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Genetic‐Algorithm‐Based Wavelength Selection in Multicomponent Spectrophotometric Determination by PLS: Application on Ascorbic Acid and Uric Acid Mixture
Author(s) -
Khajehsharifi Habibllah,
Pourbasheer Eslam
Publication year - 2008
Publication title -
journal of the chinese chemical society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.329
H-Index - 45
eISSN - 2192-6549
pISSN - 0009-4536
DOI - 10.1002/jccs.200800025
Subject(s) - ascorbic acid , chemistry , uric acid , calibration curve , partial least squares regression , chromatography , analytical chemistry (journal) , analyte , biochemistry , detection limit , food science , statistics , mathematics
Genetic algorithm (GA) is a suitable method for selecting wavelengths for partial least squares (PLS) calibration of mixtures with almost identical spectra without loss of prediction capacity using the spectrophotometric method. In this study, the concentration model is based on absorption spectra in the range of 200‐320 nm for 25 different mixtures of ascorbic acid (AA) and uric acid (UA). The calibration curve was linear over the concentration range of 1‐15 and 2‐16 μg mL −1 for ascorbic acid and uric acid, respectively. The root mean square deviation (RMSD) for ascorbic acid and uric acid with GA and without GA were 0.3071 and 0.3006, 0.3971 and 0.7063, respectively. The proposed method was successfully applied to the simultaneous determination of both analytes in human serum and urine samples.