Differentiation of toxigenic fungi using hyperspectral imagery

Some pathogenic fungi, Aspergillus flavus for example, produce mycotoxins that can contaminate grain products including wheat and corn. The contaminated grain poses a threat to the health of both humans and animals. Therefore, from the perspective of food safety and protection, it is important to detect and identify the different toxin-producing fungi encountered in food production. Earlier studies examined various spectral-based, non-destructive methods for the detection of fungi and toxins. The present report focused on the feasibility of using spectral image data for fungal species classification. A tabletop hyperspectral imaging system, VNIR-100E, was used for spectral and spatial data acquisition. A total of five fungal species were selected for a two-part experiment: Penicillium chrysogenum, Fusarium moniliforme (verticillioides), Aspergillus parasiticus, Trichoderma viride, and Aspergillus flavus. All fungal isolates were cultured on media under laboratory conditions and were imaged on day 5 of growth. The objective of the study was to use visible near-infrared hyperspectral imagery to differentiate fungal species. Results indicate that all five fungi are highly separable with classification accuracy of 97.7%. In addition, all five fungi could be classified by using only three narrow bands (bandwidth = 2.43 nm) centered at 743 nm, 458 nm, and 541 nm.