A lameness scoring system that uses posture and gait to predict dairy cattle reproductive performance

Lameness has contributed to reproductive inefficiency and increased the risk of culling in dairy cows. We developed a 5-point lameness scoring system that assessed gait and placed a novel emphasis on back posture. Our objective was to determine if this system predicted future reproductive performance and the risk of culling. The study was conducted at a commercial dairy farm with a history of declining reproductive efficiency and an increasing prevalence of lameness. A total of 66 primipara and pluripara calved, received an initial lameness score, and completed their 60-d voluntary waiting period. The overall prevalence of lameness (mean lameness score >2) was 65.2%. Scoring continued at 4-wk intervals and ceased with conception or culling. The percentage of cows confirmed pregnant and culled was 77.3 and 22.7, respectively. For each reproductive endpoint, a 2 x 2 table was constructed with lameness score >2 as the positive risk factor and either performance greater than the endpoint mean or being culled as the positive disease or condition. Positive and negative predictive values, relative risk, Chisquare statistic and regression analysis were used to evaluate the data. The positive predictive values for days to first service, days open, breeding herd days, services per pregnancy and being culled were 58, 68, 65, 39 and 35%, respectively. Similarly, the negative predictive values were 79, 96, 100, 96 and 100%, respectively. Except for one reproductive endpoint, the total number of services, all linear regressions were significant at P < 0.01. Having a lameness score >2 predicted that a cow would have extended intervals from calving to first service and to conception, spend or be assigned to (explained herein) more total days in the breeding herd, require more services per pregnancy and be 8.4 times more likely to be culled. We believe that this lameness scoring system effectively identifies lame cows. Observation of the arched-back posture in a standing cow (> or =LS 3) should trigger corrective interventions.     

Lameness Prevalence and Risk Factors in Large Dairy Farms in Upstate New York. Model Development for the Prediction of Claw Horn Disruption Lesions

The main objectives of this prospective cohort study were a) to describe lameness prevalence at drying off in large high producing New York State herds based on visual locomotion score (VLS) and identify potential cow and herd level risk factors, and b) to develop a model that will predict the probability of a cow developing claw horn disruption lesions (CHDL) in the subsequent lactation using cow level variables collected at drying off and/or available from farm management software. Data were collected from 23 large commercial dairy farms located in upstate New York. A total of 7,687 dry cows, that were less than 265 days in gestation, were enrolled in the study. Farms were visited between May 2012 and March 2013, and cows were assessed for body condition score (BCS) and VLS. Data on the CHDL events recorded by the farm employees were extracted from the Dairy-Comp 305 database, as well as information regarding the studied cows’ health events, milk production, and reproductive records throughout the previous and subsequent lactation period. Univariable analyses and mixed multivariable logistic regression models were used to analyse the data at the cow level. The overall average prevalence of lameness (VLS > 2) at drying off was 14%. Lactation group, previous CHDL, mature equivalent 305-d milk yield (ME305), season, BCS at drying off and sire PTA for strength were all significantly associated with lameness at the drying off (cow-level). Lameness at drying off was associated with CHDL incidence in the subsequent lactation, as well as lactation group, previous CHDL and ME305. These risk factors for CHDL in the subsequent lactation were included in our predictive model and adjusted predicted probabilities for CHDL were calculated for all studied cows. ROC analysis identified an optimum cut-off point for these probabilities and using this cut-off point we could predict CHDL incidence in the subsequent lactation with an overall specificity of 75% and sensitivity of 59%. Using this approach, we would have detected 33% of the studied population as being at risk, eventually identifying 59% of future CHDL cases. Our predictive model could help dairy producers focusing their efforts on CHDL reduction by implementing aggressive preventive measures for high risk cows.     

