Characterization of semen type prevalence and allocation in Holstein and Jersey females in the United States.

Our objective was to characterize semen type prevalence and allocation to inseminate US Holstein and Jersey females by year, parity, service number, and herd size. A secondary objective was to identify the prevalence of beef breed sires selected to create beef × Holstein and beef × Jersey crossbred calves. The final data set included 8,244,653 total inseminations of 4,880,752 Holstein females across 9,155 herds, and 435,267 total inseminations of 266,058 Jersey females across 2,759 herds from October 2019 to July 2021. This data set represents approximately 42 and 27% of the total dairy cows and heifers, respectively, across approximately 40% of the total licensed dairy herds in the continental United States. Holstein and Jersey females were inseminated with 1 of 4 semen types: (1) beef, (2) conventional, (3) sexed, or (4) other dairy. The top 4 beef breeds used to produce beef × Holstein and beef × Jersey crossbred calves, respectively, were Angus (55.1 and 39.1%), Limousin (13.9, and 23.5%), Simmental (11.7 and 20.5%), and Crossbreed Beef (11.3 and 4.8%). From 2019 to 2021, the use of sexed semen to inseminate Holstein and Jersey females increased from 11.0 and 24.5% to 17.7 and 32.1%, respectively, and the use of beef semen to inseminate Holstein and Jersey females increased from 18.2 and 11.4% to 26.1 and 21.2%, respectively. The use of beef semen to inseminate Holstein and Jersey females increased with increasing parity and service number, whereas the use of sexed semen decreased with increasing parity and service number supporting that farmers used sexed semen more aggressively in higher fertility and younger females with greater genetic merit. Overall, the increase in sexed and beef semen inseminations was driven primarily by larger herds. In conclusion, sexed and beef semen inseminations in US Holstein and Jersey females increased from 2019 to 2021 and was allocated differentially based on parity and service number. This increase was driven primarily by larger dairy herds possibly due to differences in reproductive performance and economies of scale.

Associations between dry period length and time to culling and pregnancy in the subsequent lactation.

The association between dry period length (DPL) and time to culling and pregnancy in the subsequent lactation may be important for the economically optimal length of the dry period. Therefore, this study aimed to (1) quantify the association between DPL and hazard of culling and pregnancy in the subsequent lactation; (2) develop continuous functions of DPL for the hazard ratios of culling and pregnancy; and (3) investigate the effect of a cause-specific hazards model and a subdistribution model to analyze competing events. The data used in this observational cohort study were from dairy herd improvement milk test lactation records from 40 states in the United States. After edits, there remained 1,108,515 records from 6,730 herds with the last days dry in 2014 or 2015. The records from 2 adjacent lactations (current, subsequent) were concatenated with the DPL of interest, 21 to 100 d, in between both lactations. We defined 8 DPL categories of 10 d each. Kaplan-Meier survival curves were used to show associations between DPL and time to culling or pregnancy for 3 lactation groups: lactation 1 and 2, lactation 2 and 3, and lactation 3 and greater. To control for confounding factors in Cox proportional models, we included 6 current lactation covariates and 3 time-dependent variables in the survival models. Hazard ratios of culling were estimated for 4 days in milk (DIM) categories from 1 to 450 DIM. Hazard ratios of pregnancy were estimated for 3 DIM categories from 61 to 300 DIM. Competing risk analysis of 8 disposal codes (i.e., farmer reported reasons) for culling and the culling event for pregnancy were conducted by a cause-specific hazards model and a subdistribution model. Hazard ratios were also estimated as quadratic polynomials of DPL. Compared with the reference DPL category of 51 to 60 d, hazard ratios of culling and pregnancy of the other 7 DPL categories ranged between 0.70 and 1.49, and 0.93 and 1.15, respectively. Short DPL were associated with lower risk of culling in the early lactation but not over the entire lactation. Short DPL were associated with greater hazard of pregnancy. Trends in hazard ratios over the ranges of the 8 DPL categories were not always consistent. Competing risk analysis with both models provided little differences in hazard ratios of culling and pregnancy. In conclusion, variations in DPL were associated with meaningful differences in the hazard ratios for culling and pregnancy and minor differences in the relative frequency of disposal codes. Subdistribution hazards models produced hazard ratios similar to cause-specific hazard models. The quadratic polynomials may be useful for decision support on customization of DPL for individual cows.

Intergenerational cycle of disease: Maternal mastitis is associated with poorer daughter performance in dairy cattle.

