Antimicrobial resistance necessitates more judicious antimicrobial use, including in dairy production where mastitis remains the primary driver of antibiotic consumption. Selective treatment of nonsevere clinical mastitis (STCM) requires rapid differentiation between gram-positive and gram-negative pathogens, as only gram-positive infections generally benefit from antimicrobial therapy. Because conventional laboratory culture is too slow for STCM, rapid testing systems for pathogen detection in milk are used on farm (performed and analyzed by farm personnel) or on practice (performed and analyzed at the veterinary practice). This study evaluated the diagnostic performance of 2 culture-based rapid tests (MicroMast and VetoRapid) via an on-practice culture approach as part of a clinical trial, with standard laboratory bacteriology as the gold standard. The performance to distinguish (1) gram-positive from gram-negative bacteria and (2) further pathogen identification was assessed by determining sensitivity, specificity, positive predictive values, negative predictive values, accuracy, and Cohen's kappa values. Both tests (VetoRapid more than MicroMast) reliably distinguished gram-positive from gram-negative pathogens, supporting their use in STCM decision-making. However, their ability to identify specific pathogens was limited, restricting their suitability for broader udder health management decisions.

Background Changing legislation regarding antimicrobial consumption (AMC) forces Flemish bovine veterinary practitioners (BVP) to rethink their business models and shift their on-farm practices from curative to preventive. However, little is known about their current practices and opinions regarding antibiotic stewardship, mastitis treatment and bacteriological culturing (BC) of milk samples, or how they envision their current and future roles on dairy farms.Methods An online questionnaire including 58 questions regarding demographics, udder health monitoring services (UHMS) and opinion on AMC, antimicrobial resistance (AMR) and BC of milk was distributed among BVP. Responses were categorised by age, sex and years in practice and statistically compared.Results Forty BVP completed the questionnaire. Although 37 BVP (92.5%) hold great value to their UHMS, we demonstrate room for improvement in the visit frequency and content. Younger and early career BVP tend to be more aware of AMC, AMR and BC of milk.Limitations Due to the limited participation rate, caution is required when extrapolating the findings of this study.Conclusion Ongoing education and support are needed to tackle challenges and boost BVP' skills and motivation regarding UHMS and AMC in Flanders in order to achieve more evidence-based and preventive practices regarding udder health.

Assessing clinical mastitis (CM) severity plays a crucial role in mastitis control. The current method for assessing CM severity mainly considers clinical symptoms while a comprehensive approach is lacking. This study aims to explore CM severity in different dimensions. We collected data on 129 CM cases detected by automatic milking system (AMS) and confirmed by herdsman from three farms in Belgium (n = 2) and the Netherlands (n = 1). The CM severity was assessed in four dimensions: production (maximum relative milk loss for the inflamed and uninflamed quarters separately), somatic cell count (deviation from cow-level baseline), clinical (mild, moderate, severe clinical symptoms), and pathogen (cultures from the inflamed quarter). We explored the relations between these dimensions and examined the impact of farm, parity, and lactation stage (LS). Our findings revealed that severity dimensions were positively correlated, with correlations from 0.30 to 0.50. The strongest correlation between dimensions occurred between the production dimension in inflamed and uninflamed quarters. Severity in the somatic cell count dimension exhibited the stronger correlation with production severity for uninflamed quarters and pathogen severity compared to other dimensions, and the clinical dimension showed the strongest association with the production dimension for uninflamed quarters. Additionally, farm, parity, and LS were found to influence both the severity within certain dimensions and the interrelationships among them. These results suggest that, although CM severity scores across the four dimensions are positively correlated, clear variations exist. Combining the four scores could help to capture the full scope of CM by simultaneously assessing the severity of cases across these dimensions. Despite potential detection bias in the CM cases, our findings provide an opportunity to develop a novel CM severity scoring system that could optimize treatment decisions and promote sustainability of the dairy sector.

