|
|
Registro completo
|
Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
03/10/2018 |
Actualizado : |
24/02/2022 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
LADO, B.; VÁZQUEZ, D.; QUINCKE, M.; SILVA, P.; AGUILAR, I.; GUTIÉRREZ, L. |
Afiliación : |
BETTINA LADO, Universidad de la República (UdelaR)/ Facultad de Agronomía; DANIEL VÁZQUEZ PEYRONEL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARTIN CONRADO QUINCKE WALDEN, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MARIA PAULA SILVA VILLELLA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIÉRREZ, Universidad de la República (UdelaR)/ Facultad de Agronomía; Universidad de Wisconsin-Madison. |
Título : |
Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality. [Original article]. |
Fecha de publicación : |
2018 |
Fuente / Imprenta : |
Theoretical and Applied Genetics, 1 December 2018, Volume 131, Issue 12, pp. 2719-2731. OPEN ACCESS. |
ISSN : |
0040-5752 |
DOI : |
10.1007/s00122-018-3186-3 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 29 January 2018 / Accepted: 10 September 2018 / Published online: 19 September 2018.
Supplementary materials.
Acknowledgements: We express our appreciation for the effort of the technical personnel of INIA La Estanzuela from ?Laboratorio de calidad industrial de granos.? Support for doctoral work of BL was provided by Agencia Nacional de Investigación e Innovación (ANII), Uruguay, through Grant POS_NAC_2013_1_11261 and by Comisión Sectorial de Investigación Científica (CSIC), Uruguay, through grants in the program internships abroad. We would like to thank two anonymous reviewers for their comments that improved the manuscript.
Open Access
Copyright information: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
Contenido : |
KEY MESSAGE: Multi-trait genomic prediction models are useful to allocate available resources in breeding programs by targeted phenotyping of correlated traits when predicting expensive and labor-intensive quality parameters.
ABSTRACT: Multi-trait genomic prediction models can be used to predict labor-intensive or expensive correlated traits where phenotyping depth of correlated traits could be larger than phenotyping depth of targeted traits, reducing resources and improving prediction accuracy. This is particularly important in the context of allocating phenotyping resource in plant breeding programs. The objective of this work was to evaluate multi-trait models predictive ability with different depth of phenotypic information from correlated traits. We evaluated 495 wheat advanced breeding lines for eight baking quality traits which were genotyped with genotyping-by-sequencing. Through different approaches for cross-validation, we evaluated the predictive ability of a single-trait model and a multi-trait model. Moreover, we evaluated different sizes of the training population (from 50 to 396 individuals) for the trait of interest, different depth of phenotypic information for correlated traits (50 and 100%) and the number of correlated traits to be used (one to three). There was no loss in the predictive ability by reducing the training population up to a 30% (149 individuals) when using correlated traits. A multi-trait model with one highly correlated trait phenotyped for both the training and testing sets was the best model considering phenotyping resources and the gain in predictive ability. The inclusion of correlated traits in the training and testing lines is a strategic approach to replace phenotyping of labor-intensive and high cost traits in a breeding program.
© 2018, The Author(s). MenosKEY MESSAGE: Multi-trait genomic prediction models are useful to allocate available resources in breeding programs by targeted phenotyping of correlated traits when predicting expensive and labor-intensive quality parameters.
