On-line versus off-line NIRS analysis of intact olives

Abstract

Visible/near-infrared calibrations were developed for the determination of the quality parameters (fat content, moisture and free acidity) of intact olive fruits. The reflectance spectra were acquired in two different instruments (diode-array versus grating monochromator based instruments). The grating monochromator based instrument was used at the laboratory (off-line analysis), whereas the portable diode-array based device was placed on top of a conveyor belt set to simulate measurements in an olive oil mill plant (on-line analysis). Partial least squares (PLS) regression and least squares support vector machine (LS-SVM) were used for the development of the calibration models. A total of 174 samples were prepared for the calibration (N = 122) and validation (N = 52) sets. The root mean square error of prediction (RMSEP) and the residual predictive deviation (RPD) values were better using the diode-array instrument and applying the PLS regression method for the fat content parameter while for the free acidity and moisture content, the LS-SVM algorithm gave the best results. The results obtained seems to suggest the viability of the on-line system, instead of the off-line analysis, for the determination of physicochemical composition in intact olives.