Robustness improvement of NIR-based determination of soluble solids in apple fruit by local calibration

•Local calibration improves model robustness of NIR-based SSC prediction.•A possible explanation is that samples of same level of starch are selected.•Selecting similar samples by PLS scores and correlation show equivalent effect. Nondestructive determination of soluble solids content (SSC) has been used in the fruit industry by using near infrared (NIR) spectroscopy. The robustness of prediction models, which is of great importance in practical application, remains a challenge because of the variability of fruit samples associated with different maturity stages and storage status. Local calibration was investigated in this study as means of improving prediction robustness. As robustness is often reduced by extrapolation, we assessed the robustness by the accuracy of predicting extrapolation samples (samples outside the range of the calibration set). Local calibration was effective in improving the robustness of models compared with global calibration. It is proposed that local calibration optimizes the composition of calibration subset by selecting the samples of same level of starch fractions for each sample to be predicted, and thus provides better robustness due to the homogeneity.