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Bayesian approach for genetic analysis of production and reproduction traits in Jersey crossbred cattle

Published online by Cambridge University Press:  08 July 2022

Poonam Ratwan Open the ORCID record for Poonam Ratwan [Opens in a new window] ,
Manoj Kumar  and
Ajoy Mandal
Poonam Ratwan*
Affiliation:
Department of Animal Genetics and Breeding, LUVAS, Hisar-125004, (Haryana), India Animal Breeding Section, Eastern Regional Station, ICAR-National Dairy Research Institute, Kalyani, Nadia-741235, (West Bengal), India
Manoj Kumar
Affiliation:
Department of Livestock Farm Complex, LUVAS, Hisar-125004, (Haryana), India
Ajoy Mandal
Affiliation:
Animal Breeding Section, Eastern Regional Station, ICAR-National Dairy Research Institute, Kalyani, Nadia-741235, (West Bengal), India
*
Author for correspondence: Poonam Ratwan. Department of Animal Genetics and Breeding, LUVAS, Hisar-125004, Haryana, India. Tel: +91 9816089896. E-mail: [email protected]
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Summary

The knowledge of genetic parameters of performance traits is crucial for any breeding programme in dairy animals. The present study was conducted to use a Bayesian approach for estimation of genetic parameters of production and reproduction traits in Jersey crossbred cattle. Data of Jersey crossbred cattle maintained at Eastern Regional Station, National Dairy Research Institute, West Bengal spread over a span of 41 years were utilized. The marginal posterior medians of heritability for 305-day milk yield (305MY), total milk yield (TMY), peak yield (PY), lactation length (LL), calving interval (CI), total milk yield per day of lactation length (TMY/LL) and total milk yield per day of calving interval (TMY/CI) were 0.31 ± 0.07, 0.29 ± 0.07, 0.27 ± 0.06, 0.16 ± 0.05, 0.15 ± 0.05, 0.29 ± 0.06, 0.27 ± 0.06, respectively. Moderate heritability estimates for 305MY, TMY, PY and production efficiency traits indicate the presence of adequate additive genetic variance in these traits to respond to selection combined with better herd management. Repeatability estimates for 305MY, TMY, PY, LL, CI, TMY/LL and TMY/CI were 0.57 ± 0.08, 0.58 ± 0.08, 0.51 ± 0.07, 0.34 ± 0.06, 0.31 ± 0.06, 0.54 ± 0.07 and 0.49 ± 0.07, respectively. Repeatability estimates for 305MY, TMY and PY were high in the current study, suggesting the use of first lactation records for early evaluation of Jersey crossbred cattle for future selection. Genetic correlations varied from 0.21 to 0.97 and maximum genetic correlation was observed between 305MY and TMY indicating that consideration of 305MY instead of TMY in breeding programmes would suffice. Positive genetic correlations of CI with 305MY and TMY indicated the antagonistic association between production and reproduction traits.

Keywords

BayesianCorrelationHeritabilityJersey crossbredPerformanceRepeatability
Type
Research Article
Information
Zygote , Volume 30 , Issue 5 , October 2022 , pp. 656 - 663
Copyright
© The Author(s), 2022. Published by Cambridge University Press

