Grape seed characterization by NIR hyperspectral imaging

Currently, the time of grape harvest is normally determined according to the sugar level in the pulp of the berry. Nonetheless, the stage of maturation in grape seeds should be taken into account more frequently to decide the appropriate harvest period. There are chemical and sensory analyses available to assess stage of maturation of grape seeds but they are destructive and time-consuming. Hyperspectral imaging is an alternative technology to characterize the grape seeds according to their chemical attributes, and the current work aimed to non-destructively characterize grape seeds in regard of the variety and stage of maturation. For this purpose, 56 samples of seeds from two red grape varieties (Tempranillo and Syrah) and one white variety (Zalema) in two kinds of soil were selected to assess their features based on the reflectance in the near-infrared (NIR) spectra by using prediction models (partial least squares regression) and multivariate analysis methods (principal component analysis and general discriminant analysis). In this study, a reliable methodology for predicting the stage of maturation was developed, and it was shown that it was possible to distinguish the variety of grape and even the type of soil from hyperspectral images of grape seeds.

► The methodology of acquiring hyperspectral images in grape seeds was established.
► A PLSR model was applied to predict the stage of maturation of grape seeds.
► PCA and GDA methods were used to characterize grape varieties and soil types.