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Information × Registration Number 0224U032837, (0123U102773) , R & D reports Title Trait phenotyping of sunflower genotypes popup.stage_title Розроблення алгоритму і програмного забезпечення для реалізації процесу систематизації генотипів соняшнику за параметрами насіння. Head Shevchenko Ihor A., Доктор сільськогосподарських наук Registration Date 09-12-2024 Organization Institute of Oilseed Crops of the National Academy of Agrarian Sciences of Ukraine popup.description1 Increasing the efficiency of selection and forecasting the development of sunflower genotypes by developing new methods, hardware and software tools for quantitative phenotypic characterization of seeds and developing a sunflower genotype model based on the combination of description of the complex of phenotypic traits of sunflower plants. popup.description2  Algorithm and software for implementing the process of systematizing sunflower genotypes by seed parameters. The algorithm includes digitization of photo images of seeds, images of the basket, seed peeling strength, surface roughness, creation of a database with a combination of weight measurements and plant indicators. A device has been developed for the algorithm, which consists of three modules: determination of morphological properties of seeds, determination of rheological properties of seeds, determination of seed surface properties. Software has been developed for each of the digitization parameters. The module for determining morphological properties ensures the accuracy of automated individual measurement of geometric dimensions, shape, color and mass of each sunflower seed. The module for determining rheological properties of seeds and provides low labor intensity and high manufacturability, allows you to determine 9 elastic force, elastic modulus, indicators of static and dynamic hysteresis of elasticity. Module for determining the surface properties of sunflower seeds (seed friction coefficient), which allows to increase the accuracy of automated individual measurement of the coefficients of static and sliding friction of sunflower seeds, depending on the direction of their movement along the working surface). At the same time, the influence of the human factor on the accuracy of measuring seed properties is significantly reduced. A database of 196 sunflower lines has been created by the following characteristics: sunflower seeds (size, weight, breaking strength, huskiness, oiliness, color, shape, surface roughness) and sunflower plants (34 characteristics according to the UPOV test and proposals for its improvement). Systematization of sunflower seeds according to the developed algorithm will shorten the path and time for decision-making, and mechatronic systems for separation, selection and classification of material using neural networks will signifi Product Description popup.authors Aliiev Elchyn B. Vedmedeva Kateryna V. Zhuravel Valentyna M. Kutishcheva Nataliia M. Liаkh Viktor O. Makhova Tetiana V. Poliakov Oleksandr I. popup.nrat_date 2024-12-09 Close