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.     

Estimating milk, fat, and protein lactation curves with a test day model.

Test day models were used to estimate lactation curves for milk, fat, protein, fat percentage, and protein percentage and to study the influence of age, season, and herd productivity on Holstein lactation curves. Random effects of lactation within herd and fixed effects of herd test date were absorbed. Fixed effects of cow's age on test day and either DIM (57 divisions) by parity (1, 2, greater than or equal to 3) class or season of calving (winter or summer) by DIM by parity class were estimated. Lactation curves for yield traits derived from DIM solutions were flatter for first versus later lactation, even without addition of age effects. Differences between lactation curves for the two seasons were slight, suggesting that most observed seasonal differences are caused by seasonal productivity accounted for by herd test date effects. At peak, winter calving cows yielded slightly more milk of similar fat percentage but of lower protein percentage than those calving in summer. Data were also partitioned into nine subsets based on rolling herd milk and fat percentage. Lactation curves for yield traits, but not percentage traits, varied with rolling herd milk. Lactation curves for fat yield and percentage varied with rolling herd fat percentage.     

Feeding and management of dairy heifers for optimal lifetime productivity

A total of 433 Holstein heifer calves were fed two different energy amounts from 6 wk of age to breeding weight to determine the effect of early nutrition and age at first calving on lifetime performance. A control group of 182 heifers was fed according to the Beltsville growth standard. A second group of 251 heifers was accelerated in growth by providing more energy during early development. Both groups of heifers were bred at a minimum weight of 340 kg. Average ages at first calving for control and accelerated heifers were 24.6 mo and 22.2 mo with corresponding 305-d first lactation unadjusted milk production values of 6985 and 6729 kg and unadjusted milk fat yields of 222 and 216 kg. Average 305-d milk production values through subsequent lactations for control and accelerated animals, were lactation 2, 7790, 7842 kg; lactation 3, 8200, 8330 kg; lactation 4, 9481, 9134 kg; lactation 5, 9865, 9588 kg; lactation 6, 9515, 10,108; lactation 7, 9661, 10,112. Average total milk yields over five lactations were 42,321 and 41,623 kg. Percentages of cows remaining in the herd after five lactations were 19 and 18 for control and accelerated animals. Reproductive problems, mastitis, and deaths accounted for 70% of cows leaving the herd and did not differ between treatment groups.     

Cow-level factors associated with subclinical hypocalcemia at calving in multiparous Jersey cows

The objective of our study was to identify cow-level factors associated with subclinical hypocalcemia at calving (SCH) in multiparous Jersey cows. A total of 598 Jersey and 218 Jersey × Holstein crossbreed cows from 2 commercial dairy herds were enrolled in a retrospective cohort study. Blood samples to determine total Ca concentration were collected from the coccygeal vessels at 3 h 19 min (±2 h 33 min) after calving. We used 2 serum Ca concentration thresholds to define SCH: <2.00 mmol/L (SCH-2.00) and <2.12 mmol/L (SCH-2.12). We evaluated the association of cow-level factors with SCH with multivariable Poisson regression models. Variables evaluated for association with SCH were herd; parity (2, 3, and ≥4); breed; previous lactation length and 305-d mature-equivalent milk yield; previous lactation first test milk yield and last test somatic cell count; lengths of calving interval, gestation, dry, and close-up periods; body condition and locomotion scores at calving; calving ease; and calf sex for singletons. We categorized continuous variables into quartiles (≤25th percentile, interquartile range and ≥75th percentile). The prevalence of SCH among Jersey cows was 40 (SCH-2.00) and 64% (SCH-2.12). Jersey cows of higher parity had greater risk of SCH-2.00 and SCH-2.12. The risk of SCH-2.12 was higher after birthing male calves. We also found a tendency for previous lactation length and previous lactation 305-d mature-equivalent milk yield effect to affect risk of SCH-2.12. The risk of SCH-2.12 was lower for cows that had a previous lactation length shorter than the 25th percentile compared with cows that had a previous lactation length within the interquartile range. The risk of SCH-2.12 was higher for cows that had a previous lactation 305-d mature-equivalent milk yield below the 25th percentile compared with cows that had a previous lactation 305-d mature-equivalent milk yield above the 75th percentile. Also, Jersey × Holstein crossbreed was associated with increased risk of SCH-2.00. In the multivariable analysis, we observed no association between SCH and previous lactation first test milk yield; last test somatic cell count; lengths of calving interval, gestation, dry, and close-up periods; body condition and locomotion scores at calving; and calving ease. Our study identified parity, breed, calf sex, previous lactation length, and previous lactation 305-d mature-equivalent milk yield as cow-level factors associated with SCH in multiparous Jersey cows.     

