Short communication: Informative value of an ELISA applied to bulk tank milk to assess within-herd prevalence of digital dermatitis in dairy herds.

The objective of this study was to assess whether an antibody ELISA applied to bulk tank milk (BTM) could be used to accurately estimate within-herd prevalence of digital dermatitis (DD). The ELISA was designed for the detection of antibodies against Treponema phagedenis-like strain V1 (PrrA antigen). The hind feet of all lactating cows from 40 commercial French dairy herds with a history of DD were scored by an observer in the milking parlor, using the 4 M-stage system. After milking, a BTM sample was collected and tested for anti-Treponema phagedenis-like antibodies using the antibody ELISA. Within-herd DD prevalence at the cow level was determined using 2 different approaches: (1) having DD lesion on at least 1 hind foot (Prev; prevalence of affected cows), and (2) having an M1 or M2 lesion on at least 1 hind foot (PrevA; prevalence of cows affected by DD in an active stage). Receiver operating characteristic analysis was used to determine both optimal within-herd DD prevalence and BTM sample to positive (S/P) ratio cut-off values. Two optimal cut-off values were identified. Herds with an S/P ratio of BTM ≤0.2 had a Prev ≤10% (sensitivity = 0.97, specificity = 1), whereas herds with an S/P ratio of BTM >0.38 had a Prev >40% (sensitivity = 0.94, specificity = 0.86). In the same way but with a slightly lower specificity, an S/P ratio >0.38 corresponds also to a PrevA >18% (sensitivity = 0.92, specificity = 0.70). The BTM antibody ELISA shows great promise for screening purposes during DD management programs.

Estimating milk loss based on somatic cell count at the cow and herd level.

There is a direct relationship between elevated somatic cell count (SCC) in an individual cow milk production and milk loss. This relationship has been used at the herd level to estimate an overall herd milk loss due to subclinical mastitis and to use recovery of this lost milk as a financial benefit to cover the cost of intervention strategies to improve milk quality. The objective of this study was to estimate the recoverable milk revenue on a per cow basis for herds moving from one herd average SCC level to a newer, lower level. Test-day records from 1,005,697 dairy cows in 3,741 herds between 2009 to 2019 were used. Milk yield loss for each cow in each herd on test day was estimated using a mixed effects regression equation, and then summed to estimated total herd milk loss. These herd average daily milk loss estimates were then related to the bulk tank SCC, and the distribution of underlying individual cow SCC were examined. The distributions in daily herd milk loss for various bulk tank SCC values were generated, and estimates of recoverable milk loss were generated to simulate a herd moving from their current bulk tank SCC to a new lower level. The results indicate that estimates of total herd milk yield loss vary with the distribution of cow-level SCC and parity within the herd, so it is imperative that milk loss be calculated on a per cow basis. Further, the recoverable milk loss estimates based on moving to a lower bulk tank SCC where milk loss is still occurring was relatively small compared with the traditional assumption that all milk loss would be recovered, and less than most herd owners and advisors would expect.

Effect of a calcium-energy supplement drink at calving on lactation performance: Milk yield and composition, odds to reach a next lactation, and calving interval.

Supplementation of Ca products to cows after calving is common in calving protocols. This study evaluated the effect of a Ca-energy drink voluntarily consumed on milk yield and composition, odds to reach a next lactation, and calving interval. This prospective randomized study included a blinded placebo and was conducted in 10 commercial dairy farms that included 504 Holstein dairy cows. Cows were blocked within farm by calving sequence and parity (primiparous or multiparous). Within each block of 2 animals, cows were randomly assigned to 1 of 2 treatments: a Ca-energy supplement drink (CAE, n = 255) providing 45 g of Ca and other components (dextrose, lactose, protein, fat, other minerals and vitamins), a placebo (i.e., 100 g of cellulose and 20 g of dextrose; CON, n = 249), both strictly offered to the animals for voluntary consumption. Treatments were offered mixed in 20 L of water within 3 h after calving. Milk data were analyzed using 2 approaches. The first, most classical, evaluated the effect of the treatments on observed milk data, whereas the second approach evaluated the effect on milk residuals (i.e., the difference between observed milk data and a prediction made by a herd test-day model). Eighty-one percent of the CAE cows fully consumed the treatment, whereas only 50% of CON cows did. No differences were detected for observed milk yield, nor for composition in multiparous cows. The only production effect observed on multiparous cows was a treatment by time interaction for milk fat yield, reflecting greater yield for CAE cows between 100 and 150 d in milk only. However, primiparous cows receiving CAE had increased milk (+0.8 kg/d) and component yields (i.e., +40 g/d of protein) compared with CON cows. These effects were more evident when milk and milk components residuals data were analyzed (i.e., +1.5 kg/d for milk yield and +57 g/d of protein). This was achieved with a herd test-day model that allowed milk and milk components data to be adjusted for environmental and genetic factors (i.e., farm effect, time effect, age at calving, parity, stage of lactation, breeding value). The treatment had no effect on the probability of reaching the next lactation (i.e., 72% of CAE cows had a next calving against 69% in CON). Primiparous cows receiving CAE had a longer calving interval compared with CON cows. At 400 d after the application of the treatment, 65% of CAE primiparous cows had a next calving, whereas 81% of CON primiparous cows had calved already. The supplementation of the tested oral Ca-energy solution at calving did not increase the probability to reach a next lactation for neither primiparous or multiparous, but positively influenced milk yield and milk component yields for primiparous.

