Models for the rapid assessment of water and oil content in olive pomace by near-infrared spectrometry

BACKGROUND Measurement of water and oil content in olive pomace is crucial in order to control the olive oil extraction process; the use of near‐infrared spectra could allow the measurement of the oil and water content in the olive pomace. RESULTS Partial least squares for pomace oil content on dry basis reached an error of 2.5% (+/− 0.5), principal component regression for pomace oil content on wet basis reached an error of 3.7% (+/− 0.5), both suitable for quantitative analysis. Principal component regression for pomace water content reached an error of 6.0% (+/− 2.3), suitable for process control. The relationship between ‘ratio of standard deviation of calibration data to standard error of prediction data’ and ‘range of confident prediction error percent’ was investigated resulting hyperbolic through a constant depending on the product under analysis: for the olive pomace this constant is equal to 45.60 (+/− 1.78). CONCLUSION As the measure of the content of water and oil still contained in pomace must be considered of strategic importance to control the olive oil extraction process, the NIR analysis has confirmed the possibility of determining the oil and water content in the olive pomace. A new algorithm has been used, jointly with standard statistical algorithms, in order to identify and remove from the models the less useful wavelengths improving the overall prediction performance. A new parameter (the ‘range of confident prediction error percent’) has been proposed to estimate the model prediction error in an objective way.