Publikationsdatenbank

Benchmarking calf health:
assessment tools for dairy herd health consultancy based on reference values from 730 German dairies with respect to seasonal, farm type, and herd size effects (2022)

Art

Zeitschriftenartikel / wissenschaftlicher Beitrag

Autoren

Dachrodt, Linda

Bartel, Alexander (WE 16)

Arndt, Heidi

Kellermann, Laura Maria

Stock, Annegret (WE 18)

Volkmann, Maria (WE 16)

Boeker, Andreas Robert

Birnstiel, Katrin

Do Duc, Phuong

Klawitter, Marcus (WE 18)

Paul, Philip

Stoll, Alexander

Woudstra, Svenja

Knubben-Schweizer, Gabriela

Müller, Kerstin Elisabeth (WE 18)

Hoedemaker, Martina

Quelle

Frontiers in veterinary science : FVETS

Bandzählung: 9

Seiten: Artikel 990798

ISSN: 2297-1769

Sprache

Englisch

Verweise

URL (Volltext): https://www.frontiersin.org/articles/10.3389/fvets.2022.990798/full

DOI: 10.3389/fvets.2022.990798

Pubmed: 36213417

Kontakt

Institut für Veterinär-Epidemiologie und Biometrie

Königsweg 67
14163 Berlin
+49 30 838 56034
epi@vetmed.fu-berlin.de

Abstract / Zusammenfassung

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).