A new approach and insights on modelling the impact of production diseases on dairy cow welfare.

Animal welfare is becoming an important consideration in animal health-related decision-making. Integrating considerations of animal welfare into the decision-making process of farmers involves recognising the significance of health disorder impacts in relation to animal welfare. Yet little research quantifies the impact, making it difficult to include animal welfare in the animal health decision-making process. Quantifying the impact of health disorders on animal welfare is incredibly challenging due to empirical animal-based data collection constraints. An approach to circumvent these constraints is to rely on expert knowledge whereby perceived welfare impairment weights are indicative of the negative welfare effect. In this research, we propose an expertise-based method to quantify the perceived impact of sub-optimal mobility (SOM) on the welfare of dairy cows, because of its welfare importance. We first quantified perceived welfare impairment weights of SOM by eliciting expert knowledge using adaptive conjoint analysis (ACA). Second, using the perceived welfare impairment weights, we derived the perceived welfare disutility (i.e., perceived negative welfare effect) of mobility scores 1-5 (1 = optimal mobility, 5 = severely impaired mobility). Third, using the perceived welfare disutility per mobility score, we quantified the perceived welfare impact at case- and herd-level of SOM for different SOM severity. Results showed that perceived welfare disutility increased with each increase in mobility score. However, the perceived welfare impact of SOM cases with lower mobility scores was higher compared to SOM cases with higher mobility scores. This was because of the longer-lasting duration of the SOM cases with lower mobility scores. Moreover, the perceived herd-level welfare impact was largely due to SOM cases with lower mobility scores because of the longer duration and more frequent incidence compared to the SOM cases with higher mobility scores. These results entail that better welfare of dairy cows with respect to SOM can be achieved if lower mobility scores are detected and treated sooner. Our research demonstrates a novel approach that quantifies the perceived impact of health disorders on animal welfare when empirical evidence is limited.

Dutch dairy farmers' perspectives on culling reasons and strategies.

Since the abolishment of the milk quota system in Europe in 2014 and the introduction of environmental policies such as the phosphate rights system in the Netherlands, the reasons for culling dairy cows might have changed. The aim of this study was to determine the culling reasons for dairy cattle and to identify farmers' culling strategies and their intentions regarding the alteration of indicated culling strategies. To this end, an online questionnaire was distributed among dairy farmers nationally that resulted in 207 responses. Results showed that the most frequent culling reasons were related to problems with reproduction, udder, and hoof health. Primiparous cows were primarily culled for miscellaneous reasons such as injury, reproduction failure, and low milk yield. Multiparous cows were culled predominantly for reproduction failure, udder health and hoof health reasons. Most respondents indicated that they consider formulating a culling strategy, based on certain rules of thumb regarding the most common reasons for culling. Most farmers also reported that culling decisions on their farms were perceived to be unavoidable, though reproductive culling decisions are primarily voluntary. Most respondents stated that they intended to reduce the culling rate for better economic gain did not intend to alter the amount of replacement stock reared. The applied rules of thumb regarding culling strategies do not seem to have changed since the policy changes in dairy farming. The question remains whether farmers' rules of thumb might have made them unaware of the actual economic consequences of their culling strategies under the altered situation.

Economic impact of highly pathogenic avian influenza outbreaks in Western Java smallholder broiler farms.

Highly Pathogenic Avian Influenza (HPAI) H5N1 is considered endemic in most parts of Indonesia and constitutes an important risk for broiler production, especially in Western Java which has the highest poultry population in the country. Most broiler farms in Western Java are smallholder farms that operate under different business types: independent (i.e., revenues based on market price and live bird weight), price-contract (i.e., revenues based on a contract selling price and live bird weight) or makloon (i.e., revenues based on a management fee per sold bird). Many studies focus on the epidemiological impacts of HPAI at the regional level, and insights into the economic impact at the farm level are scarce, especially in the Indonesian context. Meanwhile, a single HPAI outbreak could disrupt smallholder broiler farmers' primary source of income. Therefore, this study aimed to evaluate the economic impact of HPAI outbreaks under different response scenarios (i.e., no action, stamping out, and early selling) on typical Western Java smallholder broiler farms. Furthermore, the effect of different farm business types and the existence of a sick-bird market on the economic effects of HPAI outbreaks were evaluated. We developed a dynamic stochastic bio-economic simulation model to simulate epidemiological and economic impacts of HPAI outbreaks on a typical Western Java smallholder broiler farm during one production round. Our results show that the economic consequences of HPAI outbreaks for independent and price-contract farms are considerable, ranging from, on average, 1.2-62.7 million Indonesian Rupiah (IDR) losses (€76.9 to €3919), depending on the moment of and response to infection, compared to an expected gross margin of 5.3 million IDR (€331) under normal circumstances. The economic loss for makloon farms was substantially lower than for other business types, reducing their incentive to implement biosecurity. The economic impacts were sensitive to changes in a diverse set of parameters, including disease transmission rate, detection threshold, and stamping-out compensation. The losses in a scenario with stamping out were higher than in other scenarios, especially when stamping out happened near the end of the production round. Moreover, reacting to an outbreak by selling chickens early gave the lowest economic losses, incentivizing farmers to engage in behavior with a high disease transmission risk. Therefore, the results of this study suggest that it is important to consider the economic perspective of individual farmers when designing HPAI mitigation programs. Financial incentives for farmers to control HPAI differ largely between farm business types.

