Introduction

The increasing frequency of wildfires and total area burned globally, has been linked to climate change as the main driver (Canadell et al., 2021; Richardson et al., 2022). Wine produced from grapes in vineyards exposed to smoke from nearby grass or forest fires can exhibit strong smoky aromas and flavours due to orthonasal and retronasal smoky odours (Parker et al., 2012). Commonly referred to as ‘smoke taint', these characters are considered highly undesirable by winemakers. The losses to the Australian wine sector due to smoke from wildfires and prescribed burns have been estimated at $1.4 billion AUD since 2003 (Krstic et al., 2021). The issue is also a challenge for the global wine industry and has caused significant quality defects and economic impacts in recent years throughout Europe, California and South America (Mirabelli-Montan et al., 2021).

There are a broad range of descriptors attributed to smoke taint in wine, such as smoky, medicinal, campfire ash, plastic and burnt aromas; and ash tray, drying and bitter and a lingering ashy aftertaste on palate (Krstic et al., 2015; Parker et al., 2012; Ristic et al., 2011). Some smoky flavour can also be found in wines that have not been exposed to smoke, due to other processing and maturation steps, notably the use of oak barrels that have been toasted or charred using a flame (Francis and Williamson, 2015; Koussissi et al., 2009; Prida and Chatonnet, 2010). Toasted oak can impart volatile phenols to a wine, particularly guaiacol, 4-methylguaiacol, and syringol (Chatonnet et al., 1999), which are produced during oak toasting from the same lignin degradation process that occurs when wood smoke is generated (Pollnitz et al., 2004; Spillman et al., 2004). Other common wine flavours that can be present in non-smoke-affected wines and can be confused with smoke taint have been described as medicinal, burnt rubber and leather, which are generally considered negative attributes (Lattey et al., 2010; Wedral et al., 2010).

The chemical basis for the smoky characters in wildfire smoke-affected wines is complex, with a large number of compounds implicated. The compounds most associated with smoke-affected wines are volatile phenols (originating from smoke) and phenolic glycosides (produced in grapes by the addition of sugar units to the volatile phenols). These volatile phenols impart smoky aroma and flavour, and include guaiacol, 4-methylguaiacol, o-cresol, m-cresol, p-cresol, syringol and 4-methylsyringol (Parker et al., 2012). A large number of phenolic glycosides have been identified in smoke exposed wines (Caffrey et al., 2019; Hayasaka et al., 2010), and routine markers for smoke exposure of grapes include syringol gentiobioside (SyGG), methylsyringol gentiobioside (MSyGG), phenol rutinoside (PhRG), guaiacol rutinoside (GuRG), cresol rutinosides (rutinosides of o-cresol, m-cresol and p-cresol) (CrRG), and methylguaiacol rutinoside (MGuRG) (Hayasaka et al., 2013). Beyond their role as biomarkers indicating smoke exposure, the phenolic glycosides can also contribute to the flavour and lingering aftertaste of smoke-affected wines, by releasing odorants in-mouth during consumption or during extended periods of storage (Mayr et al., 2014; Parker et al., 2020).

While the concentrations of volatile phenols and phenolic glycosides are regularly compared to concentrations found in non-smoke exposed wines to determine whether there is evidence of smoke exposure (Coulter et al., 2022), the exact relationship between chemical composition and concentration, and the intensity of smoky flavours in wine is complex (Parker et al., 2023). Highly smoke-affected grapes can result in wines with strong smoky flavours and high concentrations of volatile phenols and/or glycosides. For wine made from mildly smoke-affected grapes, smoky flavours are not always evident. A recent study based on over 60 unique smoke-affected Chardonnay, Pinot noir and Shiraz wines found that statistical models based on guaiacol, o-cresol, m-cresol, p-cresol, and some glycosides gave good predictions of smoke flavour intensity, with a slightly different optimal model for each cultivar (Parker et al., 2023). In the absence of robust chemical models for predicting smoky flavours in other cultivars and wine styles, sensory analysis remains a critical tool to determine whether a wine has quality defects or is acceptable.

To inform critical business decisions it is imperative that sensory assessment is carefully conducted using recognised protocols (Lawless and Heymann, 2010). However, sensory evaluation of potentially smoky wines is challenging: the response of individuals to smoke volatile compounds such as guaiacol is known to be variable, due to genotypic and phenotypic differences among individuals (Mainland et al., 2014). Previous work has shown a large degree of interindividual variation in sensitivity to guaiacol and also guaiacol glucoside (Parker et al., 2020). Many individuals perceive a long-lasting smoky sensation from guaiacol glucoside, when the glucoside is hydrolysed in the mouth, and the volatile odorant is released which is perceived retronasally (Parker et al., 2012; Mayr et al., 2014). The variation in response to phenolic glycosides was found to be related to volatile odour sensitivity rather than the ability to cleave volatile odorants from the precursors (Parker et al., 2020). Therefore, individuals who are sensitive to these volatile phenols and glycosides experience a lengthy smoky aftertaste, and as a consequence, carry-over effects are a concern in smoke sensory assessments (Fryer et al., 2021).

