RESUMO
Good calf health is crucial for a successfully operating farm business and animal welfare on dairy farms. To evaluate calf health on farms and to identify potential problem areas, benchmarking tools can be used by farmers, herd managers, veterinarians, and other advisory persons in the field. However, for calves, benchmarking tools are not yet widely established in practice. This study provides hands-on application for on-farm benchmarking of calf health. Reference values were generated from a large dataset of the "PraeRi" study, including 730 dairy farms with a total of 13,658 examined preweaned dairy calves. At herd level, omphalitis (O, median 15.9%) was the most common disorder, followed by diarrhea (D, 15.4%) and respiratory disease (RD, 2.9%). Abnormal weight bearing (AWB) was rarely detected (median, 0.0%). Calves with symptoms of more than one disorder at the same time (multimorbidity, M) were observed with a prevalence of 2.3%. The enrolled farms varied in herd size, farm operating systems, and management practices and thus represented a wide diversity in dairy farming, enabling a comparison with similar managed farms in Germany and beyond. To ensure comparability of the data in practice, the reference values were calculated for the whole data set, clustered according to farm size (1-40 dairy cows (n = 130), 41-60 dairy cows (n = 99), 61-120 dairy cows (n = 180), 121-240 dairy cows (n = 119) and farms with more than 240 dairy cows (n = 138), farm operating systems (conventional (n = 666), organic (n = 64)) and month of the year of the farm visit. There was a slight tendency for smaller farms to have a lower prevalence of disorders. A statistically significant herd-size effect was detected for RD (p = 0.008) and D (p < 0.001). For practical application of these reference values, tables, diagrams, and an Excel® (Microsoft®) based calf health calculator were developed as tools for on-farm benchmarking (https://doi.org/10.6084/m9.figshare.c.6172753). In addition, this study provides a detailed description of the colostrum, feeding and housing management of preweaned calves in German dairy farms of different herd sizes and farm type (e.g., conventional and organic).
RESUMO
BACKGROUND: In the past years, it became apparent that health status and performance differ considerably within dairy farms in Northern Germany. In order to obtain clues with respect to possible causes of these differences, a case-control study was performed. Case farms, which showed signs of health and performance problems, and control farms, which had none of these signs, were compared. Risk factors from different areas such as health management, housing, hygiene and nutrition were investigated as these are known to be highly influential. The aim of this study was to identify major factors within these areas that have the strongest association with health and performance problems of dairy herds in Northern Germany. RESULTS: In the final model, a lower energy density in the roughage fraction of the diet, more pens with dirty lying areas and a low ratio of cows per watering spaces were associated with a higher risk for herd health problems. Moreover, case farms were affected by infections with intestinal parasites, lungworms, liver flukes and Johne's Disease numerically more often than control farms. Case farms more often had pens with raised cubicles compared to the deep bedded stalls or straw yards found in control farms. In general, the hygiene of the floors and beddings was worse in case farms. Concerning nutrition, the microbiological and sensory quality of the provided silages was often insufficient, even in control farms. Less roughage was provided to early lactating cows and the feed was pushed to the feeding fence less frequently in case farms than in control farms. CONCLUSIONS: The results show that milk yield and health status were associated with various factors from different areas stressing the importance of all aspects of management for good animal health and performance. Moreover, this study confirmed well-known risk factors for health problems and performance losses. These should better be taken heed of in herd health management.