ABSTRACT: Multi-trait genomic prediction models can be used to predict labor-intensive or expensive correlated traits where phenotyping depth of correlated traits could be larger than phenotyping depth of targeted traits, reducing resources and improving prediction accuracy. This is particularly important in the context of allocating phenotyping resource in plant breeding programs. The objective of this work was to evaluate multi-trait models predictive ability with different depth of phenotypic information from correlated traits. We evaluated 495 wheat advanced breeding lines for eight baking quality traits which were genotyped with genotyping-by-sequencing. Through different approaches for cross-validation, we evaluated the predictive ability of a single-trait model and a multi-trait model. Moreover, we evaluated different sizes of the training population (from 50 to 396 individuals) for the trait of interest, different depth of phenotypic information for correlated traits (50 and 100%) and the number of correlated traits to be used (one to three). There was no loss in the predictive ability by reducing the training population up to a 30% (149 individuals) when using correlated traits. A multi-trait model with one highly correlated trait phenotyped f... Presentar Todo |
Palabras claves : |
ABILITY TESTING; FORECASTING; GENOMIC PREDICTIONS; PLANT BREEDING PROGRAMS; PLANTS (BOTANY); PLATAFORMA AGROALIMENTOS; QUALITY CONTROL; SOFTWARE TESTING. |
Thesagro : |
GENES. |
Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/11357/1/Lado2018-Article-ResourceAllocationOptimization.pdf
http://www.ainfo.inia.uy/digital/bitstream/item/12863/1/122-2018-3186-MOESM1-ESM.pdf
https://link.springer.com/content/pdf/10.1007%2Fs00122-018-3186-3.pdf
|
Marc : |
LEADER 03937naa a2200325 a 4500 001 1059141 005 2022-02-24 008 2018 bl uuuu u00u1 u #d 022 $a0040-5752 024 7 $a10.1007/s00122-018-3186-3$2DOI 100 1 $aLADO, B. 245 $aResource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality. [Original article].$h[electronic resource] 260 $c2018 500 $aArticle history: Received: 29 January 2018 / Accepted: 10 September 2018 / Published online: 19 September 2018. Supplementary materials. Acknowledgements: We express our appreciation for the effort of the technical personnel of INIA La Estanzuela from ?Laboratorio de calidad industrial de granos.? Support for doctoral work of BL was provided by Agencia Nacional de Investigación e Innovación (ANII), Uruguay, through Grant POS_NAC_2013_1_11261 and by Comisión Sectorial de Investigación Científica (CSIC), Uruguay, through grants in the program internships abroad. We would like to thank two anonymous reviewers for their comments that improved the manuscript. Open Access Copyright information: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 520 $aKEY MESSAGE: Multi-trait genomic prediction models are useful to allocate available resources in breeding programs by targeted phenotyping of correlated traits when predicting expensive and labor-intensive quality parameters. ABSTRACT: Multi-trait genomic prediction models can be used to predict labor-intensive or expensive correlated traits where phenotyping depth of correlated traits could be larger than phenotyping depth of targeted traits, reducing resources and improving prediction accuracy. This is particularly important in the context of allocating phenotyping resource in plant breeding programs. The objective of this work was to evaluate multi-trait models predictive ability with different depth of phenotypic information from correlated traits. We evaluated 495 wheat advanced breeding lines for eight baking quality traits which were genotyped with genotyping-by-sequencing. Through different approaches for cross-validation, we evaluated the predictive ability of a single-trait model and a multi-trait model. Moreover, we evaluated different sizes of the training population (from 50 to 396 individuals) for the trait of interest, different depth of phenotypic information for correlated traits (50 and 100%) and the number of correlated traits to be used (one to three). There was no loss in the predictive ability by reducing the training population up to a 30% (149 individuals) when using correlated traits. A multi-trait model with one highly correlated trait phenotyped for both the training and testing sets was the best model considering phenotyping resources and the gain in predictive ability. The inclusion of correlated traits in the training and testing lines is a strategic approach to replace phenotyping of labor-intensive and high cost traits in a breeding program. © 2018, The Author(s). 650 $aGENES 653 $aABILITY TESTING 653 $aFORECASTING 653 $aGENOMIC PREDICTIONS 653 $aPLANT BREEDING PROGRAMS 653 $aPLANTS (BOTANY) 653 $aPLATAFORMA AGROALIMENTOS 653 $aQUALITY CONTROL 653 $aSOFTWARE TESTING 700 1 $aVÁZQUEZ, D. 700 1 $aQUINCKE, M. 700 1 $aSILVA, P. 700 1 $aAGUILAR, I. 700 1 $aGUTIÉRREZ, L. 773 $tTheoretical and Applied Genetics, 1 December 2018, Volume 131, Issue 12, pp. 2719-2731. OPEN ACCESS.