Adverse prenatal environments, such as maternal stress and infections, can influence the health and performance of offspring. Mastitis is the most common disease in dairy cattle, yet the intergenerational effects have not been specifically investigated. Therefore, we examined the associations between the dam's mammary gland health and daughter performance using somatic cell score (SCS) as a proxy for mammary health. Using data obtained from Dairy Records Management Systems (Raleigh, NC), we linked daughter records with their dam's records for the lactation in which the daughter was conceived. Linear and quadratic relationships of dam mean SCS with the daughter's age at first calving (AFC; n = 15,992 daughters, 4,366 herds), first- (n = 15,119 daughters, 4,213 herds) and second-lactation SCS (n = 3,570 daughters, 1,554 herds), first- and second-lactation mature-equivalent 305-d milk yield, and milk component yields were assessed using mixed linear regression models. We uncovered a phenomenon similar to those found in human and mouse models examining prenatal inflammation effects, whereby daughters born from dams with elevated SCS had poorer performance. Dam mean SCS was positively associated with daughter's AFC and first- and second-lactation mean SCS. Furthermore, for every 1-unit increase in dam mean SCS, daughter's first- and second-lactation mature-equivalent fat yield declined by 0.34% and 0.91% (-1.6 ± 0.49 kg, -4.0 ± 1.0 kg, respectively), although no effect was found on first- or second-lactation milk or milk protein yield. When accounting for genetics, daughter SCS, and AFC (first lactation only), dam mean SCS was associated with reduced second-lactation milk fat yield (-3.5 ± 1.8 kg/unit SCS), and a tendency was found for first-lactation milk fat yield (-1.9 ± 1.0 kg/unit SCS). Taken together, the association of greater dam mean SCS with lesser daughter milk fat yield is likely due to a few underlying mechanisms, in particular, a predisposition for mastitis and alterations in the epigenome controlling milk fat synthesis. As such, future studies should examine epigenetic mechanisms as a potential underpinning of this phenomenon.

Piecewise modeling of the associations between dry period length and milk, fat, and protein yield changes in the subsequent lactation.

Our objective was to develop predictive models of 305-d mature-equivalent milk, fat, and protein yields in the subsequent lactation as continuous functions of the number of days dry (DD) in the current lactation. In this retrospective cohort study with field data, we obtained DHIA milk recording lactation records with the last DD in 2014 or 2015. Cows included had DD from 21 to 100 d. After editing, 1,030,141 records from cows in 7,044 herds remained. Three parity groups of adjacent (current, subsequent) lactations were constructed. We conducted all analyses by parity group and yield component. We first applied control models to pre-adjust the yields in the subsequent lactation for potentially confounding effects. Control models included the covariates mature-equivalent yield, days open, somatic cell score at 180 d pregnant, daily yield at 180 d pregnant, and a herd-season random effect, all observed in the current lactation. Days dry was not included. Second, we modeled residuals from control models with smooth piecewise regression models consisting of a simple linear, quadratic, and another simple linear equation depending on DD. Yield deviations were calculated as differences from predicted mature-equivalent yield at 50 DD. For validation, predictions of yield deviations from piecewise models by DD were compared with predictions from local regression for the DHIA field records and yield deviations reported in 38 experimental and field studies found in the literature. Control models reduced the average root mean squared prediction error by approximately 21%. Yield deviations were increasingly more negative for DD shorter than 50 d, indicating lower yields in the subsequent lactation. For short DD, the decrease in 305-d mature-equivalent milk yield ranged from 43 to 53 kg per DD. For mature-equivalent fat and protein yields, decreases were between 1.28 and 1.71 kg per DD, and 1.06 and 1.50 kg per DD, respectively. Yield deviations often were marginally positive and increasing for DD >50, so that the highest yield in the subsequent lactation was predicted for 100 DD. For long DD, the 305-d mature-equivalent milk yield increased at most 4.18 kg per DD. Patterns in deviations for fat and protein yield were similar to those for milk yield deviations. Predictions from piecewise models and local regressions were very similar, which supports the chosen functional form of the piecewise models. Yield deviations from field studies in the literature typically were decreasing when DD were longer, likely because of insufficient control for confounding effects. In conclusion, piecewise models of mature-equivalent milk, fat, and protein yield deviations as continuous functions of DD fit the observed data well and may be useful for decision support on the optimal dry period length for individual cows.

Genome-wide association study for ketosis in US Jerseys using producer-recorded data.

