Quantification of soybean oil adulteration in extra virgin olive oil using portable raman spectroscopy


Tiryaki G. Y. , AYVAZ H.

JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION, vol.11, no.2, pp.523-529, 2017 (Peer-Reviewed Journal) identifier identifier

  • Publication Type: Article / Article
  • Volume: 11 Issue: 2
  • Publication Date: 2017
  • Doi Number: 10.1007/s11694-016-9419-8
  • Journal Name: JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION
  • Journal Indexes: Science Citation Index Expanded, Scopus
  • Page Numbers: pp.523-529

Abstract

Extra virgin olive oil is produced through either a cold press procedure or a centrifugation with no thermal and chemical treatments and it is considered as the best quality oil under the category of olive oils. The superior properties of olive oil due to its rich in phenolic and antioxidant content and its contribution to prevent several health problems has increased the demand for olive oil over the years. Consequently, it is nowadays sold at remarkably higher price than regular vegetable oils in the market. Unfortunately, extra virgin olive oil (EVOO) has been adulterated with other cheap oils due to potential high commercial profit. Even though, there are methods available to detect the adulteration in EVOO (such as chromatographic methods and PCR),alternative simpler and faster methods are being studied. In this study, performance of portable Raman spectroscopy to quantify soybean oil (SO) adulteration [up to 25 % (w/w)] in EVOO has been evaluated. Partial Least Square Regression (PLSR) calibration models were developed and both internally (using cross-validation, leave-one-out approach) and externally (using an independent sample set) validated. The model gave standard error of prediction (SEP) of 1.34 % (w/w) SO in EVOO and correlation coefficient of prediction (rPred) of 0.99. Additionally, the residual predictive deviation (RPD) value calculated for the model was found to be 5.71, indicating that the model was considered as "good" and could be used for routine analysis and quality control applications.