Prediction of total antioxidant activity of Prunella L. species by automatic partial least square regression applied to 2-way liquid chromatographic UV spectral images.

Four different data representations were evaluated for the determination of the total antioxidant activities of four different Prunella L. species, which are Prunella vulgaris, Prunella grandiflora, Prunella laciniata, and Prunella orientalis Bornm. Three different antioxidant assays, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABST), 2,2-diphenyl-1-picrylhydrazyl (DPPH), and Folin-Ciocalteu (FC) reagent measured the total antioxidant activity and phenolic content of the four Prunella L. species that were extracted with 12 different solvent systems. The data set of 48 Prunella L. extracts was collected by high-performance liquid chromatography (HPLC) with ultraviolet diode array detection. The prediction of total antioxidant activity of Prunella L. species by super partial least square (sPLS) regression was obtained using four different representations of the data; the entire two-way chromatographic-spectral images, the average UV spectra, the total absorbance chromatogram, the lambda max (λmax) chromatogram. The coefficients of determination (R2) for the entire two-way chromatographic-spectral images (the ABST (0.943±0.008), the DPPH (0.91±0.01), and the FC (0.963±0.006)) indicated good accuracy for predicting antioxidant activities. The three different wet chemical assays are known to yield different values so it is advantageous to estimate the three separate values with a single LC measurement. The entire two-way chromatographic-spectral images have been used to the first time for calibration. Acidic hexane, as an extraction solvent, gave the least root mean square error of prediction (RMSEP) for the two-way chromatographic-spectral images, so it would be the best solvent for modeling antioxidant activities.