Quantification of Syringic Acid in Real Samples Based on UV-Vis Spectroscopy

Abstract

In this research work, a reliable, as well as rapid Ultraviolet-visible (UV-Vis) spectroscopy technique, was employed for assessing syringic acid (SGA) contents in real samples-cauliflower (CLF), oregano (ORG) and black olive (BOL). Data measurements were performed using UV Spectrophotometer, operating in the wavelength range of 200-400 nm. Principal component analysis (PCA) was applied for analyzing and distinguishing different samples. PCA plot confirmed the effective clustering of the samples. A high-class separability index of 313.52 was obtained for the UV-vis absorbance data. Moreover, for prediction and correlation of SGA levels in the samples, principal component regression (PCR) as well as Partial least square regression (PLSR) analysis were performed. These prediction algorithms showed high average prediction accuracy of 99.68% and 99.65% respectively and almost the same correlation factor (CF) as high as 0.99 was obtained for both models. Further, high precision was observed with a low RSD value of 0.33 % for the peak absorbance at around 220nm. The primary investigation results recommend that for detecting and assessing SGA contents in real samples, the UV-Vis spectroscopy technique coupled with multivariate analysis may be a viable approach.