Review: Harnessing extant energy and protein requirement modeling for sustainable beef production

Numerous mathematical nutrition models have been developed in the last sixty years to predict the dietary supply and requirement of farm animals' energy and protein. Although these models, usually developed by different groups, share similar concepts and data, their calculation routines (i.e., submodels) have rarely been combined into generalized models. This lack of mixing submodels is partly because different models have different attributes, including paradigms, structural decisions, inputs/outputs, and parameterization processes that could render them incompatible for merging. Another reason is that predictability might increase due to offsetting errors that cannot be thoroughly studied. Alternatively, combining concepts might be more accessible and safer than combining models' calculation routines because concepts can be incorporated into existing models without changing the modeling structure and calculation logic, though additional inputs might be needed. Instead of developing new models, improving the merging of extant models' concepts might curtail the time and effort needed to develop models capable of evaluating aspects of sustainability. Two areas of beef production research that are needed to ensure adequate diet formulation include accurate energy requirements of grazing animals (decrease methane emissions) and efficiency of energy use (reduce carcass waste and resource use) by growing cattle. A revised model for energy expenditure of grazing animals was proposed to incorporate the energy needed for physical activity, as the British feeding system recommended, and eating and rumination (H_jE_er) into the total energy requirement. Unfortunately, the proposed equation can only be solved iteratively through optimization because H_jE_er requires metabolizable energy (ME) intake. The other revised model expanded an existing model to estimate the partial efficiency of using ME for growth (k_g) from protein proportion in the retained energy by including an animal degree of maturity and average daily gain (ADG) as used in the Australian feeding system. The revised k_g model uses carcass composition, and it is less dependent on dietary ME content, but still requires an accurate assessment of the degree of maturity and ADG, which in turn depends on the k_g. Therefore, it needs to be solved iteratively or using one-step delayed continuous calculation (i.e., use the previous day's ADG to compute the current day's k_g). We believe that generalized models developed by merging different models' concepts might improve our understanding of the relationships of existing variables that were known for their importance but not included in extant models because of the lack of proper information or confidence at that time.