Descargar
Esconder MarcPresentar Marc Completo |
Registro original : |
INIA Las Brujas (LB) |
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
|
Registros recuperados : 75 | |
42. | | GERMAN, S.; QUINCKE, M.; VÁZQUEZ, D.; CASTRO, M.; PEREYRA, S.; SILVA, P.; GARCIA, A. (Ed.). Seminario Internacional "1914-2014: Un siglo de mejoramiento de trigo en La Estanzuela." INIA La Estanzuela, 27-28-29 de agosto de 2014. Montevideo (UY): INIA, 2018. 307 p. (INIA Serie Técnica; 241) Editores y Comité Organizador: Silvia Germán, Martín Quincke, Daniel Vázquez, Marina Castro, Silvia Pereyra, Paula Silva, Adriana García.Biblioteca(s): INIA La Estanzuela; INIA Las Brujas. |
| |
43. | | CAMPOS, P.; CASTRO, M.; PEREYRA, S.; QUINCKE, M.; MILISICH, H.; GIECO, L.; LÓPEZ, J.; GERMAN, S. Reemergence of stem rust at epidemic levels in Argentina and Uruguay in 2014. In: BGRI Workshop, 2015, Sidney, AU. Poster abstracts. [Ithaca, NY]: Borlaug Global Rust Initiative, 2015.Biblioteca(s): INIA La Estanzuela. |
| |
44. | | ESTEVES, P.; HERNANDEZ, L.; CASTILLO, A.; DALLA RIZZA, M.; QUINCKE, M. Tecnologías para el desarrollo de líneas recombinantes de trigo. MV 20 - 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. 290Tipo: Trabajos en Congresos/Conferencias |
Biblioteca(s): INIA Las Brujas. |
| |
47. | | LUIZZI, D.; ABADIE, T.; GATTI, I.; QUINCKE, M.; CONDON, F.; PEREYRA, S.; VÁZQUEZ, D.; DÍAZ DE ACKERMANN, M.; GERMAN, S. Consideraciones finales. Capítulo 7. In: GERMAN, S.; LUIZZI, D. (Ed.). 100 años de mejoramiento de trigo en INIA La Estanzuela. Montevideo (UY): INIA, 2018. p. 68-72.Tipo: Capítulo en Libro Técnico-Científico |
Biblioteca(s): INIA La Estanzuela. |
| |
48. | | LUIZZI, D.; PEREYRA, S.; QUINCKE, M.; ABADIE, T.; GATTI, I.; DÍAZ DE ACKERMANN, M.; VÁZQUEZ, D.; CONDON, F.; GERMAN, S. Cien años de mejoramiento genético de trigo en La Estanzuela, Uruguay. In: SEMINARIO INTERNACIONAL DE TRIGO, 2014, La Estanzuela, Colonia, UY. GERMÁN, S., et al. (Org.). 1914-2014, un siglo de mejoramiento de trigo en La Estanzuela: un valioso legado para el futuro: presentaciones; resúmenes. La Estanzuela, Colonia, UY: INIA, 2014. p. 1-2.Tipo: Presentaciones Orales |
Biblioteca(s): INIA La Estanzuela. |
| |
49. | | 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)Tipo: Artículos en Revistas Agropecuarias |
Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
| |
50. | | SILVA, P.; LADO, B.; BRANDARIZ, S.; PEREYRA, S.; GERMAN, S.; VON ZITZEWITZ, J.; GUTIÉRREZ, L.; QUINCKE, M. Herramientas utilizadas y avances en mejoramiento molecular en el Programa de Mejoramiento Genético de Trigo de INIA Uruguay.[Presentación oral]. In: SEMINARIO INTERNACIONAL DE TRIGO, 2014, La Estanzuela, Colonia, UY. GERMÁN, S., et al. (Org.). 1914-2014, un siglo de mejoramiento de trigo en La Estanzuela: un valioso legado para el futuro: presentaciones; resúmenes. La Estanzuela, Colonia, UY: INIA, 2014. p. 81.Tipo: Presentaciones Orales |
Biblioteca(s): INIA La Estanzuela. |
| |
51. | | SILVA, P.; LADO, B.; BRANDARIZ, S.; BERRO, I.; GUTIÉRREZ, L.; PEREYRA, S.; GERMAN, S.; VON ZITZEWITZ, J.; QUINCKE, M. Herramientas utilizadas y avances en mejoramiento molecular en el programa de mejoramiento genético de trigo de Inia Uruguay. In: German, S.; Quincke, M.; Vázquez, D.; Castro, M.; Pereyra, S.; Silva, P.; García, A. (Eds.). Seminario Internacional "1914-2014: Un siglo de mejoramiento de trigo en La Estanzuela". Montevideo (UY): INIA, 2018. p. 277-285. (INIA Serie Técnica; 241).Tipo: Capítulo en Libro Técnico-Científico |