Coupling a reproductive function model to a productive function model to simulate lifetime performance in dairy cows

Reproductive success is a key component of lifetime performance in dairy cows but is difficult to predict due to interactions with productive function. Accordingly, this study introduces a dynamic model to simulate the productive and reproductive performance of a cow during her lifetime. The cow model consists of an existing productive function model (GARUNS) which is coupled to a new reproductive function model (RFM). The GARUNS model simulates the individual productive performance of a dairy cow throughout her lifespan. It provides, with a daily time step, changes in BW and composition, fetal growth, milk yield and composition and food intake. Genetic-scaling parameters are incorporated to scale individual performance and simulate differences within and between breeds. GARUNS responds to the discrete event signals ‘conception’ and ‘death’ (of embryo or fetus) generated by RFM. In turn, RFM responds to the GARUNS outputs concerning the cow’s energetic status: the daily total processed metabolizable energy per kg BW (TPEW) and the net energy balance (EB). Reproductive function model models the reproductive system as a compartmental system transitioning between nine competence stages: prepubertal (PRPB), anestrous (ANST), anovulatory (ANOV), pre-ovulating (PREO), ovulating (OVUL), post-ovulating (PSTO), luteinizing (LUTZ), luteal (LUTL) and gestating (GEST). The transition from PRPB to ANST represents the start of reproductive activity at puberty. The cyclic path through ANST, PREO, OVUL, PSTO, LUTZ and LUTL forms the regime of ovulatory cycles, whereas ANOV and GEST are transient stages that interrupt this regime. Anovulatory refers explicitly to a stage in which ovulation cannot occur (i.e. interrupted cyclicity), whereas ANST is a pivotal stage within ovulatory cycles. Reproductive function model generates estradiol and progesterone hormonal profiles consistent with reference profiles derived from literature. Cyclicity is impacted by the GARUNS output EB and clearance of estradiol is impacted by TPEW. A farming system model was designed to describe different farm protocols of heat detection, insemination, feeding (amount and energy density), drying-off and culling. Results of model simulation (10 000 simulations of individual cows over 5000 days lifetime period, with randomly drawn genetic-scaling parameters and standard diet) are consistent with literature for reproductive performance. This model allows simulation of deviations in reproductive trajectories along physiological stages of the cow reproductive cycle. It thus provides the basis for evaluation of the relative importance of different factors affecting fertility at individual cow and herd levels across different breeds and management environments.     

Animal board invited review: Dairy cow lameness expenditures,losses and total cost

Lameness is one of the most costly dairy cow diseases, yet adoption of lameness prevention strategies remains low. Low lameness prevention adoption might be attributable to a lack of understanding regarding total lameness costs. In this review, we evaluated the contribution of different expenditures and losses to total lameness costs. Evaluated expenditures included labor for treatment, therapeutic supplies, lameness detection and lameness control and prevention. Evaluated losses included non-saleable milk, reduced milk production, reduced reproductive performance, increased animal death, increased animal culling, disease interrelationships, lameness recurrence and reduced animal welfare. The previous literature on total lameness cost estimates was also summarized. The reviewed studies indicated that previous estimates of total lameness costs are variable and inconsistent in the expenditures and losses they include. Many of the identified expenditure and loss categories require further research to accurately include in total lameness cost estimates. Future research should focus on identifying costs associated with specific lameness conditions, differing lameness severity levels, and differing stages of lactation at onset of lameness to provide better total lameness cost estimates that can be useful for decision making at both the herd and individual cow level.     

Use of Stochastic Simulation to Evaluate the Reduction in Methane Emissions and Improvement in Reproductive Efficiency from Routine Hormonal Interventions in Dairy Herds

