Critical Review on Microbial Inulinase Production: Emerging Strategies, AI-Driven Optimization, and Applications

Abstract

Microbial inulinases are increasingly recognized as valuable biocatalysts for the sustainable production of high-value products, including fructooligosaccharides, fructose, bioethanol, and organic acids in industries, such as food, pharmaceuticals, and bioenergy. In the last few decades, microbial inulinase research has advanced significantly, from strain selection and fermentation optimization to advanced enzyme engineering and immobilization, improving yields, stability, and reusability. There are still some final bottlenecks, such as low yields, poor thermostability, and high purification costs. This review examines strategies to innovate and overcome these bottlenecks, including novel immobilization strategies that utilize nanomaterials, system-scale bioprocess optimization using artificial intelligence (AI), and bioprospecting extremophiles using metagenomics. The present review discusses how statistical and computational modeling (RSM, ANN, and AI) significantly increases yield and process efficiency, with comments on their relevance to contemporary biorefinery applications. The advanced immobilization approaches significantly enhance operational stability and reusability, allowing for continuous processing. This review situates the development of inulinase as not just an enzymological effort but a multidisciplinary effort involving process engineering and sustainability science. Overall, emphasize is given toward the thought that advancements leaning toward the future will require a synthesis of AI-designed enzyme systems; economical immobilization supports; and incorporation of circular bioeconomy principles through the valorization of agro-wastes. These barriers to knowledge transfer must be resolved if we are to unlock the full bioeconomic potential of microbial inulinase systems.