The impact of climate variability on soybean yields in Argentina. Multivariate regression

Autores
Penalba, O.C.; Bettolli, M.L.; Vargas, W.M.
Año de publicación
2007
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Climate variability is examined and discussed in this work, emphasizing its influence over the fluctuation of soybean yield in the Pampas (central-eastern Argentina). Monthly data of rainfall, maximum and minimum temperatures, thermal range and seasonal rainfall were analysed jointly with the soybean yield in the period 1973-2000. Low-frequency variability was significant only in the minimum temperature during November in almost all the stations. This situation is favourable to the crop since during this month, seed germination, a growth stage sensitive to low temperatures, takes place. In the crop's core production region, 72% of the series of soybean yield presented a positive trend. Except in years with extreme rainfall situations, interannual variability of the soybean yield is in phase with the seasonal rainfall interannual variability. During these years, losses in the soybean crop occurred, with yield negative anomalies greater than one standard deviation. Soybean yield showed spatial coherence at the local scale, except in the crop's core zone. The association between each climate variable and yield did not show a defined regional pattern. Summer high temperature and rainfall excesses during the period of maturity and harvest have the greatest negative impact on the crop, whilst higher minimum temperatures during the growing season favour high yields. The joint effect of climate variables over yield was studied with multivariate statistical models, assuming that the effect of other factors (such as soil, technology, pests) is contained in the residuals. The regression models represent the estimates of the yield satisfactorily (high percentage of explained variance) and can be used to assess expected anomalies of mean soybean yield for a particular year. However, the predictor variables of the yield depend on the region. Copyright © 2007 Royal Meteorological Society.
Fil:Penalba, O.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Bettolli, M.L. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Vargas, W.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fuente
Meteorol. Appl. 2007;14(1):3-14
Materia
Argentina
Climate variability
Soybean yield
Statistical models
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by/2.5/ar
Repositorio
Biblioteca Digital (UBA-FCEN)
Institución
Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
OAI Identificador
paperaa:paper_13504827_v14_n1_p3_Penalba

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network_name_str Biblioteca Digital (UBA-FCEN)
spelling The impact of climate variability on soybean yields in Argentina. Multivariate regressionPenalba, O.C.Bettolli, M.L.Vargas, W.M.ArgentinaClimate variabilitySoybean yieldStatistical modelsClimate variability is examined and discussed in this work, emphasizing its influence over the fluctuation of soybean yield in the Pampas (central-eastern Argentina). Monthly data of rainfall, maximum and minimum temperatures, thermal range and seasonal rainfall were analysed jointly with the soybean yield in the period 1973-2000. Low-frequency variability was significant only in the minimum temperature during November in almost all the stations. This situation is favourable to the crop since during this month, seed germination, a growth stage sensitive to low temperatures, takes place. In the crop's core production region, 72% of the series of soybean yield presented a positive trend. Except in years with extreme rainfall situations, interannual variability of the soybean yield is in phase with the seasonal rainfall interannual variability. During these years, losses in the soybean crop occurred, with yield negative anomalies greater than one standard deviation. Soybean yield showed spatial coherence at the local scale, except in the crop's core zone. The association between each climate variable and yield did not show a defined regional pattern. Summer high temperature and rainfall excesses during the period of maturity and harvest have the greatest negative impact on the crop, whilst higher minimum temperatures during the growing season favour high yields. The joint effect of climate variables over yield was studied with multivariate statistical models, assuming that the effect of other factors (such as soil, technology, pests) is contained in the residuals. The regression models represent the estimates of the yield satisfactorily (high percentage of explained variance) and can be used to assess expected anomalies of mean soybean yield for a particular year. However, the predictor variables of the yield depend on the region. Copyright © 2007 Royal Meteorological Society.Fil:Penalba, O.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Bettolli, M.L. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.Fil:Vargas, W.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.2007info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12110/paper_13504827_v14_n1_p3_PenalbaMeteorol. Appl. 2007;14(1):3-14reponame:Biblioteca Digital (UBA-FCEN)instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesinstacron:UBA-FCENenginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/ar2025-09-04T09:48:20Zpaperaa:paper_13504827_v14_n1_p3_PenalbaInstitucionalhttps://digital.bl.fcen.uba.ar/Universidad públicaNo correspondehttps://digital.bl.fcen.uba.ar/cgi-bin/oaiserver.cgiana@bl.fcen.uba.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:18962025-09-04 09:48:22.038Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturalesfalse
dc.title.none.fl_str_mv The impact of climate variability on soybean yields in Argentina. Multivariate regression
title The impact of climate variability on soybean yields in Argentina. Multivariate regression
spellingShingle The impact of climate variability on soybean yields in Argentina. Multivariate regression
Penalba, O.C.
