Forecasting of livestock

Farm animal production deals with the problem of production system. The foremost scope of machine learning applications in farm animal production is precise judgment of monetary balances with the help of which the producers can get information based on production line monitoring and thus can gain profits. This is because the machine learning algorithms have the potential for early detection and warning of problems that give the prior information to the producers.

• Morales et al. (2016) studied how to detect the egg production. SVM is used for the recognition of problems in production of eggs with the help of egg production data of egg laying hens. By using optical parameter configuration of an SVM model an alert can be indicated a day in advance that can be helpful for preventive diagnosis of clinical symptoms.
• Craninx et al. (2008) introduced the machine learning algorithm for forecasting the rumen fermentation pattern from milk fatty acids. Machining the prediction precision of the given model is done with regression model which is dependent on both odd and multi-​sequence milk fatty acids.