Affiliation:
1. AFRC Institute for Grassland and Animal Production, Hurley, Maidenhead, Berks SL6 5LR, U.K.
Abstract
Particle size, scatter, and multi-collinearity are long-standing problems encountered in diffuse reflectance spectrometry. Multiplicative combinations of these effects are the major factor inhibiting the interpretation of near-infrared diffuse reflectance spectra. Sample particle size accounts for the majority of the variance, while variance due to chemical composition is small. Procedures are presented whereby physical and chemical variance can be separated. Mathematical transformations—standard normal variate (SNV) and de-trending (DT)—applicable to individual NIR diffuse reflectance spectra are presented. The standard normal variate approach effectively removes the multiplicative interferences of scatter and particle size. De-trending accounts for the variation in baseline shift and curvilinearity, generally found in the reflectance spectra of powdered or densely packed samples, with the use of a second-degree polynomial regression. NIR diffuse reflectance spectra transposed by these methods are free from multi-collinearity and are not confused by the complexity of shape encountered with the use of derivative spectroscopy.
Subject
Spectroscopy,Instrumentation
Reference6 articles.
1. The Use of Principal Components in the Analysis of Near-Infrared Spectra
2. Martens H., Jensen S. A., and Geladi P., in Proceedings of the Nordic Symposium on Applied Statistics (Stokkand Forlag, Stavenger, Norway, 1983), pp. 235–268.
3. A designed experiment for the examination of techniques used in the analysis of near infrared spectra. Part 1. Analysis of spectral structure
4. Kendall M. G. and Stewart, in The Advanced Theory of Statistics, (Charles Griffin and Company Limited London, 1977), Vol. 1, p. 49.
Cited by
2965 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献