Automated Exposure of Colorimetric Fluctuations in Aspergillus Flavus to Permit Feasible Extraction of Antibiotics

This research article focuses on the detection of the mature stage of Aspergillus flavus fungus using an automated approach. Aspergillus flavus is a pathogenic fungus known for causing diseases in crops and producing carcinogenic mycotoxins. Detecting the mature stage is crucial for optimizing the production of antibiotics such as Aspergillic acid, which is abundantly produced during this phase. Manual color detection methods are labour-intensive and prone to errors. Existing techniques face challenges due to lighting conditions and background issues. To overcome these limitations, we propose a two-part automated process that involves background elimination using comparative thresholding techniques and mapping the mature phase on the Lab* scale. This approach eliminates lighting conditions and enhances accuracy in identifying the mature phase. By automating the detection process, our method offers a significant advancement in the production of antibiotics and reduces the reliance on manual intervention. The recommended methodology has the competence to upgrade efficiency in the pharmaceutical industry and educational research on fungal growth.