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Resumen
This article aims to discuss the arcsine–log calibration curve (ALCC) method designed for the Better Fertiliser Decisions for Cropping Systems (BFDC) to calibrate relationships between relative yield (RY) and soil test value (STV). Its main advantage lies in estimating confidence limits of the critical value (CSTV). Nevertheless, intervals for 95% confidence level are often too wide, and authors suggest a reduction in the confidence level to 70% in order [ver mas...]
dc.contributor.authorCorrendo, Adrián A.
dc.contributor.authorSalvagiotti, Fernando
dc.contributor.authorGarcía, Fernando O.
dc.contributor.authorGutierrez Boem, Flavio Hernán
dc.date.accessioned2018-04-18T14:31:29Z
dc.date.available2018-04-18T14:31:29Z
dc.date.issued2017-03
dc.identifier.issn1836-0947
dc.identifier.issn1836-5795
dc.identifier.otherhttps://doi.org/10.1071/CP16444
dc.identifier.urihttp://hdl.handle.net/20.500.12123/2271
dc.description.abstractThis article aims to discuss the arcsine–log calibration curve (ALCC) method designed for the Better Fertiliser Decisions for Cropping Systems (BFDC) to calibrate relationships between relative yield (RY) and soil test value (STV). Its main advantage lies in estimating confidence limits of the critical value (CSTV). Nevertheless, intervals for 95% confidence level are often too wide, and authors suggest a reduction in the confidence level to 70% in order to achieve narrower estimates. Still, this method can be further improved by modifying specific procedures. For this purpose, several datasets belonging to the BFDC were used. For any confidence level, estimates with the modified ALCC procedures were always more accurate than the original ALCC. The overestimation of confidence limits with the original ALCC was inversely related to the correlation coefficient of the dataset, which might allow a relatively simple and reliable correction of previous estimates. In addition, because the method is based on the correlation between STV and RY, the importance to test it for significance is emphasised in order to support the hypothesis of a relationship. Then, the modified ALCC approach could also allow a more reliable comparison of datasets by slopes of the bivariate linear relationship between transformed variables.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.sourceCrop and Pasture Science 68 (3) : 297-304 (March 2017)es_AR
dc.subjectModelos Matemáticoses_AR
dc.subjectMathematical Modelseng
dc.subjectAnálisis del Sueloes_AR
dc.subjectSoil Analysiseng
dc.subjectRendimientoes_AR
dc.subjectYieldseng
dc.subject.otherArco Senoes_AR
dc.titleA modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationshipses_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/acceptedVersiones_AR
dc.rights.licenseCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.description.origenEEA Oliveroses_AR
dc.description.filFil: Correndo, Adrián A. International Plant Nutrition Institute. Latin American Southern Cone; Argentinaes_AR
dc.description.filFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; Argentinaes_AR
dc.description.filFil: García, Fernando O. International Plant Nutrition Institute. Latin American Southern Cone; Argentinaes_AR
dc.description.filFil: Gutiérrez Boem, Flavio Hernán. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Fertilidad y Fertilizantes; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Pque. Centenario. Instituto de Investigaciones En Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomia. Instituto de Investigaciones En Biociencias Agrícolas y Ambientales; Argentinaes_AR
dc.subtypecientifico


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