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Dairy cows face many kinds of environmental challenges throughout their life, such as pathogens, sudden changes in feed quality, or heat waves. Resilient cows are cows that can cope well with such challenges – they are minimally affected and recover quickly. Having resilient cows is beneficial for both the cows themselves and farmers. We investigated if newly developed traits, based on daily milk yield can be used to genetically select for improved resilience. Cows change their milk yield in response to challenges. The hypothesis was, therefore, that daily patterns in milk yield can indicate resilience. Breeding for low variability in milk yield and for low autocorrelation, i.e. dependency between day-to-day deviations in milk yield, can help to improve resilience. Genetic improvement of resilience will likely improve welfare and profitability of cows, and improve job satisfaction of farmers.

Sub-optimal mobility in dairy cows can be broadly defined as abnormal gait which causes a deviation from the optimal walking pattern of a cow. Sub-optimal mobility is also associated with significant economic and environmental consequences, which have yet to be extensively researched or quantified in pasture-based systems. However, to quantify sub-optimal mobility in terms of its impacts economically and environmentally, and indeed to aid in the development of automated detection sensors for sub-optimal mobility, a clear understanding of the characteristics of a cow with sub-optimal mobility is required. So far, automated detection sensors have been successful for detecting moderate to severe forms of sub-optimal mobility. However, there is a need for a better understanding of the cow-level traits associated with all forms of sub-optimal mobility, including mild forms, to incorporate this into future development of automated detection sensors for sub-optimal mobility. Therefore, the aim of our study was to determine the associations between hoof disorders (both type and presence), body condition score, and all levels of sub-optimal mobility in pasture-based dairy cows using data from a large sample of Irish dairy farms. Mobility scores, body condition scores (BCS), claw disorder (presence and severity), and parity records were available for 6,927 dairy cows from 52 pasture-based herds. Binomial logistic regression analysis was completed to determine the associations between claw disorder (presence and severity), BCS, parity and sub-optimal mobility. The output variable was sub-optimal mobility (mobility score ≥ 1) and the predictor variables were specific claw disorders and their severities, BCS, and parity. Our results indicate that all severities of claw disorders, low BCS, and higher parity cows are all associated with an increased risk for sub-optimal mobility.

Shortening the dry period (DP) has been proposed as a management strategy to improve energy balance in early lactation. It is well known that both shortening and complete omission of the DP reduces milk production in the subsequent lactations. In most of these studies milk production data were obtained from planned animal experiments where cows were randomly assigned to DP length treatments, and cow management and diet composition did not differ among treatments. It may therefore be hypothesized that cows on commercial herds which apply a no-DP or short-DP-strategy, and support this by management adjustments, will have a less dramatic reduction in milk production. In this study, milk production and somatic cell count (SCC) following different DP lengths was investigated under commercial circumstances. Milk production of 342 cows (2,077 test-day records) was available from 5 Dutch commercial dairy herds which started a no DP-strategy for all cows. Test days of the year before applying the no-DP strategy are used as control (323 cows, 1,717 test-day records). Six other herds applied an individual cow approach and have different preplanned DP lengths within one herd. From these herds, information on 81 cows (482 test-day records) with a DP length between 0 and 20 d, 127 cows (925 test-day records) with a DP length between 21 and 35 d, and 143 cows (1,075 test-day records) with a DP length of more than 35 d was available. A generalized linear model incorporating an autoregressive covariance structure accounting for repeated test-day yields within cow was developed to estimate the daily yield (milk, fat and protein) and SCC of all cows. Applying no DP for all cows in the herd resulted in a reduction in postpartum milk production compared with within-herd control lactations (until 305 DIM) between 3.2 and 9.1 kg/d, which was a reduction of 12 and 32%, respectively. For the 6 herds that applied an individual cow approach with different preplanned DP lengths, the cow-specific DP strategy was based on milk production and SCC approximately 2 mo before calving. Cows with a preplanned DP length ranging between 0 and 20 d had a reduction in postpartum milk production between 5.7 and 13 kg/d compared with cows with a DP length of >35 d. Cows with a preplanned DP length ranging from 21 to 35 d had a numerically lower milk production (between 0.6 and 5.3 kg/d) than cows with a preplanned DP length of >35 d, but this difference was significant in only one herd. When corrected for milk yield, no difference in postpartum SCC for cows with different DP lengths was found.

