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Registro completo
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Biblioteca (s) : |
INIA La Estanzuela. |
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Fecha : |
10/08/2020 |
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Actualizado : |
05/09/2022 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
BHATTA, M.; GUTIERREZ, L.; CAMMAROTA, L.; CARDOZO, F.; GERMAN, S.; GÓMEZ-GUERRERO, B.; PARDO, M.F.; LANARO, V.; SAYAS, M.; CASTRO, A.J. |
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Afiliación : |
MADHAV BHATTA, Department of Agronomy, University of Wisconsin-Madison, 1575 Linden Dr., WI, 53706, USA.; LUCIA GUTIERREZ, Agronomy, University of Wisconsin-Madison, 1575 Linden Dr., WI, 53706, USA.; LORENA CAMMAROTA, Department of plant production, Facultad de Agronomía, Universidad de la República, Ruta 3, Km363, Paysandú 60000, Uruguay./Maltería Uruguay S.A. Ruta 55, Km26, Ombúes de Lavalle, Uruguay.; FERNANDA CARDOZO, Maltería Uruguay S.A. Ruta 55, Km26, Ombúes de Lavalle, Uruguay.; SILVIA ELISA GERMAN FAEDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; BLANCA GÓMEZ-GUERRERO, LATU Foundation, Av Italia 6201, Montevideo 11500, Uruguay.; MARÍA FERNANDA PARDO, Maltería Oriental S.A., Camino Abrevadero 5525, Montevideo 12400, Uruguay.; VALERIA LANARO, LATU Foundation, Av Italia 6201, Montevideo 11500, Uruguay.; MERCEDES SAYAS, Maltería Oriental S.A., Camino Abrevadero 5525, Montevideo 12400, Uruguay.; ARIEL J. CASTRO, Ariel J. Castro ?Department of plant production, Facultad de Agronomía, Universidad de la República, Ruta 3, Km363, Paysandú 60000, Uruguay,. |
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Título : |
Multi-trait genomic prediction model increased the predictive ability for agronomic and malting quality traits in barley (Hordeum vulgare L.). |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
G3: Genes, Genomes, Genetics, March 1, 2020 vol. 10 no. 3 1113-1124. Open Acces. Doi: https://doi.org/10.1534/g3.119.400968 |
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DOI : |
10.1534/g3.119.400968 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received July 26, 2019/Accepted January 22, 2020/Published online March 5, 2020. This work was funded in part by the following grants from ANII (FSA-1-2013-12977), CSIC (CSIC_I+D_ 1131 and CSIC_Movilidad_ 1131). The work was also funded by the Cereals Breeding and Quantitative Genetics group at the University of Wisconsin - Madison. We would like to acknowledge Dr. Juan Diaz at INIA, who developed the double haploid population and also contributed to the planning of the study. Malteria Oriental S.A. (MOSA) contributed with the experiments in their experimental areas and with some of the lab work. Malteria Uruguay S.A. (MUSA) contributed to the experiments in their experimental areas. We would also like to acknowledge: USDA-ARS small grains genotyping lab at Fargo, North Dakota for genotyping service; the Center for High Throughput Computing (CHTC) service at the University of Wisconsin-Madison for providing the high-performance computing resources; and Dr. Bettina Lado for sharing the R scripts. We would like to thank two anonymous reviewers and editors who provided constructive suggestions to this manuscript. |
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Contenido : |
Abstract:
Plant breeders regularly evaluate multiple traits across multiple environments, which opens an avenue for using multiple traits in genomic prediction models. We assessed the potential of multi-trait (MT) genomic prediction model through evaluating several strategies of incorporating multiple traits (eight agronomic and malting quality traits) into the prediction models with two cross-validation schemes (CV1, predicting new lines with genotypic information only and CV2, predicting partially phenotyped lines using both genotypic and phenotypic information from correlated traits) in barley. The predictive ability was similar for single (ST-CV1) and multi-trait (MT-CV1) models to predict new lines. However, the predictive ability for agronomic traits was considerably increased when partially phenotyped lines (MT-CV2) were used. The predictive ability for grain yield using the MT-CV2 model with other agronomic traits resulted in 