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The major difficulties relating to mathematical modelling of spectroscopic data are inconsistencies in spectral reproducibility and the black box nature of the modelling techniques. For the analysis of biological samples the first problem is due to biological, experimental and machine variability which can lead to sample size differences and unavoidable baseline shifts. Consequently, there is often a requirement for mathematical correction(s) to be made to the raw data if the best possible model is to be formed. The second problem prevents interpretation of the results since the variables that most contribute to the analysis are not easily revealed; as a result, the opportunity to obtain new knowledge from such data is lost.

Genetic algorithm optimization for pre-processing and variable selection of spectroscopic data