Seed Quality Assessment in an Industrial Fermentation Using MPCA

Abstract This paper investigates the benefits of including seed quality information into data-based models for final productivity estimation in an industrial tylosin fermentation process. Multiway Principal Component Analysis (MPCA) is used to assess the seed quality using only data routinely monitored on-line. It is shown that it is possible to extract seed fermentation features related to the final productivity both at pilot and production scale.