Very little is known about the levels of smoke aroma and flavour that are acceptable to consumers. For some off-flavours, such as cork taint (Prescott et al., 2005), consumer preference data has found that the presence of any degree of perceptible taint can be considered unacceptable. For other wine flavours where consumers respond negatively, such as oxidation, ‘Brett', or sulfur characters, a low intensity as determined by a trained sensory panel can potentially have no effect on consumer acceptance (Francis and Williamson, 2015). A previous study assessing consumers' acceptance of guaiacol added to a Merlot wine found an addition of 25 μg/L lowered liking scores (although not significantly) compared to the score for the base wine, but 50 μg/L added resulted in a significantly lower liking response (Herderich et al., 2012). In addition, cluster analysis indicated a relatively small group of consumers (30 %) responded negatively to the 25 μg/L addition. The sensory characters in wildfire smoke-affected wines are likely more complex, with other compounds involved and the potential for matrix effects (Parker et al., 2012), and there is no research to our knowledge that has assessed the acceptance of smoke-affected wines by wine consumers.

For determining whether a wine may be unacceptable due to grapevine exposure to smoke from nearby fires, consumer liking data are required to complement the interpretation of trained sensory panel measures. If acceptability limits can be established with the help of consumer responses (Manzocco, 2016), trained panel results or potentially chemical analytical data can be used for better informed decision-making in the wine industry.

This study aimed to test whether consumers respond negatively to wines made from smoke-affected grapes, and if so to provide guidance regarding the level of wildfire smoke flavour that might be acceptable. As numerous volatile and non-volatile compounds can contribute to smoky flavour, sets of smoke-affected wines were used rather than chemical additions to a base wine. The first study involved red wines made under controlled conditions from grapes sourced from vineyards with varied degrees of wildfire smoke exposure. This experiment was complemented by studies with two heavily smoke-affected wines, a rosé and a white wine, blended with different proportions of an unaffected wine. A secondary aim of this research was to assess the applicability of a streamlined smoke-specific panel rating procedure in comparison to a full quantitative descriptive analysis (QDA) approach.

Materials and methods

Results

1. Shiraz wines

For the Shiraz sample set, a full QDA was completed. In addition, the QDA data were compared with results from SRP assessments. The QDA data demonstrated that thirteen attributes differed significantly among the eight wines (Supplementary Table 3). These were ‘opacity’, ‘purple’, ‘dark fruit aroma’, ‘blackcurrant aroma’, ‘eucalypt aroma’, ‘smoke aroma’, ‘spices aroma’, ‘eggy/drain (reductive) aroma’, ‘astringency’, ‘hotness’, ‘viscosity’, ‘overall fruit flavour’ and ‘smoke flavour’. Only ‘smoke flavour’ was significantly different for the presentation replicate effect. There were significant (P < 0.05) assessor-by-wine-interaction effects for several attributes (Supplementary Table 4).

The sensory attributes of the Shiraz wines that were significantly different were visualised using PCA, shown in Figure 1, with the mean data in Supplementary Table 3. The first two principal components explained 51.4 % and 31.5 % of the variance. The ‘smoke aroma’ and ‘smoke flavour’ attributes were closely correlated (r = 0.93, P < 0.001), with SHZ G and SHZ C wines rated highest in these attributes, situated in the bottom left quadrant of the PCA (Figure 1), and these wines were rated low in most other attributes, suggesting the ‘smoke flavour’ suppressed other aroma and flavour attributes. Conversely, the wines made from grapes grown from vineyards with no smoke exposure, SHZ A and SHZ B, were rated lowest in the smoky attributes, plotted in the top right quadrant of Figure 1. Wines SHZ A, SHZ B and SHZ D were highest in ‘dark fruit aroma’, with SHZ D and SHZ B and SHZ I high in ‘opacity’, ‘astringency’, ‘overall fruit flavour’ and ‘spices aroma’. SHZ K was rated moderately in smoke and most other attributes and was plotted towards the centre of the PCA. One wine, SHZ F, had relatively high smoke intensity, but was also high in ‘eggy/drain aroma’ (sulfur related off-odour), while SHZ I rated highly in ‘smoke aroma’ and ‘smoke flavour’ and notably high in ‘eucalypt aroma’, ‘blackcurrant aroma’ and ‘hotness (alcohol burn)’.

