In order to ascertain whether the Electronic Olfactory System (EOS) could be used for the sensory analysis of virgin olive oil, samples of oil were evaluated by both panel test and electronic nose. The EOS comprises an array of sensors and a data analysis software, working in the same way as the human olfactory system, and it is able to identify and classify odours on the basis of a reference data base. in this work, firstly a correlation was made between the answers from the EOS and from panel (defect and intensity of defect). Secondly, the EOS was 'trained' by examining samples of oil already analysed by panel test. So the 'training data set' was used to develop a pattern recognition system. Good percentage of correct recognition if there was defect or not (70-80%) and good percentage of correct recognition of type of defect (73-81%) are got. To confirm the reproducibility of the measures, another EOS of the same type was used on a series of samples, and there was a good correlation between the results. Further studies are needed on different aromas that could interfere in the recognition of the defects: the way the measurements are made also needs other research specifically concerning a standard for the calibration of different sets of data.
Sensory analysis of virgin olive oil by means of organoleptic evaluation and electronic olfactory system
Sberveglieri G;
2006
Abstract
In order to ascertain whether the Electronic Olfactory System (EOS) could be used for the sensory analysis of virgin olive oil, samples of oil were evaluated by both panel test and electronic nose. The EOS comprises an array of sensors and a data analysis software, working in the same way as the human olfactory system, and it is able to identify and classify odours on the basis of a reference data base. in this work, firstly a correlation was made between the answers from the EOS and from panel (defect and intensity of defect). Secondly, the EOS was 'trained' by examining samples of oil already analysed by panel test. So the 'training data set' was used to develop a pattern recognition system. Good percentage of correct recognition if there was defect or not (70-80%) and good percentage of correct recognition of type of defect (73-81%) are got. To confirm the reproducibility of the measures, another EOS of the same type was used on a series of samples, and there was a good correlation between the results. Further studies are needed on different aromas that could interfere in the recognition of the defects: the way the measurements are made also needs other research specifically concerning a standard for the calibration of different sets of data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