Relationship between somatic cell count and milk yield in different stages of lactation

The association between somatic cell count (SCC) and daily milk yield in different stages of lactation was investigated in cows free of clinical mastitis (CM). Data were recorded between 1989 and 2004 in a research herd, and consisted of weekly test-day (TD) records from 1,155 lactations of Swedish Holstein and Swedish Red cows. The main data set (data set A) containing 36,117 records excluded TD affected by CM. In this data set, the geometric mean SCC was 55,000 and 95,000 cells/mL in primiparous and multiparous cows, respectively. A subset of data set A (data set B), containing 27,753 records excluding all TD sampled in lactations affected by CM, was created to investigate the effect of subclinical mastitis (SCM) in lactations free of CM. Daily milk yields were analyzed using a mixed linear model with lactation stage; linear, quadratic and cubic regressions of log₂-transformed and centered SCC nested within lactation stage; weeks in lactation; TD season; parity; breed; pregnancy status; year-season of calving; calving, reproductive, metabolic and claw disorders; and housing system as fixed effects. A random regression was included to further improve the modeling of the lactation curve. Primiparous and multiparous cows were analyzed separately. The magnitude of daily milk loss associated with increased SCC depended on stage of lactation and parity, and was most extensive in late lactation irrespective of parity. In data set A, daily milk loss at an SCC of 500,000 cells/mL ranged from 0.7 to 2.0 kg (3 to 9%) in primiparous cows, depending on stage of lactation. In multiparous cows, corresponding loss was 1.1 to 3.7 kg (4 to 18%). Regression coefficients of primiparous cows estimated from data set B were consistent with those obtained from data set A, whereas data set B generated more negative regression coefficients of multiparous cows suggesting a higher milk loss associated with increased SCC in lactations in which the cow did not develop CM. The 305-d milk loss in the average lactation affected with SCM was 155 kg of milk (2%) in primiparous cows and 445 kg of milk (5%) in multiparous cows. It was concluded that multiparous cows in late lactation can be expected to be responsible for the majority of the herd-level production loss caused by SCM, and that preventive measures need to focus on reducing the incidence of SCM in such cows.     

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.     

Effect of a short dry period on milk yield and content,colostrum quality,fertility, and metabolic status of Holstein cows

We evaluated the effect of shortening the dry period (DP) on milk and energy-corrected milk (ECM) yields, milk components, colostrum quality, metabolic status, and reproductive parameters. Primiparous (n = 372) and multiparous (n = 400) Israeli Holstein cows from 5 commercial dairy herds were subjected to a 60-d or 40-d DP. Cows within each herd were paired according to milk production, age, days in milk, and expected calving. Analysis of the data from all cows, irrespective of age, revealed significant differences in milk and ECM yields that favored the 60-d DP, with a prominent effect in 2 of 5 examined herds. In primiparous cows, milk and ECM yields were similar between groups in 4 of 5 farms. In multiparous cows undergoing a 60-d (vs. 40-d) DP, milk and ECM yields were higher in 3 herds. These differences could not be explained by milk and ECM yields in cows diagnosed with metritis, ketosis, and mastitis (defined by a somatic cell count threshold of 250,000 cell/mL), distribution of infected and noninfected cows, or new infections during DP and after calving. Including the milk and ECM yields from an average of 19.55 d from the previous lactation revealed higher milk and ECM yields for 40-d (vs. 60-d) DP cows in all herds. Analyzing 2 consecutive lactations revealed similar milk and ECM yields between groups in 4 out of 5 herds. In 1 herd, yields were higher in the 40-d compared with the 60-d DP group. One week after calving, the nonesterified fatty acid concentrations of 40-d DP cows were significantly lower than those of 60-d DP cows, indicating better postpartum energy balance. Colostrum quality, measured as IgG concentration, did not differ between the 2 DP groups. Cows assigned to 40-d DP had better reproductive performance, as reflected by fewer days to first insemination, a lower proportion with >90 d to first insemination, and fewer days to pregnancy. With respect to primiparous cows, a short DP increased conception rate after first artificial insemination and decreased the proportion of nonpregnant cows after 150 d in milk. In light of these findings, we suggest that a short DP be applied for its economic and physiological benefits. This is highly relevant to dairy herds located in regions such as Israel, Spain, and Florida that suffer from reduced milk production during the hot season.     

