In this study, Aspergillus spp., common colonists in peanut, were characterized, classified and quantified using FTIR coupled with ATR accessory. FTIR-ATR spectral data of infected peanut samples were preprocessed (mean-centering, smoothing the 1st derivative), and used for the PLS regression analysis for quantitative results. Very high R2 values (96.20-99.98%) together with low error of RMSEC values (0.014-0.153 LogCFU/g of peanut) were obtained. Even, the spectrum of peanut matrix was dominant at early stages of invasion (≤2.5LogCFU/g peanut), resulting in section separation (Nigri from Flavi) and at higher population (>4LogCFU/g, species level separation (Aspergillus alliaceus, Aspergillus caelatus, Aspergillus flavus, Aspergillus parasiticus, and Aspergillus tamari) was observed. The accuracy of correct classification increased proportionally with fungal invasion level and 100% correct classification was reached when the cell level was LogCFU/g=4.5-5. Samples with similar secondary metabolites (toxin producers) grouped close-by in PC score diagrams for all levels of fungal growth. Results highlight the possible implementation of FTIR-ATR model to detect infected peanuts even at early stages of invasion; besides, to prove the potential separation capability in terms of species and their secondary metabolites.
Bibliographical noteFunding Information:
Authors wish to express their gratitude to Peanut CRSP program of USAID for providing the financial support to the project. Authors also would like to extend their gratitude to Drs. Maria Elisa Christie, Justin Barone and Charity Mutegi for their participation in the project.
© 2014 Elsevier Ltd.
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- Aspergillus species
- Discriminant analysis
- PLS regression