Validation of a multivariate calibration method for the determination of chlorophyll a, b and c and their corresponding pheopigments

This work concerns the validation of a previously described multivariate method for determining chlorophylls and their corresponding pheopigments. The meaning of the term validation is discussed, and the work is divided into two parts, concerning model validation and method validation. The model validation showed that 40 standards are sufficient to ensure that the Y-domain is adequately spanned, and that differentiation of the data improves the models. The wavelength range was restricted to 510–770 nm, thus, eliminating interfering signals from carotenoids that had not been included in the calibration solutions. This restriction does not affect the predictive ability towards any analytes except pheophytin a. For accurate predictions of pheophytin a the wavelength region between 350 and 415 nm was included in the model. All model evaluations were based on partial least squares regression for one y-variable (PLS1). A criterion used to quantify the performance of the model was the deviation, which is an estimate of variance calculated for predictions of samples, taking into account the model’s predictive ability, the leverage and the x-residuals. In the method validation section, predictions of samples by the proposed method are compared with results obtained using an HPLC reference method. It was found for chlorophyll a that the root mean square error of cross validation (RMSECV) calculated from the model was several times higher than the corresponding root mean square error of prediction (RMSEP) calculated from the HPLC analysis. A likely explanation for this is that the RMSECV is determined in the presence of severely interfering compounds, a desired consequence of spanning the Y-space. Samples were extracted (then measured and predicted) from algal cultures, representing six different taxonomic divisions of phytoplankton. The pigment composition of these species is known, so the analyst knows in advance which chlorophylls are present. Predictions by the models are consistent with a priori knowledge of the pigment composition. To evaluate the potential of these models to deal with data recorded by different instruments, the absorption spectra for a set of samples were registered with two instruments. The results show that there is a minor and negligible bias between the predictions obtained using these instruments, probably due to a slight shift in the wavelengths recorded by them.