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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
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Fecha : |
11/05/2018 |
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Actualizado : |
28/05/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
MONTEVERDE, E.; ROSAS, J.E.; BLANCO, P.H.; PÉREZ DE VIDA, F.; BONNECARRERE, V.; QUERO, G.; GUTIERREZ, L.; MCCOUCH, S. |
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Afiliación : |
ELIANA MONTEVERDE, Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, USA.; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, 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; LUCÍA GUTIERREZ, Department of Agronomy, University of Wisconsin, WI, USA.; SUSAN MCCOUCH, Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, USA. |
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Título : |
Multienvironment models increase prediction accuracy of complex traits in advanced breeding lines of rice (O. sativa). |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Crop Science, 2018, 58:1519-1530. |
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DOI : |
10.2135/cropsci2017.09.0564 |
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Idioma : |
Inglés |
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Notas : |
Article history: Accepted on May 09, 2018. Published online June 21, 2018. |
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Contenido : |
ABSTRACT: Genotype x environment interaction (G x E) is the differential response of genotypes in different environments and represents a major challenge for breeders. Genotype x year-interaction (G x Y) is a relevant component of G x E, and accounting for it is an important strategy for identifying lines with stable and superior performance across years. In this study, we compared the prediction accuracy of modeling G x Y using covariance structures that differ in their ability to
accommodate correlation among environments.
We present the use of these approaches in two different rice (Oryza sativa L.) breeding populations (indica and tropical japonica) for predicting grain yield, plant height, and three milling quality traits—milling yield, head rice percentage, and grain chalkiness—under different cross-validation (CV) scenarios. We also compared model performance in the context of global predictions (i.e., predictions across years). Most of the benefits of multienvironment models come from modeling genetic correlations between environments when predicting performance of lines that have been tested in some environments but not others (CV2). For predicting the performance of newly developed lines (CV1), modeling between environment correlations has no effect compared with considering environments independently. Response to selection of multienvironment models when modeling covariance structures that accommodate covariances between environments was always beneficial when predicting the performance of lines across years. We also show that, for some traits, high prediction accuracies can be obtained in untested years, which is important for resource allocation in small breeding programs. MenosABSTRACT: Genotype x environment interaction (G x E) is the differential response of genotypes in different environments and represents a major challenge for breeders. Genotype x year-interaction (G x Y) is a relevant component of G x E, and accounting for it is an important strategy for identifying lines with stable and superior performance across years. In this study, we compared the prediction accuracy of modeling G x Y using covariance structures that differ in their ability to
accommodate correlation among environments.
We present the use of these approaches in two different rice (Oryza sativa L.) breeding populations (indica and tropical japonica) for predicting grain yield, plant height, and three milling quality traits—milling yield, head rice percentage, and grain chalkiness—under different cross-validation (CV) scenarios. We also compared model performance in the context of global predictions (i.e., predictions across years). Most of the benefits of multienvironment models come from modeling genetic correlations between environments when predicting performance of lines that have been tested in some environments but not others (CV2). For predicting the performance of newly developed lines (CV1), modeling between environment correlations has no effect compared with considering environments independently. Response to selection of multienvironment models when modeling covariance structures that accommodate covariances between environments was always beneficial when pr... Presentar Todo |
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Palabras claves : |
GENOTYPE X ENVIRONMENT INTERACTION; INTERACCIONES GENOTIPO-AMBIENTE. |
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Thesagro : |
ARROZ; GENOTIPOS; RICE. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 02635naa a2200289 a 4500
001 1058574
005 2019-05-28
008 2018 bl uuuu u00u1 u #d
024 7 $a10.2135/cropsci2017.09.0564$2DOI
100 1 $aMONTEVERDE, E.
245 $aMultienvironment models increase prediction accuracy of complex traits in advanced breeding lines of rice (O. sativa).$h[electronic resource]
260 $c2018
500 $aArticle history: Accepted on May 09, 2018. Published online June 21, 2018.
520 $aABSTRACT: Genotype x environment interaction (G x E) is the differential response of genotypes in different environments and represents a major challenge for breeders. Genotype x year-interaction (G x Y) is a relevant component of G x E, and accounting for it is an important strategy for identifying lines with stable and superior performance across years. In this study, we compared the prediction accuracy of modeling G x Y using covariance structures that differ in their ability to accommodate correlation among environments. We present the use of these approaches in two different rice (Oryza sativa L.) breeding populations (indica and tropical japonica) for predicting grain yield, plant height, and three milling quality traits—milling yield, head rice percentage, and grain chalkiness—under different cross-validation (CV) scenarios. We also compared model performance in the context of global predictions (i.e., predictions across years). Most of the benefits of multienvironment models come from modeling genetic correlations between environments when predicting performance of lines that have been tested in some environments but not others (CV2). For predicting the performance of newly developed lines (CV1), modeling between environment correlations has no effect compared with considering environments independently. Response to selection of multienvironment models when modeling covariance structures that accommodate covariances between environments was always beneficial when predicting the performance of lines across years. We also show that, for some traits, high prediction accuracies can be obtained in untested years, which is important for resource allocation in small breeding programs.
650 $aARROZ
650 $aGENOTIPOS
650 $aRICE
653 $aGENOTYPE X ENVIRONMENT INTERACTION
653 $aINTERACCIONES GENOTIPO-AMBIENTE
700 1 $aROSAS, J.E.
700 1 $aBLANCO, P.H.
700 1 $aPÉREZ DE VIDA, F.
700 1 $aBONNECARRERE, V.
700 1 $aQUERO, G.