ABSTRACT Staphylococcus chromogenes TA showed significantly lower growth under iron-deprived conditions, and adding an iron supplement (lactoferrin or ferritin) resulted in no improvement in growth; in contrast, growth of S. chromogenes IM was significantly recovered with ferritin iron supplementation. Only Staphylococcus hominis strains originating from quarter milk were able to significantly utilize ferritin as an iron source to reverse the growth inhibition caused by chelating agent 2,2ʹ-bipyridyl in varying degrees. Both S. chromogenes strains (IM and TA) and all S. hominis strains were unable to significantly use lactoferrin as an iron source for growth recovery.

De landbouwsector staat de laatste jaren onder druk wegens het overmatig inzetten van antibiotica. In de melkveehouderij werd het selectief droogzetten reeds geïntroduceerd om deze overmatige antibioticaconsumptie in te dijken. Hoewel selectief droogzetten - naast een geoptimaliseerde mastitispreventie - al een grote stap in de goede richting is, zijn extra maatregelen noodzakelijk en mogelijk. Naast het selectief droogzetten kan ook het selectief behandelen van niet-ernstige klinische mastitisgevallen geïntroduceerd worden. Met deze benadering kan het antibioticumgebruik voor de behandeling van niet-ernstige klinische mastitis tot 50% verminderd worden zonder negatieve consequenties voor de melkproductie en de uiergezondheid, zoals aangetoond in de Verenigde Staten, Nieuw-Zeeland, Duitsland en de Scandinavische landen. Bepalende factoren voor de grootte van deze reductie in antibioticumgebruik zijn (1) het aantal dagen dat de melk niet mee kan geleverd worden, (2) de kostprijs van de gebruikte geneesmiddelen (antibiotica en/of niet-steroïdale anti-inflammatoire geneesmiddelen), (3) de therapieduur, (4) de tijd tussen de diagnose aan de hand van een sneltest en de behandeling, (5) het risico op het besmetten van andere koeien in de kudde, (6) het aandeel van grampositieve kiemen die bijdragen tot mastitis op het bedrijf en (7) de bacteriologische genezing. Net zoals bij het selectief droogzetten, is bij het selectief behandelen voorzichtigheid geboden. Het selectief behandelen zou economisch gezien het meest interessant zijn op bedrijven met een relatief lage prevalentie van klinische uierontstekingen veroorzaakt door grampositieve mastitisverwekkers en met een hoge kans op bacteriologische genezing.

In recent years, the agricultural sector has been under pressure due to the excessive consumption of antimicrobials. In the dairy sector, selective dry cow therapy has been introduced to decrease antibiotic use, next to improved prevention. It is certainly a major step in the right direction; yet, additional measures are necessary and possible. In addition to selective dry cow therapy, selective treatment can also be introduced as a novel treatment approach for non -severe clinical mastitis cases. In the United States, New Zealand, Germany and the Scandinavian countries, such an approach has been shown to reduce antibiotic use for the treatment of clinical mastitis by up to 50%, without negative consequences for milk production nor udder health. Factors that determine the reduction in antibiotic use are (1) the number of days of milk withdrawal, (2) treatment costs (antibiotics and/or NSAID's), (3) treatment duration, (4) delay between diagnosis determined by a rapid test and the start of treatment, (5) risk of spread of infection towards other cows in the herd, (6) proportion of mastitis cases caused by gram -positive bacteria and (7) bacteriological cure. As for selective dry cow therapy, selective treatment should be used with caution. From an economic point of view, selective treatment would be most interesting on farms with a low prevalence of non -severe clinical mastitis cases due to gram -positive bacteria and with a high likelihood of bacteriological cure.

