Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes

ilustraciones

Autores:: Guevara Ruiz, Dylan Mauricio

Tipo de recurso:

Fecha de publicación:: 2023

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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dc.title.spa.fl_str_mv	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
dc.title.translated.eng.fl_str_mv	Analysis of parametric phenotypic stability in multiple environments for yield trials in Brachiaria (Brachiaria humidicola)
title	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
spellingShingle	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes 630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales Forraje Alimento para animales Forage Feeds Interacción genotipo por ambiente Selección Diseño de bloques aumentados Forrajes
title_short	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
title_full	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
title_fullStr	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
title_full_unstemmed	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
title_sort	Análisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientes
dc.creator.fl_str_mv	Guevara Ruiz, Dylan Mauricio
dc.contributor.advisor.none.fl_str_mv	Rodríguez Molano, Luis Ernesto
dc.contributor.author.none.fl_str_mv	Guevara Ruiz, Dylan Mauricio
dc.contributor.other.none.fl_str_mv	Darghan Contreras, Aquiles Enrique
dc.subject.ddc.spa.fl_str_mv	630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales
topic	630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materiales Forraje Alimento para animales Forage Feeds Interacción genotipo por ambiente Selección Diseño de bloques aumentados Forrajes
dc.subject.lemb.spa.fl_str_mv	Forraje Alimento para animales
dc.subject.lemb.eng.fl_str_mv	Forage Feeds
dc.subject.proposal.spa.fl_str_mv	Interacción genotipo por ambiente Selección Diseño de bloques aumentados Forrajes
description	ilustraciones
publishDate	2023
dc.date.accessioned.none.fl_str_mv	2023-01-30T21:57:46Z
dc.date.available.none.fl_str_mv	2023-01-30T21:57:46Z
dc.date.issued.none.fl_str_mv	2023-01-30
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
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identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
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dc.relation.references.spa.fl_str_mv	Annicchiarico, P. (1992). Cultivar adaptation and recommendation from alfalfa trials in northern Italy. J. Genet. Breed., 46: 269-278. J. Genet. & Breed, 46(November), 269–296. https://www.researchgate.net/profile/Paolo_Annicchiarico/publication/292006732_Cultivar_adaptation_and_recommendation_from_alfalfa_trials_in_Northern_Italy/links/58382a1608aed5c614880f4c/Cultivar-adaptation-and-recommendation-from-alfalfa-trials-in-Northe Becker, H. C., & Léon, J. (1988). Stability Analysis in Plant Breeding. Plant Breeding, 101(1), 1–23. https://doi.org/10.1111/j.1439-0523.1988.tb00261.x Catchpole, W. R., & Wheelert, C. J. (1992). Review Estimating plant biomass: A review of techniques. In Australian Journal of Ecology {\992) (Vol. 17). CGIAR. (2018). Tropical Forages and the DiFusion of Brachiaria Cultivars in Latin America (Issue 70). https://cas.cgiar.org/sites/default/files/pdf/ispc_brief_70_brachiaria.pdf Cubero, J., & Flores, F. (2003). Métodos estadísticos para el estudio de la estabilidad varietal en ensayos agrícolas. In Junta de Andalucía (2nd ed., Issue 2). https://doi.org/10.5281/zenodo.1477753 Eberhart, S. A., & Russell, W. A. (1966). Stability Parameters for Comparing Varieties. Crop Science, 6(1), 36–40. https://doi.org/10.2135/cropsci1966.0011183x000600010011x Falconer, D., & Mackay, D. (1996). Introduction to Quantitative Genetic (Cuarta). Fasahat, P. (2015). An Overview on the Use of Stability Parameters in Plant Breeding. Biometrics & Biostatistics International Journal, 2(5). https://doi.org/10.15406/bbij.2015.02.00043 