An experimental design approach employing artificial neural networks for the determination of potential endocrine disruptors in food using matrix solid-phase dispersion
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Ημερομηνία
Συγγραφείς
Τίτλος Εφημερίδας
Περιοδικό ISSN
Τίτλος τόμου
Εκδότης
Elsevier
Περίληψη
Τύπος
Είδος δημοσίευσης σε συνέδριο
Είδος περιοδικού
peer reviewed
Είδος εκπαιδευτικού υλικού
Όνομα συνεδρίου
Όνομα περιοδικού
Journal of Chromatography A
Όνομα βιβλίου
Σειρά βιβλίου
Έκδοση βιβλίου
Συμπληρωματικός/δευτερεύων τίτλος
Περιγραφή
Matrix solid-phase dispersion (MSPD) as a sample preparation method for the determination of two potential endocrine disruptors, linuron and diuron and their common metabolites, 1-(3,4-dichlorophenyl)-3-methylurea (DCPMU), 1-(3,4-dichlorophenyl) urea (DCPU) and 3,4-dichloroaniline (3,4-DCA) in food commodities has been developed. The influence of the main factors on the extraction process yield was thoroughly evaluated. For that purpose, a 3((4-1)) fractional factorial design in further combination with artificial neural networks (ANNs) was employed. The optimal networks found were afterwards used to identify the optimum region corresponding to the highest average recovery displaying at the same time the lowest standard deviation for all analytes. Under final optimal conditions, potato samples (0.5 g) were mixed and dispersed on the same amount of Florisil. The blend was transferred on a polypropylene cartridge and analytes were eluted using 10 ml of methanol. The extract was concentrated to 50 mu l of acetonitrile/water (50:50) and injected in a high performance liquid chromatography coupled to UV-diode array detector system (HPLC/UV-DAD). Recoveries ranging from 55 to 96% and quantification limits between 5.3 and 15.2 ng/g were achieved. The method was also applied to other selected food commodities such as apple, carrot, cereals/wheat flour and orange juice demonstrating very good overall performance. (C) 2008 Elsevier B.V. All rights reserved.
Περιγραφή
Λέξεις-κλειδιά
experimental design, artificial neural networks, matrix solid-phase dispersion, edcs, performance liquid-chromatography, gas-chromatography, mass-spectrometry, polychlorinated-biphenyls, pesticide-residues, sample preparation, optimization, extraction, contaminants, herbicides
Θεματική κατηγορία
Παραπομπή
Σύνδεσμος
<Go to ISI>://000263610500004
http://ac.els-cdn.com/S002196730802270X/1-s2.0-S002196730802270X-main.pdf?_tid=129e5a05d935db394f7dbbbc62e10d5a&acdnat=1333022724_640a66d26aa6d54e203aff331c31a07f
http://ac.els-cdn.com/S002196730802270X/1-s2.0-S002196730802270X-main.pdf?_tid=129e5a05d935db394f7dbbbc62e10d5a&acdnat=1333022724_640a66d26aa6d54e203aff331c31a07f
Γλώσσα
en
Εκδίδον τμήμα/τομέας
Όνομα επιβλέποντος
Εξεταστική επιτροπή
Γενική Περιγραφή / Σχόλια
Ίδρυμα και Σχολή/Τμήμα του υποβάλλοντος
Πανεπιστήμιο Ιωαννίνων. Σχολή Θετικών Επιστημών. Τμήμα Χημείας