Registration Number
0223U004986,
0123U102773
, R & D reports
Title
Trait phenotyping of sunflower genotypes
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Head
Shevchenko Ihor A., Доктор сільськогосподарських наук
Registration Date
12-12-2023
Organization
Institute of Oilseed Crops of the National Academy of Agrarian Sciences of Ukraine
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A formalized mathematical model for the identification of sunflower genotypes by their phenotypes is proposed. A method of processing a photo image of a sunflower head and determining the coordinates of seed placement in it has been developed. The patterns of distribution of geometric (length L, width W, thickness T) and mass (seed mass Ms, kernel mass Mk) parameters of seeds in a head of different sunflower samples were studied. The variability of the phenotype of the seeds in the head, depending on its location, was established. A complex of demonstrative phenotypic characteristics of sunflower seeds I is introduced, which is defined as the product of the ranks of individual phenotypic parameters of seeds. The grouping of seeds in the area of the head was carried out according to indicator I. A general pattern was determined: the presence of three tiers with different phenotypic characteristics in each basket. A database of phenotypic characteristics of sunflower genotypes selected by the Institute of Oil Crops of the National Academy of Sciences of the Russian Academy of Sciences has been created, which includes information on geometric dimensions, color, density, strength and durability properties. As a result of data processing of measurement of phenotypic characteristics of sunflower seeds in the basket in the Wolfram Cloud software package, regularities of the distribution of determined phenotypic characteristics of sunflower seeds from their location in the basket were established in the form of polynomials.
The structural model of the closed system of automatic phenotyping of sunflower seeds with the implementation of the principle of screening by several parameters (geometric dimensions, shape, mass, color, rheological properties, surface properties) has been improved. The developed device for automatic phenotyping of seeds consists of three modules: a module for determining the morphological properties of seeds (geometric dimensions, weight, surface colo
Product Description
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Elchyn Aliiev
Vedmedieva Kateryna V.
Kutishcheva Nataliia Mykolaivna
Liakh Viktor O.
Tеtyana V. Makhova
Polyakov Oleksandr I.
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2023-12-12
