Quantification of Phenolic Compounds in Olive Oil Mill Wastewater by Artificial Neural Network/Laccase Biosensor

• Published in: Journal of agricultural and food chemistry 2007-09, Vol.55 (18), p.7418-7426
• Main Authors: Torrecilla, José S, Mena, Maria L, Yáñez-Sedeño, Paloma, García, Julián
• Format: Article
• Language: English
• Subjects: Biological and medical sciences; Biosensing Techniques; biosensors; caffeic acid; Caffeic Acids - analysis; catechol; Catechols - analysis; chemical composition; computer analysis; Fat industries; Food industries; food processing wastes; Fundamental and applied biological sciences. Psychology; General aspects; industrial effluents; Industrial Waste - analysis; Laccase; neural networks; Neural Networks (Computer); Olive Oil; olive oil mill wastewater; phenolic compounds; Phenols - analysis; Plant Oils; Pollution and sludges; wastewater
• ISSN: 0021-8561; 1520-5118
• DOI: 10.1021/jf0703351

In this paper is considered a new computerized approach to the determination of concentrations of phenolic compounds (caffeic acid and catechol). An integrated artificial neural network (ANN)/laccase biosensor is designed. The data collected (current signals) from amperometric detection of the laccase biosensor were transferred into an ANN trained computer for modeling and prediction of output. Such an integrated ANN/laccase biosensor system is capable of the prediction of caffeic acid and catechol concentrations of olive oil mill wastewater, based on the created models and patterns, without any previous knowledge of this phenomenon. The predicted results using the ANN were compared with the amperometric detection of phenolic compounds obtained at a laccase biosensor in olive oil wastewater of the 2004−2005 harvest season. The difference between the real and the predicted values was