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| 121. |  | 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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| 124. | | SAINT PIERRE, C.; GHANEM, M.E.; BEN M'BAREK, S.; AZZIMONTI, G.; PEREYRA, S.; MARZA, F.; YAHYAOUI, A.; SINGH, P.; BAUM, M.; BRAUN, H. Global network for precision wheat phenotypin.[Resumen]. In: Latin-American Conference on Plant Phenotyping and Phenomics for Plant Breeding, 2, 2017, São Carlos, SP. Proceedings... São Carlos: Embrapa Instrumentação, 2017. p. 77.| Biblioteca(s): INIA La Estanzuela. |
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| 125. | | AZZIMONTI, G.; GARCIA, R.; GONZALEZ, N.; DOMENIGUINI, V.; CAROLINA SAINT-PIERRE, C.; SINGH, P.K.; QUINCKE, M.; PEREYRA, S.; GERMAN, S. Field-based phenotyping for wheat diseases within a new multiple diseases platform in Uruguay: promoting germplasm sharing to increase resistance diversity. P 309-Topic: Future of Wheat Improvement in Different Parts of the World. In: Buerstmayr, H.; Lang-Mladek, C.; Steiner, B.; Michel, S.; Buerstmayr, M.; Lemmens, M.; Vollmann, J.; Grausgruber, H. (Eds.). Proceedings of the 13th International Wheat Genetics Symposium. Tulln, Austria; April 23-28, 2017. p.485.| Biblioteca(s): INIA La Estanzuela. |
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| 126. | | ESTEVES, P.; MASTROPIERRO, M.; CASTILLO, A.; HERNANDEZ, L.; RODRIGUEZ, M.; DE LEON, W.; PEREIRA, F.; QUINCKE, M. Herramientas biotecnológicas para el mejoramiento genético de cultivos. Revista INIA Uruguay, 2017, no.48, p. 62-66. (Revista INIA; 48)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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| 127. | | RAFFO, M.A.; PRITSCH, C.; AZZIMONTI, G.; PEREYRA, S.; QUINCKE, M.; BONNECARRERE, V.; SILVA, P.; CASTRO, A.; LADO, B.; BARAIBAR, S.; PEREYRA, S.; GERMAN, S. Introducción de Fhb1 en germoplasma elite de trigo para incrementar la resistencia a fusariosis de espiga en Uruguay. [p24]. Bloque 2: Mejoramiento por resistencia a enfermedades. In: Sociedad Uruguaya de Fitopatología Jornada Uruguaya de Fitopatología, 4., Jornada Uruguaya de Protección Vegetal, 2., 1° setiembre, 2017, Montevideo, Uruguay. Libro de resúmenes. Montevideo (UY): Sociedad Uruguay de Fitopatología (SUFIT), 2017. p. 44. Financiamiento: Agencia Nacional de Investigación e Innovación (POS_NAC_2016_1_129877).| Biblioteca(s): INIA Las Brujas. |
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| 129. | | ELICHALT, M.; RUSSO, M.; VÁZQUEZ, D.; SUBURÚ, G.; TIHISTA, H.; GODIÑO, M. Lípidos, sodio y fibra dietética en harina de trigo y pan artesanal en Uruguay: aporte nutricional según recomendaciones para distintos grupos de población. [Lipids, sodium and dietary fiber in wheat flour and artisan bread in Uruguay: nutritional intake according to the recommendations for different population groups.] Revista Chilena de Nutrición, 44(1), p. 71-78., 2017. Este trabajo fue recibido el 25 de Mayo de 2016 y aceptado para ser publicado el 16 de Diciembre de 2016.| Biblioteca(s): INIA Las Brujas. |
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| 132. | | BUERSTMAYR, H.; LANG-MLADEK, C.; STEINER, B.; MICHEL, S.; BUERSTMAYR, M.; LEMMENS, M.; VOLLMANN, J.; GRAUSGRUBER, H. (Ed.). Proceedings of the 13th International Wheat Genetics Symposium. Tulln, Austria; April 23-28, 2017. BOKU: University of Natural Resources and Life Sciences, Vienna, Austria. 512 p. International Organizing Committee: Yasunari Ogihara (Japan-chair), Ahmed Amri (ICARDA), Cristobal Uauy (UK), Elena Salina (Russia), Hélène Lucas (Wheat Initiative), Mark E. Sorrells (USA), Parveen Chhuneja (India), Peter Langridge...| Biblioteca(s): INIA La Estanzuela. |
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| 134. | | 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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| 140. | | BARAIBAR, S.; SILVA, P.; PRITSCH, C.; GERMAN, S. Transfiriendo combinaciones de genes de resistencia a roya de tallo a background de trigo adaptado al Uruguay. [p18*]. Bloque 2: Mejoramiento por resistencia a enfermedades. In: Sociedad Uruguaya de Fitopatología Jornada Uruguaya de Fitopatología, 4., Jornada Uruguaya de Protección Vegetal, 2., 1° setiembre, 2017, Montevideo, Uruguay. Libro de resúmenes. Montevideo (UY): Sociedad Uruguay de Fitopatología (SUFIT), 2017. p. 38. [p18*]: *Trabajo ya presentado en el XVI Congreso Latinoamericano de Genética, Uruguay.
