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.     

Genotype by environment interaction for somatic cell score across bulk milk somatic cell count and days in milk

The objective of this paper was to investigate the importance of a genotype × environment interaction (G × E) for somatic cell score (SCS) across levels of bulk milk somatic cell count (BMSCC), number of days in milk (DIM), and their interaction. Variance components were estimated with a model including random regressions for each sire on herd test-day BMSCC, DIM, and the interaction of BMSCC and DIM. The analyzed data set contained 344,029 test-day records of 24,125 cows, sired by 182 bulls, in 461 herds comprising 13,563 herd test-days. In early lactation, considerable G × E effects were detected for SCS, indicated by 3-fold higher genetic variance for SCS at high BMSCC compared with SCS at low BMSCC, and a genetic correlation of 0.72 between SCS at low and at high BMSCC. Estimated G × E effects were smaller during late lactation. Genetic correlations between SCS at the same level of BMSCC, across DIM, were between 0.43 and 0.89. The lowest genetic correlation between SCS measures on any 2 possible combinations of BMSCC and DIM was 0.42. Correlated responses in SCS across BMSCC and DIM were, on some occasions, less than half the direct response to selection in the response environment. Responses to selection were reasonably high among environments in the second half of the lactation, whereas responses to selection between environments early and late in lactation tended to be low. Selection for reduced SCS yielded the highest direct response early in lactation at high BMSCC.     

Relationships between milk yield and somatic cell score in Canadian Holsteins from simultaneous and recursive random regression models

Multiple-trait random regression animal models with simultaneous and recursive links between phenotypes for milk yield and somatic cell score (SCS) on the same test day were fitted to Canadian Holstein data. All models included fixed herd test-day effects and fixed regressions within region-age at calving-season of calving classes, and animal additive genetic and permanent environmental regressions with random coefficients. Regressions were Legendre polynomials of order 4 on a scale from 5 to 305 d in milk (DIM). Bayesian methods via Gibbs sampling were used for the estimation of model parameters. Heterogeneity of structural coefficients was modeled across (the first 3 lactations) and within (4 DIM intervals) lactation. Model comparisons in terms of Bayes factors indicated the superiority of simultaneous models over the standard multiple-trait model and recursive parameterizations. A moderate heterogeneous (both across- and within-lactation) negative effect of SCS on milk yield (from −0.36 for 116 to 265 DIM in lactation 1 to −0.81 for 5 to 45 DIM in lactation 3) and a smaller positive reciprocal effect of SCS on milk yield (from 0.007 for 5 to 45 DIM in lactation 2 to 0.023 for 46 to 115 DIM in lactation 3) were estimated in the most plausible specification. No noticeable differences among models were detected for genetic and environmental variances and genetic parameters for the first 2 regression coefficients. The curves of genetic and permanent environmental variances, heritabilities, and genetic and phenotypic correlations between milk yield and SCS on a daily basis were different for different models. Rankings of bulls and cows for 305-d milk yield, average daily SCS, and milk lactation persistency remained the same among models. No apparent benefits are expected from fitting causal phenotypic relationships between milk yield and SCS on the same test day in the random regression test-day model for genetic evaluation purposes.     

Bivariate analysis of conception rates and test-day milk yields in Holsteins using a threshold-linear model with random regressions

The objective of this study was to estimate genetic correlations between conception rates (CR) and test-day (TD) milk yields in Holsteins for different days in milk (DIM) in small and large herds. The data included 217,213 first-parity service records of 94,984 cows in New York State between 1999 and 2003. The CR was defined as the outcome of a single insemination. Conception rate and TD milk were analyzed using a series of threshold-linear models with fixed effects that included herd-test-date for TD milk and herd-year for CR, age, service month, cubic regressions on DIM using Legendre polynomials and with random effects that included herd × sire interaction, sire additive genetic and permanent environments with quadratic random regressions on DIM, service sire for CR, and residual. Variance components were estimated using a Bayesian method via Gibbs sampling. Herds were categorized into small (≤80 cows) and large operations. Large herds produced a higher TD milk (34.0 vs. 30.8 kg), had lower CR (29.5 vs. 34.4%), began breeding earlier (75 vs. 92 d to first service), and had fewer days open (138 vs. 145 d). The average CR was 20% at 50 DIM, increased to about 38% at DIM 100, and then leveled off. Estimated genetic correlations between CR and TD milk stayed around −0.15 for small herds but changed from positive (0.3) at 60 DIM to negative (−0.3) at 120 DIM for large herds. Genetic correlations for CR between small and large herds were highest at 80 DIM and lowest at 140 DIM. The chi-square test showed that the frequency of service records was significantly different during a given week for 71% of large herds and for 15% of small herds, suggesting more timed artificial insemination services in large herds. For the top 15% of cows for milk, fertility peaked around 100 DIM in large herds and at around 100 and 170 DIM in small herds. It seems that optimum breeding practices in large herds of breeding cows earlier are already followed.     