This study predicts the magnitude and between herd variation in changes of methane emissions and production efficiency associated with interventions to improve reproductive efficiency in dairy cows. Data for 10,000 herds of 200 cows were simulated. Probability of conception was predicted daily from the start of the study (parturition) for each cow up to day 300 of lactation. Four scenarios of differing first insemination management were simulated for each herd using the same theoretical cows: A baseline scenario based on breeding from observed oestrus only, synchronisation of oestrus for pre-set first insemination using 2 methods, and a regime using prostaglandin treatments followed by first insemination to observed oestrus. Cows that did not conceive to first insemination were re-inseminated following detection of oestrus. For cows that conceived, gestation length was 280 days with cessation of milking 60 days before calving. Those cows not pregnant after 300 days of lactation were culled and replaced by a heifer. Daily milk yield was calculated for 730 days from the start of the study for each cow. Change in mean reproductive and economic outputs were summarised for each herd following the 3 interventions. For each scenario, methane emissions were determined by daily forage dry matter intake, forage quality, and cow replacement risk. Linear regression was used to summarise relationships. In some circumstances improvement in reproductive efficiency using the programmes investigated was associated with reduced cost and methane emissions compared to reliance on detection of oestrus. Efficiency of oestrus detection and the time to commencement of breeding after calving influenced variability in changes in cost and methane emissions. For an average UK herd this was a saving of at least £50 per cow and a 3.6% reduction in methane emissions per L of milk when timing of first insemination was pre-set.     

Technical and economic effects of an inline progesterone indicator in a dairy herd estimated by stochastic simulation

For several years progesterone in milk or blood has been recognized as an indicator of different cow states related to reproduction. For this study, an existing simulation model was modified in order to analyze the technical and economic effects of including information on progesterone status in an automatic inline monitoring system. Implementation of an inline progesterone indicator was assumed to directly affect the estrus detection rate, the period until treatment for post-partum anestrus and the number of mistimed AIs. Different implementations of an inline progesterone indicator were simulated in a typical Danish dairy herd with 120 cows and in other herd situations represented by: a herd with poor reproduction efficiency, a herd with a high estrus detection rate and a herd using a 9 week postponed AI period for primiparous cows. It was concluded that implementation of an inline progesterone indicator in a dairy herd previously using visual estrus detection has a break-even price of 3-81 euros per cow-year depending on differences in implementation type and herd reproduction management. The highest break-even price was found using the assumptions that simulated a herd with initially poor reproductive efficiency. With the assumptions that simulated a typical Danish herd the break-even price was 46 euros per cow-year. Attributable effects of using the indicator, including effects of labor time, are discussed.     

Unexpected Decrease in Milk Production after Fenbendazole Treatment of Dairy Cows during Early Grazing Season

Gastrointestinal nematodes (GIN) infection can impair milk production (MP) in dairy cows. To investigate whether MP would be optimized by spring targeted-selective anthelmintic treatment in grazing cows, we assessed (1) the effect on MP of an anthelmintic treatment applied 1.5 to 2 months after turn-out, and (2) herd and individual indicators associated with the post-treatment MP response. A randomized controlled clinical trial was conducted in 13 dairy farms (578 cows) in western France in spring 2012. In each herd, lactating cows of the treatment group received fenbendazole orally, control cows remained untreated. Daily cow MP was recorded from 2 weeks before until 15 weeks after treatment. Individual serum pepsinogen and anti-Ostertagia antibody levels (expressed as ODR), faecal egg count and bulk tank milk (BTM) Ostertagia ODR were measured at treatment time. Anthelmintic treatment applied during the previous housing period was recorded for each cow. In each herd, information regarding heifers’ grazing and anthelmintic treatment history was collected to assess the Time of Effective Contact (TEC, in months) with GIN infective larvae before the first calving. The effect of treatment on weekly MP averages and its relationships with herd and individual indicators were studied using linear mixed models with two nested random effects (cow within herd). Unexpectedly, spring treatment had a significant detrimental effect on MP (-0.92 kg/cow/day on average). This negative MP response was particularly marked in high producing cows, in cows not treated during the previous housing period or with high pepsinogen levels, and in cows from herds with a high TEC or a high BTM ODR. This post-treatment decrease in MP may be associated with immuno-inflammatory mechanisms. Until further studies can assess whether this unexpected result can be generalized, non-persistent treatment of immunized adult dairy cows against GIN should not be recommended in early grazing season.     

