PhD defence

Predicting methane emission of dairy cows using milk composition

Enteric methane is produced as a result of microbial fermentation of feed components in the gastrointestinal tract of ruminant livestock. Methane represents not only a greenhouse gas contributing to global warming, but also an energy loss. Therefore, enteric methane production is among the main targets of greenhouse gas mitigation practices in the dairy industry. The overall aim of this PhD research was to develop an indicator for methane emission that can be measured in milk of dairy cows to enable large scale methane measurements in practice.

The results indicate that milk fatty acids and infrared spectra, but not volatile and non-volatile metabolites, have the ability as an indicator of methane emission of dairy cows. Infrared spectra have a greater potential for practical implementation than milk fatty acids, because infrared spectra are currently already used in milk recording systems. Milk fatty acids, however, have a higher prediction accuracy than infrared spectra, but their lack of robustness remains a concern. The best indicator for methane emission of dairy cows is a combination of milk fatty acids with other characteristics, such as milk yield or lactation stage.