Preliminary exploration of indigenous fungi from rice fields affected by volcanic ash from Mount Semeru in Lumajang with CNN-based image support

This study is an initial exploratory study of indigenous fungi that were successfully isolated from rice paddy soil affected by volcanic ash from Mount Semeru in Lumajang Regency. The results showed that 14 fungal isolates were successfully obtained and identified macroscopically and microscopically using conventional morphological methods, which indicated the presence of the genera Curvularia, Aspergillus, Penicillium, Trichoderma, and Aphanomyces. To support the visual identification process, an image-based approach using a simple Convolutional Neural Network (CNN) model was used as a comparison. The analysis results showed that the CNN model used for this study had the ability to recognize 16 fungal isolates based on macroscopic visual parameters such as colony texture, color, and colony shape, although its use in this study was limited as a tool for fungal morphological identification.