Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

• Ano de defesa: 2010
• Autor(a) principal: Inácio, Maria Raquel Cavalcanti
• Orientador(a): Moura, Maria de Fátima Vitória de
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio Grande do Norte
• Programa de Pós-Graduação: Programa de Pós-Graduação em Química
• Departamento: Físico-Química; Química
• País: BR
• Palavras-chave em Português: Leite em pó; Infravermelho próximo; SIMCA; PLS; PCR
• Palavras-chave em Inglês: Milk powder; Near infrared; SIMCA; PLS; PCR
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::QUIMICA
• Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/17634

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples