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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 : 124 | |
| 101. |  | 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. |
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| 102. | | ERNST, O.; ESCUDERO, J.; VÁZQUEZ, D.; CADENAZZI, M.; CASTRO, M.; GONZÁLEZ, N.; LARRAMENDI, S.; BENTANCUR, O.; SUBURU, G.; GODIÑO, M. Caracterización de la calidad industrial de variedades de trigo en Uruguay Montevideo (UY): INIA, 2012. 40 p. (Serie FPTA-INIA; 37) Proyecto FPTA 231: Caracterización de la calidad industrial de variedades de trigo sembradas para fabricación de harinas en Uruguay. Período de Ejecución: Nov. 2006-Abr. 2009| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó. |
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| 104. | | 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. |
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| 105. | | JOHANSSON, E.; BRANLARD, G.; CUNIBERTI, M.; FLAGELLA, Z.; HÜSKEN, A.; NURIT, E.; PEÑA, R.J.; SISSONS, M.; VÁZQUEZ, D. Genotypic and Environmental Effects on Wheat Technological and Nutritional Quality. In: Igrejas G., Ikeda T., Guzmán C. (eds). Wheat Quality For Improving Processing And Human Health. Cham:Springer. Doi: https://doi.org/10.1007/978-3-030-34163-3_8 p. 171-204. Article histotory: First Online: 18 March 2020.| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA La Estanzuela. |
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| 106. | | VÁZQUEZ, D.; CARRASCO-LETELIER, L.; D´OTTONE, F.; RESQUIN, J.; SCOZ, R.; VILARO, F.; RODRIGUEZ, G.; VICENTE, E.; TERRA, J. Evaluating the sustainability of potential agro-industrial chains (sweet sorghum, grain sorghum, sweet potato and forestry) for agroenergy production. In: USDA-INIA Workshop of ECPA Project "Evaluating the Sustainability of Potential Agro-Industrial Chains for Agroenergy Production", 2013.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA La Estanzuela. |
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| 107. | | SPATARI, S.; ADLER, P.R.; CARRASCO-LETELIER, L.; D´OTTONE, F.; VÁZQUEZ, D.; RODRÍGUEZ, G.; VICENTE, E.; VILARO, F. Evaluation of low carbon biofuels for domestic energy supply in Uruguay. In: CANADIAN CHEMICAL ENGINEERING CONFERENCE, 62., INTERNATIONAL SYMPOSIUM ON BIOMASS AND BIOENERGY, 2012, Vancouver, BC, CA. Building the bio-economy: 583. [s.l.]: O`Zone Software, 2012.| Biblioteca(s): INIA La Estanzuela. |
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| 108. | | 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. |
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| 109. | | 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. |
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| 111. | | CASTRO, M.; PETERSON, C.J.; DALLA RIZZA, M.; DÍAZ DELLA VALLE, P.; VÁZQUEZ, D.; IBAÑEZ, W.; ROSS, A. Influence of heat stress on wheat grain characteristics and protein molecular weight distribution. ln: International Wheat Conference, 7., 27 Nov-2 Dec 2005, Mar del Plata, AR Buck, H.T.; Nisi, J.E.; Salomón, N., ed. Wheat production in stressed environments : proceedings. Dordrecht: Springer, 2007. p. 365-371. (Developments in Plant Breeding ; 12)| Tipo: Capítulo en Libro Técnico-Científico |
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| 112. | | CASTRO, M.; GASO, D.; VÁZQUEZ, D.; PIRELLI, J.; BERGER, A.G.; CALISTRO, R.; VERA, M.; VIEGA, L.; OTERO, A. Variabilidad genotípica en la tolerancia al anegamiento en cebada (Hordeum vulgare L.). In: CONGRESO LATINOAMERICANO DE CEBADA, 4., 2013, Bahía Blanca, AR. Resúmenes. Bahía Blanca: Bolsa de Cereales y Productos, 2013.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 113. | | CARRASCO-LETELIER, L.; VÁZQUEZ, D.; D´OTTONE, F.; RESQUÍN, F.; SCOZ, R.; VILARO, F.; RODRIGUEZ, G.; VICENTE, E.; TERRA, J.A. Balance energético de cadenas agro-industriales de interés para la producción de bioenergías. Revista INIA Uruguay, 2013, no. 32, p. 46-50 (Revista INIA; 32)| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA La Estanzuela; INIA Tacuarembó; INIA Treinta y Tres. |
