Feeding models to optimize dairy feed rations in view of feed availability, feed prices and milk production scenarios

In the global dairy production sector, feed ingredient price and availability are highly volatile; they may shape the composition of the feed ration and, in consequence, impact feed cost and enteric methane (CH₄ ) emissions. The objective of this study is to explore the impact of changes in feed ingredients’ prices and feed ingredients’ availability on dairy ration composition, feed cost and predicted methane yield under different levels of milk production. To meet the research aim, a series of multi-period linear programming models were developed. The models were then used to simulate 14 feed rations formulations, each covering 162 months and three dairy production levels of 10, 25 and 35 kg milk/d, representing a total of 6804 feed rations altogether. Across milk production levels, the inclusion of alfalfa hay into the feed rations declined from 55% to 38% when daily milk production increased from 10 to 35 kg, reflecting the cows’ increased energy requirements. At a daily milk production level of 35 kg, CH₄ production (per kg milk) was 21% and 53% lower than in average and low milk producing cows, respectively, whereas at 10 kg of milk production the potential to reduce CH₄ production varied between 0.6% and 5.5% (average = 3.9%). At all production levels, a reduction in CH₄ output was associated with an increase in feed costs. Overall, and considering feeding scenarios in low milk producing cows, feed cost per kg milk was 30% and 37% higher compared to that of average and high milk production, respectively. The feed ration modeling approach allows us to account for the interaction between feed ingredients over time, taking into consideration volatile global feed prices. Overall, the model provides a decision-making tool to improve the use of feed resources in the dairy sector.