Predicting milk shelf-life based on artificial neural networks and headspace gas chromatographic data

An examination on the role of artificial neural networks (ANN) for milk shelf-life revealed that that were useful for predicting milk shelf-life when applied to gas chromatographic profiles with sensory-based shelf-life. The predictive ability were better than the principal components regression. It is a more amenable for quality control situations. The principle components in this network are calculated before regression analysis is applied.