Publicação
Image analysis for automatic characterization of polyhydroxyalcanoates granules
| Resumo: | A new monitoring approach for polyhydroxyalcanoates (PHA) granules identification and characterization based on image analysis procedures is proposed. PHA granules were analyzed by Sudan Black B (SBB) staining in an enhanced biological phosphorus removal (EBPR) system. Color images captured on an optical microscope were analyzed through quantitative image analysis. The distribution of PHA granules was estimated by determination of the proportion of blue-black pixels. A relationship was found between image analysis parameters and PHA concentration. In conclusion, it may be inferred that the present image analysis procedure is suitable to quantify PHA granules in SBB staining images and a promising alternative to standard analysis. |
|---|---|
| Autores principais: | Mesquita, D. P. |
| Outros Autores: | Selvaggio, Gianluca; Cunha, J. R.; Leal, Cristiano S.; Amaral, A. L.; Ferreira, Eugénio C. |
| Assunto: | Image analysis Enhanced biological phosphorus removal (EBPR) Polyhydroxyalcanoate granules (PHA) Sudan black B (SBB) |
| Ano: | 2013 |
| País: | Portugal |
| Tipo de documento: | comunicação em conferência |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade do Minho |
| Idioma: | inglês |
| Origem: | RepositóriUM - Universidade do Minho |
| Resumo: | A new monitoring approach for polyhydroxyalcanoates (PHA) granules identification and characterization based on image analysis procedures is proposed. PHA granules were analyzed by Sudan Black B (SBB) staining in an enhanced biological phosphorus removal (EBPR) system. Color images captured on an optical microscope were analyzed through quantitative image analysis. The distribution of PHA granules was estimated by determination of the proportion of blue-black pixels. A relationship was found between image analysis parameters and PHA concentration. In conclusion, it may be inferred that the present image analysis procedure is suitable to quantify PHA granules in SBB staining images and a promising alternative to standard analysis. |
|---|