De landbouwsector staat al enige tijd onder druk wat betreft het overtollige gebruik van antibioptica. Daarom wordt in de melkveesector via het selectief droogzetten en het selectief behandelen van niet-ernstige klinische mastitis bijgedragen tot het noodzakelijk reduceren en het meer verantwoord gebruik van antibiotica. Sneltesten voor kiemdetectie in de melk, die – mits een gedegen opleiding, kwaliteitscontrole en een kleine investering – snel en gemakkelijk in te zetten zijn op dierenartsenpraktijken en melkveebedrijven, zijn hiervoor een handige tool aangezien ze als basis kunnen dienen voor het selectief droogzetten en selectief behandelen van niet-ernstige klinische mastitis. Verschillende soorten sneltesten zijn voorhanden, elk met hun eigen specifieke eigenschappen en testkarakteristieken. Sneltesten komen voor onder de vorm van specifieke agars, Petrifilms™, welletjes, microchips en zelfs PCR-testen. Sommige testen bezitten een inherent antibiogram en/of volautomatische aflezing via specifieke software. Er bestaan eenvoudige sneltesten waarbij het resultaat de kiemgroei kan classificeren als polybacterieel, geen groei, groei van een grampositieve kiem of groei van een gramnegatieve kiem. Deze testen volstaan om te beslissen of een koe met niet-ernstige mastitis of bij het droogzetten al dan niet met antibiotica kan behandeld worden. Andere, meer gesofisticeerde testen gaan verder in kiemdifferentiatie tot op genus- of zelfs speciesniveau, wat andere beslissingen met betrekking tot het behandelen en uiergezondheidsmanagement toelaat. Elke geïnteresseerde gebruiker dient na te gaan welke sneltest het beste aansluit bij zijn/haar noden.

Despite the increasing use of automated milking systems (AMS), udder health performance of farms has only been limitedly quantified on farms with a milking robot. The objective of this study was to quantify udder health parameters (UHP) at test-day and at herd level on robotic farms using routinely collected somatic cell counts (SCC) from test-day data, and to study the correlations between these UHP. Additionally, the associations between UHP and season, year and farm size as well as the association between the daily milk production and the herd milk SCC were investigated. To this end, we collected SCC test-day data from 48 Belgian and Dutch farms participating in the milk recording of a local dairy herd improvement program. The UHP were calculated based on individual animal records at each test day over three years (2017 until 2019). These UHP included herd milk SCC, average heifer SCC, average cow SCC, percentage of high SCC, percentage of new high SCC, percentage of chronic high SCC, percentage of high SCC cows after calving, and percentage of recovery during the lactation. By fitting a linear mixed model effect for each of the different UHP, significant associations between the UHP and season, year and farm size were observed at test-day level. A poorer udder health was observed during summer compared to other seasons and generally, larger farms performed worse than smaller farms. Using a linear regression model, a significant negative correlation between herd average SCC and average daily milk production was found: an increase of 6,085 cells/mL was associated with a decrease of one kg of milk production. Finally, the cow-level UHP were averaged over all test days of the entire study period per farm to investigate the farm- level udder health performance and correlations between them. At the farm level, UHP analysis revealed most farms had poor udder health performance (i.e. the herd milk SCC, average heifer SCC, average cow SCC, percentage of new high and chronic high SCC were all higher than their target values) as proposed by Barkema et al. (2013). Both at the farm and at test day level, strong correlations were found among the UHP. Similar to studies on farms with conventional milking systems, a strong correlation between herd milk SCC and the percentage of new and chronic high SCC cows was found. This study gives new insights into udder health performance on farms with an AMS and provides veterinarians and other dairy industry stakeholders with concrete benchmarks for udder health performance on farms.

The agricultural sector has been under pressure regarding the excessive use of antibiotics. In the dairy sector, selective dry cow therapy and selective treatment of non -severe clinical mastitis therefore contribute to the necessary reduction in and more responsible use of antibiotics. Rapid testing of milk samples for bacteriological culture, that - with proper training, quality control and a small investment - can be used quickly and easily at veterinary practices and dairy farms, is a useful tool in this respect as it can serve as a basis for selective dry cow treatment and selective treatment of non -severe clinical mastitis. Different types of rapid tests are available, each with its specific traits and test characteristics. Rapid tests are available as specific agars, PetrifilmsTM, wells, microchips and even as PCR tests. Some of them have an inherent antibiogram and/or fully automatic reading through specific software. Simple tests classify the sample growth as contaminated, no growth, growth of gram -positive or growth of gram -negative bacteria. These tests are sufficient to decide whether or not a cow should be treated with antibiotics when suffering from non -severe clinical mastitis or at dry -off. Other more sophisticated tests allow for differentiation on genus or even species level, facilitating different decisions regarding treatment and udder health management. Every interested user has to determine which rapid test best suits his/her needs.

