Artificial neural networks

Artificial neural networks are computing systems modelled loosely on the human nervous system and brain, built from large numbers of parallel processors that each hold learned knowledge and rules about relationships. Fed with data, the network learns to recognise patterns in large, complex datasets that simpler statistics might miss. In the food industry they are used to model processes and to predict how foods behave under defined conditions, from drying kinetics and thermal processing to shelf-life estimation, sensory scores, and defect detection on production lines. They help optimise formulations, tighten process control, and flag anomalies in quality data faster than traditional statistical methods, though they demand large, well-curated training datasets.