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Animal. 2014 Feb;8(2):217-23. doi: 10.1017/S1751731113002048. Epub 2013 Nov 14.

Genetic correlations between production and disease traits during first lactation in Holstein cows.

Author information

1
1 NARO Hokkaido Agricultural Research Center, Sapporo 062-8555 Japan.
2
2 Nihon University, Fujisawa 252-8510, Japan.
3
3 Livestock Improvement Association of Japan, Tokyo 135-0041, Japan.
4
4 Hokkaido Dairy Milk Recording and Testing Association, Sapporo 060-0004, Japan.
5
5 Holstein Cattle Association of Japan, Hokkaido Branch, Sapporo 001-8555, Japan.
6
6 Obihiro University of Agriculture and Veterinary Medicine, Obihiro 080-8555, Japan.

Abstract

The aim of this study was to estimate genetic correlations between milk yield, somatic cell score (SCS), mastitis, and claw and leg disorders (CLDs) during first lactation in Holstein cows by using a threshold-linear random regression test-day model. We used daily records of milk, fat and protein yields; somatic cell count (SCC); and mastitis and CLD incidences from 46 771 first-lactation Holstein cows in Hokkaido, Japan, that calved between 2000 and 2009. A threshold animal model for binary records (mastitis and CLDs) and linear animal model for yield traits were applied in our multiple trait analysis. For both liabilities and yield traits, additive genetic effects were used as random regression on cubic Legendre polynomials of days on milk. The highest positive genetic correlations between yields and disease incidences (0.36 for milk and mastitis, 0.56 for fat and mastitis, 0.24 for protein and mastitis, 0.32 for milk and CLD, 0.44 for fat and CLD and 0.31 for protein and CLD) were estimated at about the time of peak milk yield (36 to 65 days in milk). Selection focused on early lactation yield may therefore increase the risk of mastitis and CLDs. The positive genetic correlations of SCS with mastitis or CLD incidence imply that selection to reduce SCS in the early stages of lactation would decrease the incidence of both mastitis and CLD.

PMID:
24230485
DOI:
10.1017/S1751731113002048
[Indexed for MEDLINE]

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