Figure 1. Principal Component (PC) biplots of significant sensory attribute means from the Shiraz wines for PC1 and PC2. Significance levels are as follows: * P ≤ 0.05; ** P ≤ 0.01; *** P ≤ 0.001

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The SRP procedure also demonstrated that there were significant differences (P < 0.001) among the wines for each attribute: ‘overall fruit aroma’, ‘smoke aroma’, ‘overall fruit flavour’ and ‘smoke flavour’. SRP assessors were a significant source of variation (P < 0.05) for ‘overall fruit aroma’ and ‘overall fruit flavour’. Assessor-by-wine interaction was a significant source of variation for ‘smoke aroma’ (P < 0.05) and ‘overall fruit flavour’ (P < 0.01) (data not shown).

There was a strong correlation between the ‘smoke aroma’ and ‘smoke flavour’ ratings from the QDA assessment and the specific SRP procedure: ‘smoke aroma’ (QDA) vs ‘smoke aroma’ (SRP), r = 0.97 (P < 0.001); ‘smoke flavour’ (QDA) and ‘smoke flavour’ (SRP), r = 0.91 (P < 0.01), as illustrated in Figure 1 with smoke flavour ratings from the SRP plotted as a supplementary variable.

With both methodologies, SRP and QDA, the wines SHZ C, SHZ F, SHZ G, SHZ I, SHZ K were significantly higher (P < 0.05) in ‘smoke flavour’ than the control wines (SHZ A and SHZ B). The smoke-affected wines were rated low for ‘overall fruit aroma’ and ‘overall fruit flavour’ (Supplementary Table 5). Wines SHZ A and SHZ B were significantly different from one another for ‘overall fruit aroma’ and ‘overall fruit flavour’. For both studies only the wines SHZ C, SHZ F, and SHZ G were significantly higher than the controls for ‘smoke aroma’. As expected, the control wines had non-zero scores for smoke attributes for both studies, notwithstanding the extent of panel training. For the SRP methodology, wines SHZ A and SHZ B had relatively low ‘smoke flavour’ mean scores of 0.74 and 0.39 respectively, while for the QDA approach the values were 1.92 and 1.70.

To complement the expert panel sensory data, a subset of six Shiraz wines spanning the range of smoke flavour intensities from low to high was tasted by 111 red wine consumers, with the liking data shown in Figure 2a. Wines SHZ B and wine SHZ D, which were chosen as controls for the consumer study, were well accepted (as indicated by liking scores above 6.0), with all other wines rated significantly lower in liking. The least liked wine SHZ G (Figure 3a) had the highest ‘smoke flavour’ intensity (Supplementary Table 5) and the wines with smoke flavour rated above 1.95 from the SRP procedure were significantly less liked than the control wine.

Agglomerative hierarchical clustering analysis was performed to explore if clusters of consumers existed amongst the 111 participants. Three clusters were identified with significantly different liking scores (P < 0.05) within each cluster. The consumer liking data for each cluster and for the total consumer group tested was related to the sensory data by internal preference mapping (Figure 2b) using the mean liking scores of each cluster and of the total sample. The mean liking scores for the total consumer group were strongly negatively correlated with the intensity of the smoke attributes from the two procedures (r < -0.96). The total consumer group liking score versus ‘smoke flavour’ rating from the SRP methodology is presented in Figure 3a. The mean liking scores were significantly positively correlated with the QDA attributes ‘opacity’, ‘purple’, ‘dark fruit aroma’, ‘astringency’, ‘viscosity’ and ‘overall fruit flavour’ (r values from 0.81 – 0.96), and the SRP attributes ‘overall fruit aroma’ and ‘overall fruit flavour’ (r = 0.99).

Figure 2. Consumer response to wines with various smoke exposed vineyards. (a) Consumer liking mean scores. (b) Shiraz Principal Component Analysis biplot of the mean liking scores of three identified clusters and the total sample shown as vectors. The six wines are shown in blue. The sensory attributes from the QDA are indicated in black, as well as the smoke rating assessment attributes shown in purple. PC = Principal Component, A = Aroma, F = Flavour, SRP = Smoke Rating Panel.

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Clusters 1 (28 % of consumer) and 2 (53 %) showed similar patterns of liking as the overall group of consumers (Figure 2b and Supplementary Figure 1), with each showing a strong negative correlation with the smoke attributes (for example, cluster 1 mean scores vs smoky flavour, SRP, r = -0.92, P < 0.01) and strong positive correlation with the attribute ‘dark fruit aroma' (r > 0.91, P < 0.05), with moderate correlations (r > 0.75, P < 0.1) of liking scores for ‘opacity', ‘purple', ‘viscosity', and ‘overall fruit flavour'. The responses of clusters 1 and 2 were similar, although cluster 1 liking scores were lower overall than those of cluster 2; the SHZ D wine was significantly less liked than the control wine SHZ B; and there were notably low liking scores of approximately 3.0 for SHZ F, SHZ C and SHZ G (Supplementary Figure 1). Cluster 3 (19 % of consumers) had a different pattern of liking compared to the other two clusters, with SHZ B, a control wine with no known history of smoke exposure, scored lowest. No strong correlations of the liking scores of this cluster were found for any of the sensory attributes. This was a small cluster, and there was a significant presentation order effect which might explain the differences in liking for this cluster compared to the others, with wines presented earlier generally receiving higher scores for liking, as reported previously (Hottenstein et al., 2008).

