Discriminating power of selected physical properties of seeds of various rapeseed (Brassica napus L.) cultivars |
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Affiliation: | 1. Department of Systems Engineering, Faculty of Engineering, University of Warmia and Mazury in Olsztyn, Heweliusza 14, 10-718 Olsztyn, Poland;2. Department of Agrotechnology, Agricultural Production Management and Agribusiness, Faculty of Environmental Management and Agriculture, University of Warmia and Mazury in Olsztyn, M. Oczapowskiego 8, 10-719 Olsztyn, Poland;1. Department of Systems Engineering, Faculty of Engineering, University of Warmia and Mazury in Olsztyn, Heweliusza 14, 10-718 Olsztyn, Poland;2. Department of Chemistry, Faculty of Environmental Management and Agriculture, University of Warmia and Mazury in Olsztyn, Łódzki 4, 10-957 Olsztyn, Poland;1. Agricultural Biotechnology Research Institute of Iran (ABRII), Seed and Plant Improvement Institutes, Mahdasht Road, PO Box: 31535-1897, Karaj, 3135933151 Tehran, Iran;2. Research Center of Agriculture and Natural Resources of East Azarbaijan, Azar Shahr Road, PO Box: 53555-141, Tabriz, Iran;3. Young Researcher Club, Islamic Azad University, Sari branch, Farahabad Road, PO Box: 48186-19318, Sari, Iran;4. University of Zanjan, University Road, PO Box: 45195-313, Zanjan, Iran |
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Abstract: | 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. |
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Keywords: | Winter and spring rapeseed Open-pollinated and hybrid cultivars Neural network Discrimination |
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