Argentina
Climate variability
Soybean yield
Statistical models
title_short The impact of climate variability on soybean yields in Argentina. Multivariate regression
title_full The impact of climate variability on soybean yields in Argentina. Multivariate regression
title_fullStr The impact of climate variability on soybean yields in Argentina. Multivariate regression
title_full_unstemmed The impact of climate variability on soybean yields in Argentina. Multivariate regression
title_sort The impact of climate variability on soybean yields in Argentina. Multivariate regression
dc.creator.none.fl_str_mv Penalba, O.C.
Bettolli, M.L.
Vargas, W.M.
author Penalba, O.C.
author_facet Penalba, O.C.
Bettolli, M.L.
Vargas, W.M.
author_role author
author2 Bettolli, M.L.
Vargas, W.M.
author2_role author
author
dc.subject.none.fl_str_mv Argentina
Climate variability
Soybean yield
Statistical models
topic Argentina
Climate variability
Soybean yield
Statistical models
dc.description.none.fl_txt_mv Climate variability is examined and discussed in this work, emphasizing its influence over the fluctuation of soybean yield in the Pampas (central-eastern Argentina). Monthly data of rainfall, maximum and minimum temperatures, thermal range and seasonal rainfall were analysed jointly with the soybean yield in the period 1973-2000. Low-frequency variability was significant only in the minimum temperature during November in almost all the stations. This situation is favourable to the crop since during this month, seed germination, a growth stage sensitive to low temperatures, takes place. In the crop's core production region, 72% of the series of soybean yield presented a positive trend. Except in years with extreme rainfall situations, interannual variability of the soybean yield is in phase with the seasonal rainfall interannual variability. During these years, losses in the soybean crop occurred, with yield negative anomalies greater than one standard deviation. Soybean yield showed spatial coherence at the local scale, except in the crop's core zone. The association between each climate variable and yield did not show a defined regional pattern. Summer high temperature and rainfall excesses during the period of maturity and harvest have the greatest negative impact on the crop, whilst higher minimum temperatures during the growing season favour high yields. The joint effect of climate variables over yield was studied with multivariate statistical models, assuming that the effect of other factors (such as soil, technology, pests) is contained in the residuals. The regression models represent the estimates of the yield satisfactorily (high percentage of explained variance) and can be used to assess expected anomalies of mean soybean yield for a particular year. However, the predictor variables of the yield depend on the region. Copyright © 2007 Royal Meteorological Society.
Fil:Penalba, O.C. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Bettolli, M.L. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
Fil:Vargas, W.M. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina.
description Climate variability is examined and discussed in this work, emphasizing its influence over the fluctuation of soybean yield in the Pampas (central-eastern Argentina). Monthly data of rainfall, maximum and minimum temperatures, thermal range and seasonal rainfall were analysed jointly with the soybean yield in the period 1973-2000. Low-frequency variability was significant only in the minimum temperature during November in almost all the stations. This situation is favourable to the crop since during this month, seed germination, a growth stage sensitive to low temperatures, takes place. In the crop's core production region, 72% of the series of soybean yield presented a positive trend. Except in years with extreme rainfall situations, interannual variability of the soybean yield is in phase with the seasonal rainfall interannual variability. During these years, losses in the soybean crop occurred, with yield negative anomalies greater than one standard deviation. Soybean yield showed spatial coherence at the local scale, except in the crop's core zone. The association between each climate variable and yield did not show a defined regional pattern. Summer high temperature and rainfall excesses during the period of maturity and harvest have the greatest negative impact on the crop, whilst higher minimum temperatures during the growing season favour high yields. The joint effect of climate variables over yield was studied with multivariate statistical models, assuming that the effect of other factors (such as soil, technology, pests) is contained in the residuals. The regression models represent the estimates of the yield satisfactorily (high percentage of explained variance) and can be used to assess expected anomalies of mean soybean yield for a particular year. However, the predictor variables of the yield depend on the region. Copyright © 2007 Royal Meteorological Society.
publishDate 2007
dc.date.none.fl_str_mv 2007
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/20.500.12110/paper_13504827_v14_n1_p3_Penalba
url http://hdl.handle.net/20.500.12110/paper_13504827_v14_n1_p3_Penalba
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/2.5/ar
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/2.5/ar
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv Meteorol. Appl. 2007;14(1):3-14
reponame:Biblioteca Digital (UBA-FCEN)
instname:Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
instacron:UBA-FCEN
reponame_str Biblioteca Digital (UBA-FCEN)
collection Biblioteca Digital (UBA-FCEN)
instname_str Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
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institution UBA-FCEN
repository.name.fl_str_mv Biblioteca Digital (UBA-FCEN) - Universidad Nacional de Buenos Aires. Facultad de Ciencias Exactas y Naturales
repository.mail.fl_str_mv ana@bl.fcen.uba.ar
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