Consumers in Cluster 1 (28 % of consumers) showed significantly lower liking scores of each of the smoke exposed wines compared to the control wine (SHZ B), which was scored above 6.0, with all other wines having mean values less than 5.0. Wines SHZ C, SHZ F, SHZ G and SHZ K received similar low hedonic scores (below 4.0). Similar to the total group of consumers, the attributes ‘opacity’, ‘dark fruit aroma’, ‘astringency’ and ‘overall fruit flavour’, were positively correlated with liking for this cluster. ‘Spices aroma’ was also significantly positively correlated.

Figure 3. The relationship between the mean sensory smoke flavour intensity and the mean consumer liking for a) SH = Shiraz (R2 = 0.954**; y = -0.34x + 6.55), b) PNR = Pinot noir rosé (R2 = 0.945**; y = -0.66x + 7.14) and c) CHA = Chardonnay (R2 = 0.968**; y = -0.17x + 6.74). ** P ≤ 0.01,

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Discussion

The results clearly show that smoke flavour was a strong negative driver of consumer liking in all three wine styles. The Shiraz wine sample set, which comprised a range of wines all produced using the same winemaking procedure from grapes with varied exposure to smoke from nearby forest fires, were evaluated using a QDA approach and a specific smoke rating methodology. The smoke attribute results were very similar with both methodologies. The correlation between the SRP data and the QDA panel's smoke aroma and flavour ratings was very strong (r > 0.94), which is not surprising considering both panels were selected based on successful smoke sensitivity screening procedures and had received training prior to formal evaluations. There were lower mean ratings for the controls from the specific SRP method, indicating fewer ‘false positive' non-zero scores given by assessors for unaffected wines compared to a generic QDA panel approach. It is expected that even with a highly trained, screened and experienced sensory panel, ‘false-positives' can occur. This can be due to an expectation effect by the assessors (Meilgaard et al., 2016), and the presence of confusable characters in the wines. To effectively allow an assessment of the magnitude of a smoke rating that can be considered significant in industrial application, an unaffected control wine should always be included in the sample set. Overall, the time required for one SRP assessment (2 hours total) compared very favourably to that required for one QDA (12 hours), given the almost identical results.

Both the SRP assessments and QDA (with smoke sensitive assessors) for the Shiraz wines showed very strong predictive ability when comparing consumer liking to smoke flavour intensity ratings from trained expert panels. As smoke aroma and smoke flavour were highly correlated in each study, but smoke flavour showed greater discrimination, it was a better overall predictor of consumer liking. The results of the QDA indicated that wines with smoke aroma and flavour were less intense in fruity attributes such as dark fruit or blackcurrant, suggesting a suppressive effect of the smoke flavour as previously indicated (Parker et al., 2012).

Consumer liking was highly negatively correlated with smoke flavour intensity for each wine type (Figure 1), independent of the varietal, winemaking and matrix differences between Shiraz red wines, Pinot noir rosé wines and Chardonnay white wines. The mean smoke flavour score that significantly affected consumer liking was different between the three different wine styles, with different slopes of the regression fitted lines across the wine types. This suggests the involvement of matrix effects influencing the absolute magnitude of the smoke flavour rating and therefore consumer liking. The Chardonnay wine set had the shallowest slope, with CHA 100 % affected wine receiving a mean smoke flavour rating of approximately 5.1 on the 10-point scale and a relatively high liking score of 6.5. In contrast, in the Shiraz and Pinot noir rosé sets, the wines rated highest for smoke flavour intensity had liking scores well below 5.0. Higher smoke flavour was thus tolerated in the Chardonnay, possibly because ‘toasty/oaky' and ‘struck-flint' characters are generally well liked and accepted as part of this wine style (Iland et al., 2017), which may be confusable for most consumers.

While a relatively small number of consumers were used in these studies, evidence of clusters of consumers were found for each wine type: a more responsive group of consumers (21-46 %), a moderately responsive group that closely mimicked the total group (33-53 %), and a group that were not responding to smoke flavour (19-40 %). The size of each of these clusters was different between each consumer group and wine style, but the same classifications were found each time.

