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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
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Fecha : |
21/02/2014 |
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Actualizado : |
16/02/2018 |
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Tipo de producción científica : |
Capítulo en Libro Técnico-Científico |
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Autor : |
DE LOS CAMPOS, G.; DIGHIERO, A.; SAN JULIÁN, R.; MONTOSSI, F.; DE MATTOS, D.; CASTRO, R.; ROBAINA, R.; ABRAHAM, D. |
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Afiliación : |
GUSTAVO DE LOS CAMPOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALEJANDRO DIGHIERO FASCIOLI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ROBERTO SAN JULIAN SANCHEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FABIO MARCELO MONTOSSI PORCHILE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; DANIEL DE MATTOS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; R. CASTRO, INAC (Instituto Nacional de Carnes); RICARDO ROBAINA, INAC (Instituto Nacional de Carnes); D. ABRAHAM, INAC (Instituto Nacional de Carnes). |
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Título : |
Predicción de cortes valiosos de canales de corderos pesados a partir de variables medibles pos faena |
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Fecha de publicación : |
2002 |
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Fuente / Imprenta : |
ln: MONTOSSI, F. (Ed.) Investigación aplicada a la cadena agroindustrial cárnica: avances obtenidos: carne ovina de calidad (1998-2001). Montevideo (Uruguay): INIA, 2002. |
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Páginas : |
p. 99-108 |
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Serie : |
(INIA Serie Técnica ; 126) |
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ISBN : |
9974-38-148-7 |
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ISSN : |
1688-9266 |
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Idioma : |
Español |
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Thesagro : |
CANAL ANIMAL; CARNE; CORDERO; CORTE. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/8594/1/ST-126-p.99-108.pdf
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Marc : |
LEADER 00911naa a2200289 a 4500
001 1007155
005 2018-02-16
008 2002 bl uuuu u00u1 u #d
020 $a9974-38-148-7
022 $a1688-9266
100 1 $aDE LOS CAMPOS, G.
245 $aPredicción de cortes valiosos de canales de corderos pesados a partir de variables medibles pos faena
260 $c2002
300 $ap. 99-108
490 $a(INIA Serie Técnica ; 126)
650 $aCANAL ANIMAL
650 $aCARNE
650 $aCORDERO
650 $aCORTE
700 1 $aDIGHIERO, A.
700 1 $aSAN JULIÁN, R.
700 1 $aMONTOSSI, F.
700 1 $aDE MATTOS, D.
700 1 $aCASTRO, R.
700 1 $aROBAINA, R.
700 1 $aABRAHAM, D.
773 $tln: MONTOSSI, F. (Ed.) Investigación aplicada a la cadena agroindustrial cárnica: avances obtenidos: carne ovina de calidad (1998-2001). Montevideo (Uruguay): INIA, 2002.
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Registro original : |
INIA Las Brujas (LB) |
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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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