Although the role of iron in bacterial infections has been well described for Staphylococcus (S.) aureus, iron acquisition in (bovine-associated) non-aureus staphylococci and mammaliicocci (NASM) remains insufficiently mapped. This study aimed at elucidating differences between four diverse bovine NASM field strains from two species, namely S. chromogenes and S. equorum, in regards to iron uptake (with ferritin and lactoferrin as an iron source) and siderophore production (staphyloferrin A and staphyloferrin B) by investigating the relationship between the genetic basis of iron acquisition through whole genome sequencing (WGS) with their observed phenotypic behavior. The four field strains were isolated in a previous study from composite cow milk (CCM) and bulk tank milk (BTM) in a Flemish dairy herd. Additionally, two well-studied S. chromogenes isolates originating from a persistent intramammary infection and from a teat apex were included for comparative purpose in all assays. Significant differences between species and strains were identified. In our phenotypical iron acquisition assay, while lactoferrin had no effect on growth recovery for all strains in iron deficient media, we found that ferritin served as an effective source for growth recovery in iron-deficient media for S. chromogenes CCM and BTM strains. This finding was further corroborated by analyzing potential ferritin iron acquisition genes using whole-genome sequencing data, which showed that all S. chromogenes strains contained hits for all three proposed ferritin reductive pathway genes. Furthermore, a qualitative assay indicated siderophore production by all strains, except for S. equorum. This lack of siderophore production in S. equorum was supported by a quantitative assay, which revealed significantly lower or negligible siderophore amounts compared to S. aureus and S. chromogenes. The WGS analysis showed that all tested strains, except for S. equorum, possessed complete staphyloferrin A (SA)-synthesis and export operons, which likely explains the phenotypic absence of siderophore production in S. equorum strains. While analyzing the staphyloferrin A and staphyloferrin B operon landscapes for all strains, we noticed some differences in the proteins responsible for iron acquisition between different species. However, within strains of the same species, the siderophore-related proteins remained conserved. Our findings contribute valuable insights into the genetic elements associated with bovine NASM pathogenesis.

Staphylococcus chromogenes TA showed significantly lower growth under iron-deprived conditions, and adding an iron supplement (lactoferrin or ferritin) resulted in no improvement in growth; in contrast, growth of S. chromogenes IM was significantly recovered with ferritin iron supplementation. Only Staphylococcus hominis strains originating from quarter milk were able to significantly utilize ferritin as an iron source to reverse the growth inhibition caused by chelating agent 2,2'-bipyridyl in varying degrees. Both S. chromogenes strains (IM and TA) and all S. hominis strains were unable to significantly use lactoferrin as an iron source for growth recovery.

Streptococcus uberis is a major causative agent of bovine mastitis, an inflammation of the mammary gland with substantial economic consequences. To reduce antibiotic use in animal agriculture, alternative strategies to treat or prevent mastitis are being investigated. Bovine-associated non-aureus staphylococci are proposed in that respect due to their capacity to inhibit the in vitro growth of S. uberis. We demonstrate that priming the murine mammary gland with Staphylococcus chromogenes IM reduces S. uberis growth in comparison with non-primed glands. The innate immune system is activated by increasing IL-8 and LCN2, which may explain this decreased growth.

