Selektives antibiotisches Trockenstellen bei Milchkühen in Rheinland-Pfalz, dem Saarland und Hessen – eine Umfrage unter Landwirten
Bibliographic record
Abstract
OBJECTIVE: With the Regulation (EC) 6/2019, antibiotic drying off of the entire dairy herd is no longer permissible. Hence, it is necessary to establish selective antibiotic drying off (SDCT: Selective Dry Cow Therapy) in dairy herds. With the publication of the PraeRi study in 2020, systematic data for the implementation of SDCT on farms became available for several German states. For Rhineland-Palatinate, Saarland and Hesse this type of information is only available from individual projects. Therefore, the aim of this survey was to increase the knowledge concerning the implementation of SDCT in dairy farms located in these states. MATERIAL AND METHODS: An online questionnaire was sent via newsletters to farmers and was published in the regional farmers' bulletins in the described catchment area. The questionnaire inquired about the saving of antibiotics during drying off, the criteria guiding the farmer's decision (cell count from monthly dairy herd improvement data (DHI), mastitis history, microbiological examination of quarter foremilk samples, California mastitis test), use of teat sealants and the type of dry off procedure (abrupt/gradual). RESULTS: A total of 103 questionnaires were evaluated, making the response rate ~1% for Hesse, ~3% for Saarland, and ~5% for Rhineland-Palatinate based on the number of included farms. Approximately 29% of the farmers dried off one out of four cows, 20% half, 23% three out of four and 13% all cows without using antibiotics. Eighty-nine farm managers based their decision on the somatic cell counts of DHI. Additional criteria influencing the decision were the mastitis history, results of the California Mastitis Test, or a combination of both. In 76 farms cows were dried off abruptly. In 79 farms teat sealers were used. CONCLUSIONS: Application of SDCT is established in most of the farms that participated in the survey, even though the proportion varied between farms. Legal requirements are not the only reason farmers need to increasingly deal with SDCT; sustainability programs of the dairies rely on selective drying off as well. Herd veterinarians should be supportive in implementing these measures to achieve good udder health while reducing the use of antimicrobials to a necessary minimum.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".