BIOPROCESS OPTIMIZATION OF MICROBIAL OIL YIELD FROM Aspergillus niger USING MACHINE LEARNING MODEL AND PALM FRUIT EMPTY FIBRE AS CARBON SOURCE.

Abstract

Microbial oil is a valuable product that can be produced from Aspergillus niger through a process called fermentation and it is one of the filamentous oleaginous fungi, as several studies shows that the fungus can be cultured on various growth media showing important accumulation of single-cell oil. Palm fruit empty fiber (PFEF) is a type of agrowaste used as a bioprocess substrate in this research. The samples were collected from two dumpsites location (Afelele river and Summit university), isolation of fungi using PDA at 20-25 for 5 days incubation period, screening of oleaginous fungi isolates for lipid synthesis using Congo red Agar leaving a clear precipitation zone (hydrolysis activity) around the pure fungal colony in the plates, identification of fungi with the use of microscope, Yeast Extract Peptone Dextrose broth was used in the fermentation process using PFEF and Glucose as carbon source in extraction and optimization of lipid production was used in this research approach, so as, to utilize microbial lipids can simultaneously support the generation of clean energy, manage biomass waste and deliver clean energy. However, decision tree algorithm was used in predicting the result in this research study. Result of the fermentation, it is observed that Day 11 has the highest growth rate of 8.81g for the wet oleaginous fungi while 1.32g for the dried and for these results, it discussed the most recent developments in the bioprocessing of oleaginous fungus using palm fruit empty fiber as carbon source.