Detecção e classificação de soros lácteos em leites UHT e in natura empregando infravermelho médio com tranformada de Fourier e análises multivariadas

• Ano de defesa: 2016
• Autor(a) principal: Simone Melo Vieira
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; UFMG
• Palavras-chave em Português: Espectroscopia; Fraudes; Quimiometria; Leite; Leite Análise; Leite Adulteração e inspeção; Fourier, Espectroscopia de infravermelho por transformada de
• Link de acesso: http://hdl.handle.net/1843/BUOS-AN4FRL

Milk is a food susceptible to adulterations that can compromise its nutritional characteristics, and therefore compromise the health and economically prejudice the consumers. Among the adulterants frequently found in milk, great importance is given to the detection of whey, result of the derivatives processing such as cheeses and butters, added. This type of adulteration, prohibited by Brazilian and international legislation, corresponds to an economic fraud aimed to increasing the volume of milk sold. The inspection of the presence of whey in milk requires complex and costly analyzes that can be replaced by alternative analyzes capable of delivering fast and accurate results without demanding pre-treatment of the samples and use of reagents. In this context, the research used a medium infrared spectroscopy technique with Fourier transform and chemiometric models to propose a methodology capable of detecting and classifying of milk whey origin in raw and whole UHT milks (Ultra High Temperature). From the spectroscopic data, the chemiometric models PLS and PLS-DA were developed. The PLS quantitative predictive model was able to detect and quantify different whey contents of Minas Frescal cheese in raw milk with RMSEP (Root Mean Square Error of Prediction, % p/p) equal to 0.180. The qualitative predictive model PLS-DA was able to classify cheeses and butters whey that can be used in adulterations of UHT milk with an average error of classification for the model of prediction equal to 0.1914. The classification of the different whey in UHT milk by means of PLS-DA model corresponds to information that can be used to support surveillance actions to trace the origin of the adulterant substance. The quantitative and qualitative predictive models were validated utilizing figures of merit and were considered suitable for the purpose as fast and accurate alternative analyzes to control frauds in raw and UHT milks. The models proved that the FTIR-MIR together with chemometric models are able to provide relevant information guiding research and methodologies for detecting milk adulterations.