Identification and Detection of Fusarium in Black Fungus Using Fourier Transform Infrared Spectroscopy
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Abstract:
A qualitative and quantitative detection method for Fusarium in black fungus based on Fourier transform infrared spectroscopy was established. Autoclaved black fungus samples were inoculated with five common Fusarium species (F. proliferatum 189975, F. moniliforme 340687, F. oxysporum 120618, F. equiseti 124121, F. solani 121547) at 28 ℃ and 80% relative humidity. The infrared spectra of the samples at different storage periods were obtained at 1 800~900 cm-1. The rapid identification and detection model of Fusarium in black fungus was established using principal component analysis (PCA), linear discriminant analysis (LDA), and partial least squares regression analysis (PLSR). The results showed that the LDA model correctly identified 87.50% of the black fungus samples infected with different Fusarium species and 82.50% of the black fungus samples infected with a single Fusarium species. The PLSR model achieved good quantitative results in predicting the total number of colonies in the samples (R2 p=0.842 8, RMSEP=0.292 log CFU/g, RPD=2.81). Validation analysis of the actual samples showed that Fourier transform infrared spectroscopy could achieve rapid identification and detection of Fusarium in black fungus.
