First step for hand-held NIRS instrument field use: Table grape quality assessment consideration of temperature and sunlight chemometrics correction

Abstract

Changes of temperature and sunlight disturb the spectra and furtherly influence the prediction outcome of near infrared spectroscopy (NIRS) in assessment of fruit quality during field measurement. The hand-held NIRS device combination of chemometrics method was investigated for correcting the influence of temperature and sunlight to the grape spectra. The distribution of the soluble solids content (SSC) within one bunch was analyzed, and the middle region of the bunch was recommended for NIRS sampling position. Chemometrics algorithms of global model, external parameter orthogonalisation (EPO) and generalised least square weighting (GLSW) were employed to correct the influence of temperature and sunlight. Comparison of global model and GLSW, EPO improved the performance of the partial least square regression (PLSR) models with coefficient of determination (Rp2) of 0.88–0.90, root mean square error of prediction (RMSEPiv) in the internal validation set of 0.89–0.94% and ratio of standard deviation (SD) to RMSEPiv (RPD) of 3.27–3.14 in predicting the samples at three temperatures and Rp2 of 0.98, RMSEPiv of 0.50% and RPD of 7.00 outdoor measurement. The results suggested that it was feasibility for correcting the influence of temperature and sunlight to the hand-held NIRS device to assess the grape bunch quality for outdoor use.