Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm

Autores
Kistner, María Belén; Nazar, Lázaro; Montenegro, Lucía Daniela; Cervigni, Gerardo Domingo Lucio; Galdeano, Ernestina; Iglesias, Juliana
Año de publicación
2022
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Maize (Zea mays L.), an important cereal for human and animal nutrition, is usually affected by multiple co-occurring pathogens that reduce production. Argentina is the fourth maize producer worldwide, with common rust (CR), northern corn leaf blight (NCLB), southern corn leaf blight (SCLB) and bacterial leaf streak (BLS) being important yield-limiting diseases in most maize producing areas. In this study, we aimed to identify genotypes with multiple disease resistance (MDR) for the introgression of broad-sense resistance into temperate maize breeding programs. We evaluated 87 genotypes from the Argentine public temperate inbred maize collection available from Instituto Nacional de Tecnología Agropecuaria (INTA) for their response to CR, NCLB, SCLB and BLS in up to five environments of Argentina. We compared four strategies to select sources of resistance to multiple diseases that could be used in breeding programs. Significant genotypic variation and high heritabilities were found for all disease resistances. The panel of inbred lines had numerous genotypes resistant to CR (80%) and BLS (78%), whereas genotypes resistant to NCLB (26%) or SCLB (30%) were less frequent. However, we were able to identify 12 genotypes as potential candidates for the introgression of broad-sense resistance. Our results indicate that the selection based on principal component analysis (PCA) was the most accurate methodology to detect MDR across all accessions. Maize studies based on MDR are scarce; to our knowledge, this is the first study conducted on Argentine germplasm. These findings will contribute to the strengthening of broad-sense resistance in temperate breeding programs as well as to the study of MDR detection.
EEA Pergamino
Fil: Kistner, María Belén. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; Argentina
Fil: Kistner, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Nazar, Lázaro. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina
Fil: Montenegro, Lucía Daniela. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina
Fil: Cervigni, Gerardo Domingo Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cervigni, Gerardo Domingo Lucio. Universidad Nacional de Rosario. Centro de Estudios Fotosintéticos y Bioquímicos; Argentina
Fil: Galdeano, Ernestina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Galdeano, Ernestina. Instituto de Botánica de Noroeste (IBONE); Argentina
Fil: Iglesias, Juliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; Argentina
Fil: Iglesias, Juliana. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Escuela de Agrarias, Naturales y Ambientales; Argentina
Fuente
Euphytica 218 (5) : 48. (May 2022)
Materia
Maíz
Germoplasma
Enfermedades de las Plantas
Genotipos
Resistencia a la Enfermedad
Roya
Tizón
Maize
Germplasm
Plant Diseases
Genotypes
Disease Resistance
Rusts
Blight
Best Linear Unbiased Predictor (BLUP)
Bacterial Leaf Streak (BLS)
Nivel de accesibilidad
acceso restringido
Condiciones de uso
Repositorio
INTA Digital (INTA)
Institución
Instituto Nacional de Tecnología Agropecuaria
OAI Identificador
oai:localhost:20.500.12123/11693
Acceder
id INTADig_593dd829f42a2845bf9b5e28019c0e40
oai_identifier_str oai:localhost:20.500.12123/11693
network_acronym_str INTADig
repository_id_str l
network_name_str INTA Digital (INTA)
spelling Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasmKistner, María BelénNazar, LázaroMontenegro, Lucía DanielaCervigni, Gerardo Domingo LucioGaldeano, ErnestinaIglesias, JulianaMaízGermoplasmaEnfermedades de las PlantasGenotiposResistencia a la EnfermedadRoyaTizónMaizeGermplasmPlant DiseasesGenotypesDisease ResistanceRustsBlightBest Linear Unbiased Predictor (BLUP)Bacterial Leaf Streak (BLS)Maize (Zea mays L.), an important cereal for human and animal nutrition, is usually affected by multiple co-occurring pathogens that reduce production. Argentina is the fourth maize producer worldwide, with common rust (CR), northern corn leaf blight (NCLB), southern corn leaf blight (SCLB) and bacterial leaf streak (BLS) being important yield-limiting diseases in most maize producing areas. In this study, we aimed to identify genotypes with multiple disease resistance (MDR) for the introgression of broad-sense resistance into temperate maize breeding programs. We evaluated 87 genotypes from the Argentine public temperate inbred maize collection available from Instituto Nacional de Tecnología Agropecuaria (INTA) for their response to CR, NCLB, SCLB and BLS in up to five environments of Argentina. We compared four strategies to select