Non-aureus staphylococci and the closely related mammaliicoccal species (NASM) are the most common causes of bovine subclinical mastitis on modern dairy farms and are highly prevalent in bulk-tank milk. The purpose of this study was to determine the distribution of NASM in both composite cow milk (CCM) and bulk-tank milk (BTM) samples collected in tandem in commercial Flemish dairy herds and to estimate the origin of the different (subgroups of) NASM species present in BTM by applying strain typing (random amplification of polymorphic DNA or random amplified DNA [RAPD]). A single cross-sectional sampling was performed over 5 herds that volunteered to participate in the study. Composite cow milk samples (n = 356) were collected from all lactating cows (except those with clinical mastitis) during a milking in tandem with 6 BTM samples per herd sequentially collected immediately post that milking (n = 30). In total, 421 and 80 NASM isolates were recovered and identified by MALDI-TOF mass spectrometry from the CCM and BTM samples, respectively and a total of 21 and 12 different NASM species were identified from CCM and BTM samples, respectively. Staphylococcus cohnii was the most prevalent NASM species found in BTM followed by Staphylococcus haemolyticus, Staphylococcus epidermidis, Mammaliicoccus lentus, and Staphylococcus equorum, whereas from CCM samples the most common species were S. hemolyticus, S. cohnii, S. equorum, S. epidermidis, and Staphylococcus chromogenes. The prevalent NASM species in both CCM and BTM samples was distinct for each herd, corroborating other studies observing a herd-specific NASM microbiota. Random amplified DNA analysis was performed on 9 NASM species (S. chromogenes, S. epidermidis, S. haemolyticus, S. equorum, Mammaliicoccus sciuri, Staphylococcus xylosus, S. cohnii, Staphylococcus debuckii, and M. lentus) because these species were isolated from both sample types in a herd. The same RAPD types were found in both sample types for all NASM species selected for strain typing in varying degrees. When assessing the distribution of NASM species, differences within NASM species should be examined meaning a closer look should be taken at the strain level rather than at the species level only.

The main objective of the study was to evaluate whether or not implementing selective dry cow therapy (SDCT) on commercial dairy farms reduces antimicrobial consumption without negatively affecting future performances when compared to blanket dry cow therapy (BDCT). Twelve commercial herds in the Flemish region of Belgium with overall good udder health management were enrolled in a randomized control trial, including 466 cows that were assigned to a BDCT (n = 244) or SDCT (n = 222) group within herds. Cows in the SDCT group were dried off with internal teat sealants combined or not with long-acting antimicrobials according to a predefined algorithm based on test-day somatic cell count (SCC) data. Total antimicrobial use for udder health between drying off and 100 days in milk was significantly lower in the SDCT group (i.e., a mean of 1.06 defined the course dose) compared to the BDCT group (i.e., a mean of 1.25 defined the course dose), although with substantial variation between herds. Test-day SCC values, milk yield, and the clinical mastitis and culling hazard in the first 100 days in milk did not differ between the BDCT and SDCT groups. SCC-based and algorithm-guided SDCT is suggested to decrease the overall use of antimicrobials without jeopardizing cows' udder health and milk yield.

This study aims to describe the relation between farm-level management factors and estimated farm-level mastitis incidence and milk loss traits (MIMLT) at dairy farms with automated milking systems. In this observational study, 43 commercial dairy farms in Belgium and the Netherlands were included and 148 'management and udder health related variables' were obtained during a farm visit through a farm audit and survey. The MIMLT were estimated from milk yield data. Quarter-level milk yield perturbations that were caused by presumable mastitis cases (PMC) were selected based on quarter-level milk yield and electrical conductivity. On average, 57.6 ± 5.4% of the identified milk yield perturbations complied with our criteria. From these PMC, 3 farm-level MIMLT were calculated over a one-year period around the farm visit date: (1) the 'average number of PMC per cow per year', (2) the 'absolute milk loss per cow per day', calculated as the farm-level sum of all milk losses during PMC in one year, divided by the average number of lactating cows and the number of days, and (3) the 'relative milk loss', calculated as the farm-level sum of milk losses during PMC in one year, divided by the estimated total production in the absence of PMC. The 'average number of PMC per cow per year' was on average 1.81 ± 0.47. The PMC caused an average milk loss of 0.77 ± 0.26 kg per lactating cow per day, which corresponded to an average production loss of 2.38 ± 0.82% of the expected production in the absence of PMC. We performed a principal component regression (PCR) analysis to link the 3 MIMLT to the 'management and udder health related variables', whilst reducing the multicollinearity and the number of dimensions. The first principal component was mainly related to 'milking system brand, maintenance and settings'. The second component mainly linked to average productivity and somatic cell counts, whereas the third component mainly contained variables linked with mastitis management, treatment, and biosecurity. The 3 PCR models had R² ranging from 0.46 (for absolute milk loss per cow per day) to 0.57 (for relative milk loss). For all models, the second PC had the largest effect size. This analysis raises awareness of the impact of management factors on a factual basis and provides handles to take management actions to improve udder health.