Assessment of feed and economic efficiency of dairy farms based on multivariate aggregation of partial indicators measured on field.

Many of the metrics used to evaluate farm performance are only partial indicators of farm operations, which are assumed to be best predictors of the whole farm efficiency. The main objective of this work was to identify aggregated multiple indexes of profitability using common partial indicators that are routinely available from individual farms to better support the short-term decision-making processes of the cattle-feeding process. Data were collected from face-to-face interviews with farmers from 90 dairy farms in Italy and used to calculate 16 partial indicators that covered almost all indicators currently used to target feeding and economic efficiency in dairy farms. These partial indicators described feed efficiency, energy utilization, feed costs, milk-to-feed price ratio, income over feed costs, income equal feed cost, money-corrected milk, and bargaining power for feed costs. Calculations of feeding costs were based on lactating cows or the whole herd, and income from milk deliveries was determined with or without considering the milk quality payment. Multivariate factor analysis was then applied to the 16 partial indicators to determine simplified and latent structures. The results indicated that 5 factors explained 70% of the variability. Each of the original partial indicator was associated with all factors in different proportions, as indicated by loading scores from the multivariate factor analysis. Based on the loading scores, we labeled these 5 factors as "economic efficiency," "energy utilization," "break-even point," "milk-to-feed price," and "bargaining power of the farm," in decreasing order of explained communality. The first 3 factors shared 83% of the total communality. Feed efficiency was similarly associated with factor 1 (53% loading) and factor 2 (66% loading). Only factor 4 was significantly affected by farm location. Milk production and herd size had significant effects on factor 1 and factor 2. Our multivariate approach eliminated the problem of multicollinearity of partial indicators, providing simple and effective descriptions of farm feeding economics. The proposed method allowed the evaluation, benchmarking, and ranking of dairy herd performance at the level of single farms and at territorial level with high opportunity to be used or replicated in other areas.

A virtual dairy herd as a tool to teach dairy production and management.

The objective of this project was to develop and test a web-based virtual dairy herd to help students understand the structure and functioning of a dairy herd, and to promote active learning. At the beginning of the course, the instructor defines the profiles of herds to be assigned to students (e.g., herd size, production, diets, fertility). Each student has a unique herd and engages in decision-making for desired management practices in the herd. Modeled events are based on cow physiology and normal dairy herd management practices. Students' activities and decisions include heat detection, insemination, pregnancy diagnosis, dry-off, diet specifications, feeding groups, colostrum and milk-replacer feeding, weaning, treatment of diseases, and milk withdrawal from the tank if antibiotics are used, among others. The daily output provides information on technical indexes, economic performance, counters of incorrect decisions as feedback for students, and score. Time in class can be devoted to discussions of dairy management issues. Additional exercises based on students' own herds (e.g., calculating required space for cows, land for forage production, manure management) can also be implemented. Students' performance in the virtual dairy farm was monitored over 3 years. The average score (n = 326) was 87.8 ± 1.1 over 100 points, suggesting that self-learning with the virtual dairy farm was highly successful. At the end of each semester, students (n = 277) responded to a survey on the experience of working with the virtual dairy herd. Most students (>87%) agreed that the virtual dairy herd was more effective and motivating than traditional lectures and helped them understand dairy production better. In an unannounced test conducted at least 2 wk before the final exam, students (n = 207) were asked 14 questions on dairy cattle and 14 similar questions on other species taught in the same class through traditional lectures. A similar test on the same students (n = 142) was conducted in their fifth semester (2 years later). Results were better in dairy compared with other species questions in the first (9.6 vs. 3.7) and fifth (8.0 vs. 3.8) semesters. The virtual dairy herd is an effective tool for teaching introductory courses in dairy production. The program can be accessed at www.virtualdairyfarm.org, and a manual and videos with instructions for instructors and students are available online.

