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

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 criti...

Full description

Bibliographic Details
Main Authors: Correndo, Adrián A., Salvagiotti, Fernando, García, Fernando O., Gutierrez Boem, Flavio Hernán
Format: Artículo
Language:Inglés
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/2271
https://doi.org/10.1071/CP16444
_version_ 1855483025729519616
author Correndo, Adrián A.
Salvagiotti, Fernando
García, Fernando O.
Gutierrez Boem, Flavio Hernán
author_browse Correndo, Adrián A.
García, Fernando O.
Gutierrez Boem, Flavio Hernán
Salvagiotti, Fernando
author_facet Correndo, Adrián A.
Salvagiotti, Fernando
García, Fernando O.
Gutierrez Boem, Flavio Hernán
author_sort Correndo, Adrián A.
collection INTA Digital
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.
format Artículo
id INTA2271
institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
language Inglés
publishDate 2018
publishDateRange 2018
publishDateSort 2018
record_format dspace
spelling INTA22712019-02-01T18:32:19Z A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships Correndo, Adrián A. Salvagiotti, Fernando García, Fernando O. Gutierrez Boem, Flavio Hernán Modelos Matemáticos Análisis del Suelo Rendimiento Mathematical Models Soil Analysis Yields Arco Seno 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 2018-04-18T14:31:29Z 2018-04-18T14:31:29Z 2017-03 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/acceptedVersion http://hdl.handle.net/20.500.12123/2271 1836-0947 1836-5795 https://doi.org/10.1071/CP16444 eng 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) application/pdf Crop and Pasture Science 68 (3) : 297-304 (March 2017)
spellingShingle Modelos Matemáticos
Análisis del Suelo
Rendimiento
Mathematical Models
Soil Analysis
Yields
Arco Seno
Correndo, Adrián A.
Salvagiotti, Fernando
García, Fernando O.
Gutierrez Boem, Flavio Hernán
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
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_short A modification of the arcsine–log calibration curve for analysing soil test value–relative yield relationships
title_sort modification of the arcsine log calibration curve for analysing soil test value relative yield relationships
topic Modelos Matemáticos
Análisis del Suelo
Rendimiento
Mathematical Models
Soil Analysis
Yields
Arco Seno
url http://hdl.handle.net/20.500.12123/2271
https://doi.org/10.1071/CP16444
work_keys_str_mv AT correndoadriana amodificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT salvagiottifernando amodificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT garciafernandoo amodificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT gutierrezboemflaviohernan amodificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT correndoadriana modificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT salvagiottifernando modificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT garciafernandoo modificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships
AT gutierrezboemflaviohernan modificationofthearcsinelogcalibrationcurveforanalysingsoiltestvaluerelativeyieldrelationships