Federer, W. (1956). Augmented (or Hoonuiaku) design. Cornell University, 1–33. https://ecommons.cornell.edu/handle/1813/32841 Ferraudo, G. M., & Perecin, D. (2014). Mixed Model, AMMI and Eberhart-Russel Comparison via Simulation on Genotype × Environment Interaction Study in Sugarcane. Applied Mathematics, 05(14), 2107–2119. https://doi.org/10.4236/am.2014.514205 Finlay, K. W., & Wilkinson, G. N. (1963). THE ANALYSIS OF ADAPTATION IN A PLANT-BREEDING PROGRAMME. Australian Journal of Agricultural Research, 14(1958), 742–754. Flores, F., Moreno, M. T., & Cubero, J. I. (1998). A comparison of univariate and multivariate methods to analyze genotype by environment interaction. Field Crops Research, 56, 271–286. Fox, P. N., Skovmand, B., Thompson, B. K., Braun, H. J., & Cormier, R. (1990). Yield and adaptation of hexaploid spring triticale. Euphytica, 47(1), 57–64. https://doi.org/10.1007/BF00040364 Francis, T., & Kannenberg, L. (1978). YIELD STABILITY STUDIES IN SHORT-SEASON MAIZE. I. A DESCRIPTIVE METHOD FOR GROUPING GENOTYPES. Can. J. Plant Sci., 58, 1029–1034. Gauch, H. G. (1988). Model Selection and Validation for Yield Trials with Interaction (Vol. 44, Issue 3). Gauch, H. G., & Zobei, R. W. (1988). Predictive and postdictive success of statistical analyses of yield trials*. Theor Appl Genet. Henderson, C. (1975). Best Linear Unbiased Estimation and Prediction under a Selection Model (Vol. 31, Issue 2). Jarquín, D., Lemes da Silva, C., Gaynor, R. C., Poland, J., Fritz, A., Howard, R., Battenfield, S., & Crossa, J. (2017). Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat. The Plant Genome, 10(2). https://doi.org/10.3835/plantgenome2016.12.0130 Kang, M. (1988). rank–sum method for selectig high-yielding, stable corn genotypes. Cereal Res, 16(1), 113–115. Lin, C. S., & Binns, M. R. (1988). A Superiority Measure of Cultivar Performance for Cultivar × Location Data. Canadian Journal of Plant Science, 68(1), 193–198. https://doi.org/10.4141/cjps88-018 Miles, J. W. (2007). Apomixis for cultivar development in tropical forage grasses. Crop Science, 47(SUPPL. DEC.). https://doi.org/10.2135/cropsci2007.04.0016IPBS Miles, J. W., do Valle, C. B., Rao, I. M., & Euclides, V. P. B. (2004). Brachiaria grasses. In L. Sollenberger, L. Moser, & B. Burson (Eds.), Warm-season grasses (1st ed., Issue 45, pp. 745–783). https://doi.org/10.2134/agronmonogr45.c22 Oliveira, E., Freitas, J., & Jesus, O. (2013). AMMI analysis of yellow passion fruit Scientia Agricola. Scientia Agricola, 71(2), 139–145. Olivoto, T., Lúcio, A. D. C., da Silva, J. A. G., Marchioro, V. S., de Souza, V. Q., & Jost, E. (2019). Mean performance and stability in multi-environment trials i: Combining features of AMMI and BLUP techniques. Agronomy Journal, 111(6), 2949–2960. https://doi.org/10.2134/agronj2019.03.0220 Piepho, H. P. (1994). Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis. Theoretical and Applied Genetics, 89(5), 647–654. https://doi.org/10.1007/BF00222462 Purchase, J. L., Hatting, H., & van Deventer, C. S. (2000). Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African Journal of Plant and Soil, 17(3), 101–107. https://doi.org/10.1080/02571862.2000.10634878 Sa’diyah, H., & Hadi, A. F. (2016). AMMI Model for Yield Estimation in Multi-Environment Trials: A Comparison to BLUP. Agriculture and Agricultural Science Procedia, 9, 163–169. https://doi.org/10.1016/j.aaspro.2016.02.113 Shukla, G. K. (1972). Some statistical aspects of partitioning genotype-environmental components of variability. Heredity, 29(2), 237–245. https://doi.org/10.1038/hdy.1972.87 Tai, G. C. C. (1971). Genotypic Stability Analysis and Its Application to Potato Regional Trials. Crop Science, 11(2), 184–190. https://doi.org/10.2135/cropsci1971.0011183x001100020006x van Eeuwijk, F. A. (2006). Plant Breeding: The Arnel R. Hallauer International Symposium. In Plant Breeding: The Arnel R. Hallauer International Symposium (1st ed., pp. 155–170). Blackwell Publishing. https://doi.org/10.1002/9780470752708 van Eeuwijk, F. A., Bustos-Korts, D. v., & Malosetti, M. (2016). What should students in plant breeding know about the statistical aspects of genotype × Environment interactions? Crop Science, 56(5), 2119–2140. https://doi.org/10.2135/cropsci2015.06.0375 Yaseen, M., Eskridge, K., & Murtaza, G. (2018). Package ‘stability.’ CRAN, 1(1), 1–22. https://doi.org/10.2135/cropsci1966.0011183x000600010011x