Dynamics of neutralizing antibodies against Bovine respiratory syncytial virus in a dairy herd from Santa Fe Province, Argentina.

Bovine respiratory syncytial virus (BRSV) is one of the most relevant agents responsible for respiratory disease in cattle from both dairy and beef farms. BRSV is spread by horizontal contact causing a constant presence of seropositive animals that favors viral circulation throughout the year. Moreover, reinfections with BRSV are frequent between animals regardless of their age as BRSV does not confer long-lasting protective immunity. Several studies have demonstrated the circulation of BRSV in cattle from different regions of the world; however, little is known about the dynamics of BRSV infection in cows before and after they begin lactation. The aim of this work was to study the dynamics of BRSV neutralizing antibodies from birth up to 36 months of age in a closed dairy herd of Argentina specifically around the lactation period. Passive maternal antibodies against BRSV started to decrease monthly and became almost undetectable at 8 months of age. We detected two potential infection points at months 11 and 27 after birth, in which 30% and 45% of the animals showed seroconversion, respectively. Specifically, an increase in the proportion of seropositive cows after the start of lactation suggests that they became reinfected around the time they began lactating. We demonstrate the importance of understanding BRSV dynamics in a closed dairy herd to review the vaccination schedule of the animals to achieve protection against BRSV infection.

El virus respiratorio sincitial bovino (Bovine respiratory syncytial virus, [BRSV]) es uno de los principales agentes responsables de la enfermedad respiratoria en bovinos, tanto de tambos como de cría. El virus se transmite horizontalmente y causa la presencia constante de animales seropositivos, lo cual favorece la circulación viral a lo largo del año. A su vez, las reinfecciones por BRSV son frecuentes entre animales independientemente de su edad, dado que el virus no confiere inmunidad protectora a largo plazo. Numerosos estudios han demostrado la circulación de BRSV en bovinos de diferentes regiones del mundo, sin embargo, poco se conoce acerca de la dinámica de infección en vacas antes y después del inicio de la fase de lactancia. El objetivo de este trabajo fue estudiar la dinámica de anticuerpos neutralizantes anti- BRSV en vacas lecheras desde el nacimiento hasta los 36 meses de vida en un tambo cerrado de Argentina, específicamente, en el período de lactancia. Los anticuerpos pasivos específicos para BRSV comenzaron a declinar mensualmente hasta ser casi indetectables a los 6 meses. Detectamos dos potenciales puntos de infección a los meses 11 y 27 luego del nacimiento, momentos en los que el 30 y el 45% de los animales mostraron seroconversión, respectivamente. El incremento en la proporción de vacas seropositivas luego del comienzo de la lactancia sugiere que estas se reinfectaron en el inicio de dicha etapa. Demostramos la importancia de entender la dinámica de circulación del BRSV en un tambo cerrado, a fin de revisar el esquema de vacunación de los animales para que estén protegidos frente a la posible infección por este virus.

A survey on the incidence of Prototheca mastitis in dairy herds in Lublin province, Poland.

