Use of artificial neural networks for optimization of biogenic amines derivatization
| Authors | |
|---|---|
| Year of publication | 2014 |
| Type | Article in Proceedings |
| Conference | CECE 2014: 11TH INTERNATIONAL INTERDISCIPLINARY MEETING ON BIOANALYSIS |
| MU Faculty or unit | |
| Citation | |
| Web | http://www.ce-ce.org/CECE2014/CECE%202014%20proceedings_full.pdf#page=378 |
| Field | Analytic chemistry |
| Keywords | ANN; biogenic amines; dansyl chloride; HPLC |
| Description | Biogenic amines as biologically active molecules with potential toxicological dangers are often subject of interest in food analysis. Since these substances do not exhibit significant fluorescence nor absorbance, derivatization is necessary for analysis in combination with RP-HPLC-UV setup. The use of experimental design (ED) in combination with artificial neural networks (ANN) for optimization of dansyl derivatization conditions for seven biogenic amines is presented. Four key factors were studied – concentration of derivatization reagent, buffer pH, temperature and incubation time. With the use of ED-ANN approach, optimal conditions for dansyl chloride derivatization were found and experimentally confirmed. |
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