Daily grazing time as a risk factor for alterations at the hock joint integument in dairy cows

Structural changes lead to increasing sizes of dairy herds and a reduction in grazing use. Thus, cows spend more time in the barn and become more exposed to the barn environment. The cubicle surface can result in damages of the cows’ hock joint integument. Pasture is generally seen as a beneficial environment for cows. We hypothesized that a higher number of daily grazing hours reduce the probability of hock joint alterations in dairy cows from large herds. In total, 3148 lactating cows from 36 grazing and 20 zero-grazing dairy herds, with an average herd size of 173 cows, were assessed individually on one randomly selected body side for alterations in hock integument (score 0 for no alterations or hairless areas <2 cm, 1 for at least one hairless area of ⩾2 cm, 2 for lesion or swelling). The cows were further assessed for lameness and cleanliness. Information on breed, parity and days in milk per cow was extracted from a national database. Cubicle surface was evaluated for each herd. Daily grazing hours 30 days before herd visits were recorded by the stockmen and later categorized as follows: zero hours (zero-grazing), few hours (3 to 9) and many hours (>9 to 21). The effects of daily grazing hours and other potential cow and herd-level risk factors were evaluated for their impact on hock integument alterations using a logistic analysis with a multi-level model structure. The probability for hock integument alterations such as hair loss, lesions or swellings decreased with increasing amount of grazing hours (odds of 3 to 9 h 2.2 times and odds of >9 to 21 h 4.8 times lower than of zero-grazing). The probability for only lesions or swellings decreased with >9 to 21 grazing hours (odds 2.1 times) but not with 3 to 9 h (odds 1.0 times) compared with zero-grazing. Lameness, hard cubicle surface and Danish Holstein v. other breeds showed an increasing effect on the probability for integument alterations. Increase in days in milk only showed an increasing effect on the probability for lesions and swellings. We concluded that a long daily stay on pasture is most beneficial for the hock joint integument of a dairy cow.     

Factors of a noninfectious nature affecting fertility after artificial insemination in lactating dairy cows. A review

After 80 years of the commercial application of artificial insemination (AI) in the cow, the method still has numerous benefits over natural insemination including worldwide gene improvement. The efficiency of insemination depends, among many other factors, on the delivery of an appropriate number of normal spermatozoa to the appropriate reproductive tract site at the appropriate time of estrus. The metabolic clearance of steroid hormones and pregnancy associated glycoproteins and the negative effects of different types of stress related to high milk production makes the high-producing dairy cow a good animal model for addressing factors affecting fertility. Nevertheless, extensive studies have shown a positive link between high milk production in an individual cow and high fertility. When a cow becomes pregnant, the effect of pregnancy loss on its reproductive cycle is also a topic of interest. This paper reviews the factors of a noninfectious nature that affect the fertility of lactating dairy cows following AI. Special attention is paid to factors related to the cow and its environment and to estrus confirmation at insemination. Pregnancy maintenance during the late embryonic/early fetal period is discussed as a critical step. Finally, the use of Doppler ultrasonography is described as an available research tool for improving our current understanding of the health of the genital structures and conceptus.     

Evaluation of two dairy herd reproductive performance indicators that are adjusted for voluntary waiting period

Background

Overall reproductive performance of dairy herds is monitored by various indicators. Most of them do not consider all eligible animals and do not consider different management strategies at farm level. This problem can be alleviated by measuring the proportion of pregnant cows by specific intervals after their calving date or after a fixed time period, such as the voluntary waiting period. The aim of this study was to evaluate two reproductive performance indicators that consider the voluntary waiting period at the herd. The two indicators were: percentage of pregnant cows in the herd after the voluntary waiting period plus 30 days (PV30) and percentage of inseminated cows in the herd after the voluntary waiting period plus 30 days (IV30). We wanted to assess how PV30 and IV30 perform in a simulation of herds with different reproductive management and physiology and to compare them to indicators of reproductive performance that do not consider the herd voluntary waiting period.

Methods

To evaluate the reproductive indicators we used the SimHerd-program, a stochastic simulation model, and 18 scenarios were simulated. The scenarios were designed by altering the reproductive management efficiency and the status of reproductive physiology of the herd. Logistic regression models, together with receiver operating characteristics (ROC), were used to examine how well the reproductive performance indicators could discriminate between herds of different levels of reproductive management efficiency or reproductive physiology.