Prototheca mastitis has recently become an emerging disease; although its incidence is increasing steadily, its epidemiology remains largely understudied. The aim of this work was to investigate the prevalence of Prototheca spp. in dairy cows and their environment in Lublin province, covering most of southeastern Poland. Between December 2015 and July 2016, a total of 172 milking cows from 10 dairy farms were inspected for mastitis using clinical examination and the California Mastitis Test (CMT). Quarter milk samples (QMS, n = 179) and body site swabs (n = 151) from CMT-positive cows were collected for microbiological culture. In addition, we evaluated QMS and body site swabs from 23 healthy cows, along with 91 environmental samples. Of 100 CMT-positive cows, 71 had at least one QMS positive for microbial growth. In 8 (11.3%) of these cows, originating from 7 dairy farms, Prototheca spp. were cultured. The average somatic cell count of the Prototheca-containing milk was 4.02 × 106 cells/mL compared with 0.13 × 106 cells/mL of the Prototheca-free milk (collected from control animals). No significant differences were observed between mastitis and control cows with respect to counts of total white blood cells, lymphocytes, neutrophils, and eosinophils. Half of the cows with Prototheca spp. in their milk did not yield the algae from other anatomical sites. Eight cows were negative for the presence of Prototheca spp. in their milk but positive for the algae in swabs from anatomical sites. Among the environmental sources that were positive for Prototheca growth were watering troughs, manure, feed, and mud. All (45) Prototheca isolates recovered in this study were subjected to species- and genotype-level molecular identification. All QMS and most of the animal swabs (90%) yielded Prototheca zopfii genotype (gen.) 2. Of the animal samples, P. zopfii gen. 1 and Prototheca blaschkeae were isolated only from feces and rectum. Environmental samples grew either P. zopfii gen. 2 (67%) or P. zopfii gen. 1 (33%). This study demonstrates that P. zopfii gen. 2 is the third most common pathogen of mastitis in cattle in southeast Poland, with an overall incidence of 4.6%. Finding Prototheca spp., including P. zopfii gen. 1 and 2 and P. blaschkeae, in stool and rectal swabs from healthy animals may suggest their role as nonpathogenic microflora of bovine gut.

Inclusion of herdmate data improves genomic prediction for milk-production and feed-efficiency traits within North American dairy herds.

Genomic data are widely available in the dairy industry and provide a cost-effective means of predicting genetic merit to inform selection decisions and increase genetic gains. As more dairy farms adopt genomic selection practices, dairy producers will soon have genomic data available on all of the animals within their herds. This is a very rich, but currently underused, source of information. Herdmates provide an excellent indication of how a selection candidate's genetics will perform within a given herd, noting that herdmates often include close relatives that share a similar environment. The study objective was to evaluate the utility of incorporating herdmate data into genomic predictions in a data set composed of 3,303 Holsteins from one herd in Canada and 6 herds throughout the United States. Within-herd prediction accuracy was assessed for milk-production and feed-efficiency traits determined from genomic best linear unbiased prediction under 4 different scenarios. Scenario 1 did not include herdmates in the training population. Scenarios 2 through 4 included herdmates in the training population, and scenarios 3 and 4 also included modeling of herd-specific marker effects. Leave-one-out cross validation was used to maximize the number of herdmates in the training population in scenarios 2 through 4, while maintaining constant training population size with scenario 1. Results from the present study reveal the importance of incorporating herdmate data into genomic evaluations. Inclusion of herdmates in the training population improved mean within-herd prediction accuracy for milk-production traits (± standard error) by 0.08 ± 0.03 (milk yield), 0.07 ± 0.03 (fat percentage), and 0.05 ± 0.01 (protein percentage) and feed-efficiency traits by 0.07 ± 0.02 (milk energy), 0.03 ± 0.02 (DMI), and 0.08 ± 0.01 (metabolic body weight). Modeling herd-specific marker effects further improved mean within-herd prediction accuracy for milk yield and energy by 0.03 ± 0.01 and 0.02 ± 0.01, respectively. Herds with higher within-herd heritability and low genomic correlation with the remaining herds benefitted most from the inclusion of herdmate data.

Milk ß-hydroxybutyrate concentration measured by Fourier-transform infrared and flow-injection analyses from samples taken at different times relative to milking.

Analysis of milk BHB concentration by Fourier-transform infrared (FTIR) spectrometry more frequently than regular milk testing could help dairy producers in decision making, particularly if it would be possible to use small hand-stripped samples (hereinafter simply called samples) taken between dairy herd improvement (DHI) test-samples analysed using DHI algorithms. The aim of this Research Communication was to evaluate milk BHB concentration and the prevalence of elevated milk BHB concentration analysed by FTIR spectrometry compared with flow-injection analysis (SKALAR) from samples taken at different times relative to the milking. A total of 293 early-lactation cows in 44 commercial dairy herds were involved in the study. Herds were visited once during the morning milking when a routine DHI test-sample was obtained using in-line milk samplers. Additional milk samples were taken by hand stripping as follows: (1) Just before connecting the milking machine; (2) immediately after removing the milking machine; (3) 3 h after milking and (4) 6 h after milking. Milk samples were analysed for BHB concentration by FTIR and SKALAR, the latter being the reference method. Milk BHB concentration from samples taken before milking was different between FTIR and SKALAR whereas no difference was noted for other sampling times, although milk BHB concentration rose as time after milking increased. Except for DHI test-samples for which prevalence was not different between analysis methods, prevalence of elevated milk BHB concentration (≥0.15 mmol/l) was greater for FTIR analysis. However, no difference in prevalence was observed between SKALAR and FTIR when using a threshold of ≥0.20 mmol/l. In summary, hand-stripped milk samples taken any time after removing the milking machine until 6 h after the milking can be recommended for FTIR analysis of elevated milk BHB concentration prevalence provided a threshold of 0.20 mmol/l is used.