The aim of this study was to assess farmers’ preferences for the performance characteristics of mastitis detection systems. Additionally, we looked at whether certain groups of farmers could be distinguished with specific preferences. Farmers’ opinions concerning mastitis detection systems, as well as general information about the farm and the farmer, were investigated with a standard questionnaire. The second part of the questionnaire was specifically aimed at elucidating preferences. Definitions of time windows and performance parameters, such as sensitivity and specificity, were incorporated into characteristics of a detection system (attributes) that reflect farmers’ daily experience. Based on data from 139 farmers, we concluded that, on average, they prefer a clinical mastitis detection system that produces a low number of false alerts, while alerting in good time and with emphasis on the more severe cases. These 3 attributes were evaluated as more important than the 3 other attributes, representing the costs of the detection system, the number of missed cases, and how long before clinical signs alerts need to be given. Variation in importance per attribute, however, was high, denoting that farmers’ preferences differ considerably. Although some significant relationships were found between farm characteristics and attributes, no clear groups of farmers with specific preferences could be distinguished. Based on these results, we advise making detection systems adaptable for the farmers to satisfy their preferences and to match the circumstances on the farm. Furthermore, these results support that for evaluation of detection algorithms comparisons have to be made at high levels of specificity (e.g., 99%) and time windows have to be kept small (preferably no more than 24 h). Key words: adaptive conjoint analysis, automatic milking system, farmer preference, mastitis detection

Er is veel discussie over de varkenshouderij en zorgen over deze vorm van dierhouderij groeien wereldwijd. Ten gevolge van deze zorgen, worden aanpassingen aangebracht in de varkenshouderij. De aanpassingen worden meestal door wetenschappers in samenwerking met varkenshouders ontwikkeld. Echter, varkenshouders en burgers hebben een verschillend beeld over de varkenshouderij. Daardoor kan er onbegrip ontstaan tussen deze stakeholdergroepen wanneer aanpassingen in de varkenshouderij worden ingevoerd. Het is namelijk de vraag in hoeverre de aanpassingen tegemoet komen aan de zorgen van de burgers. Om aan de zorgen van burgers tegemoet te kunnen komen moet eerst duidelijk worden wat deze zorgen zijn. Ook de zorgen van varkenshouders dienen vastgesteld te worden, zodat aanpassingen ingevoerd kunnen worden met zowel draagvlak binnen de varkenshouderijsector als onder de burgers. Zorgen over de varkenshouderij worden gevormd op basis van het beeld dat mensen hebben over deze vorm van dierhouderij. Dit beeld wordt mede bepaald door basiswaarden en kan afhankelijk zijn van de context. Basiswaarden zijn morele waarden die mensen gedurende hun leven ontwikkelen. Het doel van dit onderzoek was om in Nederland bij verschillende stakeholdergroepen (burgers, varkenshouders, varkensdierenartsen en erfbetreders van varkenshouderijen) te inventariseren wat hun persoonlijke basiswaarden zijn en welk beeld men heeft over de varkenshouderij. Aan de hand van dat beeld kan beoordeeld worden wat men van verschillende aspecten van de varkenshouderij, met betrekking tot mens, dier en omgeving vindt. Daarmee wordt duidelijk waarop zorgen over de varkenshouderij zijn gebaseerd. Ook werd onderzocht of basiswaarden kunnen voorspellen welke beeldvorming mensen hebben ten aanzien van verschillende aspecten van de varkenshouderij.

Dairy farming in western countries with cubicle housing is an efficient way of dairy farming. Though, a disadvantage is the high prevalence and incidence of foot disorders (clinical and subclinical), which cause high economic losses and also seriously impair the welfare of dairy cattle. To point out the importance of reducing the amount and severity of foot disorders, advice to farmers should include information about the scale of the problem and the consequences in terms of economics and animal welfare. To provide support in making decisions on implementing intervention measures, insight into costs and benefits of different measures should be available. The objective of this study, therefore, is to provide more insight into the costs and benefits, for farmer and cow, of different intervention measures to improve dairy cow foot health. Intervention measures were modeled when they were applicable on a dairy farm with cubicle housing and when sufficient information was available in literature. Net costs were calculated as the difference between the costs of the measure and the economic benefits resulting from the measure. Welfare benefits were calculated as well. Cost-effective measures are: improving lying surface (mattress and bedding, €7 and €1/cow per year, respectively), reducing stocking density (break even) and performing additional foot trimming (€1/cow per year). Simultaneously, these measures have a relative high welfare benefit. Labor costs play an important role in the cost-effectiveness of labor-intensive measures. More insight into cost-effectiveness and welfare benefits of intervention measures can help to prioritize when choosing between intervention measures.

