Microbial Contaminated Paper Substrate – UV-Vis-NIR spectra of Model Systems

Abstract

This study aims to study the possibility of distinguishing the UV-Vis-NIR spectra of filamentous fungi on a paper substrate from the background. Model samples of five filamentous fungi were used: Alternaria alternata, Aspergillus niger, Cladosporium herbarum, Penicillium chrysogenum, and Trichoderma atroviride. The model samples were cultivated on paper substrates, and two methods, Cross Validation (CV) and Principal Component Analysis (PCA), were utilised to compare their spectra with the reference background spectra. The results of the CV analysis indicated that certain combined spectra sets of Cladosporium herbarum, Penicillium chrysogenum, Trichoderma atroviride, Aspergillus niger, and Alternaria alternata, at specific surface concentrations, exhibited two active components, signifying distinguishable differences from the background spectra. Additionally, the score scatter diagrams derived from PCA revealed clusters of samples, further confirming the distinguishability of the filamentous fungi spectra from the background. However, for Trichoderma atroviride, the scatter diagram demonstrated a relatively large scattering of points, impeding the resolution of spectra with a surface concentration of 2 105 cm-2 due to measurement inaccuracies. Based on the combined results of CV and PCA, the study concluded that the lower threshold of measurability for UV-Vis-NIR spectra varied among the different filamentous fungi. For example, Cladosporium herbarum, Penicillium chrysogenum, and Trichoderma atroviride exhibited a threshold around a surface concentration of 2 106 cm-2, while Aspergillus niger had a threshold around 2 105 cm-2, and Alternaria alternata had a threshold around 2 103 cm-2. In summary, this research provides insights into the distinguishability of filamentous fungi spectra on the paper substrate from background spectra using spectral analysis techniques, offering potential applications in fungal identification and characterisation.