Replicate analysis and outlier detection in multivariate NIR calibration, illustrated with biofuel analysis Original Research Article

A biofuel data set is used to show multivariate calibration and prediction of the vital parameter moisture content from near-infrared spectra. At-line sampling of heterogeneous biofuel materials and near-infrared spectroscopy (1050 wavelengths) gave prediction errors of 3 and 1% for the moisture reference. The calibration methodology and prediction diagnostics are presented in the paper with an emphasis of using replicates and duplicates for outlier detection.