Genetic analysis of herd life in Quebec Holsteins using Weibull models

Survival analysis methodologies were used to study herd life in Canadian Holstein cows. Herd life was defined as true herd life or the length of time between first calving and censoring. True herd life adjusted for 305-d milk production was defined as functional herd life. Lifetime record (censored or completed) were from 331,147 Holstein cows registered in the Programme d'Analyse des Troupeaux Laitiers du Québec (PATLQ) that calved for the first time between March 1, 1981 and March 31, 1995. The Weibull (proportional hazards) model used to analyze true herd life and functional herd life contained a Weibull baseline hazard function and the time-dependent effects of year of first calving, lactation number by stage of lactation, annual change in herd size and herd-year (random), and the time-independent effects of the milk recording option (supervised or not) and age at first calving. The model for functional herd life included also the time-dependent effect of herd-year-parity class of 305-d milk production. Genetic differences between sires with regard to the hazard function of their daughters was clearly demonstrated. The hazard rate followed a different pattern in later lactations, particularly in the first 240 d in milk. Older age at first calving was found to be associated with higher risks of culling. Changes in herd size had a small impact on the hazard function of animals. The hazard decreased as production of the cow increased. Heritability in the log scale was 0.09 for true herd life and 0.08 for functional herd life, but when heritability was expressed on the original scale, the estimates for the two traits were 0.19 and 0.15, respectively. The difference in the median survival between a bull with an estimated transmitting ability of 0.6 and another bull with an estimated transmitting ability of 1.3 was 690 d or 1.7 lactations. Rank correlations between the official estimated transmitting abilities for true herd life and functional herd life and those obtained in this study were 0.62 and 0.66, respectively.     

Effect of type of diet and energy intake on milk production of Holstein-Friesian cows with extended lactations

The aim of this study was to measure the effect of type of diet and level of energy intake on the performance of cows undergoing extended lactations. Ninety-six Holstein-Friesian cows that calved in July and August 2004 were assigned randomly to 1 of 8 groups each of 12 cows (including 4 primiparous cows). Two of the 8 groups were assigned to each of 4 treatments that varied in lactation length (300 or 670 d) and diet (3 diets: control, high, or full total mixed ration (TMR). The 4 treatments were 1) control 300: cows were managed for a 300-d lactation and grazed pasture supplemented with grain and forage to provide a minimum daily dietary intake of 160 MJ of ME/cow; 2) control 670: as for control 300 except that cows were managed for a 670-d lactation; 3) high 670: cows were managed for a 670-d lactation and pasture was supplemented with grain and forage to provide a minimum daily dietary intake of 180 MJ of ME/cow; 4) full TMR 670: cows were managed for a TMR system that included a high body condition score at calving with cows offered a TMR during a 670-d lactation. The TMR was initially offered ad libitum indoors until about 440 DIM when the amount of TMR offered was reduced by about 2 kg of DM/d to prevent excessive weight gain. The proportions of cows still milking at the end of a 670-d lactation were similar for the control and high dietary groups. The full TMR group had fewer cows milking at 600 DIM: 17 cows milking compared with 24 cows in the control 670 group and 22 cows in the high 670 group. For the period 1 to 670 DIM, increasing the energy level in the diet (control 670 vs. high 670) resulted in a similar yield of milk and a similar fat concentration in the milk, but greater yields of milk fat and protein and greater milk protein percentage of the milk. The full TMR 670 group produced greater yields of milk and milk components (fat, protein, and lactose) and also protein percentage in the milk than the other groups. The milk solids (fat + protein) ratio for the 3 extended-lactation groups, defined as production achieved during the 24-mo calving interval divided by 2 yr (annualized production) expressed as a ratio of that produced in the normal 12-mo calving interval, was not affected by increasing the level of grain in the pasture-based diets (0.93 vs. 0.90 for control and high diets, respectively), but decreased with the TMR diet (0.79). The control 670 group produced 7.1% less milk, but only 2.4% less milk solids than the control 300 group over the 2-yr period of the study. Combining our data with that from 2 earlier studies of extended lactation demonstrated that Holstein cows with a high proportion of Northern Hemisphere genes offered pasture-based diets could achieve a high milk solids ratio, a greater proportion of cows milking at drying-off, and lower body weight gain over the lactation.     