Ketosis is one of the most frequently reported metabolic health events in dairy herds. Several genetic analyses of ketosis in dairy cattle have been conducted; however, few have focused specifically on Jersey cattle. The objectives of this research included estimating variance components for susceptibility to ketosis and identification of genomic regions associated with ketosis in Jersey cattle. Voluntary producer-recorded health event data related to ketosis were available from Dairy Records Management Systems (Raleigh, NC). Standardization was implemented to account for the various acronyms used by producers to designate an incidence of ketosis. Events were restricted to the first reported incidence within 60 d after calving in first through fifth parities. After editing, there were a total of 42,233 records from 23,865 cows. A total of 1,750 genotyped animals were used for genomic analyses using 60,671 markers. Because of the binary nature of the trait, a threshold animal model was fitted using THRGIBBS1F90 (version 2.110) using only pedigree information, and genomic information was incorporated using a single-step genomic BLUP approach. Individual single nucleotide polymorphism (SNP) effects and the proportion of variance explained by 10-SNP windows were calculated using postGSf90 (version 1.38). Heritability of susceptibility to ketosis was 0.083 [standard deviation (SD) = 0.021] and 0.078 (SD = 0.018) in pedigree-based and genomic analyses, respectively. The marker with the largest associated effect was located on chromosome 10 at 66.3 Mbp. The 10-SNP window explaining the largest proportion of variance (0.70%) was located on chromosome 6 beginning at 56.1 Mbp. Gene Ontology (GO) and Medical Subject Heading (MeSH) enrichment analyses identified several overrepresented processes and terms related to immune function. Our results indicate that there is a genetic component related to ketosis susceptibility in Jersey cattle and, as such, genetic selection for improved resistance to ketosis is feasible.

Benchmarking dairy herd health status using routinely recorded herd summary data.

Genetic improvement of dairy cattle health through the use of producer-recorded data has been determined to be feasible. Low estimated heritabilities indicate that genetic progress will be slow. Variation observed in lowly heritable traits can largely be attributed to nongenetic factors, such as the environment. More rapid improvement of dairy cattle health may be attainable if herd health programs incorporate environmental and managerial aspects. More than 1,100 herd characteristics are regularly recorded on farm test-days. We combined these data with producer-recorded health event data, and parametric and nonparametric models were used to benchmark herd and cow health status. Health events were grouped into 3 categories for analyses: mastitis, reproductive, and metabolic. Both herd incidence and individual incidence were used as dependent variables. Models implemented included stepwise logistic regression, support vector machines, and random forests. At both the herd and individual levels, random forest models attained the highest accuracy for predicting health status in all health event categories when evaluated with 10-fold cross-validation. Accuracy (SD) ranged from 0.61 (0.04) to 0.63 (0.04) when using random forest models at the herd level. Accuracy of prediction (SD) at the individual cow level ranged from 0.87 (0.06) to 0.93 (0.001) with random forest models. Highly significant variables and key words from logistic regression and random forest models were also investigated. All models identified several of the same key factors for each health event category, including movement out of the herd, size of the herd, and weather-related variables. We concluded that benchmarking health status using routinely collected herd data is feasible. Nonparametric models were better suited to handle this complex data with numerous variables. These data mining techniques were able to perform prediction of health status and could add evidence to personal experience in herd management.

Short communication: Genomic selection for hoof lesions in first-parity US Holsteins.

Hoof lesions contributing to lameness are crucial economic factors that hinder the profitability of dairy enterprises. Producer-recorded hoof lesions data of US Holsteins were categorized into infectious (abscess, digital and interdigital dermatitis, heel erosion, and foot rot) and noninfectious (korn, corkscrew, sole and toe ulcer, sole hemorrhage, white line separation, fissures, thin soles, and upper leg lesions) categories of hoof lesions. Pedigree- and genomic-based univariate analyses were conducted to estimate the variance components and heritability of infectious and noninfectious hoof lesions. A threshold sire model was used with fixed effects of year-seasons and random effects of herd and sire. For genomic-based analysis, a single-step procedure was conducted, incorporating H matrix to estimate genomic variance components and heritability for hoof lesions. The pedigree-based analysis produced heritability estimates of 0.11 (±0.05) for infectious hoof lesions and 0.08 (±0.05) for noninfectious hoof lesions. The single-step genomic analysis produced heritability estimates of 0.14 (±0.06) for infectious hoof lesions and 0.12 (±0.08) for noninfectious hoof lesions. Approximated genetic correlations between hoof lesion traits and hoof type traits along with productive life and net merit were all low and ranged between -0.25 and 0.14. Sire reliabilities increased, on average, by 0.24 and 0.18 for infectious and noninfectious hoof lesions, respectively, with incorporation of genomic data.