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.     

Dynamics of culling for Jersey,Holstein, and Jersey × Holstein crossbred cows in large multibreed dairy herds

The objective of this observational study was to describe and compare the dynamics of reason-specific culling risk for the genetic groups Jerseys (JE), Holsteins (HO), and Jersey × Holstein crossbreds (JH), considering parity, stage of lactation, and milk yield, among other variables, in large multibreed dairy herds in Texas. The secondary objective was to analyze the association between survival and management factors, such as breeding and replacement policies, type of facilities, and use of cooling systems. After edits, available data included 202,384 lactations in 16 herds, ranging from 407 to 8,773 cows calving per year during the study period from 2007 to 2011. The distribution of lactation records by genetic group was 58, 36, and 6% for HO, JE, and JH crosses, respectively. Overall culling rates across breeds were 30.1, 32.1, and 35.0% for JH, JE, and HO, respectively. The dynamics of reason-specific culling were dependent on genetic group, parity, stage of lactation, milk yield, and herd characteristics. Early lactation was a critical period for “died” and “injury-sick” culling. The risk increased with days after calving for “breeding” and, in the case of HO, “low production” culling. Open cows had a 3.5 to 4.6 times greater risk for overall culling compared with pregnant cows. The odds of culling with reason “died” within the first 60 d in milk (DIM) were not significantly associated with genetic group. However, both JE and JH crosses had lower odds of live culling within the first 60 DIM compared with HO cows (OR = 0.72 and 0.82, respectively). Other cow variables significantly associated with the risk of dying within the first 60 DIM were cow relative 305-d mature equivalent (305ME) milk yield, parity, and season of calving. Significant herd-related variables for death included herd size and origin of replacements. In addition to genetic group, the risk of live culling within 60 DIM was associated with cow-relative 305ME milk yield, parity, and season of calving. Significant herd-related variables for live culling included herd-relative 305ME milk yield, herd size, type of facility, origin of replacement, and type of maternity. Overall, reason-specific culling followed similar patterns across DIM in the 3 genetic groups.     

Random regression test-day model for clinical mastitis: Genetic parameters,model comparison,and correlations with indicator traits

The objective was to study genetic (co)variance components for binary clinical mastitis (CM), test-day protein yield, and udder health indicator traits [test-day somatic cell score (SCS) and type traits of the udder composite] in the course of lactation with random regression models (RRM). The study used a data set from selected 15 large-scale contract herds including 26,651 Holstein cows. Test-day production and CM data were recorded from 2007 to 2012 and comprised parities 1 to 3. A longitudinal CM data structure was generated by assigning CM records to adjacent official test dates. Bivariate threshold-linear RRM were applied to estimate genetic (co)variance components between longitudinal binary CM (0 = healthy; 1 = diseased) and longitudinal Gaussian distributed protein yield and SCS test-day data. Heritabilities for liability to CM (heritability ~0.15 from 0 to 305 d after calving) were slightly higher than for SCS for corresponding days in milk (DIM) in the course of lactation. Daily genetic correlations between CM and SCS were moderate to high (genetic correlation ~0.70), but substantially decreased at the very end of lactation. Genetic correlations between CM at different test days were close to 1 for adjacent test days, but were close to zero for test days far apart. Daily genetic correlations between CM and protein yield were low to moderate. For identical DIM (e.g., DIM 20, 160, and 300), genetic correlations were −0.03, 0.11, and 0.18, respectively, and disproved pronounced genetic antagonisms between udder health and productivity. Correlations between estimated breeding values (EBV) for CM from the RRM and official EBV for linear type traits of the udder composite, including EBV from 74 influential sires (sires with >60 daughters), were −0.31 for front teat placement, −0.01 for rear teat placement, −0.31 for fore udder attachment, −0.32 for udder depth, and −0.08 for teat length. Estimated breeding values for CM from the RRM were compared with EBV from a multiple-trait model and with EBV from a repeatability model. For test days covering an identical time span and on a lactation level, correlations between EBV from RRM, multiple-trait model, and repeatability model were close to 1. Most relevant results suggest the routine application of threshold RRM to binary CM to (1) allow selection of genetically superior sires for distinct stages of lactation and (2) achieve higher selection response in CM compared with selection strategies based on indicator type traits or based on the indicator-trait SCS.     

