Quantifying multiple burdens of dairy cattle production diseases and reproductive inefficiency: current knowledge and proposed metrics.

The economic burden of diseases and reproductive inefficiency in dairy cattle is evident and has been quantified. Dairy diseases and reproductive inefficiency are however associated with other issues as well, including animal welfare, environmental pressure, and public health risks. Quantifying these other issues is becoming important to help farmers making decisions. Quantification of the non-economic burdens of diseases and reproductive inefficiency is rare and lacks an overview of approaches and metrics. The first aim of this paper is to provide trends for associating diseases and reproductive inefficiency with economic and non-economic burdens of disease. The second aim is to provide a review of approaches and metrics used to quantify the non-economic burdens of disease and reproductive inefficiency. For the economic burden of diseases and reproductive performance, only an overview of the approaches used to quantify the burden is provided. The final aim is to propose approaches and metrics for future quantification of non-economic burdens caused by individual diseases. A literature search was conducted in Web of Science to identify scientific articles on mastitis, lameness, metabolic disorders and reproductive inefficiency in dairy cows. The search was restricted to articles published between 1 January 2010 and 31 December 2022 and resulted in 7,565 articles. The total number of articles that mentioned the economic, animal welfare, public health, and environmental burden was 1,253, 428, 291, and 77, respectively. An increase in the percentage of articles mentioning the economic, animal welfare, and public health burden is observed between 2010 and 2022. Despite the 2,049 articles that mentioned one of the burdens, the results showed that approximately 10% of the articles quantified one or more of these burdens. The economic burden of diseases and reproductive inefficiency has been quantified in 154 articles and very few articles quantified the non-economic burdens (9 articles for environment, 29 articles for public health and 2 articles for animal welfare). Eleven articles were identified that quantified multiple burdens, and in all these studies the economic burden was combined with a non-economic burden through a modeling approach (mainly simulation). We propose to link the non-economic burdens to biological simulation models, and thus develop bio-burden simulation models. Well-established approaches and metrics can be used to quantify economic, environmental, and public health burdens. For the economic impact, costs per cow per year can be assessed. A life cycle assessment can be performed for environmental impact and the public health impact can be assessed by a defined daily dose for antimicrobial use and disability-adjusted life years for zoonotic diseases. Regarding animal welfare, approaches and metrics to quantify the welfare impact of a diseased animal are not well established. For animal welfare, we propose a welfare-adjusted life years approach. The mentioned approaches and metrics are a proposal, and it is up to the scientific community to use them or, based on empirics and research experience, propose changes so that we will end up with robust approaches and metrics that enable us to compare research results and provide more evidence for animal health decision makers.

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 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.

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.

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.

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 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.

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.

Farm-level risk factors for bovine mastitis in Dutch automatic milking dairy herds.

Automatic milking systems (AMS) are installed on a growing number of dairy farms worldwide. Management to support good udder health might be different on farms with an AMS compared with farms milking with a conventional milking system, as risk factors for mastitis on farms using an AMS may differ. The aim of this study was to identify farm level factors associated with mastitis on Dutch dairy farms using an AMS. In 2008, risk factor data were collected using a questionnaire combined with on-farm recordings of cow, stall, and AMS hygiene on 135 farms. These risk factor data were linked to 4 udder-health-associated dependent variables: average herd somatic cell count (HeSCCav), variance of the average herd somatic cell count (SCC) on test days (HeSCCvar), the average proportion of new high SCC cases (NHiSCC), and the farmer-reported annual incidence rate of clinical mastitis (IRCM). We employed regression models using multiple imputation to deal with missing values. Due to the high dimensionality of the risk factor data, we also performed nonlinear principal component analysis (NLPCA) and regressed the dependent variables on the principal components (PC). Good hygiene of cows and of AMS were found to be related to a lower HeSCCav and less NHiSCC. Effective postmilking teat disinfection was associated with a lower NHiSCC. A higher bulk tank milk SCC threshold for farmers' action was related to more NHiSCC. Larger farm size was related to lower HeSCCvar but higher NHiSCC. Negative attitude of farmers to animal health, higher frequency of checking AMS, and more time spent on viewing computer data were all positively related to higher IRCM. An NLPCA with 3 PC explained 16.3% of the variance in the risk factor variables. Only the first 2 PC were associated with mastitis. The first PC reflected older and larger farms with poor cow hygiene and AMS hygiene, and was related to higher HeSCCav and NHiSCC, whereas the second PC reflected newly built smaller farms with poor cow hygiene and low milk production, and was associated with higher HeSCCvar and NHiSCC, but lower IRCM. Our study suggests that many of the risk factors on conventional milking system farms are applicable to AMS farms, specifically concerning hygiene of the cows and the milking machine, but on large AMS farms, udder health may need more attention than on smaller AMS farms. Multiple imputation is instrumental to deal with missing values and NLPCA is a useful technique to process high dimensional data in our study.

