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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 : 11 | |
| 1. |  | DÍAZ, A.; LANFRANCO, B. Qué factores afectan el consumo de manzanas y peras en Uruguay?. Revista INIA Uruguay, 2019, no. 57, p. 61-66. (Revista INIA; 57) El articulo está basado en la tesis de la Maestría en Economía de la FCCEE (UdelaR) titulada ?Consumo de frutas: estimación y análisis de sus determinantes para lograr una ingesta acorde a la recomendación internacional ?, del Ec. Andrés...| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Las Brujas. |
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| 4. | | MIRABALLES, C.; BUSCIO, D.; SARAVIA, A.; DIAZ, A.; CASTRO-JANER, E. Comportamiento de vacas en ordeñe ante una alternativa de control no químico de la "Mosca de los cuernos" , Haematobia Irritans. In: Jornadas Uruguayas de Buiatría, 44., 2016, Paysandú, UY.; Gianneechini, E.; Elizondo, V. (Ed.).Paysandú: Centro Médico Veterinario de Paysandú/Sociedad Uruguaya de Buiatría, 2016. p.219-221.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 7. | | CASTRO JANER, E.; DÍAZ, A.; FONTES, F.; BARAIBAR, F.; SAPORITI, T.; OLHAGARAY, M. E. Molecular survey of pyrethroid and fipronil resistance in isolates of Rhipicephalus microplus in the north of Uruguay. Ticks and Tick-borne Diseases, 2021, Volume 12, Issue 5, Article number 101747. Doi: https://doi.org/10.1016/j.ttbdis.2021.101747 Article history: Received 23 July 2020; Received in revised form 29 March 2021; Accepted 6 April 2021; Available online 19 May 2021.
The authors are grateful to the funding of the Instituto Nacional de Investigación...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 10. | | Izaguirre de Artucio, P.; Díaz, A.; Millot, J.C.; Mazzella, C.; Rivas, M.; Grun, S.; Davies, P.; Baycé, D.; Pereira, J. Proyecto : estudio de los recursos geneticos de Bromus y paspalum ln: Seminario Nacional de Campo Natural, 2 : 1990 nov 15-16 : Tacuarembó Montevideo (Uruguay): Hemisferio Sur, 1990. p157-158 Participaron en el seminario : INIA, Sociedad Uruguaya de Pasturas Naturales, Facultad de Agronomía, Plan Agropecuario| Biblioteca(s): INIA La Estanzuela. |
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| 11. | | ALGORTA, I.; AZAMBUJA, T.; DÍAZ, A.; ERRO, L.; ESTABLE, L.; GONZÁLEZ, G.; HERWIG, G.; MARTÍNEZ, J.; MORIYAMA, S.; OLAIZOLA, V.; OSORIO, F.; PACHECO, P.; PÉREZ, C.; SANTÍN, V.; TRUJILLO, M.; VODANOVICH, V.; ZELMONOVICH, C. Grupo interinstitucional de promoción del consumo saludable de frutas y verduras. (Abs.1, Sección: Generales). IN: CONGRESO NACIONAL DE HORTI-FRUTICULTURA, 13. AÑO DE LA AGRICULTURA FAMILIAR DE LA FAO. "SOSTENIBILIDAD DE LA PRODUCCIÓN HORTIFRUTÍCOLA FAMILAR". 3-6 SETIEMBRE 2014, MONTEVIDEO (UY). Trabajos presentados. Montevideo (UY): INIA; SUHF, 2014. p. 17| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 11 | |
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