Effect of prepartum dry cow antibiotic treatment in dairy heifers on udder health and milk production

A high percentage of heifers calve with intramammary infections. One of the measures available to control intramammary infections is treatment with antibiotics before calving. In this study, the effects of prepartum treatment of nonlactating heifers with a 600-mg cloxacillin dry cow treatment on the prevalence of culture-positive milk samples at calving and 10 to 14 d in milk (DIM), the incidence of clinical mastitis, somatic cell count (SCC), and milk production during first lactation were quantified. A total of 184 heifers on 13 dairy farms were treated with antibiotics 8 to 10 wk before the expected calving date. Another 185 heifers served as untreated controls. Coagulase-negative staphylococci were the most frequently isolated group of bacteria in the treatment and control groups at calving (32 and 42%), and at 10 to 14 DIM (15 and 19%), respectively. The prevalence of minor pathogens at calving was lower in the treatment group compared with the control group (34 and 43%, respectively). Staphylococcus aureus was the most frequently isolated major pathogen in the treated and control heifers at calving (4 and 5%) and at 10 to 14 DIM (2 and 3%), respectively. The prevalence of major pathogens was lower in the treated heifers at 10 to 14 DIM compared with the control group (4 and 6%, respectively). Cumulative incidence risk of clinical mastitis during the lactation was 9 and 18% in the treatment and control groups, respectively. Treatment with cloxacillin 8 to 10 wk before calving resulted in a lower prevalence of culture-positive milk samples at calving and lower quarter milk SCC in early lactation [30,000 ± 4,600 (standard deviation) cells/mL in treated heifers versus 40,000 ± 4,600 cells/mL in control heifers], and was associated with lower average test-day SCC (55,000 ± 1,400 cells/mL in treated heifers versus 71,000 ± 1,500 cells/mL in control heifers) and lower incidence of clinical mastitis throughout lactation. The improved udder health resulted in a higher average test-day milk production in the first lactation (24.5 ± 3.2 kg in treated heifers versus 23.6 ± 3.1 kg in control heifers). Dairy farms with heifer mastitis problems need to analyze their mastitis management. Prepartum treatment of heifers with dry cow antibiotics may be helpful by decreasing the prevalence of mastitis-causing pathogens at calving and at 10 to 14 DIM.     

Mortality, Culling by Sixty Days in Milk, and Production Profiles in High- and Low-Survival Pennsylvania Herds

