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| Registros recuperados : 11 | |
| 1. |  | LADO,B.; BATTENFIELD, S.; POLAND, J.; QUINCKE, M.; SILVA, P.; GUTIÉRREZ, L. Comparación de metodologías de predicción de cruzamientos para rendimiento en trigo. MV 14 - COMUNICACIONES LIBRES - MV. MEJORAMIENTO VEGETAL In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016 p. 287.| Biblioteca(s): INIA La Estanzuela. |
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| 2. | | LADO, B.; MATUS, I.; BELZILE, F.; POLAND, J.; QUINCKE, M.; CASTRO, M.; VON ZITZEWITZ, J. Genotipado por secuenciación en trigo (Triticum aestivum). In: JORNADAS DE LA SOCIEDAD DE BIOQUÍMICA Y BIOLOGÍA MOLECULAR , 8., SIMPOSIO BIOLOGÍA Y BIOTECNOLOGÍA VEGETAL, 11., 2013. Resumen. Montevideo: SBBM, SUB, 2013.| Biblioteca(s): INIA La Estanzuela. |
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| 3. | | WANG, X.; SILVA, P.; BELLO, N.M.; SINGH, D.; EVERS, B.; SINGH, R.P.; POLAND, J. Improved accuracy of high-throughput phenotyping from unmanned aerial systems by extracting traits directly from orthorectified images. Frontiers in Plant Science, 21 October 2020, Volume 11, Article number 587093. Open Access. Doi: https://doi.org/10.3389/fpls.2020.587093 Article history: Received: 27 July 2020/ Accepted: 30 September 2020/Published: 21 October 2020.| Biblioteca(s): INIA La Estanzuela. |
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| 4. | | SILVA, P.; EVERS, B.; KIEFFABER, A.; WANG, X.; BROWN, R.; GAO, L.; FRITZ, A.; CRAIN, J.; POLAND, J. Applied phenomics and genomics for improving barley yellow dwarf resistance in winter wheat. G3 Genes| Genomes| Genetics, (Bethesda, Md.), 2022;, jkac064, Open Access. DOI:https://doi.org/10.1093/g3journal/jkac064 Article history: Received: 22 December 2021/Accepted: 12 March 2022/Published: 30 March 2022.
The Author(s) (2022) . Published by Oxford University Press on behalf of the Genetics Society of America. This is an Open Access article...| Biblioteca(s): INIA La Estanzuela. |
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| 5. | | MORA, F.; CASTILLO, D.; LADO, B.; MATUS, I.; POLAND, J.; BELZILE, F.; VON ZITZEWITZ, J.; DEL POZO, A. Genome-wide association mapping of agronomic traits and carbon isotope discrimination in a worldwide germplasm collection of spring wheat using SNP markers. Molecular Breeding, 2015, v,35, no.2, 12 p.| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas. |
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| 6. | | LADO, B.; BATTENFIELD, S.; SILVA, P.; QUINCKE, M.; GUZMAN, C.; SINGH, R.P.; DREISIGACKER, S.; PEÑA, J.; FRITZ, A.; POLAND, J.; GUTIERREZ, L. Comparing strategies to select crosses using genomic prediction in two wheat breeding programs. In: International Wheat Genetics Symposium, 12, Tulln, Austria; April 23-28, 2017; BOKU: University of Natural Resources and Life Sciences, Vienna, Austria. p.88-90.| Biblioteca(s): INIA La Estanzuela. |
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| 7. | | LADO, B.; POLAND, J.; BELZILE, F.; DEL POZO, A.; MATUS, I.; RODRÍGUEZ, A.; INOSTROZA, L.; LOBOS, G.A.; CASTRO, M.; QUINCKE, M.; LANDECHEA, L.; VON ZITZEWITZ, J. Genotipado por secuenciación del genoma de 384 genotipos de T. aestivum para selección genómica. BAG. Journal of Basic and Applied Genetics ,Ciudad Autónoma de Buenos Aires, v.23, supl.1, p. 267, 2012.| Biblioteca(s): INIA La Estanzuela. |
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| 8. | | LADO, B.; MATUS, I.; RODRIGUEZ, A.; INOSTROZA, L.; POLAND, J.; BELZILE ,F.; DEL POZO, A.; QUINCKE, M.; CASTRO, M.; VON ZITZEWITZ, J. Increased genomic prediction accuracy in wheat breeding through spatial adjustment of field trial data. G3: Genes, Genomes, Genetics (Bethesda), v. 3, n,12, p. 2105-2114, 2013.OPEN ACCESS. Article history: Received 2013 Aug 26 // Accepted 2013 Sep 18.| Biblioteca(s): INIA La Estanzuela. |
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| 9. | | LADO, B.; BATTENFIELD, S. D.; GUZMÁN, C.; QUINCKE, M.; SINGH, R. P.; DREISIGACKER, S.; PEÑA, R. J.; FRITZ, AL.; SILVA, P.; POLAND, J.; GUTIÉRREZ, L. Strategies for selecting crosses using genomic prediction in two wheat breeding programs. The Plant Genome, 2017, v.10, Issue 2, 12p. OPEN ACCESS Article history: Received: Dec 14, 2016 // Accepted: Mar 18, 2017 // Published: July 6, 2017.
