BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD FROM Aspergillus niger USING MACHINE LEARNING MODEL AND CO-CULTURE OF SWEET POTATO PEEL AND SHEA BUTTER KERNEL AS CARBON SOURCE

Abstract

This study investigates the optimization of microbial oil production with the fungus Aspergillus niger utilizing bioprocess engineering methodologies supplemented by machine learning models. To increase lipid yield, co-culture system that includes sweet potato peel and shea butter kernel as carbon sources. The project’s goal is to establish optimal conditions for microbial growth and oil production by investigating the relationships between co-culture substrates and fungal metabolism. This project research investigates the isolation of fungal species, the screening of oleaginous microorganisms, and the processes of fermentation, extraction, optimization, and quantification of microbial oil from oleaginous fungal strains capable of lipid production, utilizing the Congo red agar screening techniques. Five distinct fungal isolates were obtained, with two of these identified as oleaginous fungi through Congo red screening. One of these two isolates was selected for further analysis regarding microbial oil production. This isolate was characterized by its morphological features, growth rate, microscopic structure, biomass yield, and microbial oil output. The likely identify of selected isolate is Aspergillus niger. Highest biomass weight was recorded at day 7 (13.74g) for co culture fermentation of shea butter kernel and sweet potatoe peel, while the lowest weight was recorded at day3 (8.89g). Highest biomass weight was recorded at day 11 (22.50g) for fermentation of glucose, while the lowest weight was recorded at day3 (13.80g). The research indicate that the extracted microorganisms have the potential as a suitable feedstock for producing microbial oil, Due to their ability to breakdown lipids and generate high oil yields. Also, this research attempts to establish an effective and sustainable approach for microbial oil production, contributing to the advancement of bio-based alternatives.