IVAS 2022 banner
IVES 9 IVES Conference Series 9 IVAS 9 IVAS 2022 9 Discrimination of monovarietal Italian red wines using derivative voltammetry

Discrimination of monovarietal Italian red wines using derivative voltammetry

Abstract

Identification of specific analytical fingerprints associated to grape variety, origin, or vintage is of great interest for wine producers, regulatory agencies, and consumers. However, assessing such varietal fingerprint is complex, time consuming, and requires expensive analytical techniques. Voltammetry is a fast, cheap, and user-friendly analytical tool that has been used to investigate and measure wine phenolics. In this work linear sweep voltammetry with different multivariate analysis tools (PCA, LDA, KNN, Random Forest, SVM) has been exploited to discriminate and classify Italian red wines from 10 different varieties.A total of 131 monovarietal Italian red wines vinified in 2015 or 2016 were collected from wineries across Italy. The varieties are: Aglianico, Cannonau, Corvina, Montepulciano, Nebbiolo, Primitivo, Raboso, Sagrantino, Sangiovese, and Teroldego. The wines of the same variety came from the same region. Linear sweep voltammograms were collected using a PalmSense3 potentiostat and disposable Screen-Printed Carbon Electrodes. The derivative voltammograms were obtained with a Savitzky Golay smoothing filter.The results obtained indicated a great diversity of voltammetric responses, but with raw data it was not possible to identify electrochemical features that discriminated the varieties. To obtain a higher discriminant ability first and second order derivative voltammogram were built.The second order derivative voltammograms (2DV) show similar trends within the same variety, in particular the varieties appear to be divided by the potential and intensity of the first peak (180-370 mV).From the PCA of 2DV (explained variance 78% with the first two components) 3 regions of the voltammograms that mainly contribute to PC1 and 4 to PC2 can be identified. Five of these regions (3 for PC1 and 2 for PC2) are at potentials lower than 600 mV, the region associated to the more easily oxidizable compounds. PC1 vs PC2 of the second order derivative voltammetry shows 3 groups with a visible separation of Nebbiolo and Teroldego from the other varieties.The best classification result has been obtained with a PCA-LDA of 2DV using the first 5 PC scores as predictors with an overall accuracy in calibration of 77.9% and an overall accuracy in prediction of 66.7%. The best accuracy has been obtained for varieties Nebbiolo, Teroldego and Sangiovese. The classification of two varieties (Cannonau and Primitivo) resulted problematic both in calibration and in prediction. To conclude, linear sweep voltammetry coupled to chemometric can be a suitable analytical tool technique for the classification of monovarietal red wines in a fast, cheap, and easy-to-use way. In addition, second-order derivative deconvolution of the voltammograms has been proven to be a suitable data pre-processing method for the interpretation of voltammograms from complex matrixes that are rich in oxidable compounds such as red wine.

DOI:

Publication date: June 27, 2022

Issue: IVAS 2022

Type: Poster

Authors

Vanzo Leonardo1, Slaghenaufi Davide1, Nouvelet Lea1, Curioni Andrea2, Giacosa Simone3, Mattivi Fulvio4, Moio Luigi5 and Versari Andrea5

1Department of Biotechnology, University of Verona, Italy
2Department of Agronomy, Food, Natural Resources, Animals and Environment (DAFNAE), University of Padova, Italy
3Dipartimento di Scienze Agrarie, Forestali e Alimentari, Università degli Studi di Torino, Italy
4Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Italy
5Department of Agricultural Sciences, Division of Vine and Wine Sciences, University of Naples Federico II, Avellino, Italy

Contact the author

Keywords

Derivative Voltammetry, Varietal Identity, Wine Fingerprinting, Authenticity, Red Wine

Tags

IVAS 2022 | IVES Conference Series

Citation

Related articles…

Elucidating vineyard site contributions to key sensory molecules: Identification of correlations between elemental composition and volatile aroma profile of site-specific Pinot noir wines

The reproducibility of elemental profile in wines produced across multiple vintages has been previously reported using grapes from a single scion clone of Vitis vinifera L. cv. Pinot noir. The grapevines were grown on fourteen different vineyard sites, from Oregon to southern California in the U.S.A., which span distances from approximately hundreds of meters to 1450 km, while elevations range from near sea level to nearly 500 m. In addition, sensorial (i.e. aroma, taste, and mouthfeel) and chemical (i.e. polyphenolic and volatile) differences across the different vineyard sites have also been observed among these wines at two aging time points. While strong evidence exists to support that grapes grown in different regions can produce wines with unique chemical and sensorial profiles, even when a single clone is used, the understanding of growing site characteristics that result in this reproducible differentiation continues to emerge. One hypothesis is that the elemental profile that a vineyard site imparts to the grape berries and the resulting wine is an important contributor to this differentiation in chemistry and sensory of wines. For example, various classes of enzymes that catalyze the formation of key aroma compounds or their precursors require specific metals. In this work, we begin to report correlations between elemental and volatile aroma profiles of site-specific Pinot noir wines, made under standardized winemaking conditions, that have been previously shown to be distinguished separately by these chemical analyses.

