Variance components for test-day milk, fat, and protein yield, and somatic cell score for analyzing management information

Test-day (TD) models are used in most countries to perform national genetic evaluations for dairy cattle. The TD models estimate lactation curves and their changes as well as variation in populations. Although potentially useful, little attention has been given to the application of TD models for management purposes. The potential of the TD model for management use depends on its ability to describe within- or between-herd variation that can be linked to specific management practices. The aim of this study was to estimate variance components for milk yield, milk component yields, and somatic cell score (SCS) of dairy cows in the Ragusa and Vicenza areas of Italy, such that the most relevant sources of variation can be identified for the development of management parameters. The available data set contained 1,080,637 TD records of 42,817 cows in 471 herds. Variance components were estimated with a multilactation, random-regression, TD animal model by using the software adopted by NRS for the Dutch national genetic evaluation. The model comprised 5 fixed effects [region × parity × days in milk (DIM), parity × year of calving × season of calving × DIM, parity × age at calving × year of calving, parity × calving interval × stage of pregnancy, and year of test × calendar week of test] and random herd × test date, regressions for herd lactation curve (HCUR), the animal additive genetic effect, and the permanent environmental effect by using fourth-order Legendre polynomials. The HCUR variances for milk and protein yields were highest around the time of peak yield (DIM 50 to 150), whereas for fat yield the HCUR variance was relatively constant throughout first lactation and decreased following the peak around 40 to 90 DIM for lactations 2 and 3. For SCS, the HCUR variances were relatively small compared with the genetic, permanent environmental, and residual variances. For all the traits except SCS, the variance explained by random herd × test date was much smaller than the HCUR variance, which indicates that the development of management parameters should focus on between-herd parameters during peak lactation for milk and milk components. For SCS, the within-herd variance was greater than the between-herd variance, suggesting that the focus should be on management parameters explaining variances at the cow level. The present study showed clear evidence for the benefits of using a random regression TD model for management decisions.     

Use of herd solutions from a random regression test-day model for diagnostic dairy herd management

In a random regression test-day model, environmental effects in addition to individual animal factors can be included and analyzed. Moreover, instead of herd-year classification of the management groups, the herd-test-day classification within the model better accounts for month-to-month short-term environmental variation in production and somatic cell count (SCC) traits. The herd management levels of milk yield (milk deviation from whole-country mean, kilograms/day), protein and fat concentration (protein and fat deviation, %), and SCC (SCC deviation, 1,000 cells/mL) are used in the dairy herd management Web application “Maitoisa” (in English, “Milky”). This management tool helps to recognize several management problems. For recognition of systematic patterns and single unusual test-days, a monthly time-trend analysis was developed to smooth the random fluctuations and display the yearly production pattern. In addition to analyzing single test-day deviations from the mean, modeled herd solutions assist users in identifying repeated phenomena and enable the forecasting of the management pattern for the subsequent year. The solutions are displayed either as tables or graphs plotted by calendar months. In addition to management effects of the farmer's own herd, he or she can request country or region percentiles to be displayed in the graphs. The Web service has been offered to farmers and dairy advisors since 2001, and it has proved to be a powerful tool for herd monitoring and planning.     

Random herd curves in a test-day model for milk, fat, and protein production of dairy cattle in The Netherlands

With random regression models, genetic parameters of test-day milk production records of dairy cattle can be estimated directly from the data. However, several researchers that used this method have reported unrealistically high variances at the borders of the lactation trajectory and low genetic correlations between beginning and end of lactation. Recently, it has been proposed to include herd-specific regression curves in the random regression model. The objective was to study the effect of including random herd curves on estimated genetic parameters. Genetic parameters were estimated with 2 models; both included random regressions for the additive genetic and permanent environmental effect, whereas the second model also included a random regression effect for herd x 2-yr period of calving. All random regressions were modeled with fourth-order Legendre polynomials. Bayesian techniques with Gibbs sampling were used to estimate all parameters. The data set comprised 857,255 test-day milk, fat, and protein records from lactations 1, 2, and 3 of 43,990 Holstein cows from 544 herds. Genetic variances estimated by the second model were lower in the first 100 d and at the end of the lactation, especially in lactations 2 and 3. Genetic correlations between d 50 and the end of lactation were around 0.25 higher in the second model and were consistent with studies where lactation stages are modeled as different traits. Subsequently, estimated heritabilities for persistency were up to 0.14 lower in the second model. It is suggested to include herd curves in a random regression model when estimating genetic parameters of test-day production traits in dairy cattle.     