The objectives were to describe culling patterns and reasons for culling across lactation, estimate mortality and the proportion of cows leaving from 21 d before an expected calving date through 60 d in milk (DIM; CULL60) for Pennsylvania (PA) dairy herds, and to describe production measures for herds with high and low mortality and CULL60. Weekly culling frequencies and reasons for culling from 3 wk before a reported expected calving date through ≥100 wk of lactation were calculated for all PA cows with at least 1 Dairy Herd Improvement test in 2005. It was estimated that at least 5.0% of PA dairy cows died in 2005, and that at least 7.6% were culled by 60 DIM. The majority of cows exiting the herd by 60 DIM either died (35.1%) or had a disposal code of injury/other (29.9%). A total of 137,951 test-day records from 20,864 cows in herds with high mortality (>8.0%) and CULL60 (>12.0%) and 136,906 test-day records from 12,993 cows in herds with low mortality (<1.4%) and CULL60 (<2.9%) were retained to describe differences among herds with high and low survival. Least squares means for weekly milk yield, fat and protein percentages, and somatic cell score (SCS) were estimated with a model that included fixed effects for herd environment (high or low survival) and week nested within herd environment and lactation; random effects were cow, herd-test-day, and error. Cows from herds with high mortality and CULL60 produced more milk in lactations 1 (+1.9 ± 0.15 kg/d) and 2 (+0.9 ± 0.16 kg/d), but less in lactations 4 (−0.7 ± 0.22 kg/d), 5 (−1.4 ± 0.29 kg/d), and ≥6 (−0.7 ± 0.32 kg/d) and had higher SCS (+0.24 ± 0.02), more change in early-lactation fat percentage (−1.77% vs. −1.59%), and a greater frequency of fat-protein inversions (3.6 ± 0.3%). There is an opportunity to manipulate management practices to reduce mortality and early-lactation culling rates, which will improve cow welfare and the efficiency of dairy production by capturing a greater proportion of potential lactation milk yield, increasing cow salvage values, and reducing replacement costs.     

Use of test-day records beyond three hundred five days for estimation of three hundred five-day breeding values for production traits and somatic cell score of Canadian Holsteins

The Canadian Test-Day Model includes test-day (TD) records from 5 to 305 d in milk (DIM). Because 60% of Canadian Holstein cows have at least one lactation longer than 305 d, a significant number of TD records beyond 305 DIM could be included in the genetic evaluation. The aim of this study was to investigate whether TD records beyond 305 DIM could be useful for estimation of 305-d estimated breeding value (EBV) for milk, fat, and protein yields and somatic cell score. Data were 48,638,184 TD milk, fat, and protein yields and somatic cell scores from the first 3 lactations of 2,826,456 Canadian Holstein cows. All production traits were preadjusted for the effect of pregnancy. Subsets of data were created for variance-component estimation by random sampling of 50 herds. Variance components were estimated using Gibbs sampling. Full data sets were used for estimation of breeding values. Three multiple-trait, multiple-lactation random regression models with TD records up to 305 DIM (M305), 335 DIM (M335), and 365 DIM (M365) were fitted. Two additional models (M305a and M305b) used TD records up to 305 DIM and variance components previously estimated by M335 and M365, respectively. The effects common to all models were fixed effects of herd × test-date and DIM class, fixed regression on DIM nested within region × age × season class, and random regressions for additive genetic and permanent environmental effects. Legendre polynomials of order 6 and 4 were fitted for fixed and random regressions, respectively. Rapid increase of additive genetic and permanent environmental variances at extremes of lactations was observed with all 3 models. The increase of additive genetic and permanent environmental variances was at earlier DIM with M305, resulting in greater variances at 305 DIM with M305 than with M335 and M365. Model M305 had the best ability to predict TD yields from 5 through 305 DIM and less error of prediction of 305-d EBV than M335 and M365. Model M335 had smaller change of 305-d EBV of bulls over the period of 7 yr than did M305 and M365. Model M305a had the least error of prediction and change of 305-d EBV from all models. Therefore, the use of TD records of Holstein cows from 5 through 305 DIM and variance components estimated using records up to 335 DIM is recommended for the Canadian Test-Day Model.     

Effect of increased milking frequency in early lactation with or without recombinant bovine somatotropin

