Abstract

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%.

© 2006 NIR Publications

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