An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion - Boti, Vasiliki I.; Sakkas, Vasilios A.; Albanis, Triantafyllos A. (Journal of Chromatography A, 2009)
Keywords: 1-(3,4-dichlorophenyl)-3-methylurea; 3,4-dichloroaniline; Algorithms; analysis; apples; Artificial neural networks; Biological and medical sciences; carrots; chemistry; Chromatography, High Pressure Liquid; Chromatography, High Pressure Liquid - methods; Citrus; Daucus; diuron; Diuron - analysis; EDCs; Endocrine Disruptors; Endocrine Disruptors - analysis; endocrine-disrupting chemicals; Experimental design; extraction; Food Analysis; Food Analysis - methods; food contamination; Food industries; Fundamental and applied biological sciences. Psychology; General aspects; herbicide residues; linuron; Linuron - analysis; Magnesium Silicates; Magnesium Silicates - chemistry; Malus; Matrix solid-phase dispersion; metabolites; methods; Methods of analysis, processing and quality control, regulation, standards; Multivariate Analysis; neural networks; Neural Networks (Computer); orange juice; potatoes; Reproducibility of Results; sampling; Sensitivity and Specificity; Solanum tuberosum; Solanum tuberosum - chemistry; Triticum aestivum; wheat flour; Matrix solid-phase dispersion; Experimental design; Artificial neural networks; EDCs; Solid phase extraction; Chemical analysis; Metabolite; HPLC chromatography; Optimization; Chemical enrichment; Sample preparation; Phenylureas; Ureas; Food; Quantitative analysis; Matrix Solid Phase Dispersion extraction; Trace analysis; Mimetic hormone; Pesticides; Diuron; Endocrine disruptor; Neural network; Contamination; Herbicide; Ultraviolet detector; Residue; Chemometrics