Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis

Autores
Acciaresi, Horacio Abel; Chidichimo, Hugo Oscar; Fusé, Cecilia Beatriz
Año de publicación
1997
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Improvement of forage yield in oat (Avena sativa L.) depends on thorough understanding of the influences of genotype, environment and the genotype x environment interaction (G X E). The objetive of this study was to analyze G X E interaction in oat for biomass forage yield according two different models, joint linear regression analysis (JRA) and AMMI analysis. Twelve genotypes were grown in different environments during three years (1993-94-95) at the locations of La Dulce and La Plata, Buenos Aires Province, Argentina. The forage yield (dry matter yield Kg/ha) was determined at 60, 100 days after emergence and at ripening. Heterogeneity of regression in JRA was nonsignificant. Interaction sume of square accounted for by heterogeneity of regression were 12.08 % (three years mean). In contrast, the first principal component axis in AMMI was highly significant (P<.001). This first axis accounted for by 68.46 % of interaction SS (three years mean). The AMMI model was found tobe more effective than JRA analysis in accounting for GXE interaction under low environmental diversity The use of AMMI is recommended for the study of GXE effects in the oat breeding for forage yield.
Facultad de Ciencias Agrarias y Forestales
Materia
Ciencias Agrarias
Avena sativa
GXE interaction
Forage Yield
AMMI and JRA analyses
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/4.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/145287
Acceder
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oai_identifier_str oai:sedici.unlp.edu.ar:10915/145287
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysisAcciaresi, Horacio AbelChidichimo, Hugo OscarFusé, Cecilia BeatrizCiencias AgrariasAvena sativaGXE interactionForage YieldAMMI and JRA analysesImprovement of forage yield in oat (Avena sativa L.) depends on thorough understanding of the influences of genotype, environment and the genotype x environment interaction (G X E). The objetive of this study was to analyze G X E interaction in oat for biomass forage yield according two different models, joint linear regression analysis (JRA) and AMMI analysis. Twelve genotypes were grown in different environments during three years (1993-94-95) at the locations of La Dulce and La Plata, Buenos Aires Province, Argentina. The forage yield (dry matter yield Kg/ha) was determined at 60, 100 days after emergence and at ripening. Heterogeneity of regression in JRA was nonsignificant. Interaction sume of square accounted for by heterogeneity of regression were 12.08 % (three years mean). In contrast, the first principal component axis in AMMI was highly significant (P<.001). This first axis accounted for by 68.46 % of interaction SS (three years mean). The AMMI model was found tobe more effective than JRA analysis in accounting for GXE interaction under low environmental diversity The use of AMMI is recommended for the study of GXE effects in the oat breeding for forage yield.Facultad de Ciencias Agrarias y Forestales1997info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf55-62http://sedici.unlp.edu.ar/handle/10915/145287enginfo:eu-repo/semantics/altIdentifier/issn/0133-3720info:eu-repo/semantics/altIdentifier/issn/1788-9170info:eu-repo/semantics/altIdentifier/doi/10.1007/bf03543884info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:32:27Zoai:sedici.unlp.edu.ar:10915/145287Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:32:28.045SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
title Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
spellingShingle Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
Acciaresi, Horacio Abel
Ciencias Agrarias
Avena sativa
GXE interaction
Forage Yield
AMMI and JRA analyses
title_short Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
title_full Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
title_fullStr Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
title_full_unstemmed Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
title_sort Study of genotype x environment interaction for forage yield in oat (Avena sativa L.) with joint linear regression analysis and AMMI analysis
dc.creator.none.fl_str_mv Acciaresi, Horacio Abel
Chidichimo, Hugo Oscar
Fusé, Cecilia Beatriz
author Acciaresi, Horacio Abel
author_facet Acciaresi, Horacio Abel
Chidichimo, Hugo Oscar
Fusé, Cecilia Beatriz
author_role author
author2 Chidichimo, Hugo Oscar
Fusé, Cecilia Beatriz
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Agrarias
Avena sativa
GXE interaction
Forage Yield
AMMI and JRA analyses
topic Ciencias Agrarias
Avena sativa
GXE interaction
Forage Yield
AMMI and JRA analyses
dc.description.none.fl_txt_mv Improvement of forage yield in oat (Avena sativa L.) depends on thorough understanding of the influences of genotype, environment and the genotype x environment interaction (G X E). The objetive of this study was to analyze G X E interaction in oat for biomass forage yield according two different models, joint linear regression analysis (JRA) and AMMI analysis. Twelve genotypes were grown in different environments during three years (1993-94-95) at the locations of La Dulce and La Plata, Buenos Aires Province, Argentina. The forage yield (dry matter yield Kg/ha) was determined at 60, 100 days after emergence and at ripening. Heterogeneity of regression in JRA was nonsignificant. Interaction sume of square accounted for by heterogeneity of regression were 12.08 % (three years mean). In contrast, the first principal component axis in AMMI was highly significant (P<.001). This first axis accounted for by 68.46 % of interaction SS (three years mean). The AMMI model was found tobe more effective than JRA analysis in accounting for GXE interaction under low environmental diversity The use of AMMI is recommended for the study of GXE effects in the oat breeding for forage yield.
Facultad de Ciencias Agrarias y Forestales
description Improvement of forage yield in oat (Avena sativa L.) depends on thorough understanding of the influences of genotype, environment and the genotype x environment interaction (G X E). The objetive of this study was to analyze G X E interaction in oat for biomass forage yield according two different models, joint linear regression analysis (JRA) and AMMI analysis. Twelve genotypes were grown in different environments during three years (1993-94-95) at the locations of La Dulce and La Plata, Buenos Aires Province, Argentina. The forage yield (dry matter yield Kg/ha) was determined at 60, 100 days after emergence and at ripening. Heterogeneity of regression in JRA was nonsignificant. Interaction sume of square accounted for by heterogeneity of regression were 12.08 % (three years mean). In contrast, the first principal component axis in AMMI was highly significant (P<.001). This first axis accounted for by 68.46 % of interaction SS (three years mean). The AMMI model was found tobe more effective than JRA analysis in accounting for GXE interaction under low environmental diversity The use of AMMI is recommended for the study of GXE effects in the oat breeding for forage yield.
publishDate 1997
dc.date.none.fl_str_mv 1997
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Articulo
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://sedici.unlp.edu.ar/handle/10915/145287
url http://sedici.unlp.edu.ar/handle/10915/145287
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/0133-3720
info:eu-repo/semantics/altIdentifier/issn/1788-9170
info:eu-repo/semantics/altIdentifier/doi/10.1007/bf03543884
dc.rights.none.fl_str_mv 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)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/4.0/
Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.format.none.fl_str_mv application/pdf
55-62
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
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score 13.070432

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