Development of a decision support tool to compare diagnostic strategies for establishing the herd status for infectious diseases: An example with Salmonella Dublin infection in dairies.

The diagnosis of infectious diseases at herd level can be challenging as different stakeholders can have conflicting priorities. The current study proposes a "proof of concept" of an approach that considers a reasonable number of criteria to rank plausible diagnostic strategies using multi-criteria decision analysis (MCDA) methods. The example of Salmonella Dublin diagnostic in Québec dairy herds is presented according to two epidemiological contexts: (i) in herds with no history of S. Dublin infection and absence of clinical signs, (ii) in herds with a previous history of infection, but absence of clinical signs at the moment of testing. Multiple multiparty exchanges were conducted to determine: 1) stakeholders' groups; 2) the decision problem; 3) solutions to the problem (options) or diagnostic strategies to be ordered; 4) criteria and indicators; 5) criteria weights; 6) the construction of a performance matrix for each option; 7) the multi-criteria analyses using the visual preference ranking organization method for enrichment of evaluations approach; 8) the sensitivity analyses, and 9) the final decision. A total of nine people from four Québec's organizations (the dairy producers provincial association along with the DHI company, the ministry of agriculture, the association of veterinary practitioners, and experts in epidemiology) composed the MCDA team. The decision problem was "What is the optimal diagnostic strategy for establishing the status of a dairy herd for S. Dublin infection when there are no clinical signs of infection?". Fourteen diagnostic strategies composed of the three following parameters were considered: 1) biological samples (bulk tank milk or blood from 10 heifers aged over three months); 2) sampling frequencies (one to three samples collection visits); 3) case definitions to conclude to a positive status using imperfect milk- or blood-ELISA tests. The top-ranking diagnostic strategy was the same in the two contexts: testing the bulk tank milk and the blood samples, all samples collected during one visit and the herd being assigned a S. Dublin positive status if one sample is ELISA-positive. The final decision favored the top-ranking option for both contexts. This MCDA approach and its application to S. Dublin infection in dairy herds allowed a consensual, rational, and transparent ranking of feasible diagnostic strategies while taking into account the diagnostic tests accuracy, socio-economic, logistic, and perception considerations of the key actors in the dairy industry. This promising tool can be applied to other infectious diseases that lack a well-established diagnostic procedure to define a herd status.

Dataset on productive functional traits at first lactation and productive longevity from a herd of 185 Montbéliarde and Holstein cows managed on a low-input mountain-area grassland farm.

The dataset available here comes from an experimental dairy cattle farm located in a mountain region in Central France, where the feeding systems are mostly pasture grazing combined with a period of indoor overwintering during the colder months. The dataset comprises individual productive and functional traits covering over 36 different variables in 185 primiparous Montbéliarde and Holstein cows, followed by data on productive longevity and reason for culling. The data was collected over a 20-year period during which animal husbandry and data collection protocols remained consistent. Potential re-users of the data are private-sector professionals, farmer associations, and researchers interested in developing statistical and mechanistic models and simulations of individual dairy cows under low-input grassland-based systems.

Investigation of Prototheca bovis Infection and Its Correlation with Dairy Herd Improvement Data from a Dairy Farm in Central China.

Prototheca bovis (P. bovis), an alga that has attracted considerable attention over the years as a causative microorganism of mastitis in dairy cows, exhibits limited susceptibility to specific aminoglycosides and antifungal agents, and no effective clinical treatment is currently available, thereby posing challenges for both prevention and treatment. To investigate the infection of P. bovis mastitis and its impact on raw milk production, a total of 348 raw milk samples were collected from August to December 2022 from a dairy farm in central China. P. bovis and other bacteria were detected, and the average infection rate of P. bovis in raw milk was 60.34% (210/348). The total number of colonies and the somatic cell count (SCC) of P. bovis positive samples were significantly higher than those of P. bovis negative samples (p < 0.01). The daily milk yield, 305-day milk yield, peak milk yield, and days to peak milk yield of the P. bovis positive samples were significantly lower than those of P. bovis negative samples (p < 0.01). A correlation analysis showed that P. bovis infection was negatively correlated with daily milk yield, 305-day milk yield, peak milk yield, and days to peak milk yield (p < 0.0001), while being positively correlated with the total number of colonies, SCC, milk loss, and protein percentage (p < 0.0001). These findings may help practitioners in comprehending the occurrence of Prototheca mastitis and developing more effective strategies for the prevention of P. bovis infections.