Inferring causal relationships between reproductive and metabolic health disorders and production traits in first-lactation US Holsteins using recursive models.

Health disorders in dairy cows have a substantial effect on the profitability of a dairy enterprise because of loss in milk sales, culling of unhealthy cows, and replacement costs. Complex relationships exist between health disorders and production traits. Understanding the causal structures among these traits may help us disentangle these complex relationships. The principal objective of this study was to use producer-recorded data to explore phenotypic and genetic relationships among reproductive and metabolic health disorders and production traits in first-lactation US Holsteins. A total of 77,004 first-lactation daughters' records of 2,183 sires were analyzed using recursive models. Health data contained information on reproductive health disorders [retained placenta (RP); metritis (METR)] and metabolic health disorders [ketosis (KETO); displaced abomasum (DA)]. Production traits included mean milk yield (MY) from early lactation (mean MY from 6 to 60 d in milk and from 61 to 120 d in milk), peak milk yield (PMY), day in milk of peak milk yield (PeakD), and lactation persistency (LP). Three different sets of traits were analyzed in which recursive effects from each health disorder on culling, recursive effects of one health disorder on another health disorder and on MY, and recursive effects of each health disorder on production traits, including PeakD, PMY, and LP, were assumed. Different recursive Gaussian-threshold and threshold models were implemented in a Bayesian framework. Estimates of the structural coefficients obtained between health disorders and culling were positive; on the liability scale, the structural coefficients ranged from 0.929 to 1.590, confirming that the presence of a health disorder increased culling. Positive recursive effects of RP to METR (0.117) and of KETO to DA (0.122) were estimated, whereas recursive effects from health disorders to production traits were negligible in all cases. Heritability estimates of health disorders ranged from 0.023 to 0.114, in accordance with previous studies. Similarly, genetic correlations obtained between health disorders were moderate. The results obtained suggest that reproductive and metabolic health disorder and culling due to metabolic and reproductive diseases have strong causal relationships. Based on these results, we concluded that a health disorder (either reproductive or metabolic) occurring in early lactation has a moderate causal effect on the reproductive or metabolic health disorder occurring in later lactation. In addition, direct, indirect, and overall effects of reproductive and metabolic health disorders on milk yields for cows that avoid culling are weak.

Genomic selection for producer-recorded health event data in US dairy cattle.

Emphasizing increased profit through increased dairy cow production has revealed a negative relationship of production with fitness and health traits. Decreased cow health can affect herd profitability through increased rates of involuntary culling and decreased or lost milk sales. The development of genomic selection methodologies, with accompanying substantial gains in reliability for low-heritability traits, may dramatically improve the feasibility of genetic improvement of dairy cow health. Producer-recorded health information may provide a wealth of information for improvement of dairy cow health, thus improving profitability. The principal objective of this study was to use health data collected from on-farm computer systems in the United States to estimate variance components and heritability for health traits commonly experienced by dairy cows. A single-step analysis was conducted to estimate genomic variance components and heritabilities for health events, including cystic ovaries, displaced abomasum, ketosis, lameness, mastitis, metritis, and retained placenta. A blended H matrix was constructed for a threshold model with fixed effects of parity and year-season and random effects of herd-year and sire. The single-step genomic analysis produced heritability estimates that ranged from 0.02 (standard deviation = 0.005) for lameness to 0.36 (standard deviation = 0.08) for retained placenta. Significant genetic correlations were found between lameness and cystic ovaries, displaced abomasum and ketosis, displaced abomasum and metritis, and retained placenta and metritis. Sire reliabilities increased, on average, approximately 30% with the incorporation of genomic data. From the results of these analyses, it was concluded that genetic selection for health traits using producer-recorded data are feasible in the United States, and that the inclusion of genomic data substantially improves reliabilities for these traits.

Incidence validation and relationship analysis of producer-recorded health event data from on-farm computer systems in the United States.

The principal objective of this study was to analyze the plausibility of health data recorded through on-farm recording systems throughout the United States. Substantial progress has been made in the genetic improvement of production traits while health and fitness traits of dairy cattle have declined. Health traits are generally expensive and difficult to measure, but health event data collected from on-farm computer management systems may provide an effective and low-cost source of health information. To validate editing methods, incidence rates of on-farm recorded health event data were compared with incidence rates reported in the literature. Putative relationships among common health events were examined using logistic regression for each of 3 timeframes: 0 to 60, 61 to 90, and 91 to 150 d in milk. Health events occurring on average before the health event of interest were included in each model as predictors when significant. Calculated incidence rates ranged from 1.37% for respiratory problems to 12.32% for mastitis. Most health events reported had incidence rates lower than the average incidence rate found in the literature. This may partially represent underreporting by dairy farmers who record disease events only when a treatment or other intervention is required. Path diagrams developed using odds ratios calculated from logistic regression models for each of 13 common health events allowed putative relationships to be examined. The greatest odds ratios were estimated to be the influence of ketosis on displaced abomasum (15.5) and the influence of retained placenta on metritis (8.37), and were consistent with earlier reports. The results of this analysis provide evidence for the plausibility of on-farm recorded health information.

