Aleatico (Vitis vinifera L.) grapes were harvested at 21.3 Brix and dehydrated at 20°C, 45% relative humidity, and 1.5 m/sec air flow in a small-scale thermo-conditioned tunnel. Postharvest grape dehydration was performed until the fruit lost an average of 40% initial weight. During dehydration, single destemmed grape berries were analyzed nondestructively using an acousto-optically tunable filter (AOTF) near-infrared (NIR) spectrophotometer (1100–2300 nm) in reflectance. Total soluble solids (TSS) and moisture content (%) were measured on the same berries with the objective of using spectral and nonspectral information to develop regression models for predicting these parameters. Partial least squares regression applied after different statistical pretreatments (multiplicative scatter correction, Savitzky-Golay 1st or 2nd derivative filter) was tested on absorbance spectra to define the most effective approach. Two prediction models were obtained (n = 450 for TSS, n = 600 for water loss) in which the coefficient of determination in cross-validation (r2) and the root mean standard error of cross-validation were 0.93 and 0.89 Brix for TSS and 0.92 and 2.16% for water loss, respectively. A model validation procedure was performed using separate sample sets (n = 170 for TSS, n = 200 for water loss) with the following results: coefficient of determination (R2) and standard error of prediction of 0.92 and 0.72 Brix for TSS and 0.9 and 1.89% for water loss, respectively.
- © 2011 by the American Society for Enology and Viticulture