Association between somatic cell count or morbidity of chronic subclinical mastitis and longevity in dairy herds in Eastern Hokkaido, Japan: a cross-sectional study.

An epidemiological analysis was conducted on production records in Hokkaido, Japan, to investigate the potential association between improved milk quality and longevity outcomes. The study found significant variations in herd somatic cell count levels and chronic subclinical mastitis morbidity based on geographical area and herd size. The analysis also revealed a positive correlation between herd somatic cell count and chronic subclinical mastitis morbidity. Although the hypothesis of a causal link between milk quality and longevity was examined, no such association was found. However, intensive assistance for identified high-risk areas and farms is expected to enhance overall milk quality.

Monitoring of Body Condition in Dairy Cows to Assess Disease Risk at the Individual and Herd Level.

A retrospective longitudinal study assessing the explanatory and predictive capacity of body condition score (BCS) in dairy cows on disease risk at the individual and herd level was carried out. Data from two commercial grazing herds from the Argentinean Pampa were gathered (Herd A = 2100 and herd B = 2600 milking cows per year) for 4 years. Logistic models were used to assess the association of BCS indicators with the odds for anestrus at the cow and herd level. Population attributable fraction (AFP) was estimated to assess the anestrus rate due to BCS indicators. We found that anestrus risk decreased in cows calving with BCS ≥ 3 and losing ≤ 0.5 (OR: 0.07-0.41), and that anestrus rate decreased in cohorts with a high frequency of cows with proper BCS (OR: 0.22-0.45). Despite aggregated data having a good explanatory power, their predictive capacity for anestrus rate at the herd level is poor (AUC: 0.574-0.679). The AFP varied along the study in both herds and tended to decrease every time the anestrous rate peaked. We conclude that threshold-based models with BCS indicators as predictors are useful to understand disease risk (e.g., anestrus), but conversely, they are useless to predict such multicausal disease events at the herd level.

High-Impact Risk Factors for Mycobacterium avium ssp. paratuberculosis in Dairy Herds in Germany.

In a cross-sectional study, it was identified that three regions in Germany differed with respect to their herd-level prevalence for paratuberculosis in dairy cattle. In the study presented here, the same farms were analyzed to identify those components of biosecurity and farm management with the highest impact on Mycobacterium avium ssp. paratuberculosis (MAP) introduction and establishment in a farm. Hence, the data analyzes included 183, 170 and 104 herds from the study regions north, east and south, respectively. A herd was considered MAP-positive if at least one fecal environmental sample was positive. Twenty-six different possible risk factors from five different components of biosecurity and farm management were analyzed. We show that the average management of calf feeding increased the odds for a MAP-positive farm by 5.22 times (95% confidence interval (CI) = 1.25-21.83). With every 100-cow increase in farm size, the risk for a farm to test MAP-positive increased by 1.94 times (CI = 1.15-3.27), 1.14 times (CI = 1.02-1.27) and 5.53 times (CI = 0.44-68.97) in the north, east and south study regions, respectively. Furthermore, the purchase of cattle with an unknown MAP status increased the risk for a farm testing MAP-positive by 2.86-fold (CI = 1.45-5.67). Our results demonstrate that herd size, unknown MAP status of the purchased cattle and different aspects of calf feeding play an important role in the MAP status of a farm and should be in focus in regions with different MAP between-herd prevalence. Additionally, farm individual risk patterns should be identified during (veterinary) biosecurity consultancy.

Prevalence and risk factors associated with high somatic cell count in Chinese dairy herds.

This study aimed to (1) estimate the prevalence of cow-level high somatic cell count (SCC) in Chinese dairy herds and (2) identify potential factors associated with cow- and herd-level SCC variables. The monthly data on dairy herd improvement were collected from a total of 131 dairy herds in 11 provinces in China in 2019. Mixed models were constructed using the cow composite milk SCC and the variance of cow SCC as dependent variables separately and parity, seasons, days in milk (DIM), herd size, and farm types (family-owned vs. company-owned) as fixed effects, accounting for the nested random herd and cow effect. We used negative binomial regression using herd-level SCC-related variables, namely, monthly proportion of high SCC, monthly proportion of new high SCC, monthly proportion of chronic high SCC, and monthly proportion of new chronic high SCC as dependent variables separately against seasons, herd size, and farm types with the random herd effect. The overall average prevalence of high SCCs for each month per farm was 0.26 (2.5-97.5% quantile: 0-0.56). Company-owned farms performed better in herd SCC management. Seasons were significantly associated with all the aforementioned variables, and summer and autumn were the seasons associated with worse outcomes in herd SCCs. This study is the first to assess high SCC in a large number of Chinese dairy herds, which is useful for farms to tailor the on-farm mastitis control programs in China.

