ARC Training Centre for Innovative Wine Production publications
Permanent URI for this collection
Browse
Browsing ARC Training Centre for Innovative Wine Production publications by Author "Bastian, S.E.P."
Now showing 1 - 14 of 14
Results Per Page
Sort Options
Item Open Access A review of wine authentication using spectroscopic approaches in combination with chemometrics(MDPI AG, 2021) Ranaweera, R.K.R.; Capone, D.L.; Bastian, S.E.P.; Cozzolino, D.; Jeffery, D.W.In a global context where trading of wines involves considerable economic value, the requirement to guarantee wine authenticity can never be underestimated. With the ever-increasing advancements in analytical platforms, research into spectroscopic methods is thriving as they offer a powerful tool for rapid wine authentication. In particular, spectroscopic techniques have been identified as a user-friendly and economical alternative to traditional analyses involving more complex instrumentation that may not readily be deployable in an industry setting. Chemometrics plays an indispensable role in the interpretation and modelling of spectral data and is frequently used in conjunction with spectroscopy for sample classification. Considering the variety of available techniques under the banner of spectroscopy, this review aims to provide an update on the most popular spectroscopic approaches and chemometric data analysis procedures that are applicable to wine authentication.Item Metadata only Absorbance-transmission and fluorescence excitation-emission matrix (A-TEEM) with multi-block data analysis and machine learning for accurate intraregional classification of Barossa Shiraz wine(Elsevier, 2023) Ranaweera, R.K.R.; Bastian, S.E.P.; Gilmore, A.M.; Capone, D.L.; Jeffery, D.W.Authentication of wine can be considered at different scales, with classification according to country, province/ state, or appellation/wine producing region. An absorbance-transmission and excitation-emission matrix (ATEEM) technique was applied for the first time to examine intraregional differences, using Shiraz wines (n = 186) produced during three vintages from five subregions of Barossa Valley and from Eden Valley. Absorption spectra and EEM fingerprints were modelled as a multi-block data set for initial exploration with k-means cluster analysis and principal component analysis, and then with machine learning modelling using extreme gradient boosting discriminant analysis (XGBDA). Whereas some clustering was evident with the initial unsupervised approaches, classification with XGBDA afforded an impressive 100% correct class assignment for subregion and vintage year. Extending the utility and novelty of the A-TEEM approach, predictive models for chemical parameters (alcohol, glucose + fructose, pH, titratable acidity, and volatile acidity) were also validated using ATEEM data with XGB regression.Item Metadata only Authentication of the geographical origin of Australian Cabernet Sauvignon wines using spectrofluorometric and multi-element analyses with multivariate statistical modelling(Elsevier, 2021) Ranaweera, R.K.R.; Gilmore, A.M.; Capone, D.L.; Bastian, S.E.P.; Jeffery, D.W.With the increased risk of wine fraud, a rapid and simple method for wine authentication has become a necessity for the global wine industry. The use of fluorescence data from an absorbance and transmission excitation-emission matrix (A-TEEM) technique for discrimination of wines according to geographical origin was investigated in comparison to inductively coupled plasma-mass spectrometry (ICP-MS). The two approaches were applied to commercial Cabernet Sauvignon wines from vintage 2015 originating from three wine regions of Australia, along with Bordeaux, France. Extreme gradient boosting discriminant analysis (XGBDA) was examined among other multivariate algorithms for classification of wines. Models were cross-validated and performance was described in terms of sensitivity, specificity, and accuracy. XGBDA classification afforded 100% correct class assignment for all tested regions using the EEM of each sample, and overall 97.7% for ICP-MS. The novel combination of A-TEEM and XGBDA was found to have great potential for accurate authentication of wines.Item Metadata only Consumer perspectives of wine typicity and impact of region information on the sensory perception of Cabernet Sauvignon wines(Elsevier, 2022) Souza Gonzaga, L.; Bastian, S.E.P.; Capone, D.L.; Danner, L.; Jeffery, D.W.Region of origin is used in marketing of wine and by consumers as a wine quality indicator. To better understand wine consumers’ purchase decisions, sensory perception, and wine liking in connection with