EL ANÁLISIS BAYESIANO Y LA PRECISIÓN DE LOS VALORES DE LA HEREDABILIDAD EN ESPECIES PERENNES

Mora, Freddy; Scapim, Carlos Alberto; Pinto, Ronald José Barth

doi:10.5902/19805098890

RESUMEN

Los objetivos del presente trabajo fueron evaluar la precisión del valor estimado de la heredabilidad determinada por medio de la desviación estándar, considerando un enfoque Bayesiano, y comparar tal estimativa con el procedimiento clásico. Se utilizaron datos de un ensayo de progenie con 39 familias de Eucalyptus cladocalyx. La variable dependiente usada fue el diámetro basal del fuste medido a los seis años de edad. El método Bayesiano fue implementado por medio del algoritmo de Cadenas Independientes, con informaciones a priori informativas, el cual entregó bajos valores de desviaciones estándar de la heredabilidad, si comparado con la estimación clásica de Robertson y distribución a priori de Jeffreys (la cual es una clase de distribución a priori no informativa y a menudo impropia). El método de análisis Bayesiano es una herramienta de inferencia valiosa para la evaluación genética de especies perennes, ya que considera la variabilidad de los parámetros por medio de las distribuciones a posteriori.

Palabras-clave:
inferencia Bayesiana; algoritmo de cadenas independientes; Eucalyptus; heredabilidad

ABSTRACT

The objectives of the present work were to evaluate the precision of the estimate of heritability, which was determined by standard error, considering a Bayesian approach, and to compare such estimate with the classic procedure. Data from progeny trial of 39 Eucalyptus cladocalyx families were used. Trunk basal diameter (measured at age 6) was the dependent variable analyzed. The Bayesian approach was implemented by using the Independence Chain algorithm with informative priors, which had a lower standard deviation of the heritability than both the classic method of Robertson and Jeffreys’ prior distribution (Jeffreys’ prior is in fact a class of uninformative and often improper prior distributions). The Bayesian approach is a valuable inference tool for the genetic evaluation of perennial species, because it considers the variability of the parameters by using posterior distributions.

Keywords:
Bayesian inference; independence chain algorithm; Eucalyptus; heritability

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REFERENCIAS BIBLIOGRÁFICAS

ARNHOLD, E. et al. Evaluation of top-cross popcorn hybrids using mixed linear model methodology. Chilean Journal of Agriculture Research, Santiago, v. 69, n. 1, p. 46-53, 2009.
BLASCO, A. The Bayesian controversy in animal breeding. Journal of Animal Science, Champaign, v. 79, n. 8, p. 2023-2046, 2001.
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DE PAULA, M. C. Heterogeneidade de variâncias e interação genótipo x ambiente para produção de leite em bovinos da raça holandesa no estado do Paraná. 2006. 84f. Tese (Doutorado em Zootecnia) - Universidade Estadual de Maringá, 2006.
EFRON, B. Bootstrap methods: another look at the jackknife. The Annals of Statistics, Beachwood, v. 7, n. 1, p. 1-26, 1979.
GIANOLA, D.; FERNANDO, R. L. Bayesian methods in animal breeding theory. Journal of Animal Science , Champaign, v. 63, n. 1, p. 217-277, 1986.
GONÇALVES-VIDIGAL, M. C. et al. Heritability of quantitative traits in segregating common bean families using a Bayesian approach. Euphytica, Wageningen, v. 164, n. 2, p. 551-560, 2008.
MORA, F. Heredabilidad y valor genético (REML/BLUP) en genotipos de un eucalipto tolerante a la sequía, en el norte de Chile. Ciência Florestal, Santa Maria, v. 16, n. 2, p. 145-151, 2006.
MORA, F.; PERRET, S. Aplicación de técnicas bayesianas en el análisis genético de árboles forestales. Bosque, Valdivia, v. 28, n. 3, p. 198-206, 2007.
MORA, F. et al. Source-dependent blooming variability of Eucalyptus cladocalyx in the Region of Coquimbo, Chile. Ciencia e Investigación Agraria, Santiago, v. 34, n. 2, p. 99-106, 2007.
MORA, F. et al. Bayesian analysis of the genetic control of survival in F3 families of common bean. Chilean Journal of Agriculture Research , Chillán, v. 68, n. 4, p. 334-341, 2008a.
MORA, F. et al. Genetic evaluation of olive clones in the Atacama desert, Chile. Agrociencia, Montecillo, v. 42, n. 7, p. 777-786, 2008b.
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» http://www.springerlink.com/content/d78x173425v37338/fulltext.html
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Fechas de Publicación

Publicación en esta colección
Oct-Dec 2009

Este es un artículo publicado en acceso abierto bajo una licencia Creative Commons

[1] ARNHOLD, E. et al. Evaluation of top-cross popcorn hybrids using mixed linear model methodology. Chilean Journal of Agriculture Research, Santiago, v. 69, n. 1, p. 46-53, 2009.

