Zara, A. J.; Machado, S. S.; Bulhoes, L. 0.; Benedetti, A. V.; Rabockai, T. J. Electroanal. Chem. Interfacial Electrochem. 1987, 221, 165-174. Montenegro, M. I.; Pletcher, D. J. Nectroanal. Chem. Interfaclel E k t r o d "Three closely related problems associated with using multlvariate callbratlon methods In spectroscopy have surfaced recently. The flrst problem involves the deslre to transport a callbratlon model developed on one Instrument to a second or even multiple Instruments. Dlfferences between the prlmary and secondary Instruments whlch can occur for a varlety of reasons can lead to erroneous results, thereby prohibltlng transferring the callbration model and necessltating the tranqml d the callbratkn samples. The second problem occurs when instruments change over time (e.g. wavelength shift) for any reason. Again, using a calibration model for analysls when the Instrument responses are altered after the tlme calibration was performed is problematic. The third problem Is caused by the variation between samples from dlfferent productlon batches. The calibratkn model buitl from one batch mlght not be appilcable to another batch. Using the mathematlcs of multivariate cailbratlon, four dlfferent a p proaches to solving these two problems have been derived and tested wtlh computer simulation. The four standardlzatbn methods proceed by acquiring the spectra of a well-chosen subset of the calibration samples and then either correctlng the primary callbratlon model for use on secondary Instruments or correcting the spectra acqulred on the secondary Instrument to account for the response dlfferences. While standardizatlon does not outperform uslng the entire callbratlon set for recalibration, only a 1.2-1.6 times larger error Is obialned by standardlration In the slmuiatlons and a study of a near-infrared data set.

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