Using the Herd Status Index to remotely assess the welfare status of dairy herds based on prerecorded data.

The use of prerecorded data to remotely assess the herd welfare status is a promising approach to reduce the need for costly and time-consuming on-farm welfare assessments. Therefore, the objective of this study was to validate the Herd Status Index, an index developed based on Dairy Herd Improvement data from Canada, to remotely evaluate the welfare status of dairy herds. Herd-level prevalence of five animal-based welfare outcomes, measured once on 2 986 Quebec - Canada dairy herds between 2016 and 2019, were used to generate clusters with different welfare status using the algorithm partitioning around medoids. Dairy Herd Improvement data from 12 months prior to the welfare assessment were extracted and used to calculate the Herd Status Index. A linear model was used to carry out comparisons between clusters. Three stable clusters were found to best describe the data. Cluster two had the best overall welfare status since it had the lowest prevalence of all welfare issues while cluster three had the highest prevalence of most welfare issues, with the exception for the prevalence of neck lesions that was not different than cluster one. Cluster one had an overall intermediate welfare status. The Herd Status Index was higher (i.e., indicating a good welfare status) on cluster two compared to cluster three, but neither cluster three nor two differed to cluster one. In its current format, the Herd Status Index has a weak potential to identify herds with varying prevalence of welfare issues and it requires further improvements before it could be used to accurately assess the welfare status of the herds.

Determining the prevalence of antibodies to Salmonella Dublin in dairy herds in Great Britain by quarterly bulk tank testing.

Salmonella enterica subspecies enterica serovar Dublin has been the most common Salmonella serovar isolated from cattle in Great Britain for the previous 22 years. It can cause a wide variety of clinical presentations and result in significant welfare and productivity concerns in infected herds. Bulk tank antibody testing undertaken every three or four months forms the basis of eradication and monitoring programmes in Denmark and the Netherlands and has been shown to be a sensitive, specific and cost-effective way of establishing seroprevalence and monitoring infection at a herd level. A prevalence estimate based on quarterly bulk tank testing has not been previously carried out in Great Britain. This study recruited 410 herds across Great Britain, who submitted milk samples on a quarterly basis for screening by an ELISA for Salmonella Dublin antibody. Classifying herds according to the Danish eradication scheme classification gave an apparent prevalence of 38% (95% confidence intervals 34-43%) and an estimated true prevalence of 40% (95% confidence intervals 35-45%), taking into account the test sensitivity and specificity. Of the 401 herds which completed the quarterly bulk tank testing, 45% had one or more positive bulk tank results.

Modelling the Transmission of Coxiella burnetii within a UK Dairy Herd: Investigating the Interconnected Relationship between the Parturition Cycle and Environment Contamination.

Q fever infection in dairy herds is introduced through the transmission of the bacterium Coxiella burnetii, resulting in multiple detrimental effects such as reduction of lactation, abortions and chronic infection. Particularly in the UK, recent evidence suggests that the infection is endemic in dairy cattle. In this work, we investigate the dynamics of the disease with the aim to disentangle the relationship between the heterogeneity in the shedding routes and their effect on the environmental contamination. We develop a mathematical model for the transmission of Q fever within UK cattle herds by coupling the within-herd infection cycle of the disease with farm demographics and environmental effects, introduced by either the indoor or outdoor environment. Special focus is given on the mechanism of transmission in nulliparous heifers and multiparous cattle. We calibrate the model based on available knowledge on various epidemiological aspects of the disease and on data regarding farm demographics available in the UK DEFRA. The resulting model is able to reproduce the reported prevalence levels by field and in silico studies, as well as their evolution in time. In addition, it is built in an manner that allows the investigation of different housing techniques, farm management styles and a variety of interventions. Sensitivity analysis further reveals the parameters having the major effect in maintaining high prevalence levels of seropositive and shedding cattle. The present analysis aims also to indicate the gaps in the available data required to optimise the proposed model or future models that will developed on the basis of the one proposed herein. Finally, the developed model can serve as mathematical proof for the assessment of various interventions for controlling the dynamics of Q fever infection.

Thermal Environment and Behavior Analysis of Confined Cows in a Compost Barn.

