To perform advanced model based control it is important to know what is fed into a system such as a waste or biomass fired boiler or a pulp digester. In this paper, we present correlations between the lignin content of different types of wood chips and their Near-infrared (NIR) spectra. The Principal Component Regression (PCR) method is used for deriving the correlation, as well as selecting certain wave lengths. Analysis is made including different parts of the spectra in the wave length range 700 – 2500 nm. The model is then used as input to an Open Modelica pulp digester model to tune the reactivity constant of the dissolution of lignin. The lignin content of wood-chips is determined on-line through the NIR measurement at the feed to the digester. Simulations are carried out to determine the content of residual lignin on fibers at the exit (continuous digester) or at the end of a cook (batch digester). By comparing the deviation between predicted values and actual measured values the reactivity constant of the lignin is determined. The regression can be made to the NIR spectrum aside of the lignin content as such. The original content of lignin together with reactivity may then be used for optimized on-line control of the digester. It can also be used for diagnostic purposes with regard to process issues like hang-ups or channeling, as well as possible sensor faults and data reconciliation.