Approaches for Developing and Implementing Precision Feeding Programs to Maximize Feed Efficiency

Nutritional management of dairy cattle is of importance to the industry due to its influence on production performance and association with large expenses for producers. Current ration formulation may be improved by predicting feeding recommendations for individual animals, rather than groups of animals, through precision feeding. Automated feeding systems (AFS) designed to deliver individual rations must include response-based models that utilize individual cow production data to make feed recommendations. These models require large data sets of individual cow responses to a variety of nutritional interventions. As a result, an experiment was designed to collect individual response data from 24 Holstein cows fed supplemental top dresses. After analyses, dry matter intake (DMI), milk yield (MY), milk fat yield, milk protein yield, feed efficiency, and activity were significantly affected by top dress (P < 0.001). These results suggest opportunity to use precision feeding to implement economically optimal ration recommendations designed to increase dairy cow production. Therefore, a second experiment was conducted in order to develop and test two algorithms that targeted individualized feeding to increase feed efficiency. Milk protein percentage (P = 0.008) and feed efficiency (P < 0.001) were significantly affected by a 3-way interaction between top dress, algorithm, and week. These results highlight the opportunity for precision feeding to increase the efficiency of individual dairy cows. Although the control group resulted in greater income over feed costs than either of the developed algorithm feeding strategies, algorithm refinement and modification may result in more efficient feeding recommendations that are economically viable.