Application of iterative space shrinkage approach i VISSA for accurate quantification of spectrally overlapping phenolic compounds in water matrices by multivariate calibration

Environmental context Phenol mixtures are an important pollutant due to their high toxicity on the aquatic environment. In this work, we developed a multivariate calibration model to detect phenol and nitro-derivatives in complex water bodies without the need for using complex and expensive analytical procedures. The developed model, using an iterative space shrinkage approach and partial least square regression, was able to select the most informative spectral data for phenols that needed for their detection at trace levels in natural waters.