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.

Economic optimization of selective dry cow treatment.

The objective of this study was to develop a mathematical model to identify a scenario with the lowest costs for mastitis associated with the dry period while restricting the percentage of cows to be dried off with dry cow antimicrobials. Costs of clinical and subclinical mastitis as well as antimicrobial use were quantified. Based on data from a large field trial, a linear programming model was built with the goal to minimize the costs associated with antimicrobial use at drying off. To enable calculations on minimizing costs of dry cow treatment on herd-level by drying-off decisions in an "average" herd, we created an example herd. Cows were projected on 3 different types of herds, based on bulk tank somatic cell count, and were categorized in groups based on parity and somatic cell count from the last test recording before drying-off. Economically optimal use of antimicrobials was determined while restricting the maximum percentage of cows dried off with antimicrobials from 100 to 0%. This restriction reveals the relationship between the maximum percentage of cows dried off with antibiotics and the economic consequences. A sensitivity analysis was performed to evaluate the effect of variation in the most important input variables, with the effect of dry cow antimicrobials resulting in a lower or higher percentage of clinical and subclinical mastitis depending on being dried off with or without dry cow antimicrobials, respectively, and the milk price. From an economic perspective, blanket dry cow treatment seems not to be the optimal approach of dry cow therapy, although differences between approaches were small. With lower bulk tank somatic cell counts, more dry cow antimicrobials can be omitted without economic consequences. The economic impact of reducing the percentage of clinical mastitis was found to be much larger than reducing the bulk tank somatic cell count. The optimal percentage of cows to be dried off with antimicrobials depends on the udder health situation, expressed as the bulk tank somatic cell count and the incidence of clinical mastitis. For all evaluated types of herds, selective dry cow treatment was economically more beneficial than blanket dry cow treatment. Economic profits of selective dry cow treatment are greater if bulk tank somatic cell count and clinical mastitis incidence are lower. Economics is not an argument against reduction of dry cow antimicrobials by applying selective dry cow treatment.

Delaying investments in sensor technology: The rationality of dairy farmers' investment decisions illustrated within the framework of real options theory.

The adoption rate of sensors on dairy farms varies widely. Whereas some sensors are hardly adopted, others are adopted by many farmers. A potential rational explanation for the difference in adoption may be the expected future technological progress in the sensor technology and expected future improved decision support possibilities. For some sensors not much progress can be expected because the technology has already made enormous progress in recent years, whereas for sensors that have only recently been introduced on the market, much progress can be expected. The adoption of sensors may thus be partly explained by uncertainty about the investment decision, in which uncertainty lays in the future performance of the sensors and uncertainty about whether improved informed decision support will become available. The overall aim was to offer a plausible example of why a sensor may not be adopted now. To explain this, the role of uncertainty about technological progress in the investment decision was illustrated for highly adopted sensors (automated estrus detection) and hardly adopted sensors (automated body condition score). This theoretical illustration uses the real options theory, which accounts for the role of uncertainty in the timing of investment decisions. A discrete event model, simulating a farm of 100 dairy cows, was developed to estimate the net present value (NPV) of investing now and investing in 5 yr in both sensor systems. The results show that investing now in automated estrus detection resulted in a higher NPV than investing 5 yr from now, whereas for the automated body condition score postponing the investment resulted in a higher NPV compared with investing now. These results are in line with the observation that farmers postpone investments in sensors. Also, the current high adoption of automated estrus detection sensors can be explained because the NPV of investing now is higher than the NPV of investing in 5 yr. The results confirm that uncertainty about future sensor performance and uncertainty about whether improved decision support will become available play a role in investment decisions.

Effect of dry period length on milk yield over multiple lactations.