Results

The logistic regression models with the ROC analysis showed that IV30 was the indicator that best discriminated between different levels of management efficiency followed by PV30, calving interval, 200-days not-in calf-rate (NotIC200), in calf rate at100-days (IC100) and a fertility index. For reproductive physiology the ROC analysis showed that the fertility index was the indicator that best discriminated between different levels, followed by PV30, NotIC200, IC100 and the calving interval. IV30 could not discriminate between the two levels.

Conclusion

PV30 is the single best performance indicator for estimating the level of both herd management efficiency and reproductive physiology followed by NotIC200 and IC100. This indicates that PV30 could be a potential candidate for inclusion in dairy herd improvement schemes.     

Assessing the welfare impact of foot disorders in dairy cattle by a modeling approach

Foot disorders are the main cause of dairy cow lameness and are considered to have a major impact on the welfare of dairy cattle. This study adopts a modeling approach, using a dynamic stochastic model, to provide more insight into the welfare impact of different types of foot disorders, both clinical and subclinical. The impact of specific foot disorders on welfare was assessed by simulating the incidence and duration of foot disorders and the pain associated with them. Pain assessment was based on locomotion scores, with underlying knowledge obtained from scientific literature and experts. The results demonstrated the seriousness of the welfare impact of foot disorders. The negative welfare impact was measured on a scale from 0 to 60, where the maximum outcome represents a cow having very severe pain during the whole year. On average, each cow achieves a welfare impact score of 12, which is 20% of the maximum welfare impact score. This welfare score equals having severe pain for a period of 3 months, indicating a serious impact on welfare. On average, digital dermatitis impacts most on welfare, which is caused by a high incidence of the painful clinical stage, followed by sole hemorrhages (SoH) and interdigital dermatitis and heel horn erosion (IDHE). The combination of a high incidence and long duration of SoH and IDHE causes this relatively high welfare impact of foot disorders that occur mostly subclinically. On average, over 1 year, 46% of the welfare impact due to foot disorders is caused by clinical foot disorders. The fact that subclinical foot disorders contribute more or less equally to the effects on welfare as clinical ones, indicates that farmers may readily underestimate the welfare impact by a factor two. Modeling welfare impact at cow level, individual cases of foot disorders, stresses the importance of pain intensity, indicating the importance of clinical foot disorders. This study demonstrated the serious welfare impact of foot disorders in dairy cattle and pointed out the considerable impact of subclinical foot disorders. Furthermore, the approach of welfare assessment, for example herd v. cow level, influenced the ranking of foot disorders for their impact on animal welfare. Potentially, this leads to different prioritization of specific solution strategies for dairy farmers, for example, focusing on cow comfort, hygiene or preventive medical treatments, foot trimming and/or health monitoring. The findings in this study support in raising awareness about this welfare issue.     

To meet or not to meet welfare outcome thresholds: a case-control study in dairy cow herds

Recently published thresholds allow classifying dairy cattle herds according to target, caution and alert ranges for welfare outcomes. Such normative thresholds provide one way to transparently assess production practices and are a straightforward communication tool with farmers. In an ordinal response case-control study, we investigated associations of animal, management and resource-related indicators with the risk of exceeding thresholds of prevalence for lameness, claw disorders, integument alterations and leg cleanliness. To this end, we used cumulative logistic regression models on 264 tethered and 392 loose-housed Austrian dairy herds. In tethered herds, the risk indicator average lactation milk yield was positively associated with the probability to exceed thresholds for integument alteration prevalence but negatively regarding leg cleanliness. Associations were also found for operation type regarding integument alterations (lower risk on organic vs conventional farms), for herd size regarding lameness (negative association) and dirty upper hind leg (positive association), and for percentage of fifth or higher parity cows in the herd regarding dirty lower hind leg (positive association). Stall type was identified as risk indicator regarding claw disorders (lower risk of long vs short stands). In loose housing systems, none of the analysed risk indicators was associated with the probability to exceed thresholds for total lameness and claw disorder prevalence. Negative associations with the probability to exceed caution or alert thresholds were identified for lifetime milk yield (dirty upper hind leg), lactation milk yield (dirty upper and lower hind leg), percentage of cows in the herd with a fat-protein-ratio <1 (integument alterations), and percentage of cows in the herd with a fat-protein-ratio >1.5 (dirty upper hind leg). Pasture access showed negative (severe lameness, integument alterations) and herd size positive associations (severe lameness) with the probability to exceed thresholds. Deep litter cubicles compared to raised cubicles with rubber mats showed a lower probability to exceed thresholds (integument alterations, dirty lower hind leg) as well as solid rubber compared to concrete slatted flooring in alleyways (integument alterations). Assessments carried out during the pasture period compared to during winter housing were associated with a lower risk of exceeding thresholds for leg cleanliness measures in both, tethered and loose-housed herds, and for integument alteration prevalence in tethered herds. In conclusion, no principal risk indicator was identified which consistently determined the probability of exceeding predefined thresholds of considered welfare outcomes. Nevertheless, outcome-specific factors show sufficient impact on the categorisation of farms according to prevalence ranges.     

