محمدباقر صیادنژاد

In dairy cattle enterprise, there are several economic traits associated with productive and reproductive performance which milk yield is the main source of income for the herd keeper. Knowledge of lactation is considered a useful tool for management decision-making. Based on this, lactation curve modeling can be utilized as an appropriate guide for planning nutrition programs as well as genetic selection schemes. So far, main research has been focused on using raw (unadjusted) milk test day records to model the shape of the lactation curve by applying a variety of linear and non-linear mathematical models and a few research have been carried out to use adjusted milk test day records in terms of fat and protein percentages. The main objective of the present research was to compare lactation curve parameters of Iranian first-parity dairy cows among three types of milk test day records including raw milk (RM), fat-corrected milk (FCM), and energy-corrected milk (ECM).

The initial data set was provided by the Animal Breeding Center and Promotion of Animal Products of Iran. Editing of the data was carried out by FOXPRO and Excel software based on some criteria such as age at first calving (was set to be in the range of 18-48 months), minimum (3 kg), and maximum (99.9 kg) of RM. There were a minimum of five test day records for each cow during the lactation period. Final data consisted of a total number of 1,902,071 milk test day records belonging to 226,255 first-parity cows (progeny of 5,094 sires and 178,390 dams) distributed in 797 herds and calved during 1996-2015 were utilized. For a mathematical description of the shape of the lactation curve, Wood’s incomplete gamma function was used. The function has three parameters including parameter a (associated with initial milk yield), parameter b (associated with the inclining slope of the lactation), and parameter c (associated with the declining slope of the lactation). Wood's function was fitted to the records of RM, FCM, and ECM of individual cows using SAS software. Based on the estimated parameters, lactation characteristics including peak time (PT), peak yield (PY), and persistency (Per) were subsequently calculated for each cow. Estimated parameters and calculated lactation characteristics were then subjected to a fixed linear model in which the effects of herd, year of calving, the season of calving, age at first calving, genotype group (grade or purebred Holstein), type of milk test day record (RM, FCM or ECM) along with some two-way interactions were included.  

The results showed that FCM had the greatest parameter a as compared with RM and ECM (P<0.0001). The greatest magnitude of the parameters b and c were found for RM (P<0.0001). Later PT and higher Per were observed for ECM (P<0.0001), while the highest PY was detected for RM (P<0.0001). For all types of records, minimum and maximum PY were observed for the cows calving in the spring and autumn seasons, respectively. Later PT was observed for ECM in all calving seasons except autumn. As compared to RM and FCM, cows calved in spring and summer had the highest persistency based on ECM while cows calved in autumn and winter were found to have more persistence based upon RM compared with FCM and ECM. The least-square means of peak time (PT) in grade cows were found to be 77.74, 69.5, and 79.85 d for RM, FCM, and ECM, respectively, while the corresponding figures for purebred Holstein cows were 80.27, 72.89, and 83.15 d, respectively. In grade cows, least-square means of peak time (PY) were found to be 32.02, 29.23, and 30.70 kg for RM, FCM, and ECM, respectively, while the corresponding figures for purebred Holstein cows were 32.51, 29.56, and 31.14 kg, respectively. For both purebred Holstein and grade cows, minimum and maximum persistency (Per) were obtained for FCM and ECM, respectively, which were significantly different from each other (P<0.001). For RM, FCM, and ECM, annual change trends of PT were found to be 2.132, 2.306, and 2.293 d, respectively, while the corresponding figures for PY were 0.408, 0.369, and 0.395 kg, respectively, and for Per were 0.037, 0.036, and 0.035, respectively. All trends were statistically significant (P<0.0001).

The finding of the present research revealed that purebred Holsteins reach the peak time later than grade cows which is an appropriate characteristic of the lactation curve. Based upon energy-corrected milk yield, peak time as well as persistency was found to be greater than those for raw milk and fat-corrected milk yields. Therefore, the use of energy-corrected milk yield could be suggested to be applied as different experimental nutritional treatments are to be compared in terms of the persistency of the cows. All lactation characteristics of Iranian dairy cows were found to be changed favorably over time.

The main aim of the present research was the genetic analysis of the first lactation milk yield trait and evaluation of the impact of selection for milk on the phenotype of age at first calving in Iranian dairy cows using quantile regression. Lactation milk records of 327190 first parity cows (progeny of 5260 sires and 235172 dams) in 637 herds (in 15 provinces) and calved between 2007 and 2015 were utilized. Genetic analysis was carried out with the use of an animal model. In the model, fixed effects of the province, herd, year and month of calving, covariates of lactation length, age at first calving, percentage of Holstein gene, as well as the random effect of the cow were included. The model was fitted on the data using the DMU package. Regression of age at first calving on predicted breeding value was fitted through a quantile regression model. The findings revealed that the heritability of lactation milk yield was equal to 0.276. Annual genetic gain in grade and Holstein purebred were found to be 17.352 (R2=0.913) and 23.398 (R2=0.962) Kg, respectively (P<0.0001). All estimated regression coefficients were negative in different percentiles of age at first calving and ranged between -0.0009 and -0.0344 (month per Kg) which indicates that the influence of genetic potential of cows for milk yield on different parts of calving age distribution is not the same.