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.     

Correlations among first and second lactation milk yield and calving interval

Estimates of genetic correlations were .17 between first lactation milk yield and concurrent calving interval, .10 between second lactation milk yield and first calving interval, and .82 between first and second milk yields. Corresponding phenotypic correlations were .27, .16, and .58. Heritability estimates were .27 and .25 for first and second lactations and .15 for calving interval. Estimates were averages of two samples of 15 New York State herds averaging 144 AI-sired Holstein cows and 30 sires. Milk yields were 305-d, mature equivalent. Calving interval was days between first and second freshening. First milk records without a second freshening were included. Multiple-trait animal model included separate herd-year-season effects for first and second milk yields and calving interval. Numerator relationships among animals within herd, except for daughter-dam relationships, were included. The REML with the expectation-maximization algorithm was used to estimate (co)variance matrices among genetic values and environmental effects for the three traits. Results indicate a need to adjust milk records for the phenotypic effects of current and previous calving interval. The genetic association, however, between fertility and milk yield appears small. Genetic improvement of 450 kg of milk yield may result in 2 added d to first calving interval.     

Mastitis and the shape of the lactation curve in Norwegian dairy cows

An investigation of the shape of the lactation curve and the mastitis incidence was conducted to identify whether management interventions of the lactation curve constitute a potential for reducing incidence of mastitis at herd level. Lactation curves were estimated to describe the variation of daily milk yield during the 305-d lactation period in Norwegian Red cows. Associations between mastitis incidence at herd level and lactation curve characteristics such as production level at onset of lactation, magnitude and time of peak milk yield, and increase and decrease of milk yield rates were studied. Data from 250,303 lactations occurring during 2005 and 2006 from 14,766 herds were obtained from the Norwegian Dairy Herd Recording System. Besides veterinary treatments, the records included information on monthly test-day milk yields. The shapes of the lactation curves at herd level were parameterized using a modified Wilmink model in two separate mixed model analyses. In the first analysis a subset of lactations with no records of veterinary treatments was used. Lactation curves from herds with high (>0·31 cases/305-d lactation) and low (<0·07 cases/305-d lactation) herd mastitis incidence rate were parameterized and compared for three separate strata of parity. The result showed that high herd mastitis incidence rate was associated with a low intercept (P<0·05), a steep slope before peak milk yield (P<0·01) and a rapid decline after peak milk yield (P<0·01). In the second analysis a subset of high-yielding lactations with veterinary treatments of mastitis only and lactations with no records of veterinary treatment were compared. This was done to investigate whether the findings at herd level were also reflected at cow level. These results showed that lactation curves from lactations with mastitis cases were associated with a steep slope before peak milk yield (P<0·05) in second and later parities and a rapid decline after peak milk yield (P<0·01) in all three parity groups.     

Technical note: detection and adjustment of abnormal test-day yields

A method to detect and to adjust or exclude abnormally low or high milk, fat, and protein yields on test-day (TD) was developed. Predicted TD yield is calculated based on preceding and subsequent (if available) TD yields. Observed TD yields that are < 60% or > 150% of predicted TD yield are defined as abnormal. Most abnormal yields are adjusted to this floor or ceiling, but some are excluded. Yields of < 4.5 kg that are identified as from a cow that was sick or that are less than half the mean of adjacent tests are excluded as are yields of > 59 kg above predicted yield. Lactation yields are calculated from the restricted TD yields. When this procedure was applied to 2002 data, 1.8% of milk, 2.4% of fat, and 1.6% of protein yields on TD were below the acceptance range and 0.1% of milk and protein and 0.8% of fat were above. Predicted TD yield was calculated as preceding TD yield plus preceding test interval multiplied by daily yield change (slope) based on days in milk (DIM), DIM2, previous normal TD yield, and interaction between DIM and previous TD yield. To accommodate changes in slope at peak yield, separate coefficients were estimated for < 50 and > or = 50 DIM. Herd mean was used when only one TD was recorded for a cow (or when two were recorded and the second was designated as abnormal based on the first) and to determine an acceptable range for component percentages. Predicted TD yield for first TD was based on subsequent rather than previous normal TD. To test the adjustments, lactation records with one abnormal TD yield or more were matched with subsequent lactation records. Correlation between consecutive lactations increased from 0.692 to 0.693 for milk (561,063 lactation pairs), from 0.653 to 0.660 for fat (951,387 lactation pairs), and from 0.686 to 0.694 for protein (488,653 lactation pairs). Outlier adjustment improved the correlation between consecutive lactation yields and is applied routinely to TD records of cows for calvings since 1997.     