Pegbovigrastim treatment resulted in an economic benefit in a large randomized clinical trial in grazing dairy cows.

This randomized controlled trial on 4 commercial grazing dairy farms investigated whether pegbovigrastim (PEG) treatment affected partial net return as calculated from milk revenues and costs for feed, medical treatments [clinical mastitis, uterine disease, and other diseases (i.e., any medical treatment that was not intended for clinical mastitis or uterine disease)], inseminations, and culling during a full lactation in grazing dairy cows. We also explored the effect of potential interactions of PEG treatment with parity, prepartum body condition score, and prepartum nonesterified fatty acids concentration on partial net return, milk revenues, and the costs mentioned above. Holstein cows were randomly assigned to 1 of the 2 following trial arms: a first PEG dose 9.4 ± 0.3 (mean ± standard error) days before the calving date and a second dose within 24 hours after calving (PEG: primiparous = 342; multiparous = 697) compared with untreated controls (control: primiparous = 391; multiparous = 723). The effect of PEG treatment on the outcomes of interest expressed per year was tested using general linear mixed models. Results are presented as least squares means ± standard error. Overall, PEG treatment increased the partial net return, resulting in an economic benefit per cow per year of $210 ± 100. The cost of treatment of clinical mastitis was lower for PEG treated cows compared with control cows ($9 ± 3). The largest nonsignificant difference was seen for the cost of culling; additionally, PEG treatment numerically reduced the cost of culling by $145 ± 77.

Modeling the economic impacts of mobility scores in dairy cows under Irish spring pasture-based management.

Moderate to severe forms of suboptimal mobility on dairy cows are associated with yield losses, whereas mild forms of suboptimal mobility are associated with elevated somatic cell count and an increased risk to be culled. Although the economic consequences of severe forms of suboptimal mobility (also referred as clinical lameness) have been studied extensively, the mild forms are generally ignored. Therefore, the aim of the current study was to determine the economic consequences associated with varying prevalence and forms of suboptimal mobility within spring calving, pasture-based dairy herds. A new submodel predicting mobility scores was developed and integrated within an existing pastured-based herd dynamic model. Using a daily timestep, this model simulates claw disorders, and the consequent mobility score of individual cows. The impact of a cow having varying forms of suboptimal mobility on production and reproduction was simulated. The economic impact was simulated including treatment costs, as well as the production and reproductive impacts of varying levels of suboptimal mobility. Furthermore, different genetic predispositions for mobility issues and their interaction with herd-level management associated with each level of suboptimal mobility were simulated. Overall, 13 scenarios were simulated, representing a typical spring calving, pasture-based dairy herd with 100 cows. The first scenario represents a perfect herd wherein 100% of the cows had mobility score 0 (optimal mobility) throughout the lactation. The remaining 12 scenarios represent a combination of (1) 3 different herd-management levels, and (2) 4 different levels of a genetic predisposition for suboptimal mobility. The analysis showed that a 17% decrease in farm net profit was achieved in the worst outcome (wherein just 5% of the herd had optimal mobility) compared with the perfect herd. This was due to reduced milk yield, increased culling, and increased treatment costs for mobility issues compared the ideal scenario.

Observational study on associations between resilience indicators based on daily milk yield in first lactation and lifetime profitability.

