Genetic parameters for predicted methane production and laser methane detector measurements

NK Pickering, MGG Chagunda, G Banos, R Mrode, JC McEwan, E Wall

Research output: Contribution to journalArticle

24 Citations (Scopus)
1 Downloads (Pure)

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 languageEnglish
Pages (from-to)11 - 20
Number of pages10
JournalJournal of Animal Science
Volume93
Issue number1
DOIs
Publication statusFirst published - 2015

Fingerprint

methane production
methane
detectors
lasers
milk yield
body weight
greenhouse gases
energy requirements
genetic improvement
ruminants
dairy cows
feed intake
genomics
cows
breeding

Bibliographical note

1028477
1023320
1023378

Keywords

  • Dairy cattle
  • Genomewide association
  • Genomic selection
  • Heritability
  • Methane

Cite this

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title = "Genetic parameters for predicted methane production and laser methane detector measurements",
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.",
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Genetic parameters for predicted methane production and laser methane detector measurements. / Pickering, NK; Chagunda, MGG; Banos, G; Mrode, R; McEwan, JC; Wall, E.

In: Journal of Animal Science, Vol. 93, No. 1, 2015, p. 11 - 20.

Research output: Contribution to journalArticle

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T1 - Genetic parameters for predicted methane production and laser methane detector measurements

AU - Pickering, NK

AU - Chagunda, MGG

AU - Banos, G

AU - Mrode, R

AU - McEwan, JC

AU - Wall, E

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AB - 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.

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