Frequently, a calibration model is adapted after being transferred to another instrument by, e.g., direct standardization Ž .
Ž . DS or piecewise direct standardization PDS . For this, a subset from the calibration set should be measured on both instruments. Usually, however, the calibration samples cannot be measured on both instruments. Another approach is to make the model robust with respect to transfer to another instrument during the development of the model, by data preprocessing. In this paper, the robustness of the calibration model is enhanced by using variable selection as data preprocessing. In the case under consideration, variable selection consists in the calculation of a calibration model with a subset of the original wave-Ž . lengths of spectroscopic data that retains its predictive ability when it is transferred to another instrument. Both approaches Ž Ž . . variable selection and P DS are applied to the transferability of a PLS model which determines the water content in tablets. Ž . To this end, 140 tablets were measured on 2 near-infrared NIR reflectance instruments. It has been found that variable Ž . selection by simulated annealing SA enhances the model's robustness with respect to model transfer and also improves its predictive ability.