Blending a heavily smoke-affected wine with a ‘clean’ wine using a dilution-to-threshold approach was used partly to expand the study, as obtaining a range of smoke-affected grape lots can be difficult given the unpredictable nature of wildfires. The approach also allowed assessment of critical levels of smoke flavour intensity with fewer confounding variables. The approach has the drawback that it is difficult to definitively exclude other confounding sensory attributes that might have contributed to differences in consumer preferences in the blends. The different blends obtained can be considered separate wines with increasing smoke aroma and flavour, but with other possible sensory differences. In this study, careful consideration was applied to select for dilution appropriate ‘clean’ wines with similar basic chemical composition. The observed linear negative liking response with increasing smoke flavour ratings for each of the three wine sets studied provides reassurance that the smoke flavour caused the negative consumer response, independent of wine style.

Across all three studies, non-zero ratings were observed for the ‘clean' control wines in the smoke rating SRP and QDA assessments. Smoke flavour values for control wines ranged from 0.74 to 1.92, and we assume that these smoke flavour ratings in ‘clean' wines reflect their typical wine composition and are not due to experimental artifacts from carry-over effects. For both methods, enforced resting periods were used to allow a) enough time for the flavour to develop and b) avoidance of carryover effects due to long lasting smoky aftertaste, which have been problematic in smoke wine assessments (Fryer et al., 2021; Oberholster et al., 2022). Both panels had a 2-minute break between samples, and in the SRP assessments, flavour attributes were rated after 30 seconds to ensure that there was sufficient time to allow the flavour to be perceived, rather than for the perception of smoke to be perceived in the break between samples.

One benefit that the SRP methodology has over conventional QDA is the potential to be a much faster and more economical way to assess the risk of smoke taint for industry. Provided robust screening and training procedures are implemented, the SRP process would be a better option for industry to adopt, as sessions can be implemented more rapidly. This methodology was tested with a regional winemaker panel, with good agreement with the results with the data obtained in this study (r = 0.98) and could be adopted more broadly by wine companies or regional organisations (data not shown).

The main benefit of the QDA assessment over the SRP assessment is that the whole range of appearance, aroma and palate attributes is measured, which allows deeper insight into the influence of masking and enhancing sensory characteristics across the wines. The QDA results revealed interactions of smoke aroma and flavour with other elements in the wine, such as alcohol heat, acidity, sweetness and other attributes that can play a role in the intensity of smoke flavour.

An interesting sample was SHZ I, which contained high concentrations of smoke marker compounds, but received moderate ‘smoke aroma' and ‘smoke flavour' scores by panellists, both for the QDA and SRP. The QDA revealed that this wine had a ‘eucalyptus aroma', ‘blackcurrant aroma' and was high in ‘hotness (alcohol burn)', which potentially could be suppressing the smoke aroma and flavour in the wine. The SHZ I wine was found to contain a high concentration of the eucalyptus/minty compound 1,8-cineole (19.8 μg/L, well above its sensory threshold of 1.1 μg/L (Herve et al., 2003)), the blackcurrant-like compound dimethyl sulfide, (21.2 μg/L, which has a sensory threshold of 1.74 μg/L) (Lytra et al., 2014) and was high in alcohol (16.5 % v/v). More research is warranted to establish and better understand masking effects in wine, which might provide an approach to guide selection of particularly suitable blending wines.

Depending on the commercial considerations of individual wine producers, some companies might prefer not to risk releasing any even slightly smoke-affected products to the market, given the strong relationship between smoke aroma and flavour score, and reduced consumer acceptance. Others may make use of the results of this study to develop a guide regarding limits of smoke flavour above which consumer acceptance is significantly reduced, such as described in Hough et al. (2002). Further wine styles will need to be investigated to assess whether the results obtained in this study are applicable more generally. Also, sensory assessment and predictive modelling of combinations of smoke-related compounds need to be established to determine the size of the risk that winemakers and producers will face when smoke events occur. The chemical composition of smoke-affected wines and the relationships with wine flavour are discussed in detail in a separate accompanying manuscript (Parker et al., 2023). Reconstitution experiments will need to be specific for individual wine cultivars and winemaking practices. Until then, robust sensory of wine and chemical measures of smoke exposure markers are necessary to identify and gauge a potential risk of quality defects after smoke exposure of vineyards.

Conclusion

From all three studies, it is clear that consumers respond negatively to smoke flavour in wine that is caused by vineyard exposure to wildfires and smoke events. The sensitivity of consumers to smoke-affected wines correlated highly with smoke flavour ratings from a screened and trained smoke sensitive panel. While the overall group of consumers in each study showed a strong negative correlation between liking and smoke flavour, there were clusters of consumers that were more sensitive to these characters.

