Emprego de espectrômetro portátil na região do infravermelho próximo para controle de qualidade de azeite de oliva extravirgem

• Ano de defesa: 2022
• Autor(a) principal: Tosato, Flavia
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Espírito Santo; BR; Doutorado em Química; Centro de Ciências Exatas; UFES; Programa de Pós-Graduação em Química
• Palavras-chave em Português: Azeite de oliva; Controle da qualidade; NIR portátil; subject.br-rjbn; Química
• Link de acesso: http://repositorio.ufes.br/handle/10/15939

The application of spectroscopy in the study of food is on the rise, due to the demand of the food sector to face the challenges related to food quality and authenticity. Extra virgin olive oil (AOEV) is one of the main targets among food products. Although there is legislation to protect this food against fraud, there are still some points that need attention, mainly focused on quality control analysis of this product. Thus, this thesis aims to present the advances in infrared spectroscopy in the near region using the portable equipment approach, MicroNIR combined with multivariate statistical analysis for AOEV quality control. For this, case studies were developed focusing on the classification and detection of AOEV adulteration with vegetable oils (soybean, corn, canola and sunflower). The PCA and SIMCA models distinguished commercial samples according to the information contained on their labels; in addition, it identified the olive oil samples in the dataset with the blends. These results are in excellent agreement with the physical-chemical results that corroborate the limits established by law. The accuracy of the PLS models was 0.5 to 1.8 m% for transmittance mode and 1.7 to 4.6 m% for reflectance mode. In order to validate the proposed models, the classification and quantification of soybean oil was carried out for 60 samples of commercial olive oil seized by the Espírito Santo state police. In addition, physical chemical tests (acidity, peroxide and ultraviolet absorption) were performed on commercial samples. The PLS regression model built to quantify soybean oil showed a coefficient of determination (R2) greater than 0.99, proving to be satisfactory. The results showed that all samples analyzed had a high adulterant content and cannot be classified as extra virgin olive oil. With this, the application of MicroNIR and chemometric tools can be used for the quality control of AOEV adulterated with vegetable oils.