Impact of grapevine exposure to smoke on vine physiology and the composition and sensory properties of wine

Ristić, Renata; Fudge, Anthea; Pinchbeck, K.A.; Bei, Roberta De; Fuentes, Sigfredo; Hayasaka, Yoji; Tyerman, Stephen D.; Wilkinson, Kerry L.

doi:10.1007/s40626-016-0054-x

Cited by 47 publications

(135 citation statements)

References 33 publications

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“…Bushfires often occur in very close proximity to vineyards in most wine growing areas globally, with recent examples including the United States of America (Jin et al, 2015), Australia (Cox, 2018), the Iberian Peninsula (Barnes, 2018), and South Africa (SA). The contribution of VPs to the pool of taint compounds in grapes and wine has been shown to escalate severely following a bushfire event (Kennison, 2013;Krstic et al, 2015;Ristic et al, 2016). These compounds have been individually characterized in different matrices by a number of authors Parker et al, 2013;Petrozziello et al, 2014) and their odour detection thresholds (ODTs) have been established (Table 1).…”

Section: Introductionmentioning

confidence: 99%

Potentially Smoke Tainted Red Wines: Volatile Phenols and Aroma Attributes

McKay

Bauer

Panzeri

et al. 2019

SAJEV

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Malodourous compounds, including volatile phenols (VPs) are frequently found at concentrations below their odour thresholds in wine, and may therefore be considered to present no threat to wine quality. Most investigations into smoke taint quantify compounds by chemical/analytical means, or investigate sensory effects of supra-and peri-threshold contamination in model wine. In this project, twelve wines (submitted by the South African industry as potentially smoke tainted) were screened for VPs using GC-MS, and characterized using descriptive analysis (DA) by a sensory panel highly trained in smoke taint evaluation. Results were compared statistically to elucidate relationships between chemical and sensory characteristics. It was demonstrated, using the combined dataset that concentration and composition of VPs in the wines correlated well with certain sensory attributes. Guaiacol was present in most samples at peri-or suprathreshold levels, but was not correlated with taint unless in combination with other phenols, in which case it was associated with 'smoky', 'ashy' and 'herbaceous' attributes. Wines with supra-threshold levels of VPs showed negative attributes ('chemical / plastic', 'tar / BR' and 'medicinal / Elastoplast™'). In some cases, sensory effects ('earthy / dusty / potato skin', 'mouldy / musty' and 'cooked vegetables (veg.)') could not be attributed to supra-threshold VP contamination, and therefore seemed to be due to combinations of VPs at subthreshold levels. Associations between negative attributes and historical bushfire events prior to harvest were found for a number of the wines. This study emphasizes the importance of understanding effects of VPs on wine aroma, and escalating awareness and sensitivity to these issues in the wine industry.

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Section: Introductionmentioning

confidence: 99%

Potentially Smoke Tainted Red Wines: Volatile Phenols and Aroma Attributes

McKay

Bauer

Panzeri

et al. 2019

SAJEV

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“…The three smoke treatments showed significant reductions in g s , in particular, the high-density smoke without misting (HS) treatment, which showed the lowest average reading for g s ( Table 2 ). Stomatal closure is one of the first responses to smoke exposure undertaken by plants [ 6 , 26 ], and a study by Ristic and colleagues [ 26 ] found that the time required for g s to recover following one hour of smoke exposure for Cabernet Sauvignon grapevines was approximately 6–10 days. A previous study by Bell et al [ 6 ] found that g s of potted Cabernet Sauvignon grapevines had returned to 60% of pre-smoke exposure rate following fifteen min exposure to smoke using Tasmanian blue gum ( Eucalyptus globulus L.) leaves as fuel, while rates had returned to 80% of pre-smoke values following exposure to smoke derived from Coast Live Oak ( Quercus agrifolia Née) leaves.…”

Section: Discussionmentioning

confidence: 99%

“…From a physiological point of view, smoke exposure has also been shown to decrease stomatal conductance in leaves, which may result from the reaction of carbon dioxide (CO 2 ) and carbon monoxide (CO) with water vapor in the substomatal cavity producing carbonic acid (H 2 CO 3 ) [ 24 , 25 ]. Carbonic acid reduces the pH in the stomata, resulting in partial or complete stomatal closure [ 25 , 26 ]. Damage to leaf surfaces following smoke exposure has also been observed, with the development of necrotic lesions or, in extreme cases, total leaf necrosis [ 10 , 22 , 27 ].…”

