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The Terroir Concept Interpreted through Grape Berry Metabolomics and Transcriptomics
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Exploratory Analysis of South American Wines Using Artificial Intelligence.

Candice N Carneiro1, Federico J V Gomez2, Adrian Spisso2

  • 1Centro de Ciências Exatas E Tecnológicas, Universidade Federal Do Recôncavo da Bahia, Campus Universitário de Cruz das Almas, Cruz das Almas, Bahia, 44380-000, Brazil.

Biological Trace Element Research
|December 22, 2022
PubMed
Summary

Microwave-induced plasma optical emission spectrometry successfully determined elements in South American wines. This method, combined with machine learning, accurately classified wines by their geographical origin.

Keywords:
Elemental compositionMicrowave-induced plasma optical emission spectrometryWine

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Area of Science:

  • Analytical Chemistry
  • Spectroscopy
  • Machine Learning

Background:

  • Geographical origin is a key factor in wine quality and authenticity.
  • Accurate classification of wine by origin requires reliable analytical data and robust statistical methods.

Purpose of the Study:

  • To apply microwave-induced plasma optical emission spectrometry (MIP OES) for multielement determination in South American wines.
  • To evaluate the efficacy of machine learning algorithms (logistic regression, support vector machine, decision tree) in differentiating wine samples based on their geographical origin.

Main Methods:

  • Acid digestion of 47 Brazilian and Argentinian red wine samples.
  • Multielement analysis using microwave-induced plasma optical emission spectrometry (MIP OES).
  • Exploratory data analysis and classification using logistic regression, support vector machine, and decision tree algorithms.

Main Results:

  • Quantification limits (mg L⁻¹) were established for P, B, K, Mn, Cr, and Al.
  • Accurate classification of all wine samples according to their geographical origin was achieved.
  • Elemental concentration ranges for Al, Cr, Mn, P, B, Pb, Na, and K were determined.

Conclusions:

  • MIP OES is a suitable technique for multielement analysis in wine.
  • Machine learning algorithms can effectively differentiate South American red wines by region of origin using elemental composition data.