A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships

Autores
Correndo, Adrián A.; Salvagiotti, Fernando; García, Fernando O.; Gutierrez Boem, Flavio Hernán
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión aceptada
Descripción
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 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.
EEA Oliveros
Fil: Correndo, Adrián A. International Plant Nutrition Institute. Latin American Southern Cone; Argentina
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; Argentina
Fil: García, Fernando O. International Plant Nutrition Institute. Latin American Southern Cone; Argentina
Fil: 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; Argentina
Fuente
Crop and Pasture Science 68 (3) : 297-304 (March 2017)
Materia
Modelos Matemáticos
Análisis del Suelo
Rendimiento
Mathematical Models
Soil Analysis
Yields
Arco Seno
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/2271
Acceder
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oai_identifier_str oai:localhost:20.500.12123/2271
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationshipsCorrendo, Adrián A.Salvagiotti, FernandoGarcía, Fernando O.Gutierrez Boem, Flavio HernánModelos MatemáticosAnálisis del SueloRendimientoMathematical ModelsSoil AnalysisYieldsArco SenoThis 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.EEA OliverosFil: Correndo, Adrián A. International Plant Nutrition Institute. Latin American Southern Cone; ArgentinaFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; ArgentinaFil: García, Fernando O. International Plant Nutrition Institute. Latin American Southern Cone; ArgentinaFil: 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; Argentina2018-04-18T14:31:29Z2018-04-18T14:31:29Z2017-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/22711836-09471836-5795https://doi.org/10.1071/CP16444Crop and Pasture Science 68 (3) : 297-304 (March 2017)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)2025-10-23T11:16:30Zoai:localhost:20.500.12123/2271instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-23 11:16:30.879INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
title A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
spellingShingle A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
Correndo, Adrián A.
Modelos Matemáticos
Análisis del Suelo
Rendimiento
Mathematical Models
Soil Analysis
Yields
Arco Seno
title_short A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
title_full A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
title_fullStr A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
title_full_unstemmed A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
title_sort A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
dc.creator.none.fl_str_mv Correndo, Adrián A.
Salvagiotti, Fernando
García, Fernando O.
Gutierrez Boem, Flavio Hernán
author Correndo, Adrián A.
author_facet Correndo, Adrián A.
Salvagiotti, Fernando
García, Fernando O.
Gutierrez Boem, Flavio Hernán
author_role author
author2 Salvagiotti, Fernando
García, Fernando O.
Gutierrez Boem, Flavio Hernán
author2_role author
author
author
dc.subject.none.fl_str_mv Modelos Matemáticos
Análisis del Suelo
Rendimiento
Mathematical Models
Soil Analysis
Yields
Arco Seno
topic Modelos Matemáticos
Análisis del Suelo
Rendimiento
Mathematical Models
Soil Analysis
Yields
Arco Seno
dc.description.none.fl_txt_mv 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 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.
EEA Oliveros
Fil: Correndo, Adrián A. International Plant Nutrition Institute. Latin American Southern Cone; Argentina
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Departamento de Agronomía; Argentina
Fil: García, Fernando O. International Plant Nutrition Institute. Latin American Southern Cone; Argentina
Fil: 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; Argentina
description 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 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.
publishDate 2017
dc.date.none.fl_str_mv 2017-03
2018-04-18T14:31:29Z
2018-04-18T14:31:29Z
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12123/2271
1836-0947
1836-5795
https://doi.org/10.1071/CP16444
url http://hdl.handle.net/20.500.12123/2271
https://doi.org/10.1071/CP16444
identifier_str_mv 1836-0947
1836-5795
dc.language.none.fl_str_mv eng
language eng
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Crop and Pasture Science 68 (3) : 297-304 (March 2017)
reponame:INTA Digital (INTA)
instname:Instituto Nacional de Tecnología Agropecuaria
reponame_str INTA Digital (INTA)
collection INTA Digital (INTA)
instname_str Instituto Nacional de Tecnología Agropecuaria
repository.name.fl_str_mv INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuaria
repository.mail.fl_str_mv tripaldi.nicolas@inta.gob.ar
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score 12.982451

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