Trends for conception rate of Holsteins over time in the southeastern United States.

The purpose of this study was to estimate trends in conception rate (CR) of Holsteins in the southeastern United States over time across month by milk production level and month by days in milk (DIM) subclasses. Data were obtained from Dairy Records Management Systems (Raleigh, NC) and included service records from 10 states (Virginia, Kentucky, North Carolina, South Carolina, Tennessee, Georgia, Florida, Alabama, Mississippi, and Louisiana). After eliminating records with lactation >1 and uncertain and extreme records (records without calving or birth date, with days to service after calving <21 or >250, or without next calving date), the final data set included 827,802 artificial insemination service records for 424,513 cows born from 1985 to 2000, and in 2,953 herds. Effects included in the model were year of birth (1985 to 1989, 1990 to 1994, 1995 to 2000), DIM class, milk production level (high, medium, low based on SD), service month, the covariate of cow age at calving, and 2- and 3-way interactions. Over time, an increase was observed for milk production and an overall decline in CR occurred. Examination of month by milk production subclass least squares means showed that in cool months (November to April) the deterioration of CR over time was small for low and medium milk production cows and virtually none for high-producing cows. However, in other months (May to June), there was a large decline over time in CR for cows in all milk production level subclasses. The trends in CR by DIM subclasses were examined for the months of February, May, June, and August. There was a general increase in CR with increasing DIM for all months within all birth-year groups. The months of February and August were somewhat similar for CR up to 175 DIM for the different birth-year groups. Much larger differences over time were observed for the months of May and June, and it appeared that for these 2 mo, cows in recent periods did not return to the same level of performance as cows in earlier periods. It may be that there has been a decline over time in the ability of cows to handle the onset of heat stress or the switch to pasture-based management systems.

Heritability estimates associated with alternative definitions of mastitis and correlations with somatic cell score and yield.

The objectives of this study were to compare alternative mastitis definitions and to estimate genetic correlations of producer-recorded mastitis with somatic cell score (SCS) and yield. Cow health events and lactation records from June 2002 through October 2007 were provided by Dairy Records Management Systems (Raleigh, NC). First- through fifth-lactation records from cows calving between 20 and 120 mo of age and that calved in a herd-year with at least 1% of cows with a clinical mastitis event were retained. The edited data contained 118,516 lactation records and 1,072,741 test-day records of 64,893 cows. Mastitis occurrence (1 = at least one mastitis event during lactation or test-day interval, 0 = no mastitis events), number of mastitis events during lactation, SCS, and yield were analyzed with animal models (single trait) or sire-maternal grandsire models (multiple trait) in ASREML. Comparisons were made among models assuming a normal distribution, a binary distribution, or Poisson distribution (for total episodes). The overall incidence of clinical mastitis was 15.4%; and heritability estimates ranged from 0.73% (test-day interval mastitis with a linear model) to 11.07% (number of mastitis episodes with a Poisson model). Increased mastitis incidence was genetically correlated with higher SCS (range 0.66 to 0.88) and was generally correlated with higher yield (range -0.03 to 0.40), particularly during first lactation (0.04 to 0.40). Significant genetic variation exists for clinical mastitis; and health events recorded by producers could be used to generate genetic evaluations for cow health. Sires ranked similarly for daughter mastitis susceptibility regardless of how mastitis was defined; however, test-day interval mastitis and a total count of mastitis episodes per lactation allow a higher proportion of mastitis treatments to be included in the genetic analysis.

Environmental effects on conception rates of Holsteins in New York and Georgia.

