title: Second-order advantage achieved by modeling excitation-emission fluorescence matrices affected by inner filter effects using a strategy which combines standardization and calibration: reducing experimental and increasing analytical sensitivity.
abstract: A methodology based on second-order data (excitation emission matrices) modeling with one of most popular algorithms presenting the second-order advantage, parallel factor analysis (PARAFAC), combined with transference of calibration is proposed to predict the analyte concentration when significant inner filter effects occur, even in the presence of unexpected sample components. The quantitation of phenylephrine hydrochloride (PHE) in water samples (concentrations ranged between 250 and 750 ng mL(-1)) in the presence of ibuprofen, acetyl salicylic acid and paracetamol (which produce inner filter effect across the useful wavelength range) was achieved. The strategy allows reducing the experimental work and increasing the analytical sensitivity in the determination of the analyte of interest in the presence of unexpected compounds and matrix effect caused by inner filter, avoiding the preparation of a large number of solutions and maintaining acceptable figures of merit. Recoveries between 97 and 102% for validation and real spiked water samples, respectively, and a relative prediction error of 5% were achieved. Results were compared with those obtained after the application of the classical standard addition method combined with PARAFAC, carrying out five additions to each sample, in triplicate. The presented methodology constitutes a simple and low-cost method for the determination of PHE in water samples with a considerable reduction in standard handling and time. This methodology can be extended to other systems presenting matrix effect and, consequently, can become in a useful tool to know the amount of pharmaceuticals in the aquatic environment and to evaluate the effect of conventional wastewater treatment plants in the elimination of pharmaceutical compounds.
authors.affiliation: Laboratorio de Desarrollo Analítico y Quimiometría (LADAQ), Cátedra de Química Analítica I, Facultad de Bioquímica y Ciencias Biológicas, Universidad Nacional del Litoral-CONICET, Ciudad Universitaria, Santa Fe, Argentina.
authors.forename: Agustina V
authors.initials: AV
authors.lastname: Schenone
authors.forename: María J
authors.initials: MJ
authors.lastname: Culzoni
authors.forename: María Martínez
authors.initials: MM
authors.lastname: Galera
authors.forename: Héctor C
authors.initials: HC
authors.lastname: Goicoechea
mesh_terms: D000082:Acetaminophen / Q000032:analysis; D000465:Algorithms; D001241:Aspirin / Q000032:analysis; D002138:Calibration; D007052:Ibuprofen / Q000032:analysis; D057230:Limit of Detection; D008956:Models, Chemical; D004364:Pharmaceutical Preparations / Q000032:analysis*; D010656:Phenylephrine / Q000032:analysis*; D012015:Reference Standards; D013050:Spectrometry, Fluorescence / Q000295:instrumentation / Q000379:methods / Q000592:standards; D062065:Wastewater / Q000737:chemistry; D014874:Water Pollutants, Chemical / Q000032:analysis*
chemical_list: D000082:Acetaminophen; D001241:Aspirin; D007052:Ibuprofen; D004364:Pharmaceutical Preparations; D010656:Phenylephrine; D062065:Wastewater; D014874:Water Pollutants, Chemical