Macrowine 2021
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

Related articles…

Phenolic composition of Tempranillo Blanco grapes changes after foliar application of urea

Our research aimed to determine the effect and efficiency of foliar application of urea on the phenolic composition of Tempranillo Blanco grapes. The field experiment was carried out in 2019 and 2020 seasons and the plot was located in D.O.Ca Rioja (North of Spain). The vineyard was Vitis vinifera L. Tempranillo Blanco and grafted on Richter-110 rootstock. The treatments were control (C), whose plants were sprayed with water and three doses of urea: plants were sprayed with urea 3 kg N/ha (U3), 6 kg N/ha (U6) and 9 kg N/ha (U9). The applications were performed in two phenological stages, pre-veraison (Pre) and veraison (Ver). Also, each of the treatments was repeated one week later. Control and treatments were performed in triplicate and arranged in a randomised block design. Grapes were harvested at optimum ripening stage. High-performance liquid chromatography was used to analyse the phenolic composition of the grapes. Finally, the results obtained from the analytical determinations – flavonols, flavanols and non-flavonoid (hydroxybenzoic acids, hydroxycinnamic acids and stilbenes) – were studied statistically by analysis of variance. The results showed that, in 2019, U6-Pre and U9-Pre treatments increased the hydroxybenzoic acid content in grapes, and also all foliar treatments applied at Pre enhanced the stilbene concentration. Moreover, U3-Ver was the only treatment that rose flavonol and stilbene contents in the Tempranillo Blanco grapes. In 2020, all treatments applied at Pre enhanced the flavonol concentration in grapes. Furthermore, U3-Pre and U9-Pre treatments increased stilbene content in grapes. Nevertheless, the hydroxybenzoic acid content was improved by U6-Ver and U9-Ver and besides, hydroxycinnamic acid concentration in grapes was increased by all treatments applied at Ver. In conclusion, the lower and highest dose of urea (U3 and U9), applied at pre-veraison, were the best treatments to improve the Tempranillo Blanco grape phenolic composition.

Spatial determination of areas in the Western Balkans region favorable for organic production

In problematic conditions for production of grapes and wine caused by the COVID-19 pandemic and the resulting occurrence of wine surpluses, producers are increasingly turning to the innovative viticulture and winemaking of products that are more appealing to the market and the consumers. On the other hand, consumption of the food safety or organic products, and therefore of organic grapes and wine, is increasingly common in the world, in particular in Europe. The Regional Rural Development Standing Working Group (SWG RRD), as a regional intergovernmental organization gathers actors in the viticulture and winemaking sector from states and territories of the Western Balkans (South-East Europe) in the Expert Working Group for Wine, with the aim of improving viticulture and winemaking in this region through joint activities. In accordance with the aforementioned, the SWG RRD is working on advancing organic production of grapes and wine, and on recognition of specificities of the terroir of wine-growing areas in Western Balkans. In addition, as part of the project “Facilitation of Exchange and Advice on Wine Regulations in Western Balkan Countries” helmed by the German Federal Ministry of Food and Agriculture, in addition to harmonization of relevant legislation with EU regulations, efforts are being invested towards recognition of organic wines. Within activities and project implemented by this organization, expert analyses and scientific research of the terroir of Western Balkans were carried out, and some of the results are presented in this paper.

How does aromatic composition of red wines, resulting from varieties adapted to climate change, modulate fruity aroma?

One of the major issues for the wine sector is the impact of climate change linked to the increasing temperatures which affects physicochemical parameters of the grape varieties planted in Bordeaux vineyard and consequently, the quality of wine. In some varietals, the attenuation of their fresh fruity character is accompanied by the accentuation of dried-fruit notes [1]. As a new adaptive strategy on climate change, some winegrowers have initiated changes in the Bordeaux blend of vine varieties [2]. This study intends to explore the fruitiness in wines produced from grape varieties adapted to the future climate of Bordeaux. 10 commercial single–varietal wines from 2018 vintage made from the main grape varieties in the Bordeaux region (Cabernet franc, Cabernet-Sauvignon and Merlot) as well as from indigenous grape varieties from the Mediterranean basin, such as Cyprus (Yiannoudin), France (Syrah), Greece (Agiorgitiko and Xinomavro), Portugal (Touriga Nacional) and Spain (Garnacha and Tempranillo), were selected among 19 samples using sensory descriptive analyses. Both sensory and instrumental analyses were coupled, to investigate their fruity aroma expression. For sensory analysis, samples were prepared from wine, using a semi preparative HPLC method which preserves wine aroma and isolates fruity characteristics in 25 specific fractions [3,4]. Fractions of interest with intense fruity aromas were sensorially selected for each wine by a trained panel and mixed with ethanol and microfiltered water to obtain fruity aromatic reconstitutions (FAR) [5]. A free sorting task was applied to categorize FAR according to their similarities or dissimilarities, and different clusters were highlighted. Instrumental analysis of the different FAR and wines demonstrated variations in their molecular composition. Results obtained from sensory and gas chromatography analysis enrich the knowledge of the fruity expression of red wines from “new” grape varieties opening up new perspectives in wine technology, including blending, thus providing new tools for producers.