Associations of breed and feeding management with milk production curves at herd level using a random regression test-day model

Earlier studies identified large between-herd variation in estimated lactation curve parameters from test-day milk yield and milk composition records collected in Ragusa province, Italy. The objective of this study was to identify sources of variation able to explain these between-herd differences in milk production curves, by estimating associations of animal breed (Holstein Friesian vs. Brown Swiss), feeding system [separate feeding (SF) vs. total mixed ration (TMR)], and TMR chemical composition on milk and milk components herd curves. Data recorded from 1992 through 2007 for test-day (TD) milk, fat, and protein yields from 1,287,019 records of 148,951 lactations of 51,489 cows in 427 herds were processed using a random regression TD model. Random herd curves (HCUR) for milk, fat, and protein yields were estimated from the model per herd, year, and parity (1, 2, and 3+) using 4-order Legendre polynomials. From March 2006 through December 2007, samples of TMR were collected every 3 mo from 37 farms in Ragusa province. Samples were analyzed for dry matter, ash, crude protein, soluble nitrogen, acid detergent lignin, neutral detergent fiber, acid detergent fiber, and starch. Traits used to describe milk production curves were peak, days in milk at peak, persistency, and mean. Association of feeding system and animal breed with HCUR traits was investigated using a general mixed model procedure. Association of TMR chemical composition with HCUR traits was investigated using multivariate analysis with regression and stepwise model selection. Results were consistent for all traits and parities. Feeding system was significantly associated with HCUR peak and mean, with higher values for TMR. Animal breed was significantly associated with HCUR persistency, with higher values for Brown Swiss herds. Furthermore, animal breed influenced HCUR peak and mean, with higher values for Holstein Friesian herds. Crude protein had the largest effect on HCUR peak and mean, whereas the interaction between crude protein and dry matter mainly affected persistency. When provided by a national evaluation system, HCUR can be used as an indicator of herd feeding management.     

Random regression analysis of milk yield and milk composition in the first and second lactations of Murciano-Granadina goats

Records from the milk recording scheme of Spanish Murciano-Granadina goats were studied to estimate genetic (co)variance components and breeding values throughout the first and second lactations. The data used consisted of 49,696 monthly test-day records of milk (MY), protein (PY), fat (FY), and dry matter (DMY) yields from 5,163 goats, distributed in 20 herds, offspring of 2,086 does and 206 bucks. These records were analyzed by 2-trait random regression models (RRM) and a repeatability test-day model (RTDM). At the middle of lactation, heritability estimates for MY, DMY, and FY obtained with RTDM were larger than those estimated with RRM, and the opposite was true for PY. The RRM estimates of heritability for MY, FY, and PY were very similar throughout the trajectories of both lactations. Heritability estimates for DMY decreased through the lactation period. The genetic correlations between the first and second lactation records estimated for all traits by RRM were positive and ranged from 0.43 to 0.80 throughout the lactation curves. The correlation between BV estimated with RTDM and RRM was 0.742 for MY and 0.664 for DMY. The RRM could be a useful alternative to RTDM for the prediction of BV in this breed.     

Comparison of random regression test-day models for Polish Black and White cattle

Test-day milk yields of first-lactation Black and White cows were used to select the model for routine genetic evaluation of dairy cattle in Poland. The population of Polish Black and White cows is characterized by small herd size, low level of production, and relatively early peak of lactation. Several random regression models for first-lactation milk yield were initially compared using the “percentage of squared bias” criterion and the correlations between true and predicted breeding values. Models with random herd-test-date effects, fixed age-season and herd-year curves, and random additive genetic and permanent environmental curves (Legendre polynomials of different orders were used for all regressions) were chosen for further studies. Additional comparisons included analyses of the residuals and shapes of variance curves in days in milk. The low production level and early peak of lactation of the breed required the use of Legendre polynomials of order 5 to describe age-season lactation curves. For the other curves, Legendre polynomials of order 3 satisfactorily described daily milk yield variation. Fitting third-order polynomials for the permanent environmental effect made it possible to adequately account for heterogeneous residual variance at different stages of lactation.     