57% and 61% higher predictive ability than ST-CV1 and MT-CV1 models, respectively. Therefore, complex traits such as grain yield are better predicted when correlated traits are used. Similarly, a considerable increase in the predictive ability of malting quality traits was observed when correlated traits were used. The predictive ability for grain protein content using the MT-CV2 model with both agronomic and malting traits resulted in a 76% higher predictive ability than ST-CV1 and MT-CV1 models. Additionally, the higher predictive ability for new environments was obtained for all traits using the MT-CV2 model compared to the MT-CV1 model. This study showed the potential of improving the genomic prediction of complex traits by incorporating the information from multiple traits (cost-friendly and easy to measure traits) collected throughout breeding programs which could assist in speeding up breeding cycles. MenosAbstract:
Plant breeders regularly evaluate multiple traits across multiple environments, which opens an avenue for using multiple traits in genomic prediction models. We assessed the potential of multi-trait (MT) genomic prediction model through evaluating several strategies of incorporating multiple traits (eight agronomic and malting quality traits) into the prediction models with two cross-validation schemes (CV1, predicting new lines with genotypic information only and CV2, predicting partially phenotyped lines using both genotypic and phenotypic information from correlated traits) in barley. The predictive ability was similar for single (ST-CV1) and multi-trait (MT-CV1) models to predict new lines. However, the predictive ability for agronomic traits was considerably increased when partially phenotyped lines (MT-CV2) were used. The predictive ability for grain yield using the MT-CV2 model with other agronomic traits resulted in 57% and 61% higher predictive ability than ST-CV1 and MT-CV1 models, respectively. Therefore, complex traits such as grain yield are better predicted when correlated traits are used. Similarly, a considerable increase in the predictive ability of malting quality traits was observed when correlated traits were used. The predictive ability for grain protein content using the MT-CV2 model with both agronomic and malting traits resulted in a 76% higher predictive ability than ST-CV1 and MT-CV1 models. Additionally, the higher predictive ability for ... Presentar Todo |
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Palabras claves : |
GENOMIC PREDICTION; GENPRED; GRAIN QUALITY; GRAIN YIELD; MALTING QUALITY; MULTI-ENVIRONMENT; MULTI-TRAIT; SHARED DATA RESOURCES. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/16688/1/G3-Bethesda-2020.pdf
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7056970/pdf/1113.pdf
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Marc : |
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008 2020 bl uuuu u00u1 u #d
024 7 $a10.1534/g3.119.400968$2DOI
100 1 $aBHATTA, M.
245 $aMulti-trait genomic prediction model increased the predictive ability for agronomic and malting quality traits in barley (Hordeum vulgare L.).$h[electronic resource]
260 $c2020
500 $aArticle history: Received July 26, 2019/Accepted January 22, 2020/Published online March 5, 2020. This work was funded in part by the following grants from ANII (FSA-1-2013-12977), CSIC (CSIC_I+D_ 1131 and CSIC_Movilidad_ 1131). The work was also funded by the Cereals Breeding and Quantitative Genetics group at the University of Wisconsin - Madison. We would like to acknowledge Dr. Juan Diaz at INIA, who developed the double haploid population and also contributed to the planning of the study. Malteria Oriental S.A. (MOSA) contributed with the experiments in their experimental areas and with some of the lab work. Malteria Uruguay S.A. (MUSA) contributed to the experiments in their experimental areas. We would also like to acknowledge: USDA-ARS small grains genotyping lab at Fargo, North Dakota for genotyping service; the Center for High Throughput Computing (CHTC) service at the University of Wisconsin-Madison for providing the high-performance computing resources; and Dr. Bettina Lado for sharing the R scripts. We would like to thank two anonymous reviewers and editors who provided constructive suggestions to this manuscript.
