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Principal Components – Based Techniques in Voltammetric Determination of Caffeic, Syringic and Vanillic Acids
Author(s) -
Ciepiela Filip,
Sordoń Wanda,
Jakubowska Małgorzata
Publication year - 2016
Publication title -
electroanalysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.574
H-Index - 128
eISSN - 1521-4109
pISSN - 1040-0397
DOI - 10.1002/elan.201500203
Subject(s) - vanillic acid , syringic acid , caffeic acid , principal component analysis , analyte , calibration , chromatography , chemistry , principal component regression , chemometrics , multivariate statistics , factorial experiment , analytical chemistry (journal) , computer science , mathematics , artificial intelligence , statistics , machine learning , organic chemistry , antioxidant , gallic acid
It was demonstrated that Principal Components Analysis and Principal Components Regression support qualitative and quantitative investigation of three‐component synthetic samples containing micromolar concentration of caffeic acid (CA), syringic acid (SA) and vanillic acid (VA), in various proportions. The first, second and third PCs enable modelling of relationships and distinction of objects of different composition. Optimized and validated multivariate calibration models, implemented on the basis of the samples selected with the help of 3‐level full factorial design, effectively support simultaneous determination of the considered analytes. Obtained RMSEP was no higher than 0.23 μm for CA, 0.17 μm for SA and 0.21 μm for VA, in relation to the concentration of 1.9 to 21.4 μm of each compound. Recovery between 90–108% for considered analytes, determined in synthetic wine solution, was additional verification of calibration model. Application of automatic baseline correction was extensively studied.