Identifying risk factors for poor hind limb cleanliness in Danish loose-housed dairy cows

The objective of this study was to identify possible risk factors for poor cow hind limb cleanliness in Danish loose-housed, lactating dairy cows. The study was conducted as a cross-sectional study of 1315 cows in 42 commercial Danish dairy herds with primarily Danish Holstein cows. The effect of four cow-level factors (parity, days in milk, daily lying time and lameness) and eight herd-level factors (herd size, milk production, milking system, floor type, access to pasture grazing, floor scraping frequency, hoof bathing frequency and hoof washing frequency) on the risk of having dirtier hind limbs were analysed using ordinal logistic regression fitting a proportional odds model. Cow hind limb cleanliness was scored using an ordinal score from 1 to 4: 1 being clean and 4 being covered in dirt. The odds ratios (ORs) estimated from the proportional odds model depict the effect of a risk factor on the odds of having a higher rather than a lower cleanliness score. First parity cows had an increased risk of being dirtier compared with third parity or older cows (OR=1.70). Compared with late lactation, early and mid lactation were associated with an increased risk of being dirtier (OR=2.07 and 1.33, respectively). Decreasing the daily time lying by 30 min was associated with an increased risk of being dirtier (OR=1.05). Furthermore, an increased risk of being dirtier was found in herds with no pasture access (OR=3.75).     

Characterisation of the Repeat Breeding Syndrome in Swedish Dairy Cattle

Repeat breeding (RB), defined as cows failure to conceive from 3 or more regularly spaced services in the absence of detectable abnormalities, is a costly problem for the dairy producer. To elucidate the occurrence of RB in Swedish dairy herds and to identify risk factors of the syndrome totally 57,616 dairy cows in 1,541 herds were investigated based on data from the official Swedish production-, AI- and disease- recording schemes. The characteristics of the RB syndrome were studied on both herd and individual cow level. The effects of risk factors on the herd frequency of RB were studied by logistic regression. A generalised linear mixed model with logit link, and accounting for herd-level variation by including a random effect of herd, was used to study the individual animal risk for RB.     

Comparison of reproductive performance by artificial insemination versus natural service sires in California dairies

This study compared the calving to conception intervals for cows in AI pens with cows exposed to natural service sires, controlling for milk production, mastitis occurrence, parity and calving month effects. Records from 10 western United States dairy herds (mean herd size = 2058 cows) were evaluated retrospectively over an 18-month period. Eight bull breeding analysis cohorts were created (the first cohort 0-50 days in milk and the remaining cohorts at 25 days in milk intervals through 226 days). The cohorts contained non-pregnant cows that were first moved into bullpens during the described cohort period. Equal numbers of non-pregnant cows only exposed to AI during the cohort period were randomly selected from the pool of eligible non-pregnant cows. An AI cow was used only once in the data analysis, but was included in a bull breeding cohort at a later date if she remained non-pregnant and was transferred to a bullpen. Univariate and multivariate survival analysis was used to compare the calving to conception intervals. Cows in AI groups had higher hazard rates for pregnancy across all cohorts. Parity and milk production were significantly associated with risk for pregnancy. In herds that practice a mixture of AI and bull breeding, overall herd reproductive performance might be improved by allowing cows more opportunities at AI prior to moving them into clean-up bullpens.     

