Science: an intelligent knife to analyze extra virgin olive oils
An original and yet scientific method to assess the authenticity of extra virgin olive oil.
It has been developed by the University of Messina, in Italy, and it is, to say the least, original.
An article on the “progettoager.it” provides more information concerning the iKnife (intelligent knife), used in the labs of the Sicilian university.
“ This technique - the article explains - is already used in medicine to recognize tumors during operations, and it has been proven effective in differentiating, in just a few seconds, samples of oils of different geographical origin based on the fat content (lipid fingerprint).”
The iKnife "is made of an electrosurgical scalpel and a high-resolution mass spectrometer and works as follows: the scalpel heats the oil producing molecular vapors that are conveyed to a Rheims source (Rapid Evaporative Ionisation Mass Spectrometry) where the molecules become positive or negative ions (thermionic ionization). The instrument analyzes the composition of these vapors and stores them in a database. The data are then processed by a software that, through statistical methods, groups similar samples and catalogs them into well-defined categories. By comparing these samples it is possible to identify with maximum confidence and in real time the origin of an oil through the reading of the vapors present in the oil".
A method 100% valid as researchers argue: "Thanks to the software, researchers at the University of Messina participating in the project VIOLIN, supported by Ager, have been able to classify over 200 samples of high quality EVOO from northern, central and southern Italy - including some PDO (Protected Designation of Origin), PGI (Protected Geographical Indication) and monovarietal oils.
Thanks to the speed of analysis and accuracy of the results, the comparison has a validity close to 100%.
The research group has recently published an article in OPEN ACCESS mode in the journal LWT-Food Science and Technology, published by Elsevier and with Impact Factor 4.006. The article is published and available in English at the following link
https://doi.org/10.1016/j.lwt.2020.110715https://www.sciencedirect.com/science/article/pii/S0023643820317035?via%3Dihub 08 July 2021