Associations between routinely collected Dairy Herd Improvement data and insemination outcome in UK dairy herds.

Milk constituent concentrations in samples taken during early lactation are often used to generate proxy measures for energy balance in dairy herds. This study aimed to explore associations between these and other measures routinely recorded by Dairy Herd Improvement schemes and insemination outcome, with an emphasis on the likely predictiveness of such measures for conception risk (the proportion of inseminations that are successful) at herd level. Data from 312 UK dairy herds were restructured so that each unit of data represented an insemination at less than 100 d in milk (DIM). Milk constituent concentrations from the first and second test days (corrected for the effects of season and DIM at sampling) were used as potential predictors of insemination outcome in a logistic regression model. Other predictors included representations of milk yield and other information routinely collected by Dairy Herd Improvement Associations; random effects were used to account for clustering at cow and herd levels. The final model included a large number of predictors, with several interaction and nonlinear terms. The relative effect sizes of the measures of early lactation milk constituent concentrations were small. The full model predicted just under 64% of observed variation in herd-year conception risk (i.e., the proportion of inseminations that were successful in each herd in each calendar year); however, around 40% was accounted for by the herd-level random effect. The predictors based on early lactation milk constituent concentrations accounted for less than 0.5% of observed variation, and representations of milk yield (both overall level of yield and early lactation curve shape) accounted for around 7%; DIM at insemination, parity, interservice interval, year, and month accounted for the remaining 15%. These results suggest that early lactation milk constituent information is unlikely to predict herd conception risk to a useful extent. The large proportion of observed variation explained by the herd-level random effect suggests that there are unmeasured (in this study) or unmeasurable factors that are consistent within a herd and are highly influential in determining herd conception risk.

Bioeconomics of sexed semen utilization in a high-producing Holstein-Friesian dairy herd.

A bioeconomic, stochastic spreadsheet model, that included calculation of the net present value of the additional value of all future descendants resulting from increased selection intensity, was developed to study the profitability of using sexed semen in a high input-high output dairy herd. Three management strategies were modeled: (1) only heifers inseminated with sex-sorted semen and cows inseminated with unsorted semen; (2) both heifers and cows inseminated with sex-sorted semen; and (3) a reference scenario, in which all breeding females were inseminated with unsorted semen. A Monte Carlo simulation (@risk software, Palisade Corp., Ithaca, NY) was run to study the sensitivity of net profit and sexed semen advantage to key input parameters. Most input parameters were given truncated normal distributions, whereas the maximum numbers of inseminations in heifers and cows were given discrete distribution functions. The calculated intensity of selection accounted for the different numbers of dairy females born for each of the 100,000 iterations. Using sexed semen (X-sorted, female) was shown to be profitable, with insemination of both heifers and cows being most profitable. The returns on assets were higher when only heifers were inseminated with sexed semen (8.54% ± 2.94; ±SD) or all females were inseminated with sexed semen (8.85% ± 2.93) than when all females were inseminated with unsexed semen (8.38% ± 2.95). The range in net profit was most sensitive to the assumed distributions of milk protein price (€/kg), milk fat price (€/kg), cow pregnancy rate, fertilizer price (€/t), and concentrate price (€/t) when unsorted semen was used. When only heifers or both heifers and cows were inseminated with sex-sorted semen, the range in net profit was most sensitive to the same distributions, with fertilizer price and cow pregnancy rate in reverse order of sensitivity. However, the range in sex-sorted semen advantage (in net profit) when only heifers were inseminated with sex-sorted semen was most sensitive to the assumed distributions of cow pregnancy rate, sex-sorted semen pregnancy rate as a percent of unsorted semen rates, standard deviation of index, additional cost of sex-sorted semen (€/dose), dairy bull calf price (€/head), and dairy heifer calf price (€/head). When both heifers and cows were inseminated, the order of importance of the last 2 inputs was reversed. This study highlights the relatively high effect of pregnancy rate and the genetic value of dairy bulls in determining the level of financial advantage from using sex-sorted semen in a dairy herd.