Inbreeding, which has been defined as the mating between relative animals, leads to increase homozygous genotypes and decrease heterozygous genotypes in a population. As a result, the progenies of such mating are inbred (Wakchaure and Genguly 2015). Reduction of the traits associated with physiological efficiency and reproductive potential are the most important impacts of inbreeding in the farm animals (Filho et al. 2015, Fleming et al. 2018). Traits in livestock have different heritabilities suggesting that they are not influenced by inbreeding in a similar pattern and that although animals’ fitness is generally deteriorated; the magnitude of inbreeding depends on the type of the trait (Roff 1998; Derose and Roff, 1999, Wright et al. 2008, Mikkelsen et al. 2010). Until now, all studies regarding effects of inbreeding on productive and reproductive traits of dairy cows have been focused on using the statistical models in which inbreeding coefficient was included as covariable (Behmaram et al. 2017) or as the classified variable (Amirzadeh 2012). As inbreeding coefficient is defined as a covariable in the model, only a regression coefficient is estimated describing average changes of the trait per increasing / decreasing inbreeding coefficient. As a matter of fact, inbreeding may unequally influence the shape of distribution of the trait. Based on this assumption, this research aimed to estimate inbreeding effects on some productive and reproductive traits of Iranian dairy cows using Quantile regression statistical method.     

The data set was provided by Animal Breeding Centre, Iran. Foxpro (version 2.6) and UEStudio (version 09) software were utilized for editing initial data. Final data consisted of 580,802 records belonging to 580,802 first-parity cows distributed in 1,185 herds (over 20 provinces of the country) and calved between years 1991 and 2015. The traits under consideration were lactation milk yield (TMILK), 305d, 2X milk yield (MILK3052X), average daily milk yield (ADM), lactation length (LL), and age at the first calving (AFC). The average of the traits in the final data set was 9,447 Kg, 7,792 Kg, 30 Kg, 315 d and 25.6 m, respectively. Holstein gene percentage (HGP) of the cows in the pedigree file was set to be in the range of 50 to 100 and AFC of the cows was set to be between 18 and 48 months. Inbreeding coefficient (IC) of individual animals was calculated by CFC software (Sargolzaei et al. 2006). Fitting a series of the Quantile regression models was conducted with the use of SAS (version 9.4) software. Quantile regression, which was introduced by Koenker and Bassett (1978), extends the regression model to conditional quantiles of the response variable, such as the 90th percentile. Quantile regression is particularly useful when the rate of change in the conditional Quantile, expressed by the regression coefficients, depends on the Quantile (Chen 2005). In all the models used in this research, fixed effects of province, year and month of calving, as well as linear co-variables of HGP, IC and AFC (except of the model for AFC as the trait) were included. For TMILK, lactation length was also included as linear co-variable. Moreover, in addition to the quantile models and for the sake of estimating usual regression coefficient, general linear model (GLM) was also fitted for each trait in which a single regression coefficient of the trait on IC was defined. Ordinary least-squares regression can be used to estimate conditional percentiles by making a distributional assumption such as normality for the error term in the model. The main advantage of Quantile regression over ordinary least-squares regression is its flexibility for modeling data with heterogeneous conditional distributions (Chen 2005).      

Based upon the analysis of main pedigree file, the total number of animals was 1,941,871 (16,169 sires and 895,376 dams) among which the number of base and non-base animals were 246,388 (3,936 sires and 120,287 dams) and 1,695483 (12,233 sires and 775,089 dams), respectively.Total number of inbred animals in the pedigree was 1,211,343. Average IC for total as well as inbred animals was found to be 0.9149% (minimum 0% and maximum 47.02%) and 1.4651% (minimum 0.00038% and maximum 47.02%), respectively. For the cows with records for all five traits, IC ranged from 0 to 38.45% with the average of 1.13% (SD=1.63%). Estimate of annual change of IC was found to be 0.017 (SE=0.005), which was statistically significant (P<0.01) indicating that there is a positive increase of inbreeding in Iranian dairy cows’ population over the time. Within each trait, different Quantiles were unequally influenced as animal’s IC increased. Vast majority of the estimated regression coefficients in different Quantiles were statistically significant (P<0.05). Based upon fitting Quantile regression model and the average estimated regression coefficients, it was found that TMILK, MILK3052X, ADM, LL, and AFC changed -5.5 (Kg), -2.6 (Kg), -18 (g), 0.35 (d) and 0.30 (d), respectively as the IC of the animal increased by 1%. Estimated simple regression coefficients based on fitting GLM models were found to be -9.83 Kg (SE=1.332 Kg), -6.9 Kg (SE=0.169 Kg), -32 gram (SE=4.2 gram), 0.2087 d (SE=0.08234 d) and 0.0158 m (SE=0.0024 m), respectively and all were statistically significant (P<0.05).     

This research indicated that different Quantiles of some productive and reproductive traits of Iranian dairy cows are not equally affected by inbreeding phenomenon suggesting that Quantile regression models are needed to be utilized in the future research for evaluating the impacts of inbreeding on the other traits, which are of great economic importance.

In this study، 10839 records of first parity Iranian Holstein dairy cattle (that were collected by Animal Breeding Center of Iran) were used to estimate genetic and phenotype parameters of 5 different type traits، 2 longevity traits، and their correlations. The genetic parameters were estimated by restricted maximum likelihood method with an animal model using ASREML software. Heritability estimates for type traits ranged from 0. 11 (fore udder attachment) to 0. 20 (body depth). The genetic correlation between longevity traits and type traits of body depth، loin، chest width، udder width and body size were negative and type traits of fore udder attachment، udder depth، median suspensor and udder height were positive and ranged from 0. 03 (true productive herd life with fore udder attachment) to -0. 47 (functional productive herd life with fore udder attachment). According to these results، it could be recommended to use type traits index for effective selection of animals with better longevity and fertility traits.