Resilience is the ability of cows to be minimally affected by disturbances, such as pathogens, heat waves, and changes in feed quality, or to quickly recover. Obvious advantages of resilience are good animal welfare and easy and pleasant management for farmers. Furthermore, economic effects are also expected, but these remain to be determined. The goal of this study was to investigate the association between resilience and lifetime gross margin, using indicators of resilience calculated from fluctuations in daily milk yield using an observational study. Resilience indicators and lifetime gross margin were calculated for 1,325 cows from 21 herds. These cows were not alive anymore and, therefore, had complete lifetime data available for many traits. The resilience indicators were the natural log-transformed variance (LnVar) and the lag-1 autocorrelation (rauto) of daily milk yield deviations from cow-specific lactation curves in parity 1. Good resilience is indicated by low LnVar (small yield response to disturbances) and low rauto (quick yield recovery to baseline). Lifetime gross margin was calculated as the sum of all revenues minus the sum of all costs throughout life. Included revenues were from milk, calf value, and slaughter of the cow. Included costs were from feed, rearing, insemination, management around calving, disease treatments, and destruction in case of death on farm. Feed intake was unknown and, therefore, lifetime feed costs had to be estimated based on milk yield records. The association of each resilience indicator with lifetime gross margin, and also with the underlying revenues and costs, was investigated using analysis of covariance (ANCOVA) models. Mean daily milk yield in first lactation, herd, and year of birth were included as covariates and factors. Natural log-transformed variance had a significantly negative association with lifetime gross margin, which means that cows with stable milk yield (low LnVar, good resilience) in parity 1 generated on average a higher lifetime gross margin than cows that had the same milk yield level but with more fluctuations. The association with lifetime gross margin could be mainly attributed to higher lifetime milk revenues for cows with low LnVar, due to a longer lifespan. Unlike LnVar, rauto was not significantly associated with lifetime gross margin or any of the underlying lifetime costs and revenues. However, it was significantly associated with yearly treatment costs, which is important for ease of management. In conclusion, the importance of resilience for total profit generated by a cow at the end of life was confirmed by the significant association of LnVar with lifetime gross margin, although effects of differences in feed efficiency between resilient and less resilient cows remain to be studied. The economic advantage can be mainly ascribed to benefits of long lifespan.

Revenues and costs of dairy cows with different voluntary waiting periods based on data of a randomized control trial.

Based on modeling studies, a 1-yr calving interval for dairy cows is generally considered optimal from an economic point of view. Recently some dairy farmers are deliberately extending the voluntary waiting period for insemination (VWP) to extend the calving interval. Reasons to extend the VWP are to reduce the frequency of transitions such as dry-off and calving to improve health, to reduce labor associated with these transitions, and to reduce the number of surplus calves. This study aimed to evaluate yearly revenues, yearly costs, and yearly net partial cash flow (NPCF) for individual cows with a VWP of 50, 125, or 200 d based on data from a randomized control trial. The NPCF included revenues and costs for milk yield, calves born, inseminations, concentrate supply, partial mixed ration (PMR) supply, veterinary treatments, discarded milk due to veterinary treatments, culling, and labor (for milking, calving cows, inseminations, and veterinary treatments). Holstein-Friesian dairy cows (n = 153) within one herd were blocked for parity, calving season, and expected (primiparous cows) or previous (multiparous cows) 305-d milk yield. Cows were randomly assigned within the blocks to 1 of 3 VWP (VWP50, VWP125, or VWP200) in wk 6 after calving, and monitored from wk 6 after calving until wk 6 after the next calving or until culling. Revenues and costs were calculated per individual cow and expressed per cow per year. Revenues from milk and costs for PMR and concentrate contributed most to the yearly NPCF. Total yearly revenues were greater in VWP50 compared with VWP200 (€3,169 vs. €2,832), mainly because of €334 greater milk revenues. Total yearly costs were also greater in VWP50 compared with VWP200 (€1,964 vs. €1,729), mainly because of €102 greater concentrate costs. The VWP was not significantly associated with the NPCF per cow per year. A change in milk, feed, or calf price, or a change in labor costs for calving cows or for inseminations had a greater effect on the yearly NPCF of cows in VWP50 compared with cows in VWP200. To investigate variation in NPCF, cows were grouped for yearly NPCF and categorized into 3 economic classes (EC): EC1 (<€1,100/yr), EC2 (€1,100-€1,400/yr), and EC3 (>€1,400/yr). Cows in EC3 had greatest lactation production per day in the experiment (i.e., kg of milk, protein, fat, lactose), and lowest number of veterinary treatments during the experiment.

Regularly fluctuating somatic cell count pattern in dairy herds.

Online somatic cell count (SCC) measurement is widely used in dairy herds milked with automatic milking systems (AMS) and gives the opportunity to closely monitor individual cow udder health. Using automated SCC data, we observed cows displaying a remarkably regularly fluctuating SCC (rfSCC) pattern, which is described in this study. We aimed to (1) estimate the prevalence of rfSCC in cows milked by AMS, (2) characterize the rfSCC pattern, and (3) identify factors potentially associated with the rfSCC pattern. We analyzed 30-d episodes of composite SCC recordings of 1,000 cows from 55 dairy herds from 6 countries using an AMS with automated SCC measurement, and we identified the rfSCC pattern in 4.7% (95% CI: 3.5-6.2%) of these episodes. The rfSCC episodes had a median SCC of 701 × 1,000 cells/mL (2.5-97.5% quantile: 539-1,162), a median amplitude of 552 × 1,000 cells/mL (2.5-97.5% quantile: 409-886), and a median cycle length of 4.1 d (2.5-97.5% quantile: 3.7-4.9). Bacteriological culture data from quarter-milk samples collected every 2 wk in 1 Dutch AMS herd were analyzed, yielding no clear association between pathogen species and the rfSCC pattern found in that herd. Altogether, we described an intriguing phenomenon, present in almost 5% of the cows during a 1-mo study period. Further work is needed to quantify its importance in terms of udder health, but also to elucidate the mechanism behind this remarkable SCC pattern.

