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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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Registro completo
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Biblioteca (s) : |
INIA Tacuarembó. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
29/03/2017 |
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Tipo de producción científica : |
Abstracts/Resúmenes |
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Autor : |
DE BARBIERI, I.; RISSO, D.; MONTOSSI, F.; SAN JULIÁN, R.; CUADRO, R.; ZARZA, A.; DIGHIERO, A.; MEDEROS, A. |
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Afiliación : |
LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DIEGO FERNANDO RISSO RIET, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FABIO MARCELO MONTOSSI PORCHILE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROBERTO SAN JULIAN SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; WASHINGTON ROBIN CUADRO LOPEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALEJANDRO DIGHIERO FASCIOLI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; AMERICA ESTHER MEDEROS SILVEIRA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Efecto del tipo de mejoramiento de campo, la relación ovino/bovino y el momento de esquila en la producción e carne ovina Corriedale y bovina de calidad sobre suelos de cristalino del centro en Uruguay. [Resumen]. |
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Fecha de publicación : |
2003 |
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Fuente / Imprenta : |
In: CONGRESO MUNDIAL CORRIEDALE, 12, 2003, SET 1-10: MONTEVIDEO, URUGUAY. Montevideo (Uruguay): INIA; SUL; Sociedad Criadores de Corriedale, 2003. |
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Páginas : |
p. 139 |
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Idioma : |
Español |
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Notas : |
NM 25. |
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Palabras claves : |
CARCASS QUALITY; IMPROVED SWARDS; LAMB; SHEARING; STEER. |
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Thesagro : |
CALIDAD DE LA CARNE; CANAL ANIMAL; CORDERO; ESQUILA; NOVILLO; OVINOS. |
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Asunto categoría : |
L01 Ganadería |
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Marc : |
LEADER 01083nam a2200337 a 4500
001 1019545
005 2017-03-29
008 2003 bl uuuu u01u1 u #d
100 1 $aDE BARBIERI, I.
245 $aEfecto del tipo de mejoramiento de campo, la relación ovino/bovino y el momento de esquila en la producción e carne ovina Corriedale y bovina de calidad sobre suelos de cristalino del centro en Uruguay. [Resumen].
260 $aIn: CONGRESO MUNDIAL CORRIEDALE, 12, 2003, SET 1-10: MONTEVIDEO, URUGUAY. Montevideo (Uruguay): INIA; SUL; Sociedad Criadores de Corriedale$c2003
300 $ap. 139
500 $aNM 25.
650 $aCALIDAD DE LA CARNE
650 $aCANAL ANIMAL
650 $aCORDERO
650 $aESQUILA
650 $aNOVILLO
650 $aOVINOS
653 $aCARCASS QUALITY
653 $aIMPROVED SWARDS
653 $aLAMB
653 $aSHEARING
653 $aSTEER
700 1 $aRISSO, D.
700 1 $aMONTOSSI, F.
700 1 $aSAN JULIÁN, R.
700 1 $aCUADRO, R.
700 1 $aZARZA, A.
700 1 $aDIGHIERO, A.
700 1 $aMEDEROS, A.
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INIA Tacuarembó (TBO) |
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