Parameters For Milk Production Traits Research Articles

Estimation of genetic parameters of Wood’s lactation curve parameters using Bayesian and REML methods for milk production trait of Holstein dairy cattle

ABSTRACT Bayesian and average information restricted maximum likelihood (AI-REML) approaches were used to estimate variance components and genetic parameters of Wood’s lactation curve parameters of milk production traits in three lactations of Iranian Holstein dairy cows. Wood’s function parameters (a, b, and c) of each lactation were initially estimated for individual cows using the NLIN procedure of the SAS programme, separately. The variance components of the parameters of each lactation were estimated by the AI-REML method using a single-trait animal model inairemlf90 programme. To do this with the Bayesian method by using the Gibbs sampling technique, the same animal model was used in the gibbs3f90 programme. The estimated heritability values by the AI-REML were 0.018, 0.00, and 0.019 for a parameter; 0.015, 0.007, and 0.02 for b parameter; and 0.23, 0.625, and 0.049 for c parameter in the 1st, 2nd, and 3rd lactations, respectively. The corresponding results from the Bayesian procedure (a posterior means) were 0.019, 0.01, and 0.035 for a parameter; 0.018, 0.019, and 0.043 for b parameter; and 0.024, 0.1, and 0.058 for c parameter, respectively. These obtained results reveal that the differences between the Bayesian and AI-REML methods in terms of estimation of heritability and variance components were small.

503 Late-Breaking: Using Random Regression Models to Estimate Genetic Parameters for Milk Production Traits under Different Levels of Heat Stress in Canadian Holstein Cattle

Abstract Genetically selecting animals that are heat tolerant can help to maintain production efficiency of the dairy industry under thermal challenges. During the summer months in Canada, dairy cows could be under thermal stress. For instance, in Ontario, cows are expected to be 105 days under thermal stress. The objective of this study was to estimate genetic parameters for milk production traits under heat stress in Canadian Holstein cows. A total of 604,050 test-day records for milk, fat, and protein yields from 78,516 first-lactation Holstein cows were used in this study. The production data was combined with daily maximum temperature-humidity index (THI; ranging from 30 to 83) calculated based on meteorological records from public weather stations. In total, 58 weather stations were located within a maximum distance of 20 km from each of the 1,284 herds included in this study. Single-trait random regressions on THI, fitting linear splines to describe the random additive genetic and permanent environmental effects, were used in the genetic analyses. Based on preliminary analyses, the knots of the spline functions were set to THI = 70, 57, and 58 for milk, fat, and protein yields, respectively. Therefore, the models assumed a linear effect of heat stress beyond the THI threshold, allowing to estimate the additive genetic effect under thermal comfort and at different levels of heat stress. The genetic correlations estimated between thermal comfort and heat stress were -0.09, -0.33, and -0.21 for milk, fat, and protein yields, respectively. This indicates an antagonistic relationship between level of production and heat tolerance. However, small differences in heritability estimates were observed above the THI thresholds (they ranged from 0.20 to 0.22 for milk, 0.18 to 0.15 for fat, and 0.14 to 0.15 for protein yields). This study demonstrates the possibility of genetically selecting for more heat-tolerant animals in Canada.

Genetic parameters of milk production traits in response to a short once-daily milking period in crossbred Holstein × Normande dairy cows

