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| Registros recuperados : 53 | |
| 45. |  | OTERO, A.; GOÑI, C.; JIFON, J.L.; SYVERTSEN, J.P. High temperature effects on citrus orange leaf gas exchange, flowering, fruit quality and yield. (Conference paper). Acta Horticulturae, 2011, no.903, p.1069-1074. (Acta Horticulturae; 903). ISHS Acta Horticulturae 903: IX International Symposium on Integrating Canopy, Rootstock and Environmental Physiology in Orchard Systems. Editor: T.L. Robinson.
Publication date: 1 August 2011| Biblioteca(s): INIA Las Brujas. |
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| 48. | | OTERO, A.; GOÑI, C.; GRASSO, R.; MACHADO, D.; RIVAS, F. Water productivity associated to the planting system in young Nadorcott mandarin plants. [Productividad del agua asociada al sistema de plantación en plantas jóvenes de mandarina Nadorcott.]. [Produtividade hídrica em relação ao sistema de plantio em plantas jovens de tangerineira Nadorcott.]. Advances in Water in Agroscience. Irrigation and water management. Agrociencia Uruguay, 2023, Vol.27(NE1), e1188. https://doi.org/10.31285/AGRO.27.1188 -- OPEN ACCESS. Article history: Received 29 April 2023; Accepted 23 August 2023; Published 06 February 2024. -- Editor: Lucía Puppo, Universidad de la República, Montevideo, Uruguay. -- Correspondence: Álvaro Otero, aotero@inia.org.uy -- License: This...| Biblioteca(s): INIA Las Brujas. |
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| 50. | | OBERTI, H.; REYNO, R.; MURCHIO, S.; GOÑI, C.; DALLA RIZZA, M. Primer borrador del genoma de Paspalum malacophyllum, especie de relevancia como fuente de inmunidad al ergot en el pasto P. dilatatum. [resumen]. In: REDBIO México 2022, XI Congreso, "Biotecnología productiva y sostenible". Libro de resúmenes. 12-14 octubre 2022, Yucatán, México. p.20 Este proyecto fue financiado por INIA proyecto BT-19.| Biblioteca(s): INIA Las Brujas. |
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| 51. | | RIVAS, F.; BERNAL, R.; BERTALMIO, A.; BUENAHORA, J.; GOÑI, C.; LADO, J.; PEREZ, E.; OTERO, A.; MARA, H. La citricultura bajo estrés: un enfoque integral. Revista INIA, 2009, no. 17, p. 68-72.| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó; INIA Treinta y Tres. |
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| 53. | | BENNADJI, Z.; ALONSO, R.; CASTRO, M.; CIGANDA, V.; GOÑI, C.; PÉREZ DE VIDA, F.; VÁZQUEZ, D.; BERGER, A.; GASO, D.; CERETTA, S.; FASSIO, A.; SALDAIN, N.E.; OTERO, A. Mejoramiento genético más ecofisiología: generando espacios interdisciplinarios para la disminución de la vulnerabilidad al cambio climático Revista INIA Uruguay, 2011, no. 25 p. 43-48 (Revista INIA; 25)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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| Registros recuperados : 53 | |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha actual : |
29/05/2019 |
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Actualizado : |
11/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
-- - -- |
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Autor : |
MONTEVERDE, E.; GUTIERREZ, L.; BLANCO, P.H.; PÉREZ DE VIDA, F.; ROSAS, J.E.; BONNECARRERE, V.; QUERO, G.; MCCOUCH, SUSAN |
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Afiliación : |
ELIANA MONTEVERDE, Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University.; LUCÍA GUTIERREZ, Department of Agronomy, University of Wisconsin.; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GASTÓN QUERO CORRALLO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University. |
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Título : |
Integrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in subtropical areas. |
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Fecha de publicación : |
2019 |
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Fuente / Imprenta : |
G3: GENES, GENOMES, GENETICS May 1, 2019, v.9 (5), p. 1519-1531. OPEN ACCESS. |
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DOI : |
10.1534/g3.119.400064 |
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Idioma : |
Inglés |
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Notas : |
Article history: Manuscript received February 6, 2019 // Accepted for publication March 5, 2019// Published Early Online March 15, 2019.
