食品科学 ›› 2019, Vol. 40 ›› Issue (2): 293-297.doi: 10.7506/spkx1002-6630-20170906-097

• 安全检测 • 上一篇    下一篇

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

沈飞1,刘潇1,裴斐1,李彭1,姜大峰2,刘琴1   

  1. (1.江苏高校现代粮食流通与安全协同创新中心,江苏高校粮油质量安全控制及深加工重点实验室,南京财经大学食品科学与工程学院,江苏?南京 210023;2.山东省疾病预防控制中心,山东?济南 250014)
  • 出版日期:2019-01-25 发布日期:2019-01-22
  • 基金资助:
    “十三五”国家重点研发计划重点专项(2017YFC16006001);国家自然科学基金面上项目(31772061); 国家自然科学基金青年科学基金项目(21705095);国家农产品质量安全风险评估项目(GJFP2017001); 浙江省重点研发计划项目(2008C02050);江苏高校优势学科建设工程资助项目

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

SHEN Fei1, LIU Xiao1, PEI Fei1, LI Peng1, JIANG Dafeng2, LIU Qing1   

  1. (1. Collaborative Innovation Center for Modern Grain Circulation and Safety, Key Laboratory of Grains and Oils Quality Control and Processing, College of Food Science and Engineering, Nanjing University of Finance and Economics, Nanjing 210023, China; 2. Shandong Center for Disease Control and Prevention, Jinan 250014, China)
  • Online:2019-01-25 Published:2019-01-22

摘要: 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RP2、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RP2、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。

关键词: 小麦, 呕吐毒素, ATR-FTIR, 定量检测, 偏最小二乘回归, 逐步多元线性回归

Abstract: 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.

Key words: wheat, DON, ATR-FTIR, quantitative detection, PLSR, SMLR

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