Mid-infrared spectroscopy for discrimination and classification of Aspergillus spp. contamination in peanuts

Abstract

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 Log CFU/g of peanut) were obtained. Even, the spectrum of peanut matrix was dominant at early stages of invasion (≤2.5 Log CFU/g peanut), resulting in section separation (Nigri from Flavi) and at higher population (>4 Log CFU/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 Log CFU/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.