Elimination of variability sources in NIR spectra for the determination of fat content in olive fruits

Models for prediction of oil content as percentage of dried weight in olive fruits were comput- ed through PLS regression on NIR spectra. Spectral preprocessing was carried out by apply- ing multiplicative signal correction (MSC), Sa vitzky–Golay algorithm, standard normal variate correction (SNV), and detrending (D) to NIR spectra. MSC was the preprocessing technique showing the best performance. Further reduction of variability was performed by applying the Wold method of orthogonal signal correction (OSC). The calibration model achieved a R 2 of 0.93, a SEPc of 1.42, and a RPD of 3.8. The R 2 obtained with the validation set remained 0.93, and the SEPc was 1.41.