Analytical and sensory data correlation to understand consumers' grape preference

Abstract

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.