Section: Introductionmentioning

confidence: 99%

Classification of Smoke Contaminated Cabernet Sauvignon Berries and Leaves Based on Chemical Fingerprinting and Machine Learning Algorithms

Summerson

Viejo

Szeto

et al. 2020

Sensors

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Wildfires are an increasing problem worldwide, with their number and intensity predicted to rise due to climate change. When fires occur close to vineyards, this can result in grapevine smoke contamination and, subsequently, the development of smoke taint in wine. Currently, there are no in-field detection systems that growers can use to assess whether their grapevines have been contaminated by smoke. This study evaluated the use of near-infrared (NIR) spectroscopy as a chemical fingerprinting tool, coupled with machine learning, to create a rapid, non-destructive in-field detection system for assessing grapevine smoke contamination. Two artificial neural network models were developed using grapevine leaf spectra (Model 1) and grape spectra (Model 2) as inputs, and smoke treatments as targets. Both models displayed high overall accuracies in classifying the spectral readings according to the smoking treatments (Model 1: 98.00%; Model 2: 97.40%). Ultraviolet to visible spectroscopy was also used to assess the physiological performance and senescence of leaves, and the degree of ripening and anthocyanin content of grapes. The results showed that chemical fingerprinting and machine learning might offer a rapid, in-field detection system for grapevine smoke contamination that will enable growers to make timely decisions following a bushfire event, e.g., avoiding harvest of heavily contaminated grapes for winemaking or assisting with a sample collection of grapes for chemical analysis of smoke taint markers.

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“…Alternatively, other visual scales with a varying number of predefined categories have been proposed (Table ). Roberto et al () shortened the OIV descriptor code to a three‐category scale, a similar approach to those used by Kasimatis et al (), Miele et al () and Ristic et al (). Another visual scale proposes to classify bunches into four categories of growing value of compactness (El‐Banna and Weaver ), and other studies propose different five‐category ratings (Christodoulou et al , Hopping , Firoozabady and Olmo ).…”

Section: How Is Bunch Compactness Evaluated?mentioning

confidence: 99%

What do we know about grapevine bunch compactness? A state-of-the-art review

Tello

Ibáñez

2017

Australian Journal of Grape and Wine Research

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Bunch compactness (or density) is a grapevine specific trait that affects the commercial quality and sanitary status of wine and tablegrapes. Compact bunches are more susceptible to diverse pests and diseases such as Botrytis bunch rot and their berries ripen more heterogeneously, causing important economic losses through a reduction in crop yield and grape and wine quality. Bunch compactness is determined by the fraction of the morphological volume of the bunch that is filled by berries, but this simple definition contrasts sharply with the difficulty to measure it. While there are several objective and quantitative methods available to measure bunch compactness, the lack of a consistent approach between researchers makes comparing measurements difficult. The complexity of bunch compactness initially arises from the several bunch and berry traits that influence it, and from the distinct effects that these traits may cause in different cultivars. In addition to this genetic effect, diverse environmental signals impact on bunch compactness by affecting those primary factors that contribute to the solid component of the bunch (berry number, berry size) or to its spatial arrangement (rachis architecture). Last, several viticultural approaches, including agronomic techniques and growth regulators, have also proven to affect bunch compactness in different ways. This review aims to discuss present knowledge about this relevant grapevine trait.

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Impact of grapevine exposure to smoke on vine physiology and the composition and sensory properties of wine

Cited by 47 publications

References 33 publications

Potentially Smoke Tainted Red Wines: Volatile Phenols and Aroma Attributes

Potentially Smoke Tainted Red Wines: Volatile Phenols and Aroma Attributes

Classification of Smoke Contaminated Cabernet Sauvignon Berries and Leaves Based on Chemical Fingerprinting and Machine Learning Algorithms

What do we know about grapevine bunch compactness? A state-of-the-art review

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