Despite its potential utility for predicting cows' milk yield responses to once-daily milking (ODM), the genetic basis of cow milk trait responses to ODM has been scarcely if ever described in the literature, especially for short ODM periods. This study set out to (1) estimate the genetic determinism of milk yield and composition during a 3-wk ODM period, (2) estimate the genetic determinism of milk yield responses (i.e., milk yield loss upon switching cows to ODM and milk yield recovery upon switching them back to twice-daily milking; TDM), and (3) seek predictors of milk yield responses to ODM, in particular using the first day of ODM. Our trial used 430 crossbred Holstein × Normande cows and comprised 3 successive periods: 1 wk of TDM (control), 3 wk of ODM, and 2 wk of TDM. Implementing ODM for 3 wk reduced milk yield by 27.5% on average, and after resuming TDM cows recovered on average 57% of the milk lost. Heritability estimates in the TDM control period and 3-wk ODM period were, respectively, 0.41 and 0.35 for milk yield, 0.66 and 0.61 for milk fat content, 0.60 and 0.80 for milk protein content, 0.66 and 0.36 for milk lactose content, and 0.20 and 0.15 for milk somatic cell score content. Milk yield and composition during 3-wk ODM and TDM periods were genetically close (within-trait genetic correlations between experimental periods all exceeding 0.80) but were genetically closer within the same milking frequency. Heritabilities of milk yield loss observed upon switching cows to ODM (0.39 and 0.34 for milk yield loss in kg/d and %, respectively) were moderate and similar to milk yield heritabilities. Milk yield recovery (kg/d) upon resuming TDM was a trait of high heritability (0.63). Because they are easy to measure, TDM milk yield and composition and milk yield responses on the first day of ODM were investigated as predictors of milk yield responses to a 3-wk ODM to easily detect animals that are well adapted to ODM. Twice-daily milking milk yield and composition were found to be partly genetically correlated with milk yield responses but not closely enough for practical application. With genetic correlations of 0.98 and 0.96 with 3-wk ODM milk yield losses (in kg/d and %, respectively), milk yield losses on the first day of ODM proved to be more accurate in predicting milk yield responses on longer term ODM than TDM milk yield.

COMPARING GENETIC PARAMETERS OF FRIESIAN MILK PRODUCTION TRAITS IN COMMERCIAL AND STATE FARMS IN EGYPT

This study was conducted to estimate the genetic parameters for milk production traits of Friesian cattle in two selected dairy farms located in the Nile Delta of Egypt. A total of 1438 lactation records during the years2001 to 2009 were collected to represent 472 cows in Sakha Governmentfarm (SF). In comparison, a total of 1660 lactation records during the years 1998 to 2005 were collected to represent 465 cows in Gharbawy commercial (GF) farm. The derivative-free restricted maximum likelihood (REML) procedure was used to determine heritability, genetic correlation and breeding value of the studied traits. The results indicated that non genetic factors affecting lactation period (LP), total milk yield (TMY) and 305d -milk yield (305 d-MY) had highly significant (p < 0.001) effect on those traits except the effect of season of calving on TMY. Interaction between (herd & parity) and the interaction between (herd & parity & season) had highly significant effect (P< 0.001) on all milk production traits. The overall means of LP, TMY and 305-dMY were 313day; 4140kg; 3630 kg, respectively for cows in SF and as the corresponding values in GFwere 369.5day,8820Kg and 7430 kg. Estimates of direct heritability for LP, TMY, and 305MY in SF were 0.10, 0.11and 0.19 respectively, the corresponding estimates for GF were 0.10, 0.13 and 0.07 respectively on the other hand, estimates of maternal heritability for LP,TMY and 305MY in SF were 0.04, 0.07 and 0.06, respectively, while , the estimate in GF were 0.08, 0.09 and 0.12, respectively. The breeding values of sires estimated for LP,TMY and 305d-MY were 50.4, 27.4 and 42.3, respectively in SF, while the same estimates in GF were150.1, 20.04,and 30.7. The breeding values of cow concerning LP, TMY and 305MY in SF were 63.32, 45,4 and 21.5 while in GF, values were 195.1 , 29.9 , 53.2 , respectively . It can be concluded that improving environmental conditions and management practices, coupled with improved genetic potential of dairy animals in the state or commercial farms would be more effective approaches for high milk productivity.

Models for Estimating Genetic Parameters of Milk Production Traits Using Random Regression Models in Korean Holstein Cattle.