The purpose of this study was to investigate the compounded impact on conception rates (CR) of the effects of milk production, service month, and days in milk (DIM) by using recent artificial insemination records of Holsteins in New York (NY) and Georgia (GA). Dairy Herd Improvement records were obtained from Dairy Records Management Systems in Raleigh, North Carolina. After removing records with lactations >1 and uncertain and extreme records (records without a calving or birth date, with days to service after calving of <21 or >250, and without the next calving date), the final data set comprised 298,015 service records for 160,879 cows and 23,366 service records for 12,184 cows in NY and GA, respectively, from 2000 to 2003. The analytical model included DIM class, milk-production level, service month, the covariate of cow's age at calving, and all 2-way interactions. The 2 states were analyzed separately. In general across the 2 states, CR declined as milk production increased, and CR declined during the hottest months. Conception rate was similar in NY and GA, at approximately 55% from December to April. In NY, CR declined by approximately 10% in May and June and mostly recovered by July. In GA, the CR started declining in May, bottomed at 31% in September, and did not recover until December. The difference in CR between high- and low-producing cows was 7% in NY and 6% in GA. That difference was the strongest from June to July in GA (15%) and was more uniform in NY. The increase in CR with increasing DIM varied across service season. The CR was nearly flat from 50 to 125 DIM in NY for all seasons, except for a large increasing trend in spring. In GA, there was also an increasing trend in fall. Conception rates were similar in NY and GA between December and May, and were strongly influenced by heat stress in GA from June to November. A decline in CR for reasons other than heat stress was present in both states in late spring. High production resulted in a faster decline of the CR in GA under heat stress. Models analyzing service records should include the DIM x season x region interaction.

Voluntary waiting period and adoption of synchronized breeding in dairy herd improvement herds.

Voluntary waiting period and adoption of synchronized breeding (ovulation synchronization followed by timed artificial insemination) were characterized from 33 million services of Holsteins and Jerseys in Dairy Herd Improvement herds. Calving month, calving year, and parity had large effects on days to first service for both breeds. Holstein cows that calved during March and April were bred later than those that calved during other months (February and March for Jerseys), whereas cows that calved during September and October were bred earlier. First-parity cows had longer days to first service than did second-parity cows. Herd-year voluntary waiting period was measured as the days postpartum by which 10% of cows had received a first insemination. Median days to reach 10% of cows bred were 55.5 d. Over 65% of herds had 10% of cows inseminated by 60 d postpartum, the voluntary waiting period assumed for national evaluations for daughter pregnancy rate. Herd-years with synchronized breeding at first insemination were identified through chi2 analysis based on deviation of observed frequency of first inseminations by day of the week from an expected equal frequency and by the maximum percentage of cows inseminated on a particular day of the week. Herds that were identified as having synchronized breeding had fewer days to first service (17.0), more services (0.16/cow), and fewer days open (9.1) than did herds that were classified as having traditional estrus detection. Synchronized herds also had a standard deviation for days to first service that was only 38% as large as that for herds that bred on observed estrus. Adoption of synchronized breeding for first services steadily increased from 1.9% of herd-years (2% of cows) for 1996 to 19.9% of herd-years (34.9% of cows) for 2005. Procedures for genetic evaluation of daughter pregnancy rate should be examined to determine if herd regimen for reproductive management affects results.

Genetic analysis of clinical mastitis data from on-farm management software using threshold models.

Producer-recorded clinical mastitis data from 77,791 cows in 418 herds were used to determine the potential for genetic improvement of mastitis resistance using data from on-farm management software programs. The following threshold sire models were applied: 1) a single-trait lactation model, where mastitis was recorded as 0 or 1 in first lactation only; 2) a 3-trait lactation model, where mastitis was recorded as 0 or 1 in each of the first 3 lactations, and 3) a 12-trait, lactation-segment model, where mastitis was recorded as 0 or 1 in each of 4 segments (0 to 50, 51 to 155, 156 to 260, and 261 to 365 d postpartum) in each of the first 3 lactations. Lactation incidence rates were 0.16, 0.20, and 0.24 in first, second, and third lactation, respectively, and incidence rates within various segments of these lactations ranged from 0.036 in late first lactation to 0.093 in early third lactation. Estimated heritability of liability to clinical mastitis ranged from 0.07 to 0.15, depending on the model and stage of lactation. Heritability estimates were higher in first lactation than in subsequent lactations, but estimates were generally similar for different segments of the same lactation. Genetic correlations between lactations from the 3-trait model ranged from 0.42 to 0.49, while correlations between segments within lactation from the 12-trait model ranged from 0.26 to 0.64. Based on the results presented herein, it appears that at least 2 segments are needed per lactation, because mastitis in early lactation is lowly correlated with mastitis in mid or late lactation. Predicted transmitting abilities of sires ranged from 0.77 to 0.89 for probability of no mastitis during the first lactation and from 0.36 to 0.59 for probability of no mastitis during the first 3 lactations. Overall, this study shows that farmer-recorded clinical mastitis data can make a valuable contribution to genetic selection programs, but additional systems for gathering and storing this information must be developed, and more extensive data recording in progeny test herds should be encouraged.

