 IVES 9 IVES Conference Series 9 Prediction of sauvignon blanc quality gradings with static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) and machine learning

Prediction of sauvignon blanc quality gradings with static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS) and machine learning

Abstract

AIM: The main goal of the current study is the development of a cost-effective and easy-to-use method suitable for use in the laboratory of commercial wineries to analyze wine aroma. Additionally, this study attempted to establish a prediction model for wine quality gradings based on their aroma, which could reveal the important aroma compounds that correlate well with different grades of perceived quality

METHODS: Parameters of the SHS−GC−IMS instrument were first optimized to acquire the most desirable chromatographic resolution and signal intensities. Method stability was then exhibited by repeatability and reproducibility. Subsequently, compound identification was conducted. After method development, a total of 143 end-ferment wine samples of three different quality gradings from vintage 2020 were analyzed with the SHS−GC−IMS instrument. Six machine learning methods were employed to process the results and construct a quality prediction model. Techniques that aim to explain the model to extract useful insights were also applied.

RESULTS: The SHS−GC−IMS method was able to detect 23 compounds among 65 peaks, mostly esters and higher alcohols, using the current instrumentation. Several identified compounds, including methyl acetate, ethyl formate, and amyl acetate, have seldomly been reported in Sauvignon Blanc wines before. The method also indicated decent repeatability and reproducibility, both of which were below 10%. The quality prediction model was successfully established using artificial neural network (ANN) based on all peaks regardless of their identity. The model returned a highly satisfactory prediction accuracy of 95.4% using 10-fold cross-validation. SHapley Additive exPlanations (SHAP) values was used to delineate the prediction mechanism of the model. SHAP values revealed that isoamyl acetate, ethyl decanoate, ethyl octanoate and 1-hexanol were positively linked to better quality, whereas hexyl acetate, isoamyl alcohol, and 1-butanol could lower the quality grading.

CONCLUSIONS:

This study has successfully developed a method alternative to GC−MS based instruments for the non-targeted screening of wine volatile compounds. With its simple design featuring a headspace sampling unit, highly simplified sample preparation, and nitrogen being the only gas supply, the instrument has shown outstanding practicality desired by commercial winery laboratories. The powerful prediction model and the insights extracted by SHAP values could serve as a starting point for winemakers to investigate the effects of winemaking operations on the expression of the volatiles shown to correlate with higher gradings, to enhance the quality of wines. The findings of this study have been published as an original research article in the Journal of Agricultural and Food Chemistry: J. Agric. Food Chem. 2021, 69(10), 3255−3265.

DOI:

Publication date: September 22, 2021

Issue: Macrowine 2021

Type: Article

Authors

Wenyao Zhu , Frank BENKWITZ, Paul A. KILMARTIN,

School of Chemical Sciences, University of Auckland, Private Bag 92019, Auckland, New Zealand; Drylands Winery, Constellation Brands NZ, Blenheim 7273, New Zealand.

Contact the author

Keywords

Sauvignon blanc, static headspace−gas chromatography−ion mobility spectrometry (SHS−GC−IMS), quality grading, machine learning, artificial neural network (ANN), model explanation

Citation

Drought effect on aromatic and phenolic potential of seven recovered grapevine varieties in Castilla-La Mancha region (Spain)

The effects of climate change are seriously affecting the quality of wine grapes. High temperatures and drought cause imbalances in the chemical composition of grapes. The result is overripe grapes with low acidity and high sugar content, which produce wines with excessive alcohol content, lacking in freshness and not very aromatic. As a consequence, the search of varieties with capacity of produce quality grapes in adverse climate conditions is a good alternative to preserve the sustainability of vineyards. In this work, quality parameters of seven Vitis vinifera L. cultivars (five whites and two reds) recently recovered from extinction and grown under two different hydric regimes (rainfed and irrigated) were analyzed during the 2020 vintage. At harvest time, weight of 100 berries, must physicochemical parameters (brix degree, total acidity, malic acid, pH), and carbon and oxygen isotope ratios (δ13C, δ18O) were determined. Subsequently, varietal aroma potential index (IPAv) and total polyphenol index (TPI) were analyzed. Quality parameters, IPAv and TPI, showed significant differences between varieties and water regimes. Both red varieties, Moribel and Tinto Fragoso, stood out for their high aromatic and phenolic potential, which was higher under rainfed regime. Regarding to white varieties, Montonera del Casar and Jarrosuelto stood out in terms of varietal aroma potential. Montonera del Casar high acidity in its musts and Jarrosuelto showed the highest berry weights.

Can varietal ‘apricot’ aroma of Viognier wine be controlled with clonal selection and harvest timing?

Recent wine-like reconstitution sensory studies confirmed that several monoterpenes were the key aroma compounds in the perception of an ‘apricot’ aroma attribute in Viognier wine.

Revisiting esters hydrolysis in young white wines

Esters play an essential role in the young white wines’ fruity expression, particularly the groups of ethyl esters of fatty acids (EEFAs) and higher alcohol acetates (HAAs) [1]. However, generally, these groups of esters decrease relatively fast during the first two years of ageing [1, 2].

Territorial delimitation of viticultural “Oltrepo Pavese (Lombardy)” using grape ripening precocity

L’Oltrepò Pavese est une zone de collines de la Lombardie, région située au nord de l’Italie avec un vignoble qui s’étend sur près de 15 000 ha. Cette zone représente la plus grande aire de production de la région et une des A.O.C. les plus étendues de tout le pays. Les cépages les plus cultivés, même historiquement, sont autochtones : la Barbera et la Croatina utilisés pour la production de vin rouge «Oltrepò» et le Pinot noir pour la production de vins mousseux. Pour le zonage viticole de cette A.O.C., il a été pris en considération: le climat, les sols, les caractéristiques viti-vinicoles.

Quantifying water use diversity across grapevine rootstock-scion combinations

Vines require proper light levels, temperature, and water availability, and climate change is modifying these factors, hampering yield and quality. Despite the large diversity of rootstocks, varieties, and clones, we still lack knowledge of their combined effects and potential role in a warmer and dryer future. Therefore, we aim to characterize some of the existing diversity of rootstocks and genotypes and their interaction at the eco-physiological level, combining stomatal conductance (gs) and chlorophyll a fluorescence analysis.