Big Data Analysis of Beef Production and Quality: An Example with the Brazilian Cattle Industry

‘Big data’ represents the new era in data exploration and utilization in livestock systems. With recent developments in data recording technology and analytics tools, it is now possible to get important insight regarding management practices and environmental effects affecting livestock productivity and product quality on a much larger scale. Even though analyzing Big Data is challenging (as it requires cautious data curation, large computer memory, and specific data mining tools), it can be extremely valuable. In this analysis, data from Brazilian beef cattle was available from two sources: JBS S.A. (81,053 farms) and DSM Produtos Nutricionais (22,223 farms). After merging, the final dataset comprised information from 7,248 farms and 1,571,023 carcasses slaughtered in the years 2014-2016. Three outcome variables were analyzed: body weight at slaughter (BWS, kg), carcass fat index (FI, 1-5), and age at slaughter (AS, yr). Covariates included in all models were: AS (except when it was an outcome), season (dry or rainy in each year), animal category (steer, bull, cull bull, heifer and cow), frequent technical consulting (FTC, binary), regional sales team (RST, 17 levels), type of feedlot premix (no feedlot premix – NFP, finishing grazing cattle – FGC, feedlot without additives – FWA, and feedlot with additives – FA) and farm (random effect). After extensive data mining, mixed model analyses were performed for all outcomes. The use of FA premix decreased AS, and increased BWS and FI in comparison to NFP (0.55 yr, P<0.00; -1.78 kg, P<0.00; -0.13, P<0.00), FGC (0.34 yr, P<0.00; -3.58 kg, P<0.00, -0.12, P<0.00) and FWA (0.72 yr, P=0.04; -21.09 kg, P=0.05; -0.25, P=0.02). Adopting FTC increased BWS (6.38 kg, P<0.01) and FI (0.07, P<0.01), and reduced AS (-0.13 yr, P<0.01). Bulls presented greater BWS (26.51 kg, P<0.01) and lower AS (-0.46 yr, P<0.01), but presented lower FI (-0.51, P<0.00) in comparison with steers. Differences in BWS were observed for different RST and seasons (most P<0.01). Age at slaughter was reduced and BWS and FI increased for rainy seasons of 2014-2016 (P<0.01). Combining FTC and FA was capable of increasing BWS in 27.4 kg and reducing AS in approximately 10 months in comparison with FWA and non-FTC, suggesting that this approach might be favorable for production. Results presented here provided a wide snapshot of beef production in Brazil under a Big Data perspective never explored before. They provide also useful insight to validate experimental findings and aid decision-making at the farm level.