In the beer brewing industry, the biotechnological processes are in the form of multi-factorial linear systems where the mutual interference between chemical variables (metabolite, biomass concentration and substrate products) and physical variables (pH, Eh, cultivation temperature, and dissolved oxygen) is unstable and complex when the cultivation condition changes.
Sensors are currently not available for real time measurements of biological parameters. Time consuming, slow, laborious, and expensive analytics are currently being used to collect biological data.
To cater for this problem and speeding up the implementation of the EU and global food quality standards stated by the Hazard Analysis and Critical Control Point (HACCP), a group from the Bulgarian Academy of Sciences’ Institute of Control and Systems Research (ICSR), National Centre of Agrarian Sciences (NCAS, Institute of Cryobiology and Food Technologies (ICFT) is developing software analyzers that cater to individual phases of beer manufacturing.
Preparation phase of beer fermentation relates to making optimal content pitching yeasts and substrates. Industrial yeast strains refer to microbial populations of particular physiological and morphological content and cell features. By implementing artificial intelligence (AI) techniques on experimental data, it is possible to synthesize software analyzers to define concentration of many types of yeast cells (budding, weak, living, and dead), fermentation, and budding energy activity of the brewing yeasts.
During the initial phase of beer fermentation, getting industrial strains that have the desired features is typically based on synthesis of ergosterol synthesis and dissimilation of glycogen dissimilation. The content of ergosterol and glucose is defined through biochemical analysis conventionally and needs initial equipment and sample preparation.
Software analyzers for measurement of glucose and ergosterol, in real time, were developed for reducing analysis time, realizing staff and labor savings, and achieving higher accuracy statistical results as compared to biochemical analysis’ accuracy. Synthesized software analyzers depict high accuracy. Both software and synthesized software analyzers are sensitive to the conditions of cultivation (changing initial concentration of the content of the dissolved oxygen).
Prediction of beer quality on the basis of real process data is carried out by using fuzzy rules. and characterization of the beer fermentation’s influence on the indices of beer quality. This technique is also for fatty acids, vicinal dihetones (VDC), and high alcohols.
It is possible to realize software analyzers in the form of mobile calculators for the requirements of technologists or human-operator. Such mobile calculators can transmit information to highly complex control systems installed in multistage ecological and industrial systems on larger geographical regions, with the distributed parameters.
Intelligent software sensor analyzers result in considerable economic efficiency due to savings in costly equipment for measuring intercellular substances and metabolites, cell mass, and substrates which decide the final quality. It is also possible to localize and eliminate ion damages and errors efficiently in the industrial plants by implementing intelligent software analyzers.