Monitoring the quality attributes of grapes is a practice that allows to check the grapes’ state of ripeness and to decide when it is appropriate to proceed with the harvest. In the present study, a non-destructive method based on hyperspectral imaging (HSI) technology was developed. Analyses were carried out directly in the field using a Vis/NIR (400-1000 nm) hyperspectral camera (HSC) between the rows of `Sangiovese’ (Vitis vinifera L.) vineyard destined for wine production.
One vineyard row was analyzed on 13 different days. During the trials, 33 berries were collected and the soluble solids content (SSC) expressed in terms of °Brix (°Bx) was measured by a portable digital refractometer. The mean spectra of the selected berries were extracted from each hyperspectral (HS) image. The pre-treated mean spectra were used to predict the SSC of the berries by means of partial least squares (PLS) regression, obtaining a value of R 2 = 0.75 in cross-validation, with RMSECV = 0.84 °Bx.
The present study shows the potential of the use of HSI technology directly in the field through proximal measurements under natural light conditions for the prediction of the SSC quality attribute of grapes.
