Beeftrader: Optimal Economical Endpoint Decision Support System for Feedlots and Meat Packers

This study aimed to identify the most profitable feeding endpoint for feedlot cattle based on each individual animal’s optimal economical endpoint (OEE) using the BeefTrader Decision Support System (DSS). The hypothesis was that the traditional slaughter endpoint (TSE, currently used in commercial feedlots) would have different profitability than the OEE which is determined when the marginal net profit (MNV = daily change in revenue – expense) becomes negative. Using Monte Carlo simulations, MNV curves for 280 Nellore breed cattle were generated for 14 feedlots, using the Davis Growth Model reparametrized for Nellore. These simulated animals were sold by the model to 83 meat packers in Brazil. The constraints used were: feedlot period ≥ 1 d, shrunk BW ≥ 390 kg and empty body fat ≥ 16%. The optimized method considered the most suitable time for sale. From 280 animals simulated, 258 were sold by optimization process. The integrated MNV increased up to 74% (P < 0.05) for OEE compared to TSE. On average, an animal sold by OEE had net profit of R$ 202.64 ± 6.35 (± SD) and for TSE R$ 116.54 ± 34.80. The variability of the animal’s sale to OEE was significantly lower (about 3 times) in relation to the TSE, showing that BeefTrader can determine the time of slaughter based on both the chemical and physical body composition. At present, TSE is determined by visual inspection by trained technicians, resulting in greater variability and increased risk, since it is a non-optimized process. BeefTrader changes this scenario using an individual animal’s dynamic growth and chemical composition, along with internal and exogenous economic information. The next step for this DSS is to be tested in a real farming situation, because the results presented here are encouraging.

*Acknowledgements: Grant #2015/07855-7 [BeefTrader PIPE Project and scholarships (16/02347-6; 16/02451-8; 16/07154-1; 16/12825-2; 16/12709-2)].