Machine learning strategies for the forecasting of production pig growth

Over the past few years, the interest in computer-assisted farming has substantially increased. Especially with respect to applications of machine learning algorithms to farming practices, known as precision agriculture. This has been driven by the potential to improve the productivity, sustainability, and profitability of agricultural farming whilst also improving food security. However, under commercial conditions, precision agriculture has been mostly limited to crop farming, and have not been applied to livestock farming outside of research, primarily due to more complicated development and testing process.

In this talk, I will discuss machine learning strategies for the forecasting of pig growth, and show how they can benefit farm management. In particular, I will demonstrate how machine learning can assist in identifying data on an individual animal level, which before was too expensive for farms to implement.