Projects per year
Dairy products are important food sources which contain nutrients that are essential for human development and healthy ageing. Greenhouse gasses are formed during the production of dairy of which methane (CH4) emission by dairy cows is the single largest source. A reduction in CH4 emission could be achieved via selective breeding, though this requires genetic variation in CH4 emission. In order to quantify the genetic variation in CH4 emission, 3 different indicators were used. The first indicator was CH4 emission predicted based on milk fatty acids (FA) which were measured using gas chromatography. Different FA based CH4 prediction equations were used and 12 to 44% of the variation was due to genetic differences between cows. The second indicator was CH4 emission measured with breath sensors. The breath of cows was analysed during milking in automatic milking systems. Genetics explained 3 to 12% of the total variation in this CH4 indicator. The third indicator was CH4 emission predicted based on milk mid-infrared (MIR) spectra. Of this indicator, between 17 and 21% of the total variation could be attributed to genetic factors. These results suggest that there is genetic variation in CH4 emission and selective breeding for lower CH4 emission is possible. The correlations between sensor measured CH4 emission and milk MIR predicted CH4 emission were low, indicating that both indicators explain a different part of the variation in true CH4 emission. The accuracy of the estimated breeding values (EBV) of these CH4 indicators confirms this suggestion. Combining information from sensor measured CH4 emission with milk MIR predicted CH4 emission increases the accuracy of the EBV compared to using them separately. Correlations of sensor measured CH4 emission and milk MIR predicted CH4 emission with breeding goal traits (production and fertility traits) were low to medium. Genetic correlations between CH4 emission and production traits ranged between -0.61 and 0.65, and genetic correlations between CH4 emission and fertility traits ranged between -0.32 and 0.38. These results suggest that inclusion of CH4 emission in the breeding goal has a minor impact on the breeding goal traits studied. These correlations, however, are estimated on relatively small datasets. Increasing the amount of data by using EBV, correlations between the EBV of the CH4 indicators and the EBV of six breeding goal traits were also low to medium. In conclusion, there is a possibility to use selective breeding to reduce CH4 emission by dairy cows with an anticipated minor impact on other breeding goal traits.
|Qualification||Doctor of Philosophy|
|Award date||28 Mar 2018|
|Place of Publication||Wageningen|
|Publication status||Published - 2018|