Cumulative discounted expressions of sire genotypes for the complex vertebral malformation and beta-casein loci in commercial dairy herds

Based on discounted gene-flow principles, a set of recursive equations was developed to quantify the value of using sires with a specific genotype for an identified gene in a commercial dairy herd. Two examples were used to demonstrate the usefulness of the method. The first example deals with the implications of using sires that are known carriers of the lethal recessive genetic defect, complex vertebral malformation (CVM). The second example examines the value of using sires homozygous for the A2 allele of β-casein. Results are presented in terms of cumulative discounted expressions. These are then multiplied by the economic values of specific genotypes to determine the cost or benefit of using these sires. In general, the degree of mortality and the required price reduction for carrier sires increased as the proportion of carrier sires used, the duration of sire use, and the initial frequency in the cow herd increased. A semen discount of £3.10 per CVM straw used would be required to offset the expected mortality when 20% of CVM carrier sires are used for 3 yr when 5% of cows are carriers. The cumulative discounted expressions’ of using sires homozygous for the A2 allele of β-casein also increased when the proportion and duration of carrier sire use and the initial frequency of the A2 allele increased. Assuming an A2A2 cow is worth £160 more than a non-A2A2 cow, the expected benefit of using A2A2 sires in a 100-cow herd for 5 yr would be £57,120 for a 20-yr planning horizon. The results of this study demonstrate how the starting gene frequency in the herd, and the proportion and duration of use of sires of particular genotypes are critical to the economic implications of using single genes in commercial dairy farms.     

Genetic analysis of milk production traits of polish black and white cattle using large-scale random regression test-day models

Genetic parameters for milk, fat, and protein yield and persistency in the first 3 lactations of Polish Black and White cattle were estimated. A multiple-lactation model was applied with random herd-test-day effect, fixed regressions for herd-year and age-season of calving, and random regressions for the additive genetic and permanent environmental effects. Three data sets with slightly different edits on minimal number of days in milk and the size of herd-year class were used. Each subset included more than 0.5 million test-day records and more than 58,000 cows. Estimates of covariance components and genetic parameters for each trait were obtained by Bayesian methods using the Gibbs sampler. Due to the large size and a good structure of the data, no differences in estimates were found when additional criteria for record selection were applied. More than 95% of the genetic variance for all traits and lactations was explained by the first 2 principal components, which were associated with the mean yield and lactation persistency. Heritabilities of 305-d milk yield in the first 3 lactations (0.18, 0.16, 0.17) were lower than those for fat (0.12, 0.11, 0.12) and protein (0.13, 0.14, 0.15). Estimates of daily heritabilities increased in general with days in milk for all traits and lactations, with no apparent abnormalities at the beginning or end of lactation. Genetic correlations between yields in different lactations ranged from 0.74 (fat yield in lactations 1 and 3) to 0.89 (milk yield in lactations 2 and 3). Persistency of lactation was defined as the linear regression coefficient of the lactation curve. Heritability of persistency increased with lactation number for all traits and genetic correlations between persistency in different lactations were smaller than those for 305d yield. Persistency was not genetically correlated with the total yield in lactation.     