Shortening or omitting the dry period (DP) can improve the energy balance of dairy cows in early lactation through a decrease in milk yield after calving. Little is known about the effect of a short or no DP on milk yield over multiple lactations. Our objectives were (1) to assess the effect of DP length over multiple lactations on milk yield, and (2) to assess if the prediction of milk yield in response to DP length could be improved by including individual cow characteristics before calving. Lactation data (2007 to 2015) of 16 Dutch dairy farms that apply no or short DP were used to compute cumulative milk yield in the 60 d before calving (additional yield) and in the 305 d after calving (305-d yield), and the mean daily yield over the interval from 60 d before calving to 60 d before next calving (effective lactation yield). The DP categories were no (0 to 2 wk), short (3 to 5wk), standard (6 to 8 wk), and long (9 to 12 wk). The effect of current DP and previous DP on yields was analyzed with mixed models (n=1,420 lactations). The highest effective lactation yield of fat- and protein-corrected milk (FPCM) was observed for cows with a standard current DP (27.6kg per day); a daily decrease was observed of 0.6kg for a long DP, 1.0kg for a short DP, and 2.0kg for no DP. Previous DP did not significantly affect the effective lactation yield. Thus, cows can be managed with short or no DP over consecutive lactations without a change in quantity of milk losses. Cows that received no DP for consecutive lactations had a lower additional yield before calving (-172kg of FPCM), but a higher 305-d yield (+560kg of FPCM), compared with cows that received no DP for the first time. This could lessen the improvement of the energy balance in early lactation when no DP is applied a second time compared with the first time. For the second objective, a basic model was explored to predict effective lactation yield based on parity, DP length, and first-parity 305-d yield (n=2,866 lactations). The basic model was subsequently extended with data about recent yield, days open, and somatic cell count. Extending the model reduced the error of individual predictions by only 6%. Therefore, the basic model seems sufficient to predict the effect of DP length on effective lactation yield. Other individual cow characteristics can still be relevant, however, to make a practical and tailored decision about DP length.

Assessing the economic impact of an endemic disease: the case of mastitis.

A large part of the world's resources are used to produce animal products. Efficient use of these resources is important to improve social well-being. Endemic animal diseases decrease production efficiency, because they require a higher level of input to produce the same amount of output or result in a lower output with the same amount of input. The optimal level of production with and without disease differs from farm to farm and depends on varying economic circumstances. Given these difficulties, making an accurate theoretical estimation of the economic impact of endemic diseases is challenging. Current approaches towards the economic assessment of endemic diseases are, therefore, quite pragmatic. For on-farm decision-making, the total costs consist of failure costs and preventive costs. Failure costs are associated with production losses (i.e. decreases in milk production, mortality and culling), treatment costs (i.e. veterinary treatment, drugs, and discarded milk) and the use of other resources associated with the occurrence of disease (i.e. increased labour costs). Preventive costs are associated with preventive measures in terms of equipment, consumables (e.g. diagnostics and chemicals) and the use of other resources to prevent diseases (i.e. increased labour). There is a substitution relationship between failure costs and preventive costs. That means that, in order to maximise profit at the farm level, the amount of resources invested in prevention should be chosen in such a way that total costs are minimised. The most studied endemic disease in animal production is mastitis. Most publications on mastitis only assess failure costs, and studies on assessing the total costs and best methods to determine an optimal level of prevention are scarce. Future challenges lie in researching frameworks that can assist decision-makers to establish optimal prevention levels for endemic diseases.

Une grande partie des ressources mondiales est consacrée à la production de produits d'origine animale. Il est important d'utiliser rationnellement ces ressources si l'on veut améliorer le bien-être des sociétés. Les maladies animales endémiques réduisent la rentabilité des élevages car en cas de maladie il faut plus d'intrants pour maintenir le niveau de production, tandis que celui-ci décroît si la quantité d'intrants demeure inchangée. Le niveau optimal de production avec ou sans maladie varie d'une exploitation à l'autre et dépend du contexte et des fluctuations économiques. Ces facteurs complexes expliquent la difficulté de réaliser une estimation théorique exacte de l'impact économique des maladies endémiques. En conséquence, les approches actuelles en matière d'évaluation économique des maladies animales privilégient le pragmatisme. Au niveau décisionnel des élevages, les coûts totaux englobent les pertes d'exploitation et les coûts de la prévention. Les pertes d'exploitation sont liées aux pertes de production (baisse de la production de lait, mortalité et animaux sacrifiés), au coût des traitements (prestations vétérinaires, médicaments, perte de lait en raison des traitements) et à l'utilisation d'autres ressources en lien avec l'apparition de la maladie (augmentation des coûts de main-d'oeuvre). Les coûts de prévention sont liés aux mesures de prévention et couvrent les équipements, les consommables (les réactifs et matériels de diagnostic et les produits chimiques) et l'utilisation d'autres ressources pour prévenir les maladies (augmentation des coûts de maind'oeuvre). Les pertes d'exploitation et les coûts de prévention sont mutuellement substituables. Ainsi, pour optimiser la rentabilité à l'échelle de la ferme, il conviendra de choisir le montant des ressources investies dans la prévention de manière à minimiser les coûts totaux. La mammite est la maladie endémique la plus étudiée en production animale. La plupart des publications sur la mammite évaluent uniquement les coûts de perte d'exploitation, peu d'études ayant été consacrées à l'évaluation des coûts totaux ou aux méthodes permettant de déterminer le niveau optimal de la prévention. Les défis futurs consisteront à élaborer des cadres permettant d'aider les décideurs à déterminer les niveaux optimaux de la prévention des maladies endémiques.

