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| Registros recuperados : 193 | |
| 103. |  | CASTRO, M.; PEREYRA, S.; GERMAN, S.; AZZIMONTI, G. II. Caracterizacion de la zafra 2017. In: Resultados experimentales de la evaluación nacional de cultivares de trigo ciclo largo: período 2017. La Estanzuela (UY): INIA; INASE, 2018. p. 3-4. Editado por el Equipo de Evaluación de Cultivares Impreso por Unidad de Comunicación y Transferencia de Tecnología INIA La Estanzuela. Convenio INASE-INIA.| Biblioteca(s): INIA La Estanzuela. |
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| 104. | | SANTIÑAQUE, F.; AMÉNDOLA, R.; SALDANHA, S.; CASTRO, M. Implantación, producción y persistencia de mejoramientos de pasturas con niveles contrastantes de aplicación de insumos : producción y persistencia. ln: REUNIÓN DEL GRUPO TÉCNICO REGIONAL DEL CONO SUR EN MEJORAMIENTO Y UTILIZACIÓN DE LOS RECURSOS FORRAJEROS DEL ÁREA TROPICAL Y SUB-TROPICAL. GRUPOS CAMPOS Y CHACO, 9., 1987, TACUAREMBÓ, URUGUAY.; SILVA, J. (Ed.). Memoria. Montevideo (Uruguay): CIAAB, 1988. p. 109-110| Biblioteca(s): INIA Tacuarembó. |
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| 106. | | PEREYRA, S.; GONZALEZ, N.; STANTON ,J.; CASTRO, M. Integrated management of fusarium head blight in Uruguay. In: International Symposium on Fusarium Head Blight, 5o., International Workshop on Wheat Blast, 2o.,Florianópolis, SC, Brazil,2016. p.96. P49- Session -Epidemiology and Management.| Biblioteca(s): INIA La Estanzuela. |
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| 113. | | PÉREZ, O.; VIEGA, L.; GUTIÉRREZ, L.; CASTRO, M. Post-anthesis water deficit in spring wheat: effects on yield components and relative water content. In: SEMINARIO INTERNACIONAL DE TRIGO, 2014, La Estanzuela, Colonia, UY. GERMÁN, S., et al. (Org.). 1914-2014, un siglo de mejoramiento de trigo en La Estanzuela: un valioso legado para el futuro: resúmenes; posters. La Estanzuela, Colonia, UY: INIA, 2014. p. 41.| Biblioteca(s): INIA La Estanzuela. |
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| 114. | | PÉREZ, O.; VIEGA, L.; GUTIERREZ, L.; CASTRO, M. Post-anthesis water deficit in spring wheat: effects on yield components and relative water content. [Poster]. In: German, S.; Quincke, M.; Vázquez, D.; Castro, M.; Pereyra, S.; Silva, P.; García, A. (Eds.). Seminario Internacional "1914-2014: Un siglo de mejoramiento de trigo en La Estanzuela". Montevideo (UY): INIA, 2018. P.130. (INIA Serie Técnica; 241).| Biblioteca(s): INIA La Estanzuela. |
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| 116. | | VERA, M.; VÁZQUEZ, D.; STEWART, S.; CASTRO, B.; CASTRO, M. Resultados experimentales de colza en Uruguay. In:Simposio Latinoamericano de Canola,1.,Centro Cultural Notre Dame Menino Jesus, Passo Fundo, RS, Brasil, 2014.| Biblioteca(s): INIA La Estanzuela. |
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| 119. | | CASTRO, M.; HOFFMAN, E.; PÉREZ, O.; VIEGA, L. Variabilidad en la respuesta al estrés hídrico de cultivares de trigo en Uruguay. In: German, S.; Quincke, M.; Vázquez, D.; Castro, M.; Pereyra, S.; Silva, P.; García, A. (Eds.). Seminario Internacional "1914-2014: Un siglo de mejoramiento de trigo en La Estanzuela". Montevideo (UY): INIA, 2018. p. 78-86. (INIA Serie Técnica; 241).| Biblioteca(s): INIA La Estanzuela. |
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| 120. | | CASTRO, M.; HOFFMAN, E.; PÉREZ, O.; VIEGA, L. Variabilidad en la respuesta al estrés hídrico de cultivares de trigo.[Presentación oral]. In: SEMINARIO INTERNACIONAL DE TRIGO, 2014, La Estanzuela, Colonia, UY. GERMÁN, S., et al. (Org.). 1914-2014, un siglo de mejoramiento de trigo en La Estanzuela: un valioso legado para el futuro. presentaciones; resúmenes. La Estanzuela, Colonia, UY: INIA, 2014.| Biblioteca(s): INIA La Estanzuela. |
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| Registros recuperados : 193 | |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
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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Circulación / Nivel : |
Internacional - -- |
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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 : |
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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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