Milk urea nitrogen concentration: heritability and genetic correlations with reproductive performance and disease.

The objectives of this study were to estimate the heritability of milk urea nitrogen (MUN) concentration and describe the genetic relationship between MUN and reproductive performance and between MUN and diseases in Holsteins. Dairy Records Management Systems (Raleigh, NC) provided lactation data. The Danish Agricultural Advisory Center provided breeding value estimates for diseases. Infrared (IR) and wet chemistry (WC) data were analyzed separately. Heritabilities and genetic correlations for 2 different measures of MUN and reproductive performance were estimated with an animal model using ASREML. Heritabilities for MUN were estimated using all lactations combined (lactations 1 through 5) and separately for first lactation and second lactation. Genetic correlations with reproduction and health were estimated separately for parities 1 and 2. Herd-test-day or herd-year-season along with age at calving and days in milk were included as fixed effects in all models. Heritability estimates for all lactations combined were 0.15 for WC MUN and 0.22 for IR MUN. Genetic correlations between WC MUN and 2 measures of reproductive performance, days to first service, and first service conception were not different from zero. In contrast, the genetic correlation between WC MUN and days open of 0.21 in first lactation and 0.41 in second lactation indicated that higher WC MUN values were associated with increased days open. Correlations among estimated breeding values for MUN and estimated breeding values for Danish diseases identified no significant relationships. Although the results of this study indicate that heritable variation for MUN exists, the inability to identify significant genetic relationships with several measures of disease or reproductive performance appears to limit the value of MUN in selection for disease resistance and improved reproduction.

Genetic evaluation of dairy sires for milking duration using electronically recorded milking times of their daughters.

The potential of using electronically recorded data from on-farm milking parlor and herd management software programs for genetic evaluation of dairy sires for milking duration of their daughters was assessed in the present study. Single measurements of milking duration were collected weekly from 29 herds between June 1, 2003 and April 1, 2004. These included 73,547 observations corresponding to 10,152 Holstein cows from 1551 sires. Average milking duration for a single milking in our data set was 4.5 min. Estimated heritability of milking duration was 0.17, and predicted transmitting abilities (PTA) of individual sires ranged from -0.48 min for sires with the fastest milking daughters to 0.59 min for sires with the slowest milking daughters. The correlation between PTA for milking duration and PTA for somatic cell score (SCS) was -0.15, indicating that sires whose daughters milk most quickly also tend to transmit higher SCS to their progeny. Correlations between PTA milking duration and PTA for teat placement and teat length were -0.14 and 0.20, respectively, indicating that sires that transmit wide teat placement and long teats tend to have daughters that milk slowly. Based on the results presented herein, it appears that genetic selection based on objective, electronically recorded milking times is possible. This approach would greatly improve the quality and efficiency of data collection relative to conventional evaluations of milking speed, which are based on farmer surveys. The number of herds currently equipped to routinely capture milking times is limited, but this number is increasing very rapidly. Future research should focus on refinement of data reporting and validation systems, as well as estimation of the economic value of milking duration. This trait may have an intermediate optimum, because cows that milk too slowly will disrupt parlor flow and reduce milking efficiency, but cows that milk too quickly may be at greater risk for mastitis.

Genetic selection for health traits using producer-recorded data. II. Genetic correlations, disease probabilities, and relationships with existing traits.

The objectives of this study were to calculate genetic correlations between health traits that were recorded in on-farm herd management software programs and to assess relationships between these traits and other traits that are routinely evaluated in US dairy sires. Data consisted of 272,576 lactation incidence records for displaced abomasum (DA), ketosis (KET), mastitis (MAST), lameness (LAME), cystic ovaries (CYST), and metritis (MET) from 161,622 cows in 646 herds. These data were collected between January 1, 2001 and December 31, 2003 in herds using the Dairy Comp 305, DHI-Plus, or PCDART herd management software programs. Binary incidence data for all disorders were analyzed simultaneously using a multiple-trait threshold sire model that included random sire and herd-year-season of calving effects. Although data from multiple lactations were available for some animals, our genetic analysis included only first parity records due to concerns about selection bias and improper modeling of the covariance structure. Heritability estimates for the presence or absence of each disorder during first lactation were 0.14 for DA, 0.06 for KET, 0.09 for MAST, 0.03 for LAME, 0.04 for CYST, and 0.06 for MET. Estimated genetic correlations were 0.45 between DA and KET, 0.42 between KET and CYST, 0.20 between MAST and LAME, 0.19 between KET and LAME, 0.17 between DA and CYST, 0.17 between KET and LAME, 0.17 between KET and MET, and 0.16 between LAME and CYST. All other correlations were negligible. Correlations between predicted transmitting abilities for the aforementioned health traits and existing production, type, and fitness traits were low, though it must be noted that these estimates may have been biased by low reliability of the health trait evaluations. Based on results of this study, it appears that genetic selection for health disorders recorded in on-farm software programs can be effective. These traits can be incorporated into selection indices directly, or they can be combined into composite traits, such as "reproductive disorders", "metabolic disorders", or "early lactation disorders".

