Abstract

Pistacia atlantica belongs to the Anacardiaceae family, and originated from the Atlas mountains of north Africa, which has been employed in traditional medicine for the treatment of various diseases. There are many limitations regarding their activities. The bioactive compounds present in the extract of P. atlantica leaves are not well defined. For these identifications HPLC fingerprint methodology can be used. In the present study, 28 extracts were obtained from male and female leaves of P. atlantica, collected monthly during 6months, in two different growing regions. The total antioxidant capacity (TAC) values of P. atlantica extracts were determined using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical method and the potassium ferricyanide (PFC) reduction method. The fingerprints were pre-treated using several techniques, such as column centering; normalization followed by column centering, and standard normal variate (SNV) transformation followed by column centering; each after initial alignment of the chromatographic profiles with Correlation Optimized Warping (COW). The multivariate calibration methods, Partial Least Squares (PLS) and Orthogonal Projections to Latent Structures (O-PLS), were employed to model TAC. The regression coefficients of the best models were evaluated to indicate the peaks probably responsible for the antioxidant activity. The O-PLS model seems preferable because of its better predictive and describing abilities, and its good interpretability of the contribution of compound peaks to the TAC. Several peaks in the chromatograms were recognized as importantly contributing to the model due to their large regression coefficients. The structural elucidation of the relevant peaks was achieved by negative ionization LC–QTOF–MS. The phenolic compounds galloylquinic acid, quinic acid and gallic acid mainly seemed to be responsible for scavenging the DPPH radical, while glucogallin, trigalloylglucose, gallic acid and tetragalloylquinic acid were considered specifically important for the prediction of TAC determined by the PFC method.

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