The effect of model structure on the model performance to fit milk production data in Isfahan Holstein cows

Document Type : Original Research Article (Regular Paper)


Department of Animal Science, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran


The structure of the fixed and random parts of the genetic evaluation model plays a significant role in fitting data and the estimation of genetic parameters for economic traits in livestock. The present study was conducted to investigate the effect of different fixed and random effects combinations in an animal model framework on the general properties of the model and estimates of the genetic parameters for milk production traits. Traits studied were 305-day milk production (305-MY, 15920 records), fat percentage (FP, 27954 records), protein percentage (PP, 26183 records), average daily milk production (ADM, 30954 records) and milk somatic cell score (SCS, 25408 records) in Isfahan Holstein cows. In general, 54 scenarios were studied which differed in fixed and random parts of the model. Variance components were estimated using the animal model fitting restricted maximum likelihood (REML) procedure. The best model for each trait was selected based on the Bayesian Information Criterion (BIC). Results showed that for all traits studied, models in which the effect of contemporary groups Herd-Year-Season (HYS) or Herd-Year-Month (HYM) were fitted as the random or fixed effect together with age at the first calving and inbreeding as a classified fixed effect or covariate lead to a significantly better data fit instead of fitting herd, year, season and month of calving separately. For each trait, a wide range of heritability was obtained by fitting 54 models. Based on the best models, the estimates of heritability for 305-MY, ADM, FP, PP and SCS were 0.33, 0.28, 0.21, 0.16 and 0.61, respectively. It was concluded that a single model should not be used for analyzing all milk production traits and that for each trait a series of models which differ in random and fixed parts should be tested to find the most suitable model which describes the data best. Fitting the effects of herd and year, season and month of calving as contemporary groups the HYS or HYM was recommended for genetic evaluation of milk production traits as resulted in better data fit. Depending on the trait, inbreeding and age at first calving can be fitted as a classified fixed effect or as a covariate.  


