Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina

Autores
Curti, Ramiro Nestor; de la Vega, A. J.; Andrade, A. J.; Bramardi, Sergio Jorge; Bertero, Hector Daniel
Año de publicación
2014
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The quinoa growing region of Northwest Argentina (NWA) shows a strong environmental variability, both seasonal and spatial. In consequence, the site-year combinations in which yield trials are established can complicate quinoa genotypic selection through strong genotype-by-environment interactions (G × E). The magnitude and nature of the genotype (G) and G × E interaction effects for grain yield, its physiological determinants and components, and days-to-flower exhibited by quinoa at NWA were examined in a multi-environment trial involving a reference set of 12 genotypes tested in six environments. The tested genotypes were selected based on their known contrasting relative performance to environments and different geographical origin. They represent three out of the four genotypic groups identified in previous studies. The G × E interaction to G component of variance was 3:1, 30:1 and 1.3:1 for grain yield, harvest index and grain number, respectively. Conversely, the G effect was large for biomass, grain weight and days-to-flower. Two-mode pattern analysis of the double-centred matrix for grain yield revealed four genotypic groups with different response pattern across environments. This clustering which separates genotypes from Highlands and Valleys showed a close correspondence with the genotypic groups previously proposed based on phenotypic and genetic characterization. On the other hand, a strong and repeatable negative association was observed between Highland and Valley sites, in terms of their G × E interaction effects. Phenological variation among genotypes in combination with environmental differences in the incidence of mildew or frost risk gave rise to significant crossover yield responses to site changes and determined specific adaptation to different ecological conditions. All yield components and determinants were involved in the genotype-specific yield responses. The genotypic variability observed for time to flowering determined the form of the G × E interactions observed for total above-ground biomass in Valley Environments, while in the Highland sites, harvest index made a significant contribution. On the other hand, grain number was the major component in grain yield determination, while grain weight showed a weak to strongly negative association with grain number across both types of environment. In this sense, the future breeding programs in NWA region should focus on these physiological attributes underlying grain yield variation among genotypes across groups of environments for faster genetic progress.
Fil: Curti, Ramiro Nestor. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Produccion Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; Argentina
Fil: de la Vega, A. J.. DuPont Pioneer; España
Fil: Andrade, A. J.. Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Salta-Jujuy; Argentina
Fil: Bramardi, Sergio Jorge. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales; Argentina. Universidad Nacional del Comahue. Facultad de Ciencis Agrarias; Argentina
Fil: Bertero, Hector Daniel. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Produccion Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Materia
CHENOPODIUM QUINOA WILLD
DOWNY MILDEW
GROUPS OF ENVIRONMENTS
G×E INTERACTION
QUINOA
YIELD COMPONENTS
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/7102

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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest ArgentinaCurti, Ramiro Nestorde la Vega, A. J.Andrade, A. J.Bramardi, Sergio JorgeBertero, Hector DanielCHENOPODIUM QUINOA WILLDDOWNY MILDEWGROUPS OF ENVIRONMENTSG×E INTERACTIONQUINOAYIELD COMPONENTShttps://purl.org/becyt/ford/4.1https://purl.org/becyt/ford/4The quinoa growing region of Northwest Argentina (NWA) shows a strong environmental variability, both seasonal and spatial. In consequence, the site-year combinations in which yield trials are established can complicate quinoa genotypic selection through strong genotype-by-environment interactions (G × E). The magnitude and nature of the genotype (G) and G × E interaction effects for grain yield, its physiological determinants and components, and days-to-flower exhibited by quinoa at NWA were examined in a multi-environment trial involving a reference set of 12 genotypes tested in six environments. The tested genotypes were selected based on their known contrasting relative performance to environments and different geographical origin. They represent three out of the four genotypic groups identified in previous studies. The G × E interaction to G component of variance was 3:1, 30:1 and 1.3:1 for grain yield, harvest index and grain number, respectively. Conversely, the G effect was large for biomass, grain weight and days-to-flower. Two-mode pattern analysis of the double-centred matrix for grain yield revealed four genotypic groups with different response pattern across environments. This clustering which separates genotypes from Highlands and Valleys showed a close correspondence with the genotypic groups previously proposed based on phenotypic and genetic characterization. On the other hand, a strong and repeatable negative association was observed between Highland and Valley sites, in terms of their G × E interaction effects. Phenological variation among genotypes in combination with environmental differences in the incidence of mildew or frost risk gave rise to significant crossover yield responses to site changes and determined specific adaptation to different ecological conditions. All yield components and determinants were involved in the genotype-specific yield responses. The genotypic variability observed for time to flowering determined the form of the G × E interactions observed for total above-ground biomass in Valley Environments, while in the Highland sites, harvest index made a significant contribution. On the other hand, grain number was the major component in grain yield determination, while grain weight showed a weak to strongly negative association with grain number across both types of environment. In this sense, the future breeding programs in NWA region should focus on these physiological attributes underlying grain yield variation among genotypes across groups of environments for faster genetic progress.Fil: Curti, Ramiro Nestor. