Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone

Autores
Di Mauro, Guido; Parra, Gonzalo; Santos, Diego Jose; Enrico, Juan Martin; Zuil, Sebastian; Murgio, Marcos; Zbinden, Facundo; Costanzi, Jerónimo; Arias, Norma Monica; Carrio, Alejandro Javier; Vissani, Cristian Angel; Fuentes, Francisco Horacio; Salvagiotti, Fernando
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Soybean genotypes are grouped in maturity groups (MG) based on the response to photoperiod, and a genotype belonging to a particular MG is recommended according to latitude and planting date. From an agronomic viewpoint, an “optimum maturity group” (MGopt) can be defined as the one that maximizes soybean yield in a particular environment, and not necessarily corresponds with the recommended MG based on thermo-photoperiod response. Our objectives were to (i) delineate spatial pattern of MGopt across contrasting environmental conditions for full-season soybean using geostatistics, and (ii) test whether the weather scenario change the spatial distribution of the MGopt. We hypothesized that, for the same region, the MGopt in dry years (i.e. La Niña phase) is larger than in humid years (i.e. El Niño phase). We analyzed multi-environment trials of full-season soybean (1675 site-years) using recent soybean genotypes and management practices across the Southern Cone of America. The MGopt ranged between 3.8 and 7.8 across regions and ENSO phases. The geostatistics approach indicated a spatial MGopt auto-correlation. The map for each ENSO phase indicates zones with contrasting MGopt and independently of ENSO phase, MGopt increased as latitude decreased. Also, for a particular latitude range, MGopt also varied according to longitude, suggesting that its variation can be associated with rainfall pattern and soil types in the region. Our approach delineated the distribution of MGopt for the American Southern Cone and highlighted that the inclusion of ENSO phase is important for guiding farmers MG options at regional scale.
EEA Paraná
Fil: Di Mauro, Guido. Grupo Don Mario (Buenos Aires); Argentina
Fil: Parra, Gonzalo. Grupo Don Mario (Buenos Aires); Argentina
Fil: Santos, Diego Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina
Fil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Grupo Manejo de Cultivos, Suelos y Agua. Argentina
Fil: Zuil, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina
Fil: Murgio, Marcos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Zbinden, Facundo. Grupo Don Mario (Buenos Aires); Argentina
Fil: Costanzi, Jerónimo. Grupo Don Mario (Buenos Aires); Argentina
Fil: Arias, Norma Monica. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; Argentina
Fil: Carrio, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Vissani, Cristian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Fuentes, Francisco Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fuente
Field Crops Research 287 : 108676 (October 2022)
Materia
Soja
Tiempo Meteorológico
Madurez
Manejo del Cultivo
América del Sur
Soybeans
Weather
Maturity
Crop Management
South America
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/12851
Acceder
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oai_identifier_str oai:localhost:20.500.12123/12851
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Defining soybean maturity group options for contrasting weather scenarios in the American Southern ConeDi Mauro, GuidoParra, GonzaloSantos, Diego JoseEnrico, Juan MartinZuil, SebastianMurgio, MarcosZbinden, FacundoCostanzi, JerónimoArias, Norma MonicaCarrio, Alejandro JavierVissani, Cristian AngelFuentes, Francisco HoracioSalvagiotti, FernandoSojaTiempo MeteorológicoMadurezManejo del CultivoAmérica del SurSoybeansWeatherMaturityCrop ManagementSouth AmericaSoybean genotypes are grouped in maturity groups (MG) based on the response to photoperiod, and a genotype belonging to a particular MG is recommended according to latitude and planting date. From an agronomic viewpoint, an “optimum maturity group” (MGopt) can be defined as the one that maximizes soybean yield in a particular environment, and not necessarily corresponds with the recommended MG based on thermo-photoperiod response. Our objectives were to (i) delineate spatial pattern of MGopt across contrasting environmental conditions for full-season soybean using geostatistics, and (ii) test whether the weather scenario change the spatial distribution of the MGopt. We hypothesized that, for the same region, the MGopt in dry years (i.e. La Niña phase) is larger than in humid years (i.e. El Niño phase). We analyzed multi-environment trials of full-season soybean (1675 site-years) using recent soybean genotypes and management practices across the Southern Cone of America. The MGopt ranged between 3.8 and 7.8 across regions and ENSO phases. The geostatistics approach indicated a spatial MGopt auto-correlation. The map for each ENSO phase indicates zones with contrasting MGopt and independently of ENSO phase, MGopt increased as latitude decreased. Also, for a particular latitude range, MGopt also varied according to longitude, suggesting that its variation can be associated with rainfall pattern and soil types in the region. Our approach delineated the distribution of MGopt for the American Southern Cone and highlighted that the inclusion of ENSO phase is important for guiding farmers MG options at regional scale.EEA ParanáFil: Di Mauro, Guido. Grupo Don Mario (Buenos Aires); ArgentinaFil: Parra, Gonzalo. Grupo Don Mario (Buenos Aires); ArgentinaFil: Santos, Diego Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; ArgentinaFil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Grupo Manejo de Cultivos, Suelos y Agua. ArgentinaFil: Zuil, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; ArgentinaFil: Murgio, Marcos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; ArgentinaFil: Zbinden, Facundo. Grupo Don Mario (Buenos Aires); ArgentinaFil: Costanzi, Jerónimo. Grupo Don Mario (Buenos Aires); ArgentinaFil: Arias, Norma Monica. