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 pro cess control. Some of these benefits include faster generation of informati on and improved quality control. This paper describes a series of chemometr ic 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 diese l fuels.