Multiparous Holstein cows (n = 300) were assigned to 1 of 2 milking frequency treatments at parturition. Cows were either milked 6 times (6×) or 3 times (3×) daily to determine effects on early lactation milk yields and subsequent lactation persistency with or without use of recombinant bST (rbST). Treatments included a control group milked 3× and 3 groups milked 6× for either the first 7, 14, or 21 days in milk (DIM). Those 4 groups of cows all received rbST starting at 63 DIM. The fifth treatment group was also milked 6× for the first 21 DIM but those cows received no rbST during the entire lactation. All cows returned to 3× milking after their respective treatment periods ended. Cows milked 3× tended to produce more milk (43.2 vs. 41.5 and 41.0 ± 1.1 kg/d) during the first 9 wk of lactation compared with cows milked 6× for 7 or 21 DIM, respectively. Group milk yields after wk 9 averaged 38.3 ± 0.7 kg/d and did not differ among various groups assigned to an increased milking frequency in early lactation. Percentages of milk fat (3.8 ± 0.12%) and protein (2.9 ± 0.06%) did not differ among treatments during the first 9 wk after calving. Early lactation milk yield (41.9 ± 1.2 kg/d) did not differ between the 2 groups of cows milked 6× for 21 DIM. However, cows subsequently administered rbST (at 63 DIM) produced more milk (38.8 vs. 34.2 ± 0.9 kg/d) from wk 10 to 44. The number of cows sent to the hospital during the 305-d trial for mastitis (97), digestive disorders (14), respiratory issues (9), lameness (22), or retained placenta (16), were not affected by treatments (χ² = 0.49). Under the conditions of this commercial dairy herd in Arizona, increasing milking frequency to 6 times daily for 7 to 21 d at the start of lactation conditions did not increase milk yield nor improve lactation persistency.     

A model for the genetic evaluation of number of clinical mastitis cases per lactation in Czech Holstein cows

Cases of mastitis from 9,550 lactations of 6,242 cows were recorded on 5 farms in the Czech Republic from 1996 to 2008. The number of clinical mastitis (CM) cases per cow adjusted to a lactation length of 305 d was analyzed with 4 linear single-trait animal models and one 3-trait model, which also included lactation mean somatic cell score (SCS) and 305-d milk yield. Factors included in the model of choice were parity, combined effect of herd and a 2-yr calving period, calving season, permanent environmental effect of the cow, and additive genetic effect of the cow. From both the single-trait and multiple-trait models, estimated heritability of number of CM cases was 0.11 (±0.015 for the multiple-trait model). Permanent environmental effects accounted for approximately one-third of the phenotypic variance. Heritability estimates for lactation mean SCS and 305-d milk yield were 0.17 ± 0.019 and 0.25 ± 0.011, respectively, and genetic correlations of these traits with number of CM cases were 0.80 ± 0.059 and 0.34 ± 0.079, respectively. Genetic evaluation of the number of CM cases in Czech Holsteins could be carried out including data from all parities using a 3-trait animal model with SCS and milk yield as additional traits.     

Genetic correlations between the cumulative pseudo-survival rate,milk yield,and somatic cell score during lactation in Holstein cattle in Japan using a random regression model

Trends in genetic correlations between longevity, milk yield, and somatic cell score (SCS) during lactation in cows are difficult to trace. In this study, changes in the genetic correlations between milk yield, SCS, and cumulative pseudo-survival rate (PSR) during lactation were examined, and the effect of milk yield and SCS information on the reliability of estimated breeding value (EBV) of PSR were determined. Test day milk yield, SCS, and PSR records were obtained for Holstein cows in Japan from 2004 to 2013. A random subset of the data was used for the analysis (825 herds, 205,383 cows). This data set was randomly divided into 5 subsets (162–168 herds, 83,389–95,854 cows), and genetic parameters were estimated in each subset independently. Data were analyzed using multiple-trait random regression animal models including either the residual effect for the whole lactation period (H0), the residual effects for 5 lactation stages (H5), or both of these residual effects (HD). Milk yield heritability increased until 310 to 351 d in milk (DIM) and SCS heritability increased until 330 to 344 DIM. Heritability estimates for PSR increased with DIM from 0.00 to 0.05. The genetic correlation between milk yield and SCS increased negatively to under ?0.60 at 455 DIM. The genetic correlation between milk yield and PSR increased until 342 to 355 DIM (0.53–0.57). The genetic correlation between the SCS and PSR was ?0.82 to ?0.83 at around 180 DIM, and decreased to ?0.65 to ?0.71 at 455 DIM. The reliability of EBV of PSR for sires with 30 or more recorded daughters was 0.17 to 0.45 when the effects of correlated traits were ignored. The maximum reliability of EBV was observed at 257 (H0) or 322 (HD) DIM. When the correlations of PSR with milk yield and SCS were considered, the reliabilities of PSR estimates increased to 0.31–0.76. The genetic parameter estimates of H5 were the same as those for HD. The rank correlation coefficients of the EBV of PSR between H0 and H5 or HD were greater than 0.9. Additionally, the reliabilities of EBV of PSR of H0 were similar to those for H5 and HD. Therefore, the genetic parameter estimates in H0 were not substantially different from those in H5 and HD. When milk yield and SCS, which were genetically correlated with PSR, were used, the reliability of PSR increased. Estimates of the genetic correlations between PSR and milk yield and between PSR and SCS are useful for management and breeding decisions to extend the herd life of cows.     

