Bayesian approach for evaluation of lactation curve in cross bred cattle based on monthly and bimonthly test day milk yield.
BLUP- AM
Bayesian
Bimonthly test day
Woods incomplete gamma function
Journal
Tropical animal health and production
ISSN: 1573-7438
Titre abrégé: Trop Anim Health Prod
Pays: United States
ID NLM: 1277355
Informations de publication
Date de publication:
09 Apr 2024
09 Apr 2024
Historique:
received:
24
08
2023
accepted:
22
03
2024
medline:
10
4
2024
pubmed:
9
4
2024
entrez:
8
4
2024
Statut:
epublish
Résumé
In field progeny testing program milk recording at monthly or bimonthly intervals and prediction of first lactation 305-day milk yield (FL305DMY) from these test day yields have been adapted as an alternative to daily milk recording. Wood's incomplete gamma function is the one of the commonly used nonlinear lactation curve model. In recent years Bayesian approach of fitting nonlinear biological models is gaining attention among researchers. In this study Wood's incomplete gamma function was fitted using Bayesian approach using monthly (MTDY) and bimonthly test day (BTDY) yields. The lactation curve parameters thus obtained were used for prediction of FL305DMY. Efficiency of prediction based on monthly and bimonthly test day milk yield were compared using error of prediction. It was found to be 5.78% and 7.59% as root mean square error (RMSE) based on MTDY and BTDY respectively.The Breeding values of 97 Karan Fries sires were estimated using BLUP-AM based on actual and predicted FL305DMY thus obtained. The RMSE was calculated as the difference between estimated breeding values based on actual and predicted yield. It was found that RMSE calculated based on MTDY showed only a marginal superiority of 0.79% over BTDY and showed high degree of correlation with actual yield. Therefore, recording at bimonthly intervals could be an economical alternative without compromising the efficiency.
Identifiants
pubmed: 38589528
doi: 10.1007/s11250-024-03960-w
pii: 10.1007/s11250-024-03960-w
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
118Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Nature B.V.
Références
Bakri, N.E., Pieramati, C., Sarti, F.M., Giovanini, S. and Djemali, M.N. 2022. Estimates of genetic parameters and genetic trend for Wood’s lactation curve traits of Tunisian Holstein–Friesian cows. Tropical Animal Health and Production, 54(4): 223.
doi: 10.1007/s11250-022-03219-2
pubmed: 35776218
Chen F. 2009. Bayesian modeling using the MCMC procedure. In Proceedings of the SAS Global Forum 2008 Conference, Cary NC: SAS Institute Inc.
Finco, E.M., Marcato, S.M., Furlan, A.C., Rossi, R.M., Grieser, D.D.O., Zancanela, V., Oliveira, T.M.M.D. and Stanquevis, C.E. 2016. Adjustment of four growth models through Bayesian inference on weight and body nutrient depositions in laying quail. Revista Brasileira de Zootecnia, 45: 737-744.
doi: 10.1590/s1806-92902016001200002
Firat, M.Z., Karaman, E., Başar, E.K. and Narinç, D., 2016. Bayesian analysis for the comparison of nonlinear regression model parameters: an application to the growth of Japanese quail. Brazilian Journal of Poultry Science, 18: 19-26.
doi: 10.1590/1806-9061-2015-0066
Groenewald, P.C. and Viljoen, C.S. 2003. A Bayesian model for the analysis of lactation curves of dairy goats. Journal of agricultural, biological, and environmental statistics, 8: 75-83.
doi: 10.1198/1085711031201
Gunes F and Chen F. 2014. Getting started with the MCMC procedure. https://support.sas.com/rnd/app/stat/papers/2014/gettingstartedMCMC2014.pdf . Accessed 20 July 2021
Gupta, R., Sahoo, S.K., Kaur, S., Dash, S.K. and Malhotra, P. 2021. Prediction of First Lactation 305-Day Milk Yield by Test Day Simple and Multiple Regression Models in Holstein Friesian Crossbred Cattle. International Journal of Livestock Research, 11(4): 95-99.
