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Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines

Understanding the sensory attributes that explain the typicity of Australian Cabernet Sauvignon wines is essential for increasing value and growth of Australia’s reputation as a fine wine producer. Content analysis of 2598 web-based wine reviews from well-known wine writers, including tasting notes...

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Autores principales: Souza Gonzaga, Lira, Capone, Dimitra L., Bastian, Susan E.P., Danner, Lukas, Jeffery, David W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6963444/
https://www.ncbi.nlm.nih.gov/pubmed/31861236
http://dx.doi.org/10.3390/foods8120691
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author Souza Gonzaga, Lira
Capone, Dimitra L.
Bastian, Susan E.P.
Danner, Lukas
Jeffery, David W.
author_facet Souza Gonzaga, Lira
Capone, Dimitra L.
Bastian, Susan E.P.
Danner, Lukas
Jeffery, David W.
author_sort Souza Gonzaga, Lira
collection PubMed
description Understanding the sensory attributes that explain the typicity of Australian Cabernet Sauvignon wines is essential for increasing value and growth of Australia’s reputation as a fine wine producer. Content analysis of 2598 web-based wine reviews from well-known wine writers, including tasting notes and scores, was used to gather information about the regional profiles of Australian Cabernet Sauvignon wines and to create selection criteria for further wine studies. In addition, a wine expert panel evaluated 84 commercial Cabernet Sauvignon wines from Coonawarra, Margaret River, Yarra Valley and Bordeaux, using freely chosen descriptions and overall quality scores. Using content analysis software, a sensory lexicon of descriptor categories was built and frequencies of each category for each region were computed. Distinction between the sensory profiles of the regions was achieved by correspondence analysis (CA) using online review and expert panellist data. Wine quality scores obtained from reviews and experts were converted into Australian wine show medal categories. CA of assigned medal and descriptor frequencies revealed the sensory attributes that appeared to drive medal-winning wines. Multiple factor analysis of frequencies from the reviews and expert panellists indicated agreement about descriptors that were associated with wines of low and high quality, with greater alignment at the lower end of the wine quality assessment scale.
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spelling pubmed-69634442020-02-26 Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines Souza Gonzaga, Lira Capone, Dimitra L. Bastian, Susan E.P. Danner, Lukas Jeffery, David W. Foods Article Understanding the sensory attributes that explain the typicity of Australian Cabernet Sauvignon wines is essential for increasing value and growth of Australia’s reputation as a fine wine producer. Content analysis of 2598 web-based wine reviews from well-known wine writers, including tasting notes and scores, was used to gather information about the regional profiles of Australian Cabernet Sauvignon wines and to create selection criteria for further wine studies. In addition, a wine expert panel evaluated 84 commercial Cabernet Sauvignon wines from Coonawarra, Margaret River, Yarra Valley and Bordeaux, using freely chosen descriptions and overall quality scores. Using content analysis software, a sensory lexicon of descriptor categories was built and frequencies of each category for each region were computed. Distinction between the sensory profiles of the regions was achieved by correspondence analysis (CA) using online review and expert panellist data. Wine quality scores obtained from reviews and experts were converted into Australian wine show medal categories. CA of assigned medal and descriptor frequencies revealed the sensory attributes that appeared to drive medal-winning wines. Multiple factor analysis of frequencies from the reviews and expert panellists indicated agreement about descriptors that were associated with wines of low and high quality, with greater alignment at the lower end of the wine quality assessment scale. MDPI 2019-12-17 /pmc/articles/PMC6963444/ /pubmed/31861236 http://dx.doi.org/10.3390/foods8120691 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Souza Gonzaga, Lira
Capone, Dimitra L.
Bastian, Susan E.P.
Danner, Lukas
Jeffery, David W.
Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines
title Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines
title_full Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines
title_fullStr Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines
title_full_unstemmed Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines
title_short Using Content Analysis to Characterise the Sensory Typicity and Quality Judgements of Australian Cabernet Sauvignon Wines
title_sort using content analysis to characterise the sensory typicity and quality judgements of australian cabernet sauvignon wines
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6963444/
https://www.ncbi.nlm.nih.gov/pubmed/31861236
http://dx.doi.org/10.3390/foods8120691
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