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…

De novo Vitis champinii whole genome assembly allows rootstock-specific identification of potential candidate genes for drought and salt tolerance

Vitis champinii cultivars Ramsey and Dog-ridge are main choices for rootstocks to adapt viticulture in semi-arid and arid regions thanks to their distinctive tolerance to drought and salinity. However, genetic studies on non-vinifera rootstocks have heavily relied on the grapevine (Vitis vinifera) reference genome, which difficulted the assessment of the genetic variation between rootstock species and grapevines. In the present study, this limitation is addressed by introducing a novo phased genome assembly and annotation of Vitis champinii. This new Vitis champinii genome was employed as reference for mapping RNA-seq reads from the same species under drought and salt stresses, and for comparison the same reads were also mapped to the Vitis vinifera PN40024.V4 reference genome. A significant increase in alignment rate was gained when mapping Vitis champinii RNA-seq reads to its own genome, compared to the Vitis vinifera PN40024.V4 reference genome, thus revealing the expression levels of genes specific to Vitis champinii. Moreover, differences in coding sequences were observed in ortholog genes between Vitis champinii and Vitis vinifera, which therefore challenges previous differential expression analyses performed between contrasting Vitis genotypes on the same gene from the Vitis vinifera genome. Genes with possible implications in drought and salt tolerance have been identified across the genome of Vitis champinii, and the same genomic data can potentially guide the discovery of candidate genes specific from Vitis champinii for other traits of interest, therefore becoming a valuable resource for rootstock breeding designs, specially towards increased drought and salinity due to climate change.

Mapping and tracking canopy size with VitiCanopy

Understanding vineyard variability to target management strategies, apply inputs efficiently and deliver consistent grape quality to the winery is essential. However, despite inherent vineyard variability, the majority are managed as if they are uniform. VitiCanopy is a simple, grower-friendly tool for precision/digital viticulture that allows users to collect and interpret objective spatial information about vineyard performance. After four years of field and market research, an upgraded VitiCanopy has been created to achieve a more streamlined, technology-assisted vine monitoring tool that provides users with a set of superior new features, which could significantly improve the way users monitor their grapevines. These new features include:
• New user interface
• User authentication
• Batch analysis of multiple images
• Ease the learning curve through enhanced help features
• Reporting via the creation of colour maps that will allow users to assess the spatial differences in canopies within a vineyard.
Use-case examples are presented to demonstrate the quantification and mapping of vineyard variability through objective canopy measurements, ground-truthing of remotely sensed measurements, monitoring of crop conditions, implementation of disease and water management decisions as well as creating a history of each site to forecast quality. This intelligent tool allows users to manage grapevines and make informed management choices to achieve the desired production targets and remain profitable.

Mechanisms involved in the heating of the environment by the aerodynamic action of a wind machine to protect a vineyard against spring frost

One of the main consequences of global warming is the rise of the mean temperature. Thus, the heat summation by the plants begins sooner in the early spring, and by cumulating growing degree-days, phenological development tends to happen earlier. However, spring frost is still a recurrent phenomenon causing serious damages to buds and therefore, threatening the harvests of the winegrowers. The wind machine is a solution to protect fruit crops against spring frost that is increasingly used. It is composed of a 10-m mast with a blowing fan at its peak. By tapping into the strength of the nocturnal thermal inversion, it sweeps the crop by propelling warm air above to the ground. Thus, stratification is momentarily suppressed. Furthermore, the continuous action of the machine, alone or in synergy, or the addition of a heater allow the bud to be bathed in a warmer environment. Also, the punctual action of the tower’s warm gust reaches the bud directly at each rotation period. All these actions allow the bud to continuously warm up, but with different intensities and over a different period. Although there is evidence of the effectiveness of the wind machines, the thermal transfers involved in those mechanisms raise questions about their true nature. Field measurements based on ultrasonic anemometers and fast responding thermocouples complemented by laboratory measurements on a reduced scale model allow to characterize both the airflow produced by the wind machine and the local temperature in its vicinity. Those experiments were realized in the vineyard of Quincy, in the framework of the SICTAG project. In the future paper, we will detail the aeraulic characterization of the wind machine and the thermal effects resulting from it and we will focus on how the wind machine warms up the local atmosphere and enables to reduce the freezing risk.

Elevational range shifts of mountain vineyards: Recent dynamics in response to a warming climate

Increasing temperatures worldwide are expected to cause a change in spatial distribution of plant species along elevational gradients and there are already observable shifts to higher elevations as a consequence of climate change for many species. Not only naturally growing plants, but also agricultural cultivations are subject to the effects of climate change, as the type of cultivation and the economic viability depends largely on the prevailing climatic conditions. A shift to higher elevations therefore represents a viable adaptation strategy to climate change, as higher elevations are characterized by lower temperatures. This is especially important in the case of viticulture because a certain wine-style can only be achieved under very specific climatic conditions. Although there are several studies investigating climatic suitability within winegrowing regions or longitudinal shifts of winegrowing areas, little is known about how fast vineyards move to higher elevations, which may represent a viable strategy for winegrowers to maintain growing conditions and thus wine-style, despite the effects of climate change. We therefore investigated the change in the spatial distribution of vineyards along an elevational gradient over the past 20 years in the mountainous wine-growing region of Alto Adige (Italy). A dataset containing information about location and planting year of more than 26000 vineyard parcels and 30 varieties was used to perform this analysis. Preliminary results suggest that there has been a shift to higher elevations for vineyards in general (from formerly 700m to currently 850 m a.s.l., with extreme sites reaching 1200 m a.s.l.), but also that this development has not been uniform across different varieties and products (i.e. vitis vinifera vs hybrid varieties and still vssparkling wines). This is important for climate change adaptation as well as for rural development. Mountain areas, especially at mid to high elevations, are often characterized by severe land abandonment which can be avoided to some degree if economically viable and sustainable land management strategies are available.

Effect of multi-level and multi-scale spectral data source on vineyard state assessment

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.