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

Zhimin Xu,Fanglin Bing,Haining Zhuang,Tao Feng,Kelin Xie,Wenhua Lin

doi:10.19026/ajfst.12.2910

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.

Highlights

The aroma of wine is one of the most important factors contributing to its quality
The purpose of this study was to find the aroma compounds in five different Chinese grape wines and determine the relationship between the aroma profiles and sensory characteristics of these wines using Partial Least Squares Regression (PLSR) method
Odour Activity Value (OAV) of each detected volatile compound was calculated and found 26 kinds of the aroma compounds whose OAV > 1 in part of the samples. All these aroma compounds with OAV > 1 were selected for evaluating the correlations between the aroma profiles and sensory characteristics of the wines using PLSR and their Relative Odour Contribution (ROC)

Summary

Introduction

The aroma of wine is one of the most important factors contributing to its quality. The formation of wine aroma is mainly influenced by the grape variety, vine growing conditions and fermentation technology. Only part of the volatile compounds make a contribution to wine aroma. Many researchers have proved that only those odorants with an Odour Activity Value (OVA) above 1 can contribute to the entire aroma of the wine (Allen et al, 1994). Odour Activity Value (OAV) and Relative Odour Contribution (ROC) are two conventional indicators for evaluation of contribution of volatile compounds to wine aroma (Wang et al, 2015). The OAV is calculated through dividing the concentration of an aroma compound by its odour threshold (Gómez-Míguez et al, 2007; Gil et al, 2006). ROC is defined as the ratio of the OAV percentage of each compound and the sum of the OAV of compounds which OAV>1 (Welke et al, 2014)

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