Henderson, C. R. 1975. Use of relationship among sires to increase accuracy of sire evaluation. Journal of Dairy Science, 58(11): 1731-37
doi: 10.3168/jds.S0022-0302(75)84777-1
Jeffreys, H. 1946. An invariant form for the prior probability in estimationproblems. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 186(1007): 453–461.
Karaman, E., Basar, E.K. and Firat, M.Z. 2015. Bayesian Hierarchical Modeling Applied to Test Day Milk Yield Data. Journal of Selcuk University Natural and Applied Science, 102–108.
Kokate, L.S., Singh, A., Banu, R., Gandhi, R.S., Chakravarty, A.K., Gupta, A.K. and Sachdeva, G.K. 2014. Prediction of 305-day lactation milk yield based on bimonthly test day values in Karan Fries cattle. Indian Journal of Animal Research, 48(2): 103-105.
doi: 10.5958/j.0976-0555.48.2.023
Meyer, K. 2007. WOMBAT version 1.0 User notes. Uni New England, Armidale, NSW, Australia.
Muniz, J.A., Fonseca, F., de Paiva Guedes, M.H. and de Moraes Gonçalves, T. 2007. Evaluation of lactation curve of low-yielding gir cows: a Bayesian approach. Acta Scientiarum. Animal Sciences, 29(1): 79-83.
Oliveira, J. G. D., Sant'Anna, D. F. D., Lourenco, M. C., Tavares, D. S. T., Rodrigues, M. T., Tedeschi, L. O. and Vieira, R. A. M. 2020. The geometry of the lactation curve based on Wood's equation: a two-step prediction. Revista Brasileira de Zootecnia. 49.
Radjabalizadeh, K., Alijani, S., Gorbani, A. and Farahvash, T. 2022. Estimation of genetic parameters of Wood’s lactation curve parameters using Bayesian and REML methods for milk production trait of Holstein dairy cattle. Journal of Applied Animal Research, 50(1): 363-368.
doi: 10.1080/09712119.2022.2080211
Rahayu, A.P., Hartatik, T., Purnomoadi, A. and Kurnianto, E. 2018, February. Estimation of 305 day milk yield from cumulative monthly and bimonthly test day records in Indonesian Holstein Cattle. In IOP Conference Series: Earth and Environmental Science, 119(1).
Rana, E., Gupta, A.K., Singh, A., Ruhil, A.P., Malhotra, R., Yousuf, S. and Ete, G. 2021. Prediction of first lactation 305-day milk yield based on bimonthly test day milk yield records in murrah buffaloes. Indian Journal of Animal Research, 55(4): 486-490.
Rekaya, R., Carabano, M. J., & Toro, M. A. 2000. Bayesian analysis of lactation curves of Holstein-Friesian cattle using a nonlinear model. Journal of Dairy Science, 83(11): 2691-2701.
doi: 10.3168/jds.S0022-0302(00)75163-0
pubmed: 11104290
SAS Institute Inc. 2013. SAS® 9.4 Guide to Software Updates and Product Changes. Cary, NC: SAS Institute Inc.
Spearman. 1904. The proof and Measurement of association between two things. The American Journal of Psychology, 15(1): 22-26
Stokes M, Chen F and Gunes F. 2014. An introduction to Bayesian analysis with SAS/STAT® software. In Proceedings of the SAS Global Forum 2014 Conference, SAS Institute Inc, Cary, USA
Sturges, H. A. 1926. The choice of a class interval. Journal of the american statistical association. 21(153): 65-66
doi: 10.1080/01621459.1926.10502161
Varona, L., Moreno, C., Cortes, L.G. and Altarriba, J. 1998. Bayesian analysis of Wood's lactation curve for Spanish dairy cows. Journal of Dairy Science, 81(5): 1469-1478.
doi: 10.3168/jds.S0022-0302(98)75711-X
pubmed: 9621251
Wood, P. D. P. 1967. Algebraic model of lactation curve in cattle. Nature, 216(5111): 164.
doi: 10.1038/216164a0