Near-infrared hyperspectral imaging for deoxynivalenol and ergosterol estimation in wheat samples
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The present study aimed to evaluate the use of hyperspectral imaging (HSI)-NIR spectroscopy to assess the presence of DON and ergosterol presence in wheat samples through prediction and classification models. To achieve these objectives, a first set of bulk samples was scanned by HSI-NIR and divided into two subsamples, in which one that was analysed for ergosterol and the other another that was analysed for DON by HPLC. Thise method was repeated for a second larger set to build prediction and classification models. All the spectra were pretreated and statistically processed by PLS and LDA. The pPrediction models presented a RMSEP of 1.17 mg/kg and 501 µg/kg for ergosterol and DON, respectively. Classification achieved an encouraging accuracy of 85.4% for an independent validation set of samples. The results confirm that HSI-NIR may be a suitable technique for ergosterol quantification and DON classification of samples according to the DON EU legal limit for DON.
Is part ofFood Chemistry, 2021, vol. 341, part 2, article 128206
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