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Information × Registration Number 0225U004791, (0124U001069) , R & D reports Title Evaluation of breeding material of common millet in order to identify transgressive forms of hybrids of synthetics in the system of reciprocal crossings popup.stage_title Розсадники гібридів синтетиків. Формування єдиних математико – статистичних платформ спектральних проявів параметрів ознак з активною модуляцією екстремумів максимальних амплітуд цінних господарських ознак, які можуть ідентифікувати трансгресивні стани нащадків Head Chernuskyi Vadym V., Кандидат сільськогосподарських наук Registration Date 18-12-2025 Organization Institute of Bioenergy Crops and Sugar Beet of National Academy of Agrarian Sciences of Ukraine popup.description1 Development of theoretical foundations and creation of practical models of transgressive productive-adaptive varieties of common millet by involving in hybridization schemes (reciprocal and backcross) geneplasm of original forms with a complex of valuable economic traits. popup.description2 In the context of climate change, increasing temperature extremes, and precipitation instability, the breeding of short-season crops, particularly common millet (Panicum miliaceum L.), has become increasingly important. Despite its long-standing cultivation, the potential of millet’s genetic plasticity in terms of stress adaptability has long remained underutilized. During 2024–2025, the IBKiCB system conducted comprehensive research on the creation and evaluation of hybrid common millet material, aimed at identifying transgressive forms. Over 700 samples were studied in hybrid and breeding nurseries, among which more than 60 exhibited transgressive traits for key agronomically valuable parameters. The research included the use of precise phenotyping methods and digital analysis, which enabled the creation of an extensive photobank of plant parametric states, comprising over 200 high-resolution images of panicles with a complete morphometric database. An updated methodology for detecting transgressions was developed, combining classical breeding analysis with neural network modeling, along with a modified formula for the quantitative assessment of transgressive effects. Neural network analysis of 150 morphotypes allowed the identification of five main clusters, among which Cluster 4 (transgressive samples) was characterized by increased panicle density (up to 0.43 g/cm³) while maintaining 1000-grain weight at 7.6–7.9 g. Product Description popup.authors Svitlana M. Mandrovska Nataliia K. Filatova Vadym V. Chernuskyi Larysa M. Levchenko popup.nrat_date 2025-12-18 Close