The response to smoke flavour was variable across the different wine styles. However, the wines that showed a negative response from consumers all had concentrations of smoke marker compounds lower than that of the reported sensory thresholds for all individual compounds. With a maximum acceptable concentration of smoke marker compounds not currently known, it will be crucial for the wine industry to incorporate both sensory and chemical analysis for making decisions post-smoke events. Research investigating the way in which these phenolic (and potentially other) flavour compounds interact with one another, and the complexity of the background matrix of the grape cultivars and wine styles, will also be important in solving this issue. Overall, the information from the present study will enable grape-growers and winemakers to make better informed business decisions about reducing or eliminating potential quality defects after smoke events.

Funding

This work was performed by the AWRI, a member of the Wine Innovation Cluster in Adelaide, South Australia. Funding was provided by Australian grapegrowers and winemakers through their investment body Wine Australia, with matching funds from the Australian Government. Additional funding and in-kind contributions from PIRSA, the South Australian, Victorian and NSW State Governments, Wine Victoria and NSW Wine, and the Australian Government’s Department of Agriculture and Water Resources Rural R&D for Profit program are gratefully acknowledged. External funders were not involved in the study design, collection of data, analysis and interpretation of data, writing the report, or the decision to submit the article for publication.

Acknowledgements

The authors would like to acknowledge Affinity Labs for analysis, Kantar Australia for screening consumers for the Chardonnay study, and use of their facilities in Melbourne, Peter Leske and the Adelaide Hills winemakers, and the AWRI sensory panellists for their smoke rating and descriptive evaluations. Additional thanks to Patricia Williamson, Desireé Likos, Damian Espinase Nandorfy, Sheridan Barter, Ella Robinson, Con Simos and Mark Krstic for their assistance. The authors would also like to thank the industry partners who provided access to vineyards and samples for analysis, and finally the numerous staff at the AWRI involved in smoke analysis.