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

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

Economic opportunities for using sexed semen and semen of beef bulls in dairy herds.

Dairy farmers can increase the number of dairy heifer calves born in their herd by using sexed semen. They can reduce the number of both dairy bull and heifer calves by using beef semen. Long before sexed semen became commercially available, it was believed that it would provide opportunities for increasing genetic level in both herds and populations. In this study, we studied the potential for increasing the genetic level of a herd by using beef semen in combination with sexed semen. We tested the hypothesis that the potential of increasing the genetic level and the overall net return would depend on herd management. To test this hypothesis, we simulated 7 scenarios using beef semen and sexed semen in 5 herds at different management levels. We combined the results of 2 stochastic simulation models, SimHerd and ADAM. SimHerd simulated the effects of the scenarios and management levels on economic outcomes (i.e., operational return) and on technical outcomes such as the parity distribution of the dams of heifer calves, but it disregarded genetic progress. The ADAM model quantified genetic level by using the dams' parity distributions and the frequency of sexed and beef semen to estimate genetic return per year. We calculated the annual net return per slot as the sum of the operational return and the genetic return, divided by the total number of slots. Net return increased up to €18 per slot when using sexed semen in 75% genetically superior heifers and beef semen in 70% genetically inferior, multiparous cows. The assumed reliability of selection was 0.84. These findings were for a herd with overall high management for reproductive performance, longevity, and calf survival. The same breeding strategy reduced net return by €55 per slot when management levels were average. The main reason for the large reduction in net return was the heifer shortage that arose in this scenario. Our hypothesis that the potential for beef semen to increase genetic level would be herd-specific was supported. None of the scenarios were profitable under Danish circumstances when the value of the increased genetic level was not included. A comparable improvement in genetic level could be realized by selectively selling dairy heifer calves rather than using beef semen.

Novel approaches to assess the quality of fertility data stored in dairy herd management software.

Scientific journals and popular press magazines are littered with articles in which the authors use data from dairy herd management software. Almost none of such papers include data cleaning and data quality assessment in their study design despite this being a very critical step during data mining. This paper presents 2 novel data cleaning methods that permit identification of animals with good and bad data quality. The first method is a deterministic or rule-based data cleaning method. Reproduction and mutation or life-changing events such as birth and death were converted to a symbolic (alphabetical letter) representation and split into triplets (3-letter code). The triplets were manually labeled as physiologically correct, suspicious, or impossible. The deterministic data cleaning method was applied to assess the quality of data stored in dairy herd management from 26 farms enrolled in the herd health management program from the Faculty of Veterinary Medicine Ghent University, Belgium. In total, 150,443 triplets were created, 65.4% were labeled as correct, 17.4% as suspicious, and 17.2% as impossible. The second method, a probabilistic method, uses a machine learning algorithm (random forests) to predict the correctness of fertility and mutation events in an early stage of data cleaning. The prediction accuracy of the random forests algorithm was compared with a classical linear statistical method (penalized logistic regression), outperforming the latter substantially, with a superior receiver operating characteristic curve and a higher accuracy (89 vs. 72%). From those results, we conclude that the triplet method can be used to assess the quality of reproduction data stored in dairy herd management software and that a machine learning technique such as random forests is capable of predicting the correctness of fertility data.

Associations between exposure to bovine herpesvirus 1 (BoHV-1) and milk production, reproductive performance, and mortality in Irish dairy herds.

As cost-benefit analyses are required to prioritize and promote disease control and eradication programs within a jurisdiction, national data relating to disease-related production losses are particularly useful. The objectives of the current study were to use Irish bovine herpesvirus 1 (BoHV-1) prevalence data in dairy herds, obtained by bulk milk sampling on 4 occasions over the 2009 lactation, to document associations between milk production, fertility performance, mortality, and BoHV-1 herd status. Bulk milk (n = 305) antibody ELISA was used to classify farms as positive or negative in terms of endemic BoHV-1. Cow-level (milk parameters only) and herd-level performance data were sourced from the Irish Cattle Breeding Federation. Ordinary linear and negative binomial regressions were used to investigate associations between milk, fertility, and mortality performance and herd-level BoHV-1 results (both categorical and continuous variables). Only slight effects on the rates of carryover cows, nonpregnant cows, and total deaths were highlighted with increasing ELISA sample/positive (%) values (incidence rate ratio = 1.001). Multiparous cows in herds BoHV-1 bulk milk antibody positive recorded a reduction in milk yield per cow per year of 250.9 L in the multivariable linear model. Milk fat and protein yields were also affected by herd BoHV-1 status, again highlighting sub-optimal milk production in BoHV-1 bulk milk-positive herds. The current study has highlighted an economical method of investigating losses due to endemic infection using repeated bulk milk sampling over a single lactation. These data can contribute to analyzing the cost-benefit of applying BoHV-1 control strategies both on farm and at a national level.