520 $aAbstract: Plant breeders regularly evaluate multiple traits across multiple environments, which opens an avenue for using multiple traits in genomic prediction models. We assessed the potential of multi-trait (MT) genomic prediction model through evaluating several strategies of incorporating multiple traits (eight agronomic and malting quality traits) into the prediction models with two cross-validation schemes (CV1, predicting new lines with genotypic information only and CV2, predicting partially phenotyped lines using both genotypic and phenotypic information from correlated traits) in barley. The predictive ability was similar for single (ST-CV1) and multi-trait (MT-CV1) models to predict new lines. However, the predictive ability for agronomic traits was considerably increased when partially phenotyped lines (MT-CV2) were used. The predictive ability for grain yield using the MT-CV2 model with other agronomic traits resulted in 57% and 61% higher predictive ability than ST-CV1 and MT-CV1 models, respectively. Therefore, complex traits such as grain yield are better predicted when correlated traits are used. Similarly, a considerable increase in the predictive ability of malting quality traits was observed when correlated traits were used. The predictive ability for grain protein content using the MT-CV2 model with both agronomic and malting traits resulted in a 76% higher predictive ability than ST-CV1 and MT-CV1 models. Additionally, the higher predictive ability for new environments was obtained for all traits using the MT-CV2 model compared to the MT-CV1 model. This study showed the potential of improving the genomic prediction of complex traits by incorporating the information from multiple traits (cost-friendly and easy to measure traits) collected throughout breeding programs which could assist in speeding up breeding cycles.
653 $aGENOMIC PREDICTION
653 $aGENPRED
653 $aGRAIN QUALITY
653 $aGRAIN YIELD
653 $aMALTING QUALITY
653 $aMULTI-ENVIRONMENT
653 $aMULTI-TRAIT
653 $aSHARED DATA RESOURCES
700 1 $aGUTIERREZ, L.
700 1 $aCAMMAROTA, L.
700 1 $aCARDOZO, F.
700 1 $aGERMAN, S.
700 1 $aGÓMEZ-GUERRERO, B.
700 1 $aPARDO, M.F.
700 1 $aLANARO, V.
700 1 $aSAYAS, M.
700 1 $aCASTRO, A.J.
773 $tG3: Genes, Genomes, Genetics, March 1, 2020 vol. 10 no. 3 1113-1124. Open Acces. Doi: https://doi.org/10.1534/g3.119.400968
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INIA La Estanzuela (LE) |
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| Registros recuperados : 62 | |
| 41. |  | ROSAS, J.E.; MARTÍNEZ, S.; BONNECARRERE, V.; BLANCO, P.H.; PÉREZ DE VIDA, F.; GERMAN, S.; JANNINK, J.L.; GUTIÉRREZ, L. Evaluación de nuevos métodos de selección para resistencia a enfermedades del tallo y la vaina en arroz. In: Zorrilla, G.; Martínez, S.; Saravia, H. (Eds.) Arroz 2017. Montevideo (UY): INIA, 2017. p. 31-34. (INIA Serie Técnica; 233)| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Treinta y Tres. |