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dc.format.extent.spa.fl_str_mv	xvi, 34 páginas
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ciencias Agrarias - Maestría en Ciencias Agrarias
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ciencias Agrarias
dc.publisher.place.spa.fl_str_mv	Bogotá - Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
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spelling	Atribución-NoComercial-CompartirIgual 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-sa/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Rodríguez Molano, Luis Ernesto31367cf7e0e2a380de113594da90c09fGuevara Ruiz, Dylan Mauricio24bb3f6dc69c35253a0ccab1a1bb6f0aDarghan Contreras, Aquiles Enrique2023-01-30T21:57:46Z2023-01-30T21:57:46Z2023-01-30https://repositorio.unal.edu.co/handle/unal/83197Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustracionesBrachiaria (Brachiaria humidicola) es una especie de amplia adopción como forraje para la alimentación bovina adaptada a amplias zonas tropicales y subtropicales de Sudamérica, África y Asia. El programa de mejoramiento genético de brachiaria, que adelanta el Centro internacional de Agricultura Tropical (CIAT) en Colombia, busca seleccionar híbridos estables de alto rendimiento para suelos ácidos. Sin embargo, la interacción genotipo por ambiente (IGA) dificulta la selección y estabilidad fenotípica, sin embargo, no existe un consenso común sobre la definición de estabilidad ni como estimarla. Para el análisis de estabilidad se han utilizado desde métodos univariados hasta modelos multivariados, donde existe una tendencia actual por el uso de modelos lineales multivariados. El objetivo de esta investigación fue comparar la precisión en la estimación de la IGA mediante modelos univariados, el modelo de efectos principales aditivos e interacción multiplicativa de efectos fijos (AMMI) y el modelo best linear unbiased prediction (BLUP). Se encontró que los métodos explicaron la estabilidad de diferentes formas, algunos se relacionan más con el concepto biológico de la estabilidad, mientras que otros explican el concepto agronómico de la estabilidad. El modelo BLUP tuvo mayor precisión predictiva que el modelo AMMI. Por lo tanto, se recomienda el uso del modelo BLUP para la selección de híbridos de brachiaria, aunque, la selección de híbridos estables de brachiaria dependerá del concepto de estabilidad que están alineados con los objetivos de mejoramiento. (Texto tomado de la fuente)Brachiaria (Brachiaria humidicola) is a widely adopted specie as forage for cattle feed in Latin America. The brachiaria breeding program seeks to select high-yielding hybrids for acid soils. However, the genotype by environment (IGA) interaction makes it difficult to select superior hybrids. The IGA is related to stability. However, there is no common consensus on the definition of stability or how to estimate it. For the stability analysis, from univariate methods to multivariate models have been used, where there is a current trend for the use of multivariate linear models. The objective of this research was to evaluate univariate models, the model of additive main effects and multiplicative interaction (AMMI) and the model BLUP. It was found that the methods explained stability in different ways, some are more related to the biological concept of stability, while others explain the agronomic concept of stability. The model BLUP had a higher predictive