wine provenance, this study used regular wine consumers (n = 112) to evaluate two Cabernet Sauvignon wines from each of four wine producing regions through hedonic rating and rate-all-that-apply (RATA) testing in conjunction with preand post-tasting questionnaires. The majority of consumers rated the region of origin stated on the label as important for purchase intent and for deciding the price they were willing to pay for a wine. The questionnaire also revealed that consumers were familiar with the wine typicity concept, but seemed to consider it only as an extrinsic characteristic rather than an intrinsic aspect of the wine. By randomly dividing the consumers into two groups (n = 56 each), one having information on the origin of samples and the other tasting without such knowledge, it was demonstrated that origin information had a positive impact on hedonic scores. Sensory profiling revealed that origin information did not impact the sample sensory characterisation, and liking for both groups was related to ‘full body’, ‘jammy’, and ‘dark fruits’ attributes. Some regional profile features were apparent for the samples, such as ‘minty’ for Coonawarra and savoury attributes for Bordeaux. Overall, this work highlighted that consumers could differentiate wines from distinct regions on the basis of sensory characteristics.Item Metadata only Defining wine typicity: sensory characterisation and consumer perspectives(Wiley, 2021) Souza Gonzaga, L.; Capone, D.L.; Bastian, S.E.P.; Jeffery, D.W.Wine encapsulates the expression of multiple inputs – from the vineyard location and environment to viticultural and winemaking practices – collectively 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.Item Metadata only Impact of Lachancea thermotolerans on chemical composition and sensory profiles of Merlot wines(Elsevier, 2021) Hranilovic, A.; Albertin, W.; Capone, D.L.; Gallo, A.; Grbin, P.R.; Danner, L.; Bastian, S.E.P.; Masneuf-Pomarede, I.; Coulon, J.; Bely, M.; Jiranek, V.Wines from warm(ing) climates often contain excessive ethanol but lack acidity. The yeast Lachancea thermotolerans can ameliorate such wines due to partial conversion of sugars to lactic acid during alcoholic fermentation. This study compared the performance of five L. thermotolerans strains in two inoculation modalities (sequential and co-inoculation) to Saccharomyces cerevisiae and un-inoculated treatments in high sugar/low acidity Merlot fermentations. The pH and ethanol levels in mixed-culture dry wines were either comparable, or significantly lower than in controls (decrease of up to 0.5 units and 0.90% v/v, respectively). The analysis of volatile compounds revealed marked differences in major flavour-active yeast metabolites, including up to a thirty-fold increase in ethyl lactate in certain L. thermotolerans modalities. The wines significantly differed in acidity perception, alongside 18 other sensory attributes. Together, these results highlight the potential of some L. thermotolerans strains to produce ‘fresher’ wines with lower ethanol content and improved flavour/balance.Item Open Access Impact of Lachancea thermotolerans on Chemical Composition and Sensory Profiles of Viognier Wines(MDPI AG, 2022) Hranilovic, A.; Albertin, W.; Capone, D.L.; Gallo, A.; Grbin, P.R.; Danner, L.; Bastian, S.E.P.; Masneuf-Pomarede, I.; Coulon, J.; Bely, M.; Jiranek, V.Viognier is a warm climate grape variety prone to loss of acidity and accumulation of excessive sugars. The yeast Lachancea thermotolerans can improve the stability and balance of such wines due to the partial conversion of sugars to lactic acid during alcoholic fermentation. This study compared the performance of five L. thermotolerans strains in co-inoculations and sequential inoculations with Saccharomyces cerevisiae in high sugar/pH Viognier fermentations. The results high lighted the dichotomy between the non-acidified and the bio-acidified L. thermotolerans treatments, with either comparable or up to 0.5 units lower pH relative to the S. cerevisiae control. Significant differences were detected in a range of flavour-active yeast volatile metabolites. The perceived acidity mirrored the modulations in wine pH/TA, as confirmed via “Rate-All-That-Apply” sensory analysis. Despite major variations in the volatile composition and acidity alike, the varietal aromatic expression (i.e., stone fruit aroma/flavour) remained conserved between the treatments.Item Open Access Modelling Cabernet-Sauvignon wine sensory traits from spectrofluorometric data(International Viticulture and Enology Society - IVES, 2021) Souza Gonzaga, L.; Bastian, S.E.P.; Capone, D.L.; Ranaweera, R.K.R.; Jeffery, D.W.