Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 532610
Title Genetic background of methane emission by Dutch Holstein Friesian cows measured with infrared sensors in automatic milking systems
Author(s) Engelen, S. van; Bovenhuis, H.; Tol, P.P.J. van der; Visker, M.H.P.W.
Source Journal of Dairy Science 101 (2018)3. - ISSN 0022-0302 - p. 2226 - 2234.
DOI https://doi.org/10.3168/jds.2017-13441
Department(s) Animal Breeding and Genetics
WIAS
Publication type Refereed Article in a scientific journal
Publication year 2018
Availibility Full text available from 2019-03-01
Keyword(s) AMS - Dairy cow - Methane emission - Nondispersive infrared sensor
Abstract International environmental agreements have led to the need to reduce methane emission by dairy cows. Reduction could be achieved through selective breeding. The aim of this study was to quantify the genetic variation of methane emission by Dutch Holstein Friesian cows measured using infrared sensors installed in automatic milking systems (AMS). Measurements of CH4 and CO2 on 1508 Dutch Holstein Friesian cows located on 11 commercial dairy farms were available. Phenotypes per AMS visit were the mean of CH4, mean of CO2, mean of CH4 divided by mean of CO2, and their log10-transformations. The repeatabilities of the log10-transformated methane phenotypes were 0.27 for CH4, 0.31 for CO2, and 0.14 for the ratio. The log10-transformated heritabilities of these phenotypes were 0.11 for CH4, 0.12 for CO2, and 0.03 for the ratio. These results indicate that measurements taken using infrared sensors in AMS are repeatable and heritable and, thus, could be used for selection for lower CH4 emission. Furthermore, it is important to account for farm, AMS, day of measurement, time of day, and lactation stage when estimating genetic parameters for methane phenotypes. Selection based on log10-transformated CH4 instead of the ratio would be expected to give a greater reduction of CH4 emission by dairy cows.
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