Supplemental material available at Figshare: https://doi.org/10.25387/g3.7685636 |
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Contenido : |
Understanding the genetic and environmental basis of genotype · environment interaction (G·E) is of fundamental importance in plant breeding. If we consider G·E in the context of genotype · year interactions (G·Y), predicting which lines will have stable and superior performance across years is an important challenge for breeders. A better understanding of the factors that contribute to the overall grain yield and quality of rice (Oryza sativa L.) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. In this study, we used molecular marker data and environmental covariates (EC) simultaneously to predict rice yield, milling quality traits and plant height in untested environments (years), using both reaction norm models and partial least squares (PLS), in two rice breeding populations (indica and tropical japonica). We also sought to explain G·E by differential quantitative trait loci (QTL) expression in relation to EC. Our results showed that PLS models trained with both molecular markers and EC gave better prediction accuracies than reaction norm models when predicting future years. We also detected milling quality QTL that showed a differential expression conditional on humidity and solar radiation, providing insight for the main environmental factors affecting milling quality in subtropical and temperate rice growing areas. |
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Palabras claves : |
ENVIRONMENTAL COVARIATES; GENOMIC PREDICTIONS; GENOTYPE BY ENVIRONMENT INTERACTION; QTL BY ENVIRONMENT INTERACTION. |
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Thesagro : |
ARROZ; FITOMEJORAMIENTO; RICE. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12705/1/Blanco-Genes-Genomes-Genetics-2019.pdf
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Marc : |
LEADER 02649naa a2200313 a 4500
001 1059786
005 2019-10-11
008 2019 bl uuuu u00u1 u #d
024 7 $a10.1534/g3.119.400064$2DOI
100 1 $aMONTEVERDE, E.
245 $aIntegrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in subtropical areas.$h[electronic resource]
260 $c2019
500 $aArticle history: Manuscript received February 6, 2019 // Accepted for publication March 5, 2019// Published Early Online March 15, 2019. Supplemental material available at Figshare: https://doi.org/10.25387/g3.7685636
520 $aUnderstanding the genetic and environmental basis of genotype · environment interaction (G·E) is of fundamental importance in plant breeding. If we consider G·E in the context of genotype · year interactions (G·Y), predicting which lines will have stable and superior performance across years is an important challenge for breeders. A better understanding of the factors that contribute to the overall grain yield and quality of rice (Oryza sativa L.) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. In this study, we used molecular marker data and environmental covariates (EC) simultaneously to predict rice yield, milling quality traits and plant height in untested environments (years), using both reaction norm models and partial least squares (PLS), in two rice breeding populations (indica and tropical japonica). We also sought to explain G·E by differential quantitative trait loci (QTL) expression in relation to EC. Our results showed that PLS models trained with both molecular markers and EC gave better prediction accuracies than reaction norm models when predicting future years. We also detected milling quality QTL that showed a differential expression conditional on humidity and solar radiation, providing insight for the main environmental factors affecting milling quality in subtropical and temperate rice growing areas.
650 $aARROZ
650 $aFITOMEJORAMIENTO
650 $aRICE
653 $aENVIRONMENTAL COVARIATES
653 $aGENOMIC PREDICTIONS
653 $aGENOTYPE BY ENVIRONMENT INTERACTION
653 $aQTL BY ENVIRONMENT INTERACTION
700 1 $aGUTIERREZ, L.
700 1 $aBLANCO, P.H.
700 1 $aPÉREZ DE VIDA, F.
700 1 $aROSAS, J.E.
700 1 $aBONNECARRERE, V.
700 1 $aQUERO, G.
700 1 $aMCCOUCH, SUSAN
773 $tG3: GENES, GENOMES, GENETICS May 1, 2019$gv.9 (5), p. 1519-1531. OPEN ACCESS.
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