Buena parte de los recursos del mundo se destinan a la obtención de productos de origen animal. Para alcanzar mayores cotas de bienestar social es importante pues utilizar esos recursos de modo eficiente. Las enfermedades animales endémicas merman la eficiencia productiva porque exigen una mayor cantidad de insumos para obtener el mismo nivel de producción o, alternativamente, reducen la producción obtenida por una misma cantidad de insumos. El nivel óptimo de producción, en presencia y en ausencia de enfermedades, difiere de una explotación a otra y depende de parámetros económicos que son variables. Estas dificultades explican por qué resulta tan arduo hacer una estimación teórica precisa del impacto económico de enfermedades endémicas. De ahí que los métodos actuales para evaluar en clave económica las enfermedades endémicas revistan un carácter bastante empírico. En lo que concierne a las decisiones adoptadas en el ámbito de la explotación, el costo total está formado por las pérdidas de explotación y los costos de prevención. Las pérdidas de explotación vienen determinadas por las pérdidas productivas (menor producción de leche, mortalidad y animales sacrificados), el costo de los tratamientos (servicios veterinarios, medicamentos y leche desechada a consecuencia del tratamiento) y el uso de otros recursos ligados a la aparición de la enfermedad (mayores costes laborales). Los costos de prevención, que son aquellos vinculados a las medidas profilácticas, corresponden al equipo empleado, los bienes consumibles (como productos químicos o de diagnóstico) y la utilización de otros recursos para prevenir enfermedades (mayores costes laborales). Existe una relación de sustitución entre las pérdidas de explotación y los costos de prevención. Ello significa que, para que una explotación rinda el máximo beneficio, conviene fijar la cantidad de recursos invertidos en prevención de tal manera que ello reduzca al mínimo los costos totales. La enfermedad endémica más estudiada en producción animal es la mastitis. En la mayoría de las publicaciones que se le han dedicado solo se evalúan las pérdidas de explotación, y en cambio escasean los estudios encaminados a evaluar los costos totales o a definir el mejor método para determinar el nivel óptimo de prevención. De cara al futuro, se trata de buscar modelos que puedan ayudar a las instancias decisorias a fijar los niveles óptimos de prevención de enfermedades endémicas.

A prognostic model to predict the success of artificial insemination in dairy cows based on readily available data.

A prognosis of the likelihood of insemination success is valuable information for the decision to start inseminating a cow. This decision is important for the reproduction management of dairy farms. The aim of this study was to develop a prognostic model for the likelihood of successful first insemination. The parameters considered for the model are readily available on farm at the time a farmer makes breeding decisions. In the first step, variables are selected for the prognostic model that have prognostic value for the likelihood of a successful first insemination. In the second step, farm effects on the likelihood of a successful insemination are quantified and the prognostic model is cross-validated. Logistic regression with a random effect for farm was used to develop the prognostic model. Insemination and test-day milk production data from 2,000 commercial Dutch dairy farms were obtained, and 190,541 first inseminations from this data set were used for model selection. The following variables were used in the selection process: parity, days in milk, days to peak production, production level relative to herd mates, milk yield, breed of the cow, insemination season and calving season, log of the ratio of fat to protein content, and body condition score at insemination. Variables were selected in a forward selection and backward elimination, based on the Akaike information criterion. The variables that contributed most to the model were random farm effect, relative production factor, and milk yield at insemination. The parameters were estimated in a bootstrap analysis and a cross-validation was conducted within this bootstrap analysis. The parameter estimates for body condition score at insemination varied most, indicating that this effect varied most among Dutch dairy farms. The cross-validation showed that the prognosis of insemination success closely resembled the mean insemination success observed in the data set. Insemination success depends on physiological conditions of the cow, which are approximated indirectly by production and reproduction data that are routinely recorded on the farm. The model cannot be used as a detection model to distinguish cows that conceive from cows that do not. The model validation indicates, however, that routinely collected farm data and test-day milk yield records have value for the prognosis of insemination success in dairy cows.