323 Assessing the economic injury threshold and decay of performance after onset due to Horn fly abundance in beef cattle.

Abstract Horn flies (Haematobia irritans) are among the most economically detrimental ectoparasites in beef cattle, negatively impacting animal welfare and productivity by reducing feed intake and growth performance. The industry-standard economic injury threshold (EIT) of 200 flies per animal has been widely used to determine the point at which intervention is necessary. However, individual tolerance to horn fly infestation varies, and a one-size-fits-all threshold may not be suitable for optimal herd management. The objective of this study was to determine individualized EITs for beef heifers using Bayesian changepoint models, incorporating both subjective and image-based horn fly counts, as well as growth performance metrics. Data were collected from 337 heifers at two University of Georgia research farms (Eatonton and Calhoun) over three years (2022–2024). At each time point (March, June, and August), animals were weighed, and horn fly infestation was assessed using two methods: trained evaluator assessments (subjective counts) and image-based fly counts. Bayesian changepoint models were implemented to determine the exact threshold at which growth performance started declining (EIT), the rate of decline after reaching this threshold (DPO), and an upper limit beyond which additional fly burden no longer affected performance (UST). The results indicated substantial variation in EIT across animals, with estimates ranging from 261 to 322 flies, depending on the growth interval considered. This suggests that the widely accepted industry threshold (200 flies) may underestimate tolerance in some animals while being too high for others. The rate of decline in growth performance (DPO) also varied, emphasizing the need for individualized fly management strategies. Furthermore, the two-changepoint model identified an upper threshold (UST), at which further increases in fly burden did not significantly impact growth, reinforcing the idea that fly tolerance is not uniform across all animals. These findings demonstrate that Implementing data-driven EITs tailored to individual, or herd-level susceptibility could improve economic outcomes by optimizing intervention timing and reducing unnecessary pesticide applications. Future research can focus on validating these thresholds in different genetic lines and management environments, further enhancing precision livestock farming approaches.