700 1 $aGUTIERREZ, L.
700 1 $aMCCOUCH, S.
773 $tCrop Science, 2018, 58:1519-1530.
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INIA Treinta y Tres (TT) |
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| Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
31/07/2017 |
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Actualizado : |
18/10/2017 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
JÁUREGUI, J. M.; MICHELINI, D. F.; AGNUSDEI, M. G.; BAUDRACCO, J.; SEVILLA, J. H.; CHILIBROSTE, P.; LATTANZI, F. |
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Afiliación : |
J. M. JÁUREGUI, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Facultad de Ciencias Agrarias, Universidad Nacional del Litoral, Esperanza (SF), Argentina; D. F. MICHELINI, Universidad de la República, Centro Universitario Región Litoral Norte, Salto, Uruguay; MÓNICA GRACIELA AGNUSDEI, Instituto Nacional de Tecnologia Agropecuaria Buenos Aires, Estación Experimental Agropecuaria Balcarce, Buenos Aires, Argentina; JAVIER BAUDRACCO, Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Buenos Aires, Argentina; Facultad de Ciencias Agrarias, Universidad Nacional del Litoral, Esperanza (SF), Argentina; J. H. SEVILLA, Instituto Nacional de Tecnología Agropecuaria, Concepción del Uruguay, Argentina; PABLO CHILIBROSTE, Universidad de la República, Estación Experimental Dr. Mario A. Cassinoni, Paysandú, Uruguay; FERNANDO A. LATTANZI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Persistence of tall fescue in a subtropical environment: tiller survival over summer in response to flowering control and nitrogen supply. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
Grass and Forage Science, 72(3):454-466, 2017. |
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DOI : |
10.1111/gfs.12252 |
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Idioma : |
Inglés |
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Notas : |
Article history: Version of record online: 5 September 2016 // Manuscript Revised: 25 July 2016 // Manuscript Received: 12 January 2016 |
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Contenido : |
ABSTRACT.
Enhancing pasture persistence is crucial to achieve more sustainable grass-based animal production systems. Although it is known that persistence of perennial ryegrass is based on a high turnover of tillers during late spring and summer, little is known about other forage species, particularly in subtropical climates. To address this question, this study evaluated survival of grazed tall fescue tillers growing in a subtropical climate. We hypothesized that hard tactical grazing during winter to remove reproductive stems (designated as 'flowering control'), and nitrogen fertilization in spring, would both improve tiller survival over summer, and thus enhance tiller density. This was assessed in two experiments. In both experiments, few tillers appeared during late spring and summer and so tiller density depended on the dynamics of vegetative tillers present in the sward in spring. In Experiment 2, flowering control and nitrogen fertilization both enhanced the survival of that critical tiller cohort, but the effects were not additive. Responses were similar but not statistically significant in Experiment 1, which had a warmer, drier summer and lower overall survival rates. Unlike grasses in temperate environments, persistence of tall fescue in this subtropical site appeared to follow a 'vegetative pathway'; i.e., new tillers were produced largely in autumn, from vegetative tillers that survived the summer.
© 2016 John Wiley & Sons Ltd. |
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Palabras claves : |
GRAZING INTENSITY; NITROGEN FERTILIZATION; PERSISTENCE; TALL FESCUE; TILLER TURNOVER. |
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Asunto categoría : |
-- |
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Marc : |
LEADER 02444naa a2200277 a 4500
001 1057426
005 2017-10-18
008 2017 bl uuuu u00u1 u #d
024 7 $a10.1111/gfs.12252$2DOI
100 1 $aJÁUREGUI, J. M.
245 $aPersistence of tall fescue in a subtropical environment$btiller survival over summer in response to flowering control and nitrogen supply.$h[electronic resource]
260 $c2017
500 $aArticle history: Version of record online: 5 September 2016 // Manuscript Revised: 25 July 2016 // Manuscript Received: 12 January 2016
520 $aABSTRACT. Enhancing pasture persistence is crucial to achieve more sustainable grass-based animal production systems. Although it is known that persistence of perennial ryegrass is based on a high turnover of tillers during late spring and summer, little is known about other forage species, particularly in subtropical climates. To address this question, this study evaluated survival of grazed tall fescue tillers growing in a subtropical climate. We hypothesized that hard tactical grazing during winter to remove reproductive stems (designated as 'flowering control'), and nitrogen fertilization in spring, would both improve tiller survival over summer, and thus enhance tiller density. This was assessed in two experiments. In both experiments, few tillers appeared during late spring and summer and so tiller density depended on the dynamics of vegetative tillers present in the sward in spring. In Experiment 2, flowering control and nitrogen fertilization both enhanced the survival of that critical tiller cohort, but the effects were not additive. Responses were similar but not statistically significant in Experiment 1, which had a warmer, drier summer and lower overall survival rates. Unlike grasses in temperate environments, persistence of tall fescue in this subtropical site appeared to follow a 'vegetative pathway'; i.e., new tillers were produced largely in autumn, from vegetative tillers that survived the summer. © 2016 John Wiley & Sons Ltd.
653 $aGRAZING INTENSITY
653 $aNITROGEN FERTILIZATION
653 $aPERSISTENCE
653 $aTALL FESCUE
653 $aTILLER TURNOVER
700 1 $aMICHELINI, D. F.
700 1 $aAGNUSDEI, M. G.
700 1 $aBAUDRACCO, J.
700 1 $aSEVILLA, J. H.
700 1 $aCHILIBROSTE, P.
700 1 $aLATTANZI, F.
773 $tGrass and Forage Science, 72(3):454-466, 2017.
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