Abstract

The current mycotoxin safety concerns demand the availability of reliable and selective control systems to measure the content of mycotoxins present in daily food. To address this, we report a prospective analytical tool involving the application of a flow injection mass spectrometry (FI/MS) tandem artificial neural network (ANN) strategy to predict the amount of ochratoxin A and B (OTA and OTB) in beer. Triple stage mass spectrometry (MS3) aided by chromatographic separation was applied as a reference method for comparison. 0.1% formic acid and methanol were used to convert ochratoxins into their respective ions under negative MS polarity. For experiments involving MS3, ochratoxins were separated by reversed-phase liquid chromatography in a 6 min run, ionised using electrospray ionisation, and detected by tandem mass spectrometry. Analyte-specific mass-to-charge ratios were used to perform quantitation in MS3 mode. For experiments involving FI/MS, no chromatographic separation was performed. Approximately 2% of the mass spectra was used for model construction. ANN models representing each ochratoxin were individually trained and validated using three sets of matrix-matched and matrix-free calibration curves at nine concentration levels of 2.5, 10, 25, 50, 100, 200, 300, 400 and 500 μg/l. Quintuplicate analyses were made in FI/ MS mode providing a total of 270 spectra for both OTA and OTB. Single measurement was made for each sample in MS3 mode. A root-mean-square error value of <1% was reported for both ochratoxin models in beer. Limits of quantitation were determined to be 0.2 μg/kg for both MS3 and FI/MS mode. Recovery assessment was performed over two days using beer blanks (n=6) spiked at three concentration levels of 5, 100 and 200 μg/kg. Extraction using acetonitrile provided excellent recovery ranges of 88 to 102% for both MS techniques. Relative standard deviations of 10% or better were achieved for interday spike recovery experiments. The successful utilisation of FI/MS without performing chromatographic separation implies the availability of a new analytical tool relevant to the field of mycotoxin analysis, possibly offering analyte specificity exceeding the capability of MS3 through chemometry.

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