Individualised automated lameness detection in dairy cows and the impact of historical window length on algorithm performance

Lameness is an important economic problem in the dairy sector, resulting in production loss and reduced welfare of dairy cows. Given the modern-day expansion of dairy herds, a tool to automatically detect lameness in real-time can therefore create added value for the farmer. The challenge in developing camera-based tools is that one system has to work for all the animals on the farm despite each animal having its own individual lameness response. Individualising these systems based on animal-level historical data is a way to achieve accurate monitoring on farm scale. The goal of this study is to optimise a lameness monitoring algorithm based on back posture values derived from a camera for individual cows by tuning the deviation thresholds and the quantity of the historical data being used. Back posture values from a sample of 209 Holstein Friesian cows in a large herd of over 2000 cows were collected during 15 months on a commercial dairy farm in Sweden. A historical data set of back posture values was generated for each cow to calculate an individual healthy reference per cow. For a gold standard reference, manual scoring of lameness based on the Sprecher scale was carried out weekly by a single skilled observer during the final 6 weeks of data collection. Using an individual threshold, deviations from the healthy reference were identified with a specificity of 82.3%, a sensitivity of 79%, an accuracy of 82%, and a precision of 36.1% when the length of the healthy reference window was not limited. When the length of the healthy reference window was varied between 30 and 250 days, it was observed that algorithm performance was maximised with a reference window of 200 days. This paper presents a high-performing lameness detection system and demonstrates the importance of the historical window length for healthy reference calculation in order to ensure the use of meaningful historical data in deviation detection algorithms.     

Preliminary field evidence for the association of clinical mastitis with altered interestrus intervals in dairy cattle

Clinical mastitis and reproductive records from two southern California dairy herds were used in a cross-sectional study to determine the risk of an altered interestrus interval following clinical mastitis. An altered interestrus interval was defined as cycles occurring at either less than 18 day or more than 24-day intervals. The data were stratified by herd to assess herd differences and by lactation number to assess confounding by cow parity. The predominant pathogen isolated from mastitis cases in Herd 1 was Staphylococcus aureus , whereas the predominant pathogens in Herd 2 were gram-negative isolates. Cows in Herd 1 which had coliforms cultured from mastitic milk were excluded in the analysis for comparison with Herd 2. In Herd 1, cows with clinical mastitis were less likely to have an altered interestrus interval (Relative Risk [RR]=0.9; 95% Confidence Interval [CI]=0.6,1.6) than herdmates without clinical mastitis. However, cows in Herd 2 were almost two times more likely to have an altered interestrus interval following an episode of clinical mastitis compared to herdmates without clinical mastitis (RR=1.6; 95% CI=1.3,2.0). Because herd management practices differ and could cause differences in mastitis and reproductive outcomes at the dairies, this preliminary field evidence should be followed by prospective studies of luteal function after clinical coliform mastitis.     

Managing the transition from purebred to rotational crossbred dairy cattle herds: three technical pathways from a retrospective case-study analysis