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References

Ali, I., Muhammad Suhail, S. and Shafiq, M. (2019). Heritability estimates and genetic correlations of various production and reproductive traits of different grades of dairy cattle reared under subtropical condition. Reproduction in Domestic Animals, 54(7), 1026–1033. doi: 10.1111/rda.13458 CrossRefGoogle ScholarPubMed
Aspilcueta-Borquis, R., Bignardi, A. B., Seno, L. O., Camargo, G. M., Munoz-Berrocal, M., Albuquerque, L. G., Di Palo, R. and Tonhati, H. (2010). Genetic parameters for milk yield analyzed by test-day models in Murrah buffaloes in Brazil. Italian Journal of Animal Science, 9, 179–182.Google Scholar
Ayalew, W., Aliy, M. and Negussie, E. (2017). Estimation of genetic parameters of the productive and reproductive traits in Ethiopian Holstein using multi-trait models. Asian-Australasian Journal of Animal Sciences, 30(11), 1550–1556. doi: 10.5713/ajas.17.0198 CrossRefGoogle ScholarPubMed
BAHS (2019). Basic Animal Husbandry Statistics. Department of Animal Husbandry, Dairying & Fisheries, Ministry of Agriculture, Govt. of India.Google Scholar
Berry, D. P., Buckley, F., Dillon, P., Evans, R. D., Rath, M. and Veerkamp, R. F. (2003). Genetic relationships among body condition score, body weight, milk yield, and fertility in dairy cows. Journal of Dairy Science, 86(6), 2193–2204. doi: 10.3168/jds.S0022-0302(03)73809-0 CrossRefGoogle ScholarPubMed
Dash, S. K., Gupta, A. K., Avtar, S., Chakravarty, A. K., Mohanty, T. K., Panmei, A. and Pushp, R. S. (2016). Genetic analysis of first lactation production and fertility traits in Karan Fries cattle. Indian Journal of Animal Sciences, 86(10), 1159–1164.Google Scholar
Ebangi, A. L., Erasmus, G. J., Neser, F. W. C. and Tawah, C. L. (2000). Genetic trends for growth in the Gudali and Wakwa cattle breeds of Cameroon. South African Journal of Animal Science 38th Congress of the South African Society of Animal Science, 30(4), 36–37. doi: 10.4314/sajas.v30i4.3899 Google Scholar
Edriss, M. A., Nilforooshan, M. A. and Sadeghi, J. M. (2006). Estimation of direct genetic and maternal effects for production traits of Iranian Holstein cows using different animal models. Pakistan Journal of Biological Sciences, 9(4), 636–640. doi: 10.3923/pjbs.2006.636.640 CrossRefGoogle Scholar
Gelfand, A. E. and Smith, A. F. M. (1990). Sampling-based approaches to calculating marginal densities. Journal of the American Statistical Association, 85(410), 398–409. doi: 10.1080/01621459.1990.10476213 CrossRefGoogle Scholar
Getahun, K., Beneberu, N. and Lemma, Z. (2020). Genetic trend and heritability estimates for milk production traits of Jersey breed in Ethiopian highland environment. International Journal of Animal Health and Livestock Production Research, 4(2), 16–28.Google Scholar
Getahun, K., Tadesse, M., Hunde, D. and Lemma, Z. (2021). Genetic parameters of milk production traits in crossbred cows in Ethiopia. Journal of Livestock Science, 12(2), 103–110. doi: 10.33259/JLivestSci.2021.103-110 CrossRefGoogle Scholar
Ghafoor, A., Khan, U. N. and Khan, M. A. (1992). Repeatability of lactation yield, peak milk yield and days in milk in Tharparkar cows. Pakistan Journal of Agricultural Sciences, 29(4), 339–341.Google Scholar
Gianola, D. and Fernando, R. L. (1986). Bayesian methods in animal breeding theory. Journal of Animal Science, 63(1), 217–244. doi: 10.2527/jas1986.631217x CrossRefGoogle Scholar
Harvey, W. R. (1990). Guide for LSMLMW, PC-1 Version, mixed model least squares and maximum likelihood computer programme. Mimeograph, Ohio State University.Google Scholar
Hermiz, H. and Hadad, J. M. (2020). Factors affecting and estimates of repeatability for milk production and composition traits in several breeds of dairy cattle. Indian Journal of Animal Sciences, 90(3), 129–133.Google Scholar
Ilahi, H., Hammouda, M. B. and Othmane, M. H. (2012). Bayesian genetic analysis of milk yield in Tunisian Holstein dairy cattle population. Open Journal of Genetics, 02(2), 103–108. doi: 10.4236/ojgen.2012.22015 CrossRefGoogle Scholar
