Quantification of phenolic compounds in olive oil mill wastewater by artificial neural network/laccase biosensor.
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 <0.5%. biosensor; olive oil mill wastewater; chemical analysis; phenolic compounds.
Department of Chemical Engineering, Complutense University of Madrid, 28040 Madrid, Spain. jstorre@quim.ucm.es
José S
JS
Torrecilla
Maria L
ML
Mena
Paloma
P
Yáñez-Sedeño
Julián
J
García
D015374:Biosensing Techniques; D002109:Caffeic Acids / Q000032:analysis; D002396:Catechols / Q000032:analysis*; D007220:Industrial Waste / Q000032:analysis*; D042845:Laccase; D016571:Neural Networks, Computer; D000069463:Olive Oil; D010636:Phenols / Q000032:analysis*; D010938:Plant Oils
D002109:Caffeic Acids; D002396:Catechols; D007220:Industrial Waste; D000069463:Olive Oil; D010636:Phenols; D010938:Plant Oils; D042845:Laccase; C034221:catechol; C040048:caffeic acid