Abstract
Relevance. One of the problematic issues in crop production remains the quality of sown seeds. Vegetable plants during the period of generative development are demanding to the conditions of light and heat supply, but the conditions of most regions of our country cannot meet these requirements. Post-harvest refinement and pre-treatment of seeds is also not carried out at the proper level. There are no reliable informative tools for analyzing seed quality. Employees of the FSBSI FSVC, Agrophysical Research Institute and Argus-Bio LLC are developing a method of digital morphometry of vegetable seeds.Methods. The material for the studies was the seeds of various samples of varieties of the genus Allium: Allium cristophii Trautv., Allium schoenoprasum L., Allium fistulosum L. Digital images of seeds were obtained using the HP Scanjet 200 tablet scanner, BMP, TIFF, JPG save file format, 600 DPI resolution. Morphometric analysis of digital scanned images of seeds was carried out on the basis of the Agrophysical Research Institute using the serial software Argus-BIO, manufactured by Argus Soft LLC, St. Petersburg.Results. Analysis of the color characteristics of seeds (values of color components according to the RGB model) Allium cristophii Trautv. revealed a statistically significant decrease in all color channels in the row from the lower tier – the upper, which is an indicator of different levels of maturity. Seeds of various samples of Allium schoenoprasum L. in size (projection area) varied significantly within the species from 2.39 to 3.06 mm2 , in shape they also turned out to be unaligned: elliptical with an elongation factor of 1.99 to 2.21 relative units. Analysis of morphometric parameters of seeds of varieties Allium fistulosum L. made it possible to distinguish the influence of natural and genetic factors on these parameters: the factor of the year had a significant effect (from 43.5% to 45.4%), the factor of the variety – from 39.5% to 43.2%, on the main morphometric parameters of seeds. So, a new approach to seed quality analysis is presented, which includes rapid digital morphometry, data modeling and their integration with standard ISTA tests.
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