Abstract
This chapter describes the model-based preprocessing technique extended multiplicative signal correction (EMSC) and several of its applications in biospectroscopy. EMSC can be used for reducing a number of undesired effects in sample measurements, such as stochastic measurement noise, nonlinear instrument responses, shift problems as well as interfering effects of undesired chemical and physical variations that can create problems in multivariate calibration and in the interpretation of results. Many of these phenomena can be removed computationally by EMSC before subsequent data analysis. Here, several undesired effects are described together with respective EMSC data preprocessing and scaling techniques. Examples for applications of EMSC in biospectroscopy are provided.
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