Relationship between sensory and NIR spectroscopy in consumer preference of table grape (cv Italia)

A combination of near infrared spectroscopy (NIR) instrumental measurements and sensory analysis was investigated to predict solids soluble content (SSC, assessed as Brix) and to classify preference in table grape cv Italia. SSC was monitored in each berry of whole bunches in order to evaluate intra-bunch distribution and variability. NIR spectra were recorded in the spectral region 12,000-4000 cm(-1) (833-2500nm) using a set of 682 berries. The Partial Least Square (PLS) model based on cross-validation provided acceptable value for the main statistical parameters (coefficient of determination of cross-validation, r(2): 0.85; standard error of cross-validation, SECV: 1.08; residual predictive deviation, RPD: 2.6) and was confirmed by external validation performed with 115 independent berries (coefficient of determination of prediction, r(p)(2): 0.82; standard error of prediction, SEP: 0.83). For consumer testing, the selected PLS model was used to predict the Brix value in 400 berries and Discriminant Analysis (DA) was then carried out to classify berries in terms of preference by relating NIR data to consumer judgment. The three defined preference clusters of berries were fully classified obtaining 100% membership. In cross-validation the value decreased especially for class 1 (78.5%) and 3 (75%) whereas class 2 obtained comparable values (98.7%). According to our results, NIR technology appears to be a promising technique for predicting SSC and obtaining information with regard to consumer preference in 'Italia' table grape for application of efficient and low cost on-Line instruments in the fruit industry. (C) 2013 Elsevier B.V. All rights reserved.