Enhancing sustainability through resource efficiency in beef production systems using a sliding time window-based approach and frame scores.

The food needs of the increasing global population, inefficiencies in supply chains, customer expectations and environmental concerns are the challenges to meeting resource-intensive protein needs sustainably. Collectively, this increases the need to enhance sustainability in the beef sector. This study proposes a sliding time-window-based multi-period livestock production model using mixed-integer linear programming (MILP) to simultaneously balance economic and environmental losses. It identifies the optimal finishing time using frame score (FS) and feed conversion ratio (FCR), targeting flexibility by allowing variable growth periods to reduce food/nutritional losses while meeting the variability in demands with minimum inventory levels. Furthermore, sequencing and assigning animals to facilities with optimum separation time is applied to avoid bad handling of animals and ensure quality meat with hygienic standards for longer shelf life. The system boundary of the proposed model includes beef farms and processing facilities. Compared to the recently proposed batch processing models over seven months with a herd size of 1980 animals, the findings reduce the average forage needed by ∼126.90 kips and methane emissions by ∼2560 kg, with a significant benefit in terms of the live animals' weight gain by ∼10,276 lbs.