Invited review: Toward a common language in data-driven mastitis detection research.

Sensor technologies for mastitis detection have resulted in the collection and availability of a large amount of data. As a result, scientific publications reporting mastitis detection research have become less driven by approaches based on biological assumptions and more by data-driven modeling. Most of these approaches try to predict mastitis events from (combinations of) raw sensor data to which a wide variety of methods are applied originating from machine learning and classical statistical approaches. However, an even wider variety in terminologies is used by researchers for methods that are similar in nature. This makes it difficult for readers from other disciplines to understand the specific methods that are used and how these differ from each other. The aim of this paper was to provide a framework (filtering, transformation, and classification) for describing the different methods applied in sensor data-based clinical mastitis detection research and use this framework to review and categorize the approaches and underlying methods described in the scientific literature on mastitis detection. We identified 40 scientific publications between 1992 and 2020 that applied methods to detect clinical mastitis from sensor data. Based on these publications, we developed and used the framework and categorized these scientific publications into the 2 data processing techniques of filtering and transformation. These data processing techniques make raw data more amendable to be used for the third step in our framework, that of classification, which is used to distinguish between healthy and nonhealthy (mastitis) cows. Most publications (n = 34) used filtering or transformation, or a combination of these 2, for data processing before classification, whereas the remaining publications (n = 6) classified the observations directly from raw data. Concerning classification, applying a simple threshold was the most used method (n = 19 publications). Our work identified that within approaches several different methods and terminologies for similar methods were used. Not all publications provided a clear description of the method used, and therefore it seemed that different methods were used between publications, whereas in fact just a different terminology was used, or the other way around. This paper is intended to serve as a reference for people from various research disciplines who need to collaborate and communicate efficiently about the topic of sensor-based mastitis detection and the methods used in this context. The framework used in this paper can support future research to correctly classify approaches and methods, which can improve the understanding of scientific publication. We encourage future research on sensor-based animal disease detection, including that of mastitis detection, to use a more coherent terminology for methods, and clearly state which technique (e.g., filtering) and approach (e.g., moving average) are used. This paper, therefore, can serve as a starting point and further stimulates the interdisciplinary cooperation in sensor-based mastitis research.

Effects of extended voluntary waiting period from calving until first insemination on body condition, milk yield, and lactation persistency.

A 1-yr calving interval (CInt) is usually associated with maximized milk output, due to the calving-related peak in milk yield. Extending CInt could benefit cow health and production efficiency due to fewer transition periods per unit of time. Extending CInt can affect lactation performance by fewer days dry per year, delayed pregnancy effect on milk yield, and greater milk solid yield in late lactation. This study first investigated the effects of 3 different voluntary waiting periods (VWP) from calving until first insemination on body weight, body condition, milk yield, and lactation persistency. Second, individual cow characteristics in early lactation were identified that contributed to milk yield and persistency of cows with different VWP. Holstein-Friesian dairy cows (n = 154) within 1 herd were blocked for parity, calving season, and expected milk yield. Cows were randomly assigned within the blocks to 1 of 3 VWP (50, 125, or 200 d: VWP50, VWP125, or VWP200, respectively) and monitored through 1 complete lactation and the first 6 wk of the subsequent lactation, or until culling. Minimum and mean CInt (384 vs. 452 vs. 501 d for VWP50 vs. VWP125 vs. VWP200) increased with increasing VWP, but maximum CInt was equal for the 3 VWP. Fat- and protein-corrected milk yield (FPCM) was analyzed weekly. Milk yield and FPCM were also expressed per day of CInt, to compare yields of cows with different VWP. Persistency was determined between d 100 and d 200 of the lactation, as well as between d 100 and dry-off. Values are presented as least squares means ± standard error of the mean. During the first 44 wk of lactation, VWP did not affect FPCM yield in both primiparous and multiparous cows. The VWP did not affect milk yield per day of CInt. The VWP did not affect FPCM yield per day of calving interval for primiparous cows. Multiparous cows in VWP125 had FPCM yield per day of CInt similar to that of VWP50. Multiparous cows in VWP200 had lower FPCM yield per day of CInt compared with VWP50 (27.2 vs. 30.4 kg/d). During the last 6 wk before dry-off, cows in VWP125 had lower yield compared with cows in VWP50, which could benefit their udder health in the dry period and after calving. Persistency was better for cows in VWP200 compared with cows in VWP50 (-0.05 vs. -0.07 kg/d). Body weight was not different among VWP groups. Multiparous cows in VWP200 had a higher body condition score in the last 3 mo before dry-off and the first 6 wk of the next lactation, compared with multiparous cows in VWP125 and VWP50. The VWP could be extended from 50 d to 125 d without an effect on daily yield per day of calving interval. Extending VWP until 200 d for primiparous cows did not affect their daily milk yield, but multiparous cows with a 200-d VWP had a reduced milk yield per day of calving interval and an increased body condition in late lactation and the subsequent lactation, compared with multiparous cows with a 50-d VWP.