Quantification of antimicrobial consumption in adult cattle on dairy herds in Flanders, Belgium, and associations with udder health, milk quality, and production performance.

The main objective of this study was to quantify the (compound-specific) antimicrobial consumption (AMC) in adult cattle in a convenience sample of Flemish dairy herds. Antimicrobial consumption data were obtained between 2012 and 2013 by "garbage can audits" and expressed as antimicrobial treatment incidence (ATI), with the unit of the ATI being the number of defined daily doses animal (DDDA) used per 1,000 cow-days. Herds were stratified by DDDA into low-, medium-, and high-consuming herds to study the AMC per route of administration, and associations with parameters reflecting udder health, milk quality, and production performances were examined. The average ATI in adult dairy cattle for all compounds was 20.78 DDDA (per 1,000 cow-days). Large variation existed between herds (ranging from 8.68 to 41.62 DDDA). Fourth-generation cephalosporins were used most (4.99 DDDA), followed by penicillins (3.70 DDDA) and third-generation cephalosporins (2.95 DDDA). The average ATI of the critically important antimicrobials for human health (i.e., third- and fourth-generation cephalosporins and fluoroquinolones according to the World Organisation for Animal Health classification) was somewhat lower than the average ATI of the other antimicrobials (8.59 and 12.18 DDDA, respectively). The average ATI for intramammary treatment of (sub)clinical mastitis, for dry-cow therapy, and for systemically administered antimicrobials was 6.30, 6.89, and 7.44 DDDA, respectively. In low-consuming herds, most antimicrobials were being used for dry-cow therapy, whereas in high-consuming herds, most antimicrobials were being used as injectable or intramammary mastitis therapy. The incidence rate of treated mastitis was positively associated with ATI. Herds that applied blanket dry-cow therapy tended to have a higher ATI than herds in which cows were selectively dried off with long-acting antimicrobials. The ATI decreased with an increasing prevalence of primiparous cows.

Management characteristics, lameness, and body injuries of dairy cattle housed in high-performance dairy herds in Wisconsin.

The objective of this study was to benchmark the prevalence of lameness, hock and knee injuries, and neck and back injuries among high-performance, freestall-housed dairy herds in Wisconsin. A random selection of 66 herds with 200 or more cows was derived from herds that clustered with high performance in year 2011 Dairy Herd Improvement records for milk production, udder health, reproduction, and other health parameters. Herds were surveyed to collect information about management, facilities, and well-being. Well-being measures were obtained through direct observation of the high-producing mature cow group, surveying 9,690 cows in total. Total herd size averaged (mean ± standard deviation) 851±717 cows, ranging 203 to 2,966 cows, with an energy-corrected milk production of 40.1±4.4kg/cow per day. Prevalence of clinical lameness (5-point scale, locomotion score ≥3) and severe lameness (locomotion score ≥4) averaged 13.2±7.3 and 2.5±2.7%, respectively. The prevalence of all hock and knee injuries, including hair loss, swelling, and ulceration, was similar at 50.3±28.3 and 53.0±24.0%, respectively. Severe (swelling and ulceration) hock and knee injury prevalence were 12.2±15.3 and 6.2±5.5%, respectively. The prevalence of all neck injuries (including hair loss, swelling and ulceration) was 8.6±16.3%; whereas the prevalence of swollen or abraded necks was low, averaging 2.0±4.1%. Back injuries (proportion of cows with missing or abraded spinous processes, hooks, or pins) followed a similar trend with a low mean prevalence of 3.6±3.4%. Overall, physical well-being characteristics of this selection of high-producing, freestall-housed dairy herds provide evidence that lameness and injury are not inevitable consequences of the confinement housing of large numbers of dairy cattle. In particular, lameness prevalence rivals that of lower-production grazing systems. However, hock and other injury risk remains a concern that can be addressed through a choice in stall surface type. Use of deep, loose bedding yielded significant advantages over a mat or mattress type surface in terms of lameness, hock and knee injury, and proportion of cows with dirty udders (distinct demarcated to confluent plaques of manure). The performance benchmarks achieved by these herds may be used to set standards by which similarly managed herds may be judged using welfare audit tools.

