Comparative Fingerprint Changes of Toxic Volatiles in Low PUFA Vegetable Oils Under Deep-Frying

• Autor(a) principal: Molina-Garcia, L
• Data de Publicação: 2017
• Outros Autores: Santos, CSP, Cunha, SC, Casal, S, Fernandes, JO
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10216/111557
• topic: Volatile fraction; Oxidative stability

The volatile fraction of three vegetable oils recommended for deep-frying due to their high MUFA:PUFA ratios, namely extra-virgin olive oil, peanut oil and canola oil, was compared before and after frying potatoes, with a particular focus on toxic volatiles. For the purpose, a headspace solid-phase-micro extraction technique coupled with gas chromatography and mass spectrometry was optimized, with semi-quantification achieved using two internal standards. Significant qualitative and quantitative differences were observed, both before and after frying. From a total of 51 compounds, aldehydes were the main group formed after deep-frying, their nature and abundance being highly associated with the initial fatty acid composition, particularly linoleic acid (r2 = −0.999, p ≤ 0.001). Globally, extra-virgin olive oil revealed fewer formations of unsaturated aldehydes, including toxic ones, and correlated with lower amounts of degradation indicators, as polar compounds (r2 = 0.998, p ≤ 0.001) and p-anisidine value (r2 = 0.991, p ≤ 0.001). Despite the similarities in total unsaturation degree between canola and peanut oils, the former presented lower amount of volatiles, including E,E-2,4-decadienal and acrolein, the more toxic ones. These results highlight for the pertinence of volatile analyses to evaluate and compare oil degradation under thermal and oxidative stress, while complementing other degradation indicators. Additionally, the optimized methodology allows a direct comparison of different oil matrices, supporting further developments into more general methods for volatiles quantification, enabling more efficient comparison of results between research teams.