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Castor is one of the most promising non-edible oil crops, due to its high oil content and since it can be grown on marginal lands and in a semi-arid climate. However, the high content of ricinoleic acid results in an extremely high viscosity of castor-based biodiesel. In this study, we report on the development of a rapid and non-destructive method for large-scale screening of intact castor seeds according to their viscosity by time domain NMR and chemometrics. A qualitative principal component analysis model was constructed, where each observation was assigned to a different viscosity group. This model straightforwardly detects desirable outliers, and can also be applied for detection of other transgenic oilseeds, especially those containing small levels of hydroxylated fatty acid.