An autoregressive repeatability animal model for test-day records in multiple lactations

Test-day (TD) models are becoming a standard for genetic evaluation of production traits in dairy cattle. Various approaches to model covariances between TD records include random regression, autoregressive repeatability, orthogonal polynomials, and models based on character processing. The applicability of these models is mainly associated with the number of parameters to estimate, incorporation of multiple lactations, and the accuracy of correlations generated by the cow's repeated expression of milking performance (TD yields) within and across lactations. We define and evaluate a multiple-lactation, autoregressive-repeatability model that disentangles environmental effects due to cow within and between lactations. Simulated records either included or ignored a long-term environmental effect between lactations. Our autoregressive TD animal model correctly detected presence and the absence of this effect and accurately recovered the assumed variance components and correlations underlying the data (10 parameters for three lactations). Estimates of variance components and autocorrelation coefficients were obtained using DFREML-simplex methodology. Given the value of this approach to reduce the size of residual variance components, autoregressive animal models are a preferable alternative to classical methods based on cumulative lactation yield to improve milk production in dairy cattle.     

Genetic parameters for tunisian holsteins using a test-day random regression model

Genetic parameters of milk, fat, and protein yields were estimated in the first 3 lactations for registered Tunisian Holsteins. Data included 140,187; 97,404; and 62,221 test-day production records collected on 22,538; 15,257; and 9,722 first-, second-, and third-parity cows, respectively. Records were of cows calving from 1992 to 2004 in 96 herds. (Co)variance components were estimated by Bayesian methods and a 3-trait-3-lactation random regression model. Gibbs sampling was used to obtain posterior distributions. The model included herd × test date, age × season of calving × stage of lactation [classes of 25 days in milk (DIM)], production sector × stage of lactation (classes of 5 DIM) as fixed effects, and random regression coefficients for additive genetic, permanent environmental, and herd-year of calving effects, which were defined as modified constant, linear, and quadratic Legendre coefficients. Heritability estimates for 305-d milk, fat and protein yields were moderate (0.12 to 0.18) and in the same range of parameters estimated in management systems with low to medium production levels. Heritabilities of test-day milk and protein yields for selected DIM were higher in the middle than at the beginning or the end of lactation. Inversely, heritabilities of fat yield were high at the peripheries of lactation. Genetic correlations among 305-d yield traits ranged from 0.50 to 0.86. The largest genetic correlation was observed between the first and second lactation, potentially due to the limited expression of genetic potential of superior cows in later lactations. Results suggested a lack of adaptation under the local management and climatic conditions. Results should be useful to implement a BLUP evaluation for the Tunisian cow population; however, results also indicated that further research focused on data quality might be needed.     

A survey on antibiotic usage in dairy herds in Pennsylvania

A survey was conducted (July 2001 to June 2002) on antibiotic usage of 113 dairy herds from 13 counties in Pennsylvania. Fifty percent of dairy farms surveyed maintained antibiotic treatment records. Only 21% of dairy producers had written plans for treating sick animals. Thirty-two percent of dairy producers sought veterinarian advice before administering antibiotics and on most farms (93%), antibiotics were administered by the owner/manager or designated herdsman. Twenty-four percent of the dairy producers said they always completed the course of antibiotic treatment. Any extra-label use of antibiotics was administered only on the guidelines of a veterinarian on majority of the farms. Comprehensive records from 33 dairy farms indicated that antibiotic usage was largest for calves with enteritis (36%) followed by pneumonia in calves (25%) and foot rot in cattle (16%). Twenty-four antibiotics including beta-lactams, spectinomycin, florfenicol, and tetra-cyclines were used on these farms. Beta-lactam antibiotics were used mostly for dry cow therapy, clinical mastitis, and on some farms for pneumonia and metritis. On 18% of the dairy herds surveyed, ceftiofur was used in an extra-label manner to treat mastitis in lactating cattle. On 70% of farms, calves were fed medicated milk replacers containing oxytetracycline and neomycin. The results of this study suggest that antibiotics are used extensively on dairy herds for both therapeutic and prophylactic purposes. Beta-lactams and tetracyclines were the most widely used antibiotics. There is considerable variation in the management practices associated with antibiotic use on dairy farms. It is anticipated that the findings of this survey will permit developing new strategies for prudent use of antibiotics on dairy herds.     