Biblioteca(s): INIA La Estanzuela. |
| |
52. | | LUIZZI, D.; PEREYRA, S.; ABADIE, T.; GATTI, I.; QUINCKE, M.; VÁZQUEZ, D.; CONDON, F.; DÍAZ DE ACKERMANN, M.; GERMAN, S. Introducción. In: GERMAN, S.; LUIZZI, D. (Ed.). 100 años de mejoramiento de trigo en INIA La Estanzuela. Montevideo (UY): INIA, 2018. p. 5-6.Tipo: Capítulo en Libro Técnico-Científico |
Biblioteca(s): INIA La Estanzuela. |
| |
53. | | LUIZZI, D.; PEREYRA, S.; ABADIE, T.; GATTI, I.; QUINCKE, M.; CONDON, F.; VÁZQUEZ, D.; DÍAZ DE ACKERMANN, M.; GERMAN, S. Objetivos del mejoramiento genético de trigo. Capítulo 2. In: GERMAN, S.; LUIZZI, D. (Ed.). 100 años de mejoramiento de trigo en INIA La Estanzuela. Montevideo (UY): INIA, 2018. p. 10-16.Tipo: Capítulo en Libro Técnico-Científico |
Biblioteca(s): INIA La Estanzuela. |
| |
54. | | GERMAN, S.; PEREYRA, S.; CASTRO, M.; AZZIMONTI, G.; QUINCKE, M.; KOHLI, M.; MADARIAGA, R.; CHAVES , M.; CAMPO, P. Las royas del trigo: situación a nivel regional y amenazas para el cultivo. In: CONGRESO NACIONAL DE TRIGO, 8o. ; SIMPOSIO DE CEREALES DE SIEMBRA OTOÑO INVERNAL, 6o. ; ENCUENTRO DEL MERCOSUR, 2º, Pergamino, Argentina: AIANBA, 14-16 setiembre,2016.Biblioteca(s): INIA La Estanzuela. |
| |
55. | | QUINCKE, M.; PETERSON, C.J.; ZEMETRA, R.S.; HANSEN, J.L.; CHEN, J.; RIERA-LIZARAZU, O.; MUNDT, C.C. Quantitative trait loci analysis for resistance to cephalosporium stripe, a vascular wilt disease of wheat. Theoretical and Applied Genetics, 2011, v.122, No.7, p.1339-1349. Article history: Received: 20 August 2010 / Accepted: 6 January 2011 / Published online: 23 January 2011.Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 1 |
Biblioteca(s): INIA La Estanzuela; INIA Las Brujas. |
| |
56. | | AZZIMONTI, G.; DOMENIGUINI, V.; GONZALEZ, N.; GARCIA, R.; SAINT-PIERRE, C.; SINGH, P.; QUINCKE, M.; PEREYRA, S.; GERMAN, S. Three years of the Precision Wheat Phenotyping Platform for diseases in Uruguay: current status and future prospects. [Poster]. In: Proceedings of the Borlaug Global Rust Initiative Technical Workshop ,14-18 April, 2018, Marrakesh, Marruecos.Biblioteca(s): INIA La Estanzuela. |
| |
57. | | 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.Tipo: Trabajos en Congresos/Conferencias |
Biblioteca(s): INIA La Estanzuela. |
| |
58. | | 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.Tipo: Trabajos en Congresos/Conferencias |
Biblioteca(s): INIA La Estanzuela. |
| |
59. | | 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.Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : B - 3 |
Biblioteca(s): INIA La Estanzuela. |
| |
60. | | SILVA, P.; CALVO-SALAZAR, V.; CONDON, F.; QUINCKE, M.; PRITSCH, C.; GUTIÉRREZ, L.; CASTRO, A.; HERRERA-FOESSEL, S.; VON ZITZEWITZ, J.; GERMAN, S. Effects and interactions of genes Lr34, Lr68 and Sr2 on wheat leaf rust adult plant resistance in Uruguay Euphytica, 2015, v. 204, p. 599?608.Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
Biblioteca(s): INIA La Estanzuela; INIA Las Brujas. |
| |
Registros recuperados : 75 | |
|
Expresión de búsqueda válido. Check! |
|
|