The beef cattle seed stock industry in the USA is searching for ways to select for improved beef cow efficiency. Most selection indexes for efficiency have a goal of using less resource while obtaining the same outcome in a sustainable environment. However, the inputs required to determine individual beef cow feed efficiency are not readily available in practical conditions. A mathematical model was developed to use inputs readily available in each production situation to estimate the ratio of cow metabolizable energy (ME) required to calf weaning weight (WW) for computing an energy efficiency index (EEI). This model ranks EEI estimates and compares individual cow EEI within the range of expected EEI using Monte Carlo methods to identify the upper and lower cutoff values. It uses the National Research Council recommendations as implemented in the Cornell Net Carbohydrate and Protein System (CNCPS) for energy requirements for maintenance, lactation and pregnancy. Data containing varying levels of milk and forage intake of individual calves during the first 200 days after birth were used to develop a submodel to estimate calf forage and peak milk intake (PKM) based on calf body weight (BW) and forage composition. A database collected at the Bell Ranch, New Mexico (N = 182), was used to evaluate the ranking from most to least efficient cows. The simulation indicated that as PKM increases, WW increases almost linearly, the difference in the calf WW between small and large cows tends to increase, and EEI estimates improve exponentially. As PKM increased, the EEI difference between small- and largesize cows decreased.The model-predicted least efficient cows corresponded with culling decisions made prior to evaluating the EEI ranking. The Monte Carlo simulation based on the distribution, mean and variability of cow BW, PKM and forage quality indicated that cows having EEI lower than 30.6 or higher than 38 Mcal/kg are within the 10% most efficient and least efficient cows, respectively. Our analysis suggested that this model could assist beef producers in identifying the most and least efficient cows for their resource, and can be used to simulate different production scenarios to identify the best match of cow type to alternative management systems. CAB International 2006.
