Abstract
A different approach to the traditional sensory method was used for the sensory quality evaluation of virgin olive oils. Two hundred and four oil samples differing in their quality, and extracted from olives of various varieties, ripeness, sanitary state and geographical origin, were submitted to sensory evaluation by a panel test and dynamic head-space analysis for the quantification of volatile fractions. An artificial neural network (ANN), using the back-propagation algorithm, was applied to the head-space results (input) with the aim of predicting panel test scores (output). It was found that the ANN was able to generalise well and to assign the sensory evaluations with a good degree of accuracy. The high proportion of correct answers (96%) suggested that sensory evaluation from the panel test could be successfully replaced by the dynamic head-space analysis–ANN coupled approach.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
