全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Heritability and Genetic Correlation of Niamey’s Local Chicken Growth (Niger)

DOI: 10.4236/ojgen.2022.124006, PP. 57-68

Keywords: Bayesian, Genetic Correlations, Heritability, Local Chicken, MCMCglmm, Weight Gain, Niger

Full-Text   Cite this paper   Add to My Lib

Abstract:

The exploitation of industrial strains of chickens in the Sahelian climate of Niger is characterized by a decline in performance and significant costs associated with their maintenance. In contrast, local chickens are well adapted to these environmental conditions but with poor production performance. Genetic selection of these local chickens could improve their productivity. The first step is to determine if the genetic parameters of their growth are high enough to ensure a successful selection strategy. To do so, weekly weights of 69 parents and 119 offspring were followed for 20 weeks. The heritability and genetic correlations of these weights were estimated through the Bayesian approach using the MCMCglmm package on R software. At hatching, weights ranged from 23 to 25 g. At 20 weeks, these weights ranged from 1031 to 1052 g for females and 1308 to 1445 g for males. Heritabilities for hatch weights at 4, 8, 12, 16, and 20 weeks of age were estimated to be 0.56, 0.31, 0.52, 0.53, 0.52 and 0.48 respectively and all genetic correlations were positive. In particular, weight at 8 weeks of age showed both good heritability (h2 = 0.52) and strong, positive genetic correlations with weights at older ages. These results indicate that genetic selection to improve weight at 8 weeks of age would be a good strategy to improve the overall growth performance of these chickens.

