A new quantitative analysis method for mixtures of calcium carbonate (CaCO3), calcium sulphite hemihydrate (CaSO3.1/2H(2)O) and gypsum (CaSO4.2H(2)O) by FTIR spectroscopy is developed. The method involves the FTIR analysis of powder mixtures of several compositions on KBr disc specimens. Intensities of the resulting absorbance peaks for CaCO3, CaSO3.1/2H(2)O and CaSO4.2H(2)O at 1453, 980, 1146 cm(-1) were used as input data for an artificial neural network (ANN) model, the output being the weight percent compositions of the mixtures. The training and testing data were randomly separated from the complete original data set. Testing of the model was done with successfully low-average error levels. The utility of the model is in the potential ability to use FTIR spectrum to predict the proportions of the three substances in unknown mixtures. (C) 2003 Elsevier B.V. All rights reserved.