The growing interest in rotational crossbreeding in Western countries is due to its potential to improve reproductive and health performances of cows. Although a large amount of research focuses on assessing crossbred cows’ performances, how to manage the transition from purebred to rotational crossbred herds is under-explored. Based on a retrospective analysis of French dairy herd case studies, we aimed to identify and characterise technical pathways to make such a transition. In 2018, we performed semi-directive interviews on 26 commercial dairy farms. Data were collected to describe changes in breeding, replacement and culling management practices from the first crossbred mating with purebred cows to the management of a mainly crossbred herd in 2018. Based on a multivariate analysis, we identified two main guidelines structuring technical pathways to move towards rotational crossbred herds: (i) the depth and scale of change (i.e. farm v. herd) associated with the introduction of rotational crossbreeding in the whole-farm dynamics and (ii) the changes in herd replacement and breeding practices to adapt to the evolution of herd demographics induced by the evolution of the dairy crossbred mating rate over time (high from the beginning v. distributed over time). Hierarchical clustering discriminated three groups of farmers differing in their technical pathway to move towards a rotational crossbred herd. In pathway 1, farmers customised one or several rotational crossbreeding schemes to support whole-farm transition towards an organic or grass-based system. Once the scheme stabilised, they quickly implemented it and had to readjust replacement and culling practices to regulate imbalance in herd demographics induced by the improvement in cow fertility. In pathway 2, farmers also customised one or several rotational crossbreeding schemes to support whole-farm redesign but they implemented it more gradually in the herd, which induced no major imbalance in herd demographics. In pathway 3, farmers predefined a relatively well-known rotational crossbreeding scheme to correct fertility issues of purebred cows without any changes at the farm level. They implemented it quickly from the beginning and had to adapt herd replacement and culling to regulate imbalance in herd demographics induced by the improvement in cow fertility. These first empirical evidences on how dairy farmers manage the transition from a purebred to rotational crossbred herd provide original scientific and operational contributions.     

Machine learning approaches for the prediction of lameness in dairy cows

Lameness is one of the costliest health problems, as well as a welfare concern in dairy cows. However, it is difficult to detect cows with possible lameness, or the ones that are at risk of becoming lame e.g. in the next week or so. In this study, we investigated the ability of three machine learning algorithms, Naïve Bayes (NB), Random Forest (RF) and Multilayer Perceptron (MLP), to predict cases of lameness using milk production and conformation traits. The performance of these algorithms was compared with logistic regression (LR) as the gold standard approach for binary classification. We had a total of 2 535 lameness scores (2 248 sound and 287 unsound) and 29 predictor features from nine dairy herds in Australia to predict lameness incidence. Training was done on 80% of the data within each herd with the remainder used as validation set. Our results indicated that in terms of area under curve of receiver operating characteristics, there were negligible differences between LR (0.67) and NB (0.66) while MLP (0.62) and RF (0.61) underperformed compared to the other two methods. However, the F1-score in NB (27%) outperformed LR (1%), suggesting that NB could potentially be a more reliable method for the prediction of lameness in practice, given enough relevant data are available for proper training, which was a limitation in this study. Considering the small size of our dataset, lack of information about environmental conditions prior to the incidence of lameness, management practices, short time gap between production records and lameness scoring, and farm information, this study proved the concept of using machine learning predictive models to predict the incidence of lameness a priori to its occurrence and thus may become a valuable decision support system for better lameness management in precision dairy farming.     

Bio-economic model to evaluate twinning rate using sexed embryo transfer in dairy herds

A stochastic bio-economic model has been used to determine the effects of new reproductive technologies over a 15-year period. A strategy of using conventional artificial insemination (AI) or embryo transfer (ET) using two sex-controlled embryos at different conception rates (CRs) and herd sizes resulted in a 24 state model. The genetic means of AI population increased over the years, and the genetic means of milk production for all of the embryo strategies were greater than those of AI. In addition, the genetic means of milk yield using different embryo-based scenarios in the expanding herds were greater than those for the fixed herds. The net profit of using sexed ET in the expanding herds was greater (P < 0.05) than that of fixed size herds. In general, there was a roughly consistent trend in net profit per cow for sexed ET strategies in the expanding herds over the years, but there was an increasing trend in net profit per cow for sexed ET strategies in the fixed herds over the years. Medium to high CRs for ET and the use of sex-controlled embryo systems, especially for induction of twin births to produce dairy replacements, will be critical elements of a system that produces significant numbers of female calves. The greater number of female calves produced in the sex-controlled scenarios allows the farmer to select animals with the best genetic potential as dairy replacement heifers; therefore, the rate of genetic gain increased in the dairy herd. Results of sensitivity analyses showed that a significant decrease in the production costs and increase in the ET performance are essential for embryo-based technologies to be profitable.