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

Gonzaga, Lira Souza; Capone, Dimitra L.; Bastian, Susan E.P.; Danner, Lukas; Jeffery, David W.

doi:10.3390/foods8120691

Cited by 18 publications

(12 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Some samples in Cluster 2 indicated that 'minty' flavour was an important characteristic, although in general not much difference was seen between the samples (Figure 1A). A 'minty' character has been reported previously for Coonawarra Cabernet-Sauvignon wines, which might indicate this as a dominant trait for the Coonawarra region (Robinson et al, 2011;Souza Gonzaga et al, 2019;Souza Gonzaga et al, 2020). Characters described as 'minty' and 'eucalyptus' in Cabernet-Sauvignon wines have been associated with the presence of eucalyptol (i.e., 1,8-cineole) and hydroxycitronellol, and although 'eucalyptus' aroma and flavour were not statistically significant (α = 0.1) in the present work (Supplementary data, Table S3), studies have shown that they might be interchangeable and indistinguishable by a sensory panel (Capone et al, 2012;Robinson et al, 2011;Souza Gonzaga et al, 2020).…”

Section: Rata Sensory Profiling and Clustering Of Winesmentioning

confidence: 56%

“…Cluster 5 was especially related to 'cherry cola' and 'vanilla/chocolate' flavours (Figure 1B), as opposed to the savoury profile found for Cluster 1 (Figure 1A). Sensory profiles have similarly been used in the past for regional classification of Australian Cabernet-Sauvignon wines (Souza Gonzaga et al, 2019;Souza Gonzaga et al, 2020) and Australian Shiraz and Chardonnay wines (Kustos et al, 2020). Those studies with commercial wines reported that some distinctive sensory traits can be more important and more associated with a specific wine-producing region, with the current work on unreleased wines also indicating the existence of perceived differences within a GI according to Figure 1.…”

Section: Rata Sensory Profiling and Clustering Of Winesmentioning

confidence: 99%

See 1 more Smart Citation

Modelling Cabernet-Sauvignon wine sensory traits from spectrofluorometric data

et al. 2021

Self Cite

View full text Add to dashboard Cite

Understanding how wine compositional traits can be related to sensory profiles is an important and ongoing challenge. Enhancing knowledge in this area could assist producers to select practices that deliver wines of the desired style and sensory specifications. This work reports the use of spectrofluorometry in conjunction with chemometrics for prediction, correlation, and classification based on sensory descriptors obtained using a rate-all-that-apply sensory assessment of Cabernet-Sauvignon wines (n = 26). Sensory results were first subjected to agglomerative hierarchical cluster analysis, which separated the wines into five clusters represented by different sensory profiles. The clusters were modelled in conjunction with excitation-emission matrix (EEM) data from fluorescence measurements using extreme gradient boosting discriminant analysis. This machine learning technique was able to classify the wines into the pre-defined sensory clusters with 100 % accuracy. Parallel factor analysis of the EEMs identified four main fluorophore components that were tentatively assigned as catechins, phenolic aldehydes, anthocyanins, and resveratrol (C1, C2, C3, and C4, respectively). Association of these four components with different sensory descriptors was possible through multiple factor analysis, with C1 relating to ‘dark fruits’ and ‘savoury’, C2 with ‘barnyard’, C3 with ‘cooked vegetables’ and ‘vanilla/chocolate’, and C4 with ‘barnyard’ and a lack of C1 descriptors. Partial least squares regression modelling was undertaken with EEM data and sensory results, with a model for perceived astringency being able to predict the panel scores with 68.1 % accuracy. These encouraging outcomes pave the way for further studies that relate sensory traits to fluorescence data and move research closer to the ultimate goal of predicting wine sensory expression from a small number of compositional factors.

show abstract

Section: Rata Sensory Profiling and Clustering Of Winesmentioning

confidence: 56%

Section: Rata Sensory Profiling and Clustering Of Winesmentioning

confidence: 99%

Modelling Cabernet-Sauvignon wine sensory traits from spectrofluorometric data

et al. 2021

Self Cite

View full text Add to dashboard Cite

show abstract

“…In this case, descriptions provided by the expert panel were analysed through a text mining tool so that sensory characteristics could be assessed (Souza Gonzaga et al 2019). These results were compared with a large collection of webbased wine reviews by well-known wine writers, also analysed with the text mining methodology, thereby revealing some agreement between the two cohorts for the sensory attributes that were considered important for the evaluated GIs (Souza Gonzaga et al 2019). Leriche et al (2020) have recently proposed a methodology to assess the sensory typicity of wines coming from a region controlled by PDO regulation.…”

Section: Approaches To Measure Wine Sensory Typicitymentioning

confidence: 99%

Section: Approaches To Measure Wine Sensory Typicitymentioning

confidence: 99%

“…In another study utilising the expertise of industry professionals, Souza Gonzaga et al (2019) used a free vocabulary description approach with the aim of elucidating the sensory typicity of Australian Cabernet Sauvignon wines. In this case, descriptions provided by the expert panel were analysed through a text mining tool so that sensory characteristics could be assessed (Souza Gonzaga et al 2019). These results were compared with a large collection of web‐based wine reviews by well‐known wine writers, also analysed with the text mining methodology, thereby revealing some agreement between the two cohorts for the sensory attributes that were considered important for the evaluated GIs (Souza Gonzaga et al 2019).…”

Section: Approaches To Measure Wine Sensory Typicitymentioning

confidence: 99%

See 1 more Smart Citation

Defining wine typicity: sensory characterisation and consumer perspectives

Gonzaga

Capone

Bastian

et al. 2020

Australian Journal of Grape and Wine Research

Self Cite

View full text Add to dashboard Cite

Wine encapsulates the expression of multiple inputsfrom the vineyard location and environment to viticultural and winemaking practicescollectively known as terroir. Each of these inputs influence a wine's chemical composition and sensory traits, which vary depending on cultivar as well as provenance. These aspects underpin the overall concept of wine typicity, an important notion that enables wine from a delimited geographical area to be differentiated and recognisable in national and international wine markets. Indeed, consumers are increasingly more aware of the significance of regionality and may use this to influence their purchasing decisions. Understanding which sensory attributes represent regional typicity and how these are best conveyed to consumers is therefore important for the prosperity and reputation of producers. As reviewed herein, the sensory typicity of wine can be identified using different types of testing methods, with the most effective being a combination of approaches, such as sorting task in combination with descriptive sensory analysis. Consumer perceptions of regionality and wine typicity are then examined to provide insight into their behaviours. This includes consideration of the importance of origin to perceptions of quality and typicity, in terms of meeting expectations and engaging consumers. Based on the literature reviewed, it is proposed that wine typicity can be defined as a juxtaposition of unique traits that define a class of wines having common aspects of terroir involving biophysical and human dimensions that make the wines recognisable, and in theory, unable to be replicated in another territory.

show abstract