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dc.contributor.authorMoral, Francisco Jesús, 1968--
dc.contributor.authorSerrano, João-
dc.date.accessioned2024-11-07T15:34:21Z-
dc.date.available2024-11-07T15:34:21Z-
dc.date.issued2019-
dc.identifier.issn1385-2256-
dc.identifier.urihttp://hdl.handle.net/10662/23140-
dc.descriptionPublicado en: Precision Agriculture, Volume 20, Pages 1000–1014, (2019); con DOI: https://doi.org/10.1007/s11119-018-09631-9es_ES
dc.description.abstractUsually, soils utilised for livestock production have similar high spatial variability as those for agricultural or forest use. As a consequence, it is necessary to determine the spatial patterns of the main soil properties as the first stage to implement site-specific management. However, this has to be performed using an inexpensive technique because the profitability in these types of farm are very low, so owners need a cheap, effective, and reliable method to know which zones have similar production potential. Using soil apparent electrical conductivity (ECa) measurements, obtained with a contact sensor at many locations, as the basis to perform a directed soil sampling, 10 samples were taken at two depths (0–0.25 m and 0.25–0.50 m) in a 2.3 ha field in Évora (southern Portugal). Firstly, relationships between ECa and many soil properties were analysed using regression analysis. Six soil properties (clay, silt, fine sand, soil moisture content, pH, and cation exchange capacity) were significantly correlated with ECa. Consequently, spatial distributions of these variables were visualised using map algebra techniques. Later, a fuzzy clustering algorithm was utilised to delineate management zones, resulting in two subfields to be managed separately. Finally, a principal component analysis was conducted to analyse the influence of the soil properties and elevation on the soil variability. It was determined that elevation and clay were the most important contributing properties. Therefore, these can be regarded as key latent variables in this soil. Results showed that low-cost data based on ECa surveys can be used to implement site-specific management in soils with permanent pastures, such as those in the montado or dehesa ecosystems, in the southwest of the Iberian Peninsula.es_ES
dc.description.sponsorshipThis research was funded by the Junta de Extremadura and the European Regional Development Fund (ERDF) through the Project GR15050 (Research Group TIC008), by ERDF through the Operational Programme for Competitiveness Factors: COMPETE and National Funds through FCT: Foundation for Science and Technology under the Strategic Project PEst-C/AGR/UI0115/2011 and under the FCT Project: EXCL_AGR-TEC_0336_2012, and also by ERDF and the Spanish Ministry of Economy and Competitiveness through the Project AGL2015-65036-C3-3-R.es_ES
dc.format.extent27 p.es_ES
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenges_ES
dc.publisherSpringeres_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectGestión específica del lugares_ES
dc.subjectSensor de contactoes_ES
dc.subjectConductividad eléctrica aparente del sueloes_ES
dc.subjectAnálisis de componentes principaleses_ES
dc.subjectSite-specific managementes_ES
dc.subjectContact sensores_ES
dc.subjectSoil apparent electrical conductivityes_ES
dc.subjectPrincipal component analysises_ES
dc.titleUsing low‑cost geophysical survey to map soil properties and delineate management zones on grazed permanent pastureses_ES
dc.typearticlees_ES
dc.description.versionpeerReviewedes_ES
europeana.typeTEXTen_US
dc.rights.accessRightsopenAccesses_ES
dc.subject.unesco2202.01 Conductividades_ES
dc.subject.unesco2511 Ciencias del Suelo (Edafología)es_ES
dc.subject.unesco2511.03 Cartografía de Sueloses_ES
dc.subject.unesco2511.05 Clasificación de Sueloses_ES
europeana.dataProviderUniversidad de Extremadura. Españaes_ES
dc.identifier.bibliographicCitationMoral, F.J., Serrano, J.M. (2019). Using low-cost geophysical survey to map soil properties and delineate management zones on grazed permanent pastures. Precision Agriculture, 1-27es_ES
dc.type.versionacceptedVersiones_ES
dc.contributor.affiliationUniversidade de Évora. Portugales_ES
dc.contributor.affiliationUniversidad de Extremadura. Departamento de Expresión Gráficaes_ES
dc.contributor.affiliationUniversidad de Extremadura. Grupo de Investigación Alcántara-
dc.contributor.affiliationUniversidad de Extremadura. Instituto de Investigación de la Dehesa (INDEHESA)-
dc.relation.publisherversionhttps://link.springer.com/article/10.1007/s11119-018-09631-9es_ES
dc.identifier.doi10.1007/s11119-018-09631-9-
dc.identifier.publicationtitlePrecision Agriculturees_ES
dc.identifier.e-issn1573-1618-
dc.identifier.orcid0000-0001-8465-1318es_ES
Colección:DEXGR - Artículos

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