Spectrofluorimetric Determination of Ochratoxin a in Wheat and Rice Products Using an Artificial Neural Network

Abstract

In order to determine Ochratoxin A (OTA) levels in wheat and rice products, an analytical study based on extraction with acetonitrile–water, immunoaffinity column cleanup, and spectrofluorimetric detection for separation and identification of OTA was carried out. The performance of artificial neural networks for modeling the OTA system in spectrofluorimetry was compared with HPLC. Obtained results using these two methods did not show significant differences. Proposed method may be a good alternative to the traditional methods of OTA analysis.