Avaliação de adulteração em farinha de maca peruana por espectroscopia e colorimetria associados a métodos quimiométricos

• Ano de defesa: 2020
• Autor(a) principal: Rodrigues, Heloísa de Carvalho
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Tecnológica Federal do Paraná; Medianeira; Brasil; Programa de Pós-Graduação em Tecnologia de Alimentos; UTFPR
• Palavras-chave em Português: Análise de componentes principais; Análise espectral; Colorimetria; Principal components analysis; Spectrum analysis; Colorimetry; CNPQ::CIENCIAS AGRARIAS::CIENCIA E TECNOLOGIA DE ALIMENTOS; Tecnologia de Alimentos
• Link de acesso: http://repositorio.utfpr.edu.br/jspui/handle/1/5288

Peruvian Maca is a food originally found in the Central Andes of Peru, is widely used thanks to its believed medicinal properties, which are attributed by popular cultures. It is sold in the form of flour, consisting of carbohydrates, proteins, fibers, lipids, amino acids, and minerals. Its cultivation occurs between 3700-4500 meters above sea level, exposed to extreme conditions of temperature and solar radiation. Due to the suggested nutritional richness, Maca flour can be used to replace other flours in order to enrich processed foods, such as cakes, bread, pies, and derivatives. For this, it is interesting to study the possibility of detecting tampering with this product. In this way, this work proposes the study of the detection of adulteration in Peruvian Maca flour with rice flour and rice bran. After the adulterations in the proportions of 25%, 50%, and 75%, the samples were evaluated by colorimetry and by the technique of spectroscopy in the near-infrared (NIR), being the results evaluated through Principal Components Analysis (PCA). At the end of the study, the results demonstrated that NIR spectroscopy combined with principal component analysis proved to be efficient for the detection of adulteration in Maca samples with at least 50% adulteration. The colorimetric method was not efficient to distinguish between pure and adulterated samples.