sources of resistance to multiple diseases that could be used in breeding programs. Significant genotypic variation and high heritabilities were found for all disease resistances. The panel of inbred lines had numerous genotypes resistant to CR (80%) and BLS (78%), whereas genotypes resistant to NCLB (26%) or SCLB (30%) were less frequent. However, we were able to identify 12 genotypes as potential candidates for the introgression of broad-sense resistance. Our results indicate that the selection based on principal component analysis (PCA) was the most accurate methodology to detect MDR across all accessions. Maize studies based on MDR are scarce; to our knowledge, this is the first study conducted on Argentine germplasm. These findings will contribute to the strengthening of broad-sense resistance in temperate breeding programs as well as to the study of MDR detection.EEA PergaminoFil: Kistner, María Belén. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; ArgentinaFil: Kistner, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Nazar, Lázaro. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; ArgentinaFil: Montenegro, Lucía Daniela. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; ArgentinaFil: Cervigni, Gerardo Domingo Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Cervigni, Gerardo Domingo Lucio. Universidad Nacional de Rosario. Centro de Estudios Fotosintéticos y Bioquímicos; ArgentinaFil: Galdeano, Ernestina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Galdeano, Ernestina. Instituto de Botánica de Noroeste (IBONE); ArgentinaFil: Iglesias, Juliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; ArgentinaFil: Iglesias, Juliana. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Escuela de Agrarias, Naturales y Ambientales; ArgentinaSpringer Nature2022-04-21T11:07:46Z2022-04-21T11:07:46Z2022-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttp://hdl.handle.net/20.500.12123/11693https://link.springer.com/article/10.1007/s10681-022-03000-40014-23361573-5060 (online)https://doi.org/10.1007/s10681-022-03000-4Euphytica 218 (5) : 48. (May 2022)reponame:INTA Digital (INTA)instname:Instituto Nacional de Tecnología Agropecuariaenginfo:eu-repo/semantics/restrictedAccess2025-10-16T09:30:40Zoai:localhost:20.500.12123/11693instacron:INTAInstitucionalhttp://repositorio.inta.gob.ar/Organismo científico-tecnológicoNo correspondehttp://repositorio.inta.gob.ar/oai/requesttripaldi.nicolas@inta.gob.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:l2025-10-16 09:30:42.301INTA Digital (INTA) - Instituto Nacional de Tecnología Agropecuariafalse
dc.title.none.fl_str_mv Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
title Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
spellingShingle Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
Kistner, María Belén
Maíz
Germoplasma
Enfermedades de las Plantas
Genotipos
Resistencia a la Enfermedad
Roya
Tizón
Maize
Germplasm
Plant Diseases
Genotypes
Disease Resistance
Rusts
Blight
Best Linear Unbiased Predictor (BLUP)
Bacterial Leaf Streak (BLS)
title_short Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
title_full Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
title_fullStr Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
title_full_unstemmed Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
title_sort Detecting sources of resistance to multiple diseases in Argentine maize (Zea mays L.) germplasm
dc.creator.none.fl_str_mv Kistner, María Belén
Nazar, Lázaro
Montenegro, Lucía Daniela
Cervigni, Gerardo Domingo Lucio
Galdeano, Ernestina
Iglesias, Juliana
author Kistner, María Belén
author_facet Kistner, María Belén
Nazar, Lázaro
Montenegro, Lucía Daniela
Cervigni, Gerardo Domingo Lucio
Galdeano, Ernestina
Iglesias, Juliana
author_role author
author2 Nazar, Lázaro
Montenegro, Lucía Daniela
Cervigni, Gerardo Domingo Lucio
Galdeano, Ernestina
Iglesias, Juliana
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Maíz
Germoplasma
Enfermedades de las Plantas
Genotipos
Resistencia a la Enfermedad
Roya
Tizón
Maize
Germplasm
Plant Diseases
Genotypes
Disease Resistance
Rusts
Blight
Best Linear Unbiased Predictor (BLUP)
Bacterial Leaf Streak (BLS)
topic Maíz
Germoplasma
Enfermedades de las Plantas
Genotipos
Resistencia a la Enfermedad
Roya
Tizón
Maize
Germplasm
Plant Diseases
Genotypes
Disease Resistance
Rusts
Blight
Best Linear Unbiased Predictor (BLUP)
Bacterial Leaf Streak (BLS)
