Non-destructive detection of mycotoxins in maize kernels using diffuse reflectance spectroscopy
Non-destructive detection of mycotoxins in maize kernels using diffuse reflectance spectroscopy
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DOI：
10.1016/j.foodcont.2016.05.039
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发表时间：
2016-12
期刊：
影响因子：
6
通讯作者：
L. Smeesters;W. Meulebroeck;S. Raeymaekers;H. Thienpont
中科院分区：
文献类型：
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作者：
L. Smeesters;W. Meulebroeck;S. Raeymaekers;H. Thienpont
脱氧雪腐镰刀菌醇是世界范围内农作物中含量最多的污染物之一。它在食品和饲料产品中的存在造成健康风险并造成经济损失。迄今为止，脱氧雪腐镰刀菌醇主要是通过基于样品的、耗时的化学分析来检测的。为了获得一种无损检测未经加工的固体玉米籽粒中的脱氧雪腐烯醇，我们研究了紫外-可见-近红外漫反射光谱。具体来说，我们提出了一个两阶段的光谱测量程序，允许表征和鉴定在未磨碎的玉米粒脱氧雪腐镰刀菌醇。第一阶段的重点是表征最佳照明和检测波长，通过测量玉米籽粒的平均污染，使用250毫米反射积分球。第二个测量阶段通过使用30毫米反射积分球测量单个玉米粒上的局部污染，实现对受污染玉米颗粒的准确分类。我们首先对低（150 ppb）和高（1388 ppb）天然脱氧雪腐菌醇污染玉米籽粒的反射光谱进行了表征和比较。此外，我们通过参考脱氧雪腐菌醇污染玉米粉（1840±30 ppb）的表征验证了这些测量结果。在700 nm和1400 nm之间可以观察到低污染和高污染样品的光谱对比。此外，可以定义检测标准，使我们能够成功地将受污染的玉米批次分为高（18184 ppb）和低（654 ppb）污染的子样本。因此，这验证了两阶段测量方法，并说明了漫反射光谱作为玉米中脱氧雪腐烯醇浓度测量的宝贵工具的使用，为基于实时无损工业扫描的检测铺平了道路。
Deoxynivalenol is one of the most abundant contaminants in crops worldwide. Its presence in food and feed products causes health risks and induces economic losses. To date, deoxynivalenol is mostly detected by sample-based, time-consuming chemical analyses. To obtain a non-destructive detection of deoxynivalenol in unprocessed, solid maize kernels, we investigate UV–Vis–NIR diffuse reflection spectroscopy. Specifically, we propose a two-stage spectroscopic measurement procedure, allowing the characterization and identification of deoxynivalenol in ungrounded maize kernels. The first stage focuses on the characterization of the optimum illumination and detection wavelengths, by the measurement of the mean contamination of a collection of maize kernels, using a 250 mm-reflection integrating sphere. The second measurement stage enables an accurate classification of contaminated maize grains, by the measurement of the local contamination on individual kernels, using a 30 mm-reflection integrating sphere. We first characterized and compared the reflection spectra of low (150 ppb) and high (1388 ppb) natural deoxynivalenol-contaminated maize kernels. Moreover, we validated these measurement results by the characterization of a reference deoxynivalenol-contaminated maize powder (1840 ± 30 ppb). A spectral contrast between the low and high contaminated samples could be observed between 700 nm and 1400 nm. Furthermore, a detection criterion could be defined, allowing us to successfully classify a contaminated maize batch into a high (18184 ppb) and low (654 ppb) contaminated subsample. As a result, this verifies the two-stage measurement approach and illustrates the use of diffuse reflection spectroscopy as a valuable tool for the measurement of deoxynivalenol concentrations in maize, paving the way for real-time non-destructive industrial scanning-based detection.