| ABSTRACT This study aimed to determine a model to predict mean surface temperature of broiler chicks and live load microclimate conditions during transport by using neural networks. The research was conducted in the state of São Paulo, Brazil, by monitoring nine shipments with different density of boxes using an air-conditioned truck with an average capacity of 380 boxes. Fourteen chick boxes were chosen on each shipment, assessing five chicks per box. The mean surface temperature of chicks (MST) was measured with an infrared thermometer in both loading and unloading. By assessing the container microclimate (center and inside boxes), air temperature (T), relative humidity (RH) and specific enthalpy (h) were recorded; thereby, seventeen data loggers were... |
