terclim by ICS banner
IVES 9 IVES Conference Series 9 International Congress on Grapevine and Wine Sciences 9 2ICGWS-2023 9 Applicability of spectrofluorometry and voltammetry in combination with machine learning approaches for authentication of DOCa Rioja Tempranillo wines

Applicability of spectrofluorometry and voltammetry in combination with machine learning approaches for authentication of DOCa Rioja Tempranillo wines

Abstract

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to  region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).

Linear sweep voltammetry (using disposable carbon paste electrodes) and A-TEEM signals of 132 Tempranillo red wines were acquired. Data were analysed following non-supervised statistical strategies such as principal component analysis (PCA) to reduce the number of variables, and two-way ANOVA (origin and category) and supervised modeling strategies derived from machine learning algorithms.

The voltammogram in the region of 691-771 mV provided clear classification of the three ageing categories and Rioja Oriental and Rioja Alavesa/Alta could be separated, but Alavesa could not be differentiated from Alta based on voltammetric signals. Results showed that A-TEEM was more efficient in classifying subareas and ageing categories of Tempranillo Rioja wines, with an ML approach using extreme gradient boosting discriminant analysis (XGBDA) providing 100% correct class assignment for subregion and wine category. A-TEEM coupled with ML algorithms is presented as a powerful and rapid approach to classify Tempranillo Rioja wines according to their origin and style of ageing.

Acknowledgements: This project was funded by the Corporation DOCa Rioja and the José Castillejo program through the Ministerio de Universidades: Programa Estatal de Promoción del Talento y su Empleabilidad en I+D+i, Subprograma Estatal de Movilidad, del Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 (CAS21/00221).

DOI:

Publication date: October 13, 2023

Issue: ICGWS 2023

Type: Poster

Authors

M. P. Sáenz-Navajas1*, S. Bastian2, D. W. Jeffery2

1Instituto de Ciencias de la Vid y del Vino (Universidad de La Rioja-Consejo Superior de Investigaciones Científicas-Gobierno de La Rioja). Departamento de Enología, Logroño, La Rioja, Spain
2School of Agriculture, Food and Wine, The University of Adelaide, PMB 1, Glen Osmond, South Australia 5064, Australia

Contact the author*

Keywords

designated origin, A-TEEM, extreme gradient boosting, classification, red wine, statistical modeling

Tags

2ICGWS | ICGWS | ICGWS 2023 | IVES Conference Series

Citation

Related articles…

Drought responses of grapevine cultivars under different environments

Using grapevine genetic diversity is one of the strategies to adapt viticulture to climate change. In this sense, assessing the plasticity of cultivars in their responses to environmental conditions is essential. For this purpose, the drought tolerance of Grenache, Tempranillo and Semillon cultivars grafted onto SO4 was evaluated at two experimental vineyards, one located in Valencia (Spain) and the other in Bordeaux (France). This was done by assessing gas exchange parameters, water relations and leaf hydraulic traits at the end of the season.

Model-assisted analysis of the root traits underlying RSA genotypic diversity in Vitis: a promising approach for rootstock selection?

By dissecting the root system architecture (RSA) into its underpinning components (e.g. root emission, axial growth, radial growth, branching, root direction or tropism) and identifying the relationships between them, functional-structural 3D root models are promising tools for analyzing the diversity and complexity of root system phenotypes with Genotype × Environment interactions. The model parameters are assumed to be synthetic traits, less influenced by the environment, and consequently with less polygenic architectures than the integrative RSA traits they drive. Root models can serve as a basis for in silico development of root system ideotypes by highlighting the developmental processes and parameters that most likely influence RSA fitness.

Impact of polyclonal selection for abiotic stress tolerance on the yield and must quality traits of grapevine varieties

The effects of climate change in viticulture are currently a major concern, with heat waves and drought affecting yield, wine quality, and in extreme cases, even plant survival. Ancient grapevine varieties have high intravarietal genetic variability that so far has been explored successfully to improve yield and must quality. Currently, there is little information available on intravarietal variability regarding responses to stress. In the current work, the intravarietal genetic variability of several Portuguese varieties was studied for yield, must quality, and tolerance to abiotic stress, through indirect, rapid, and nondestructive measurements carried out in the field.

Antimicrobial activity of oenological polyphenols against Gram positive and Gram negative intestinal multidrug-resistant bacteria

Bacterial antibiotic resistance is a major current health problem. Polyphenols have demonstrated antibacterial activity, and in this work we studied the effect of oenological polyphenols on the growth of intestinal multidrug-resistant strains of human and animal origin. Two Enterococcus faecium strains, resistant to vancomycin and other antibiotics, and four Escherichia coli strains, resistant to ampicillin and other antibiotics, were included in this study. All strains showed multidrug resistant phenotypes and genotypes to at least two antibiotic families.

A novel approach for the identification of new biomarkers of wine consumption in human urine using untargeted metabolomics

Wine is one of the most representative components of Mediterranean diet. Moderate wine intake together with food, has been positively correlated with reduced risk of many chronic diseases. This beneficial effect seems to be ascribed to elevated polyphenolic content of wine [1]. Traditional approaches for the identification of wine biomarkers consumption include targeted metabolomics that focuses on the quantification of well-defined metabolites, losing a valuable information about a massive number of compounds. On the other hand, untargeted metabolomics can disclose a large quantity of signals corresponding to potential biomarkers in a single analysis with high sensitivity and resolution.