References

• Caffrey, A., Lerno, L., Rumbaugh, A., Girardello, R., Zweigenbaum, J., Oberholster, A., & Ebeler, S. E. (2019). Changes in Smoke-Taint Volatile-Phenol Glycosides in Wildfire Smoke-Exposed Cabernet Sauvignon Grapes throughout Winemaking. American Journal of Enology and Viticulture, 70(4), 373-381. https://doi.org/10.5344/ajev.2019.19001
• Canadell, J. G., Meyer, C. P., Cook, G. D., Dowdy, A., Briggs, P. R., Knauer, J., Pepler, A., & Haverd, V. (2021). Multi-decadal increase of forest burned area in Australia is linked to climate change. Nature Communications, 12(1), 6921. https://doi.org/10.1038/s41467-021-27225-4
• Chatonnet, P., Cutzach, I., Pons, M., & Dubourdieu, D. (1999). Monitoring Toasting Intensity of Barrels by Chromatographic Analysis of Volatile Compounds from Toasted Oak Wood. Journal of Agricultural and Food Chemistry, 47(10), 4310-4318. https://doi.org/10.1021/jf981234t
• Coulter, A., Baldock, G., Parker, M., Hayasaka, Y., Francis, I. L., & Herderich, M. (2022). Concentration of smoke marker compounds in non‐smoke‐exposed grapes and wine in Australia. Australian Journal of Grape and Wine Research. https://doi.org/10.1111/ajgw.12543
• Culbert, J. A., Jiang, W., Bilogrevic, E., Likos, D., Francis, I. L., Krstic, M. P., & Herderich, M. J. (2021). Compositional changes in smoke-affected grape juice as a consequence of activated carbon treatment and the impact on phenolic compounds and smoke flavor in wine. Journal of Agricultural and Food Chemistry, 69(35), 10246-10259. https://doi.org/10.1021/acs.jafc.1c02642
• Francis, I. L., & Williamson, P. O. (2015). Application of consumer sensory science in wine research. Australian Journal of Grape and Wine Research, 21(S1), 554-567. https://doi.org/https://doi.org/10.1111/ajgw.12169
• Fryer, J. A., Collins, T. S., & Tomasino, E. (2021). Evaluation of Different Interstimulus Rinse Protocols on Smoke Attribute Perception in Wildfire-Affected Wines. Molecules, 26(18), 5444-5461. https://doi.org/10.3390/molecules26185444
• Hayasaka, Y., Baldock, G. A., Parker, M., Pardon, K. H., Black, C. A., Herderich, M. J., & Jeffery, D. W. (2010). Glycosylation of smoke-derived volatile phenols in grapes as a consequence of grapevine exposure to bushfire smoke. Journal of Agricultural and Food Chemistry, 58(20), 10989-10998. https://doi.org/10.1021/jf103045t
• Hayasaka, Y., Parker, M., Baldock, G. A., Pardon, K. H., Black, C. A., Jeffery, D. W., & Herderich, M. J. (2013). Assessing the impact of smoke exposure in grapes: development and validation of a HPLC-MS/MS method for the quantitative analysis of smoke-derived phenolic glycosides in grapes and wine. Journal of Agricultural and Food Chemistry, 61(1), 25-33. https://doi.org/10.1021/jf305025j
• Herderich, M. J., Seibert, T. E., Parker, M., Capone, D. L., Jeffery, D. W., Osidacz, P., & Francis, I. L. (2012). Spice Up Your Life: Analysis of Key Aroma Compounds in Shiraz. In M. Qian & T. H. Shellhammer (Eds.), Flavor Chemistry of Wine and Other Alcoholic Beverages (pp. 3-13). American Chemical Society. https://doi.org/10.1021/bk-2012-1104.ch001
• Heymann, H., King, E. S., & Hopfer, H. (2016). Classical Descriptive Analysis. In P. Varela & G. Ares (Eds.), Novel Techniques in Sensory Characterization and Consumer Profiling (1 ed., pp. 9-40). Taylor & Francis Group. https://ebookcentral.proquest.com/lib/jfml/detail.action?docID=1566585.
• Hottenstein, A. W., Taylor, R., & Carr, B. T. (2008). Preference segments: A deeper understanding of consumer acceptance or a serving order effect? Food Quality and Preference, 19(8), 711-718. https://doi.org/10.1016/j.foodqual.2008.04.004
• Hough, G., Sánchez, R., Pablo, G., Sánchez, R., Villaplana, S., Giménez, A., & Gámbaro, A. (2002). Consumer Acceptability Versus Trained Sensory Panel Scores of Powdered Milk Shelf-Life Defects. Journal of dairy science, 85, 2075-2080. https://doi.org/10.3168/jds.S0022-0302(02)74285-9
• Iland, P., Gago, P., Caillard, A., & Dry, P. (2017). Australian wine: styles and tastes : people and places. Patrick Iland Promotions Pty Ltd.
• Jiang, W., Bilogrevic, E., Parker, M., Francis, I. L., Leske, P., Hayasaka, Y., Barter, S., & Herderich, M. (2022). The effect of pre-veraison smoke exposure of grapes on phenolic compounds and smoky flavour in wine. Australian Journal of Grape and Wine Research, 2022, https://doi.org/10.1155/2022/9820204
• Koussissi, E., Dourtoglou, V. G., Ageloussis, G., Paraskevopoulos, Y., Dourtoglou, T., Paterson, A., & Chatzilazarou, A. (2009). Influence of toasting of oak chips on red wine maturation from sensory and gas chromatographic headspace analysis. Food Chemistry, 114(4), 1503-1509. https://doi.org/10.1016/j.foodchem.2008.11.003
• Krstic, M., Culbert, J., Parker, M., & Herderich, M. (2021). Smoke taint and climate change. In A. G. Reynolds (Ed.), Managing wine quality (pp. 763-778).
• Krstic, M. P., Johnson, D. L., & Herderich, M. J. (2015). Review of smoke taint in wine: smoke-derived volatile phenols and their glycosidic metabolites in grapes and vines as biomarkers for smoke exposure and their role in the sensory perception of smoke taint. Australian Journal of Grape and Wine Research, 21, 537-553. https://doi.org/10.1111/ajgw.12183
