Rapid quantitative determination of oleuropein in olive leaves (Olea europaea) using mid-infrared spectroscopy combined with chemometric analyses

Oleuropein, the major active compound in olive leaf, is well known for its benefits for human health. Oleuropein is classically quantified by HPLC, which is time and chemical consuming, laborious and expensive. The aim of this work was to examine the potential of mid-infrared spectroscopy, as a rapid tool, to predict oleuropein content in olive leaf from five Tunisian cultivars (Chemlali, Chetoui, Meski, Sayali and Zarrazi) and one French cultivar (Bouteillan). The reference data of oleuropein content were obtained by the HPLC method. Hundred five samples were analyzed by HPLC and mid-infrared spectroscopy. Samples were randomly divided in a calibration set (73 samples) and in a validation set (32 samples). The spectral data sets were correlated with reference data of oleuropein content by using partial least squares (PLS) regression algorithm. The results showed that the PLS model gave satisfactory model for quantitative prediction of oleuropein content in olive leaf (relative error of prediction = 8.5%). The correlation coefficient was 0.91 and 0.74 for calibration set and validation set, respectively. It can be concluded that mid-infrared spectroscopy constitutes a promising technique for rapid quantification of oleuropein in olive leaf.

► We examined the potential of MIRS to predict oleuropein content in olive leaf.
► 105 samples were analyzed by HPLC (reference data) and mid-infrared spectroscopy.
► MIR data were correlated with HPLC data by using PLS regression.
► PLS regression gave satisfactory model to predict oleuropein content (error = 8.5%).
► MIRS presents potential for a rapid quantification of oleuropein in olive leaves.