Many pre-processing methods aim at improving calibration model robustness in relation to the effect of an influence factor G. Orthogonal projection methods, such as OSC (Orthogonal Signal Correction) or EPO (External Parameter Orthogonalisation), are particularly well suited to process existing calibration databases. This work proposes a pre-processing strategy for the numerous cases where G variability is missing in the existing calibration database, and where effects of G and Y, the variable of interest, are not independent. The application in this study concerns the correction of the light scattering effect in NIR turbid spectra of grape musts. Ethanol content was thus correctly predicted (RMSEP = 0.5°) on very turbid samples (below 3000 NTU), much better than using all other geometric or multidimensional existing pre-processings tested.