Abstract
Enteric ruminant methane is the most
important greenhouse gas emitted from the pastoral
agricultural systems. Genetic improvement of livestock
provides a cumulative and permanent impact on
performance, and using high-density SNP panels can
increase the speed of improvement for most traits. In
this study, a data set of 1,726 dairy cows, collected
since 1990, was used to calculate a predicted methane
emission (PME) trait from feed and energy intake
and requirements based on milk yield, live weight,
feed intake, and condition score data. Repeated measurements
from laser methane detector (LMD) data
were also available from 57 cows. The estimated
heritabilities for PME, milk yield, DMI, live weight,
condition score, and LMD data were 0.13, 0.25, 0.11,
0.92, 0.38, and 0.05, respectively. There was a high
genetic correlation between DMI and PME. No SNP
reached the Bonferroni significance threshold for the
PME traits. One SNP was within the 3 best SNP for
PME at wk 10, 20, 30, and 40. Genomic prediction
accuracies between dependent variable and molecular
breeding value ranged between 0.26 and 0.30.
These results are encouraging; however, more work
is required before a PME trait can be implemented in
a breeding program.
Original language | English |
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Pages (from-to) | 11 - 20 |
Number of pages | 10 |
Journal | Journal of Animal Science |
Volume | 93 |
Issue number | 1 |
DOIs | |
Publication status | First published - 2015 |
Bibliographical note
10284771023320
1023378
Keywords
- Dairy cattle
- Genomewide association
- Genomic selection
- Heritability
- Methane