AI-Based Media Optimization for Sustainable Production of Single Cell Protein from Banana Leaves.

AbstractThe growing global population and rising food insecurity demand sustainable proteinalternatives, especially in regions burdened by agricultural waste. Single Cell Protein (SCP),derived from microbial biomass, offers a promising solution by converting low-cost organicresidues into protein-rich material. Microorganisms like Saccharomyces cerevisiae andLactobacillus brevis are commonly used to ferment substrates such as banana leaves, whichare rich in cellulose, hemicellulose, and trace nitrogen.Traditional SCP production relies onlabor-intensive, trial-and-error methods to optimize fermentation parameters—nutrientconcentration, pH, temperature, and time—often yielding inconsistent results due to complexmicrobial interactions. To overcome these limitations, artificial intelligence (AI) and machinelearning (ML) techniques, including Artificial Neural Networks (ANN), Genetic Algorithms(GA), and Response Surface Methodology (RSM), are being integrated into bioprocessworkflows. AI-driven modeling enables precise control over fermentation variables such aspH, substrate composition, and nutrient feed rates, significantly improving biomassproductivity and process stability. This review highlights the synergy between computationalintelligence and sustainable biotechnology, focusing on banana leaf biomass as a substrate forSCP production.