Assessment of new constraints applied to the alternating least squares method

The introduction of constraints in multivariate curve resolution methods, such as the Alternating Least Squares (ALS), is commonly used to limit the span of possible solutions, guiding the iterative process to a final result as close as possible to the true situation. In the present work, two modifications of the unimodality constraint and a new constraint for chromatographic concentration profiles related to the prevention of fronting have been checked. Simulated data sets as well as real data have been used to evaluate the effect of these new constraints in the resolution results. The parameters measured to assess the goodness of the constraints are related to the recovery of the concentration profiles and the quality of the data fit.