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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
03/10/2018 |
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Actualizado : |
24/02/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LADO, B.; VÁZQUEZ, D.; QUINCKE, M.; SILVA, P.; AGUILAR, I.; GUTIÉRREZ, L. |
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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. |
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Título : |
Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality. [Original article]. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Theoretical and Applied Genetics, 1 December 2018, Volume 131, Issue 12, pp. 2719-2731. OPEN ACCESS. |
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ISSN : |
0040-5752 |
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DOI : |
10.1007/s00122-018-3186-3 |
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Idioma : |
Inglés |
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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. |
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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 |
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Palabras claves : |
ABILITY TESTING; FORECASTING; GENOMIC PREDICTIONS; PLANT BREEDING PROGRAMS; PLANTS (BOTANY); PLATAFORMA AGROALIMENTOS; QUALITY CONTROL; SOFTWARE TESTING. |
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Thesagro : |
GENES. |
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Asunto categoría : |
U10 Métodos matemáticos y estadísticos |
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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
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Marc : |
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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.
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INIA Las Brujas (LB) |
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| Registros recuperados : 62 | |
| 3. |  | GUTIÉRREZ, L.; LADO, B.; GONZÁLEZ, P.; SILVA, P.; QUINCKE, M. Handling Genotype-By-Environment Interaction in Genomic Selection to Predict New Genotypes and New Environments. [P0814] In: International Plant & Animal Genome, Conference PAG XXIV, "The largest Ag-genomics Meeting in the World San Diego, CA, USA; January 9-13, 2016. [Abstract] .| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| 5. | | PÉREZ, O.; VIEGA, L.; GUTIÉRREZ, L.; CASTRO, M. Post-anthesis water deficit in spring wheat: effects on yield components and relative water content. 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: resúmenes; posters. La Estanzuela, Colonia, UY: INIA, 2014. p. 41.| Biblioteca(s): INIA La Estanzuela. |
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| 6. | | PÉREZ, O.; VIEGA, L.; GUTIERREZ, L.; CASTRO, M. Post-anthesis water deficit in spring wheat: effects on yield components and relative water content. [Poster]. 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.130. (INIA Serie Técnica; 241).| Biblioteca(s): INIA La Estanzuela. |
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| 7. | | BORGES, A.; GONZÁLEZ-REYMUNDEZ, A.; ERNST, O.; CADENAZZI, M.; TERRA, J.A.; GUTIÉRREZ, L. Can spatial modeling substitute experimental design in agricultural experiments? Crop Science, 2018, v. 59, no. 1, p. 1-10. Article history: Accepted paper, posted 10/05/18. Published online December, 13. 2018.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Treinta y Tres. |
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| 8. | | PEREYRA, S.; GERMAN, S.; GONZÁLEZ, S.N.; CASTRO, A.; GAMBA, F.; GUTIERREZ, L. Advances in the integrated management of leaf blotches in Uruguay. In: International Workshop on Barley Leaf Diseases , 2o. Rabat, Morocco: The International Center for Agricultural Research in the Dry Areas (ICARDA), April 5-7, 2017. p. 46.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 9. | | GUTIÉRREZ, L.; BERBERIAN, N.; CAPETTINI, F.; GERMAN, S.; PEREYRA, S.; PÉREZ, C.; CASTRO, A. Disease resistance QTLs in barley germplasm from Latin America In: INTERNATIONAL ANIMAL AND PLANT GENOME CONFERENCE, 20., 2012, San Diego, CA, US. Posters: wheat, barley, oat, and related. P0350. [s.l.: INTL-PAG], 2012.| Biblioteca(s): INIA La Estanzuela. |
