[Study of quantitative calibration model suitability in near-infrared spectroscopy analysis]

Near-infrared spectroscopy is a fast, high efficiency and low cost analytical technique, that depended on analytical models which are built through near-infrared spectra, the primary method results of calibration set and chemometrics methods. The reliability of analytical results mostly depends on the suitability of analytical model to unknown samples. To judge the suitability of analytical model, a new method is presented that combine principle factor analysis (PCA) and Mahalanobis distance. It is different with traditional method, that the Mahalanobis distance is calculated through PCA factor scores. It can avoid the wavelengths selection problem in traditional method of spectral Mahalanobis distance. Through the determination of cetane number of diesel fuel, some factors that affect model suitability judgement are discussed.