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

When cows are milked with an automatic milking system (AMS), clinical mastitis (CM) cannot be detected adequately without using electronic sensing devices. This paper describes approaches to improve automated CM detection in AMS using sensor inputs and data mining. Sensor data and observational CM data, both at quarter level, were collected over two years at nine Dutch AMS farms. Decision-tree induction was used for model development using data from cows that were highly likely to be healthy or that were clearly suffering from CM. The model was validated including quarter milkings with a less clear CM status. A decision-tree was developed with sensitivity of 40% and specificity of 99% using a strict time-window (

The aim of this study was to explore whether, during automatic milking, milking interval or its variation is related to somatic cell count (SCC), even when corrected for effects of production, lactation stage, and parity. Data on milking interval and production level were available from the automatic milking systems of 151 farms. Data on SCC, parity, and lactation stage were derived from dairy herd improvement records of the same farms. Mainly due to incomplete records, data of 100 farms were used in the final analysis. For every cow, only 1 test day was used in the final analysis. Milking interval, the coefficient of variation of milking interval, production rate, the difference in production rate between short- and long-term, parity, days in milk, and some biologically relevant interactions were used in a linear mixed model with farm as random variable to assess their association with log10-transformed SCC. None of the interactions was significantly related to SCC, whereas all main effects were, and thus, stayed in the final model. The effect of milking interval was, although significant, not very strong, which shows that the effect of milking interval on SCC is marginal when corrected for the other variables. The variation in milking intervals was positively related with SCC, showing that the variation in milking interval is even more important than the milking interval itself. In the end, this study showed only a limited association between milking interval and SCC when milking with an automatic milking system.

Our objective was to use data mining to develop and validate a detection model for clinical mastitis (CM) using sensor data collected at nine Dutch dairy herds milking automatically. Sensor data was available for almost 3.5 million quarter milkings (QM) from 1,109 cows; 348 QM with CM were observed by the participating farmers. Data was divided into a training and a test set, stratified at the cow level. For model building, QM with CM (n = 243) from the training set were taken together with 24,987 QM with a somatic cell count less than 200,000 cells/ml on a milk production test day from cows that never exceeded this threshold during all test days within parity and that were never visually checked by the farmers for CM. The model used decision tree (DT) induction as base classifier, with and without bagging and boosting techniques. Both bagging and boosting techniques work by building models using the base classifier on various samples of the training data. For validation two test sets were created. The first included 105 QM with CM and 13,313 QM without CM, using the same selection as for the training. This test set (Test_GreyOut) excluded the large pool of QM that have a less clear mastitis status. The second test set included the same 105 QM with CM but this dataset included QM with a less clear mastitis status (Test_GreyIn): for negative examples, those QM that were not scored as having CM by the farmers were labeled as negative for CM. From this large sample (n = 1,146,544), a random sample of 50,000 QM was selected. Sensitivity levels were computed at fixed SP levels, and the transformed partial area under the curve (pAUC) was calculated for specificity values of 97% or more to evaluate performance. To visualize performance of the detection models for specificity values of 97% or more, receiver operating characteristic (ROC) curves were constructed. When using the Test_GreyOut set, the transformed pAUC increased from 0.713 when using the base classifier alone, to 0.787 when combined with boosting, to 0.800 when combined with bagging. At a specificity of 99%, sensitivity was 43.5% for the base classifier, 60.0% when combined with boosting and 61% when combined with bagging. When testing on the TestInGrey set, pAUC values were lower, but still increased when bagging and boosting techniques were used: values increased from 0.643 when using the base classifier alone, to 0.677 when combined with boosting, to 0.702 when combined with bagging. At a specificity of 99%, sensitivity was 24.7% for the base classifier, 30.5% when combined with boosting and 35.2% when combined with bagging. These results were obtained using very narrow time-windows. It is therefore concluded that models developed by DT induction are promising for future implementation

Niet direct zichtbare kosten als melkproductieverliezen en verlengde tussenkalftijd blijken bij klauwaandoeningen grote kostenposten. Mortellaro kost de Nederlandse veehouder jaarlijks het meest. Dat blijkt uit de eerste resultaten van promotieonderzoek van Mariëlle Bruijnis aan Wageningen Universiteit.