Heritability and genetic correlations of test day milk yield and composition,individual laboratory cheese yield,and somatic cell count for dairy ewes

Genetic parameters for milk yield, contents of fat, total protein, casein and serum protein, individual laboratory cheese yield, and somatic cell counts (SCC) were estimated from 7492 monthly test-day records of 1119 Churra ewes. Estimates were from multivariate REML using analytical gradients (AG-REML) procedures. Except for fat content, estimates for the other routinely recorded traits (milk yield, protein content, and SCC) agreed with those previously obtained in this and other dairy sheep populations. Protein content and composition had the highest heritabilities and repeatabilities. Heritabilities for protein and casein contents were very similar (0.23 and 0.21, respectively), and genetic correlation between the traits was close to unity (0.99). Accordingly, casein content is not advisable as an alternative to protein content as a selection criterion in dairy ewes; it does not have any compelling advantages and costs more to measure. Individual laboratory cheese yield (ILCY) obtained with Churra ewes had a low heritability (0.08), suggesting that potential for selection for this parameter would be possible but is not recommended. All correlations with ILCY were high and positive except for milk yield. A high SCC was accompanied by an increase in serum protein content and involved a loss in milk yield.     

Management,operational, animal health,and economic characteristics of large dairy herds in 4 states in the Upper Midwest of the United States

Recent trends in dairy farm structure in the United States have included a decreasing number of farms, although farm size has increased, especially the share of milk production from very large herds (>2,500 cows). The objectives of this observational study were to describe common management practices; to characterize labor and operational structure; to measure some aspects of animal health, including lameness, hock lesions, mortality, and mastitis incidence; and to summarize cost of production on farms with more than 2,500 cows in 4 states in the Upper Midwest of the United States. The study included 15 dairy farms in Minnesota, Wisconsin, Iowa, and South Dakota. Farms were visited twice, once each year, and on-farm herd records were collected for those 2 yr. On-farm herd records were used to investigate mortality, culling, pregnancy rate, and clinical mastitis incidence. At least 1 high-producing pen of mature cows and 1 pen of fresh cows were scored for locomotion. Likewise, at least 1 pen of high-producing mature cows was scored for cleanliness and hock lesions. Median herd size was 3,975 cows (range = 2,606–13,266). Milk sold per employee was 1,120,745 kg and the number of cows per employee was 105. Eighty percent of the farms had Holstein cows, 13% had Jersey, and 7% had Jersey-Holstein crosses. All farms used artificial insemination as the sole form of breeding and 100% of the farms used hormonal synchronization or timed artificial insemination programs in their reproductive protocols; 21-d pregnancy rate was 21.7%. Median lameness prevalence was 18.3% and median severe lameness prevalence was 5.1%. Median hock lesion prevalence was 17.4% and median severe hock lesion prevalence was 1.9%; mortality rate was 7.4%. Clinical mastitis incidence was 62.5 cases per 100 cow-years. Feed costs accounted for approximately 53% of the total cost of producing milk, followed by labor at 11%, interest and depreciation expenses at 10%, and replacement costs at 9.5%. Herds in the top 50th percentile for profitability had a net income of $2.40 per hundredweight of milk sold compared with $0.95 per hundredweight for herds in the bottom 50th percentile. Although results of this study were helpful in understanding how large dairy systems operate in the Upper Midwest, more research is yet needed with a larger number of farms and wider variety of management practices to identify factors within these large farms that promote optimal animal health and profitability.     

Interrelationships between herd-level reproductive performance measures based on intervals from initiation of the breeding program in year-round and seasonal calving dairy herds

