Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines
The aim of the study was to propose a methodology for the elucidation of sensory and chemical wine quality drivers. The winners of the 2018 Top 10 Chenin Blanc and Top 10 Pinotage challenges and additional lower scoring wines for each cultivar were evaluated. The two sets underwent sensory profiling...
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doaj-158c397bb33f441e80701e1e919b101c2020-11-25T03:08:05ZengMDPI AGFoods2304-81582020-06-01980580510.3390/foods9060805Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage WinesJeanne Brand0Valeria Panzeri1Astrid Buica2South African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, Stellenbosch 7600, South AfricaSouth African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, Stellenbosch 7600, South AfricaSouth African Grape and Wine Research Institute, Department of Viticulture and Oenology, Stellenbosch University, Stellenbosch 7600, South AfricaThe aim of the study was to propose a methodology for the elucidation of sensory and chemical wine quality drivers. The winners of the 2018 Top 10 Chenin Blanc and Top 10 Pinotage challenges and additional lower scoring wines for each cultivar were evaluated. The two sets underwent sensory profiling by Check-All-That-Apply (CATA) and a 20-point quality rating by industry experts in non-competition conditions and chemical fingerprinting by Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS). Data were submitted to Correspondence Analysis (CA) and Principal Component Analysis (PCA) for sensory and chemistry, respectively, from which the standardised deviates were correlated to quality scores to identify the quality drivers. The results illustrated the possibility to determine positive and negative sensory quality drivers (attributes), while the identification of drivers for chemistry (ions) was challenging due to the number of signals generated by the fingerprinting technique. The configurations of the sensory and chemical spaces were compared, but the similarities were relatively low as measured by Regression Vector (RV) coefficients, 0.437 and 0.505 for Pinotage and Chenin Blanc, respectively. The proposed methodology can also be used to explore the sensory space of wine sample sets with the added dimension of the quality drivers which, in turn, highlight the experts’ opinions on what makes a winning wine.https://www.mdpi.com/2304-8158/9/6/805quality driverswine qualityPinotageChenin Blancsensory evaluationchemical fingerprint |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Jeanne Brand Valeria Panzeri Astrid Buica |
spellingShingle |
Jeanne Brand Valeria Panzeri Astrid Buica Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines Foods quality drivers wine quality Pinotage Chenin Blanc sensory evaluation chemical fingerprint |
author_facet |
Jeanne Brand Valeria Panzeri Astrid Buica |
author_sort |
Jeanne Brand |
title |
Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines |
title_short |
Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines |
title_full |
Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines |
title_fullStr |
Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines |
title_full_unstemmed |
Wine Quality Drivers: A Case Study on South African Chenin Blanc and Pinotage Wines |
title_sort |
wine quality drivers: a case study on south african chenin blanc and pinotage wines |
publisher |
MDPI AG |
series |
Foods |
issn |
2304-8158 |
publishDate |
2020-06-01 |
description |
The aim of the study was to propose a methodology for the elucidation of sensory and chemical wine quality drivers. The winners of the 2018 Top 10 Chenin Blanc and Top 10 Pinotage challenges and additional lower scoring wines for each cultivar were evaluated. The two sets underwent sensory profiling by Check-All-That-Apply (CATA) and a 20-point quality rating by industry experts in non-competition conditions and chemical fingerprinting by Liquid Chromatography-High Resolution Mass Spectrometry (LC-HRMS). Data were submitted to Correspondence Analysis (CA) and Principal Component Analysis (PCA) for sensory and chemistry, respectively, from which the standardised deviates were correlated to quality scores to identify the quality drivers. The results illustrated the possibility to determine positive and negative sensory quality drivers (attributes), while the identification of drivers for chemistry (ions) was challenging due to the number of signals generated by the fingerprinting technique. The configurations of the sensory and chemical spaces were compared, but the similarities were relatively low as measured by Regression Vector (RV) coefficients, 0.437 and 0.505 for Pinotage and Chenin Blanc, respectively. The proposed methodology can also be used to explore the sensory space of wine sample sets with the added dimension of the quality drivers which, in turn, highlight the experts’ opinions on what makes a winning wine. |
topic |
quality drivers wine quality Pinotage Chenin Blanc sensory evaluation chemical fingerprint |
url |
https://www.mdpi.com/2304-8158/9/6/805 |
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AT jeannebrand winequalitydriversacasestudyonsouthafricancheninblancandpinotagewines AT valeriapanzeri winequalitydriversacasestudyonsouthafricancheninblancandpinotagewines AT astridbuica winequalitydriversacasestudyonsouthafricancheninblancandpinotagewines |
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