Automated milking systems (AMSs) already incorporate a variety of milk monitoring and sensing equipment, but the sensitivity, specificity, and positive predictive value of clinical mastitis (CM) detection remain low. A typical symptom of CM is the presence of clots in the milk during fore-stripping. The objective of this study was the development and evaluation of a deep learning model with image recognition capabilities, specifically a convolutional neural network (NN), capable of detecting such clots on pictures of the milk filter socks of the milking system, after the phase in which the first streams of milk have been discarded. In total, 696 pictures were taken with clots and 586 pictures without. These were randomly divided into 60/20/20 training, validation, and testing datasets, respectively, for the training and validation of the NN. A convolutional NN with residual connections was trained, and the hyperparameters were optimized based on the validation dataset using a genetic algorithm. The integrated gradients were calculated to explain the interpretation of the NN. The accuracy of the NN on the testing dataset was 100%. The integrated gradients showed that the NN identified the clots. Further field validation through integration into AMS is necessary, but the proposed deep learning method is very promising for the inline detection of CM on AMS farms.

Despite the increased use of automatic milking systems in recent years, udder health performance is only limitedly quantified on farms milking with a robot. In the present study we describe various key udder health parameters (UHP) reflecting udder health based on the somatic cell count (SCC) test-day data obtained from milk recording, and studied the correlations between them. Additionally, the association between UHP and season, year and farm size was investigated as well as the association between the daily milk production and the herd milk SCC. The UHP included herd milk SCC, average heifer SCC, average cow SCC, percentage of high SCC, percentage of new high SCC, percentage of chronic high SCC, percentage of high SCC cows after calving, and percentage of recovery during lactation. We collected SCC test-day data from 48 Belgian and Dutch farms participating in the milk recording of a local dairy herd improvement program. The UHP were calculated based on the individual animal records at each test day over a time period of three years (2017 to 2019). Then, the UHP were averaged per farm over all test days of the entire study period to study the farm-level udder health performance and correlations. At test-day level, significant associations of the UHP with season, year and farm size were observed. The UHP differed between seasons and years, and a poorer udder health was observed during summer compared to other seasons. Generally, larger farms performed worse compared to smaller farms. At test-day level, a significant negative association between average SCC and average daily milk production was found: each increase of 6,085 cells/mL was associated with a decrease of one kg of milk production. The farm-level UHP analysis revealed a poor udder health, i.e. the herd milk SCC, average heifer SCC, average cow SCC, percentage of new high and chronic high SCC were all higher than the target value. Both at the farm and at test day level, strong correlations were found among the UHP. Similar to previous studies on conventional farm data, our analyses showed a strong correlation between the herd milk SCC and the percentage of new and chronic high SCC. This study provides new insights into UHP on farms with an automated milking system and will be helpful in tailoring udder health advice.