The objectives of the study were to estimate genetic parameters for milk production traits of Holstein cattle using random regression models (RRMs), and to compare the goodness of fit of various RRMs with homogeneous and heterogeneous residual variances. A total of 126,980 test-day milk production records of the first parity Holstein cows between 2007 and 2014 from the Dairy Cattle Improvement Center of National Agricultural Cooperative Federation in South Korea were used. These records included milk yield (MILK), fat yield (FAT), protein yield (PROT), and solids-not-fat yield (SNF). The statistical models included random effects of genetic and permanent environments using Legendre polynomials (LP) of the third to fifth order (L3–L5), fixed effects of herd-test day, year-season at calving, and a fixed regression for the test-day record (third to fifth order). The residual variances in the models were either homogeneous (HOM) or heterogeneous (15 classes, HET15; 60 classes, HET60). A total of nine models (3 orders of polynomials×3 types of residual variance) including L3-HOM, L3-HET15, L3-HET60, L4-HOM, L4-HET15, L4-HET60, L5-HOM, L5-HET15, and L5-HET60 were compared using Akaike information criteria (AIC) and/or Schwarz Bayesian information criteria (BIC) statistics to identify the model(s) of best fit for their respective traits. The lowest BIC value was observed for the models L5-HET15 (MILK; PROT; SNF) and L4-HET15 (FAT), which fit the best. In general, the BIC values of HET15 models for a particular polynomial order was lower than that of the HET60 model in most cases. This implies that the orders of LP and types of residual variances affect the goodness of models. Also, the heterogeneity of residual variances should be considered for the test-day analysis. The heritability estimates of from the best fitted models ranged from 0.08 to 0.15 for MILK, 0.06 to 0.14 for FAT, 0.08 to 0.12 for PROT, and 0.07 to 0.13 for SNF according to days in milk of first lactation. Genetic variances for studied traits tended to decrease during the earlier stages of lactation, which were followed by increases in the middle and decreases further at the end of lactation. With regards to the fitness of the models and the differential genetic parameters across the lactation stages, we could estimate genetic parameters more accurately from RRMs than from lactation models. Therefore, we suggest using RRMs in place of lactation models to make national dairy cattle genetic evaluations for milk production traits in Korea.

Genetic parameters for milk production traits and breeding goals for Gir dairy cattle in Brazil.

To implement an animal breeding program, it is important to define the production circumstances of the animals of interest to determine which traits of economic interest will be selected for the breeding goal. The present study defined breeding goals and proposed selection indices for milk production and quality traits of Gir dairy cattle. First, a bioeconomic model was developed to calculate economic values. The genetic and phenotypic parameters were estimated based on records from 22,468 first-lactation Gir dairy cows and their crosses for which calving occurred between 1970 and 2011. Statistical analyses were carried out for the animal model, with multitrait analyses using the restricted maximum likelihood method. Two situations were created in the present study to define the breeding goals: 1) including only milk yield in the breeding goal (HGL1) and 2) including fat and protein in addition to the milk yield (HGL2). The heritability estimates for milk, protein, and fat production were 0.33 ± 0.02, 0.26 ± 0.02, and 0.24 ± 0.02, respectively. All phenotypic and genetic correlations were highly positive. The economic values for milk, fat, and protein were US$0.18, US$0.27, and US$7.04, respectively. The expected economic responses for HGL2 and for HGL1 were US$126.30 and US$79.82, respectively. These results indicate that milk component traits should be included in a selection index to rank animals evaluated in the National Gir Dairy Breeding Program developed in Brazil.

Comparison of different polynomial functions in Random Regression Model for milk production traits of Iranian Holstein dairy cattle

Abstract The aim of this research was to compare different polynomial functions including Legendre polynomials (LP), Wilmink (WRR) and Ali-Schaeffer (ARR) functions, in random regression model (RRM) for estimation of genetic parameters for milk production traits of Iranian Holstein dairy cattle. For this purpose the performance records obtained from test-day (TD) regarding milk yield, fat and protein contents of the cows calving for the first time were used. The numbers of records for the above mentioned traits were 701212, 657004, and 560775, respectively. These records were collected from the years 2006 to 2010 by the National Breeding Center of Iran. The genetic parameters were estimated using Restricted Maximum Likelihood (REML) method by applying RRM. Residual variances were considered homogeneous over the lactation period. To compare the model, different criteria (-2Logl, AIC, BIC and RV) were used for considered traits. Based on the results obtained, for all traits, RRM with LP function (2,5) were chosen as the best model. Considering residual variance (RV), LP (2,2) was proved to be a model which has the lowest performance, while using -2Logl, AIC, BIC criteria, RRM with ARR function was the worst model. According to the results, it is recommended to use LP with low orders for the additive genetic effects and with more orders for the permanent environment effects in the RRM for Iranian Holstein cattle. Permanent environment variance was higher in early lactation than during lactation and additive genetic variance in the early lactation was lower than at the end of lactation. Heritability range of milk yield, fat and protein contents was estimated to be from 0.08 to 0.23, 0.05 to 0.20 and 0.08 to 0.14, respectively. Phenotypic variance of the considered traits during lactation was not constant and it was higher at the beginning and the end of lactation. The additive genetic correlation between adjacent test days was higher than between distant test days.