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.Item Open Access Preliminary investigation of potent thiols in Cypriot wines made from indigenous grape varieties Xynisteri, Maratheftiko and Giannoudhi(International Viticulture and Enology Society - IVES, 2021) Copper, A.W.; Collins, C.; Bastian, S.E.P.; Johnson, T.E.; Capone, D.L.Polyfunctional thiols have previously been shown to be key aroma compounds in Sauvignon blanc and more recently in Chardonnay wines. Their role in other wine varieties such as those made from three popular indigenous Cypriot grape varieties has remained unexplored. As an extension of a previous project that profiled the sensory and chemical characteristics of Cypriot wines and their comparison to Australian wines, this study aimed to investigate five potent thiols in Xynisteri, Maratheftiko, Giannoudhi, Pinot gris, Chardonnay and Shiraz wines. Wines were analysed utilising Stable Isotope Dilution Assay (SIDA) with derivatisation and High-Performance Liquid Chromatography–Tandem Mass Spectrometry (HPLC-MS/MS). The varietal thiols measured were 4-methyl-4-sulfanylpentan-2-one (4MSP) that has an aroma of “boxwood” and “cat urine” at high concentration, 3-sulfanylhexan-1-ol (3SH) which has been described as having a “grapefruit/tropical fruit” aroma, and 3-sulfanylhexyl acetate (3SHA) that has also been described as having an aroma of “passionfruit”. Additionally, two other potent thiols were measured including benzyl mercaptan (BM) that has an aroma of “smoke and meat” and furfuryl thiol (FFT) that has been described as having a “roasted coffee” like aroma. The reason these thiols are known as potent thiols are due to their very low aroma detection thresholds in the low ng/L (ppt) range. Of the thiols that were measured, 3SH was the only varietal thiol detected in the red wine samples. All of the white wine samples contained 3SH, BM and 3SHA, whereas 4MSP was only detected in Pinot gris and three Xynisteri wines. The potent thiol, FFT, was detected only in the Chardonnay and four of the Xynisteri wines. Interestingly the thiols that were present in the samples were found at concentrations above their aroma detection thresholds (determined in hydroalcoholic solutions), especially 3SH which was found in an order of magnitude above its aroma detection threshold. These findings provide early knowledge of the presence of these thiols in Cypriot wines, compared with Australian wines and establish any relationships between this chemical data with previous wine sensory profile data.Item Open Access Sensory and chemical drivers of wine consumers' preference for a new shiraz wine product containing ganoderm alucidum extract as a novel ingredient(MDPI, 2020) Nguyen, A.N.H.; Johnson, T.E.; Jeffery, D.W.; Capone, D.L.; Danner, L.; Bastian, S.E.P.This study explored wine consumers' preferences towards a novel Australian Shiraz wine product containing Ganoderma lucidum (GL). Wine consumers (n = 124) were asked to complete a questionnaire and participate in a blind tasting of six GL wine products (differing in the amount and timing of GL extract additions). Based on individual liking scores for each GL wine product that was tasted, four hedonic clusters C1 (n = 44, preferred control and low levels of GL additions), C2 (n = 28, preferred control only), C3 (n = 26, generally preferred all GL additions) and C4 (n = 26, preferred 1 g/L additions and 4 g/L post-fermentation) were identified. Sensory attributes of the GL wine products were also profiled with rate-all-that-apply (n = 65) and the 31 sensory attributes that significantly differentiated the wines underwent principal component analysis with the hedonic clusters overlaid to explain consumers' preferences. There was a clear separation between hedonic clusters. Sensory attributes and volatile flavor compounds that significantly differentiated the wines were subjected to partial least squares regression, which indicated the important positive drivers of liking among the hedonic clusters. Pepper and jammy aroma, 3-methylbutanoic acid (linked to fruity notes) and non-fruit aftertaste positively drove C2's preference, whereas spice flavor and hexanoic acid (known for leafy and woody descriptors) drove C3's liking. There were no positive drivers for C1's liking but bitter taste, cooked vegetable, and toasty aromas drove this cluster' dislike. C4 preferred brown appearance, tobacco aroma, and jammy and cooked vegetable flavors. These findings provide the wine industry with deeper insights into consumers' liking towards new GL wine products targeted at the Australasian market.Item Metadata only Spectrofluorometric analysis