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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
04/01/2018 |
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Actualizado : |
30/01/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
GONZALEZ-BARRIOS, P.; CASTRO, M.; PÉREZ, O.; VILARÓ, D.; GUTIÉRREZ, G. |
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Afiliación : |
PABLO GONZALEZ-BARRIOS,; MARINA CASTRO DERENYI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OSVALDO MARTIN PÉREZ GONZÁLEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO VILARÓ; LUCÍA GUTIÉRREZ. |
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Título : |
Genotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Spanish Journal of Agricultural Research, v.15. n.4, e0705, 2017. |
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DOI : |
10.5424/sjar/2017154-11016 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 06 Jan 2017, Accepted: 01 Dec 2017. |
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Contenido : |
Abstract:
Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars. MenosAbstract:
Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and f... Presentar Todo |
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Palabras claves : |
GENOTYPE BY ENVIRONMENT INTERACTION; MULTI-ENVIRONMENT TRIALS; NETWORK EFFICIENCY; SUNFLOWER; YIELD STABILITY. |
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Thesagro : |
GIRASOL; INTERACCIÓN GENOTIPO AMBIENTE. |
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Asunto categoría : |
F01 Cultivo |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/8628/1/SJAR.2017.v.15.n.4.pdf
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Marc : |
LEADER 02709naa a2200277 a 4500
001 1057950
005 2020-01-30
008 2017 bl uuuu u00u1 u #d
024 7 $a10.5424/sjar/2017154-11016$2DOI
100 1 $aGONZALEZ-BARRIOS, P.
245 $aGenotype by environment interaction in sunflower (Helianthus annus L.) to optimize trial network efficiency.$h[electronic resource]
260 $c2017
500 $aArticle history: Received: 06 Jan 2017, Accepted: 01 Dec 2017.
520 $aAbstract: Modeling genotype by environment interaction (GEI) is one of the most challenging aspects of plant breeding programs. The use of efficient trial networks is an effective way to evaluate GEI to define selection strategies. Furthermore, the experimental design and the number of locations, replications, and years are crucial aspects of multi-environment trial (MET) network optimization. The objective of this study was to evaluate the efficiency and performance of a MET network of sunflower (Helianthus annuus L.). Specifically, we evaluated GEI in the network by delineating mega-environments, estimating genotypic stability and identifying relevant environmental covariates. Additionally, we optimized the network by comparing experimental design efficiencies. We used the National Evaluation Network of Sunflower Cultivars of Uruguay (NENSU) in a period of 20 years. MET plot yield and flowering time information was used to evaluate GEI. Additionally, meteorological information was studied for each sunflower physiological stage. An optimal network under these conditions should have three replications, two years of evaluation and at least three locations. The use of incomplete randomized block experimental design showed reasonable performance. Three mega-environments were defined, explained mainly by different management of sowing dates. Late sowings dates had the worst performance in grain yield and oil production, associated with higher temperatures before anthesis and fewer days allocated to grain filling. The optimization of MET networks through the analysis of the experimental design efficiency, the presence of GEI, and appropriate management strategies have a positive impact on the expression of yield potential and selection of superior cultivars.
650 $aGIRASOL
650 $aINTERACCIÓN GENOTIPO AMBIENTE
653 $aGENOTYPE BY ENVIRONMENT INTERACTION
653 $aMULTI-ENVIRONMENT TRIALS
653 $aNETWORK EFFICIENCY
653 $aSUNFLOWER
653 $aYIELD STABILITY
700 1 $aCASTRO, M.
700 1 $aPÉREZ, O.
700 1 $aVILARÓ, D.
700 1 $aGUTIÉRREZ, G.
773 $tSpanish Journal of Agricultural Research$gv.15. n.4, e0705, 2017.
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Registro original : |
INIA La Estanzuela (LE) |
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| Registros recuperados : 286 | |
| 161. |  | BERMÚDEZ, R.; AYALA, W.; SERRON, N. Control de gramilla en mejoramientos de Lotus Maku In: INIA TREINTA Y TRES. Jornada de divulgación de Producción Animal - Pasturas Treinta y Tres (Uruguay): INIA, 2009 p. 7-12 (INIA Serie Actividades de Difusión ; 591) Programa Nacional Pasturas y Forrajes: Ing. Agr., PhD. Walter Ayala, Director de Programa, Ing. Agr., MPhil. Raúl Bermúdez, Ing. Agr., MSc. Virginia Pravia, Lic., MSc. Felipe Lezama, Téc. en Sistemas Intensivos de Prod.Animal Ethel...| Tipo: Actividades de Difusión |
| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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| 162. | | BERMÚDEZ, R.; BARRIOS, E.; VELAZCO, J.; SERRÓN, N.; AYALA, W. Efecto de la carga animal en la performance de terneros pastoreando Trifolium vesiculosum In CONGRESO ARGENTINO DE PRODUCCIÓN ANIMAL, 33., 2010, Viedma, AR. Sistemas de producción. Revista Argentina de Producción Animal, v. 30, supl. 1, p. 155-156, 2010.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 167. | | BERMÚDEZ, R.; CARÁMBULA, M.; AYALA, W. Respuesta a la fertilización fosfatada de un mejoramiento de segundo año. [Resumen]. In: Anais do Reuniao do Grupo Técnico em Forrageiras do Cone Sul, Grupo Campos, 17, 1998, Lages, SC, Brasil: Epagri/UDESC, 1998, p. 93.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Treinta y Tres. |
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| 173. | | CARÁMBULA, M.; AYALA, W.; CARRIQUIRY, E. Algunos aspectos de manejo de mejoramientos extensivos Sección 1. Caracterización del sistema productivo pastoril en la región basáltica In: Berretta, E.J. (Ed.). Reunión del Grupo Técnico Regional del Cono Sur en mejoramiento y utilización de los recursos forrajeros del área tropical y subtropical, Grupos Campos, 14., 1994, Termas del Arapey, Salto, Uruguay. Anales. Montevideo (Uruguay): INIA, 1998. p. 45-48 (INIA Serie Técnica ; 94)| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Las Brujas. |
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| 180. | | CARDOZO, G.; AYALA, W.; BARRIOS, E. Management strategies to increase festulolium productivity and persistence ln: International Grassland Congress, 22, 2013, Orange New South Wales, Australia Michalk, D.L.; Millar, G.D.; Badgery, W.B.; Broadfoot, K.M.; eds. Proceedings of the 22 International Grassland Congress : revitalising grasslands to sustain our communities. Orange New South Wales, (Australia): SCIRO Publishing, 2013. Formato electrónico Material editado en formato electrónico| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Treinta y Tres. |
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| Registros recuperados : 286 | |
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