Abstract

NIR spectroscopic models lack robustness towards the influence of external parameters. Orthogonalisation techniques have demonstrated their ability to improve model robustness with regard to external parameter effects. The dynamic orthogonal projection (DOP) method is applied to the correction of the growing season effect on wheat protein content prediction using NIR spectroscopy. A few reference samples are measured at the beginning of each harvest. For each one, DOP generates an “ideal spectrum” by applying a reference-centred linear kernel on the calibration database. The parasitic sub-space, spanned by the differences between ideal and measured spectra, is then removed from the calibration space, by means of an orthogonal projection. The application database covered eight years of wheat NIR spectra related to protein content. The first four years were used for calibration and the remaining years for testing. The corrections were calculated using the first scanned samples of every year, for each variety [between five and ten samples (four samples per year)]. Results were compared with standard partial least squares calibration models.

© 2008 IM Publications LLP

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