The Use of Near-Infrared Spectroscopy in Rapeseed Breeding Programs

Abstract

In order to determine qualitative traits of rapeseed, FT-NIR calibration models were developed, based on the data from routine reference methods. The correlation of the obtained FT-NIR spectra and the analytical data was implemented using PLS regression algorithm. The models were subsequently verified using the root mean square error of calibration, the root mean square error of cross validation, the root mean square error of prediction factors and the correlation coefficients. The applicability of the calibration models (dry matter, oil, oleic, linoleic, linolenic, and palmitic acid, glucosinolates) for the routine assessment of samples was verified. The predicted contents of erucic acid, stearic acid, and glucosinolates (genetic resources) exhibit the root mean square errors of prediction which are higher in comparison with the root mean square error of calibration, the root mean square error of cross validation values; nevertheless, all developed models are acceptable for the preliminary screening at the breeding programs of oilseed rapeseed.