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

Autores
Correndo, Adrián A.; Salvagiotti, Fernando; Garcia, Fernando Oscar; Gutiérrez Boem, Flavio Hernán
Año de publicación
2017
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
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.
Fil: Correndo, Adrián A.. International Plant Nutrition Institute; Argentina
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Garcia, Fernando Oscar. International Plant Nutrition Institute; Argentina
Fil: Gutiérrez Boem, Flavio Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Ingeniería Agrícola y Uso de la Tierra. Cátedra de Fertilidad y Fertilizantes; Argentina
Materia
Bivariate Model
Correlation
Standardised Major Axis Regression.
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/48727
Acceder
id CONICETDig_45c2af570c000d26a1c3b955bc4ae83a
oai_identifier_str oai:ri.conicet.gov.ar:11336/48727
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A modification of the arcsine-log calibration curve for analysing soil test value-relative yield relationshipsCorrendo, Adrián A.Salvagiotti, FernandoGarcia, Fernando OscarGutiérrez Boem, Flavio HernánBivariate ModelCorrelationStandardised Major Axis Regression.https://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4This 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.Fil: Correndo, Adrián A.. International Plant Nutrition Institute; ArgentinaFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria; ArgentinaFil: Garcia, Fernando Oscar. International Plant Nutrition Institute; ArgentinaFil: Gutiérrez Boem, Flavio Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Ingeniería Agrícola y Uso de la Tierra. Cátedra de Fertilidad y Fertilizantes; ArgentinaCsiro Publishing2017-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/48727Correndo, Adrián A.; Salvagiotti, Fernando; Garcia, Fernando Oscar; Gutiérrez Boem, Flavio Hernán; A modification of the arcsine-log calibration curve for analysing soil test value-relative yield relationships; Csiro Publishing; Crop & Pasture Science; 68; 3; 4-2017; 297-3041836-5795CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1071/CP16444info:eu-repo/semantics/altIdentifier/url/http://www.publish.csiro.au/cp/CP16444info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:51:25Zoai:ri.conicet.gov.ar:11336/48727instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 09:51:25.648CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
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.
Bivariate Model
Correlation
Standardised Major Axis Regression.
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
Garcia, Fernando Oscar
Gutiérrez Boem, Flavio Hernán
author Correndo, Adrián A.
author_facet Correndo, Adrián A.
Salvagiotti, Fernando
Garcia, Fernando Oscar
Gutiérrez Boem, Flavio Hernán
author_role author
author2 Salvagiotti, Fernando
Garcia, Fernando Oscar
Gutiérrez Boem, Flavio Hernán
author2_role author
author
author
dc.subject.none.fl_str_mv Bivariate Model
Correlation
Standardised Major Axis Regression.
topic Bivariate Model
Correlation
Standardised Major Axis Regression.
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
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.
Fil: Correndo, Adrián A.. International Plant Nutrition Institute; Argentina
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria; Argentina
Fil: Garcia, Fernando Oscar. International Plant Nutrition Institute; Argentina
Fil: Gutiérrez Boem, Flavio Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Ingeniería Agrícola y Uso de la Tierra. Cátedra de Fertilidad y Fertilizantes; 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 2017-04
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/48727
Correndo, Adrián A.; Salvagiotti, Fernando; Garcia, Fernando Oscar; Gutiérrez Boem, Flavio Hernán; A modification of the arcsine-log calibration curve for analysing soil test value-relative yield relationships; Csiro Publishing; Crop & Pasture Science; 68; 3; 4-2017; 297-304
1836-5795
CONICET Digital
CONICET
url http://hdl.handle.net/11336/48727
identifier_str_mv Correndo, Adrián A.; Salvagiotti, Fernando; Garcia, Fernando Oscar; Gutiérrez Boem, Flavio Hernán; A modification of the arcsine-log calibration curve for analysing soil test value-relative yield relationships; Csiro Publishing; Crop & Pasture Science; 68; 3; 4-2017; 297-304
1836-5795
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1071/CP16444
info:eu-repo/semantics/altIdentifier/url/http://www.publish.csiro.au/cp/CP16444
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Csiro Publishing
publisher.none.fl_str_mv Csiro Publishing
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844613581364002816
score 13.070432

Publicaciones similares