Non-Invasive Monitoring of Berry Ripening Using On-the-Go Hyperspectral Imaging in the Vineyard

Hyperspectral imaging offers enormous potential for measuring grape composition with a high degree of representativity, allowing all exposed grapes from the cluster to be examined non-destructively. On-the-go hyperspectral images were acquired using a push broom hyperspectral camera (400-100 nm) that was mounted in the front part of a motorized platform moving at 5 km/h in a commercial Tempranillo vineyard in La Rioja, Spain. Measurements were collected on three dates during grape ripening in 2018 on the east side of the canopy, which was defoliated in the basal fruiting zone. A total of 144 grape clusters were measured for Total soluble solids (TSS), Titratable acidity (TA), pH, Tartaric and Malic acid, Anthocyanins and Total polyphenols, using standard wet chemistry reference methods, throughout the entire experiment. Partial Least Squares (PLS) regression was used to build calibration, cross validation and prediction models for the grape composition parameters. The best performances returned determination coefficients values of external validation (R-p(2)) of 0.82 for TSS, 0.81 for Titratable acidity, 0.61 for pH, 0.62 for Tartaric acid, 0.84 for Malic acid, 0.88 for Anthocyanins and 0.55 for Total polyphenols. The promising results exposed in this work disclosed a notable methodology on-the-go for the non-destructive, in-field assessment of grape quality composition parameters along the ripening period.

Automated summary

The study demonstrates the potential of hyperspectral imaging for non-destructive assessment of grape composition parameters in a commercial vineyard. Using PLS regression, models were built to predict grape composition with high accuracy, showing promising results for on-the-go assessment along the ripening period.