Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractCharacterization of key odor-active compounds in Chinese Dornfelder wine and its regional variations by application of molecular sensory science approaches    Next AbstractFlavor Profile Evolution of Bottle Aged Rose and White Wines Sealed with Different Closures »

Food Res Int


Title:An efficient methodology for modeling to predict wine aroma expression based on quantitative data of volatile compounds: A case study of oak barrel-aged red wines
Author(s):Ling M; Bai X; Cui D; Shi Y; Duan C; Lan Y;
Address:"Center for Viticulture & Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; Key Laboratory of Viticulture and Enology, Ministry of Agriculture and Rural Affairs, Beijing 100083, China. Center for Viticulture & Enology, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; Key Laboratory of Viticulture and Enology, Ministry of Agriculture and Rural Affairs, Beijing 100083, China. Electronic address: lanyibin@cau.edu.cn"
Journal Title:Food Res Int
Year:2023
Volume:20221231
Issue:
Page Number:112440 -
DOI: 10.1016/j.foodres.2022.112440
ISSN/ISBN:1873-7145 (Electronic) 0963-9969 (Linking)
Abstract:"Correlating aroma expression with volatile compounds has long been an ambition in researches of flavor chemistry. To propose a reliable methodology to depict wine aroma, 76 oak barrel-aged dry red wines were investigated through the combination of machine learning algorithm and multivariate analysis. Aromatic characteristic was evaluated by quantitative descriptive analysis (QDA), while non- or oak derived volatiles were detected by HS-SPME-GC-MS and targeted SPE-GC-QqQ-MS/MS, respectively. Results showed that variable importance for projection values (VIPs) from partial least-squares regression (PLSR) and mean decrease accuracy (MDA) from random forest were efficient parameters for feature selection. The correlating accuracy of the optimal PLSR model to predict intensities of different aroma characteristics through selected volatile compounds could achieve 0.754 to 0.943, representing potential application to manage wine aroma by chemical assay in winemaking. From the perspective of mathematical modeling in the real wine matrix, the network analysis between aroma characteristics and key volatile compounds indicated that the expression of oak aroma was not only directly contributed by volatiles derived from oak wood, but also influenced by ethyl esters, including ethyl acetate, ethyl butanoate, ethyl hexanoate, ethyl decanoate, and ethyl nonanoate"
Keywords:*Wine/analysis *Quercus/chemistry Tandem Mass Spectrometry *Volatile Organic Compounds/analysis Aroma Network Oak barrel aging Oak-derived volatiles Plsr Random forest;
Notes:"MedlineLing, Mengqi Bai, Xiaoxuan Cui, Dongsheng Shi, Ying Duan, Changqing Lan, Yibin eng Research Support, Non-U.S. Gov't Canada 2023/02/05 Food Res Int. 2023 Feb; 164:112440. doi: 10.1016/j.foodres.2022.112440. Epub 2022 Dec 31"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 03-07-2024