ATR-FTIR在小麦及其制品呕吐毒素污染水平快速测定中的应用

Rapid Identification of Deoxynivalenol Contamination in Wheat and Its Products by Attenuated Total ReflectanceFourier Transform Infrared Spectroscopy(ATR-FTIR)

为快速测定小麦及其制品呕吐毒素(deoxynivalenol,DON)污染情况,搜集小麦、面粉及面粉制品共98份,利用衰减全反射-傅里叶变换红外光谱(attenuated total reflectance-Fourier transform infrared spectroscopy,ATR-FTIR)获取样品在4 000～600 cm^(-1)的光谱信息,对样品中的DON含量建立了基于偏最小二乘回归(partial least squares regression,PLSR)分析和逐步多元性回归(stepwise multiple linear regression,SMLR)分析方法的定量分析模型。结果显示,不同DON含量样品在1 740、1 648、1 549 cm^(-1)和1 300～900 cm^(-1)等波段处的吸收值存在显著差异。PLSR和SMLR均能较好预测样品中的DON含量,其中PLSR模型的预测集决定系数R_P^2、预测均方根误差(root mean squared error of prediction,RMSEP)和相对分析偏差(residual predictive deviation,RPD)值分别为0.86、0.438 mg/kg和2.6。SMLR结合9个波长所建模型的R_P^2、RMSEP和RPD值分别为0.86、0.426 mg/kg和2.6。结果表明,ATR-FTIR用于小麦及其制品DON污染快速分析具有可行性。

For rapid detection of the contamination level of deoxynivalenol (DON) in wheat and its products, a total of 98 samples of wheat, flour and flour products were collected and subjected to attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) analysis in the wavenumber range of 4 000 to 600 cm-1. Quantitative models between ATR-FTIR spectra and DON concentration were established by partial least squares regression analysis (PLSR) or stepwise multiple linear regression (SMLR). The results showed that the absorption values of samples with various DON contents were markedly different at 1 740, 1 648, 1 549 and 900–1 300 cm-1. Both PLSR and SMLR models could effectively predict DON contamination in samples. The coefficient of determination for prediction (RP2), root mean square error for prediction (RMSEP) and residual predictive deviation (RPD) of the PLSR model were 0.86, 0.438 mg/kg and 2.6, respectively. The SMLR model built with 9 wavenumbers was found to be optimal, with RP2, RMSEP and RPD of 0.86, 0.426 mg/kg and 2.6, respectively. These results indicated that ATR-FTIR offers the feasibility for rapid determination of wheat samples contaminated by DON.