Visible/Near Infrared (VIS/NIR) spectroscopy as an optical sensor for evaluating olive oil quality

The quality of olive oils can be tested by chemical ways, and these methods are time consuming and very expensive. Therefore, the aim of this study is focused on reducing both time and cost, by using Visible/Near Infrared (VIS/NIR) spectroscopy (i.e. 400-1100 nm) absorbance to evaluate the quality of olive oil. Thus, 48 olive oil samples were collected from different governorates in Palestine and the samples covered the four quality groups (i.e. extra virgin, virgin, ordinary virgin and lampante). Chemical analysis was carried out, and then spectra were acquired by VIS/NIR spectroscopy. Spectral data was analyzed by principal component analysis (PCA). The relation between spectra and chemical data were evaluated by partial least squares (PLS). It was found the PCA was able to distinguish between four quality groups, also it was found that the VIS/NIR spectroscopy was able to model some quality parameters (i.e. acidity and peroxide) with good accuracy. The PLS correlation coefficients for acidity and peroxide were 0.88 and 0.86 for validation sets, respectively. The ratios of standard error of performance to standard deviation (RPD) values were 3.08 and 2.25 for validation set for acidity and peroxide, respectively. The results showed that it was possible to model/predict acidity and peroxide parameters with good accuracy. Moreover, it was also possible to distinguish between different quality groups of olive oil.