Assessing the agronomic and environmental effects of the application of cattle manure compost on soil by multivariate methods
Multivariate analysis was used for interpreting data from a pot experiment using samples of three Spanish soils. Samples of soil fertilized with compost were compared with untreated control samples. We also compared the effect of adding the compost to soil with a controlled moisture content of 50% o...
| Autores: | , , , |
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| Formato: | artículo |
| Estado: | Versión aceptada para publicación |
| Fecha de publicación: | 2008 |
| País: | España |
| Recursos: | Consejo Superior de Investigaciones Científicas (CSIC) |
| Repositorio: | DIGITAL.CSIC. Repositorio Institucional del CSIC |
| OAI Identifier: | oai:digital.csic.es:10261/342938 |
| Acesso em linha: | http://hdl.handle.net/10261/342938 https://api.elsevier.com/content/abstract/scopus_id/43049145500 |
| Access Level: | acceso abierto |
| Palavra-chave: | Principal component analysis Bovine manure Compost Hierarchical cluster analysis Multivariate analysis http://metadata.un.org/sdg/13 Take urgent action to combat climate change and its impacts |
| Resumo: | Multivariate analysis was used for interpreting data from a pot experiment using samples of three Spanish soils. Samples of soil fertilized with compost were compared with untreated control samples. We also compared the effect of adding the compost to soil with a controlled moisture content of 50% of its water holding capacity (WHC), and to a near-saturated soil (95% WHC). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were used; they perfectly differentiated sample groups both as a function of the treatment applied and by sampling date. The compost samples were characterized by higher pH, electrical conductivity (EC), organic matter (OM) content and cation exchange capacity (CEC), together with nutrient concentrations than the control pots. The pots with a soil-compost mixture at 95% WHC presented lower values of EC, CEC, inorganic N, K, Na and B than the mixtures at 50% WHC. Multivariate methods may therefore be useful for the analysis and interpretation of a large number of data in soil research. |
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