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The monitoring of the main variables and parameters of biotechnological processes is of key importance for the research and control of the processes, especially in industrial installations, where there is a limited number of measurements. For this reason, many researchers are focusing their efforts on developing appropriate algorithms (software sensors (SS)) to provide reliable information on unmeasurable variables and parameters, based on the available on-line information. In the literature, a large number of developments related to this topic that concern data-based and model-based sensors are presented. Up-to-date reviews of data-driven SS for biotechnological processes have already been presented in the scientific literature. Hybrid software sensors as a combination between the abovementioned ones are under development. This gives a reason for the article to be focused on a review of model-based software sensors for biotechnological processes. The most applied model-based methods for monitoring the kinetics and state variables of these processes are analyzed and compared. The following software sensors are considered: Kalman filters, methods based on estimators and observers of a deterministic type, probability observers, high-gain observers, sliding mode observers, adaptive observers, etc. The comparison is made in terms of their stability and number of tuning parameters. Particular attention is paid to the approach of the general dynamic model. The main characteristics of the classic variant proposed by D. Dochain are summarized. Results related to the development of this approach are analyzed. A key point is the presentation of new formalizations of kinetics and the design of new algorithms for its estimation in cases of uncertainty. The efficiency and applicability of the considered software sensors are discussed.

Three different kinetic models – Monod’s model, Monod’s model with substrate inhibition, and Monod's model with substrate and product inhibition were developed for studying of beer fermentation with free and immobilized cells at different main fermentation and maturation temperatures. The most accurate model was Monod's model with substrate and product inhibition. It showed that maturation temperature had no effect on primary metabolism but it affected significantly the secondary metabolites production. In regard to carbonyl compounds and esters, the increase in maturation temperature led to different trends for free and immobilized cells. Regarding the higher alcohols, the increase in maturation temperature resulted in increase in their yield coefficients for both immobilized and free cells. A sensory evaluation of beers produced with free and immobilized cells were also carried out and the results showed similar results for two beer types.

Investigations of inhomogeneous dynamics in industrial-scale bioreactors can be realized in laboratory simulators. Such studies will be improved by on line observation of the growth of microorganisms and their product synthesis at oscillating substrate availability which represents the conditions in industrial-scale fed-batch cultivations. A method for the kinetic monitoring of such processes, supported by on line measurements accessible in industrial practice, is proposed. It consists of a software sensor (SS) system composed of a cascade structure. Process kinetics are simulated in models with a structure including time-varying yield coefficients. SSs for measured variable kinetics have classical structures. The SS design of unmeasured variables is realized after a linear transformation using a logarithmic function. For these software sensors, a tuning procedure is proposed, at which an arbitrary choice of one tuning parameter value that guarantees stability of the monitoring system allows the calculation of the optimal values of six parameters. The effectiveness of the proposed monitoring approach is demonstrated with experimental data from a glucose-limited fed-batch process of Bacillus subtilis in a laboratory two-compartment scale down reactor which tries to mimic the conditions present in industrial scale nutrient-limited fed-batch cultivations.