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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 : |
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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 : 125 | |
| 21. |  | GIORELLO, D.; DO CANTO, J.; PORCILE, V.; DE BARBIERI, I.; SOARES DE LIMA, J.M.; MONTOSSI, F.; ROSSI, C.; MARANGES, F.; REYNO, R. Paspalum notatum INIA Sepé: una gramínea nativa de alta productividad y persistencia. Revista INIA Uruguay, Setiembre 2021, no.66, p. 51-54. (Revista INIA; 66).| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Treinta y Tres. |
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| 22. | | OBERTI, H.; DALLA RIZZA, M.; REYNO, R.; MURCHIO, S.; ALTIER, N.; ABREO, E. Diversity of Claviceps paspali reveals unknown lineages and unique alkaloid genotypes. Mycologia, 3 March 2020, Volume 112, Issue 2, Pages 230-243. Doi: https://doi.org/10.1080/00275514.2019.1694827 Article history: Received 25 Apr 2019 // Accepted 15 Nov 2019 // Published online: 07 Jan 2020. CONTACT: E. Abreo, eabreo@inia.org.uy. FUNDING: This work was supported by the National Institute of Agricultural Research (INIA) of Uruguay...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Tacuarembó. |
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| 26. | | OBERTI, H.; ABREO, E.; REYNO, R.; FEIJOO, M.; MURCHIO, S.; DALLA RIZZA, M. New draft genome sequence of the ergot disease fungus claviceps paspali. Microbiology Resource Announcements, 16 July 2020, Volume 9, Issue 29, Article number e00498-20. OPEN ACCESS. Doi: https://doi.org/10.1128/MRA.00498-20 Article history: Received 28 May 2020; Accepted 20 June 2020; Published 16 July 2020.
Editor: Antonis Rokas - Vanderbilt University.
Corresponding author: Dalla-Rizza, M.; Instituto Nacional de Investigación Agropecuaria (INIA), Unidad de...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 28. | | DALLA RIZZA, M.; OBERTI, H.; MURCHIO, S.; DO CANTO, J.; ABREO, E.; ROSSI, C.; AYALA, W.; REYNO, R. Surgen nuevos caminos para aportar soluciones a problemas en el "pasto miel". Biotecnología. Revista INIA Uruguay, 2020, no.63, p.68-72. (Revista INIA; 63).| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Las Brujas. |
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| 29. | | DALLA RIZZA, M.; OBERTI, H.; MURCHIO, S.; DO CANTO, J.; ABREO, E.; ROSSI, C.; AYALA, W.; REYNO, R. Surjen nuevos caminos para aportar soluciones a problemas en el "pasto miel". Biotecnología. Revista INIA Uruguay, 2020, no.63, p.68-72. (Revista INIA; 63).| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Treinta y Tres. |
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| 35. | | REYNO, R.; DALLA RIZZA, M.; CASTILLO, A.; DO CANTO, J.; CONDON, F.; MENESES, L.; LATTANZI, F.; MONZA, J. Estrategias de mejoramiento de forrajeras en Uruguay: enfrentando nuevos desafíos. [Presentación oral]. In: Encuentro Latinoamericano y del Caribe de Biotecnología Agropecuaria; Simposio RedBio Argentina, 11., Montevideo 12-15 noviembre, 2019. Serie Técnica 253: Libro de Resúmenes.| Tipo: Presentaciones Orales |
| Biblioteca(s): INIA Tacuarembó. |
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| 36. | | MARANGES, M.; DO CANTO, J.; GUTIERREZ, F.; REYNO, R.; ROSSI, C.; LATTANZI, F.; DÍAZ, J.; STEWART, A. Festuca "RIZAR": una nueva opción rizomatosa de alta productividad, persistencia y rusticidad. Revista INIA Uruguay, 2019, no. 56, p. 40-42. (Revista INIA; 56)| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Tacuarembó. |
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| 40. | | MEDINA, S.; BERGÓS, F.; REYNO, R.; ROSSI, C.; ZARZA, R.; CARRASCO-LETELIER, L.; SILVEIRA, D.; CETRULO, F.; BECEIRO, J.; VERCELLINO, D. Restauración de servicios ecosistémicos en base a implantación de pasturas nativas en el área protegida de los montes del Queguay. Revista INIA Uruguay, 2019, no. 56, p. 43-47. (Revista INIA; 56).| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Tacuarembó. |
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| Registros recuperados : 125 | |
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