Predicting Milk Yield of Holstein Cows from 306 to 395 Days in Milk

Prediction equations were determined to estimate daily milk yield from 306 to 395 d in milk for forecasting herd milk sales from Holstein cows in lactation >305 d. Data were test day milk weights for 65,322 primiparous and 119,220 pluriparous lactations of > 305 d from the Southern US. A forecast model was developed using same lactation 305 d milk yield (in classes of 500 kg increments) that gave similar predicted daily yields as models utilizing last sample milk weight information. This model has the advantage of early forecasting of later milk using projected 305-d yields.Reduced forecast models ignoring days pregnant, yield class, or both accounted for 95, 68, and 59%, and 91, 67, and 56% as much variation in daily milk as the full model for the primiparous and pluriparous cows. Percentage of 305-d milk yielded in mo 11, 12, and 13, depending on 305-d yield class, ranged from 7.1 to 7.0%, 6.2 to 6.0%, and 5.4 to 5.0%, and 5.4 to 5.0%, 4.3 to 3.9%, and 3.3 to 3.0% for first parity and pluriparous cows calving in winter and 125 d open. Cows not calving in winter or with more than 125 d open yielded more milk in extended lactation. These percentages are larger than generally assumed in studies of days open, thus indicating that cost of days open may have been overestimated.     

Long-term effects of postpartum clinical disease on milk production,reproduction, and culling of dairy cows

Two retrospective studies examining data of 7,500 lactating cows from a single herd were performed with the objective of evaluating the long-term effects of clinical disease during the early postpartum period on milk production, reproduction, and culling of dairy cows through 305 days in milk (DIM). In the first study, data regarding health, milk production, reproduction, and culling of 5,085 cows were summarized. Cows were classified according to incidence of clinical problem (metritis, mastitis, lameness, digestive problem, or respiratory problem) during the first 21 DIM (ClinD21). During 305 d of lactation, cows that had ClinD21 produced, on average, 410 kg less milk, 17 kg less fat, and 12 kg less protein compared with cows that did not have ClinD21 (NoClinD21). Although the interval to first breeding was not different between groups of interest, pregnancy rate through 305 DIM was lower in cows that had ClinD21 [adjusted hazard ratio (AHR) = 0.81]. When individual breedings were analyzed, cows that had ClinD21 presented lower rates of pregnancy per breeding for breedings performed before 150 DIM, reduced numbers of calving per breeding for breedings performed before 200 DIM, and greater number of pregnancy losses for all breedings performed through 305 DIM. The rate of culling from calving through 305 DIM was higher in cows that had a single ClinD21 (AHR = 1.79) and in cows that had multiple ClinD21 (AHR = 3.06), which resulted in a greater proportion of cows leaving the herd by 305 DIM (NoClinD21 = 22.6%; single ClinD21 = 35.7%; multiple ClinD21 = 53.8%). In the second study, data regarding postpartum health and 305-d yields of milk, fat, and protein were collected from 2,415 primiparous cows that had genomic testing information. Genomic estimated breeding values (EBV) were used to predict 305-d yields of milk, fat, and protein. Genomic EBV and predicted yields of milk, fat, and protein did not differ between cows that had ClinD21 and those that did not have ClinD21. In contrast, the observed 305-d yields of milk, fat, and protein were reduced by 345, 10, and 10 kg, respectively, in cows that had ClinD21 compared with cows that did not have ClinD21. We conclude that clinical disease diagnosed and treated during the first 21 DIM has long-term effects on lactation performance, reproduction, and culling of dairy cows, which contribute to detrimental consequences of health problems on sustainability of dairy herds. Replication of our studies in multiple herds will be important to confirm our findings in a larger population.     

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.     