Genetic parameters of milk production traits and fatty acid contents in milk for Holstein cows in parity 1 – 3

The objective of this study was to estimate genetic parameters of milk, fat, and protein yields, fat and protein contents, somatic cell count, and 17 groups and individual milk fatty acid (FA) contents predicted by mid-infrared spectrometry for first-, second- and third-parity Holstein cows. Edited data included records collected in the Walloon region of Belgium from 37,768 cows in parity 1,22,566 cows in parity 2 and 8221 in parity 3. A total of 69 (23 traits for three parities) single-trait random regression animal test-day models were run. Approximate genetic correlations among traits were inferred from pairwise regressions among estimated breeding values of cow having observations. Heritability and genetic correlation estimates from this study reflected the origins of FA: de novo synthetized or originating from the diet and the body fat mobilization. Averaged daily heritabilities of FA contents in milk ranged between 0.18 and 0.47. Average daily genetic correlations (averaged across days in milk and parities) among groups and individual FA contents in milk ranged between 0.31 and 0.99. The genetic variability of FAs in combination with the moderate to high heritabilities indicated that FA contents in milk could be changed by genetic selection; however, desirable direction of change in these traits remains unclear and should be defined with respect to all issues of importance related to milk FA.

Prospects for genetic improvement of milk production traits of Sahiwal cattle in Kenya

The primary emphasis of the long-term Sahiwal cattle breeding programme is to increase milk yield by selecting cows based on their performance in first three lactations. It is therefore important to have knowledge on the extend of additive genetic variance and genetic parameters for these traits. Genetic and phenotypic parameter estimates normally apply directly to the specific population and environment from which the data were collected. In the Sahiwal cattle in Kenya, very little is known about the genetic variation of milk production traits and their genetic relationships. Furthermore, genetic and phenotypic parameter estimates for the Sahiwal cattle based on multivariate animal model are scarce. This paper presents estimates of variance components and genetic parameters for milk production traits using trivariate animal model.

Genetic Parameters for Yield Traits of Cows Treated or Not Treated with Bovine Somatotropin

The objective of this study was to estimate genetic correlations between yield traits of cows treated with bovine somatotropin (bST) and the same yield traits of untreated cows. Lactation records from registered Holstein cows were divided by parity into 3 data sets: 1, 2, and 3 through 5. Approximately 10% of the records in each data set were from cows treated with bST. The numbers of records of treated and untreated cows in the data sets were 4,337 and 48,765; 3,730 and 37,796; and 3,645 and 33,957. Two-trait animal models (records for cows treated or not treated) were used to estimate genetic parameters for milk production traits and somatic cell score (SCS). Estimates of heritability for milk yield for records of treated and untreated cows for the 3 data sets were 0.13, 0.16, and 0.09, and 0.18, 0.18, and 0.14, respectively, with estimates of repeatability of 0.50 and 0.41 for data set 3. Estimates of heritability for fat yield for records of treated and untreated cows were 0.31, 0.16, and 0.12, and 0.27, 0.21, and 0.16. Estimates of repeatability were 0.50 and 0.43 for data set 3. Heritability estimates for protein yield for records of treated and untreated cows were 0.13, 0.17, and 0.12, and 0.20, 0.23, and 0.16, with estimates of repeatability of 0.52 and 0.47. Estimates of heritability for SCS for treated and untreated cows were 0.08, 0.15, and 0.13, and 0.11, 0.13, and 0.13 with repeatability estimates of 0.52 and 0.45. Estimates of genetic correlations between milk yields with and without bST treatment in lactations 1, 2, and 3 to 5 were all 0.99. Estimates of genetic correlations for fat and protein yields were 0.96 for all data sets. Estimates for SCS were 0.99. Estimates of genetic correlations between records of treated and untreated cows were large enough to conclude that records of treated and untreated cows could be considered to be one trait, with treatment as a fixed effect to account for differences in means.

