실측 및 모델베이스 계산을 통한 계사의 온열환경파악 및 THI 예측식 개발

Abstract

The heat waves cause heat stress to livestock thereby degrading productivity and increasing the mortality rate. Thus, this study aims to identify the thermal environment of hen house through on-site measurements and depending on ventilation type to increase the efficiency of management of the laying house during severely hot weather by deriving a Temperature and Humidity Index (THI Index) prediction equation from the viewpoint of productivity. To do this, this study comparatively analyzed the exposure risk level to the heat stress of layers according to the ventilation method in the hen house using the THI, which was an index to quantitatively evaluate heat stress, for 26 summer days. In addition, the laying house in this study were modeled through simulations. The simulation results exhibited the highest reliability values under 25°C inside the cage and an 85.7% fan operating rate in the case of the cross ventilation method, which had 0.46 of mean bias error (MBE) and 10.58 coefficient of variation of the root mean square error (CVRMSE), while the tunnel ventilation method had 1.14 MBE and an 8.64 CVRMSE with temperature values under 27°C inside the cage, and a 100% fan operating rate. Since the above conditions were found for a simulated target building, the calculated values were utilized to derive the prediction equation. The regression analysis results showed that the coefficients of determination, which displayed the reliability of the correlation between THI and the outdoor air temperature and between THI and enthalpy, which were 0.9328 and 0.5149 respectively in the case of the cross ventilation method and 0.9551 and 0.6044 respectively in the case of the tunnel ventilation method.