Genetic analysis of Pollott-Gootwine mechanistic model parameters for lactation curve of Iranian dairy cows

Successful animal breeding strategies rely on selecting superior animals to produce progeny which are expected to have better performance compared to contemporaries at different rearing environments (Doeschl-Wilson 2007). Based on this, the main aim of a breeding scheme is to promote genetic potential of livestock for the traits of great economic importance. Milk yield varies over a course of lactation as a result of continuous physiological mechanisms of growth and death of udder cells (Val-Arreola 2004). Mathematical models used for description of the lactation curve can be empirical (shape-oriented) or mechanistic (biology-oriented) (Farhangfar 2015). Using mechanistic (biological) models it would be possible to study genetic aspects of cows' lactation curve from the biology of milk secretion in udder tissue standpoint. Vast majority of the research undertaken on the lactation curve of Iranian dairy cows have been focused on the use of empirical models. This research was carried out with the objective of evaluating genetic characteristics of the lactation curve of Iranian Holstein grade and pure-bred dairy cows using a mechanistic model. The data used in this research were provided by Animal Breeding Centre, Karaj, Iran. The data set consisted of 1,448,292 test day milk records belonging to 161,676 first parity cows (progeny of 3979 bulls) in 921 herds (in 14 provinces over the country) and calved during 1997- 2012. Minimum and maximum number of test day records were 4 and 13, respectively. Based on the percentage of Holstein gene inheritance (H), cows were divided into four groups. Pollott-Gootwine mechanistic model with two parameters of MS (maximum secretion potential of the lactation) and DR (relative decline in cell numbers) was applied to describe the shape of lactation curve. This nonlinear function was fitted to the individual lactation curves and the parameters were estimated for each cow by using nonlinear procedure of SAS software. Heritability of MS and DR traits was estimated using a fitting univariate animal model. In the model, effects of province, contemporary group of herd-year-season, calving age, type of genotype, interval of first test day from calving, fat to protein ratio, length of lactation as well as random effect of cow were included. All relationship among the animals were taken into account through including pedigree. The model was run for each trait using DMU software and restricted maximum likelihood (REML) estimate of additive genetic and residual variance components and prediction of breeding value of the animals were obtained. Genetic trend was subsequently calculated through fitting weighted regression of mean breeding value on calving year. Additive genetic and residual variance components for MS were 5.7123 and 13.7759, respectively and the corresponding figures for DR were 0.0000012 and 0.0000051, respectively. Heritabilities of MS and DR were found to be 0.293 (SE=0.008) and 0.194 (SE=0.120), respectively indicating that there is relatively good genetic variation for the traits to be used in selection programmes. Mean predicted breeding value (PBV) of the cows with records were 0.255 (Kg) and -0.000005 for MS and DR, respectively. Regarding MS, cows with 50  H  75 had minimum PBV (0.072 Kg) while cows with 87.5  H 100 had maximum PBV (0.309 Kg) and the difference was statistically significant (P<0.05). Based upon mean PBV for MS, mean PBV for the trait of 305-day milk yield in pure-bred Holstein cows (H=100) was expected to be 82.96 Kg. Pearson correlation between breeding values of the traits was -0.29 (P<0.0001) suggesting that cows of high genetic potential for MS are expected to have low breeding value for DR. Phenotypic and genetic trends for MS were 0.52 (SE=0.017) and 0.063 (SE=0.004, R2=0.95) kg per year, respectively, while the corresponding figures for DR were -0.000025 (SE=0.0000021) and -0.000007 (SE=0.00000054, R2=0.92), respectively and that all the trends were statistically significant (P<0.0001). High heritability of MS and DR suggests that appropriate genetic gain could be obtained as the selection of the cows is based upon these traits. As DR is associated with lactation persistency, it could be therefore concluded that Iranian dairy cows have become phenotypically and genetically persistent over the years of 1997-2012.