Current decisions on breeding in dairy farming are mainly based on economic values of heritable traits, as earning an income is a primary objective of farmers. Recent literature, however, shows that breeding also has potential to reduce greenhouse gas (GHG) emissions. The objective of this paper was to compare 2 methods to determine GHG values of genetic traits. Method 1 calculates GHG values using the current strategy (i.e., maximizing labor income), whereas method 2 is based on minimizing GHG per kilogram of milk and shows what can be achieved if the breeding results are fully directed at minimizing GHG emissions. A whole-farm optimization model was used to determine results before and after 1 genetic standard deviation improvement (i.e., unit change) of milk yield and longevity. The objective function of the model differed between method 1 and 2. Method 1 maximizes labor income; method 2 minimizes GHG emissions per kilogram of milk while maintaining labor income and total milk production at least at the level before the change in trait. Results show that the full potential of the traits to reduce GHG emissions given the boundaries that were set for income and milk production (453 and 441kg of CO2 equivalents/unit change per cow per year for milk yield and longevity, respectively) is about twice as high as the reduction based on maximizing labor income (247 and 210kg of CO2 equivalents/unit change per cow per year for milk yield and longevity, respectively). The GHG value of milk yield is higher than that of longevity, especially when the focus is on maximizing labor income. Based on a sensitivity analysis, it was shown that including emissions from land use change and using different methods for handling the interaction between milk and meat production can change results, generally in favor of milk yield. Results can be used by breeding organizations that want to include GHG values in their breeding goal. To verify GHG values, the effect of prices and emissions factors should be considered, as well as the potential effect of variation between farm types.

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