Multivariate calibration applied to a highly interfering chemical system: The simultaneous spectrophotometric determination of aluminium and iron in plants using xylenol orange and partial least-squares regression Original Research Article

A partial least squares (PLS) calibration model was developed for the simultaneous spectrophotometric determination of Al and Fe in plant extracts by using an excess of xylenol orange as the cromogenic reagent. Experimental conditions were established to reduce interferences, decrease system complexity and produce a robust procedure that could be used for routine analysis. The spectra should be recorded from 2 to 4 h after mixing the reagents. Ethanolic solutions were used to improve the formation of the Al-XO complexes. The best calibration model was obtained using the PLS-2 algorithm after mean centering the data with five latent variables. Under the experimental conditions adopted, only Zn was found to be a potential interfering species with the plant extracts used. Validation of the proposed spectrophotometric method was performed by running nine plant samples from the 1997 International Plant-Analytical Exchange (IPE) which were also analyzed by ICP-AES for further correlation. The proposed procedure showed to be useful for prediction of Al and Fe values from 12.5 to 2500 mg kg−1 in plant dry weight basis.