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
- Institución
- Instituto Nacional de Tecnología Agropecuaria
- OAI Identificador
- oai:localhost:20.500.12123/2271
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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)2025-09-29T13:44:17Zoai: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:l2025-09-29 13:44:18.216INTA 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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1844619121579261952 |
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12.559606 |