Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens D.P. (2018): Bayesian inference of genetic parameters for reproductive and performance traits in White Leghorn hens. Czech J. Anim. Sci., 63: 230-236.
download PDF

This study estimated the genetic parameters for reproductive and performance traits and determined which ones can be used as selection criteria for egg production in laying hens using the Bayesian inference. The data of 1894 animals from three generations of White Leghorn laying hens were analyzed for fertility (FERT), hatchability (HATC), and birth rate measurements at 60 weeks of age (BIRTH), body weight at 16 and 60 weeks of age (BW16 and BW60), age at sexual maturity (ASM), egg height/width ratio, weight, and density at 28, 36, and 40 weeks of age (RHW28, RHW36, RHW40, WEGG28, WEGG36, WEGG40, DENS28, DENS36, and DENS40, respectively) traits. The genetic parameters were estimated by the Bayesian inference method of multi-trait animal model. The model included the additive and residual genetic random effects and the fixed effects of generation. The a posteriori mean distributions of the heritability estimates for reproductive traits ranged from 0.14 ± 0.003 (HATC) to 0.22 ± 0.005 (FERT) and performance from 0.07 ± 0.001 (RHW28) to 0.42 ± 0.001 (WEGG40). The a posteriori mean distributions of the genetic correlation between reproductive traits ranged from 0.18 ± 0.026 (FERT and HACT) to 0.79 ± 0.007 (FERT and BIRTH) and those related to performance ranged from –0.49 ± 0.001 (WEGG36 and DENS36) to 0.75 ± 0.003 (DENS28 and DENS36). Reproductive and performance traits showed enough additive genetic variability to respond to selection, except for RHW28. This trait alone would have little impact on the genetic gain because environmental factors would have a higher impact compared to those from the additive genetic factors. Based on the results of this study, the selection applied on the BIRTH trait can be indicated to improve FERT and HATC of eggs. Furthermore, the use of the WEGG40 could improve egg quality in this population.

Abou Khadiga G., Mahmoud B. Y. F., El-Full E. A. (2016): Genetic evaluation of early egg production and maturation traits using two different approaches in Japanese quail. Poultry Science, 95, 774-779
Alsobayel A.A., Albadry M.A. (2012): Effect of age and sex ratio on fertility and hatchability of Baladi and Leghorn laying hens. Journal of Animal and Plant Sciences, 22, 15–19.
Falconer D., Mackay T. (eds) (1996): Introduction to Quantitative Genetics. Longmans Green, Harlow, UK.
Hanna Lauren L. Hulsman, Garrick Dorian J., Gill Clare A., Herring Andy D., Sanders James O., Riley David G. (2014): Comparison of breeding value prediction for two traits in a Nellore-Angus crossbred population using different Bayesian modeling methodologies. Genetics and Molecular Biology, 37, 631-637
Icken W., Thurner S., Heinrich A., Kaiser A., Cavero D., Wendl G., Fries R., Schmutz M., Preisinger R. (2013): Higher precision level at individual laying performance tests in noncage housing systems. Poultry Science, 92, 2276-2282
Jafarnejad A., Kamali M.A., Fatemi S.J., Aminafshar M. (2017): Genetic evaluation of laying traits in Iranian indigenous hens using univariate and bivariate animal models. Journal of Animal and Plant Sciences, 27, 2017–2020.
Jamrozik J., Koeck A., Kistemaker G.J., Miglior F. (2016): Multiple-trait estimates of genetic parameters for metabolic disease traits, fertility disorders, and their predictors in Canadian Holsteins. Journal of Dairy Science, 99, 1990-1998
Kjaer J.B. (2016): Divergent selection on home pen locomotor activity in a chicken model: selection program, genetic parameters and direct response on activity and body weight. PLoS ONE, 12, e0182103.
Misztal I. (2004): GIBBS2F90 Manual. Available at (accessed Sep 10, 2017).
Niknafs Shahram, Nejati-Javaremi Ardeshir, Mehrabani-Yeganeh Hassan, Fatemi Seyed Abolghasem (2012): Estimation of genetic parameters for body weight and egg production traits in Mazandaran native chicken. Tropical Animal Health and Production, 44, 1437-1443
Rajaravindra K.S., Rajkumar U., Rekha K., Niranjan M., Reddy B.L.N., Chatterjee R.N. (2014): Evaluation of egg quality traits in a synthetic coloured broiler female line. Journal of Applied Animal Research, 43, 10-14
Rozempolska-Rucińska I., Zięba G., Łukaszewicz M., Ciechońska M., Witkowski A., Ślaska B. (2011): Egg specific gravity in improvement of hatchabilityin laying hens. Journal of Animal and Feed Sciences, 20, 84-92
Rozempolska-Rucinska I., Zieba G., Lukaszewicz M. (2013): Heritability of individual egg hatching success versus hen hatchability in layers. Poultry Science, 92, 321-324
Shadparvar A.A., Enayati B. (2012): Genetic parameters for body weight and laying traits in Mazandaran native breeder hens. Iranian Journal of Applied Animal Research, 2, 251–256.
Silva Luciano P., Ribeiro Jeferson C., Crispim Aline C., Silva Felipe G., Bonafé Cristina M., Silva Fabyano F., Torres Robledo A. (2013): Genetic parameters of body weight and egg traits in meat-type quail. Livestock Science, 153, 27-32
Smith B.J. (2005): Bayesian Output Analysis Program (BOA) Version 1.1. User’s Manual. Available at (accessed Sep 9, 2017).
Tumova E., Gous R. M. (2012): Interaction of hen production type, age, and temperature on laying pattern and egg quality. Poultry Science, 91, 1269-1275
van de Schoot Rens, Broere Joris J., Perryck Koen H., Zondervan-Zwijnenburg Mariëlle, van Loey Nancy E. (2015): Analyzing small data sets using Bayesian estimation: the case of posttraumatic stress symptoms following mechanical ventilation in burn survivors. European Journal of Psychotraumatology, 6, 25216-
Venturini G.C., Grossi D.A., Ramos S.B., Cruz V.A.R., Souza C.G., Ledur M.C., El Faro L., Schmidt G.S., Munari D.P. (2012): Estimation of genetic parameters for partial egg production periods by means of random regression models. Genetics and Molecular Research, 11, 1819-1829
Venturini G. C., Savegnago R. P., Nunes B. N., Ledur M. C., Schmidt G. S., El Faro L., Munari D. P. (2013): Genetic parameters and principal component analysis for egg production from White Leghorn hens. Poultry Science, 92, 2283-2289
download PDF

© 2021 Czech Academy of Agricultural Sciences | Prohlášení o přístupnosti