Main Subjects

Akaike, H., 1974. A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 719-723.
Alinaghizadeh, R., Mohammad Abadi, M.R., Moradnasab Badrabadi, S., 2007. Kappa-casein gene study in Iranian Sistani cattle breed (Bos indicus) using PCR-RFLP. Pakistan Journal of Biological Science 10, 4291-4294.
Atashi, H., Hostens, M., 2021. Genetic aspects of somatic cell count in Holstein dairy cows in Iran. Animals 11, 1637-1645.
Bahreini Behzadi, M.R, Amini, A., Aslaminejad, A., Tahmoorespour, M., 2013. Estimation of genetic parameters for production traits of Iranian Holstein dairy cattle. Livestock Research for Rural Development 25, 1-5.
Bignardi, A.B., El Faro, L., Torres, R.A.A., Cardoso, V.L., Machado, P.F., Albuquerque, L.G., 2011. Random regression models using function to model test-day Milk yield of Brazilian Holstein cows. Genetics and Molecular Research 10, 3565-3575.
Buaban, S., Duangjinda, M., Suzuki, M., Masuda, Y., Sanpote, J., Kuchida, K., 2015. Genetic relationships of fertility traits with test-day milk yield and fat-to-protein ratio in tropical smallholder dairy farms. Animal Science Journal 87, 627-637.
Castillo-juarez, H., Oltenacu, P.A., Blake, R.W., Mccullouch, C.E., Cienfuegos-Rivas E.G., 2000. Effect of herd environment on the genetic and phenotypic relationship among milk yield, conception rate and somatic cell score in Holstein cattle. Journal of Dairy Science 83, 807-814.
Cho, C.I, Alam, M., Choi, T.J., Lee, S., Cho, K.H., 2016. Models for estimating genetic parameters of milk production traits using random regression models in Korean Holstein cattle. Asian Australas. Journal of Animal Science 29, 607-614.
Dong, M.C., Vanvleck, L.D., Wigans, G.R., 1998. Effect of relationship on estimation of variance component with an animal model and restricted maximum likelihood. Journal of Dairy Science 71, 3047-3052.
Goli, B., 2020. Effects of fixed factors in animal mixed models on estimates of variance components and breeding values for body weight traits in Moghani sheep. MSc Thesis, Bu-Ali Sina University, Hamedan, Iran.
Hanford, K.J, Vanvleck, L.D., Snowder, G.D., 2002. Estimation of genetic parameters and genetic change for reproduction weight and wool characteristic of Columbia sheep. Journal of Animal Science 80, 30860-3098.
Hill, W.G., 2008. Estimation, effectiveness and opportunities of long term genetic improvement in animals and maize. Lohman Information 43, 3-19.
Jorjani, H., 2003. An overview of validation issues in national genetic evaluation system. Interbull Bulletin 30, 49-58.
Kadarmideen, H.N., Thompson, R., Coffey, M.P., Kossaibati, M.A., 2003. Genetic parameters and evaluations from single and multiple Traits analysis of dairy cows feretility and milk production. Livestock Production Science 81,183-195.
Lasley, J.F., 1978. Genetics of Livestock Improvement. 4th ed. Prentice hall, New Jersey, USA.
Macgahlela M.L., Banga, C.B., Norris, D., Dzama, K., Ngambi, J.W., 2008. Genetic analysis of age at first calving and calving interval in South African Holstein cattle. Asian-Australasian Journal of Animal Sciences 3, 197-205.
Mehrpoor, Z., Bahreini Behzadi, M.R., 2017. Comparison of genetic parameters of 305-day milk yield trait in dairy cows in Isfahan province by using different animal models. Livestock Research 5, 53­-62.
Meyer, K., 2007. WOMBAT: A program for mixed model analyses by restricted maximum likelihood. Animal genetics and breeding unit, University of New England, Armidale, NSW 2351, Australia.
Mohammadabadi, M.R., Soflaei, M., Mostafavi, H., Honarmand, M., 2011. Using PCR for early diagnosis of bovine leukemia virus infection in some native cattle. Genetics and Molecular Research 10, 2658-2663.
Nassiry, M.R., Shahroodi, F.E., Mosafer, J., Mohammadi, A., Manshad, E., Ghazanfari, S., Mohammad Abadi, M.R., Sulimova, G.E., 2005. Analysis and frequency of bovine lymphocyte antigen (BoLA-DRB3) alleles in Iranian Holstein cattle. Russian Journal of Genetics 41, 664-668.
Nilforooshan, M.A., Edriss, M.A., 2004. Effect of age at first calving on some productive and longevity traits in Iranian Holsteins of the Isfahan province. Journal of Dairy Science 87, 2130-2135.
Pezhman, L., 2009. Estimation of variance components and genetic parameters of reproductive traits in Mehraban sheep. MSc Thesis, Bu-Ali Sina University, Hamedan, Iran.
Pirlo, G., Miglior, F., Speroni, M., 2000. Effect of age at first calving on production traits and on difference between milk yield returns and rearing costs in Italian Holstein. Journal of Dairy Science 83, 603-608.
Qanbari, S., Pausch, H., Jansen, S., Somel, M., Strom, T.M., Fries, R., Nielsen, R., Simianer, H., 2014. Classic selective sweeps revealed by massive sequencing in cattle. PLoS Genetics, 10:e1004148
Sargolzaei M., Iwaisaki, H., Colleau, J.J., 2006. Contribution, Inbreeding F, Coancestry (CFC): A software package for pedigree analysis and monitoring genetic diversity. Release 1.0.
Schwarz, G., 1978. Estimating the dimension of a model. The Annals of Statistics 6, 461-464.
Shadparvar, A.A., Yazdanshenas, M.S., 2005. Genetic parameters of milk yield and milk fat percentage test-day records of Iranian Holstein cows. Asian-Australasian Journal of Animal Sciences 18, 1231-1236.
Shahdadi, A.R., Tahmoorespur, M., Shariati, M.M., 2022. Genetic analysis of productive performance of Holstein dairy cows in different climate regions of Iran. Iranian Journal of Animal Science Research 9, 93-103 (In Persian with English abstract).
Weller, J.I., Ezra, E., 2004. Genetics analysis of the Israeli Holstein dairy cattle population for production and nonproduction trait with a multi-trait animal model. Journal of Dairy Science 87, 1519-1527.
Xue, X., Hu, H., Zhang, J., Ma, Y., Han, L., Hao, F., Jiang, Y., Ma, Y., 2022. Estimation of genetic parameters for conformation traits and milk production traits in Chinese Holsteins. Animals 13, 100.
Zaabaza H.B,  Gara, A.B., Ferhchichi, A.A., Rekik, B., 2016. Estimation of variance components of milk, fat and protein yields of Tunisian Holstein dairy cattle using Bayesian and REML methods. Archiv Animal Breeding 59, 243-246.
Zink, V., Lassen J., Stipkova, M., 2012. Genetic parameters for female fertility and milk production traits in first parity Czech Holstein cows. Czech Journal of Animal Science 57, 108-114.