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| 42. | | ROSAS, J.E.; BONNECARRERE, V.; MARTÍNEZ, S.; PÉREZ DE VIDA, F.; BLANCO, P.H.; QUERO, G.; FERNANDEZ, S.; GARAYCOCHEA, S.; JANNINK, J.; GUTIERREZ, L. Mapeo asociativo de la resistencia a enfermedades del tallo y la vaina en germoplasma avanzado de arroz. 2 - SIMPOSIOS "MEJORAMIENTO GENÉTICO POR RESISTENCIA A ENFERMEDADES E INTERACCIONES PLANTA-PATÓGENO" 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. 61| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 43. | | BONNECARRERE, M.; QUERO, G.; ROSAS, J.E.; FERNANDEZ, S.; GARAYCOCHEA, S.; MARTÍNEZ, S.; PÉREZ DE VIDA, F.; BLANCO, P.H.; BERBERIAN, N.; GUTIERREZ, L. Marcadores moleculares identificados en el Proyecto "Mapeo asociativo para asistir el mejoramiento genético de arroz". In: JORNADA TÉCNICA, VIII JORNADA DE AGROBIOTECNOLOGÍA. INIA LAS BRUJAS, 30 DE OCTUBRE DE 2014. UNIDAD DE BIOTECNOLOGÍA. Montevideo (Uruguay): INIA, 2014. 5-6 (Actividades de Difusión; 741)| Biblioteca(s): INIA Las Brujas. |
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| 44. | | BONNECARRERE, V.; QUERO, G.; ROSAS, J.; FERNÁNDEZ, S.; GARAYCOCHEA, S.; MARTINEZ, S.; PÉREZ DE VIDA, F.; BLANCO, P.H.; BERDERIAN, N.; GUTIERREZ, L. Marcadores moleculares identificados en el proyecto mapeo asociativo para asistir el mejoramiento por calidad del grano. En: INIA TREINTA Y TRES. Arroz-Soja:Resultados Experimentales 2013-2014. Treinta y Tres (UY): INIA Treinta y Tres. cap. 6. p. 24-26 (INIA Serie Actividades de Difusión; 735)| Biblioteca(s): INIA Treinta y Tres. |
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| 45. | | GUTIÉRREZ, L.; CAPETTINI, F.; FROS, D.; GERMÁN, S.; HERRERA, S.; HUERTA-ESPINO, J.; PEREYRA, S.; PEREZ, S.; SANDOVAL-ISLAS, S.; SINGH, R.; CASTRO, A. Identifying disease resistance QTLs in barley germplasm from Latin America. In: INTERNATIONAL PLANT AND GENOME CONFERENCE, 19., 2011, San Diego, CA. [Abstracts]. [s.l.: INTLPAG], 2011.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 46. | | BHATTA, M.; GUTIERREZ, L.; CAMMAROTA, L.; CARDOZO, F.; GERMAN, S.; GÓMEZ-GUERRERO, B.; PARDO, M.F.; LANARO, V.; SAYAS, M.; CASTRO, A.J. Multi-trait genomic prediction model increased the predictive ability for agronomic and malting quality traits in barley (Hordeum vulgare L.). G3: Genes, Genomes, Genetics, March 1, 2020 vol. 10 no. 3 1113-1124. Open Acces. Doi: https://doi.org/10.1534/g3.119.400968 Article history: Received July 26, 2019/Accepted January 22, 2020/Published online March 5, 2020. This work was funded in part by the following grants from ANII (FSA-1-2013-12977), CSIC (CSIC_I+D_ 1131 and CSIC_Movilidad_ 1131). The work...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| 47. | | MONTEVERDE, E.; BLANCO, P.H.; BONNECARRERE, V.; GUTIÉRREZ, L.; ROSAS, J.E.; QUERO, G.; BARBERIÁN, N.; GARAYCOCHEA, S.; FERNANDEZ, S.; MCCOUCH, S. Implementing Genomic Selection in a temperate Rice Breeding Program. [P0716] 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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| 48. | | ROSAS, J.E.; MARTÍNEZ, S.; BONNECARRERE, V.; PÉREZ DE VIDA, F.; BLANCO, P.H.; FERNANDEZ, S.; GARAYCOCHEA, S.; JANNINK, J-L.; GUTIERREZ, L. Resistance to multiple temperate and tropical stem and sheath diseases of rice. [Poster]. En: Jornadas de Investigación, Facultad de Agronomía (UdelaR), 8-9, nov. 2018, Montevideo, UY.| Biblioteca(s): INIA Treinta y Tres. |