combined with machine learning for geographical and varietal authentication, and prediction of phenolic compound concentrations in red wine(Elsevier, 2021) Ranaweera, R.K.R.; Gilmore, A.M.; Capone, D.L.; Bastian, S.E.P.; Jeffery, D.W.Fluorescence spectroscopy is rapid, straightforward, selective, and sensitive, and can provide the molecular fingerprint of a sample based on the presence of various fluorophores. In conjunction with chemometrics, fluorescence techniques have been applied to the analysis and classification of an array of products of agricultural origin. Recognising that fluorescence spectroscopy offered a promising method for wine authentication, this study investigated the unique use of an absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) technique for classification of red wines with respect to variety and geographical origin. Multi-block data analysis of A-TEEM data with extreme gradient boosting discriminant analysis yielded an unrivalled 100% and 99.7% correct class assignment for variety and region of origin, respectively. Prediction of phenolic compound concentrations with A-TEEM based on multivariate calibration models using HPLC reference data was also highly effective, and overall, the A-TEEM technique was shown to be a powerful tool for wine classification and analysis.Item Open Access Spectrofluorometric analysis to trace the molecular fingerprint of wine during the winemaking process and recognise the blending percentage of different varietal wines(International Viticulture and Enology Society - IVES, 2022) Ranaweera, R.K.R.; Gilmore, A.M.; Bastian, S.E.P.; Capone, D.; Jeffery, D.As a robust analytical method, spectrofluorometric analysis with machine learning modelling has recently been used to authenticate wine from different regions, vintages and varieties. This preliminary study investigated whether the molecular fingerprint obtained with this approach is maintained throughout the winemaking process, along with assessing different percentages of wine in a blend. Monovarietal wine samples were collected at different stages of the winemaking process and analysed with the absorbance-transmission and fluorescence excitation-emission matrix (A-TEEM) technique. Wines were clustered tightly according to origin for the different winemaking stages, with some clear separation of different regions and varieties based on principal component analysis. In addition, wines were classified with 100 % accuracy according to varietal origin using extreme gradient boosting (XGB) discriminant analysis. The sensitivity of the A-TEEM technique was such that it allowed for accurate modelling of wine blends containing as little as 1 % of Cabernet-Sauvignon or Grenache in Shiraz wine when employing XGB regression, which performed better than partial least squares regression. The overall results indicated the potential for applying A-TEEM and machine learning modelling to wine chemical traceability through production to guarantee the provenance of wine or identify the composition of a blend.Item Open Access Using content analysis to characterise the sensory typicity and quality judgements of Australian Cabernet Sauvignon wines(MDPI AG, 2019) Souza Gonzaga, L.; Capone, D.L.; Bastian, S.E.P.; Danner, L.; Jeffery, D.W.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.Item Open Access Volatile composition and sensory profiles of a shiraz wine product made with pre- and post-fermentation additions of Ganoderma Lucidum extract(MDPI, 2019) Nguyen, A.N.H.; Capone, D.L.; Johnson, T.E.; Jeffery, D.W.; Danner, L.; Bastian, S.E.P.Novel Shiraz red wine products enriched with Ganoderma lucidum (GL) extract, a traditional Asian medicinal mushroom, were developed and characterized. GL extract was added at different levels prior to and after primary fermentation to investigate its impact on the juice fermentation kinetics, and the chemical composition and sensory properties of the resulting wines. The fermentation kinetics of red grape juice were not significantly different between ferments. Basic chemical analyses plus headspace solid-phase micro-extraction (HS-SPME), gas chromatography‒mass spectrometry (GC-MS), and a rate-all-that-apply (RATA) (n = 65) sensory panel were used to investigate the influence of GL extract additions on wine composition and sensory characteristics. Of the 54 sensory attributes assessed, 39 significantly differentiated the wines. A clear separation between GL wine treatments was evident with PLS regression, where specific volatiles were correlated with relevant sensory attributes that dominated the wines. These products could be promising for emerging wine markets.