A self-tuning vision system for monitoring biotechnological processes. I. Application to production of pullulan by Aureobasidium pullulans

A prototype of a self-tuning vision system (STVS) has been developed to monitor cell population in fermentations. The STVS combines classical image processing techniques, neural networks and fuzzy logic technologies. By combining these technologies the STVS is able to analyze sampled images of the culture. The proposed system can be 'tailored' with minimum effort by an expert who can 'teach' the system to recognize cells by showing examples of different morphologies. After adaptation, the STVS is able to capture images, isolate the different cells, classify them according to the expert's criteria, and provide the profile of the cell's population. The system was applied to the classification and analysis of Aureobasidium pullulans. The importance of understanding the changes of population distribution during the fermentation and its effect in the production of pullulan are emphasized. The STVS can be used for monitoring and control of the cell population in small research fermentors or in large-scale production.