Effects of flow-controlled vacuum on milking performance and teat condition in a rotary milking parlor.

The objective of this study was to compare a vacuum control system that increases milking system vacuum during the peak flow period of milking to conventional constant vacuum control technology regarding its effect on milk flowrate and milking duration. Further objectives were to study the effects of flow-controlled vacuum on milking parlor performance. An observational study was conducted on a commercial dairy farm milking from 848 to 896 cows per day over the study period using a 60-stall rotary milking parlor. The flow-controlled vacuum control system was applied for 3 wk. Milking performance and teat condition were compared with 3-wk periods prior and subsequent to the test period using conventional vacuum control. Statistical analysis was performed assuming a cross-sectional study design during each period. Flow-controlled vacuum increased peak milk flowrate by 12% and increased average milk flowrate by 4%. The decrease in individual cow milking duration was proportional to milk yield per milking. Postmilking teat condition was good during the entire study period. The occurrence of rough teat ends was slightly reduced during the flow-controlled vacuum period with no meaningful difference in the occurrence of teats with blue color, palpable rings, or petechia. The combination of reduced vacuum during the low flow period of milking and the decrease in milking duration are likely factors that are protective of teat tissues. Bioeconomic modeling of the use of flow-controlled vacuum on the performance of rotary milking parlors, using the data that were collected during the study, showed that the reduction in milking duration of individual cows allows a higher rotary parlor speed. Modeled parlor throughput increased by 5.0% to 419 cows/h, 6.8% to 407 cows/h, and 4.2% to 326 cows/h when 80%, 95%, and 99% of the cows were finished milking at the end of the rotation for a 60-stall parlor. Model results showed that increased parlor throughput resulted in increased labor efficiency, reduced labor costs for milking, and a positive benefit-cost ratio on the investment for all but the smallest herd and parlor sizes considered.

Fertility and milk production on commercial dairy farms with customized lactation lengths.

Drying-off, calving, and start of lactation are critical transition events for a dairy cow. As a consequence, most animal health issues occur during these periods. By extending the voluntary waiting period for first insemination after calving, calving interval (CInt) can be extended, with possible positive effects for fertility and health. Some cows might be better suited for an extended CInt than others, due to differences in milk yield level, lactation persistency, or health status, which would justify a customized CInt based on individual cow characteristics. This study aims to investigate 13 farms with customized CInt, with respect to calving to first service interval (CFSI), accomplished CInt, services per conception (SC), conception rate at first artificial insemination (CR1AI), peak yield, lactation persistency, 305-d yield, and effective lactation yield. In total, 4,858 complete lactations of Holstein Friesian cows between 2014 and 2019 from the 13 farms were grouped by parity (1 or 2+) and CFSI (CFSI class; CFSI-1 < 84; 84 ≤ CFSI-2 < 140; 140 ≤ CFSI-3 < 196; 196 ≤ CFSI-4 < 252, CFSI-5 ≥ 252 d) or CInt (CInt class; CInt-1 < 364; 364 ≤ CInt-2 < 420; 420 ≤ CInt-3 < 476; 476 ≤ CInt-4 < 532, CInt-5 ≥ 532 d). Cow inseminations, available for 11 out of 13 farms (3,597 complete lactations), were grouped by parity (1 and 2+) and CFSI class or CInt class. The fertility and milk production characteristics were analyzed with generalized and general linear mixed models. The CFSI class was not associated with SC, but extended CInt class was associated with increased SC (CInt-1-5; 1.11-3.70 SC). More than 50% of cows in the CFSI class <84 d ended up in longer than expected CInt (>364 d), showing that these cows were not able to conceive for the desired CInt. More than 50% of cows in CInt classes 3 and higher (CInt ≥ 420 d) had an earlier first insemination before successful insemination (CFSI class 1; <196 d), showing that these extended CInt classes consisted of both cows with an extended waiting period for first insemination and cows that failed to conceive at earlier insemination(s). On most farms, lactation persistency was greatest in CInt class 1 (<364 d), probably related to the low peak yield in this class. When this shortest CInt class was excluded, persistency increased with extended CInt classes on most farms. Although at the majority of farms 305-d yield was greater in CInt ≥ 532 d, effective lactation yield at most farms was greatest in CInt from 364 to 531 d, especially for multiparous cows. Based on the results of this study, a CInt between 364 and 531 days seems most optimal for milk production, when high-yielding cows were selected.

