Differentiating Alternaria Species Using Hyperspectral Imaging

Rice is one of the most important cereal crops. This plant is native to tropical and subtropical regions and has the largest cultivated area in the world after wheat. Rice is exposed to various types of biotic and abiotic stresses at different stages of cultivation. Among the different pathogens, fungi have the largest pathogenicity spectrum. Hyperspectral imaging is used specifically in assessing the safety and quality of food. The present study demonstrates the possibility of using hyperspectral imaging to differentiate Alternaria species. The samples used in the study included A. solani, A. dumosa, and A. atra. Hyperspectral images of the samples were obtained using a scanning imaging system. The effective wavelengths were selected using principal component analysis (PCA). According to the principal component analysis, the increase in time was associated with enhanced enzymatic activity, which led to a lighter color of the solution. Moreover, a significant difference in enzyme activity levels was observed across the different days. Also, fungal growth increased with increasing enzyme activity duration. Also, in the comparison between different fungal isolates, significant differences were observed between different isolates.

کلیدواژه ها:

Enzyme Activity ، fungi ، Principal component analysis ، Spectral reflectance processing