[2] BLASCO, A. The Bayesian controversy in animal breeding. Journal of Animal Science, Champaign, v. 79, n. 8, p. 2023-2046, 2001.

[3] CAPPA, E. P.; CANTET, R. J. C. Bayesian inference for normal multiple-trait individual-tree models with missing records via full conjugate Gibbs. Canadian Journal of Forest Research, Ottawa, v. 36, n. 5, p. 1276-1285, 2006.

[4] DE PAULA, M. C. Heterogeneidade de variâncias e interação genótipo x ambiente para produção de leite em bovinos da raça holandesa no estado do Paraná. 2006. 84f. Tese (Doutorado em Zootecnia) - Universidade Estadual de Maringá, 2006.

[5] EFRON, B. Bootstrap methods: another look at the jackknife. The Annals of Statistics, Beachwood, v. 7, n. 1, p. 1-26, 1979.

[6] GIANOLA, D.; FERNANDO, R. L. Bayesian methods in animal breeding theory. Journal of Animal Science , Champaign, v. 63, n. 1, p. 217-277, 1986.

[7] GONÇALVES-VIDIGAL, M. C. et al. Heritability of quantitative traits in segregating common bean families using a Bayesian approach. Euphytica, Wageningen, v. 164, n. 2, p. 551-560, 2008.

[8] MORA, F. Heredabilidad y valor genético (REML/BLUP) en genotipos de un eucalipto tolerante a la sequía, en el norte de Chile. Ciência Florestal, Santa Maria, v. 16, n. 2, p. 145-151, 2006.

[9] MORA, F.; PERRET, S. Aplicación de técnicas bayesianas en el análisis genético de árboles forestales. Bosque, Valdivia, v. 28, n. 3, p. 198-206, 2007.

[10] MORA, F. et al. Source-dependent blooming variability of Eucalyptus cladocalyx in the Region of Coquimbo, Chile. Ciencia e Investigación Agraria, Santiago, v. 34, n. 2, p. 99-106, 2007.

[11] MORA, F. et al. Bayesian analysis of the genetic control of survival in F3 families of common bean. Chilean Journal of Agriculture Research , Chillán, v. 68, n. 4, p. 334-341, 2008a.

[12] MORA, F. et al. Genetic evaluation of olive clones in the Atacama desert, Chile. Agrociencia, Montecillo, v. 42, n. 7, p. 777-786, 2008b.

[13] MORA, F. et al. Genetic variation for early flowering, survival and growth in sugar gum (Eucalyptus cladocalyx F. Muell) in southern Atacama Desert. Euphytica , Wageningen. v. 169, n. 3, 2009. Disponível em: <Disponível em: http://www.springerlink.com/content/d78x173425v37338/fulltext.html > Acesso em: 08 de julho de 2009.
» http://www.springerlink.com/content/d78x173425v37338/fulltext.html

[14] MORRIS, J. S. The BLUPs are not “best” when it comes to bootstrapping. Statistics and Probability Letters, Madison, v. 56, n. 4, p. 425-430, 2002.

[15] NOGUEIRA, D. A. et al. Análises clássica e Bayesiana de um modelo misto aplicado ao melhoramento animal: uma ilustração. Ciência e Agrotecnologia, Lavras, v. 27, n. especial, p. 1614-1624, 2003.

[16] RESENDE, M. D. V. Genética biométrica e estatística no melhoramento de plantas perenes. Brasília, Brasil: Embrapa Informação Tecnológica, 2002. 975 p.

[17] RESENDE, M. D. V. et al. Efeito do tamanho amostral na estimativa da herdabilidade em espécies perenes. Revista Floresta, Curitiba, v. 28, n. 1-2, p. 51-63, 1998.

[18] ROBERTSON, A. Experimental design in the evaluation of genetic parameters. Biometrics, Raleigh, v. 15, n. 2, p.219-226, 1959.

[19] RODOVALHO, M. A. et al. Survival heritability in 169 families of white grain popcorn: a Bayesian approach. Ciencia e Investigación Agraria , Santiago, v. 35, n. 3, p. 255-260, 2008.

[20] SAS-INSTITUTE. Statistical analysis system. User’s guide. USA: SAS Institute, 1996. 956p.

[21] TIERNEY, L. Markov chains for exploring posterior distributions (with discussion). Annals of Statistics, v. 23, n. 4, p.1701-1762, 1994.

[22] WOLFINGER, R. D.; KASS, R. E. Non-conjugate Bayesian analysis of variance component models. Biometrics , Beachwood, v. 56, n. 3, p. 768-774, 2000.

[23] WRIGHT, D. R.; STERN, H. S.; BERGER, P. J. Comparing traditional and Bayesian analyses of selection experiments in animal breeding. Journal of Agricultural, Biological, and Environmental Statistics, Alexandria, v. 5, n. 2, p. 240-256, 2000.

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