Green berries on Gewürztraminer (Vitis vinifera L.) in South Tyrol (Italy)

The grape variety Gewürztraminer is known to be affected by two physiological disorders namely berry shrivel and bunch stem necrosis. During the season 2014 we noticed a new symptomatology type of ripening disorder on the variety. The new symptom showed not all berries fallowing the normal maturation stages, but single berries remaining at a soft but green stage till harvest. The broad distribution of these so called “green berries” symptoms in different production sites of our region, caused huge damage due to the difficulty of eliminating single berries per bunch before harvesting. Therefore, the Research Centre Laimburg began to investigate the reasons and origins of this new symptom. This work shows the results of first attempts to find causes for the symptom as well as the resulting approach to mitigate symptoms. Applications of magnesium leaf fertilizer showed first promising results against this putative disorder. To study the causal effect of the green berries 30 symptomatic vineyards in 2014 have been selected for a monitoring during the season 2016. To evaluate the foliar nutrient treatment two vineyards have been selected for application of magnesium sulfate and magnesium chloride. Leaf and berry nutrient analysis, as well as the main quality parameters during ripening have been performed. As soon as “green berries” symptoms appeared, incidence and severity have been evaluated. Most of the symptomatic vineyards of the 2016 monitoring showed light to clear magnesium deficit symptoms on their foliage. Only during the seasons 2020 and 2021 “green berries” symptoms could be found in the leaf fertilizer treatment vineyards. Both seasons showed a significant effect of the magnesium treatments to reduce the incidence and severity of the symptom. It seems that the appearance of the “green berries” symptom on Gewürztraminer is correlated to a disturbed uptake of magnesium of the vines.

Effect of partial net shading on the temperature and radiation in the grapevine canopy, consequences on the grape quality of cv. Gros Manseng in PDO Pacherenc-du-vic-Bilh

As elsewhere, southwestern France vineyards face more recurrent summer heat waves these last years. Among the possibilities of adaptation to this climate changing parameter, the use of net shading is a technique that allow for limiting canopy exposure to radiations. In this trial, we tested net shading installed on one face of the canopy, on a north-south row-oriented plot of cv. Gros Manseng trained on VSP system in the PDO Pacherenc-du-Vic-Bilh. The purpose was to characterize the effects on the ambient canopy temperatures and radiations during the season and to observe the consequences on the composition of grapes and wines. Two sorts of net were used with two levels of obstruction (50% and 75%) of the photosynthesis active radiation (PAR). They have been installed on the west side of the canopy and compared to a netless control. Temperature and PAR sensors registered hourly data during the season. On specific summer day (hot and sunny) manual measurements took also place on bunches (temperature) and in different spots of the canopy (PAR). The results showed that, on clear days, the radiation is lowered by the shade nets respecting the supplier criteria. The effects on the ambient canopy temperature were inconstant on this plot when we observed the data from the global period of shading between fruit set and harvest. However, during hot days (>30°C), the temperature in the canopy was reduced during afternoon and the temperature of the bunch surface was reduced as well comparing to the control. A decrease of the maturity parameters of the berries, sugar and acidity, was also observed. Concerning the wine aromatic potential, no differences clearly appeared.

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Spatiotemporal patterns of chemical attributes in Vitis vinifera L. cv. Cabernet Sauvignon vineyards in Central California

Spatial variability of vine productivity in winegrapes is important to characterise as both yield and quality are relevant for the production of different wine styles and products. The objectives were to understand how patterns of variability of Cabernet Sauvignon fruit composition changed over time and space, how these patterns could be characterised with indirect measurements, and how spatial patterns of the variation in fruit compositional attributes can aid in improving management. Prior to the 2017 vintage, 125 data vines were distributed across each of four vineyards in the Lodi American Viticultural Area (AVA) of California. Each data vine was sampled at commercial harvest in 2017, 2018, and 2019. Yield components and fruit composition were measured at harvest for each data vine, and maps of yield and fruit composition were produced for eight ‘objective measures of fruit quality’: total anthocyanins, polymeric tannins, quercetin glycosides, malic acid, yeast assimilable nitrogen, β-damascenone, C6 alcohols and aldehydes, and 3-isobutyl-2-methoxypyrazine. Patterns of variation in anthocyanins and phenolic compounds were found to be most stable over time. Given this relative stability, management decisions focused on fruit quality could be based on zonal descriptions of anthocyanins or phenolics to increase profitability in some vineyards. In each vineyard, dormant season pruning weights and soil cores were collected at each location, elevation and soil apparent electrical conductivity surveys were completed, and remotely sensed imagery was captured by fixed wing aircraft and two satellite platforms at major phenological stages. The data collected were used to develop relationships among biophysical data, soil, imagery, and fruit composition. The standardised and aggregated samples from four vineyards over three seasons were included in the estimation of ‘common variograms’ to assess how this technique could aid growers in producing geostatistically rigorous maps of fruit composition variability without cumbersome, single season sampling efforts.