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…

Grape berry size is a key factor in determining New Zealand Pinot noir wine composition

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

First step in the preparation of a soil map of the Protected Designation of Origin Valdepeñas (Central, Spain)

This work is a first step to make a map of vineyard soils. The characterization of the soils of the Protected Designation of Origin (D.P.O.) Valdepeñas will allow to group the studied profiles according to their physico-chemical characteristics and the concentrations of most relevant chemical elements. 90 soil profiles were analysed throughout the territory and the soils were sampled and described according to FAO (2006) and classified according to and Soil Taxonomy (2014). All samples were air dried, sieved and some physico-chemical parameters were determined following standard protocols. Also, major and trace elements were analysed by X-ray fluorescence. The statistically study was made using the SPSS program. Trend maps were made using the ArcGIS program. The studied soils have the following average properties: pH, 8.3; electrical conductivity, 0,20 dS/m (low); clay, 18.8% (medium) and CaCO3, 17.1% (high). In the study for the major elements. The major elements of these soils are Si, followed by Ca and Al, with an average content of 203.7 g/kg, 105.5 g/kg and 74.0 g/kg respectively. On the other hand, 27 trace elements have been studied. Of all of them, it can be highlighted the average values of Ba (361.8 mg/kg), Sr (129.3 mg/kg), Rb (83.4 mg/kg), V (74.2 mg/kg) and Ce (70.6 mg/kg). Ba, V and Ce values are higher and the values of Sr and Rb are lower to those found in the literature. The discriminant analysis shows a percentage of grouping of 91%. The content of chemical elements together with the physico-chemical characteristics allows grouping the soils in 4 group according to their order in the classification to Soil Taxonomy; due to the importance of the Calcisols in Castilla-La Mancha, it has been decided to establish them as their own group even if they do not appear in Soil Taxonomy classification.

Differential responses of red and white grape cultivars trained to a single trellis system – the VSP

Commercial grape production relies on training grapevine cultivars onto a variety of trellis systems. Training allows for well-lit leaves and clusters, maximizing fruit quality in addition to facilitating cultivation, harvesting, and diseases control. Although grapevines can be trained onto an infinite variety of trellis systems, most red and white cultivars are trained to the standard VSP (Vertical Shoot Positioning) system. However, red and white cultivars respond differently to VSP in fruit composition and growth characteristics, which are yet to be fully understood. Therefore, the objective of this study was to examine the influence of the VSP trellis system on fruit composition of three red, Cabernet Sauvignon, Merlot and Syrah, and three white, Chardonnay, Riesling, and Gewurztraminer cultivars grown under uniform growing conditions in the same vineyard. All cultivars were monitored for maturity and harvested at their physiologically maximum possible sugar concentration to compare various fruit quality attributes such as Brix, pH, TA, malic and tartaric acids, glucose and fructose, potassium, YAN, and phenolic compounds including total anthocyanins, anthocyanin profile, and tannins. A distinct pattern in fruit composition was observed in each cultivar. In regards to growth characteristics, Syrah grew vigorously with the highest cluster weight. Although all cultivars developed pyriform seeds, the seed size and weight varied among all cultivars. Also varied were mesocarp cell viability, brush morphology, and cane structure. This knowledge of the canopy architectural characteristics assessed by the widely employed fruit compositional attributes and growth characteristics will aid the growers in better management of the vines in varied situations.

The interplay between grape ripening and weather anomalies – A modeling exercise

Current climate change is increasing inter- and intra-annual variability in atmospheric conditions leading to grapevine phenological shifts as well altered grape ripening and composition at ripeness. This study aims to (i) detect weather anomalies within a long-term time series, (ii) model grape ripening revealing altered traits in time to target specific ripeness thresholds for four Vitis vinifera cultivars, and (iii) establish empirical relationships between ripening and weather anomalies with forecasting purposes. The Day of the Year (DOY) to reach specific grape ripeness targets was determined from time series of sugar concentrations, total acidity and pH collected from a private company in the period 2009-2021 in North-Eastern Italy. Non-linear models for the DOY to reach the specified ripeness thresholds were assessed for model efficiency (EF) and error of prediction (RMSE) in four grapevine cultivars (Merlot, Cabernet Sauvignon, Glera and Garganega). For each vintage and cultivar, advances or delays in DOY to target specified ripeness thresholds were assessed with respect to the average ripening dynamics. Long-term meteorological series monitored at ground weather station by means of hourly air temperature and rainfall data were analyzed. Climate statistics were obtained and for each time period (month, bimester, quarter and year) weather anomalies were identified. A linear regression analysis was performed to assess a possible correlation that may exist between ripening and weather anomalies. For each cultivar, ripeness advances or delays expressed in number of days to target the specific ripening threshold were assessed in relation to registered weather anomalies and the specific reference time period in the vintage. Precipitation of the warmest month and spring quarter are key to understanding the effect of climate change on sugar ripeness. Minimum temperatures of May-June bimester and maximum temperatures of spring quarter best correlate with altered total acidity evolution and pH increment during the ripening process, respectively.

Upscaling the integrated terroir zoning through digital soil mapping: a case study in the Designation of Origin Campo de Borja

homogeneous zones by intersecting several partial zonings of major factors that influence vineyard growth. Each of them follows specific process from their corresponding disciplines. Soil zoning specifically refers to a Soil Resource Inventory map that has traditionally been generated by conventional soil mapping methods. These methods have shortcomings in reaching fine cartographic and categorical details and involve significant expenses, which undermines their applicability. A new framework named Digital Soil Mapping has introduced quantitative models by statistical techniques to establish soil-landscape relationships and is able to provide intensive scale cartography.

In the present study, a microzoning at 1:10.000 scale is generated from an initial zoning, where the conventional soil map with polytaxic map units is replaced by a new one from digital techniques that disaggregates them. The comparison between the zonings considers a quantitative evaluation of capability for each Homogeneous Terroir Unit by means of the Viticultural Quality Index and its categorization based on its distribution by map. The spatial intersection of both maps gives rise to a confusion matrix in which the flows of class variations after the substitution are assessed.

The results show a five-fold increase in the number of Homogeneous Terroir Units identified and a larger differentiation among them, evidenced by a wider range in the capability index distribution. Both elements are accompanied by an increase in the detection of areas of higher potential within previously undervalued uniform zones.These features are a direct effect of the improvements brought by Digital Soil Mapping techniques and would verify the advantages of their implementation in the Integrated Terroir zoning. Eventually, such new highly detailed terroir units would benefit precision viticulture and sustainable management practices.