Estimation of olive oil acidity using FT-IR and partial least squares regression

Sensing and Instrumentation for Food Quality and Safety 01/2009; 3(3):187-191. DOI: 10.1007/s11694-009-9084-2

ABSTRACT Olive oil characteristics are directly related to olive quality. Information about olive quality is of paramount importance
to olive and olive oil producers, in order to establish its price. Real-time characterization of the olives avoids mixtures
of high quality with low quality fruits, and allows improvement of olive oil quality. This work describes an indirect determination
of olive acidity and that allows a rapid evaluation of olive oil quality. The applied method combines chemical analysis (30min
Soxhlet olive pomace extraction) in tandem with a spectroscopic technique (FT-IR) and multivariate regression (PLS1). The
most suitable calibration model found used SNV pre-processing and was built with 4 Latent Variables giving a RMSECV of 8.7%
and a Q2 of 0.97. This accurate calibration model allows the estimation of olive acidity using a FT-IR spectrum of the corresponding
Soxhlet oil dry extract and therefore is a suitable method for indirect determination of FFA in olives.

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