Exploring relationships between Dairy Herd Improvement monitors of performance and the Transition Cow Index in Wisconsin dairy herds.

Transition cow management has been tracked via the Transition Cow Index (TCI; AgSource Cooperative Services, Verona, WI) since 2006. Transition Cow Index was developed to measure the difference between actual and predicted milk yield at first test day to evaluate the relative success of the transition period program. This project aimed to assess TCI in relation to all commonly used Dairy Herd Improvement (DHI) metrics available through AgSource Cooperative Services. Regression analysis was used to isolate variables that were relevant to TCI, and then principal components analysis and network analysis were used to determine the relative strength and relatedness among variables. Finally, cluster analysis was used to segregate herds based on similarity of relevant variables. The DHI data were obtained from 2,131 Wisconsin dairy herds with test-day mean ≥30 cows, which were tested ≥10 times throughout the 2014 calendar year. The original list of 940 DHI variables was reduced through expert-driven selection and regression analysis to 23 variables. The K-means cluster analysis produced 5 distinct clusters. Descriptive statistics were calculated for the 23 variables per cluster grouping. Using principal components analysis, cluster analysis, and network analysis, 4 parameters were isolated as most relevant to TCI; these were energy-corrected milk, 3 measures of intramammary infection (dry cow cure rate, linear somatic cell count score in primiparous cows, and new infection rate), peak ratio, and days in milk at peak milk production. These variables together with cow and newborn calf survival measures form a group of metrics that can be used to assist in the evaluation of overall transition period performance.

An assessment of dairy herd bulls in southern Australia: 2. Analysis of bull- and herd-level risk factors and their associations with pre- and postmating breeding soundness results.

In pasture-based, seasonally calving dairy herds of southern Australia, the mating period usually consists of an initial artificial insemination period followed by a period of natural service using herd bulls. The primary objective of this study was to identify associations between individual bull- and herd-level management factors and bull fertility as measured by a pre- and postmating bull breeding soundness evaluation (BBSE). Multivariable mixed effects logistic regression models were used to identify factors associated with bulls being classified as high risk of reduced fertility at the premating and postmating BBSE. Bulls older than 4 yr of age at the premating BBSE were more likely to be classified high risk compared with bulls less than 4 yr of age. Bulls that were in herds in which concentrates were fed before mating were more likely to be classified as high risk at the postmating BBSE compared with bulls that were in herds where concentrates were not fed. Univariable analyses also identified areas in need of further research, including breed differences between dairy bulls, leg conformation and joint abnormalities, preventative hoof blocking for bulls, and mating ratios.

An assessment of dairy herd bulls in southern Australia: 1. Management practices and bull breeding soundness evaluations.

In the pasture-based, seasonally calving dairy herds of southern Australia, the mating period usually consists of an initial artificial insemination period followed by a period of natural service using herd bulls. Bull breeding soundness evaluations (BBSE) were performed on 256 bulls from 32 dairy herds in southwest Victoria, using guidelines produced by the Australian Cattle Veterinarians, before and immediately after a single natural mating period. At the same time, herd managers were questioned regarding the management of the bulls. The objectives of this study were to describe the management practices of dairy herd bulls; to describe the causes of increased risk of reduced fertility in dairy herd bulls, as measured by a standard BBSE; and to describe the reasons for bull removal by herd managers during mating. At the premating BBSE, 19.5% of bulls were classified as high risk of reduced fertility, mostly due to physical abnormalities and reduced semen quality. At the postmating BBSE, 36.5% of bulls were classified as high risk of reduced fertility, mostly due to physical abnormalities, primarily lameness. Of the bulls used, 15.9% were removed from normal mating use by the herd manager, predominantly due to lameness and injuries. A premating BBSE is recommended in dairy herd bulls to identify bulls at risk of reduced fertility. Lameness is the most common problem in dairy herd bulls during the natural mating period, and risk factors associated with lameness in these bulls should be identified to better manage herd bulls.