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2015
Conference Paper
Titel
Non-destructive determination of grape berry sugar concentration using visible/near infrared imaging and possible impact on wine quality
Abstract
Reducing heterogeneity in harvest material may be beneficial for wine quality and this goal may be achieved through advanced berry sorting systems. The general aim is to assess if a relationship could be found between berry sugar concentration and hyperspectral images to determine the possible impact on wine quality. Grapes were picked at different stages of maturity in a one-year time interval and the berries were sorted according to their size and density. Hyperspectral images of the groups were obtained in the vis/NIR wavelength range with a complete spectrum from 400 nm to 2500 nm. Our results showed that vis/NIR images can be used as a tool to improve the segregation of berries from all tested grape varieties based on their sugar content. The PLSR algorithm is trained on all grape varieties together and later validated on each variety separately, proving the possibility of using a general regression model with constant parameters to predict sugar concentrations. Finally, the impact on quality was tested for red wines. Pinot noir berries with higher sugar concentrations presented more color since anthocyanin concentration was higher. Nevertheless, tannin concentration in skins and seeds tended to decrease with increasing sugar concentration. Groups with higher sugar concentration resulted in wines with higher anthocyanin and lower tannin concentration.