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; ArgentinaFil: Carrio, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Vissani, Cristian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Fuentes, Francisco Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; ArgentinaFil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; ArgentinaFil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier2022-09-12T12:22:14Z2022-09-12T12:22:14Z2022-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/12851https://www.sciencedirect.com/science/article/abs/pii/S03784290220024770378-4290https://doi.org/10.1016/j.fcr.2022.108676Field Crops Research 287 : 108676 (October 2022)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repograntAgreement/INTA/2019-RIST-E6-I226-001/2019-RIST-E6-I226-001/AR./Red de evaluación de cultivaresSouth America .......... (continent) (World)1000002info:eu-repo/semantics/restrictedAccess2025-09-29T13:45:42Zoai:localhost:20.500.12123/12851instacron: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 13:45:43.157INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
title Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
spellingShingle Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
Di Mauro, Guido
Soja
Tiempo Meteorológico
Madurez
Manejo del Cultivo
América del Sur
Soybeans
Weather
Maturity
Crop Management
South America
title_short Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
title_full Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
title_fullStr Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
title_full_unstemmed Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
title_sort Defining soybean maturity group options for contrasting weather scenarios in the American Southern Cone
dc.creator.none.fl_str_mv Di Mauro, Guido
Parra, Gonzalo
Santos, Diego Jose
Enrico, Juan Martin
Zuil, Sebastian
Murgio, Marcos
Zbinden, Facundo
Costanzi, Jerónimo
Arias, Norma Monica
Carrio, Alejandro Javier
Vissani, Cristian Angel
Fuentes, Francisco Horacio
Salvagiotti, Fernando
author Di Mauro, Guido
author_facet Di Mauro, Guido
Parra, Gonzalo
Santos, Diego Jose
Enrico, Juan Martin
Zuil, Sebastian
Murgio, Marcos
Zbinden, Facundo
Costanzi, Jerónimo
Arias, Norma Monica
Carrio, Alejandro Javier
Vissani, Cristian Angel
Fuentes, Francisco Horacio
Salvagiotti, Fernando
author_role author
author2 Parra, Gonzalo
Santos, Diego Jose
Enrico, Juan Martin
Zuil, Sebastian
Murgio, Marcos
Zbinden, Facundo
Costanzi, Jerónimo
Arias, Norma Monica
Carrio, Alejandro Javier
Vissani, Cristian Angel
Fuentes, Francisco Horacio
Salvagiotti, Fernando
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Soja
Tiempo Meteorológico
Madurez
Manejo del Cultivo
América del Sur
Soybeans
Weather
Maturity
Crop Management
South America
topic Soja
Tiempo Meteorológico
Madurez
Manejo del Cultivo
América del Sur
Soybeans
Weather
Maturity
Crop Management
South America
dc.description.none.fl_txt_mv Soybean genotypes are grouped in maturity groups (MG) based on the response to photoperiod, and a genotype belonging to a particular MG is recommended according to latitude and planting date. From an agronomic viewpoint, an “optimum maturity group” (MGopt) can be defined as the one that maximizes soybean yield in a particular environment, and not necessarily corresponds with the recommended MG based on thermo-photoperiod response. Our objectives were to (i) delineate spatial pattern of MGopt across contrasting environmental conditions for full-season soybean using geostatistics, and (ii) test whether the weather scenario change the spatial distribution of the MGopt. We hypothesized that, for the same region, the MGopt in dry years (i.e. La Niña phase) is larger than in humid years (i.e. El Niño phase). We analyzed multi-environment trials of full-season soybean (1675 site-years) using recent soybean genotypes and management practices across the Southern Cone of America. The MGopt ranged between 3.8 and 7.8 across regions and ENSO phases. The geostatistics approach indicated a spatial MGopt auto-correlation. The map for each ENSO phase indicates zones with contrasting MGopt and independently of ENSO phase, MGopt increased as latitude decreased. Also, for a particular latitude range, MGopt also varied according to longitude, suggesting that its variation can be associated with rainfall pattern and soil types in the region. Our approach delineated the distribution of MGopt for the American Southern Cone and highlighted that the inclusion of ENSO phase is important for guiding farmers MG options at regional scale.
