TY - JOUR
T1 - Mid-infrared spectroscopy for discrimination and classification of Aspergillus spp. contamination in peanuts
AU - Kaya-Celiker, Hande
AU - Mallikarjunan, P. Kumar
AU - Kaaya, Archileo
N1 - Publisher Copyright:
© 2014 Elsevier Ltd.
PY - 2015/6/1
Y1 - 2015/6/1
N2 - 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.
AB - 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.
KW - Aspergillus species
KW - Discriminant analysis
KW - FTIR-ATR
KW - PLS regression
KW - Peanut
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U2 - 10.1016/j.foodcont.2014.12.013
DO - 10.1016/j.foodcont.2014.12.013
M3 - Article
AN - SCOPUS:84920885598
SN - 0956-7135
VL - 52
SP - 103
EP - 111
JO - Food Control
JF - Food Control
ER -