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Validation and transferability study of a method based on near-infrared hyperspectral imaging for the detection and quantification of ergot bodies in cereals Rapid Detection in Food and Feed

机译:基于近红外高光谱成像的谷物麦角体检测与定量方法的验证与转移性研究食品和饲料中的快速检测

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摘要

In recent years, near-infrared (NIR) hyperspectral imaging has proved its suitability for quality and safety control in the cereal sector by allowing spectroscopic images to be collected at single-kernel level, which is of great interest to cereal control laboratories. Contaminants in cereals include, inter alia, impurities such as straw, grains from other crops, and insects, as well as undesirable substances such as ergot (sclerotium of Claviceps purpurea). For the cereal sector, the presence of ergot creates a high toxicity risk for animals and humans because of its alkaloid content. A study was undertaken, in which a complete procedure for detecting ergot bodies in cereals was developed, based on their NIR spectral characteristics. These were used to build relevant decision rules based on chemometric tools and on the morphological information obtained from the NIR images. The study sought to transfer this procedure from a pilot online NIR hyperspectral imaging system at laboratory level to a NIR hyperspectral imaging system at industrial level and to validate the latter. All the analyses performed showed that the results obtained using both NIR hyperspectral imaging cameras were quite stable and repeatable. In addition, a correlation higher than 0.94 was obtained between the predicted values obtained by NIR hyperspectral imaging and those supplied by the stereo-microscopic method which is the reference method. The validation of the transferred protocol on blind samples showed that the method could identify and quantify ergot contamination, demonstrating the transferability of the method. These results were obtained on samples with an ergot concentration of 0.02 % which is less than the EC limit for cereals (intervention grains) destined for humans fixed at 0.05 %. [Figure not available: see fulltext.]
机译:近年来,近红外(NIR)高光谱成像通过允许在单核水平上收集光谱图像而证明了其在谷物行业中质量和安全控制的适用性,这是谷物控制实验室非常感兴趣的。谷物中的污染物尤其包括诸如稻草,其他农作物的谷物和昆虫的杂质,以及诸如麦角(麦角菌(Claviceps purpurea)的菌核)的不良物质。对于谷物行业,麦角的存在由于其生物碱含量而对动物和人类造成高毒性风险。进行了一项研究,其中开发了基于谷物近红外光谱特征的完整麦角麦角体检测程序。这些用于基于化学计量工具和从NIR图像获得的形态学信息建立相关的决策规则。该研究试图将该程序从实验室级的在线NIR高光谱成像系统试点转移到工业级的NIR高光谱成像系统,并对其进行验证。所有执行的分析表明,使用两个NIR高光谱成像相机获得的结果都非常稳定且可重复。另外,在通过NIR高光谱成像获得的预测值与通过作为参考方法的立体显微镜方法提供的预测值之间,获得了高于0.94的相关性。对盲样品上转移方案的验证表明,该方法可以鉴定和定量麦角污染,证明了该方法的可转移性。这些结果是在麦角浓度为0.02%的样品上获得的,该麦角浓度低于预定为0.05%的人类谷物(干预谷物)的EC限值。 [图不可用:请参见全文。]

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