EEA Paraná
Fil: Di Mauro, Guido. Grupo Don Mario (Buenos Aires); Argentina
Fil: Parra, Gonzalo. Grupo Don Mario (Buenos Aires); Argentina
Fil: Santos, Diego Jose. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Paraná; Argentina
Fil: Enrico, Juan Martin. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros. Grupo Manejo de Cultivos, Suelos y Agua. Argentina
Fil: Zuil, Sebastian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Rafaela; Argentina
Fil: Murgio, Marcos. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi; Argentina
Fil: Zbinden, Facundo. Grupo Don Mario (Buenos Aires); Argentina
Fil: Costanzi, Jerónimo. Grupo Don Mario (Buenos Aires); Argentina
Fil: Arias, Norma Monica. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Concepción del Uruguay; Argentina
Fil: Carrio, Alejandro. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Vissani, Cristian. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Fuentes, Francisco Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Marcos Juárez; Argentina
Fil: Salvagiotti, Fernando. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Oliveros; Argentina
Fil: Salvagiotti, Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description Soybean genotypes are grouped in maturity groups (MG) based on the response to photoperiod, and a genotype belonging to a particular MG is recommended according to latitude and planting date. From an agronomic viewpoint, an “optimum maturity group” (MGopt) can be defined as the one that maximizes soybean yield in a particular environment, and not necessarily corresponds with the recommended MG based on thermo-photoperiod response. Our objectives were to (i) delineate spatial pattern of MGopt across contrasting environmental conditions for full-season soybean using geostatistics, and (ii) test whether the weather scenario change the spatial distribution of the MGopt. We hypothesized that, for the same region, the MGopt in dry years (i.e. La Niña phase) is larger than in humid years (i.e. El Niño phase). We analyzed multi-environment trials of full-season soybean (1675 site-years) using recent soybean genotypes and management practices across the Southern Cone of America. The MGopt ranged between 3.8 and 7.8 across regions and ENSO phases. The geostatistics approach indicated a spatial MGopt auto-correlation. The map for each ENSO phase indicates zones with contrasting MGopt and independently of ENSO phase, MGopt increased as latitude decreased. Also, for a particular latitude range, MGopt also varied according to longitude, suggesting that its variation can be associated with rainfall pattern and soil types in the region. Our approach delineated the distribution of MGopt for the American Southern Cone and highlighted that the inclusion of ENSO phase is important for guiding farmers MG options at regional scale.
publishDate 2022
dc.date.none.fl_str_mv 2022-09-12T12:22:14Z
2022-09-12T12:22:14Z
2022-10
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/20.500.12123/12851
https://www.sciencedirect.com/science/article/abs/pii/S0378429022002477
0378-4290
https://doi.org/10.1016/j.fcr.2022.108676
url http://hdl.handle.net/20.500.12123/12851
https://www.sciencedirect.com/science/article/abs/pii/S0378429022002477
https://doi.org/10.1016/j.fcr.2022.108676
identifier_str_mv 0378-4290
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repograntAgreement/INTA/2019-RIST-E6-I226-001/2019-RIST-E6-I226-001/AR./Red de evaluación de cultivares
dc.rights.none.fl_str_mv info:eu-repo/semantics/restrictedAccess
eu_rights_str_mv restrictedAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv South America .......... (continent) (World)
1000002
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv Field Crops Research 287 : 108676 (October 2022)
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 12.559606

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