Parallel factor analysis and multivariate curve resolution as data fusion tools to supervise a stream
In this work, a new method is proposed to monitor the distribution, evolution and correlation of dissolved organic matter on the superficial water of a stream with respect to physicochemical variables that characterize the basin and season sampling of each campaign. The method is based on measuring...
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2014 |
| País: | Argentina |
| Institución: | Consejo Nacional de Investigaciones Científicas y Técnicas |
| Repositorio: | CONICET Digital (CONICET) |
| Idioma: | inglés |
| OAI Identifier: | oai:ri.conicet.gov.ar:11336/6014 |
| Acceso en línea: | http://hdl.handle.net/11336/6014 |
| Access Level: | acceso abierto |
| Palabra clave: | Chemometrics Multivariate Curve Resolution Parallel Factor Analysis Environmental Monitoring https://purl.org/becyt/ford/1.4 https://purl.org/becyt/ford/1 |
| Sumario: | In this work, a new method is proposed to monitor the distribution, evolution and correlation of dissolved organic matter on the superficial water of a stream with respect to physicochemical variables that characterize the basin and season sampling of each campaign. The method is based on measuring fluorescence emission-excitation matrices and some physicochemical parameters of water samples through both time and space. In a first phase, parallel factor analysis (PARAFAC) or multivariate curve resolution with alternating least-squares (MCR-ALS) were applied to extract the information on the relative proportions of each fluorophore on each sample. Then, MCR-ALS was applied again to the entire database, in order to study the spatial and time distribution. This methodology was used to study the behavior of a basin stream that is significantly modified by anthropic activities. |
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