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Using Molecular Spectroscopic Techniques (NIR and ATR-FT/MIR) Coupling with Various Chemometrics to Test Possibility to Reveal Chemical and Molecular Response of Cool-Season Adapted Wheat Grain to Ergot Alkaloids

The objectives of this study were to explore the possibility of using near infrared (NIR) and Fourier transform mid-infrared spectroscopy—attenuated total reflectance (ATR-FT/MIR) molecular spectroscopic techniques as non-invasive and rapid methods for the quantification of six major ergot alkaloids...

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Detalles Bibliográficos
Autores principales: Shi, Haitao, Yu, Peiqiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9962322/
https://www.ncbi.nlm.nih.gov/pubmed/36828464
http://dx.doi.org/10.3390/toxins15020151
Descripción
Sumario:The objectives of this study were to explore the possibility of using near infrared (NIR) and Fourier transform mid-infrared spectroscopy—attenuated total reflectance (ATR-FT/MIR) molecular spectroscopic techniques as non-invasive and rapid methods for the quantification of six major ergot alkaloids (EAs) in cool-season wheat. In total, 107 wheat grain samples were collected, and the concentration of six major EAs was analyzed using the liquid chromatography-tandem mass spectrometry technique. The mean content of the total EAs—ergotamine, ergosine, ergometrine, ergocryptine, ergocristine, and ergocornine—was 1099.3, 337.5, 56.9, 150.6, 142.1, 743.3, and 97.45 μg/kg, respectively. The NIR spectra were taken from 680 to 2500 nm, and the MIR spectra were recorded from 4000–700 cm(−1). The spectral data were transformed by various preprocessing techniques (which included: FD: first derivative; SNV: standard normal variate; FD-SNV: first derivative + SNV; MSC: multiplicative scattering correction; SNV-Detrending: SNV + detrending; SD-SNV: second derivative + SNV; SNV-SD: SNV + first derivative); and sensitive wavelengths were selected. The partial least squares (PLS) regression models were developed for EA validation statistics. Results showed that the constructed models obtained weak calibration and cross-validation parameters, and none of the models was able to accurately predict external samples. The relatively low levels of EAs in the contaminated wheat samples might be lower than the detection limits of the NIR and ATR-FT/MIR spectroscopies. More research is needed to determine the limitations of the ATR-FT/MIR and NIR techniques for quantifying EAs in various sample matrices and to develop acceptable models.