Robustness of calibration models based on near infrared spectroscopy to the in-line grading of stonefruit for total soluble solids

The utility of near infrared spectroscopy as a non-invasive technique for the assessment of internal eating quality parameters of stonefruit (peaches, nectarines and plums) was assessed. Calibration model performance for the attributes of total soluble solids (TSS) was encouraging (typical R2 > 0.88, RMSECV 0.53–0.88%TSS, SDRCV 2.9–3.7). Model performance was acceptable using a combined multi-variety peach–nectarine data set, but it was advantageous to maintain a separate multi-variety plum model. Model robustness to temperature was achieved by including into the calibration set samples scanned at a range of temperatures, with less than 5% of total population required to be treated in this way. Similarly, where models incorporated the range of TSS seen in the validation population, prediction performance was good. Model performance was stable over several seasons in terms of R2 (typical R2 > 0.8), with bias corrected SEP varying in proportion to population S.D. Prediction bias for new populations could be corrected by model updating or direct bias adjustment.