Use of Remote sensing technology to assess grapevine quality

The aim of this study was to increase the insight on the application of hyperspectral imaging as a non-destructive method in the prediction of the principal parameters that compose technological and phenolic maturity (i.e. sugar concentration, total acidity, total phenols, and anthocyanin content) in wine grapes. The research was conducted in a Babic (Croatian autochthonous cultivar) vineyard grown in artificially transformed karst terrain (Croatia). The hyperspectral images were recorded by a hyperspectral imaging system Hyspex VNIR-1600 and Swir-384 (Norsk Elektro Optikk, Norway) with a spectral range from 400-1000 nm (VNIR), and 1000-2500 nm (SWIR). PLS regression enables us to predict the amount of sugar and acid in grapes with acceptable accuracy $({\mathrm {R_{sugar}}}^{2} = 0.92$, and ${\mathrm {R_{acid}}}^{2} = 0.83)$. By using hyperspectral imaging measurements of sugar content in grapes can become non-invasive, and by using mobile remote sensing systems, cover entire vineyards.