Department of Nutrition and Food Science, University of Maryland, College Park, MD 20742, USA.
Food Addit Contam Part A Chem Anal Control Expo Risk Assess. 2009 Oct;26(10):1396-401. doi: 10.1080/02652030903013310.
Rapid detection of deoxynivalenol (DON) in cereal-based food and feed has long been the goal of regulators and manufacturers. As non-destructive approaches, infrared (IR) and near-infrared (NIR) spectroscopic techniques have been used for the prediction and classification of contaminated single-kernel and ground grain without any DON extraction steps. These methods, however, are hindered by the intense and broad spectral bands attributed to naturally occurring moisture. Raman spectroscopy could be an alternative to IR and NIR due to its insensitivity to water and fewer overlapped bands. This study explored the feasibility of the Raman technique for rapid and non-destructive screening of DON-contaminated wheat and barley meal. The advantages of this technique include the use of a 1064-nm NIR excitation laser that reduces interference from fluorescence of biological compounds in wheat and barley, the use of a simple intensity-intensity algorithm at two unique frequencies, plus the technique's ease of sample preparation. The results indicate that the simple algorithm, as well as principal component analysis applied to the Raman spectra, can be used to classify low from high DON grain.
快速检测谷物类食品和饲料中的脱氧雪腐镰刀菌烯醇（DON）一直是监管机构和制造商的目标。作为一种非破坏性的方法，红外（IR）和近红外（NIR）光谱技术已被用于预测和分类污染的单粒和研磨谷物，无需进行任何 DON 提取步骤。然而，这些方法受到归因于天然水分的强烈和宽光谱带的阻碍。由于拉曼光谱对水不敏感且重叠带较少，因此它可能是 IR 和 NIR 的替代方法。本研究探讨了拉曼技术在快速、非破坏性筛选 DON 污染的小麦和大麦粉中的可行性。该技术的优点包括使用 1064nm 的近红外激发激光，可减少小麦和大麦中生物化合物荧光的干扰，使用两个独特频率的简单强度-强度算法，以及该技术易于制备样品。结果表明，简单的算法以及应用于拉曼光谱的主成分分析可用于对低 DON 谷物和高 DON 谷物进行分类。
