Multivariate Analysis of Microbial Volatile Organic Compounds for Aflatoxigenic A. flavus Detection
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- Aspergillus Flavus, Microbial Volatile Organic Compound, Multivariate Analysis, Partial Least Square Discriminant Analysis
- Sun, Dongdi; Gower, Julie L.; Stokes, C. Elizabeth; Windham, Gary L.; Baird, Richard E.; Mlsna, Todd E.
- This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. CC BY-NC-SA 4.0 Creative Commons License: https://creativecommons.org/licenses/by-nc-sa/4.0/
- The identification and classification of Aspergillus flavus (A. flavus) from an examination of the microbial volatile organic compounds (MVOCs) emitted by the fungus has the potential to be the part of an early warning system for aflatoxigenic fungi contamination. MVOCs profiles of different A. flavus isolates have been identified using a headspace solid phase microextraction gas chromatography mass spectrometry (HS-SPME-GCMS) technique. Multivariate analysis approaches were used to discriminate the aflatoxigenic and non-aflatoxigenic A. flavus isolates using their MVOC profiles. Significant variations were found when comparing both individual MVOCs and groups of MVOCs by chemical classes (with the same functional group) using multivariate ANOVA (MANOVA) analysis. Partial least-squares discriminant analysis (PLS-DA) models were used for discriminating isolates using 78 individual key MVOCs. The PLS-DA model has excellent classification specificity, where (-)-aristolene, calarene, β-germacrene, and γ-muurolene were discovered as possible volatile biomarkers for identifying aflatoxigenic isolates. This study strongly supports the concept that MVOC profiling can be used for identification of toxigenic fungal isolates and HS-SPME-GCMS combined with PLS-DA is a powerful method for fungal contamination identification and potential biomarkers discovery.
Full text: IJRAS_279_Final.pdf