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Produccion Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; ArgentinaFil: de la Vega, A. J.. DuPont Pioneer; EspañaFil: Andrade, A. J.. Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Salta-Jujuy; ArgentinaFil: Bramardi, Sergio Jorge. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales; Argentina. Universidad Nacional del Comahue. Facultad de Ciencis Agrarias; ArgentinaFil: Bertero, Hector Daniel. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Produccion Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaElsevier Science2014-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/7102Curti, Ramiro Nestor; de la Vega, A. J.; Andrade, A. J.; Bramardi, Sergio Jorge; Bertero, Hector Daniel; Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina; Elsevier Science; Field Crops Research; 166; 7-2014; 46-570378-4290enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0378429014001567info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fcr.2014.06.011info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:18:17Zoai:ri.conicet.gov.ar:11336/7102instacron: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:34982025-09-10 13:18:17.882CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
title Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
spellingShingle Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
Curti, Ramiro Nestor
CHENOPODIUM QUINOA WILLD
DOWNY MILDEW
GROUPS OF ENVIRONMENTS
G×E INTERACTION
QUINOA
YIELD COMPONENTS
title_short Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
title_full Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
title_fullStr Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
title_full_unstemmed Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
title_sort Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina
dc.creator.none.fl_str_mv Curti, Ramiro Nestor
de la Vega, A. J.
Andrade, A. J.
Bramardi, Sergio Jorge
Bertero, Hector Daniel
author Curti, Ramiro Nestor
author_facet Curti, Ramiro Nestor
de la Vega, A. J.
Andrade, A. J.
Bramardi, Sergio Jorge
Bertero, Hector Daniel
author_role author
author2 de la Vega, A. J.
Andrade, A. J.
Bramardi, Sergio Jorge
Bertero, Hector Daniel
author2_role author
author
author
author
dc.subject.none.fl_str_mv CHENOPODIUM QUINOA WILLD
DOWNY MILDEW
GROUPS OF ENVIRONMENTS
G×E INTERACTION
QUINOA
YIELD COMPONENTS
topic CHENOPODIUM QUINOA WILLD
DOWNY MILDEW
GROUPS OF ENVIRONMENTS
G×E INTERACTION
QUINOA
YIELD COMPONENTS
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.1
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv The quinoa growing region of Northwest Argentina (NWA) shows a strong environmental variability, both seasonal and spatial. In consequence, the site-year combinations in which yield trials are established can complicate quinoa genotypic selection through strong genotype-by-environment interactions (G × E). The magnitude and nature of the genotype (G) and G × E interaction effects for grain yield, its physiological determinants and components, and days-to-flower exhibited by quinoa at NWA were examined in a multi-environment trial involving a reference set of 12 genotypes tested in six environments. The tested genotypes were selected based on their known contrasting relative performance to environments and different geographical origin. They represent three out of the four genotypic groups identified in previous studies. The G × E interaction to G component of variance was 3:1, 30:1 and 1.3:1 for grain yield, harvest index and grain number, respectively. Conversely, the G effect was large for biomass, grain weight and days-to-flower. Two-mode pattern analysis of the double-centred matrix for grain yield revealed four genotypic groups with different response pattern across environments. This clustering which separates genotypes from Highlands and Valleys showed a close correspondence with the genotypic groups previously proposed based on phenotypic and genetic characterization. On the other hand, a strong and repeatable negative association was observed between Highland and Valley sites, in terms of their G × E interaction effects. Phenological variation among genotypes in combination with environmental differences in the incidence of mildew or frost risk gave rise to significant crossover yield responses to site changes and determined specific adaptation to different ecological conditions. All yield components and determinants were involved in the genotype-specific yield responses. The genotypic variability observed for time to flowering determined the form of the G × E interactions observed for total above-ground biomass in Valley Environments, while in the Highland sites, harvest index made a significant contribution. On the other hand, grain number was the major component in grain yield determination, while grain weight showed a weak to strongly negative association with grain number across both types of environment. In this sense, the future breeding programs in NWA region should focus on these physiological attributes underlying grain yield variation among genotypes across groups of environments for faster genetic progress.