B. Lado and S. Battenfield contributed equally.Assigned to Associate Editor Nicholas Tinker.
This is an open access article distributed under...| Biblioteca(s): INIA Las Brujas. |
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| 10. | | GAO, L.; KOO, D.H.; JULIANA, P.; RIFE, T.; SINGH, D.; CRISTIANO LEMES DA SILVA; LUX, T.; DORN, K.M.; CLINESMITH, M.; SILVA, P.; WANG, X.; SPANNAGL, M.; MONAT, C.; FRIEBE, B.; STEUERNAGEL, B.; MUEHLBAUER, G.J.; WALKOWIAK, S.; POZNIAK, C.; SINGH, R.; STEIN, N.; MASCHER, M.; FRITZ, A.; POLAND, J. The Aegilops ventricosa 2N v S segment in bread wheat: cytology, genomics and breeding. Theoretical and Applied Genetics, volume 134, pag. 529?542, feb 2021. Open Access. Doi: https://doi.org/10.1007/s00122-020-03712-y Article history:Received: 22 June 2020 / Accepted: 17 October 2020/ Published:12 November 2020/ Issue Date:February 2021| Biblioteca(s): INIA La Estanzuela. |
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| 11. | | GAURAV, K.; ARORA, S.; SILVA, P.; SÁNCHEZ-MARTÍN, J.; HORSNELL,R.; GAO, L.; BRAR ,G.S.; WIDRIG,V.; JOHN RAUPP,W.; SINGH, N.; WU, S.; KALE, S.M.; CHINOY, C.; NICHOLSON, P.; QUIROZ-CHÁVEZ, J.; SIMMONDS, J.; HAYTA, S.; SMEDLEY, M. A; HARWOOD, W.; PEARCE, S.; GILBERT, D.; KANGARA, N.; GARDENER, C.; FORNER-MARTÍNEZ, M.; LIU, J.; YU, G.; BODEN, S.A.; PASCUCCI, A.; GHOSH, S.; HAFEEZ, A.N.; O'HARA, T.; WAITES, J.; CHEEMA, J.; STEUERNAGEL, B.; PATPOUR, M.; JUSTESEN, A.F.; LIU, S.; RUDD, J. C.; AVNI, R.; SHARON, A.R; STEINER, B.; KIRANA, R.P.; BUERSTMAYR, H.; MEHRABI, A.A.; NASYROVA, F.Y.; CHAYUT, N.; MATNY, O.; STEFFENSON, B. J.; SANDHU, N.; CHHUNEJA, P.; LAGUDAH, E.; ELKOT, A.F.; TYRRELL, S.; BIAN, X.; DAVEY, R.P.; SIMONSEN, M.; SCHAUSER, L.; TIWARI, V.K.; RANDY KUTCHER, H.; HUCL, P.; LI, A.; LIU, D.C.; MAO, L.; XU, S.; BROWN-GUEDIRA, G.; FARIS, J.; DVORAK, J.; LUO, M.CH.; KRASILEVA, K.; LUX, T.; ARTMEIER, S.; MAYER, K. F. X.; UAUY, C.; MASCHER, M.; BENTLEY, A.R.; KELLER, B.; POLAND, J.; WULFF, B. B. H. Population genomic analysis of Aegilops tauschii identifies targets for bread wheat improvement. Nature Biotechnology, Volume 40, Pages 422-431, March 2022. Open Access. doi: https://doi.org/10.1038/s41587-021-01058-4| Biblioteca(s): INIA La Estanzuela. |
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| Registros recuperados : 11 | |
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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 : |
20/02/2019 |
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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 : |
LADO, B.; BATTENFIELD, S. D.; GUZMÁN, C.; QUINCKE, M.; SINGH, R. P.; DREISIGACKER, S.; PEÑA, R. J.; FRITZ, AL.; SILVA, P.; POLAND, J.; GUTIÉRREZ, L. |
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Afiliación : |
