Quantifying seed oil adulteration in extra virgin olive oil by multiple linear regression analysis of fatty acid profiles
AbstractOlive oil is more expensive than most of vegetableand seed types of oil which makes extra virgin olive oil vulnerableto adulteration. The aim of the study was to evaluate the effec-tiveness of chromatographic fatty acid profile determination forthe detection of extra virgin olive oil adulteration with soybean,sunflower and rapeseed oil. Multiple linear regression modelswere built to predict the content of foreign oil in extra virginolive oil. Models A were built with the use of fatty acid pro-files, while models B were built on the basis of calculated sumsof fatty acid groups and the relations between them. The predic-tion ability of the models was assessed and confirmed using theroot mean square errors of calibration (RMSEC) and the rootmean square errors of cross validation (RMSECV). The lowerRMSEC and RMSECV were obtained for models A in the caseof models built for the data obtained for extra virgin olive oiladulterated with soybean oils and rapeseed oil and equaled 1.4,1.5 and 3.7, 4.4, respectively. In the case of MLR models builtfor the data obtained for extra virgin olive oil adulterated withsunflower oil a better prediction ability was obtained for modelB with RMSEC and RMSECV values at 1.6 and 1.8.
|Journal series||PhD Interdisciplinary Journal, ISSN 2300-617X , (0 pkt)|
|Publication size in sheets||0.5|
|Keywords in Polish||zafałszowania żywności, jakość, profil kwasów tłuszczowych|
|Keywords in English||gas chromatography; olive oil quality; multiplelinear regression; fatty acid profile|
|Score|| = 0.0, 19-12-2019, ArticleFromJournal|
= 0.0, 19-12-2019, ArticleFromJournal
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.