Seasonal variability attributed to heat stress (HS) has a large economic impact on the US swine industry by reducing daily gain and finishing market weights. Strategies to mitigate HS lack evidence showing effectiveness in different climates and have not been adequately controlled to provide a thermally optimum environment for pigs. Hence, the goal of this study was to describe the initial experimental design and instrumentation as well as develop innovative control algorithms for operating evaporative pads (EPs) and sprinklers. Located in northeast Iowa, a four room (~1,875 head per room) grow-finish facility featured side-by-side rooms separated by a hallway. Three thermal environment sensor arrays (TESAs) quantifying dry-bulb and globe temperature, relative humidity, and airspeed were placed in each room and served as feedback for control system to evaluate the thermal environment and potential HS conditions. The newly developed housed swine heat stress index (HS2I) combines TESA measurements and optional wetted skin to assess the potential for HS onset. Custom software interfaced with a multifunction data acquisition board was used to condition TESA signals and control EP pumps and sprinkler solenoids. A control algorithm was developed and simulated using data collected during a 23-d period in July 2017 to preliminarily evaluate the robustness and potential control decisions. Linear models developed to predict indoor dry-/wet-bulb temperature showed good agreement with measured data and will be critical for developing a control systems to selects the best cooling system given forecasted ambient conditions.
Available at: http://works.bepress.com/brett-ramirez/21/