In spectroscopy, multivariate calibrations more than often include a pre-processing step to reduce the effect of unwanted (not Y-related) sources of variability. Because there are many types of background noise, there are many pre-treatment methods. It is therefore tedious to select and/or combine the best pre-treatments. This article proposes to combine several pre-treatments through the use of sequential and orthogonalized partial least squares (SO-PLS), thus leading to a boosting method. The performances and properties of this new method, called Sequential Preprocessing through ORThogonalization (SPORT), are compared to those of a previously published stacking method. SPORT demonstrates very good calibration performances, but also the ability to make significant pretreatment selections.