Islam, M. S., Akhtar, A., Hossain, M. A., Rahman, M. F. and Hossain, S. S. (2017). Reproductive performance and repeatability estimation of some traits of crossbred cows in Savar dairy farm. Journal of Environmental Science and Natural Resources, 10(2), 87–94. doi: 10.3329/jesnr.v10i2.39017 CrossRefGoogle Scholar
Kinghorn, B. and Kinghorn, S. (2015). Pedigree Viewer version 6.5 f. http://bkinghor.une.edu.au/pedigree.htm. (Version on 28 December 2015)Google Scholar
Kumar, A. and Mandal, A. (2021). Evaluation of animal models to explore the influence of maternal genetic and maternal permanent environment effect on reproductive performance of Jersey crossbred cattle. Reproduction in Domestic Animals, 56(3), 511–518. doi: 10.1111/rda.13889 CrossRefGoogle ScholarPubMed
Kumar, M., Vohra, V., Ratwan, P., Valsalan, J., Patil, C. S. and Chakravarty, A. K. (2016). Estimates of genetic parameters for fat yield in Murrah buffaloes. Veterinary World, 9(3), 295–298. doi: 10.14202/vetworld.2016.295-298 CrossRefGoogle ScholarPubMed
Lakshmi, S. B., Gupta, B. R., Prakash, M. G., Sudhakar, K. and Sharma, S. (2010). Genetic analysis of the production performance of Frieswal cattle. Tamilnadu Journal of Veterinary & Animal Sciences, 6(5), 215–222.Google Scholar
Makgahlela, M. L., Banga, C. B., Norris, D., Dzama, K. and Ng’ambi, J. W. (2007). Genetic correlations between female fertility and production traits in South African Holstein cattle. South African Journal of Animal Science, 37(3), 180–188. doi: 10.4314/sajas.v37i3.4090 CrossRefGoogle Scholar
Mandal, A., Roy, P. K., Ghosh, M. K., Chatterjee, A. and Das, S. K. (2013). Genetic and environmental effects on First Lactation traits of Jersey crossbred cattle in an organized herd of Eastern India. Indian Journal of Dairy Sciences, 66(2), 130–133.Google Scholar
Missanjo, E., Imbayarwo-Chikosi, V. and Halimani, T. (2013). Estimation of genetic and phenotypic parameters for production traits and somatic cell count for Jersey dairy cattle in Zimbabwe. ISRN Veterinary Science, 2013, 470585. doi: 10.1155/2013/470585 CrossRefGoogle ScholarPubMed
Misztal, I., Tsuruta, S., Lourenco, D., Aguilar, I., Legarra, A. and Vitezica, Z. (2015). Manual for BLUPF90 Family of Programs.Google Scholar
Ojango, J. M. and Pollott, G. E. (2001). Genetics of milk yield and fertility traits in Holstein-Friesian cattle on large-scale Kenyan farms. Journal of Animal Science, 79(7), 1742–1750. doi: 10.2527/2001.7971742x CrossRefGoogle ScholarPubMed
Penasa, M., Cecchinato, A., Battagin, M., De Marchi, M. D., Pretto, D. and Cassandro, M. (2010). Bayesian inference of genetic parameters for test-day milk yield, milk quality traits, and somatic cell score in Burlina cows. Journal of Applied Genetics, 51(4), 489–495. doi: 10.1007/BF03208878 CrossRefGoogle ScholarPubMed
Pereira, J. A. C., Suzuki, M., Hagiya, K., Yoshizawa, T., Tsuruta, S. and Misztal, I. (2001). Method R estimates of heritability and repeatability for milk, fat and protein yields of Japanese Holstein. Nihon Chikusan Gakkaiho, 72(5), 372–377. doi: 10.2508/chikusan.72.372 CrossRefGoogle Scholar
Plasse, D., Verde, O., Fossi, H., Romero, R., Hoogesteijn, R., Bastidas, P. and Bastardo, J. (2002). (Co)variance components, genetic parameters and annual trends for calf weights in a pedigree Brahman herd under selection for three decades. Journal of Animal Breeding and Genetics, 119(3), 141–153. doi: 10.1046/j.1439-0388.2002.00321.x CrossRefGoogle Scholar
Pollak, E. J., Werf, J. V. and Quaas, R. L. (1983). Selection bias and multiple trait evaluation. Journal of Dairy Science, 67, 1590–1595 CrossRefGoogle Scholar
Ratwan, P., Mandal, A., Kumar, M., Kumar, A. and Chakravarty, A. K. (2016). Genetic analysis of lactation traits in Jersey crossbred cattle. Indian Journal of Dairy Science, 69, 182–185.Google Scholar
Ratwan, P., Mandal, A., Kumar, M. and Chakravarty, A. K. (2017). Genetic analysis of milk production efficiency traits in Jersey crossbred cattle. Indian Journal of Animal Research, 51(4), 644–647. doi: 10.18805/ijar.7076 Google Scholar
