Unravelling the complexities of wine: a big data approach to yeast assimilable nitrogen

• Gabriella Petrovic ^[1] ; Jose-Luis Aleixandre-Tudo ^[1] ; Astrid Buica ^[1]
  1. [1] Department of Viticulture and Oenology, P/Bag X1 Matieland, Stellenbosch
• Localización: OENO ONE: Journal international des sciences de la vigne et du vin = International journal of vine and wine sciences, ISSN 1151-0285, Vol. 53, Nº 2, 2019, págs. 107-127
• Idioma: inglés
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• Resumen

  • Aim: Assimilable Nitrogen (YAN) has been identified as one of the main drivers of wine quality, influencing the production of various aromas and ensuring a successful fermentation to dryness. Due to the number of factors affecting YAN concentration and composition, paired with the complexities of yeast metabolism, more data is required to enable a comprehensive understanding of this important component of the grape juice matrix. The use of high throughput and information-rich techniques such as InfraRed spectroscopy can lead to a fast generation of a large amount of data. In addition, there is a possibility to maximise the information output of the generated data when combined with various descriptive and exploratory statistical techniques.

    Conclusion: Given the recent developments in the fields of analytical equipment and chemometrics, the review explores the possibility of a Big Data approach for the research of one of the most important and versatile grape juice parameters, namely YAN