By Ali Cinar; et al
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Additional info for Batch fermentation : modeling, monitoring, and control
Chapter 2 focuses on the development of process models based on first principles. Considering the uncertainty in some reaction and metabolic pathways, and in various parameters, both unstructured and structured kinetic models are discussed. Case studies for penicillin fermentation are presented for both types of models along with simulation results. Chapter 3 presents various concepts and techniques that deal with experimental data collection and pretreatment. 4. Outline of the Book 17 is discussed first.
In a growing cell population, there is cell-to-cell variation as concerns cell age and cell function (cell activity). Thus, at a given time and in a sufficiently small region of physical space in a culture, some cells may be newly born, others may be of intermediate age and dividing, while still others may be much older and subject to death or lysis. In the case of molds, in an individual multicellular unit, there may be significant variation as concerns cell age. There is also differentiation among different cells as concerns replication, utilization of essential nutrients and formation of the target end product (for example, antibiotics such as cephalosporin and penicillin).
Hence, the capability to explain the mechanisms in play for the observed behavior is severely limited. One has to rely on sensitivity analysis between inputs and outputs, and expert knowledge to extract information that sheds light on fundamental phenomena that are important in a specific process. However, one should not underestimate the power of good data-based models. In diverse fields such as the stock market, aircraft and ship navigation, oceanography, agriculture, and manufacturing, data-based models have played a significant role.
Batch fermentation : modeling, monitoring, and control by Ali Cinar; et al