Mid-Infrared Spectral Characterization of Aflatoxin Contamination in Peanuts

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Date
2012-09-11
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Publisher
Virginia Tech
Abstract

Contamination of peanuts by secondary metabolites of certain fungi, namely aflatoxins present a great health hazard when exposed either at low levels for prolonged times (carcinogenic) or at high levels at once (poisonous). It is important to develop an accurate and rapid measurement technique to trace the aflatoxin and/or source fungi presence in peanuts. Thus, current research focused on development of vibrational spectroscopy based methods for detection and separation of contaminated peanut samples.

Aflatoxin incidence, as a chemical contaminant in peanut paste samples, was investigated, in terms of spectral characteristics using FTIR-ATR. The effects of spectral pre-processing steps such as mean-centering, smoothing the 1st derivative and normalizing were studied. Logarithmic method was the best normalization technique describing the exponentially distributed spectral data. Spectral windows giving the best correlation with respect to increasing aflatoxin amount led to selection of fat associated spectral bands. Using the multivariate analysis tools, structural contributions of aflatoxins in peanut matrix were detected. The best region was decided as 3028-2752, 1800-1707, 1584-1424, and 1408-1127 cm-1 giving correlation coefficient for calibration (R2C), root mean square error for calibration (RMSEC) and root mean square error for prediction (RMSEP) of 98.6%, 7.66ppb and 19.5ppb, respectively. Applying the constructed partial least squares model, 95% of the samples were correctly classified while the percentage of false negative and false positive identifications were 16% and 0%, respectively.

Aspergillus species of section Flavi and the black fungi, A. niger are the most common colonists of peanuts in nature and the majority of the aflatoxin producing strains are from section Flavi. Seed colonization by selected Aspergillus spp. was investigated by following the chemical alterations as a function of fungal growth by means of spectral readouts. FTIR-ATR was utilized to correlate spectral characteristics to mold density, and to separate Aspergillus at section, species and strain levels, threshold mold density values were established. Even far before the organoleptic quality changes became visually observable (~10,000 mold counts), FTIR distinguished the species of same section. Besides, the analogous secondary metabolites produced increased the similarity within the spectra even their spectral contributions were mostly masked by bulk peanut medium; and led to grouping of species producing the same mycotoxins together.

Aflatoxigenic and non-aflatoxigenic strains of A. flavus and A. parasiticus were further studied for measurement capability of FTIR-ATR system in discriminating the toxic streams from just moldy and clean samples. Owing to increased similarity within the collected spectral data due to aflatoxin presence, clean samples (having aflatoxin level lower than 20 ppb, n=44), only moldy samples (having aflatoxin level lower than 300 ppb, n=28) and toxic samples (having aflatoxin level between 300-1200 ppb, n=23) were separated into appropriate classes (with a 100% classification accuracy).

Photoacoustic spectroscopy (PAS) is a non-invasive technique and offers many advantages over more traditional ATR system, specifically, for in-field measurements. Even though the sample throughput time is longer compared to ATR measurements, intact seeds can be directly loaded into sample compartment for analysis. Compared to ATR, PAS is more sensitive to high moisture in samples, which in our case was not a problem since peanuts have water content less than 10%. The spectral ranges between: 3600-2750, 1800-1480, 1200-900 cm-1 were assigned as the key bands and full separation between Aspergillus spp. infected and healthy peanuts was obtained. However, PAS was not sensitive as ATR either in species level classification of Aspergillus invasion or toxic-moldy level separation. When run for separation of aflatoxigenic versus non-aflatoxigenic batches of samples, 7 out of 54 contaminated samples were misclassified but all healthy peanuts were correctly identified (15 healthy/ 69 total peanut pods).

This study explored the possibility of using vibrational spectroscopy as a tool to understand chemical changes in peanuts and peanut products to Aspergillus invasion or aflatoxin contamination. The overall results of current study proved the potential of FTIR, equipped with either ATR or PAS, in identification, quantification and classification at varying levels of mold density and aflatoxin concentration. These results can be used to develop quality control laboratory methods or in field sorting devices.

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Keywords
Peanut, Aflatoxin, Aspergillus species, PLS regression, Fourier Transform Infrared Spectroscopy, Attenuated Total Reflectance, Photoacoustic Spectroscopy, Discriminant Analysis
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