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| 49. | | BARAIBAR, S.; GARCIA, R.; SILVA, P.; LADO, B.; CASTRO, A.; GUTIÉRREZ , L.; KAVANOVÁ, M.; QUINCKE, M.; BHAVANI , S.; RANDHAWA, M.S.; GERMAN, S. QTL of resistance to Ug99 and other stem rust pathogen races in bread wheat. Molecular Breeding, 1 August 2020, Volume 40, Issue 8, Article number 82. DOI: https://doi.org/10.1007/s11032-020-01153-5 Article history: Received 26 June 2019/ Accepted 23 October 2019/ Published 15 August 2020.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| 50. | | RAEGAN HOEFLER; GONZALEZ-BARRIOS , P.; MADHAV BHATTA; NUNES, J.A.R.; BERRO, I.; NALIN, R.S.; BORGES, A.; COVARRUBIAS, E.; DIAZ-GARCIA, L.; QUINCKE, M.; GUTIERREZ, L. Do Spatial Designs Outperform Classic Experimental Designs?. Journal of Agricultural, Biological, and Environmental Statistics, 1 December 2020, volume 25, number 4, pag.523-552, 1 December 2020. OPEN ACCESS. Doi: https://doi.org/10.1007/s13253-020-00406-2 Article history: Received 15 October 2019/Accepted 01 July 2020/Published 29 August 2020. This project was partially funded through a USDA_AFRI_NIFA_2018-67013-27620 award and by the Hatch Act Formula Fund WISO1984 and WIS03002....| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| 51. | | 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 52. | | BRANDARIZ , S.; GONZÁLEZ RAYMÚNDEZ, A.; LADO, B.; MALOSETTI, M.; FRANCO GARCIA, A.; QUINCKE, M.; VON ZITZEWITZ, J.; CASTRO, M.; MATUS,I.; DEL POZO, A.; CASTRO, A.J.; GUTIÉRREZ, L. Ascertainment bias from imputation methods evaluation in wheat. BMC Genomics, 2016, v. 17, p.773. OPEN ACCESS. Article history: Received 2016 Feb 24 // Accepted 2016 Sep 23.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 1 |
| Biblioteca(s): INIA La Estanzuela. |
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| 53. | | SPINDEL, J.E.; MONTEVERDE, E.; BEGUM, H.; AKDEMIR, D.; COLLARD, B.; REDOÑA, E.; BLANCO, P.H.; PÉREZ DE VIDA, F.; BONNECARRERE, V.; GUTIÉRREZ, L.; ROSAS, J.E.; QUERO, G.; BERBERIÁN, N.; GARAYCOCHEA, S.; FERNANDEZ, S.; JANNINK, J.L.; MCCOUCH, S. GS + de novo GWAS in Tropical and Temperate Irrigated Rice Breeding Programs. [W809] 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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| 54. | | VON ZITZEWITZ, J.; CUESTA-MARCOS, A.; CONDON, F.; CASTRO, A. J.; CHAO, S.; COREY, A.; FILICHKIN, T.; FISK, S.P.; GUTIERREZ, L.; HAGGARD, K.; KARSAI, I.; MUEHLBAUER, G. J.; SMITH, K.P.; VEISZ, O.; HAYES, P.M. The genetics of winterhardiness in barley: perspectives from genome-wide association mapping. The Plant Genome, v. 4., n,1, p. 76-91, 2011.| Tipo: Artículos Indexados |
| Biblioteca(s): INIA La Estanzuela. |
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| 55. | | GUTIÉRREZ, L.; BERBERIAN, N.; CAPETTINI, F.; FALCIONI, E.; FROS, D.; GERMAN, S.; HAYES, P. M.; HUERTA-ESPINO, J.; HERRERA, S.; PEREYRA, S.; PEREZ, C.; SANDOVAL-ISLAS, S.; SINGH, R.; CASTRO, A. Genome-wide association mapping identifies disease resistance QTLs in barley germplasm from Latin America: chapter 18. In: INTERNATIONAL BARLEY GENETICS SYMPOSIUM, 11., 2012, Hangzhou, CN. Advance in barley sciences: proceedings. Dordrecht: Zhejiang University Press/Springer, 2013. p. 209-215| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA La Estanzuela. |
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| 56. | | QUERO, G.; GUTIÉRREZ, L.; MONTEVERDE, E.; BLANCO, P.H.; PÉREZ DE VIDA, F.; ROSAS, J.E.; FERNANDEZ, S.; GARAYCOCHEA, S.; MC COUCH, S.; BERBERIAN, N.; SIMONDI, S.; BONNECARRERE, V. Genome-wide association study using historical breeding populations discovers genomic regions involved in high-quality rice. Plant Genome, 2018, Volume 11, Article number 170076. Open Access. Article history: Received: Aug 25, 2017 // Accepted: Apr 09, 2018 // Published: July 12, 2018.