Genetic selection for health traits using producer-recorded data. I. Incidence rates, heritability estimates, and sire breeding values.

The objective of this study was to determine the feasibility of genetic selection for health traits in dairy cattle using data recorded in on-farm herd management software programs. Data regarding displaced abomasum (DA), ketosis (KET), mastitis (MAST), lameness (LAME), cystic ovaries (CYST), and metritis (MET) were collected between January 1, 2001 and December 31, 2003 in herds using Dairy Comp 305, DHI-Plus, or PCDART herd management software programs. All herds in this study were either participants in the Alta Genetics (Watertown, WI) Advantage progeny testing program or customers of the Dairy Records Management Systems (Raleigh, NC) processing center. Minimum lactation incidence rates were applied to ensure adequate reporting of these disorders within individual herds. After editing, DA, KET, MAST, LAME, CYST, and MET data from 75,252 (313), 52,898 (250), 105,029 (429), 50,611 (212), 65,080 (340), and 97,318 (418) cows (herds) remained for analysis. Average lactation incidence rates were 0.03, 0.10, 0.20, 0.10, 0.08, and 0.21 for DA, KET, MAST, LAME, CYST, and MET (including retained placenta), respectively. Data for each disorder were analyzed separately using a threshold sire model that included a fixed parity effect and random sire and herd-year-season of calving effects; both first lactation and all lactation analyses were carried out. Heritability estimates from first lactation (all lactation) analyses were 0.18 (0.15) for DA, 0.11 (0.06) for KET, 0.10 (0.09) for MAST, 0.07 (0.06) for LAME, 0.08 (0.05) for CYST, and 0.08 (0.07) for MET. Corresponding heritability estimates for the pooled incidence rate of all diseases between calving and 50 d postpartum were 0.12 and 0.10 for the first and all lactation analyses, respectively. Mean differences in PTA for probability of disease between the 10 best and 10 worst sires were 0.034 for DA, 0.069 for KET, 0.130 for MAST, 0.054 for LAME, 0.039 for CYST, and 0.120 for MET. Based on the results of this study, it appears that genetic selection against common health disorders using data from on-farm recording systems is possible.

Correlations among body condition scores from various sources, dairy form, and cow health from the United States and Denmark.

The objectives of this study were to estimate genetic correlations among body condition scores (BCS) from various sources, dairy form, and measures of cow health. Body condition score and dairy form evaluated during routine type appraisal was obtained from the Holstein Association USA, Inc. A second set of BCS was obtained from Dairy Records Managements Systems (DRMS) and was recorded by producers that use PCDART dairy management software. Disease observations were obtained from recorded veterinarian treatments in several dairy herds in the United States. Estimated breeding values for diseases in Denmark were also obtained. Genetic correlations among BCS, dairy form, and cow health traits in the United States were generated with sire models. Models included fixed effects for age, DIM, and contemporary group. Random effects included sire, permanent environment, herd-year season for health traits, and error. Predicted transmitting abilities (PTA) for BCS and dairy form were correlated with estimated breeding values for disease in Denmark. The genetic correlation estimate between BCS from DRMS and BCS from the Holstein Association USA, Inc., was 0.85. The genetic correlation estimate between BCS and a composite of all diseases in the United States was -0.79, and PTA for BCS was favorably correlated with an index of resistance to disease other than mastitis in Denmark (0.27). Dairy form was positively correlated with a composite of all diseases in the United States (0.85) and was unfavorably correlated with an index for resistance to disease other than mastitis in Denmark (-0.29). Adjustment for protein yield PTA had a minimal affect on correlations between PTA for BCS or dairy form and disease in Denmark. Selection for higher body condition or lower dairy form with continued selection for yield may slow deterioration in cow health as a correlated response to selection for increased yield.