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Comparison of visible and near infrared reflectance spectroscopy for the detection of faeces/ingesta contaminants for sanitation verification at slaughter plants

机译:可见光和近红外反射光谱的比较,用于检测粪便/肠毒素,用于屠宰厂的卫生验证

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Visible and near infrared (NIR) spectra were acquired to explore the potential for the discrimination of faeces/ingesta ("F/I") objectives from rubber belt and stainless steel ("RB/SS") backgrounds by using several wavelengths. Spectral features of "F/I" objectives and "RB/SS" backgrounds showed large differences in both visible and NIR regions, due to the diversity of their chemical compositions. These spectral distinctions formed the basis on which to develop simple three-band ratio algorithms for the classification analysis. Meanwhile, score-score plots from principal component analysis (PCA) indicated the obvious cluster separation between "F/I" objectives and "RB/SS" backgrounds, but the corresponding loadings did not show any specific wavelengths for developing effective algorithms. Furthermore, two-class soft independent modelling of class analogy models were developed to compare the correct classifications with those from the ratio algorithms. Results indicated that using ratio algorithms in the visible or NIR region could separate "F/I" objectives from "RB/SS" backgrounds with a success rate of over 97%.
机译:获取可见和近红外(NIR)光谱,以探索通过使用多个波长从橡胶带和不锈钢(“ RB / SS”)背景中区分粪便/肠梗(“ F / I”)物镜的潜力。 “ F / I”物镜和“ RB / SS”背景的光谱特征在可见光和近红外区域均显示出很大差异,这是由于其化学成分的差异。这些光谱差异构成了开发用于分类分析的简单三频比算法的基础。同时,来自主成分分析(PCA)的得分得分图显示了“ F / I”目标和“ RB / SS”背景之间明显的群集分离,但是相应的载荷并未显示任何特定的波长来开发有效的算法。此外,开发了类比类模型的两类软独立建模,以将正确的分类与比率算法的分类进行比较。结果表明,在可见或近红外区域使用比率算法可以将“ F / I”物镜与“ RB / SS”背景分离,成功率超过97%。

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