BIO Web Conf.
Volume 15, 201942nd World Congress of Vine and Wine
|Number of page(s)||4|
|Published online||23 October 2019|
Analytical and sensory data correlation to understand consumers' grape preference
Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria -Centro di ricerca Viticoltura ed Enologia (CREA- VE), Via Casamassima 148, 70010 Turi (Ba), Italy
NIR spectroscopy is a rapid, economic and not destructive technique employed in food analysis. Concerning fresh table grape, the analysis is usually limited to juices, homogenates or skin extracts which usually give better NIR prediction models. Scanning of intact berries is challenging since each berry has specific features (berry shape, presence of superficial pigmentation, etc.) and, moreover, there are punctual variations even within the same berry. It would be of great interest to obtain information about maturity parameters and consumer's appreciation directly from intact berries, since it would save both time and money. In this article, near infrared (NIR) spectroscopy and chemometric methods have been employed to search for a correlation between sensory analysis and analytical data. The research findings show how it is possible to use a rapid, economic and not destructive emerging technology such as NIR spectroscopy to understand consumer's preference directly from intact berries.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.