A New Statistical Approach to Describe the Quality of Extra Virgin Olive Oils Using Near Infrared Spectroscopy (NIR) and Traditional Analytical Parameters

SummaryNIR prediction models were developed for the determination of relevant parameters to evaluate olive oil quality such as acidity (FFA), peroxide value (PV), UV ‐absorption at 232 nm and at 268/270 nm,p‐anisidine value (AnV), isomeric diacylglycerols (DG), and pyropheophytin A (PPP). In addition a new NIR method to estimate the age of olive oil is presented. The relevant wavenumbers are given for the calculation of the parameters and the precision data are presented in comparison to the chemical reference methods. The calibration and validation of the methods were executed with independent data sets (test in test instead of cross‐validation) to cover the wide range of variability of the analytical parameters including the corresponding accurate analytical results from the reference chemi cal methods. The correctness and accuracy of the developed NIR methods were verified by analyzing certified materials.Finally, a simple statistical approach has been developed to describe the quality of olive oils using the parameters FFA, PV, K232 and K270, DG and PPP. The probability of presence of a sensory defect (100% ≙ 1; 0% ≙ 0) was calculated using the following equation:Pred (BIN) = 1/(1+exp( ‐(‐9+37*FFA‐0.9*PV‐2.9*K232+14*K270+3.7*PPP‐0.27*DG))).Practical applications: The use of NIR allows the analysis of different parameters relevant for the quality of olive oil in one run in comparison to the individual chemical reference methods. That allows saving t...
Source: European Journal of Lipid Science and Technology - Category: Lipidology Authors: Tags: Research Article Source Type: research