Delaying irrigation initiation linearly reduces yield with little impact on maturity in Pinot noir

When to initiate irrigation is a critical annual management decision that has cascading effects on grapevine productivity and wine quality in the context of climate change. A multi-site trial was begun in 2021 to optimize irrigation initiation timing using midday stem water potential (ψstem) thresholds characterized as departures from non-stressed baseline ψstemvalues (Δψstem). Plant material, vine and row spacing, and trellising systems were concomitant among sites, while vine age, soil type, and pruning systems varied. Five target Δψstem thresholds were arranged in an RCBD and replicated eight times at each site: 0.2, 0.4, 0.6, 0.8, and 1.0 MPa (T1, T2, T3, T4, and T5, respectively). When thresholds were reached, plots were irrigated weekly at 70% ETc. Yield components and berry composition were quantified at harvest. To better generalize inferences across sites, data were analyzed by ANOVA using a mixed model including site as a random factor. Across sites, irrigation was initiated at Δψstem = 0.24, 0.50, 0.65, 0.93, and 0.98 MPa for T1, T2, T3, T4, and T5, respectively. Consistent significant negative linear trends were found for several key yield and berry composition variables. Yield decreased by 12.9, 15.9, 19.5, and 27.4% for T2, T3, T4, and T5, respectively, compared to T1 (p < 0.0001) across sites that were driven by similarly linear reductions in berry weight (p < 0.0001). Comparatively, berry composition varied little among treatments. Juice total soluble solids decreased linearly from T1 to T5 – though only ranged 0.9 Brix (p = 0.012). Because producers are paid by the ton, and contracts simply stipulate a target maturity level, first-year results suggest that there is no economic incentive to induce moderate water deficits before irrigation initiation, regardless of vineyard site. Subsequent years will further elucidate the carryover effects of delaying irrigation initiation on productivity over the long term.

A multidisciplinary approach to evaluate the effects of the training system on the performance of “Aglianico del Vulture” vineyards

Vineyards are complex agro-ecosystems with high spatial and temporal variability. An efficient training system may counteract the adverse effects of this variability. Moreover, considering the climate change issues, choosing an efficient training system that enhances water use and protects the vines from radiative thermal stress has become a priority for the farmers. A multidisciplinary approach that assesses the soil-crop-yield-wine relationships of vineyards in a distributed and holistic way could bring added knowledge on the behavior of the different training systems. This ongoing research aimed to implement a multidisciplinary approach to study the behavior of “Aglianico del Vulture” grapevines trained with two different systems: a spurred cordon (SC) and an “Alberello in parete” (AL), grown in a high-quality wine production area of Basilicata region (Italy). The approach merged several methods and scales of soil, ecophysiology, must/wine quality, and spectral data collection to assess the influence of the training system. Homogeneous zones (HZs) in both training systems were defined through a procedure based on geomorphological classification, unmanned aerial vehicles (UAV) images analysis, and a traditional soil survey supported by geophysical scanning. During the 2021 season, TDR probes monitored soil water content, while grapevine health status was assessed using eco-physiological measurements (LWP, chlorophyll content, PSII photosynthetic efficiency, LAI, and point-based field spectroscopy). These grapevine in-vivo measurements validated the spectral vegetation indexes (NDVI, RENDVI, CVI, and TVI) derived from the UAV multispectral imagery, which monitored the grapevine status in a distributed and non-invasive way. Grape yield, quality of berries, must and wine were measured to assess the effects of the training systems. The first experimental year results showed the variability of the vineyards and revealed relationships among soil parameters, crop characteristics, and vegetation indices of the SC and AL training systems. This multidisciplinary study could bring new insights into the vineyard training system’s effects on grape yield and wine quality.