In year-round calving herds, reproductive performance has traditionally been described in relation to each cow's calving date. This research described reproductive performance in year-round and seasonal calving dairy herds using herd-level measures based on interval from each cow's initiation of breeding program date, and assessed interrelationships between such measures. A large, prospective, single cohort study, implemented in 1997 and 1998, included 29,327 cows from 167 Australian dairy herds. Herd reproductive performance was described using 2 measures of primary importance to herd managers: the proportion of cows that became pregnant by 6 wk after their initiation of breeding program date (6-wk pregnancy rate) and the proportion of cows that were nonpregnant 21 wk after their initiation of breeding program date (21-wk nonpregnancy rate). Measures that contribute to these primary measures (secondary measures) were calculated for each herd for both the first and second 3-wk periods of each cow's breeding program; submission rates were calculated as proportions of cows that were inseminated at least once in the 3-wk period, and conception rates were calculated as the proportions of inseminations in the 3-wk period that resulted in pregnancy. The individual herd was the unit of analysis. The study results indicate that high submission rates are essential if herd reproductive performance is to be achieved. Six-week pregnancy rate was predicted to increase by 6 to 8 percentage points following a 10-percentage-point increase in submission rates in both 3-wk periods, and by 6 to 10 percentage points following a 10-percentage-point increase in conception rates. Submission rates were more variable than conception rates, indicating that managers may be able to achieve large increases in submission rates more easily than substantial increases in conception rates. However, the predicted benefits of increasing submission rates were greatest when conception rates were high and vice versa, highlighting the need to improve both submission and conception rates when both are low. The study results indicate that some herd managers can concurrently achieve high submission and conception rates.     

Differences between performance of F1 crossbreds and Holsteins at different production levels

Crossbreeding in dairy cattle has recently become of increased interest. However, farmers in Scandinavian countries are reluctant to implement crossbreeding in their herds, and one reason is the common opinion that only herds at a poor level of management can benefit from crossbreeding. The Danish Cattle Database (SEGES, Aarhus, Denmark) provided data on 14 traits regarding milk yield, udder health, fertility traits, stillbirth, and survival. The data were collected from 103,307 pure Holstein cows and 14,832 F₁ crosses (Holstein dam and Nordic Red sire). The cows were born between 2008 and 2014 and originated from 424 herds that contributed data from at least 5 purebreds and 5 crossbreds across the years. We split the animals into 3 production levels: high, average, and low according to the herd's average production (kg) of 305-d fat plus protein in the given birth year of the cow. We estimated least squares means of breed group (purebred and crossbred) performance within each production level. Crossbred performance in 305-d fat yield in first-parity cows was greater than that of Holstein across all herd production levels; the gain was greater in high- (9 kg more than Holstein) and average-producing herds (7 kg more than Holstein) than in low-producing herds (3 kg more than Holstein). Regardless of production level or parity, crossbreds did not outperform Holstein in terms of 305-d protein yield (0 to 8 kg less). Crossbreds had relatively better udder health than Holstein in both first and second parity (up to 15% less mastitis) within any of the production levels. In terms of fertility, stillbirth, and survival, crossbreds performed better than purebreds, and improved performance was independent of herd production level. We conclude that differences in performance between F₁ crossbreds and Holstein are independent of production level.     

A stochastic model simulating pathogen-specific mastitis control in a dairy herd

The objective of this study was to develop a model simulating mastitis control in dairy herds and to investigate how sensitive the model is when varying the effect parameters according to the uncertainty. The model simulates 9 pathogen-specific mastitis types, each of which can be subclinical or clinical. The clinical cases can be 1 of 4 severities defined according to the effect of the mastitis case: mild, moderate, severe, and permanent effect. The risk factors include lactation stage, parity, yield level, previous diseases, season, and contagious spread of the infection from herd mates. Occurrence of mastitis is modeled to have direct effects on feed intake, body weight, milk yield, somatic cell count in the milk, subsequent mastitis cases within the cow and in herd mates, voluntary and involuntary culling, mortality, and milk withdrawal. Thirty-five scenarios were simulated to study model behavior and model sensitivity. The consequences per cow/yr of mastitis in the default simulated herd included 0.42 clinical mastitis occurrences, 0.56 subclinical mastitis occurrences, loss of 385-kg milk yield, a 1.3% reduced feed intake, 61-kg milk withdrawal and €146 in reduced economic net return. Based on scenarios demonstrating model behavior and sensitivity analysis, the model appears to produce valid consequences of mastitis control strategies. Representation of the effect of subclinical mastitis and of variation in mastitis severity was concluded in this study to be important when modeling mastitis economics in a dairy herd. The model offers the opportunity to study the long-term herd specific effects of a wide range of control strategies against mastitis.