These results demonstrate that the HS-MS e-nose is not only an aroma sensor capable to classify and/or differentiate samples but it can also provide information about the compounds responsible for this differentiation.
引用
收藏
页码:2073 / 2081
页数:9
相关论文
共 50 条
  • [21] Aroma Components Analysis and Origin Differentiation of Black Tea Based on ATD-GC-MS and E-Nose
    Huang, Jianfeng
    Yan, Tingyu
    Yang, Jiangfan
    Xu, Hui
    HORTICULTURAE, 2023, 9 (08)
  • [22] A Portable E-nose System for Classification of Chinese Liquor
    Qi, Pei-Feng
    Meng, Qing-Hao
    Zhou, Yu
    Jing, Ya-Qi
    Zeng, Ming
    2015 IEEE SENSORS, 2015, : 335 - 338
  • [23] Analysis of volatile bread aroma for evaluation of bread freshness using an electronic nose (E-nose)
    Botre, B.
    Gharpure, D.
    MATERIALS AND MANUFACTURING PROCESSES, 2006, 21 (03) : 279 - 283
  • [24] A Model of Classification for E-Nose Based on Genetic Algorithm
    Jiang Min-jun
    Liu Yunxiang
    Yang Jingxin
    Yu Wanjun
    SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS II, PTS 1 AND 2, 2014, 475-476 : 952 - 955
  • [25] Seafood freshness: e-nose data for classification purposes
    Grassi, Silvia
    Benedetti, Simona
    Magnani, Luca
    Pianezzola, Alberto
    Buratti, Susanna
    FOOD CONTROL, 2022, 138
  • [26] Classification and pattern recognition algorithms applied to E-Nose
    Rahman, Md. Mizanur
    Charoenlarpnopparut, Chalie
    Suksompong, Prapun
    2015 2ND INTERNATIONAL CONFERENCE ON ELECTRICAL INFORMATION AND COMMUNICATION TECHNOLOGY (EICT), 2015, : 44 - 48
  • [27] Aroma analysis of Fuyun 6 and Jinguanyin black tea in the Fu'an area based on E-nose and GC-MS
    Yan, Tingyu
    Lin, Jiexin
    Zhu, Jianxin
    Ye, Naixing
    Huang, Jianfeng
    Wang, Pengjie
    Jin, Shan
    Zheng, Deyong
    Yang, Jiangfan
    EUROPEAN FOOD RESEARCH AND TECHNOLOGY, 2022, 248 (04) : 947 - 961
  • [28] Quaternion Domain k-Means Clustering for Improved Real Time Classification of E-Nose Data
    Kumar, Ravi
    Dwivedi, Ramashraya
    IEEE SENSORS JOURNAL, 2016, 16 (01) : 177 - 184
  • [29] Detection Potential of Multi-Features Representation of E-Nose Data in Classification of Moldy Maize Samples
    Yong Yin
    Yinfeng Hao
    Huichun Yu
    Yunhong Liu
    Fengxia Hao
    Food and Bioprocess Technology, 2017, 10 : 2226 - 2239
  • [30] Wastewater monitoring by means of e-nose, VE-tongue, TD-GC-MS, and SPME-GC-MS
    Moufid, Mohammed
    Hofmann, Michael
    El Bari, Nezha
    Tiebe, Carlo
    Bartholmai, Matthias
    Bouchikhi, Benachir
    TALANTA, 2021, 221