Multivariate analysis of near-infrared spectra using the G-programming language

Real-time chemometrics as envisioned by the union of instrument control, data acquisition, and chemometric analysis with a single software platform can provide substantial benefits to manufacturing concerns that require process control. Some of these benefits include faster generation of information and improved quality control. This paper describes a series of chemometric routines written in LabVIEW and demonstrates their use in predicting six properties of diesel fuel. In particular, near-infrared spectral data were used to predict the boiling point at 50% recovery, cetane number, density, freezing temperature, total aromatics, and viscosity for a series of diesel fuels.