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SING tute of SUMMARY The B-spline zero (BO) compression method has been investigated for three different raw spectrometric data sets, namely NIR reflectance, FT-IR reflectance and UV-VIS transmittance data. The data were modelled with partial least squares (PLS) regression and we have investigated the compression ratio and model dimensionality versus the ability to preserve the information of the original data as a function of knot sequence guide type, i.e. mean, standard deviation (SD) and relative standard deviation (RSD) of the variables.Generally we conclude that the investigated data can be compressed to about 20% of the original number of variables without loss of prediction ability or change in model dimensionality (number of pc's) in comparison with the original data. O

SING tute of SUMMARY The B-spline zero (BO) compression method has been investigated for three different raw spectrometric data sets, namely NIR reflectance, FT-IR reflectance and UV-VIS transmittance data. The data were modelled with partial least squares (PLS) regression and we have investigated the compression ratio and model dimensionality versus the ability to preserve the information of the original data as a function of knot sequence guide type, i.e. mean, standard deviation (SD) and relative standard deviation (RSD) of the variables.Generally we conclude that the investigated data can be compressed to about 20% of the original number of variables without loss of prediction ability or change in model dimensionality (number of pc's) in comparison with the original data. O