Environmental factors and management practices associated with beef cattle carcass quality in the mid-west of Brazil

The "Precoce MS" program, established by the Brazilian government in Mato Grosso do Sul in 2017, aims to encourage beef producers to harvest animals at younger ages to enhance carcass quality. About 40% of the beef produced in the state now comes from this program, which offers tax refunds ranging from 49% to 67% based on carcass classification and production system. Despite the program success, with participants delivering younger animals (with a maximum of 4 incisors), there remains significant variability in carcass quality. This paper investigates management practices and environmental factors affecting farm performance regarding carcass quality. Data from all animals harvested between the beginning of 2017 and the end of 2018 were analyzed, totaling 1,107 million animals from 1,470 farms. Farm performance was assessed based on the percentage of animals achieving grades "AAA" and "AA." Each batch of harvested cattle from each farm was categorized into two groups: high farm performance (HFP, with more than 50% of animals classified as "AAA" or "AA") and low farm performance (LFP, with less than 50% classified as such). A predictive logistic model was developed to forecast farm performance (FP) using 14 continuous and 15 discrete pre-selected variables. The most effective model, obtained through backward stepwise variable selection, had an R2 of 0.18, accuracy of 71.5%, and AUC of 0.715. Key predictors included animal category, production system type, carcass weight, individual identification, traceability system, presence of a feed plant, location, and the Normalized Difference Vegetation Index (NDVI) from the 12-mo average before harvest. Developing predictive models of carcass quality by integrating data from commercial farms with other sources of information (animal, production system, and environment) can improve our understanding of production systems, optimize resource allocation, and advance sustainable animal production. Additionally, they offer valuable insights for designing and implementing better sectorial, social, and environmental policies by public administrations, not only in Brazil but also in other tropical and subtropical regions worldwide. Unlocking the secrets of producing superior beef in the tropics, a case study in Mato Grosso do Sul, Brazil. By analyzing data from over a million animals across 1,470 farms, this study identifies key management practices and environmental factors that contribute to superior carcass quality. A predictive was developed to forecast farm performance, paving the way for more efficient production and informed policy-making in the beef industry. The Brazilian government launched the "Precoce MS" program in 2017 to incentivize beef producers in Mato Grosso do Sul to harvest animals at a young age for superior carcass quality, offering tax benefits. Despite the program's success, variability in carcass quality persists among producers. This study examines data from over one million animals across 1,470 farms to investigate the management practices and environmental factors affecting carcass quality. A predictive model was developed to forecast farm performance and identified several key factors-such as animal category, production system type, carcass weight, individual identification, traceability system, on-farm feed-plant presence, location, and vegetation index-as significant predictors of carcass quality. The findings suggest that using data from commercial farms and various information sources to develop predictive models can enhance understanding of production systems, optimize resource allocation, and improve sustainable animal production. Additionally, these results may guide the development and implementation of more effective policies by public administrations in Brazil and other regions worldwide.