Proactive model to predict and notify the risk of CRD problem in broiler farms

Abstract

CRD (Chronic Respiratory Disease) is the main cause of rejection in broiler farm industry. The large number of CRD rejections is due to the difficulty in determining root causes of disease. Moreover, this disease is very hard to be observed from outside. Hence, farmers cannot setup strategy to prevent or reduce the large number of infected chickens in time. This project proposed the proactive model for predicting the number of infected chickens by association rules technique that can continually predict the number of CRD rejections in every state of broiler raising cycle. The rules are generated from historical data and the set of risk parameters for a specific farm is extracted. Hence, for each state, farmers can obtain the notification if they have a risk to have high CRD infection. Moreover, the suggestion and avoidance to prevent the CRD problem is discovered based on the set of risk parameters of the current state. This strategy can help farmers to reduce the rate of CRD infection in time.