Wine Metabolomics

Objective Measures of Sensory Properties of Semillon from GC-MS Profiles

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26 Citations (Scopus)

Abstract

The contribution of volatile aroma compounds to the overall composition and sensory perception of wine is well recognized. The classical targeted measurement of volatile compounds in wine using GC-MS is laborious and only a limited number of compounds can be quantified at any time. Application of an automated multivariate curve resolution technique to nontargeted GC-MS analysis of wine makes it possible to detect several hundred compounds within a single analytical run. Hunter Valley Semillon (HVS) is recognized as a world class wine with a range of styles. Subtle characters reliant upon the development of bottle maturation characteristics are a feature of highly esteemed HVS. In this investigation a metabolomic approach to wine analysis, using multivariate curve resolution techniques applied to GC-MS profiles coupled with full descriptive sensory analysis, was used to determine the objective composition of various styles of HVS. Over 250 GC-MS peaks were extracted from the wine profiles. Sensory scores were analyzed using PARAFAC prior to development of predictive models of sensory features from the extracted GC-MS peak table using PLS regression. Good predictive models of the sensorial attributes honey, toast, orange marmalade, and sweetness, the defining traits for HVS, could be determined from the extracted peak tables. Compound identification for these rated attributes indicated the importance of a range of ethyl esters, aliphatic alcohols and acids, ketones, aldehydes, furanic derivatives, and norisoprenoids in the development of HVS and styles. The development of automated metabolomic data analysis of GC-MS profiles of wines will assist in the development of wine styles for specific consumer segments and enhance understanding of production processes on the ultimate sensory profiles of the product.
Original languageEnglish
Pages (from-to)11957-11967
Number of pages11
JournalJournal of Agricultural and Food Chemistry
Volume61
DOIs
Publication statusPublished - Nov 2013

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Metabolomics
Wine
metabolomics
wines
sensory properties
valleys
marmalades
Norisoprenoids
norisoprenoids
Honey
sweetness
Bottles
ketones
Ketones
Chemical analysis
bottles
odor compounds
Aldehydes
honey
volatile compounds

Cite this

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title = "Wine Metabolomics: Objective Measures of Sensory Properties of Semillon from GC-MS Profiles",
abstract = "The contribution of volatile aroma compounds to the overall composition and sensory perception of wine is well recognized. The classical targeted measurement of volatile compounds in wine using GC-MS is laborious and only a limited number of compounds can be quantified at any time. Application of an automated multivariate curve resolution technique to nontargeted GC-MS analysis of wine makes it possible to detect several hundred compounds within a single analytical run. Hunter Valley Semillon (HVS) is recognized as a world class wine with a range of styles. Subtle characters reliant upon the development of bottle maturation characteristics are a feature of highly esteemed HVS. In this investigation a metabolomic approach to wine analysis, using multivariate curve resolution techniques applied to GC-MS profiles coupled with full descriptive sensory analysis, was used to determine the objective composition of various styles of HVS. Over 250 GC-MS peaks were extracted from the wine profiles. Sensory scores were analyzed using PARAFAC prior to development of predictive models of sensory features from the extracted GC-MS peak table using PLS regression. Good predictive models of the sensorial attributes honey, toast, orange marmalade, and sweetness, the defining traits for HVS, could be determined from the extracted peak tables. Compound identification for these rated attributes indicated the importance of a range of ethyl esters, aliphatic alcohols and acids, ketones, aldehydes, furanic derivatives, and norisoprenoids in the development of HVS and styles. The development of automated metabolomic data analysis of GC-MS profiles of wines will assist in the development of wine styles for specific consumer segments and enhance understanding of production processes on the ultimate sensory profiles of the product.",
keywords = "Multivariate curve resolution alternative least-squares (MCR-ALS), Parallel factor analysis (PARAFAC), Partial least-squares (PLS), Semillon wine, Sensory, Volatile compounds",
author = "Leigh Schmidtke and John Blackman and Andrew Clark and Paris Grant-Preece",
note = "Imported on 12 Apr 2017 - DigiTool details were: month (773h) = November, 2013; Journal title (773t) = Journal of Agricultural and Food Chemistry. ISSNs: 0021-8561;",
year = "2013",
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doi = "10.1021/jf403504p",
language = "English",
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pages = "11957--11967",
journal = "Journal of Agricultural and Food Chemistry",
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publisher = "American Chemical Society",

