Modelling of N excretion from dairy cattle to improve national emission inventories and individual farm assessment
MoMiNE" project
Livestock farming, and dairy cow husbandry in particular, is the most significant cause of nitrogen surpluses in Germany. The most efficient measure to reduce these emissions at the same time is to reduce the nitrogen intake and thus excretion of the animals by optimising the design of feed and feeding with regard to nitrogen requirements. The project "MoMiNE - Modelling the N excretion of dairy cattle to improve national emission inventories and individual farm assessments" investigates potential reductions in feeding, develops practical guidelines and establishes the creditability of these reduction measures by mapping them in the national emission inventory.
In the context of the joint project objectives, the sub-projects of the project partners are organised as follows:
The research focus of the FLI Institute of Animal Nutrition is on nutritional physiology, feed science and animal nutrition. Animal health forms the basis for high-quality food and sustainable animal husbandry. Optimising the feeding of dairy cows to reduce nitrogen emissions is a core aspect, as dairy cows are considered to be the main cause of nitrogen excretion due to their high feed intake and performance. For the MoMiNE project, feeding trials(feeding studies) were carried out as experimental studies on the needs-based supply of crude protein. The aim is to derive optimisation options for operational use.
The work at the LFA Mecklenburg-Vorpommern was divided into two main areas of research. As a first focus, possible health influences on the milk urea content in dairy cows(The milk urea content in focus) were analysed using five different data sets from dairy cow farms and experimental facilities from all regions of Germany from 2014-2023. The focus here was on the effects of metabolic and udder health on milk urea content. Increasing milk urea levels were found in ketotic metabolic states (FEQ > 1.6) and decreasing milk urea levels in high cell counts and acute mastitis. As a second focus, the development of the crude protein efficiency of German dairy cow farms from 2005 to 2023 was analysed to estimate the environmental impact over time. This showed increases in milk yield, milk protein content and herd size, while the number of farms, milk urea content, crude protein content of grass and maize silage and grass silage yields decreased. In addition, the dry matter intake of dairy cows increased while the crude protein content of the rations decreased, which shows that the crude protein intake increased less than the total feed intake. Thus, an increase in crude protein efficiency was observed.
The LfL Bayern sub-project focussed on the estimation of N excretion in milking cows(determination of the amount of urine in dairy cows). With the same ration design and milk yield, Brown Swiss cows showed higher milk urea and milk protein contents with lower N excretion compared to cows of the Holstein and Fleckvieh breeds. The N excretion of milking cows was modelled separately for the Brown Swiss and Holstein/Fleckvieh breed groups on the basis of milk quantity and milk urea and milk protein content. When applied to Holstein/Fleckvieh cows, the model shows an improved goodness of fit compared to the frequently used estimation equation by Bannink and Hindle (2003).
For the analyses in the sub-project of the Thünen Institute, the MLP data collected nationwide for the years 2005 to 2022 were evaluated. This showed an increase in herd size and milk yield with a simultaneous reduction in milk urea content. In addition, breed-specific differences in milk yield and milk urea content were identified: The highest milk yield was found in Holstein-Schwarzbunt cows and the highest fat and protein content in Jersey cows. The highest milk urea content was found in Brown Swiss cattle.
The previous calculation of the national emission inventories(Thuenen: Emissionsinventare: Buchhaltung für den Klimaschutz) by the Thünen Institute was based on tabular values for the (crude protein) feeding of dairy cows. This meant that the development of N-reduced feeding in recent years could not be mapped. By applying the estimation formula derived by Honig et al. (2024) in the German Emissions Inventory, it was possible to estimate approx. 20 kt NH3 lower emissions nationwide for 2023 than with the previous estimation formula(calculation of N emissions from dairy cattle in the National Emissions Inventory). This means that a considerable reduction in emissions(measures to reduce emissions in dairy farming / transfer of results from the project into practice) can be achieved by optimising protein feeding, management and other measures already applied in practice.