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Genetics of mastitis in the Walloon Region of Belgium

Authors
  • Bastin, Catherine
  • Vandenplas, Jérémie
  • Laine, Aurélie
  • Gengler, Nicolas
Publication Date
Aug 01, 2013
Source
ORBi
Keywords
Language
English
License
Unknown
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Abstract

The objective of this study was to estimate genetic parameters of mastitis traits for Walloon dairy covw Data included a total of 4,489 lactations from 3,277 cows in 38 herds. The following mastitis traits wer investigated: mastitis as a binary trait based on whether or not the cow had at least 1 mastitis case either fror 10 days before calving till 365 days after calving (MAS) or from 10 days before calving till 50 days afte calving (MAS50) or from 50 days after calving till 365 days after calving (MAS365). The number of mastiti cases from 10 days before calving till 365 days after calving (NMAS) was also studied. The frequency wa 22 % for MAS , 10 % for MAS50 , and 15 % for MAS365 . Variance components were estimated by Gibb sampling using a 4-trait threshold mixed model that combined binary (i.e. MAS, MAS50, and MAS365 and continuous (i.e. NMAS) traits. The model included herd, year x season of calving, and age at calvin lactation as fixed effects and genetic and permanent environment as random effects. Heritability was 0.0 (+0.03) for MAS, 0.09 (+0.04) for MAS50, 0.08 (0.03) for MAS365, and 0.05 (+0.02) for NMAS. Geneti correlations were 0.78 between MAS and MAS50, 0.88 between MAS and MAS365, 0.99 between MAS an NMAS, 0.44 between MAS50 and MAS365, 0.86 between MAS50 and NMAS, and 0.83 between MAS36 and NMAS. Standard error of correlation estimates ranged from o.01 to 0.25. Genetic parameters fro this study were in line with the literature. Further studies will investigate the genetic correlations betwee mastitis traits and somatic cell score and other production traits. This research is a part of a larger proje which aims to develop selection tools to allow dairy farmers to prevent mastitis in their herd traits and somatie cell score and other production traits. This research is a part of a larger project wich aims to develop selection tools to allow dairy farmers to prevent mastitis in their herd.

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