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     Advance Journal of Food Science and Technology


Correlations between Aroma Profiles and Sensory Characteristics of Red Wines by Using Partial Least Squares Regression Method

1Kelin Xie, 1Tao Feng, 1Wenhua Lin, 2Haining Zhuang, 3Zhimin Xu and 1Fanglin Bing
1School of Perfume and Aroma Technology, Shanghai Institute of Technology, No. 100 Hai Quan Road, Shanghai 201418
2Institute of Edible Fungi, Shanghai Academy of Agricultural Sciences; National Engineering Research Center of Edible Fungi, Shanghai 201403, China
3School of Nutrition and Food Sciences, Louisiana State University Agricultural Center, Baton Rouge, USA
Advance Journal of Food Science and Technology  2016  5:271-280
http://dx.doi.org/10.19026/ajfst.12.2910  |  © The Author(s) 2016
Received: November ‎3, ‎2015  |  Accepted: January ‎8, ‎2016  |  Published: October 05, 2016

Abstract

The aim of this study is to examine the effectiveness of Partial Least Squares Regression (PLSR) method in determing correlations between the aroma profiles and sensory characteristics of wines. A total of 45 volatile compounds in five different Chinese grape wines were identified and quantified by HS-SPME/GC-MS and 26 of them with OAV (odour activity value) >1. All aroma compounds with OAV>1 were selected for evaluating the correlations between the aroma profiles and 12 sensory descriptors using PLSR and their ROC (Relative Odour Contribution). The results showed that ethyl decanoate, ethyl hexanoate, acetaldehyde, isoamyl acetate, hexanoic acid, 4-vinylguaiacol and geraniol were the major contributors to the desirable balanced aroma of muscat wine. Ethyl hexanoate, ethyl butyrate, isoamyl acetate, acetaldehyde, hexanoic acid, 3-methyl-1-butanol and octanoic acid were mainly responsible for the aroma of black beet wine and cabernet gernischt wine whereas ethyl tetradecanoate, neryl acetate and nerol were the particular aroma compounds in black beet wine and γ-butyrolactone, nerolidol and β-ionone were special aroma compounds in cabernet gernischt wine. Both PLSR and ROC are effective methods to demonstrate the correlations between the sensory characteristics of the analyzed wines and their aroma compositions.

Keywords:

Chinese grape wines, HS-SPME/GC-MS, odour activity value, partial least squares regression, relative odour contribution, sensory descriptors,


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Competing interests

The authors have no competing interests.

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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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The authors have no competing interests.

ISSN (Online):  2042-4876
ISSN (Print):   2042-4868
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