Events occurring during the previous lactation,the dry period,and peripartum as risk factors for early lactation mastitis in cows receiving 2 different intramammary dry cow therapies

The objective of this study was to investigate the association between mastitis events occurring during the previous lactation, the dry period, and the peripartum period on the incidence of early lactation mastitis in cows receiving ceftiofur hydrochloride or penicillin dihydrostreptomycin as intramammary dry cow antibiotic therapy. Cows (n = 402) from 2 large dairy farms in Central Florida were enrolled in the study at the time of dry-off processing and were randomly assigned to 1 of 2 dry cow therapies: ceftiofur hydrochloride or penicillin dihydrostreptomycin. Composite milk samples were collected at dry-off and after calving for bacteriological examination and somatic cell count. Peripartal health disorders were monitored during the first 30 d of lactation and included calving difficulty, metritis, ketosis, and left displaced abomasum. Milk production and individual somatic cell scores (SCS) were recorded monthly by the Dairy Herd Improvement Association. The main outcome variables were the risk of clinical mastitis during the first 30 and 60 d of lactation, and the risk of subclinical mastitis at the first 2 monthly Dairy Herd Improvement Association tests after calving (up to 70 d in milk). Additionally, the SCS and the presence of mastitis pathogens in milk at dry-off and at calving were analyzed. Explanatory variables consisted of events occurring during the previous lactation, at dry-off and during the dry period, at calving, and within the first 30 d after calving. Multiple events occurring during the previous lactation had a significant effect on the incidence of mastitis in the subsequent lactation. These events included low milk yield, intermediate lactation length, clinical mastitis, and lactation SCS average. Similarly, intramammary infections with environmental bacteria at dry-off increased the chances of clinical mastitis the first month after calving. Dry-off therapy had a significant effect on mastitis incidence; cows treated with ceftiofur hydrochloride had lower odds of having clinical and subclinical mastitis in the subsequent early lactation compared with cows treated with penicillin dihydrostreptomycin.     

Effect of selenium source on selenium status, neutrophil function, and response to intramammary endotoxin challenge of dairy cows

The effects of feeding dry and early lactation dairy cows diets with selenate or selenized yeast (Se-yeast) on concentrations of Se in serum, milk, and newborn calves, neutrophil function, and inflammatory response were determined. At 60 d before anticipated calving until approximately 30 d in milk (DIM), cows were fed diets that contained 0.3 mg of supplemental Se/kg of DM from sodium selenate or Se-yeast. Diets also contained 0.2% supplemental S (as sulfate) because it has been shown to reduce absorption of Se by dairy cows. The concentration of Se in serum at calving and 28 DIM was about 1.4 times greater for cows fed Se-yeast than for those fed selenate. Serum concentrations decreased 45 and 23% from dry-off to calving for cows fed selenate or Se-yeast, respectively. Selenium concentrations in serum from newborn calves were also about 1.4 times greater when the dams were fed Se-yeast. Concentrations of Se in colostrum and milk were about 1.8 times greater when cows were fed Se-yeast. Blood neutrophils were isolated from cows at 28 DIM and were used in an in vitro kill assay. Selenium treatment did not affect bacterial kill or the percentage of neutrophils that phagocytized bacteria. At approximately 28 DIM, one quarter from each cow was infused with a solution containing endotoxin. Peak body temperature (40.7°C) occurred 6 h postinfusion, and peak somatic cell count (6.5 log₁₀/mL) occurred at 12 h postinfusion. Neither measure was influenced by Se treatment.     