Fil: Curti, Ramiro Nestor. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Produccion Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Salta; Argentina
Fil: de la Vega, A. J.. DuPont Pioneer; España
Fil: Andrade, A. J.. Instituto Nacional de Tecnologia Agropecuaria. Centro Regional Salta-Jujuy; Argentina
Fil: Bramardi, Sergio Jorge. Universidad Nacional de La Plata. Facultad de Ciencias Agrarias y Forestales; Argentina. Universidad Nacional del Comahue. Facultad de Ciencis Agrarias; Argentina
Fil: Bertero, Hector Daniel. Universidad de Buenos Aires. Facultad de Agronomia. Departamento de Producción Vegetal. Cátedra de Produccion Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
description The quinoa growing region of Northwest Argentina (NWA) shows a strong environmental variability, both seasonal and spatial. In consequence, the site-year combinations in which yield trials are established can complicate quinoa genotypic selection through strong genotype-by-environment interactions (G × E). The magnitude and nature of the genotype (G) and G × E interaction effects for grain yield, its physiological determinants and components, and days-to-flower exhibited by quinoa at NWA were examined in a multi-environment trial involving a reference set of 12 genotypes tested in six environments. The tested genotypes were selected based on their known contrasting relative performance to environments and different geographical origin. They represent three out of the four genotypic groups identified in previous studies. The G × E interaction to G component of variance was 3:1, 30:1 and 1.3:1 for grain yield, harvest index and grain number, respectively. Conversely, the G effect was large for biomass, grain weight and days-to-flower. Two-mode pattern analysis of the double-centred matrix for grain yield revealed four genotypic groups with different response pattern across environments. This clustering which separates genotypes from Highlands and Valleys showed a close correspondence with the genotypic groups previously proposed based on phenotypic and genetic characterization. On the other hand, a strong and repeatable negative association was observed between Highland and Valley sites, in terms of their G × E interaction effects. Phenological variation among genotypes in combination with environmental differences in the incidence of mildew or frost risk gave rise to significant crossover yield responses to site changes and determined specific adaptation to different ecological conditions. All yield components and determinants were involved in the genotype-specific yield responses. The genotypic variability observed for time to flowering determined the form of the G × E interactions observed for total above-ground biomass in Valley Environments, while in the Highland sites, harvest index made a significant contribution. On the other hand, grain number was the major component in grain yield determination, while grain weight showed a weak to strongly negative association with grain number across both types of environment. In this sense, the future breeding programs in NWA region should focus on these physiological attributes underlying grain yield variation among genotypes across groups of environments for faster genetic progress.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
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/11336/7102
Curti, Ramiro Nestor; de la Vega, A. J.; Andrade, A. J.; Bramardi, Sergio Jorge; Bertero, Hector Daniel; Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina; Elsevier Science; Field Crops Research; 166; 7-2014; 46-57
0378-4290
url http://hdl.handle.net/11336/7102
identifier_str_mv Curti, Ramiro Nestor; de la Vega, A. J.; Andrade, A. J.; Bramardi, Sergio Jorge; Bertero, Hector Daniel; Multi-environmental evaluation for grain yield and its physiological determinants of quinoa genotypes across Northwest Argentina; Elsevier Science; Field Crops Research; 166; 7-2014; 46-57
0378-4290
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0378429014001567
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fcr.2014.06.011
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
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
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