Associating mobility scores with production and reproductive performance in pasture-based dairy cows.

Lameness in dairy cows can have significant effects on cow welfare, farm profitability, and the environment. To determine the economic and environmental consequences of lameness, we first need to quantify its effect on performance. The objective of this study, therefore, was to determine the associations of various production and reproductive performance measurements (including milk, fat, and protein yield, somatic cell count, calving interval, cow death, or cow slaughter), and mobility scores in spring-calving, pasture-based dairy cows. We collected mobility scores (0 = good, 1 = imperfect, 2 = impaired, and 3 = severely impaired mobility), body condition scores, and production data for 11,116 cows from 68 pasture-based dairy herds. Linear mixed modeling was used to determine the associations between specific mobility scores and milk, fat and protein yield, and somatic cell count and calving interval. Binomial logistic regression was used to determine the association between mobility score and cow death, or slaughter. Significant yield losses of up to 1.4% of the average yield were associated with mobility score 2 and yield losses of up to 4.7% were associated with mobility score 3 during the early scoring period. Elevated somatic cell count was associated with all levels of suboptimal mobility during the late scoring period. Cows with a mobility score of 2 during the early scoring period were associated with longer calving interval length, whereas only cows with a mobility score of 3 during the late scoring period were associated with longer calving interval length. Cows with a mobility score ≥1 were more likely to be culled during both scoring periods. Our study, therefore, shows an association between specific mobility scores and production and reproductive performance in spring-calving, pasture-based dairy cows scored during the summer grazing period.

Pathogen effects on milk yield and composition in chronic subclinical mastitis in dairy cows.

This study aimed to evaluate the effects of chronic subclinical mastitis (CSM) on milk production and component yields in dairy cows. A total of six herds located in the Midwest area of São Paulo State, Brazil were selected. Herds were visited once every 2 weeks to measure milk yield and to collect milk samples from lactating Holstein cows. Milk samples were collected at two stages (1 and 2), and each stage comprised three milk samplings. In stage 1, a total of 117 of 647 cows were diagnosed with CSM based on at least two of three repeated somatic cell counts (SCC) > 2000,000 cells/mL and positive bacterial milk culture results (BC). Cows with CSM were selected for the second stage. In stage 2, selected cows had quarter sampling aseptically collected for BC analyses prior to milking, and quarter milk yield was measured. Milk components (total protein, fat, lactose, and total solids) were measured using mid-infrared spectroscopy. Mammary quarters were considered healthy if all three repeated SCC results were ≤ 200,000 cells/mL and no bacterial growth was detected on BC. All quarters with positive bacterial growth were classified as having (non-chronic) subclinical mastitis when only one of three SCC results were > 200,000 cells/mL, and CSM when at least two of three SCC results were > 200,000 cells/mL. The effects of CSM by type of pathogen on milk and components yield were assessed using a linear mixed model. Mammary quarters with CSM caused by major pathogens had milk loss of 1.1 kg/quarter milking in comparison to healthy quarters. Milk losses were 0.8 and 1.3 kg/quarter milking when CSM was caused by Staphylococcus aureus or environmental streptococci, respectively. In addition, healthy quarters produced more milk components than quarters with CSM caused by major pathogens. Minor pathogens causing CSM (non-aureus staphylococci and Corynebacterium spp.) had no effect on milk yield. Quarters with CSM had lower milk and component yields when compared with healthy quarters. Milk losses varied according to the type of pathogen and were higher when associated with major pathogens such as S. aureus and environmental streptococci compared with healthy quarters.

Cow and herd-level risk factors associated with mobility scores in pasture-based dairy cows.

Lameness in dairy cows is an area of concern from an economic, environmental and animal welfare point of view. While the potential risk factors associated with suboptimal mobility in non-pasture-based systems are evident throughout the literature, the same information is less abundant for pasture-based systems specifically those coupled with seasonal calving, like those in Ireland. Therefore, the objective of this study was to determine the potential risk factors associated with specific mobility scores (0 = good, 1 = imperfect, 2 = impaired, and 3 = severely impaired mobility) for pasture-based dairy cows. Various cow and herd-level potential risk factors from Irish pasture-based systems were collected and analyzed for their association with suboptimal mobility, whereby a mobility score of 0 refers to cows with optimal mobility and a mobility score ≥ 1 refers to a cow with some form of suboptimal mobility. Combined cow and herd-level statistical models were used to determine the increased or decreased risk for mobility score 1, 2, and 3 (any form of suboptimal mobility) compared to the risk for mobility score 0 (optimal mobility), as the outcome variable and the various potential risk factors at both the cow and herd-level were included as predictor type variables. Cow-level variables included body condition score, milk yield, genetic predicted transmitting ability for 'lameness', somatic cell score, calving month and cow breed. Herd-level variables included various environmental and management practices on farm. These analyses have identified several cow-level potential risk factors (including low body condition score, high milk yield, elevated somatic cell count, stage of lactation, calving month, and certain breed types), as well as various herd-level potential risk factors (including the amount of time taken to complete the milking process, claw trimmer training, farm layout factors and foot bathing practices) which are associated with suboptimal mobility. The results of this study should be considered by farm advisors when advising and implementing a cow/herd health program for dairy cows in pasture-based systems.