Estimation of genetic and environmental parameters of milk production traits in Slovak purebred sheep using test-day model

Covariance matrices and genetic parameters for milk production traits in sheep were estimated for the Improved Valachian and Tsigai breeds. These multipurpose breeds are of local importance, and are bred for milk, meat and wool. The traits under study were daily milk yield and fat and protein content. Genetic analyses were based on test-day records gathered over the period from 1995 to 2001. Each breed was analyzed separately. Only purebred animals with at least four test days per lactation were considered. The data set for the Improved Valachian consisted of 117,959 test-day records of 28,753 lactations belonging to 18,867 ewes. The corresponding pedigree comprised information on 32,804 animals. For the Tsigai breed, the data set consisted of 52,191 test-day records of 12,382 lactations belonging to 8,132 ewes and the pedigree comprised 14,576 animals. The three-trait animal model was used for analyses. To account for different lactation stage, a fixed regression on individual test days was employed. In addition to the function describing, effects of days in milk, effects of lactation, litter size, number of milkings per day, age at lambing, and flock-test day as well as additive genetic and permanent environmental effect of the animal were included in the model. Of these, flock-test day, additive genetic and permanent environmental effects were treated as random. Restricted maximum likelihood (REML) algorithm was used to estimate genetic parameters and covariance matrices. Heritabilities were 0.10 and 0.19 for daily milk yield, 0.06 and 0.12 for fat content, 0.07 and 0.17 for protein content for the Improved Valachian and Tsigai breeds, respectively. Genetic correlations between milk yield and fat content for the two breeds were −0.29 and −0.23 and those between milk yield and protein content were −0.30 and −0.27. Genetic correlations between fat and protein content were 0.58 and 0.57. Higher values (either positive or negative) were found for the breed with the larger number of records. Variance ratios and correlations were also estimated for nongenetic effects for both breeds. Variance ratios for the flock-test-day effects were rather high, ranging from 0.34 to 0.48. Higher values for these effects were found in the Improved Valachian sheep, reflecting more variability in management conditions in this breed. The genetic parameters estimated in this study should be used in routine genetic evaluation of milk production traits of local sheep breeds to replace present selection criteria based on phenotype values of dam milk yield.

Genetic and Phenotypic Parameters of Milk Production Traits of Crossbred Cattle in a Selected Farm of Bangladesh

3 Abstract: The study was conducted in Milk and Cattle Improvement Farm, Bogra, Bangladesh from 1995 to 2003 with a view to estimate genetic and phenotypic parameters of crossbred cattle. The reproductive traits considered in the study were services per conception (SPC), age at first heat (AFH), age at first calving (AFC), gestation length (GL), calving interval (CI), post parturition heat (PPH) and birth weight (BW). Heritability was calculated from parental half-sib relationship. The average mean of SPC, AFH, AFC, GL, PPH, CI and BW were 2.76±0.13, 1223.60±62.47, 1751.02±71.79, 277.61±0.58, 105.80±6.08, 554.59±17.85 days and 22.18±0.23 kg, respectively. The heritability estimates of SPC, GL, PPH, CI and BW were 0.08±0.05, 0.31±0.08, 0.14±0.06, 0.38±0.05 and 0.33±0.09, respectively. The repeatability estimates of SPC, GL, PPH and CI were 0.46±0.08, 0.012±0.6, 0.35±0.09 and 0.022±0.04, respectively. The effects of genetic groups on various traits were non-significant except PPH (p<0.001). The results of the study revealed that the Local Crossbred cows are late maturing animals with a long inter-calving interval. High services per conception indicate their poor fertility. However, high magnitude of heritability estimates of some traits indicates additive genetic variance is pronounced and good response to selection can be achieved for these traits.

Genetic parameters for milk production traits in a closed herd of Egyptian buffaloes

Genetic parameters for milk production traits in a closed herd of Egyptian buffaloes