The compost barn system has become popular in recent years for providing greater animal well-being and quality of life, favoring productivity and longevity. With the increase in the use of compost barn in dairy farms, studies related to the thermal environment and behavior are of paramount importance to assess the well-being of animals and improve management, if necessary. This work aimed to characterize the thermal environment inside a compost barn during the four seasons of a year and to evaluate the standing and lying behavior of the cows through images. The experiment was carried out during March (summer), June (autumn), August (winter), and November (spring). Dry bulb temperature (tdb, °C), dew point temperature (tdp, °C), and relative humidity (RH,%) data were collected every 10 minutes during all analyzed days, and the temperature and humidity index (THI) was subsequently calculated. In order to analyze the behavior of the cows, filming of the barn interior was carried out during the evaluated days. Subsequently, these films were analyzed visually, and in an automated way to evaluate the behavior of these animals. For the automated analysis, an algorithm was developed using artificial intelligence tools, YOLOv3, so that the evaluation process could be automated and fast. It was observed that during the experimental period, the highest mean values of THI were observed during the afternoon and the autumn. The animals' preference to lie down on the bed for most of the day was verified. It was observed that the algorithm was able to detect cow behavior (lying down or standing). It can be concluded that the behavior of the cows was defined, and the artificial intelligence was successfully applied and can be recommended for such use.

Simulation of the lifetime productivity of a dairy herd in Japan according to the number of days to first service of cows.

To determine the optimal voluntary waiting period to first service after calving for maximizing the lifetime productivity of cows in a dairy herd, we simulated the changes in lifetime productivity due to increasing the number of days from calving to first service. We also assessed the effects of changes in the maximum number of services within a lactation, maximum number of calvings, and calf sale prices on lifetime productivity. We evaluated lifetime productivity as lifetime average productivity, that is, the sum of daily revenues from milk and calf sales from first calving to culling. The lifetime productivity at ≤65 days to first service was low because of the low conception rate during early lactation. In addition, lifetime productivity at ≥185 days to first service decreased as the number of days to first service increased. The number of days to first service for maximum lifetime productivity decreased as the maximum number of calvings increased. Furthermore, the decrease in lifetime productivity associated with decreasing the maximum number of services within a lactation from five to four was greater than that when the maximum number of calvings was decreased from six to five.

Impact of Veterinary Herd Health Management on German Dairy Farms: Effect of Participation on Farm Performance.

German dairy farming has intensified markedly in recent years, and the demand for Veterinary Herd Health Management (VHHM) is rising. To protect farms from epidemics, ensure food safety, and prevent developing of antibiotic resistance, VHHM has been anchored in EU law since April 2021. Via an online survey, distributed by different farmers' organizations, dairy farmers were asked about the cooperation with their veterinarian. The aim was to evaluate farm performance as a function of participation in VHHM. From 216 analyzed questionnaires, 106 respondents participated in VHHM. Results showed that farmers who make use of VHHM and consult their veterinarian in decision-making frequently have the highest 305-day milk yield (305dMY), the lowest bulk tank somatic cell counts, and the lowest age at first calving (AFC). However, these farmers tended to have higher replacement rates and a higher mortality of cows in the period up to 60 days in milk (MORT60DIM). Furthermore, respondents who defined VHHM as "evaluation of herd data, strategic planning" had the highest 305dMY compared with those who defined VHHM through one of the different options given ("pregnancy checks and support in reproduction"/"problem solving"). In the multifactorial regression model, VHHM participating farms had a 660-kg higher 305dMY and 1 month less in AFC, compared with farms not participating in VHHM. However, within the VHHM participants, no association between VHHM practices and performance parameters was found. Further research is needed, to find out if tailored advice of the VHHM approach may show effect herein.

Transmission patterns of a Mycobacterium avium subsp. paratuberculosis clone within a single heard investigated by Whole Genome Sequencing.