Investigating the effect of temporal,geographic, and management factors on US Holstein lactation curve parameters

We fit the Wood's lactation model to an extensive database of test-day milk production records of US Holstein cows to obtain lactation-specific parameter estimates and investigated the effects of temporal, spatial, and management factors on lactation curve parameters and 305-d milk yield. Our approach included 2 steps as follows: (1) individual animal-parity parameter estimation with nonlinear least-squares optimization of the Wood's lactation curve parameters, and (2) mixed-effects model analysis of 8,595,413 sets of parameter estimates from individual lactation curves. Further, we conducted an analysis that included all parities and a separate analysis for first lactation heifers. Results showed that parity had the most significant effect on the scale (parameter a), the rate of decay (parameter c), and the 305-d milk yield. The month of calving had the largest effect on the rate of increase (parameter b) for models fit with data from all lactations. The calving month had the most significant effect on all lactation curve parameters for first lactation models. However, age at first calving, year, and milking frequency accounted for a higher proportion of the variance than month for first lactation 305-d milk yield. All parameter estimates and 305-d milk yield increased as parity increased; parameter a and 305-d milk yield rose, and parameters b and c decreased as year and milking frequency increased. Calving month estimates parameters a, b, c, and 305-d milk yield were the lowest values for September, May, June, and July, respectively. The results also indicated the random effects of herd and cow improved model fit. Lactation curve parameter estimates from the mixed-model analysis of individual lactation curve fits describe well US Holstein lactation curves according to temporal, spatial, and management factors.     

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.     

Positive genetic merit for fertility traits is associated with superior reproductive performance in pasture-based dairy cows with seasonal calving

New Zealand's Fertility Breeding Value (FertBV) is reported as the percentage of a sire's daughters that calve in the first 42 d of the seasonal calving period and is an estimate of genetic merit for fertility for dairy cattle. Reproductive physiology, milk production, and changes in body weight and body condition score of 2 groups of cows divergent in FertBV (+5.0%: POS; −5.1%: NEG) were characterized during their first 2 lactations. Cows grazed fresh pasture and were managed in a seasonal calving system; they were bred by artificial insemination on observed estrus for the entire breeding period (98 d in lactation 1 and 76 d in lactation 2). During lactation 1, all animals were primiparous and were randomly allocated to 1 of 2 herds, ensuring each herd was balanced for FertBV and expected calving date. During lactation 2, cows that became pregnant during lactation 1 were managed as 1 herd. Cows not inseminated in the first 42 d of the breeding season were examined for the presence of a corpus luteum and treated with an anestrus program. On average, the interval from calving to ovulation was 19 d longer in lactation 1 and 10 d longer in lactation 2 for NEG FertBV cows. The percent of cows submitted for artificial insemination after 21 d (i.e., submission rate) was 38 and 25 percentage points greater in the POS FertBV cows during lactations 1 and 2, respectively. Pregnancy rate from 42 d of breeding was 33 and 30 percentage points greater, respectively. There was no effect of FertBV on vaginal discharge score postcalving; however, POS FertBV cows had a 50% lower risk of having subclinical endometritis (polymorphonuclear leukocytes >7%) 42 d postcalving. Interactions between FertBV and month relative to calving identified that NEG FertBV cows were fatter (greater body condition score) in the month before calving, but thinner between 3 and 5 mo postcalving. There was no effect of FertBV on lactation length, estimated 270-d milk yields, or daily milk, fat, or protein yields, and only small effects on milk fat and protein percentage across the lactations. In summary, the POS FertBV cows had superior uterine health, a shorter calving to ovulation interval, a greater submission rate, and a greater pregnancy rate earlier in the breeding season when compared with the NEG FertBV cohort. Based on these results, these may be useful phenotypes to include in genetic selection indices.     

Accounting for pregnancy diagnosis in predicting days open

The system for estimating days open for cows with no subsequent lactation was examined to determine if estimates should vary depending on pregnancy diagnosis. Pregnancy diagnosis information was unavailable when the original prediction system was developed, but collection was begun in 2002. New prediction equations were estimated from nearly 1.1 million Holstein lactations for 20-d intervals from 110 to 250 days in milk (DIM). Use of pregnancy diagnosis improved accuracy compared with the original system. The improvement was particularly evident for lactations of cows confirmed to be open in the 130-to-149 DIM interval, where predicted days open increased by > 96 d. For lactations of cows with a confirmed pregnancy, predicted days open decreased by 18 d for the same interval. Prediction errors decreased with increasing DIM. Jersey lactations averaged fewer days open, but in most cases Holstein solutions provided adequate predictions. Specific adjustments were generated for Jersey lactations with no breedings reported. Those adjustments reduced the predicted days open averaged across parity by an amount that increased from 9 to 27 d with DIM interval. The new prediction equations were implemented for November 2004 evaluations for daughter pregnancy rate.