dc.description.none.fl_txt_mv Maize (Zea mays L.), an important cereal for human and animal nutrition, is usually affected by multiple co-occurring pathogens that reduce production. Argentina is the fourth maize producer worldwide, with common rust (CR), northern corn leaf blight (NCLB), southern corn leaf blight (SCLB) and bacterial leaf streak (BLS) being important yield-limiting diseases in most maize producing areas. In this study, we aimed to identify genotypes with multiple disease resistance (MDR) for the introgression of broad-sense resistance into temperate maize breeding programs. We evaluated 87 genotypes from the Argentine public temperate inbred maize collection available from Instituto Nacional de Tecnología Agropecuaria (INTA) for their response to CR, NCLB, SCLB and BLS in up to five environments of Argentina. We compared four strategies to select sources of resistance to multiple diseases that could be used in breeding programs. Significant genotypic variation and high heritabilities were found for all disease resistances. The panel of inbred lines had numerous genotypes resistant to CR (80%) and BLS (78%), whereas genotypes resistant to NCLB (26%) or SCLB (30%) were less frequent. However, we were able to identify 12 genotypes as potential candidates for the introgression of broad-sense resistance. Our results indicate that the selection based on principal component analysis (PCA) was the most accurate methodology to detect MDR across all accessions. Maize studies based on MDR are scarce; to our knowledge, this is the first study conducted on Argentine germplasm. These findings will contribute to the strengthening of broad-sense resistance in temperate breeding programs as well as to the study of MDR detection.
EEA Pergamino
Fil: Kistner, María Belén. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; Argentina
Fil: Kistner, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Nazar, Lázaro. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina
Fil: Montenegro, Lucía Daniela. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina
Fil: Cervigni, Gerardo Domingo Lucio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Cervigni, Gerardo Domingo Lucio. Universidad Nacional de Rosario. Centro de Estudios Fotosintéticos y Bioquímicos; Argentina
Fil: Galdeano, Ernestina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Galdeano, Ernestina. Instituto de Botánica de Noroeste (IBONE); Argentina
Fil: Iglesias, Juliana. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Maíz; Argentina
Fil: Iglesias, Juliana. Universidad Nacional del Noroeste de la Provincia de Buenos Aires. Escuela de Agrarias, Naturales y Ambientales; Argentina
description Maize (Zea mays L.), an important cereal for human and animal nutrition, is usually affected by multiple co-occurring pathogens that reduce production. Argentina is the fourth maize producer worldwide, with common rust (CR), northern corn leaf blight (NCLB), southern corn leaf blight (SCLB) and bacterial leaf streak (BLS) being important yield-limiting diseases in most maize producing areas. In this study, we aimed to identify genotypes with multiple disease resistance (MDR) for the introgression of broad-sense resistance into temperate maize breeding programs. We evaluated 87 genotypes from the Argentine public temperate inbred maize collection available from Instituto Nacional de Tecnología Agropecuaria (INTA) for their response to CR, NCLB, SCLB and BLS in up to five environments of Argentina. We compared four strategies to select sources of resistance to multiple diseases that could be used in breeding programs. Significant genotypic variation and high heritabilities were found for all disease resistances. The panel of inbred lines had numerous genotypes resistant to CR (80%) and BLS (78%), whereas genotypes resistant to NCLB (26%) or SCLB (30%) were less frequent. However, we were able to identify 12 genotypes as potential candidates for the introgression of broad-sense resistance. Our results indicate that the selection based on principal component analysis (PCA) was the most accurate methodology to detect MDR across all accessions. Maize studies based on MDR are scarce; to our knowledge, this is the first study conducted on Argentine germplasm. These findings will contribute to the strengthening of broad-sense resistance in temperate breeding programs as well as to the study of MDR detection.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-21T11:07:46Z
2022-04-21T11:07:46Z
2022-04
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/20.500.12123/11693
https://link.springer.com/article/10.1007/s10681-022-03000-4
0014-2336
1573-5060 (online)
https://doi.org/10.1007/s10681-022-03000-4
url http://hdl.handle.net/20.500.12123/11693
https://link.springer.com/article/10.1007/s10681-022-03000-4
https://doi.org/10.1007/s10681-022-03000-4
identifier_str_mv 0014-2336
1573-5060 (online)
dc.language.none.fl_str_mv eng
language eng
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.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv Euphytica 218 (5) : 48. (May 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
_version_ 1846143545725943808
score 12.712165

Publicaciones similares