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AU - Schmidtke, Leigh

AU - Blackman, John

AU - Clark, Andrew

AU - Grant-Preece, Paris

N1 - Imported on 12 Apr 2017 - DigiTool details were: month (773h) = November, 2013; Journal title (773t) = Journal of Agricultural and Food Chemistry. ISSNs: 0021-8561;

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Y1 - 2013/11

N2 - The contribution of volatile aroma compounds to the overall composition and sensory perception of wine is well recognized. The classical targeted measurement of volatile compounds in wine using GC-MS is laborious and only a limited number of compounds can be quantified at any time. Application of an automated multivariate curve resolution technique to nontargeted GC-MS analysis of wine makes it possible to detect several hundred compounds within a single analytical run. Hunter Valley Semillon (HVS) is recognized as a world class wine with a range of styles. Subtle characters reliant upon the development of bottle maturation characteristics are a feature of highly esteemed HVS. In this investigation a metabolomic approach to wine analysis, using multivariate curve resolution techniques applied to GC-MS profiles coupled with full descriptive sensory analysis, was used to determine the objective composition of various styles of HVS. Over 250 GC-MS peaks were extracted from the wine profiles. Sensory scores were analyzed using PARAFAC prior to development of predictive models of sensory features from the extracted GC-MS peak table using PLS regression. Good predictive models of the sensorial attributes honey, toast, orange marmalade, and sweetness, the defining traits for HVS, could be determined from the extracted peak tables. Compound identification for these rated attributes indicated the importance of a range of ethyl esters, aliphatic alcohols and acids, ketones, aldehydes, furanic derivatives, and norisoprenoids in the development of HVS and styles. The development of automated metabolomic data analysis of GC-MS profiles of wines will assist in the development of wine styles for specific consumer segments and enhance understanding of production processes on the ultimate sensory profiles of the product.

AB - The contribution of volatile aroma compounds to the overall composition and sensory perception of wine is well recognized. The classical targeted measurement of volatile compounds in wine using GC-MS is laborious and only a limited number of compounds can be quantified at any time. Application of an automated multivariate curve resolution technique to nontargeted GC-MS analysis of wine makes it possible to detect several hundred compounds within a single analytical run. Hunter Valley Semillon (HVS) is recognized as a world class wine with a range of styles. Subtle characters reliant upon the development of bottle maturation characteristics are a feature of highly esteemed HVS. In this investigation a metabolomic approach to wine analysis, using multivariate curve resolution techniques applied to GC-MS profiles coupled with full descriptive sensory analysis, was used to determine the objective composition of various styles of HVS. Over 250 GC-MS peaks were extracted from the wine profiles. Sensory scores were analyzed using PARAFAC prior to development of predictive models of sensory features from the extracted GC-MS peak table using PLS regression. Good predictive models of the sensorial attributes honey, toast, orange marmalade, and sweetness, the defining traits for HVS, could be determined from the extracted peak tables. Compound identification for these rated attributes indicated the importance of a range of ethyl esters, aliphatic alcohols and acids, ketones, aldehydes, furanic derivatives, and norisoprenoids in the development of HVS and styles. The development of automated metabolomic data analysis of GC-MS profiles of wines will assist in the development of wine styles for specific consumer segments and enhance understanding of production processes on the ultimate sensory profiles of the product.

KW - Multivariate curve resolution alternative least-squares (MCR-ALS)

KW - Parallel factor analysis (PARAFAC)

KW - Partial least-squares (PLS)

KW - Semillon wine

KW - Sensory

KW - Volatile compounds

U2 - 10.1021/jf403504p

DO - 10.1021/jf403504p

M3 - Article

VL - 61

SP - 11957

EP - 11967

JO - Journal of Agricultural and Food Chemistry

JF - Journal of Agricultural and Food Chemistry

SN - 0021-8561

ER -