Financiamiento: Proyecto INNOVAGRO FSA_1_2013_1_12980, ANII.| Biblioteca(s): INIA Las Brujas. |
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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha actual : |
12/12/2017 |
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Actualizado : |
12/12/2017 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
LADO, B.; BATTENFIELD, S.; SILVA, P.; QUINCKE, M.; GUZMAN, C.; SINGH, R.P.; DREISIGACKER, S.; PEÑA, J.; FRITZ, A.; POLAND, J.; GUTIERREZ, L. |
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Afiliación : |
BETTINA LADO, Facultad de Agronomía, Universidad de la República, Montevideo, Uruguay.; SARAH BATTENFIELD, AgriPro Wheat, Syngenta, 11783 Ascher Rd. Junction City, KS, 66441, USA.; MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; CARLOS GUZMAN, CIMMYT, El Batan, Mexico, Mexico.; RAVI P. SINGH, CIMMYT, El Batan, Mexico, Mexico.; SUSANNE DREISIGACKER, CIMMYT, El Batan, Mexico, Mexico.; JAVIER PEÑA, CIMMYT, El Batan, Mexico, Mexico.; ALLAN FRITZ, Wheat Genetics Resource Center, Department of Plant Pathology, 1712 Claflin Rd., Kansas State University, Manhattan, KS 66506, USA; .; JESSE POLAND, Wheat Genetics Resource Center, Department of Plant Pathology, 1712 Claflin Rd., Kansas State University, Manhattan, KS 66506, USA.; LUCIA GUTIERREZ, Department of Agronomy, University of Wisconsin, 1575 Linden Dr., Madison, WI 53706, USA. |
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Título : |
Comparing strategies to select crosses using genomic prediction in two wheat breeding programs. |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
In: International Wheat Genetics Symposium, 12, Tulln, Austria; April 23-28, 2017; BOKU: University of Natural Resources and Life Sciences, Vienna, Austria. |
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Páginas : |
p.88-90. |
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Idioma : |
Español |
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Contenido : |
Key message: Evaluation of crosses prediction methods with and without accounting for progeny variance. Mid-parent values was a much larger factor determining genetic gain than increasing the progeny variance of a cross.
In wheat breeding programs, a critical decision is to determine crosses that have high probability to deliver progenies with higher genetics gains (Zhong & Jannink 2007, Bernardo 2014). We present an application of genomic models for predicting parental cross combinations for grain yield, grain protein, and loaf volume across two wheat-breeding programs, INIA-Uruguay and CIMMYT. We evaluated three methods for selecting the ?best? crosses based on (1) mid-parents, (2) top 10% of the progeny within a cross, and (3) maximizing mean and variance within progeny using thresholds. The last two methods were evaluated with the predicted variances obtained through progeny simulation using the PopVar (Mohammadi et al. 2015, Tiede et al. 2015) package in R software. The first two methods showed 82% of crosses in common for yield, 55% for loaf volume and 53% for grain protein, even though only the second method accounts for the variance of the progeny (Figure 1). While the expected variance of the progeny is important to increase chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses selected was a much larger factor determining genetic gain than increasing the progeny variance of a cross (Figure 2). 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, but further understanding on optimizing the cross combinations is needed. MenosKey message: Evaluation of crosses prediction methods with and without accounting for progeny variance. Mid-parent values was a much larger factor determining genetic gain than increasing the progeny variance of a cross.
