title: Virgin olive oil quality classification combining neural network and MOS sensors.
abstract: A model based on neural networks has been designed to detect lampante virgin olive oils, a category of olive oil that cannot be consumed without a previous refining process according to the current regulation of the European Communities. The response of 7 metal oxide sensors analyzing 114 olive oil samples has been used in the design, training, and internal validation of the neural network with only 4.5% error in validation. The designed mathematical model, the equations of which are fully described, has been validated also with an external set of 13 samples of diverse varieties and geographical origins with 100% correct classification.
authors.affiliation: Instituto de la Grasa, Padre García Tejero 4, 41012 Sevilla, Spain. dluisg@cica.es
authors.forename: Diego L
authors.initials: DL
authors.lastname: García-González
authors.forename: Ramón
authors.initials: R
authors.lastname: Aparicio
mesh_terms: D002623:Chemistry Techniques, Analytical / Q000379:methods*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D000069463:Olive Oil; D010938:Plant Oils / Q000032:analysis / Q000145:classification* / Q000592:standards*; D011786:Quality Control; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012903:Smell
chemical_list: D000069463:Olive Oil; D010938:Plant Oils