Short communication: best prediction of 305-day lactation yields with regional and seasonal effects

In the United States, lactation yields are calculated using best prediction (BP), a method in which test-day (TD) data are compared with breed- and parity-specific herd lactation curves that do not account for differences among regions of the country or seasons of calving. Complete data from 538,090 lactations of 348,123 Holstein cows with lactation lengths between 250 and 500 d, records made in a single herd, at least 5 reported TD, and twice-daily milking were extracted from the national dairy database and used to construct regional and seasonal lactation curves. Herds were assigned to 1 of 7 regions of the country, individual lactations were assigned to 3-mo seasons of calving, and lactation curves for milk, fat, and protein yields were estimated by parity group for regions, seasons, and seasons within regions. Multiplicative pre-adjustment factors (MF) also were computed. The resulting lactation curves and MF were tested on a validation data set of 891,806 lactations from 400,000 Holstein cows sampled at random from the national dairy database. Mature-equivalent milk, fat, and protein yields were calculated using the standard and adjusted curves and MF, and differences between 305-d mature-equivalent yields were tested for significance. Yields calculated using 50-d intervals from 50 to 250 d in milk (DIM) and using all TD to 500 DIM allowed comparisons of predictions for records in progress (RIP). Differences in mature-equivalent milk ranged from 0 to 51 kg and were slightly larger for first-parity than for later parity cows. Milk and components yields did not differ significantly in any case. Correlations of yields for 50-d intervals with those using all TD were similar across analyses. Yields for RIP were slightly more accurate when adjusted for regional and seasonal differences.     

Best prediction of yields for long lactations

Lactation records of any reasonable length now can be processed with the selection index method known as best prediction (BP). Previous prediction programs were limited to the 305-d standard used since 1935. Best prediction was implemented in 1998 to calculate lactation records in USDA genetic evaluations, replacing the test interval method used since 1969 to calculate lactation records. Best prediction is more complex but also more accurate, particularly when testing is less frequent. Programs were reorganized to output better graphics, give users simpler access to options, and provide additional output, such as BP of daily yields. Test-day data for 6 breeds were extracted from the national dairy database, and lactation lengths were required to be ≥500 d (Ayrshire, Milking Shorthorn) or ≥800 d (all others). Average yield and SD at any day in milk (DIM) were estimated by fitting 3-parameter Wood's curves (milk, fat, protein) and 4-parameter exponential functions (somatic cell score) to means and SD of 15- (≤300 DIM) and 30-d (>300 DIM) intervals. Correlations among TD yields were estimated using an autoregressive matrix to account for biological changes and an identity matrix to model daily measurement error. Autoregressive parameters (r) were estimated separately for first (r = 0.998) and later parities (r = 0.995). These r values were slightly larger than previous estimates due to the inclusion of the identity matrix. Correlations between traits were modified so that correlations between somatic cell score and other traits may be nonzero. The new lactation curves and correlation functions were validated by extracting TD data from the national database, estimating 305-d yields using the original and new programs, and correlating those results. Daily BP of yield were validated using daily milk weights from on-farm meters in university research herds. Correlations ranged from 0.900 to 0.988 for 305-d milk yield. High correlations ranged from 0.844 to 0.988 for daily yields, although correlations were as low as 0.015 on d 1 of lactation, which may be due to calving-related disorders that are not accounted for by BP. Correlations between 305-d yield calculated using 50-d intervals from 50 to 250 DIM and 305-yield calculated using all TD to 500 DIM increased as TD data accumulated. Many cows can profitably produce for >305 DIM, and the revised program provides a flexible tool to model these records.     

Effects of genetic selection for milk yield on somatotropin, insulin-like growth factor-I, and placental lactogen in Holstein cows