Mastitis kost geld. Maar hoeveel? Beduidend meer dan melkveehouders denken, zo blijkt uit recent onderzoek van het Uiergezondheidscentrum Nederland en de faculteit Diergeneeskunde onder 64 veehouders. Vooral het productieverlies bij subklinische mastitis kost veel euro’s

Treatment of subclinical mastitis is traditionally no common practice. However, some veterinarians regard treatment of some types of subclinical mastitis to be effective. The goal of this research was to develop a stochastic Monte Carlo simulation model to support decisions around treatment of chronic subclinical mastitis caused by Streptococcus uberis. Factors in the model include, amongst others, the probability of spontaneous cure, probability of the cow becoming clinically diseased, transmission of infection to other cows, cure rate under treatment and physiological effects of the infection. The average economic damage (with basic input parameters for the Dutch circumstances) of an untreated chronic subclinical mastitis case caused by S. uberis is € 88. With a short (3 day) treatment, the average damage was higher. For the average cow, treatment is not economical efficient. Sensitivity analysis showed that this might depend on some specific cow and farm factors. Moreover, the spread of economic damage indicates that the risk of a high damage is much higher when a cow with chronic subclinical mastitis is not treated

De EU heeft in de verordening 21/2004 vastgesteld dat per 1 januari 2008 schapen en geiten individueel moeten worden geregistreerd in een bedrijfsregister en op vervoersdocumenten en dat dit dient te worden ondersteund door elektronische identificatie. Voor mogelijke implementatie van de EU-verordening 21/2004 is via veldwerk onderzocht of het technisch en praktisch haalbaar is om bij schapen en geiten met elektronische identificatie en registratie te gaan werken. Tevens is met modelleerwerk, (spel)simulatie en expertsessies naar de betrouwbaarheid en de kosten-baten gekeken van 2 alternatieve registratiesystematieken: CIR en CAR

Slepende melkziekte veroorzaakt productieverlies en verminderde vruchtbaarheid. Onderzoekers van Wageningen UR en de faculteit Diergeneeskunde bogen zich over de vraag hoeveel dat kost

In dit rapport wordt een kosten-batenanalyse gepresenteerd van de invoering van elektronische identificatie van schapen en geiten. In de analyse worden effecten vertaald in monetaire termen voor sectoren en subsectoren. Kosten worden onder meer gevormd door extra registratie- en meldapparatuur en de identificatiemiddelen zelf: oormerken of bolussen. Baten komen voort uit besparing van arbeid, maar ook uit risicoreductie bij dierziektenuitbraak en exportbeperkingen. Niet alle baten zijn overigens op grond van de huidige beschikbare informatie nauwkeurig in beeld te brengen. De algemene conclusie is, dat de kosten de berekenbare baten overtreffen met een bedrag in de orde van ¿ 3,5 miljoen op jaarbasis. De baten uit risicoreductie en het vermijden van exportbeperkingen worden daarnaast indicatief geraamd op enkele miljoenen euro per jaar.

In this study, direct economic losses due to Neospora caninum infection, based on actual data from N. caninum seropositive reference herds and from herds that experienced an N. caninum- associated abortion epidemic, were calculated using a stochastic model with random elements. The results demonstrated that 76% of seropositive reference herds had no economic losses, whereas in the remaining 24% of herds, the economic losses went up to maximally Euro 2000 per year. In epidemic abortion herds, economic losses continued after the actual event of the abortion epidemic for at least two more years with average costs of Euro 50 per animal per 2 years. In both herd situations, highest losses were related to premature culling of seropositive cows and to a lesser extent to the effects of abortion (extended calving interval and age of first calving).

Wageningen UR en Alfa Accountants en Adviseurs analyseerden de resultaten van ruim 60 melkveebedrijven om meer inzicht te krijgen in het rendement van automatisch melken

Waarom kiezen sommige melkveehouders voor een robot en anderen voor een melkstal? Wageningse onderzoekers vroegen veehouders naar hun motivatie. voor de aanschaf van een melkrobot luiden die anders dan voor een melkstal