Antimicrobial use and farmers' attitude toward mastitis treatment on dairy farms with automatic or conventional milking systems.

Mastitis is one of the major causes for antimicrobial use on dairy cattle farms. On farms with an automatic milking system (AMS), diagnostics differ from those with a conventional milking system (CMS), with potentially a different attitude toward mastitis treatment. This may result in differences in antimicrobial usage (AMU) between these 2 types of farms. The aims of this study were (1) to compare AMU between AMS and CMS farms, (2) to identify variables associated with AMU in both types of herds, and (3) to describe the distribution of mastitis-causing pathogens and their antimicrobial resistance patterns. Data on AMU was collected for 42 AMS and 254 CMS farms in the Netherlands and was expressed as animal-defined daily dose (ADDD). The ADDD variables were total usage (ADDDTOTAL), intramammary usage during lactation (ADDDIMM), usage for dry cow therapy (ADDDDCT), and usage by injection (ADDDINJ). Eighteen AMS farms and 24 CMS farms participated in a survey on factors potentially related to AMU. These farmers collected 5 quarter milk samples from quarters with clinical mastitis or high somatic cell count, which were subjected to bacteriological culture and antimicrobial susceptibility testing. In addition, routinely collected udder health data of these farms were used in the analysis. Nonlinear principal component analysis (NLPCA) was used to explore associations between AMU, udder health, and questionnaire variables. The ADDDTOTAL and ADDDDCT were comparable between AMS and CMS farms, whereas ADDDIMM tended to be lower and ADDDINJ higher on AMS farms than on CMS farms. The NLPCA yielded 3 principal components (PC) that explained 48% of the variation in all these variables. The AMS farms were not distinguished from CMS farms in the principal component space. The 3 PC represented different aspects of udder health, ADDDTOTAL, and treatment strategy. Differences in treatment strategy were unrelated to total antimicrobial usage or overall udder health. The distribution of mastitis-causing pathogens and their antimicrobial resistance were comparable between AMS and CMS farms. In conclusion, our study shows that AMU on AMS farms was similar to that of CMS farms, but AMS farmers tend to apply more injectable and fewer intramammary treatments during lactation than CMS farmers. Across both farm types, farmers' attitudes toward udder health in general and toward mastitis treatment are associated with AMU.

Associating cow characteristics with mobility scores in pasture-based dairy cows.

The quality of dairy cow mobility can have significant welfare, economic, and environmental consequences that have yet to be extensively quantified for pasture-based systems. The objective of this study was to characterize mobility quality by examining associations between specific mobility scores, claw disorders (both the type and severity), body condition score (BCS), and cow parity. Data were collected for 6,927 cows from 52 pasture-based dairy herds, including mobility score (0 = optimal mobility; 1, 2, or 3 = increasing severities of suboptimal mobility), claw disorder type and severity, BCS, and cow parity. Multinomial logistic regression was used for analysis. The outcome variable was mobility score, and the predictor variables were BCS, type and severity of claw disorders, and cow parity. Three models were run, each with 1 reference category (mobility score 0, 1, or 2). Each model also included claw disorders (overgrown claw, sole hemorrhage, white line disease, sole ulcer, and digital dermatitis), BCS, and cow parity as predictor variables. The presence of most types of claw disorders had odds ratios >1, indicating an increased likelihood of a cow having suboptimal mobility. Low BCS (BCS <3.00) was associated with an increased risk of a cow having suboptimal mobility, and relatively higher parity was also associated with an increased risk of suboptimal mobility. These results confirm an association between claw disorders, BCS, cow parity, and dairy cow mobility score. Therefore, mobility score should be routinely practiced to identify cows with slight deviations from the optimal mobility pattern and to take preventive measures to keep the problem from worsening.

The economic impact of drying off cows with a dry-off facilitator (cabergoline) compared with 2 methods of gradual cessation of lactation for European dairy farms.