Mycobacterium avium subsp. paratuberculosis (MAP) is characterized by a low genomic rate of mutation. Current subtyping tools, such as Mini-Micro-satellite analyses, do to have not sufficient discriminatory power to disclose MAP's evolution on small spatial and temporal scales. The aim of the study was to investigate the population structure of MAP inside a single dairy herd using whole genome sequencing (WGS) approaches. For this purpose, the genomes of 43 field isolates, recovered from the faeces of 36 cows of the same dairy herd from 2012 to 2016, were sequenced by WGS. The isolates' genomes showed a low number (43) of polymorphic sites (SNPs), confirming the clonal origin of the herd infection. However, despite the limited genomic diversity found in WGS, the phylogenetic analysis was discriminatory enough to detect the presence of different genomic clades and sub-clades inside the herd population. In addition, the phylodynamic reconstruction showed the existence of an ancestor clade from which the other clades and sub-clades originated. Moreover, by reconstructing the putative within-herd transmission networks using WGS data, we demonstrated that: (i) in a herd where MAP is endemic, multiple isolates recovered from a single animal and differing from each other by few (three/four) SNPs can originate from different transmission or passive shedding events and not from intra-host evolution; and (ii) variability of minisatellites coupled with a few microsatellites does not represent reliable tracers of within-herd infection chains. Our findings show that WGS, coupled with relevant epidemiological information, represents a valuable tool to work out fine epidemiological and micro-evolutionary relationships such as those at herd-level scale.

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.

Milk yield depression and its economic loss due to production diseases: Iran's large dairy herds.

BACKGROUND: Incidences of production and metabolic diseases in dairy cows have increased over the last few decades because of the increasing trends in milk production. Production diseases cause different and distinct depressions in milk production that lead to different and major economic losses in large dairy herds. AIMS: The objective of this study was to determine milk production depression and its economic losses due to different production diseases in selected large dairy herds of Iran. METHODS: Production and health data from 17 large dairy herds with a total of 146464 observations across three parities were obtained. Milk yield depressions were estimated for three phases of lactation including 1) 5-60, 2) 61-120, and 3) 121-180 days in milk. Data were analyzed using Mixed Models of SAS program (v. 9.3) with fixed effects of the diseases, calving year, calving month, parity, and herd with cow age at calving as covariates. RESULTS: The data demonstrated significant effects of different production diseases on milk production depression during 5-60, 61-120, and 121-180 days in milk (P<0.05). During 5-60 days in milk, ketosis, displaced abomasums (DAs), laminitis, mastitis, metritis, retained placenta (RP), and dystocia resulted in, respectively, 253, 682, 39, 38, 110, 215, and 55 kg of milk yield depressions that were equivalent to 38.5, 103.7, 6.0, 5.8, 16.7, 32.6, and 8.4 U.S. Dollars (USD) economic losses. Milk yield depressions due to laminitis and mastitis over the 180 days in milk were, respectively, 207 and 404 kg equivalent to 31.5 and 63.0 USD economic losses. Since the milk yield depression constitutes about 20-35% of total costs of production and metabolic disorders, the total economic losses would be 3-5 times the above values. CONCLUSION: Displaced abomasum and laminitis caused the highest and lowest depressions in milk yield, respectively. The findings suggest that commercial dairy production management strategies in Iran require reassessment and refinement. Overfeeding of concentrates should be ceased. Future economic and reproductive studies are needed to enable developing effective strategies for optimizing modern and postmodern dairy production in Iran.

Severe outbreak of bovine neonatal diarrhea in a dairy calf rearing unit with multifactorial etiology.

This study describes the etiological diversity observed in a severe neonatal diarrhea outbreak with morbidity and mortality rates of 80 and 20%, respectively, with detection of mixed infections with viral, bacterial, and protozoan disease agents in a dairy calf rearing unit. Diarrheic fecal samples were collected from eight 5 to 18 days of age calves and were submitted to the investigation of the presence of rotavirus A (RVA), bovine coronavirus (BCoV), bovine kobuvirus (BKV), bovine viral diarrhea virus 1 and 2 (BVDV-1 and BVDV-2), enteropathogenic Escherichia coli (ETEC), Salmonella sp., and Cryptosporidium spp. Fragments of the small intestine of one calf with diarrhea that spontaneously died were submitted for histopathological analyses. The most frequent infectious agent detected in diarrheic fecal samples was BKV (8/8-100%), followed by RVA (5/8-62.5%), BVDV (5/8-62.5%), Cryptosporidium parvum (5/8-62.5%), ETEC (4/8-50%), and Cryptosporidium ryanae (1/8-12.5%). These etiological agents were found in mixed infections with two or more pathogens per diarrheic fecal sample. The association of viral and protozoan pathogens was the most frequently identified (37.5%) in these samples, followed by viral and bacterial (25%); viral, bacterial, and protozoan (25%); and only viral agents (12.5%). BCoV and Salmonella sp. were not identified in the diarrheic fecal samples analyzed. Additionally, histopathology of the small intestine diagnosed chronic lymphocytic enteritis. In conclusion, in calf rearing units, the adoption and strict monitoring of health management practices are critical to the success of this calf creation system.

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.

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.

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.