dc.contributorLeandro Soares de Oliveira
dc.contributorAdriana Silva Franca
dc.creatorNádia Reis
dc.date.accessioned2019-08-11T01:47:18Z
dc.date.accessioned2022-10-03T23:08:40Z
dc.date.available2019-08-11T01:47:18Z
dc.date.available2022-10-03T23:08:40Z
dc.date.created2019-08-11T01:47:18Z
dc.date.issued2012-02-28
dc.identifierhttp://hdl.handle.net/1843/BUOS-96PF4N
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3817497
dc.description.abstractCoffee has been the target of fraudulent admixtures with several materials, including coffee husks and cheaper roasted grains such as corn. Given the successful application of spectroscopic methods in the field of food adulteration as fast and reliable routine techniques, the objective of this work was to evaluate the feasibility of employing DRIFTS (Diffuse Reflectance Fourier Transform Infrared Spectroscopy) for discrimination between roasted coffee and common adulterants such as roasted corn and coffee husks. Arabica coffee beans, coffee husks and ground corn kernels were submitted to light, medium and dark roasts at temperatures ranging from 200 to 260°C. Principal Components Analysis of the DRIFTS spectra (normalized or not) and of the first derivatives of the spectra provided separation of the samples into three groups: coffee, coffee husks and corn. Classification models were developed based on Linear Discriminant Analysis and recognition and prediction abilities of these models were 100%. Such results indicate that DRIFTS presents potential for the development of a fast and reliable analytical methodology for discrimination between coffee and its common adulterants.
dc.publisherUniversidade Federal de Minas Gerais
dc.publisherUFMG
dc.rightsAcesso Aberto
dc.subjectMilho
dc.subjectEspectroscopia no infravermelho com transformada de Fourier (FTIR)
dc.subjectCasa de café
dc.subjectCafé adulteração
dc.titleDetecção de adulteração de café torrado e moído com cascas de café e milho por espectroscopia no infravermelho
dc.typeDissertação de Mestrado


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