accuracy than AMMI model. Therefore, model BLUP is recommended for selection of brachiaria hybrids, although also it is recommended that the selection of stable brachiaria hybrids be carried out in accordance with the objectives of the breeding program and stability concepts.MaestríaGenética y Fitomejoramientoxvi, 34 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ciencias Agrarias - Maestría en Ciencias AgrariasFacultad de Ciencias AgrariasBogotá - ColombiaUniversidad Nacional de Colombia - Sede Bogotá630 - Agricultura y tecnologías relacionadas::631 - Técnicas específicas, aparatos, equipos, materialesForrajeAlimento para animalesForageFeedsInteracción genotipo por ambienteSelecciónDiseño de bloques aumentadosForrajesAnálisis de estabilidad fenotípica paramétrica de híbridos apomícticos de Brachiaria (Brachiaria humidicola) en múltiples ambientesAnalysis of parametric phenotypic stability in multiple environments for yield trials in Brachiaria (Brachiaria humidicola)Trabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAnnicchiarico, P. (1992). Cultivar adaptation and recommendation from alfalfa trials in northern Italy. J. Genet. Breed., 46: 269-278. J. Genet. & Breed, 46(November), 269–296. https://www.researchgate.net/profile/Paolo_Annicchiarico/publication/292006732_Cultivar_adaptation_and_recommendation_from_alfalfa_trials_in_Northern_Italy/links/58382a1608aed5c614880f4c/Cultivar-adaptation-and-recommendation-from-alfalfa-trials-in-NortheBecker, H. C., & Léon, J. (1988). Stability Analysis in Plant Breeding. Plant Breeding, 101(1), 1–23. https://doi.org/10.1111/j.1439-0523.1988.tb00261.xCatchpole, W. R., & Wheelert, C. J. (1992). Review Estimating plant biomass: A review of techniques. In Australian Journal of Ecology {\992) (Vol. 17).CGIAR. (2018). Tropical Forages and the DiFusion of Brachiaria Cultivars in Latin America (Issue 70). https://cas.cgiar.org/sites/default/files/pdf/ispc_brief_70_brachiaria.pdfCubero, J., & Flores, F. (2003). Métodos estadísticos para el estudio de la estabilidad varietal en ensayos agrícolas. In Junta de Andalucía (2nd ed., Issue 2). https://doi.org/10.5281/zenodo.1477753Eberhart, S. A., & Russell, W. A. (1966). Stability Parameters for Comparing Varieties. Crop Science, 6(1), 36–40. https://doi.org/10.2135/cropsci1966.0011183x000600010011xFalconer, D., & Mackay, D. (1996). Introduction to Quantitative Genetic (Cuarta).Fasahat, P. (2015). An Overview on the Use of Stability Parameters in Plant Breeding. Biometrics & Biostatistics International Journal, 2(5). https://doi.org/10.15406/bbij.2015.02.00043Federer, W. (1956). Augmented (or Hoonuiaku) design. Cornell University, 1–33. https://ecommons.cornell.edu/handle/1813/32841Ferraudo, G. M., & Perecin, D. (2014). Mixed Model, AMMI and Eberhart-Russel Comparison via Simulation on Genotype × Environment Interaction Study in Sugarcane. Applied Mathematics, 05(14), 2107–2119. https://doi.org/10.4236/am.2014.514205Finlay, K. W., & Wilkinson, G. N. (1963). THE ANALYSIS OF ADAPTATION IN A PLANT-BREEDING PROGRAMME. Australian Journal of Agricultural Research, 14(1958), 742–754.Flores, F., Moreno, M. T., & Cubero, J. I. (1998). A comparison of univariate and multivariate methods to analyze genotype by environment interaction. Field Crops Research, 56, 271–286.Fox, P. N., Skovmand, B., Thompson, B. K., Braun, H. J., & Cormier, R. (1990). Yield and adaptation of hexaploid spring triticale. Euphytica, 47(1), 57–64. https://doi.org/10.1007/BF00040364Francis, T., & Kannenberg, L. (1978). YIELD STABILITY STUDIES IN SHORT-SEASON MAIZE. I. A DESCRIPTIVE METHOD FOR GROUPING GENOTYPES. Can. J. Plant Sci., 58, 1029–1034.Gauch, H. G. (1988). Model Selection and Validation for Yield Trials with Interaction (Vol. 44, Issue 3).Gauch, H. G., & Zobei, R. W. (1988). Predictive and postdictive success of statistical analyses of yield trials*. Theor Appl Genet.Henderson, C. (1975). Best Linear Unbiased