Discriminating power of selected physical properties of seeds of various rapeseed (Brassica napus L.) cultivars

In this study, the seeds of open-pollinated winter rapeseed cultivars, hybrid winter rapeseed cultivars, open-pollinated spring rapeseed cultivars and hybrid spring rapeseed cultivars were investigated. The physical, optical, mechanical, geometric and image texture properties of rapeseeds were compared. Statistical models were developed based on the analyzed parameters to discriminate between seed groups. Most parameters effectively discriminated between cultivars of winter and spring rapeseed, including true density, porosity, L*, a*, b*, and spectral values at 400 nm, 470 nm, 500-530 nm, 560-620 nm, 640-650 nm and 690 nm. Four homogeneous groups were identified based on linear dimensions: F (surface area), S (width) and shape factors W6 (circularity ratio), Rb (Blair-Bliss coefficient) and W13 (roundness). No statistically significant differences in the mean values of hardness or area under the force-displacement graph were observed between seed groups. The model developed based on image texture variables from channel Y (luminance) was characterized by the highest discrimination accuracy of 82-87%. The experimental groups were classified with 89-92% accuracy in the model combining the best variables from each group of physical parameters. Total classification accuracy in neural networks reached 75% for a validation set comprising geometric properties and 91-92% for a validation set containing physical characteristics.