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Bacterial identification by near-infrared chemical imaging of food-specific cards

机译:通过食品专用卡片的近红外化学成像进行细菌鉴定

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摘要

Near-infrared chemical imaging (NIR-CI) is investigated as a tool for the high-throughput analysis of self-contained microbial identification test cards for micro-organisms of concern in food. In this initial work, a NIR-CI system operating in the spectral range 1000-2350 nm was used to acquire NIR chemical images of bacterial cells deposited on a 'card', containing both the calibration and test samples. Results show that some bacteria can be identified from differences observed at unique wavelengths, and that a standard operating procedure can be developed for a particular 'card' to differentiate and hence identify the various organisms it contains using discrete wavelengths. For situations where a particular organism of concern is sought, a PLS chemometric model may offer better performance by accounting for variables that can be incorporated in the calibration without the need to know the taxonomic identity of the complete complement of bacteria present on the 'card'. Overall, the NIR-CI results obtained in this investigation show that this high throughput technique possesses the specificity required to differentiate bacteria on the basis of their NIR spectra.
机译:研究人员对近红外化学成像(NIR-CI)进行了研究,该工具可用于对食品中涉及的微生物进行独立的微生物鉴定测试卡的高通量分析。在此初始工作中,使用在1000-2350 nm光谱范围内运行的NIR-CI系统获取沉积在“卡”上的细菌细胞的NIR化学图像,其中包含校准和测试样品。结果表明,可以从在唯一波长处观察到的差异中识别出某些细菌,并且可以针对特定的“卡片”开发标准操作程序,以区分并因此使用离散波长识别其包含的各种生物。对于需要关注的特定生物的情况,PLS化学计量模型可以通过考虑可纳入校准的变量来提供更好的性能,而无需知道“卡”上存在的细菌的完整补体的分类学身份。 。总体而言,在这项研究中获得的NIR-CI结果表明,这种高通量技术具有根据细菌的NIR光谱区分细菌所需的特异性。

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