Cows from static, low-merit control (CL) and contemporary, high-merit select (SL) lines that differed in milk yield by more than 4,000 kg/305-d lactation (SL > CL) were used to determine effects of selection for milk yield on blood serum concentrations of somatotropin (ST), insulin-like growth factor (IGF-I), and placental lactogen (PL). Cows were exposed to the same environment and management conditions and fed the same diets. Serum and milk samples were collected from primiparous (18 CL, 18 SL) and multiparous (12 CL, 18 SL) cows relative to day of lactation (from −28 to 280 d for nonpregnant cows and to subsequent calving for cows that conceived). Data were analyzed as repeated measures using mixed model procedures. Serum ST increased at calving, remained elevated for a longer interval in SL than in CL cows, and was greater in SL than in CL cows. Serum IGF-I decreased at calving, remained low through 14 DIM, and gradually returned to precalving concentrations as lactation progressed. Postpartum concentrations of IGF-I were less in SL than CL through 84 DIM and were similar through the remainder of lactation, resulting in a line by day interaction. Serum IGF-I and PL were not affected by merit during gestation. There was an interaction of merit and postconception interval on IGF-I, with the difference in IGF-I concentration between lines decreasing as gestation progressed. Change in serum IGF-I and PL appeared to be synchronous. Results indicate that selection for milk yield increased serum ST, prolonged the postpartum reduction in serum IGF-I, and did not alter serum PL. Results also indicate a positive relationship between PL and IGF-I and support the concept that PL plays a role in the regulation of serum IGF-I during gestation.     

Relationship of test-day somatic cell score with test-day and lactation milk yields

To determine the relationship of test-day (TD) somatic cell score (SCS) to TD and lactation milk yields, 1,320,590 records from Holstein first and second calvings from 1995 through 2002 were examined. All lactations had recorded yield and SCS for at least the first 4 TD. Least square analyses were conducted for yields on TD 2 through 10 within herd and cow. The model included regressions on current TD SCS and mean SCS of all previous TD with separate estimates by parity; effects for parity and calving year were included as well as regression on days in milk on TD 1. Corresponding analyses were conducted without regression on current SCS. An analysis of lactation yield was performed with a similar model and regression on all TD SCS. The SCS was highest most often on TD 1 for parity 1 (22.5%) and on TD 10 for parity 2 (18.5%). Regression of TD milk yield on mean of previous TD SCS was highest during the latter half of lactation (maximum of -0.346 kg/SCS unit on TD 9) for parity 1 and during TD through 7 (maximum of -0.366 kg/SCS unit on TD 4) for parity 2. Regression of TD yield on current TD SCS tended to be larger for later lactation. Regression of lactation yield on TD SCS was negative and important for TD 1 through 6 for parity 1 and for all TD for parity 2. To minimize milk loss, mastitis control is most important immediately pre- and postcalving for parity 1 and throughout lactation for parity 2.     

Estimates of genetic parameters and eigenvector indices for milk production of Holstein cows

The objectives of the present study were to estimate genetic parameters of monthly test-day milk yield (TDMY) of the first lactation of Brazilian Holstein cows using random regression (RR), and to compare the genetic gains for milk production and persistency, derived from RR models, using eigenvector indices and selection indices that did not consider eigenvectors. The data set contained monthly TDMY of 3,543 first lactations of Brazilian Holstein cows calving between 1994 and 2011. The RR model included the fixed effect of the contemporary group (herd-month-year of test days), the covariate calving age (linear and quadratic effects), and a fourth-order regression on Legendre orthogonal polynomials of days in milk (DIM) to model the population-based mean curve. Additive genetic and nongenetic animal effects were fit as RR with 4 classes of residual variance random effect. Eigenvector indices based on the additive genetic RR covariance matrix were used to evaluate the genetic gains of milk yield and persistency compared with the traditional selection index (selection index based on breeding values of milk yield until 305 DIM). The heritability estimates for monthly TDMY ranged from 0.12 ± 0.04 to 0.31 ± 0.04. The estimates of additive genetic and nongenetic animal effects correlation were close to 1 at adjacent monthly TDMY, with a tendency to diminish as the time between DIM classes increased. The first eigenvector was related to the increase of the genetic response of the milk yield and the second eigenvector was related to the increase of the genetic gains of the persistency but it contributed to decrease the genetic gains for total milk yield. Therefore, using this eigenvector to improve persistency will not contribute to change the shape of genetic curve pattern. If the breeding goal is to improve milk production and persistency, complete sequential eigenvector indices (selection indices composite with all eigenvectors) could be used with higher economic values for persistency. However, if the breeding goal is to improve only milk yield, the traditional selection index is indicated.