DOI: 10.1093/jas/skag272.042 ISSN: 0021-8812

368. Accuracy, Reliability, and Value of New Digital Technologies in Swine Production Systems.

Christopher L Puls, Matthew J Ritter, Chris L Eden, Eric Nyberg, John Bell

Abstract

Over the last 20 years, technological innovations have dramatically improved efficiency and accuracy of highly controlled, precision farming in US crop production systems. Inventions such as spot sprayers, planter row shutoffs, soil mapping and precision nutrient applications, and GPS have dramatically shaped row cropping landscapes. Similar advancements have not been largely implemented in the US swine industry. Largely, pigs are still placed into commercial facilities, fed a common diet regardless of sex or body weight, and reared using standard operating procedures largely unchanged over 20 years. Innovative technologies are available today to fundamentally shift livestock rearing and data management efficiency. United Animal Health (Sheridan, IN) has implemented a number of technologies in a commercial finisher and is actively engaging data outputs to predict and manage optimum growth of pigs. Technologies installed include individual animal RFID tags and electronic data capture system, a computerized feed system capable of recording daily feed deliveries by pen, pen-level digital water meters, pen-level weight prediction cameras, feed bin sensors, remote access environmental controls, and digital pig counters for accurate inventory control. Over four growing-finishing turns (n = 3,000+ pigs), pigs have been placed into 64 pens and technologies have been evaluated for accuracy and reliability, and outputs are being used to determine economic value and return over investment for commercial application. Digital pig counter cameras had over a 99% accuracy. Weight prediction cameras have proved largely accurate with reported concordance correlation coefficient (CCC) of 0.98 + (Phelps et al., 2026). Most interesting, camera technology detected a negative shift in pen and barn ADG approximately 5 days due to a health event prior to observations by farm personnel. Water meter readings were 95% of measured values, with average differences of ∼0.25 gallons/meter. Data outputs are linked together in Power BI dashboard with visibility of different technologies in a single location, offering real-time view of barn and pen performance. Cost, data management, and return over investment will remain the largest barriers to producer implementation and acceptance. Nonetheless, technology continues to be developed to increase management and productivity of both animals and farm labor.