An abrupt method to dry off cows has disadvantages and is considered inappropriate for current dairy cows due to welfare issues and risks for intramammary infections (IMI). A gradual cessation of lactation (by feeding or milking frequency reduction) has been the generally recommended method for drying off cows to prevent these adverse effects. However, a new alternative to the gradual approach is to abruptly stop milking at the same time as using cabergoline (CAB), a prolactin inhibitor. The aim of the study was to compare the net costs of 3 different methods of drying off cows [gradual reduction in feed (referred to as gradual feeding), gradual reduction in milking frequency (referred to as gradual milking), and abrupt cessation of milking with CAB]. A stochastic Monte Carlo simulation model, at cow level, was developed to calculate the net costs of applying these methods. All inputs for the model were based on literature information, authors' expertise, and expert knowledge. The net costs were determined by only including costs and benefits, which varied between the 3 methods. The model simulated a cow from 7 d before the day of drying off until the end of the next lactation. The likelihood of whether a cow was leaking milk early in the dry period was determined. Subsequently, it was determined whether or not the cow will get an IMI during the dry period, where the probability of getting an IMI was higher for cows leaking milk than for cows not leaking milk. If the IMI was not cured during the dry period, the cow had an IMI at calving. Also, milk production and feed requirements were modeled, and labor for applying the drying off method was included. For all methods, the net costs were calculated as the sum of costs for feed during the gradual feed reduction period, costs for applying the gradual-milking method, and the IMI costs during the dry period and lactation, minus the milk revenues during the transition from lactation to the dry period. Under default conditions, the average net cost of abrupt cessation of milking with CAB was €49.6/cow. The data showed that 90% of the net costs ranged from -€13.7 to €307.8/cow. The average net costs for gradual feeding and gradual milking were €99.1 and €71.5/cow, respectively. In conclusion, abrupt cessation of milking with CAB saved €49.5 and €21.9/cow on average compared with gradual feeding and gradual milking, respectively. This difference was mainly due to more milk returns and lower labor and IMI costs during lactation.

Failure costs associated with mastitis in smallholder dairy farms keeping Holstein Friesian × Zebu crossbreed cows.

Mastitis is a costly disease and in many areas of the world, these costs have been quantified to support farmers in their decision making with regard to prevention of mastitis. Although for subsaharan circumstances estimates have been made for the costs of subclinical mastitis (SCM), farm-specific cost estimations comprising both clinical mastitis (CM) and SCM are lacking. In this paper, we quantified failure costs of both CM and SCM on 150 Ethiopian market-oriented dairy farms keeping Holstein Friesian × Zebu breed cows. Data about CM were collected by face-to-face interviews and the prevalence of SCM was estimated for each farm using the California mastitis test. All other relevant information needed to calculate the failure costs, such as the consequences of mastitis and price levels, was collected during the farm visits, except for the parameter for milk production losses due to SCM, which was based on literature estimates and subjected to sensitivity analyses. The average total failure costs of mastitis was estimated to be 4 765 Ethiopian Birr (ETB) (1 ETB = 0.0449 USD) per farm per year of which SCM contributed 54% of the costs. The average total failure costs per lactating cow per farm per year were 1 961 ETB, with a large variation between farms (range 0 to 35 084 ETB). This large variation in failure costs between farms was mainly driven by variation in incidence of CM and prevalence of SCM. Milk production losses made the largest contribution (80%), whereas culling contributed 13% to 17% to the total failure costs. In our estimates, costs of veterinary services, drugs, discarded milk and labour made a minor contribution to the total failure costs of mastitis. Relative to the income of dairy farmers in North Western Ethiopia; the total failure costs of mastitis are high. In general, Ethiopian farmers are aware of the negative consequences of CM, but creating awareness of the high costs of SCM and showing large variation between farmers may be instrumental in motivating farmers to also take preventive measures for SCM.

Farm-specific failure costs of production disorders in European organic dairy herds.

On-farm decision support in animal health management requires a tailor-made failure costs (FCs) assessment of production disorders for the individual farm. In our study we defined a generic framework to estimate the FC of production disorders in dairy cows. We converted the framework to a practical tool in which the farm-specific FC of mastitis, ketosis, lameness and metritis were estimated for 162 organic dairy farms in four European countries. Along with the structure of the framework, the FC estimation required three distinct types of model input: performance input (related to herd performance parameters), consequential input (related to the consequences of the disorders) and economic input (related to price levels). Input was derived from official herd recordings (e.g. test-day records and animal health recordings) and farmers' responses (e.g. questionnaire replies). The average FC of mastitis, ketosis, lameness and metritis amounted to € 96, € 21, € 43 and € 10 per cow per year, respectively. The variation in FC outcomes was high among farmers and countries. Overall ranking of the disorders based on absolute values was the same for all countries, with mastitis being the costliest disorder followed in order by lameness, ketosis, and metritis. Farm specific estimates can be used to rank production related disorders in terms of their associated failure costs and thus provide valuable insights for herd health management. The practical calculation tool developed in this study should be considered by farmers or herd health advisors to support their animal health practices or advice.