Estimation and Prediction under a Selection Model (Vol. 31, Issue 2).Jarquín, D., Lemes da Silva, C., Gaynor, R. C., Poland, J., Fritz, A., Howard, R., Battenfield, S., & Crossa, J. (2017). Increasing Genomic‐Enabled Prediction Accuracy by Modeling Genotype × Environment Interactions in Kansas Wheat. The Plant Genome, 10(2). https://doi.org/10.3835/plantgenome2016.12.0130Kang, M. (1988). rank–sum method for selectig high-yielding, stable corn genotypes. Cereal Res, 16(1), 113–115.Lin, C. S., & Binns, M. R. (1988). A Superiority Measure of Cultivar Performance for Cultivar × Location Data. Canadian Journal of Plant Science, 68(1), 193–198. https://doi.org/10.4141/cjps88-018Miles, J. W. (2007). Apomixis for cultivar development in tropical forage grasses. Crop Science, 47(SUPPL. DEC.). https://doi.org/10.2135/cropsci2007.04.0016IPBSMiles, J. W., do Valle, C. B., Rao, I. M., & Euclides, V. P. B. (2004). Brachiaria grasses. In L. Sollenberger, L. Moser, & B. Burson (Eds.), Warm-season grasses (1st ed., Issue 45, pp. 745–783). https://doi.org/10.2134/agronmonogr45.c22Oliveira, E., Freitas, J., & Jesus, O. (2013). AMMI analysis of yellow passion fruit Scientia Agricola. Scientia Agricola, 71(2), 139–145.Olivoto, T., Lúcio, A. D. C., da Silva, J. A. G., Marchioro, V. S., de Souza, V. Q., & Jost, E. (2019). Mean performance and stability in multi-environment trials i: Combining features of AMMI and BLUP techniques. Agronomy Journal, 111(6), 2949–2960. https://doi.org/10.2134/agronj2019.03.0220Piepho, H. P. (1994). Best Linear Unbiased Prediction (BLUP) for regional yield trials: a comparison to additive main effects and multiplicative interaction (AMMI) analysis. Theoretical and Applied Genetics, 89(5), 647–654. https://doi.org/10.1007/BF00222462Purchase, J. L., Hatting, H., & van Deventer, C. S. (2000). Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African Journal of Plant and Soil, 17(3), 101–107. https://doi.org/10.1080/02571862.2000.10634878Sa’diyah, H., & Hadi, A. F. (2016). AMMI Model for Yield Estimation in Multi-Environment Trials: A Comparison to BLUP. Agriculture and Agricultural Science Procedia, 9, 163–169. https://doi.org/10.1016/j.aaspro.2016.02.113Shukla, G. K. (1972). Some statistical aspects of partitioning genotype-environmental components of variability. Heredity, 29(2), 237–245. https://doi.org/10.1038/hdy.1972.87Tai, G. C. C. (1971). Genotypic Stability Analysis and Its Application to Potato Regional Trials. Crop Science, 11(2), 184–190. https://doi.org/10.2135/cropsci1971.0011183x001100020006xvan Eeuwijk, F. A. (2006). Plant Breeding: The Arnel R. Hallauer International Symposium. In Plant Breeding: The Arnel R. Hallauer International Symposium (1st ed., pp. 155–170). Blackwell Publishing. https://doi.org/10.1002/9780470752708van Eeuwijk, F. A., Bustos-Korts, D. v., & Malosetti, M. (2016). What should students in plant breeding know about the statistical aspects of genotype × Environment interactions? Crop Science, 56(5), 2119–2140. https://doi.org/10.2135/cropsci2015.06.0375Yaseen, M., Eskridge, K., & Murtaza, G. (2018). Package ‘stability.’ CRAN, 1(1), 1–22. https://doi.org/10.2135/cropsci1966.0011183x000600010011xEstudiantesInvestigadoresMaestrosPúblico generalLICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/83197/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL1018480868.2022.pdf1018480868.2022.pdfTesis de Maestría en Ciencias Agrariasapplication/pdf1228700https://repositorio.unal.edu.co/bitstream/unal/83197/2/1018480868.2022.pdfb193de24871a221f1b1f02cd835e22a7MD52THUMBNAIL1018480868.2022.pdf.jpg1018480868.2022.pdf.jpgGenerated Thumbnailimage/jpeg4821https://repositorio.unal.edu.co/bitstream/unal/83197/3/1018480868.2022.pdf.jpga465239800abc3d8f22eaeae16a47151MD53unal/83197oai:repositorio.unal.edu.co:unal/831972023-08-14 23:04:46.86Repositorio Institucional Universidad Nacional de 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