• Lattey, K. A., Bramley, B. R., & Francis, I. L. (2010). Consumer acceptability, sensory properties and expert quality judgements of Australian Cabernet Sauvignon and Shiraz wines. Australian Journal of Grape and Wine Research, 16(1), 189-202. https://doi.org/10.1111/j.1755-0238.2009.00069.x
• Lawless, H. T., & Heymann, H. (2010). Sensory evaluation of food : principles and practices (2 ed., Vol. 1). Springer. https://doi.org/https://doi.org/10.1007/978-1-4419-6488-5
• Mainland, J. D., Keller, A., Li, Y. R., Zhou, T., Trimmer, C., Snyder, L. L., Moberly, A. H., Adipietro, K. A., Liu, W. L., Zhuang, H., Zhan, S., Lee, S. S., Lin, A., & Matsunami, H. (2014). The missense of smell: functional variability in the human odorant receptor repertoire. Nature Neuroscience, 17(1), 114-120. https://doi.org/10.1038/nn.3598
• Manzocco, L. (2016). The Acceptability Limit in Food Shelf Life Studies. Crit Rev Food Sci Nutr, 56(10), 1640-1646. https://doi.org/10.1080/10408398.2013.794126
• Mayr, C. M., Parker, M., Baldock, G. A., Black, C. A., Pardon, K. H., Williamson, P. O., Herderich, M. J., & Francis, I. L. (2014). Determination of the importance of in-mouth release of volatile phenol glycoconjugates to the flavor of smoke-tainted wines. Journal of Agricultural and Food Chemistry, 62(11), 2327-2336. https://doi.org/10.1021/jf405327s
• Meilgaard, M. C., Civille, G. V., & Carr, B. T. (2016). Sensory evaluation techniques (Fifth edition. ed.). CRC Press, Taylor & Francis Group, CRC Press is an imprint of the Taylor & Francis Group, an Informa business.
• Mirabelli-Montan, Y. A., Marangon, M., Graça, A., Mayr Marangon, C. M., & Wilkinson, K. L. (2021). Techniques for Mitigating the Effects of Smoke Taint While Maintaining Quality in Wine Production: A Review. Molecules, 26(6), 1672-1691. https://doi.org/10.3390/molecules26061672
• Oberholster, A., Wen, Y., Dominguez Suarez, S., Erdmann, J., Cauduro Girardello, R., Rumbaugh, A., Neupane, B., Brenneman, C., Cantu, A., & Heymann, H. (2022). Investigation of Different Winemaking Protocols to Mitigate Smoke Taint Character in Wine. Molecules, 27(5). https://doi.org/10.3390/molecules27051732
• Parker, M., Onetto, C., Hixson, J., Bilogrevic, E., Schueth, L., Pisaniello, L., Borneman, A., Herderich, M., de Barros Lopes, M., & Francis, L. (2020). Factors Contributing to Interindividual Variation in Retronasal Odor Perception from Aroma Glycosides: The Role of Odorant Sensory Detection Threshold, Oral Microbiota, and Hydrolysis in Saliva. Journal of Agricultural and Food Chemistry, 68(38), 10299-10309. https://doi.org/10.1021/acs.jafc.9b05450
• Parker, M., Osidacz, P., Baldock, G. A., Hayasaka, Y., Black, C. A., Pardon, K. H., Jeffery, D. W., Geue, J. P., Herderich, M. J., & Francis, I. L. (2012). Contribution of several volatile phenols and their glycoconjugates to smoke-related sensory properties of red wine. Journal of Agricultural and Food Chemistry, 60(10), 2629-2637. https://doi.org/10.1021/jf2040548
• Parker, M.; Jiang, W.W.; Bilogrevic, E.; Likos, D.; Gledhill, J.; Coulter, A. D.; Cowey, G. D.; Simos, C. A.; Francis, I. L.; and Herderich, M. J. (2023). Modelling Smoke Flavour in Wine from Chemical Composition of Smoke-Exposed Grapes and Wine. Australian Journal of Grape and Wine Research. 1-14. https://doi.org/10.1155/2023/4964850
• Peryam, D. R., & Pilgrim, F. J. (1957). Hedonic scale method of measuring food preferences. Food Technology, 11, Suppl., 9-14.
• Pollnitz, A. P., Pardon, K. H., Sykes, M., & Sefton, M. A. (2004). The Effects of Sample Preparation and Gas Chromatograph Injection Techniques on the Accuracy of Measuring Guaiacol, 4-Methylguaiacol and Other Volatile Oak Compounds in Oak Extracts by Stable Isotope Dilution Analyses. Journal of Agricultural and Food Chemistry, 52(11), 3244-3252. https://doi.org/10.1021/jf035380x
• Prescott, J., Norris, L., Kunst, M., & Kim, S. (2005). Estimating a “consumer rejection threshold” for cork taint in white wine. Food Quality and Preference, 16(4), 345-349. https://doi.org/10.1016/j.foodqual.2004.05.010
• Prida, A., & Chatonnet, P. (2010). Impact of Oak-Derived Compounds on the Olfactory Perception of Barrel-Aged Wines. American Journal of Enology and Viticulture, 61(3), 408-413. https://www.ajevonline.org/content/ajev/61/3/408.full.pdf
• Richardson, D., Black, A. S., Irving, D., Matear, R. J., Monselesan, D. P., Risbey, J. S., Squire, D. T., & Tozer, C. R. (2022). Global increase in wildfire potential from compound fire weather and drought. npj Climate and Atmospheric Science, 5(1), 23. https://doi.org/10.1038/s41612-022-00248-4
• Ristic, R., Osidacz, P., Pinchbeck, K. A., Hayasaka, Y., Fudge, A. L., & Wilkinson, K. L. (2011). The effect of winemaking techniques on the intensity of smoke taint in wine. Australian Journal of Grape and Wine Research, 1-13. https://doi.org/10.1111/j.1755-0238.2011.00146.x
• Spillman, P. J., Sefton, M. A., & Gawel, R. (2004). The effect of oak wood source, location of seasoning and coopering on the composition of volatile compounds in oak-matured wines. Australian Journal of Grape and Wine Research, 10(3), 216-226. ://WOS:000225549200006
• Wedral, D., Shewfelt, R., & Frank, J. (2010). The challenge of Brettanomyces in wine. LWT - Food Science and Technology, 43(10), 1474-1479. https://doi.org/10.1016/j.lwt.2010.06.010