Dataset Information

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

ABSTRACT: 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.

SUBMITTER: Summerson V

PROVIDER: S-EPMC7571113 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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

Summerson Vasiliki V Gonzalez Viejo Claudia C Szeto Colleen C Wilkinson Kerry L KL Torrico Damir D DD Pang Alexis A De Bei Roberta R Fuentes Sigfredo S

Sensors (Basel, Switzerland) 20200907 18

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 t ...[more]

PMID: 32906800

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Project description:BackgroundWater deficit has significant effects on grape berry composition resulting in improved wine quality by the enhancement of color, flavors, or aromas. While some pathways or enzymes affected by water deficit have been identified, little is known about the global effects of water deficit on grape berry metabolism.ResultsThe effects of long-term, seasonal water deficit on berries of Cabernet Sauvignon, a red-wine grape, and Chardonnay, a white-wine grape were analyzed by integrated transcript and metabolite profiling. Over the course of berry development, the steady-state transcript abundance of approximately 6,000 Unigenes differed significantly between the cultivars and the irrigation treatments. Water deficit most affected the phenylpropanoid, ABA, isoprenoid, carotenoid, amino acid and fatty acid metabolic pathways. Targeted metabolites were profiled to confirm putative changes in specific metabolic pathways. Water deficit activated the expression of numerous transcripts associated with glutamate and proline biosynthesis and some committed steps of the phenylpropanoid pathway that increased anthocyanin concentrations in Cabernet Sauvignon. In Chardonnay, water deficit activated parts of the phenylpropanoid, energy, carotenoid and isoprenoid metabolic pathways that contribute to increased concentrations of antheraxanthin, flavonols and aroma volatiles. Water deficit affected the ABA metabolic pathway in both cultivars. Berry ABA concentrations were highly correlated with 9-cis-epoxycarotenoid dioxygenase (NCED1) transcript abundance, whereas the mRNA expression of other NCED genes and ABA catabolic and glycosylation processes were largely unaffected. Water deficit nearly doubled ABA concentrations within berries of Cabernet Sauvignon, whereas it decreased ABA in Chardonnay at véraison and shortly thereafter.ConclusionThe metabolic responses of grapes to water deficit varied with the cultivar and fruit pigmentation. Chardonnay berries, which lack any significant anthocyanin content, exhibited increased photoprotection mechanisms under water deficit conditions. Water deficit increased ABA, proline, sugar and anthocyanin concentrations in Cabernet Sauvignon, but not Chardonnay berries, consistent with the hypothesis that ABA enhanced accumulation of these compounds. Water deficit increased the transcript abundance of lipoxygenase and hydroperoxide lyase in fatty metabolism, a pathway known to affect berry and wine aromas. These changes in metabolism have important impacts on berry flavor and quality characteristics. Several of these metabolites are known to contribute to increased human-health benefits.

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Dataset Information

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

Publications

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

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