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| 10. | | CAJARVILLE, C.; BRITOS, A.; ERRANDONEA, N.; GUTIÉRREZ, L.; COZZOLINO, D.; REPETTO, J.L. Diurnal changes in water-soluble carbohydrate concentration in lucerne and tall fescue in autumn and the effects on in vitro fermentation. Research Article. New Zealand Journal of Agricultural Research, 2015, v. 58, no.3, p. 281-291. Article history: Received 23 January 2014 // Accepted 5 February 2015.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 11. | | PORTA, B.; CONDON, F.; BONNECARRERE, V.; GUTIÉRREZ, L.; FRANCO, J.; GALVÁN, G. Diversidad y estructura genética del germoplasma de maíz blanco dentad de Uruguay mediante microsatélites. [Resumen]. In: SIMPÓSIO DE RECURSOS GENÉTICOS PARA A AMÉRICA LATINA E CARIBE, 10., 2015, Bento Gonçalves. Recursos genéticos no século 21: de Vavilov a Svalbard. Anais... [s.l.]: Sociedade Brasileira de Recursos Genéticos, 2015. p.65. Agradecimientos: Comisión Sectorial de Investigación Científica, CSIC - UdelaR, Uruguay.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| 12. | | GUTIERREZ, L.; BORGES, A.; QUERO, G.; GONZALEZ-REYMUNDEZ, A.; BERRO, I.; LADO, B.; CASTRO, A. Biostatistical tools for plant breeding in the genomics era. 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.46-57. (INIA Serie Técnica; 241).| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA La Estanzuela. |
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| 13. | | 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.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 14. | | REBOLLO, I.; AGUILAR, I.; PÉREZ DE VIDA, F.; MOLINA, F.; GUTIÉRREZ, L.; ROSAS, J.E. Genotype by environment interaction characterization and its modeling with random regression to climatic variables in two rice breeding populations. Original article. Crop Science. 2023, Volume 63, Issue 4, Pages 2220-2240. https://doi.org/10.1002/csc2.21029 -- OPEN ACCESS. Article history: Received 21 November 2022, Accepted 10 May 2023, Published online 16 June 2023. -- Correspondence: Rosas, J.E.; INIA, Estación Experimental Treinta y Tres, Road 8 km 281, Treinta y Tres, Uruguay; email:jrosas@inia.org.uy...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 15. | | QUERO, C.; FERNANDEZ, S.; BRANDARIZ, S.B.; SIMONDI, S.; GUTIÉRREZ, L. Herramientas de análisis y visualización genómica. MV 10 - 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. 285| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 18. | | BERBERIAN, N.; CASTRO, A.; CAPETTINI, F.; FROS, D.; GERMAN, S.; PEREYRA, S.; PEREZ, C.; GUTIÉRREZ, L. Modelos mixtos para la identificación de QTL para enfermedades en cebada a traves de mapeo asociativo. In: REUNIÓN CIENTIFICA DEL GRUPO ARGENTINO DE BIOMETRÍA, 16., 2011, Salta, AR. Libro de resúmenes: modelos lineales y generalizados mixtos. La Plata: GAB, 2011. p. 108.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 19. | | GONZÁLEZ BARRIOS, P.; PÉREZ, O.; CASTRO, M.; CERETTA, S.; VILARO, D.; GUTIÉRREZ, L. Identificación de limitantes a la expresión del potencial de rendimiento en girasol en Uruguay mediante GGE biplots y PLS regression. In: IV Encuentro Iberoamericano de Biometría; 4o. y XVIII Reunión Científica del GAB, 17o., Setiembre 2013, Mar del Plata ,ROMERO, M.C.; MARINELLI, C.; CEPEDA, R. Eds., La Plata, Bs As, Argentina: Grupo Argentino de Biometría. p. 236-239| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 20. | | LADO, B.; VÁZQUEZ, D.; QUINCKE, M.; SILVA, P.; AGUILAR, I.; GUTIÉRREZ, L. Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality. [Original article]. Theoretical and Applied Genetics, 1 December 2018, Volume 131, Issue 12, pp. 2719-2731. OPEN ACCESS. 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 62 | |
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