In wheat breeding programs, a critical decision is to determine crosses that have high probability to deliver progenies with higher genetics gains (Zhong & Jannink 2007, Bernardo 2014). We present an application of genomic models for predicting parental cross combinations for grain yield, grain protein, and loaf volume across two wheat-breeding programs, INIA-Uruguay and CIMMYT. We evaluated three methods for selecting the ?best? crosses based on (1) mid-parents, (2) top 10% of the progeny within a cross, and (3) maximizing mean and variance within progeny using thresholds. The last two methods were evaluated with the predicted variances obtained through progeny simulation using the PopVar (Mohammadi et al. 2015, Tiede et al. 2015) package in R software. The first two methods showed 82% of crosses in common for yield, 55% for loaf volume and 53% for grain protein, even though only the second method accounts for the variance of the progeny (Figure 1). While the expected variance of the progeny is important to increase chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses selected was a much larger factor determining genetic gain than increasing the progeny variance of a cross (Figure 2)... Presentar Todo |
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Palabras claves : |
WHEAT BREEDING PROGRAMS; WHEAT QUALITY. |
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Thesagro : |
MEJORAMIENTO GENETICO DE PLANTAS; TRIGO. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 02689nam a2200289 a 4500
001 1057873
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008 2017 bl uuuu u01u1 u #d
100 1 $aLADO, B.
245 $aComparing strategies to select crosses using genomic prediction in two wheat breeding programs.
260 $aIn: International Wheat Genetics Symposium, 12, Tulln, Austria; April 23-28, 2017; BOKU: University of Natural Resources and Life Sciences, Vienna, Austria.$c2017
300 $ap.88-90.
520 $aKey message: Evaluation of crosses prediction methods with and without accounting for progeny variance. Mid-parent values was a much larger factor determining genetic gain than increasing the progeny variance of a cross. In wheat breeding programs, a critical decision is to determine crosses that have high probability to deliver progenies with higher genetics gains (Zhong & Jannink 2007, Bernardo 2014). We present an application of genomic models for predicting parental cross combinations for grain yield, grain protein, and loaf volume across two wheat-breeding programs, INIA-Uruguay and CIMMYT. We evaluated three methods for selecting the ?best? crosses based on (1) mid-parents, (2) top 10% of the progeny within a cross, and (3) maximizing mean and variance within progeny using thresholds. The last two methods were evaluated with the predicted variances obtained through progeny simulation using the PopVar (Mohammadi et al. 2015, Tiede et al. 2015) package in R software. The first two methods showed 82% of crosses in common for yield, 55% for loaf volume and 53% for grain protein, even though only the second method accounts for the variance of the progeny (Figure 1). While the expected variance of the progeny is important to increase chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses selected was a much larger factor determining genetic gain than increasing the progeny variance of a cross (Figure 2). 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, but further understanding on optimizing the cross combinations is needed.
650 $aMEJORAMIENTO GENETICO DE PLANTAS
650 $aTRIGO
653 $aWHEAT BREEDING PROGRAMS
653 $aWHEAT QUALITY
700 1 $aBATTENFIELD, S.
700 1 $aSILVA, P.
700 1 $aQUINCKE, M.
700 1 $aGUZMAN, C.
700 1 $aSINGH, R.P.
700 1 $aDREISIGACKER, S.
700 1 $aPEÑA, J.
700 1 $aFRITZ, A.
700 1 $aPOLAND, J.
700 1 $aGUTIERREZ, L.
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