Automation and artificial intelligence in filamentous fungi-based bioprocesses: A review. (February 2023)

• Record Type: Journal Article
• Authors: Wainaina, Steven; Taherzadeh, Mohammad J.
• Is Part Of: Bioresource technology. Volume 369(2023)
• Publication Date: 2023-02
• Subjects: Filamentous fungi -- Machine learning -- Smart sensors -- Robotic systems -- Process control; Biomass -- Periodicals; Biomass energy -- Periodicals; Bioremediation -- Periodicals; Agricultural wastes -- Periodicals; Factory and trade waste -- Periodicals; Organic wastes -- Periodicals; Bioénergie -- Périodiques; Déchets agricoles -- Périodiques; Déchets industriels -- Périodiques; Déchets organiques -- Périodiques; Déchets (Combustible) -- Périodiques; 662.88
• DOI: 10.1016/j.biortech.2022.128421
• Languages: English
• ISSNs: 0960-8524

Abstract

Graphical abstract: Highlights: AI and automation can help fungi-based bioprocesses to increase production yields. Machine learning can discover non-linear interactions during fungi cultivation. Soft sensors enable the understanding of the complex bioprocess dynamics. Robots minimize direct labor costs while improving the quality of fungal products. Further improvements are needed for automating fungi-based industrial bioprocesses. Abstract: By utilizing their powerful metabolic versatility, filamentous fungi can be utilized in bioprocesses aimed at achieving circular economy. With the current digital transformation within the biomanufacturing sector, the interest of automating fungi-based systems has intensified. The purpose of this paper was therefore to review the potentials connected to the use of automation and artificial intelligence in fungi-based systems. Automation is characterized by the substitution of manual tasks with mechanized tools. Artificial intelligence is, on the other hand, a domain within computer science that aims at designing tools and machines with the capacity to execute functions that would usually require human aptitude. Process flexibility, enhanced data reliability and increased productivity are some of the benefits of integrating automation and artificial intelligence in fungi-based bioprocesses. One of the existing gaps that requires further investigation is the use of such data-based technologies in the production of food from fungi.