BETTINA LADO, Statistics Dep., Facultad de Agronomía, Univ. de la República, Montevideo, Uruguay; SARAH D. BATTENFIELD, Kansas State University, Department of Plant Pathology, Manhattan, United States; CARLOS GUZMÁN, Centro Internacional de Mejoramiento de Maiz y Trigo, Global Wheat Program, Mexico City, Mexico; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; RAVI PRAKASH SINGH, Centro Internacional de Mejoramiento de Maiz y Trigo, Global Wheat Program, Mexico City, Mexico; SUSANNE DREISIGACKER, Centro Internacional de Mejoramiento de Maiz y Trigo, Applied Biotechnology Center, Mexico City, Mexico; ROBERTO JAVIER PEÑA, Centro Internacional de Mejoramiento de Maiz y Trigo, Global Wheat Program, Mexico City, Mexico; ALLAN K. FRITZ, Kansas State University, Manhattan, United States; MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JESSE A. POLAND, Kansas State University, Department of Plant Pathology and Department of Agronomy, Manhattan, United States; LUCÍA GUTIÉRREZ, Kansas State University, Department of Plant Pathology and Department of Agronomy, Manhattan, United States. |
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Título : |
Strategies for selecting crosses using genomic prediction in two wheat breeding programs. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
The Plant Genome, 2017, v.10, Issue 2, 12p. OPEN ACCESS |
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ISSN : |
1940-3372 |
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DOI : |
10.3835/plantgenome2016.12.0128 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: Dec 14, 2016 // Accepted: Mar 18, 2017 // Published: July 6, 2017.
B. Lado and S. Battenfield contributed equally.Assigned to Associate Editor Nicholas Tinker.
This is an open access article distributed under the CC BY-NC-ND license. |
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Contenido : |
ABSTRACT.
The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (VLD) or assuming linkage equilibrium (VLE). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat (Triticum aestivum L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses.
© Crop Science Society of America |
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Palabras claves : |
GENOMIC SELECTION; WHEAT; WHEAT BREEDING PROGRAMS. |
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Thesagro : |
TRIGO. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12466/1/tpg-10-2-plantgenome2016.12.0128.pdf
https://dl.sciencesocieties.org/publications/tpg/articles/10/2/plantgenome2016.12.0128
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Marc : |
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245 $aStrategies for selecting crosses using genomic prediction in two wheat breeding programs.$h[electronic resource]
260 $c2017
500 $aArticle history: Received: Dec 14, 2016 // Accepted: Mar 18, 2017 // Published: July 6, 2017. B. Lado and S. Battenfield contributed equally.Assigned to Associate Editor Nicholas Tinker. This is an open access article distributed under the CC BY-NC-ND license.
520 $aABSTRACT. The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (VLD) or assuming linkage equilibrium (VLE). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat (Triticum aestivum L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. © Crop Science Society of America
650 $aTRIGO
653 $aGENOMIC SELECTION
653 $aWHEAT
653 $aWHEAT BREEDING PROGRAMS
700 1 $aBATTENFIELD, S. D.
700 1 $aGUZMÁN, C.
700 1 $aQUINCKE, M.
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700 1 $aDREISIGACKER, S.
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773 $tThe Plant Genome, 2017$gv.10, Issue 2, 12p. OPEN ACCESS
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