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| 114. | | JOHANSSON, E.; KUKTAITE, R.; LABUSCHAGNE, M.; LAMA, S.; LAN, Y.; NAKIMBUGWE, D.; REPO-CARRASCO-VALENCIA, R.; TAFESSE, F.; TESFAYE, K.; VÁZQUEZ, D. Adaptation to abiotic stress factors and their effects on cereal and pseudocereal grain quality. (Chapter 14). In: Marianna Rakszegi, Maria Papageorgiou, João Miguel Rocha (eds). Developing sustainable and health promoting cereals and pseudocereals. Academic Press, 2023,
Pages 339-358. https://doi.org/10.1016/B978-0-323-90566-4.00001-1| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA Las Brujas. |
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| 115. | | BOGLIACCINI, A.; AGUIAR, L.; FIORENTINO, G.; FRANCHI, S.; ROVETTA, N.; OTONELLI, H.; VÁZQUEZ, D.; TIHISTA, H.; SUBURÚ, G.; CADENAZZI, M.; CEA, J.; MORIYAMA, C.; GODIÑO, M. Caracterización anual de calidad de la zafra de trigo. In: MESA NACIONAL DE TRIGO. Informe de calidad e inocuidad de trigo Uruguayo: zafra 2013-2014. Montevideo, UY: MGAP, FAGRO, CIPU,INIA, LATU, 2013.| Biblioteca(s): INIA La Estanzuela. |
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| 116. | | VÁZQUEZ, D.; BERGER, A.; CUNIBERTI, M.; BAINOTTI, C.; MIRANDA, M. Z. de; SCHEEREN, P. L.; JOBET, C.; PEÑA, R. J.; CABRERA, G.; VERGES, R. Genotype and environment effects on quality of 23 wheat genotypes cultivated in 20 Latin American environments. In: INTERNATIONAL WHEAT CONFERENCE, 8., 2010, St. Petersburg, RU. Abstracts...: wheat genetics and breeding for grain quality; oral presentations. St. Petersburg: VIR, 2010. p. 493-494.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 117. | | HELGUERA, M.; ABUGALIEVA, A.; BATTENFIELD, S.; BÉKÉS, F.; BRANLARD, G.; CUNIBERTI, M.; HÜSKEN,A.; JOHANSSON, E.; MORRIS, C.F.; NURIT, E.; SISSONS, M.; VÁZQUEZ, D. Grain Quality in Breeding. In: Igrejas G., Ikeda T., Guzmán C. (eds). Wheat Quality For Improving Processing And Human Health. Cham:Springer. Doi:
https://doi.org/10.1007/978-3-030-34163-3_12 p. 273-307. Article history:First Online: 18 March 2020.| Tipo: Capítulo en Libro Técnico-Científico |
| Biblioteca(s): INIA La Estanzuela. |
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| 118. | | VÁZQUEZ, D.; CUNIBERTI, M.; BAINOTTI, C.; MIRANDA, M. Z. DE; SCHEEREN, P. L.; JOBET, C.; CABRERA, G.; KOHLI, M. M.; VERGES, R.; PEÑA, R. J. Grain quality of latin american wheat cultivars: current development and future perspectives. In: CONFERENCIA LATINOAMERICANA CEREALES, 2., 2011, Santiago, Chile. "Key for cereal chain innovation": event guide. Santiago: ICC: Granotec, 2011. p. 100., 2011| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA La Estanzuela. |
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| 119. | | CARRASCO-LETELIER, L.; VÁZQUEZ, D.; RESQUÍN, F.; RACHID, C.; D´OTTONE, F.; TERRA, J.A.; SCOZ, R.; VILARO, F.; SALDIAS, R.; OTEGUI, O.; SOUTO, G. Evaluando la sostenibilidad energética de las agroenergías Revista INIA Uruguay, 2011, no. 27, p. 48-51 (Revista INIA; 27)| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA La Estanzuela; INIA Las Brujas; INIA Tacuarembó; INIA Treinta y Tres. |
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| 120. | | VÁZQUEZ, D.; BERGER, A.G.; CUNIBERTI , M.; BAINOTTI , C.; ZAVARIZ DE MIRANDA , M.; SCHEEREN , P.L.; JOBET, C.; ZÚÑIGA, J.; CABRERA, G.; VERGES, R.; PEÑA, R.J Influence of cultivar and environment on quality of Latin American wheats. Journal of cereal science , v. 56, n.2, p. 196-203, 2012. Article history: Received 15 August 2011 / Received in revised form / 20 March 2012 / Accepted 27 March 2012.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 1 |
| Biblioteca(s): INIA La Estanzuela. |
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| Registros recuperados : 124 | |
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