Controle de qualidade de óleos de linhaça e ginkgo biloba usando espectrometria no infravermelho médio e ferramentas quimiométricas

• Autor(a) principal: Souza, Letícia Maria de
• Data de Publicação: 2018
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Repositório Institucional da UFU
• Texto Completo: https://repositorio.ufu.br/handle/123456789/21078; http://dx.doi.org/10.14393/ufu.te.2018.64
• topic: Linhaça; Ginkgo biloba; Nutracêuticos; Controle de qualidade; PLS; PLS-DA; Quality control; Flaxseed; Óleos; Oils; CNPQ::CIENCIAS EXATAS E DA TERRA::QUIMICA::QUIMICA ANALITICA; CNPQ::CIENCIAS EXATAS E DA TERRA::QUIMICA::QUIMICA ANALITICA::INSTRUMENTACAO ANALITICA

The growing interest in plant-based therapies aimed at the prevention and/or treatment of various pathologies has become increasingly noticeable. In recent years, there has been a significant increase in the number of scientific studies aimed at proving these benefits.Flaxseed is an oil rich in α-Tocopherol and α-linolenic acid, components with anticancer effects studied, in addition to its application in the prevention of heart disease and diabetes. Ginkgo biloba extract and oil, in turn, has been proposed in the literature as a promising candidate in the treatment of degenerative diseases of the nervous system, with potential beneficial effects in the prevention of throat, cervix, ovary and control cancer hormonal activity.In this context, extra virgin oils from Ginkgo biloba and Linnaeus have become high added value raw materials, making it possible to adulterate targets, which results in the need to develop tools to control their quality.Thus, the main objective of this work was the development ofefficient analytical methodologies to detect and classify adulterations in Flaxseed and Ginkgo biloba extra virgin oil samples and to quantify lower cost vegetable oils such as soybean oil, sunflower oil, corn oil and Mineral oil using the Medium InfraredSpectrometry technique coupled with the Partial Minimum Square Multivariate Calibration (PLS) and Discriminating Partial Minimum Square Analysis (PLS-DA) methods, applying in commercial samples, in order to propose such methodologies as stages a to be implemented in routine analyzes and control of quality and purity of these extra virgin oils by inspection agencies. The multivariate validation was evaluated according to ASTM 1655-05, by calculating NAS and Merit Figures for the PLS models obtained, while for the PLS-DA the parameters of the Bayes Confusion Table were evaluated. The constructed models were efficient in detecting adulterations by vegetable oils of lower nutritional value.