Permissions: This is an open access article under the CC BY-NC-ND license. Proper attribution is required for reuse. No permissions are needed...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas; INIA Treinta y Tres. |
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| 57. | | ROSAS, J.E.; MARTÍNEZ, S.; BLANCO, P.H.; PÉREZ DE VIDA, F.; GARAYCOCHEA, S.; FERNANDEZ, S.; IRIARTE, W.; MONTEVERDE, E.; BERBERIÁN, N.; BONNECARRERE, V.; GUTIERREZ, L.; MCCOUCH, S.; JANNINK, J.L. Mapeo asociativo de resistencia a enfermedades del tallo y la vaina en arroz.[Poster]. In: Jornadas de Agrobiotecnologìa, (9a., 2015, Montevideo)| Biblioteca(s): INIA Treinta y Tres. |
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| 58. | | GUTIÉRREZ, L.; BERBERIAN, N.; CAPETTINI. F.; FALCIONI, E.; FROS, D.; GERMAN, S.; HAYES, P.; HUERTA-ESPINO, J.; HERRERA, S.; PEREYRA, S.; PEREZ, C.; SANDOVAL-ISLAS, S.; SINGH, R.; CASTRO, A. Identifying disease resistance QTLs in barley germplasm from Latin America using genome-wide association mapping. In: NORTH AMERICAN BARLEY RESEARCHERS WORKSHOP, 20., 2011, Corvallis, OR. Abstracts. Corvallis: OSU, 2011.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 59. | | GUTIÉRREZ, L.; BERBERIAN, N.M.; GERMÁN, S.; PEREYRA, S.; CAPETTINI, F.; FALCONI, E.; HAYES, P.M.; PÉREZ, C.; SANDOVAL-ISLAS, S.; ORJEDA, G.; NEYRA, E.; GONZA, V.A.; CASTRO, A. Multi-environment multi-QTL association mapping in barley In: INTERNATIONAL ANIMAL AND PLANT GENOME CONFERENCE, 21., 2013, San Diego, CA, US. Genome mapping, tagging and characterization: wheat, barley, oat, and related. P0285. [s.l.: INTLPAG], 2013.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 60. | | ROSAS, J.E.; MARTÍNEZ, S.; BLANCO, P.H.; PÉREZ DE VIDA, F.; BONNECARRERE, V.; MOSQUERA, G.; CRUZ, M.; GARAYCOCHEA, S.; MONTEVERDE, E.; GERMAN, S.; MCCOUCH, S.; JANNINK, J.; GUTIÉRREZ, L. Resistance to multiple temperate and tropical stem and sheath diseases of rice. The Plant Genome, 2018, v. 11, no. 1. art. 170029. OPEN ACCESS. Doi: https://doi.org/10.3835/plantgenome2017.03.0029 p. 1-13. History paper: Received 29 Mar. 2017, Accepted 19 Sep. 2017. Publihed online December 14, 2017.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : -- - -- |
| Biblioteca(s): INIA Treinta y Tres. |
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| Registros recuperados : 62 | |
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