Ratwan, P., Kumar, M., Kumar, A., Chakravarty, A. K. and Mandal, A. (2018). Impact of additive direct and maternal heritability on production efficiency traits in Jersey crossbred cattle. Indian Journal of Animal Sciences, 88(7), 848–852.Google Scholar
Ratwan, P., Kumar, M., Chakravarty, A. K. and Mandal, A. (2019). Estimation of direct and maternal (co)variance components for lactation traits in Jersey crossbred cattle at an organized farm. Indian Journal of Animal Sciences, 89(2), 193–199.Google Scholar
Ratwan, P., Chakravarty, A. K. and Kumar, M. (2022). Assessment of relation among production and reproduction traits in Sahiwal cattle at an organized herd of northern India. Biological Rhythm Research, 53(1), 70–78. doi: 10.1080/09291016.2019.1628391 CrossRefGoogle Scholar
Rekaya, R., Carabaño, M. J. and 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 CrossRefGoogle ScholarPubMed
Resende, M. D. V., Duda, L. L., Guimaraes, P. R. B. and Fernandes, J. S. C. (2001). Analise de modelos lineares mistos via inferencia Bayesiana. Revista de Matematica e Estatistica, 19, 41–70.Google Scholar
Saha, S., Joshi, B. K. and Singh, A. (2010). Generation wise genetic evaluation of various first lactation traits and herd life in Karan Fries cattle. Indian Journal of Animal Sciences, 80(5), 451–456.Google Scholar
Singh, A., Singh, A., Singh, M., Prakash, V., Ambhore, G. S., Sahoo, S. K. and Dash, S. (2016). Estimation of genetic parameters for first lactation monthly test-day milk yields using random regression test day model in Karan-Fries cattle. Asian-Australasian Journal of Animal Sciences, 29(6), 775–781. doi: 10.5713/ajas.15.0643 CrossRefGoogle ScholarPubMed
Sorensen, D. and Gianola, D. (2007). Likelihood, Bayesian, and MCMC methods in quantitative genetics. Springer Science+Business Media.Google Scholar
Taggar, R. K., Das, A. K., Kumar, D. and Mahajan, V. (2014). Genetic studies on performance traits of Jersey crossbred cows in sub-temperate region. Indian Journal of Animal Sciences, 84(7), 771–774.Google Scholar
Usman, T., Guo, G., Suhail, S. M., Ahmed, S., Qiaoxiang, L., Qureshi, M. S. and Wang, Y. (2012). Performance traits study of Holstein Friesian cattle under subtropical conditions. Journal of Animal and Plant Sciences, 22, 92–95.Google Scholar
Varaprasad, A. R., Raghunandan, T., Kumar, M. K. and Prakash, M. G. (2013). Studies on the reproductive performance of Jersey × Sahiwal cows in Chittoor district of Andhra Pradesh. International Journal of Agricultural Sciences and Veterinary Medicine, 1(1), 52–57.Google Scholar
Vijayakumar, P., Singaravadivelan, A., Silambarasan, P., Ramachandran, M. and Churchil, R. (2019). Production and reproduction performances of crossbred Jersey cows. Veterinary Research International, 7(2), 56–59.Google Scholar
Vinothraj, S., Subramaniyan, A., Venkataramanan, R., Joseph, C. and Sivaselvam, S. N. (2016). Genetic evaluation of reproduction performance of Jersey × Red Sindhi crossbred cows. Veterinary World, 9(9), 1012–1017. doi: 10.14202/vetworld.2016.1012-1017 CrossRefGoogle ScholarPubMed
Visscher, P. M. and Thompson, R. (1992). Univariate and multivariate parameter estimates for milk production traits using an animal model. I. Description and result of REML analyses. Genetics Selection Evolution, 24(5), 415–430. doi: 10.1186/1297-9686-24-5-415 CrossRefGoogle Scholar
Wall, E., Brotherstone, S., Woolliams, J. A., Banos, G. and Coffey, M. P. (2003). Genetic evaluation of fertility using direct and correlated traits. Journal of Dairy Science, 86(12), 4093–4102. doi: 10.3168/jds.S0022-0302(03)74023-5 CrossRefGoogle ScholarPubMed
Worku, D., Gowane, G. R., Kumar, R., Joshi, P., Gupta, I. D. and Verma, A. (2021). Estimation of genetic parameters for production and reproductive traits in Indian Karan-Fries cattle using multi-trait Bayesian approach. Tropical Animal Health and Production, 53(3), 369. doi: 10.1007/s11250-021-02806-z CrossRefGoogle ScholarPubMed