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The development of simple predictors of sulfur (S) mineralization and its correlation with field-derived data may help improving corn S availability diagnosis. The objectives of this study were (1) to compare methods to estimate soil S mineralization, (2) to develop a model to predict soil S mineralization from S mineralization indexes and edaphic variables, and (3) to predict fieldgrown corn S uptake (Suptake) and apparent S mineralization (Smin-app) [ver mas...]
dc.contributor.authorCarciochi, Walter Daniel
dc.contributor.authorWyngaard, Nicolás
dc.contributor.authorDivito, Guillermo Adrián
dc.contributor.authorCabrera, Miguel L.
dc.contributor.authorReussi Calvo, Nahuel Ignacio
dc.contributor.authorEcheverria, Hernan Eduardo
dc.date.accessioned2018-03-27T15:53:07Z
dc.date.available2018-03-27T15:53:07Z
dc.date.issued2018-04
dc.identifier.issn0178-2762 (Print)
dc.identifier.issn1432-0789 (Online)
dc.identifier.otherhttps://doi.org/10.1007/s00374-018-1266-9
dc.identifier.urihttp://hdl.handle.net/20.500.12123/2137
dc.identifier.urihttps://link.springer.com/article/10.1007/s00374-018-1266-9
dc.description.abstractThe development of simple predictors of sulfur (S) mineralization and its correlation with field-derived data may help improving corn S availability diagnosis. The objectives of this study were (1) to compare methods to estimate soil S mineralization, (2) to develop a model to predict soil S mineralization from S mineralization indexes and edaphic variables, and (3) to predict fieldgrown corn S uptake (Suptake) and apparent S mineralization (Smin-app) from different S mineralization indexes and edaphicclimatic variables.We evaluated 26 experimental sites where we measured edaphic variables as soil organic C (SOC), organic C in the particulate fraction (C-PF), S mineralization potential (Smin-10wk), S mineralized during a short-term (7 days) aerobic incubation + initial inorganic S (Smin-7d+ Sinorg), and N mineralized during a short-term (7 days) anaerobic incubation (Nan). Additionally, 18 field experiments were carried out to quantify Suptake and Smin-app. TheC-PF, Smin-7d+ Sinorg, Nan, and SOC were variables significantly correlated with Smin-10wk (r = 0.89, 0.89, 0.88, and 0.85, respectively). We developed a simple model to predict Smin-10wk from selected edaphic variables (Smin-10wk= 0.038*Nan + 0.106*SOC + 0.74; Ra 2 = 0.87). The Smin-10wk, C-PF, and Smin-7d+ Sinorg showed a liner-plateau association with Suptake (R2 = 0.73, 0.53, and 0.48, respectively). We modified the method to estimate Smin-app to account for S losses (Smin-app (modified)) and developed a model to predict Smin-app (modified) from CPF (Smin-app (modified)= 4.65*C-PF + 9.86; R2 = 0.62) or Smin-10wk (Smin-app (modified)= 3.0*Smin-10wk+ 7.4; R2 = 0.54). Our results demonstrate that S mineralization indexes can be used to predict corn S availability under field conditions.eng
dc.formatapplication/pdfeng
dc.language.isoeng
dc.rightsinfo:eu-repo/semantics/restrictedAccesseng
dc.sourceBiology and fertility of soils 54 (3) : 349–362. (April 2018)eng
dc.subjectFertilidad del Suelo
dc.subjectSoil Fertilityeng
dc.subjectExperimentación en Campo
dc.subjectField Experimentationeng
dc.subjectAzufre
dc.subjectSulphureng
dc.subjectMineralización
dc.subjectMineralizationeng
dc.titleA Comparison of indexes to estimate corn S uptake and S mineralization in the fieldeng
dc.typeinfo:ar-repo/semantics/artículo
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.description.origenEEA Balcarce
dc.gic156648
dc.description.filFil: Carciocchi, Walter Daniel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.filFil: Wyngaard, Nicolás. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.filFil: Divito, Guillermo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina.
dc.description.filFil: Cabrera, Miguel L. University of Georgia. Crop and Soil Sciences Department; Estados Unidos
dc.description.filFil: Reussi Calvo, Nahuel Ignacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
dc.description.filFil: Echeverria, Hernan Eduardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Balcarce. Unidad Integrada. Universidad Nacional de Mar del Plata. Facultad de Ciencias Agrarias; Argentina
dc.subtypecientifico


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