Rapid evaluation of oxidized fatty acid concentration in virgin olive oils using metal oxide semiconductor sensors and multiple linear regression.
This works aims to set up a rapid and nondestructive method to evaluate the advanced oxidation of virgin olive oils (VOOs). An electronic nose based on an array of six metal oxide semiconductor sensors was used, jointly with multiple linear regression (MLR), to predict the oxidized fatty acid (OFA) concentration in VOO samples characterized by different oxidative status. An MLR model constructed using five predictors was able to predict OFA concentration with an average validation error of 9%.
Lerma-García
María Jesús
MJ
Departamento de Química Analtica, Universidad de Valencia, C. Doctor Moliner 50, E-46100 Burjassot, Valencia, Spain. m.jesus.lerma@uv.es
Simó-Alfonso
Ernesto F
EF
Bendini
Alessandra
A
Cerretani
Lorenzo
L
D015374:Biosensing Techniques / Q000295:instrumentation / Q000379:methods*; D005227:Fatty Acids / Q000737:chemistry*; D016014:Linear Models; D000069463:Olive Oil; D010084:Oxidation-Reduction; D010087:Oxides / Q000737:chemistry; D010938:Plant Oils / Q000737:chemistry*; D012666:Semiconductors
D005227:Fatty Acids; D000069463:Olive Oil; D010087:Oxides; D010938:Plant Oils