| Título: |
Self-organizing maps as a chemometric tool for aromatic pattern recognition of soluble coffee - doi: 10.4025/actascitechnol.v34i1.10892 |
| Autores: |
Bona, Evandro; Universidade Tecnológica Federal do Paraná Silva, Rui Sérgio dos Santos Ferreira da; Universidade Estadual de Londrina Borsato, Dionísio; Universidade Estadual de Londrina Bassoli, Denisley Gentil; Companhia Iguaçu de Café Solúvel |
| Fecha: | 2011-11-23 |
| Publicador: | Universidade Estadual De Maringá |
| Fuente: |
Ver documento |
| Tipo: |
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| Tema: |
self organizing maps; soluble coffee; electronic nose Tecnologia de Alimentos |
| Descripción: |
The electronic nose (EN) is an instrument very used for food flavor analysis. However, it is also necessary to integrate the equipment with a multivariable pattern recognition system, and to this end the principal component analysis (PCA) is the first choice. Alternatively, self-organizing maps (SOM) had been also suggested, since they are a nonlinear and reliable technique. In this study SOM were used to distinguish soluble coffee according to EN data. The proposed methodology had identified all of the seven coffees evaluated; in addition, the groups and relationships detected were similar to those obtained through PCA. Also, the analysis of network weights allowed gathering the e-nose sensors into 4 groups according to the behavior regarding the samples. Results confirm SOM as an efficient tool to EN data pos-processing, and have showed the methodology as a promising choice for the development of new products and quality control of soluble coffee. |
| Idioma: | Inglés |