Also in Belgium, the agricultural sector has been under pressure for quite a while regarding the ex-cessive and insufficiently substantiated use of antibiotics and the link with the development of acquired antibiotic resistance, also in human pathogens. Since 2012, many efforts have been taken by several animal sectors to restrict the excessive use and misuse of antibiotics through recommendations, sensi-bilization, non-statutory measurements and through legislation. Also in the dairy sector, the search towards more prudent use of these important products is on-going, aiming at the rational use of antibiotics as well as a substantial reduction of its use. On an average Flemish dairy farm, sixty to seventy percent of the antibiotic consumption is used to manage udder health. Therefore, improving udder health through optimized management and imple-mentation of prevention measures will immediately lead to a decrease in antibiotic use. A tool to score mastitis management objectively at the herd level is available (www.u-scan.eu), allowing to achieve improved mastitis management and udder health. In addition to a better prevention via an improved mastitis management, selective dry cow treatment is, besides selective treatment of clinical mastitis, an essential step towards a targeted reduction in antibiotic use. Within the concept of selective dry cow treatment, specific parameters (i.e. bacteriological culture, clinical mastitis history, cell count data) are used to identify cows (most likely) having an intramammary infection at dry-off. Only these animals should receive long-acting antibiotics. The non-infected cows are dried off without antibiotics, yet are protected against the development of new intramammary infections with teat sealants, implying a decrease in defined daily doses without or with very few negative long-term effects on udder health and milk production. A prerequisite for implementing selective dry cow treatment is that mastitis ma-nagement on the farm is optimal. In Scandinavian countries and the Netherlands, selective dry cow tre-atment has been the norm for years and it has recently been introduced on Flemish dairy farms. Since the new European Regulation (2019/6) came into effect on the 28th of January 2022, it, theoretically speaking, became the norm. Experiences from the above mentioned countries can help to better unroll this concept in Belgium.

De landbouwsector ligt -ook in België- reeds langere tijd onder vuur met betrekking tot overmatig en onvoldoende onderbouwd antibioticumgebruik en de daaraan gekoppelde link met de ontwikkeling van verworven antibioticumresistentie, ook bij humane pathogenen. Sinds 2012 wordt in verschillende sectoren actie ondernomen om het overmatige en/of het verkeerde gebruik van antibiotica aan banden te leggen via adviezen, sensibilisatie, bovenwettelijke maatregelen en wetgeving. Ook in de melkveesector wordt gezocht naar meer verantwoorde manieren om deze belangrijke geneesmiddelen op een correctere manier in te zetten, om tot een substantiële reductie te komen. Aangezien zestig tot zeventig procent van het antibioticumgebruik op een gemiddeld Vlaams melkveebedrijf ingezet wordt in het kader van uiergezondheid, zal een betere uiergezondheid dankzij een geoptimaliseerd management leiden tot een verminderd antibioticumgebruik. Vandaag bestaan zelfs tools om het mastitismanagement op een bedrijf objectief te scoren, zodoende een betere mastitispreventie en uiergezondheid te bekomen. Ook zijn het selectief droogzetten van koeien en het selectief behandelen van klinische mastitis essentiële elementen om tot een meer verantwoord en verminderd gebruik van antibiotica te komen. Binnen dit concept van selectief droogzetten wordt aan de hand van specifieke parameters (bacteriologisch onderzoek, historiek van klinische mastitis, celgetalgegevens) bepaald welke koeien (hoogstwaarschijnlijk) intramammair geïnfecteerd zijn op het moment van droogzetten. Enkel deze dieren krijgen langwerkende antibiotica toegediend. De niet-geïnfecteerde koeien worden drooggezet zonder antibioticum maar worden wel beschermd tegen nieuwe intramammaire infecties met speenafsluiters. Dit leidt tot een daling van het aantal dierdagdoseringen zonder of met erg beperkte negatieve effecten voor de uiergezondheid en melkproductie op langere termijn. De voorwaarde is wel dat het uiergezondheidsmanagement op het bedrijf op punt staat. Het selectief droogzetten is al enkele jaren de norm in de Scandinavische landen en Nederland en het heeft nu ook zijn intrede gemaakt in de Belgische melkveehouderij. Het werd door de nieuwe Europese Verordening (2019/6), die in voege is sinds 28 januari 2022, theoretisch gezien toch, zelfs de norm. Ervaringen vanuit de vermelde landen kunnen helpen om het concept in België breder toe te passen.