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 | Acceso al texto completo restringido a Biblioteca INIA La Estanzuela. Por información adicional contacte bib_le@inia.org.uy. |
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
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
005 2017-12-12
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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Registro original : |
INIA La Estanzuela (LE) |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
21/11/2022 |
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Actualizado : |
21/11/2022 |
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Tipo de producción científica : |
Abstracts/Resúmenes |
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Autor : |
VERA, B.; NAVAJAS, E.; DE BARBIERI, I.; VAN LIER, E.; CIAPPESONI, G. |
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Afiliación : |
BRENDA VERA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ELLY ANA NAVAJAS VALENTINI, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUIS IGNACIO DE BARBIERI ETCHEBERRY, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ELIZE VAN LIER, Dpto. de Producción Animal y Pasturas, Facultad de Agronomía, Universidad de la República, Uruguay; CARLOS GABRIEL CIAPPESONI SCARONE, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Agroecological breeding: genomic evaluation in Australian Merico. [abstract]. |
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Fecha de publicación : |
2022 |
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Fuente / Imprenta : |
In: REDBIO México 2022, XI Congreso, "Biotecnología productiva y sostenible". Libro de resúmenes. 12-14 octubre 2022, Yucatán, México. p.29 |
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Idioma : |
Inglés |
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Notas : |
This project received funding from SMARTER Horizon 2020 number 772787, RUMIAR, CSIC I+D-2018-287. |
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Contenido : |
The objective of this work was to evaluate the impact of using genomics in selection decisions in the Uruguayan Merino Information Nucleus (UMIN). |
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Palabras claves : |
Agroecological; Genomic selection; SsGBLUP. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16865/1/Vera-B.-Agroecological-breeding-REDBIO-Mexico-2022.pdf
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Marc : |
LEADER 00917nam a2200205 a 4500
001 1063766
005 2022-11-21
008 2022 bl uuuu u01u1 u #d
100 1 $aVERA, B.
245 $aAgroecological breeding$bgenomic evaluation in Australian Merico. [abstract].$h[electronic resource]
260 $aIn: REDBIO México 2022, XI Congreso, "Biotecnología productiva y sostenible". Libro de resúmenes. 12-14 octubre 2022, Yucatán, México. p.29$c2022
500 $aThis project received funding from SMARTER Horizon 2020 number 772787, RUMIAR, CSIC I+D-2018-287.
520 $aThe objective of this work was to evaluate the impact of using genomics in selection decisions in the Uruguayan Merino Information Nucleus (UMIN).
653 $aAgroecological
653 $aGenomic selection
653 $aSsGBLUP
700 1 $aNAVAJAS, E.
700 1 $aDE BARBIERI, I.
700 1 $aVAN LIER, E.
700 1 $aCIAPPESONI, G.
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