References

[1]  Assoumane, I. and Ousseini, G.I. (2009) Revue du secteur avicole du Niger. FAO, division de la production et de la santé animale, Niger, 69.
http://www.fao.org/3/ak770f/ak770f00.pdf
[2]  Ousseini, M.H., Keambou Tiambo, C., Hima, K., Issa, S., Joseline, M.S. and Bakasso, Y. (2018) Indigenous Chicken Production in Niger. Veterinary and Animal Science, 7, Article No. 100040.
https://doi.org/10.1016/j.vas.2018.11.001
[3]  Guisso Taffa, A., Moula, N., Issa, S., Mahamadou, C. and Detilleux, J. (2022) Phenotypic Characterization of Local Chickens in West Africa: Systematic Review. Poultry, 1, 207-219.
https://doi.org/10.3390/poultry1040018
[4]  Manyelo, T.G., Selaledi, L., Hassan, Z.M. and Mabelebele, M. (2020) Local Chicken Breeds of Africa: Their Description, Uses and Conservation Methods. Animals, 10, 2257.
https://doi.org/10.3390/ani10122257
[5]  Ranjan, A., Sinha, R., Devi, I., Rahim, A. and Tiwari, S. (2019) Effect of Heat Stress on Poultry Production and Their Managemental Approaches. International Journal of Current Microbiology and Applied Sciences, 8, 1548-1555.
https://doi.org/10.20546/ijcmas.2019.802.181
[6]  Sohail, M.U., Hume, M.E., Byrd, J.A., Nisbet, D.J., Ijaz, A., Sohail, A., et al. (2012) Effect of Supplementation of Prebiotic Mannan-Oligosaccharides and Probiotic Mixture on Growth Performance of Broilers Subjected to Chronic Heat Stress. Poultry Science, 91, 2235-2240.
https://doi.org/10.3382/ps.2012-02182
[7]  Geraert, P.A. (1991) Métabolisme énergétique du poulet de chair en climat chaud. INRAE Productions Animales, 4, 257-267.
https://doi.org/10.20870/productions-animales.1991.4.3.4340
[8]  Lara, L.J. and Rostagno, M.H. (2013) Impact of Heat Stress on Poultry Production. Animals, 3, 356-369.
https://doi.org/10.3390/ani3020356
[9]  Hamani, B., Moula, N., Guisso Taffa, A., Leyo, I.H., Mahamadou, C., Detilleux, J., et al. (2022) Effect of Housefly (Musca domestica) Larvae on the Growth Performance and Carcass Characteristics of Local Chickens in Niger. Veterinary World, 15, 1738-1748.
https://doi.org/10.14202/vetworld.2022.1738-1748
[10]  Ducrocq, V. (1992) Les bases de la génétique quantitative: Du modèle génétique au modèle statistique. INRAE Productions Animales, 5, 75-78.
https://doi.org/10.20870/productions-animales.1992.5.HS.4266
[11]  Beaumont, C. and Chapuis, H. (2004) Génétique et sélection avicoles: évolution des méthodes et des caractères. INRAE Productions Animales, 17, 35.
https://hal.inrae.fr/hal-02682906
https://doi.org/10.20870/productions-animales.2004.17.1.3551
[12]  Marchand, P. (2019) Introduction à l’analyse bayésienne.
https://pmarchand1.github.io/ECL8202/notes_cours/08-Intro_Bayes.html
[13]  Tolonen, V.H. & T. Bayesian Inference.
https://vioshyvo.github.io/Bayesian_inference/index.html
[14]  Wiener, G. and Rouvier, R. (2009) L’amélioration génétique animale. éditions Quae.
https://doi.org/10.35690/978-2-7592-0371-0
[15]  Robert, C.P. (2006) Le choix bayésien: Principes et pratique. Springer, Paris.
[16]  Gelman, A., Vehtari, A., Simpson, D., Margossian, C.C., Carpenter, B., Yao, Y., et al. (2020) Bayesian Workflow.
[17]  Zhang, Z. (2021) A Note on Wishart and Inverse Wishart Priors for Covariance Matrix. Journal of Behavioral Data Science, 1, 2.
https://doi.org/10.35566/jbds/v1n2/p2
[18]  Honkela, A. (2020) Chapter 8 MCMC Diagnostics and Sampling Multimodal Distributions. Computational Statistics I.
https://www.cs.helsinki.fi/u/ahonkela/teaching/compstats1/book/mcmc-diagnostics-and-sampling-multimodal-distributions.html
[19]  RCore, T. (2022) R: A Language and Environment for Statistical Computing. CRAN, Vienna.
https://www.r-project.org
[20]  RStudio, T. (2022) RStudio: Integrated Development for R. RStudio, Boston.
http://www.rstudio.com
[21]  Hadfield, J.D. (2010) MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package. Journal of Statistical Software, 33, 1-22.
https://doi.org/10.18637/jss.v033.i02
[22]  Villemereuil, P.D. (2021) Estimation of a Biological Trait Heritability Using the Animal Model and MCMCglmm (Version 2).
https://devillemereuil.legtux.org/wp-content/uploads/2021/09/tuto_en.pdf
[23]  Hadfield, J.D. (2015) MCMCglmm Course Notes.
http://ftp.zut.edu.pl/dsk0/CRAN/web/packages/MCMCglmm/vignettes/CourseNotes.pdf
[24]  Bungsrisawat, P., Tumwasorn, S., Loongyai, W., Nakthong, S. and Sopannarath, P. (2018) Genetic Parameters of Some Carcass and Meat Quality Traits in Betong Chicken (KU Line). Agriculture and Natural Resources, 52, 274-279.
https://doi.org/10.1016/j.anres.2018.09.010
[25]  Hermiz, H.N. and Abdullah, M.S. (2020) Genetic and Non-Genetic Parameters for Body Weights of Two Iraqi Local Chickens. The Iraqi Journal of Agricultural Sciences, 51, 323-332.
https://doi.org/10.36103/ijas.v51i1.931
[26]  El-Attrouny, M.M., Iraqi, M.M. and Sh, A.-H.M. (2021) The Estimation of Genetic Parameters for Body Weight, Body Dimension, and Carcass Traits in Four Egyptian Chickens Strains. The Journal of World’s Poultry Research, 11, 230-240.
https://doi.org/10.36380/jwpr.2021.28
[27]  Dana, N., vander Waaij, E.H. and van Arendonk, J.A.M. (2011) Genetic and Phenotypic Parameter Estimates for Body Weights and Egg Production in Horro Chicken of Ethiopia. Tropical Animal Health and Production, 43, 21-28.
https://doi.org/10.1007/s11250-010-9649-4
[28]  Sanda, A.J., Olowofeso, O., Adeleke, M.A., Oso, A.O., Durosaro, S.O. and Sanda, M.O. (2014) Heritability and Repeatability Estimates of Some Measurable Traits in Meat Type Chickens Reared for Ten Weeks in Abeokuta, Nigeria. International Journal of Animal and Veterinary Sciences, 8, 782-785.
[29]  Renand, G., Larzul, C., Bihan-Duval, E.L. and Roy, P.L. (2003) L’amélioration génétique de la qualité de la viande dans les différentes espèces: Situation actuelle et perspectives à court et moyen terme. INRAE Productions Animales, 16, 159-173.
https://doi.org/10.20870/productions-animales.2003.16.3.3657
[30]  Mignon-Grasteau, S. and Faure, J.M. (2002) Génétique et adaptation: Le point des connaissances chez les volailles. INRAE Productions Animales, 15, 357-364.
https://doi.org/10.20870/productions-animales.2002.15.5.3715
[31]  Falconer, D.S. (1996) Introduction to Quantitative Genetics. 4e Edition, Longman, Harlow.
http://archive.org/details/IntroductionToQuantitativeGenetics
[32]  Sulaiman, M. (2020) Estimation of Some Genetic Parameters for Body Weight and Egg Production Traits of Two Iraqi Chicken Lines [PhD]. Salahaddin University-Erbil, Erbil.
https://www.researchgate.net/publication/339657822
[33]  Beaumont, C., Calenge, F., Chapuis, H., Fablet, J., Minvielle, F. and Tixier-Boichard, M. (2011) Génétique de La Qualité de l’oeuf. INRAE Productions Animales, 23, 123-132.
https://doi.org/10.20870/productions-animales.2010.23.2.3294
[34]  BAD (2018) Perspectives économiques en Afrique de l’Ouest. Banque africaine de développement, Abidjan.
http://www.wallonia.ci/sites/default/files/Perspectives_economiques_en_Afrique_2018_Afrique_de_l_Ouest.pdf
[35]  OCDE et FAO (2021) Perspectives agricoles de l’OCDE et de la FAO 2021-2030. Editions OECD, Paris.

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413