Thermal Stability Assessment of Vegetable Oils by Raman Spectroscopy and Chemometrics

Author(s)

Alvarenga, Benedito Roberto, Jr. ; Neres Xavier, Felipe Augusto ; Felipe Soares, Frederico Luis ; Carneiro, Renato Lajarim

• Document type: Journal article
• Source: FOOD ANALYTICAL METHODS; v. 11, n. 7, p. 8-pg., 2018-07-01.

Abstract

Vegetable oils are widely used in culinary, e.g. in deep frying, cooking, and baking. During these processes, the oils are submitted to high temperatures, giving rise to unhealthy compounds. The risk for the health related to oil consumption resulted in a search for more healthy and stable oils, which could maintain their properties during the cooking process. The aim of this work was to evaluate the thermal stability of the most common oils used for cooking in Brazil by Raman spectroscopy. Eight types of vegetable oils (cotton, extra virgin olive oil, refined olive oil, canola, coconut, sunflower, corn, and soybean) were evaluated, heating them at temperatures ranging from 25 A degrees C to 205 A degrees C. The stability of oils presented high correlation with their smoke points. As expected, the more evident spectral changes were observed in the oils that present lower smoke points. The refined oils, which in general present higher smoke points, presented better stability. In this study, the more stable oils were sunflower, cotton, and canola. These results showed that Raman spectroscopy allied with chemometric tools as a fast and accurate method to evaluate the thermal stability of edible oils. At the same way, this technique could be employed to monitor and check the quality of oils used in restaurants. (AU)

• FAPESP's process: 17/13095-0 - Experimental design applied to forced degradation of Nitazoxanide and Sofosbuvir pharmaceutical drugs
• Grantee: Benedito Roberto de Alvarenga Junior
• Support Opportunities: Scholarships in Brazil - Doctorate
• FAPESP's process: 10/16520-5 - Application of calibration chemometrics methods and multivariate curve resolution in Raman spectroscopy for qualitative, quantitative and polymorphism analyses in medicines
• Grantee: Renato Lajarim Carneiro
• Support Opportunities: Regular Research Grants