Fermentation analysis by clustering

To supervise, stabilize and optimize antibiotic fermentations in the industrial scale expert systems are presently worked out. For the knowledge acquisition various classifiers are tested using a set of 27 nourseothricin fermentation runs. Two methods are applied: optimal clustering by help of minimum variance criterion and hierarchical clustering by help of dendrograms. The fermentations are classified with respect to the specific material costs as well as the product formation kinetics.