Segmentação geográfica e genotípica de café arábica utilizando o FTIR e análise multivariada
The coffee comes from a tree of the genus Coffea and belongs to the family Rubiaceae, which includes more than 500 genera and 6,000 species being Arabica coffee accounts for approximately 60% of the world market. There are different forms of adulteration of coffee, which may be by the addition of su...
| Autor principal: | Sato, Herily Pereira |
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| Formato: | Trabalho de Conclusão de Curso (Graduação) |
| Idioma: | Português |
| Publicado em: |
Universidade Tecnológica Federal do Paraná
2020
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| Assuntos: | |
| Acesso em linha: |
http://repositorio.utfpr.edu.br/jspui/handle/1/6770 |
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| Resumo: |
The coffee comes from a tree of the genus Coffea and belongs to the family Rubiaceae, which includes more than 500 genera and 6,000 species being Arabica coffee accounts for approximately 60% of the world market. There are different forms of adulteration of coffee, which may be by the addition of substitutes like malt, cereal, caramel, maltodextrin, and in some cases after drying. The change can also be made by mixing two different species or varieties of the same species of coffees and blending coffee beans with other high-value obtained from other regions, which have lower commercial value. There is a demand for efficient analytical methods capable of ensuring high levels of safety and quality in coffee production as FTIR. However, the interpretation of the infrared spectrum is more complex than other techniques such as high performance liquid chromatography (HPLC), so it becomes essential to use multivariate methods. The aim of this study was to develop a methodology that is able to discriminate the different genotypes of arabica coffee that is grown in Brazil. To this end, the FTIR spectra obtained are analyzed by multivariate analysis. Spectroscopy was performed on 18 samples of four regions and four different clones were analyzed in five replications totaling 90 data to be analyzed by ACP, SIMCA,KNN and FDA. The best classification routine has the LDA, however, still cannot be
considered satisfactory for this type of classification differentiation arabica coffees on the genotype. One option would be to use artificial neural networks. |
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