Abstract

Soyabean flours, as additives and protein enrichment materials to foods having low protein content, have a major role in the food industry to increase the nutritional value of processed products. In the technology of soyabean flour production there is a great need for rapid information about the oil–protein complex of raw soyabean varieties. The main goal of our present investigation is to develop classification models, which are adequate to set the process parameters of soyabean flour production. We gathered raw soyabeans from the Agricultural Producing and Trading Inc. of Boly, Hungary. Fifteen different types, spanning three years, were studied by NIR using a NIRSystems 6250 monochromator. For pretreatment of the raw spectra smoothing and 2OFD (Second Order of Finite Difference) algorithms were used. PCA was performed and loading spectra were analysed to gain information on the main regions of interest. Based on the selected wavelength regions SIMCA classification was carried out. The results show that between years certain types of raw soyabeans are stable in oil–protein composition. In addition, the ratio of the constituents in the selected types is suitable for the above mentioned technology.

© 1998 NIR Publications

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