Modelling the effects of changes in reproductive performance of dairy cattle on pasture-based farms from Waikato, New Zealand on greenhouse gas emissions, production, and financial performance.

AIMS: To use a commercially available, deterministic, whole-farm model to assess the impact on production (milk solids (MS)/ha), greenhouse gas (GHG) emissions (total and per kg MS), and gross margin per ha, from changes in the calving pattern alone or combined with changes in non-pregnancy and replacement rate, for a pasture-based dairy farming system in Waikato, New Zealand.

METHODS

A baseline model of a dairy farm was developed. Reproductive data from actual Waikato dairy farms were used to assess the change and variability in GHG production (total and per kg MS), MS/ha and gross margin/ha of the baseline model farm. Two different scenarios were modelled using data reflecting a range in reproductive performance: firstly, calving pattern data from 82 farms were used to model, over the subsequent lactation, the range in outputs associated with these differences. Secondly, calving pattern and non-pregnancy rate data from 70 of these farms were used to model the range in outputs associated with differences in these combined metrics.

RESULTS

Sequentially changing the calving pattern data to reflect the variation in the 82 farms demonstrated relatively small changes in the outputs: higher 6-week calving rates tended to produce more MS per ha and a higher gross margin per ha. These herds also had lower GHG emissions intensity but tended to produce more overall GHG. Including the variance in the calving and non-pregnancy rate also led to small changes in outputs. Herds with higher 6-week calving rates and lower non-pregnancy rates - necessitating the user to manually reduce the replacement rate - resulted in a decrease in emissions intensity and overall emissions. However, despite the large variation in both the non-pregnancy and 6-week calving rate in the actual farm data, there was much less variation in the model's predicted production/ha, gross margin/ha and environmental emissions.

CONCLUSIONS

Although these herds demonstrated variation in reproductive performance, and a resultant variance in the replacement rate, the model predicted that the financial, production and environmental outputs were only slightly better for herds with the optimum reproductive performance. In particular, even for herds with the best reproductive performance, overall GHG emissions were only slightly reduced. Thus, our modelling suggests it is the opportunity to further manipulate the farming system - stemming from improvements in the reproductive performance - that is likely to create the greatest gains in the production, financial and environmental performance for a dairy farm.

UNLABELLED: Abbreviations: CO2e: Carbon dioxide equivalents; GHG: Greenhouse gas; MS: Milk solids.