Søren Balling Engelsen

Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, DK-1958 Frederiksberg C, Denmark
se@food.ku.dk

The use of advanced spectroscopic sensors and multivariate data analysis are key technologies for the succesful implementation of Process Analytical Technology (PAT) in the food industry. PAT represents a silent revolution in industrial quality control by introducing real-time process monitoring through fingerprinting of complex process streams using spectroscopic sensors and thereby moving from inferential monitoring and control towards 100% process control of core quality parameters [2]. A new challenge related to the introduction of PAT will be to analyze the continuous stream of spectroscopic big data from multiple process points simultaneously. As chemometric methods are capable of simultaneously analyzing plentiful data origins from different sources (e.g., spectroscopy, temperature, and pressure), it will be natural to use them in a holistic data analysis strategy and monitor the manufacturing process by all available data. This means that data integration, data timing, and alignment will be key issues in future process control. Continuous learning through data collection and analysis over the life cycle of a product is important (FDA: PAT guidance, 2004).
The introduction of PAT can not only be used to minimize end-product variation and increase production capacity, but also to make optimal use of energy and raw materials. Examples of PAT implementation will be given in different areas of food production.

F. van den Berg, C.B. Lyndgaard, K.M. Sørensen & S.B. Engelsen, Process Analytical Technology in the Food Industry, Trends in Food Science and Technology (2013), 31(1), 27-35. (http://dx.doi.org/10.1016/j.tifs.2012.04.007)