The relevance of this dissertation is determined by the urgency of addressing a key scientific challenge in modern maize breeding: the development and identification of early-maturing source material of the southern ecotype, capable of consistently realising its genetic productivity potential under insufficient and unstable moisture conditions in the Steppe zone of Ukraine.
The relevance of the research is determined by the increasing impact of global climate change on maize production, as evidenced by rising temperatures, longer periods of drought, uneven distribution of rainfall and a growing risk of yield losses in modern hybrids. Under such conditions, the development of early-maturing genotypes that combine high productivity, accelerated grain moisture-yielding ability, suitability for modern cultivation technologies, resistance to abiotic stresses and the stable manifestation of valuable economic traits takes on particular importance.
The research was aimed at theoretically substantiating and experimentally confirming the effectiveness of developing early-maturing maize breeding material of the southern ecotype, to conduct a comprehensive assessment of this material based on morphobiological, agronomic and genetic parameters, to identify patterns in the development of productivity and adaptability, and to develop promising heterosis models for the breeding of new hybrids.
The research was conducted at the State Enterprise Institute of Grain Crops of NAAS of Ukraine in 2023–2025. The research focused on 302 early-maturing, self-pollinating families of S₄–S₆ generations, derived from sister hybrids of the southern ecotype, their test crosses and newly developed interline maize hybrids.
Field, laboratory, biometric, and genetic-statistical research methods were applied for the comprehensive assessment of the breeding material. We evaluated morphobiological and valuable economic traits, analysed the structure of productivity, determined general and specific combining ability (GCA and SCA), assessed adaptability, as well as applied correlation, regression and cluster analysis, and the principal component analysis (PCA).
Scientific novelty of the work involves the comprehensive identification of a new generation of early-maturing maize source material of the southern ecotype based on the combination of productivity, early maturity, adaptability, and combining ability.
The patterns governing the formation of productivity under contrasting hydrothermal growing conditions have been established for the first time in the inbred families developed, the most informative morphobiological selection criteria have been determined, and the sources of enhanced adaptability and high combining ability have been identified.
The system for assessing early-maturing breeding material has been improved through the integrated application of correlation, regression and multivariate analysis methods, as well as test cross trials, which has allowed the identification of relationships between the components of productivity, adaptability and the degree of heterosis.
A three-year assessment of 302 early-maturing inbred families revealed significant genotypic differentiation across a range of morphobiological and valuable economic traits. The contrasting weather conditions of 2023–2025 allowed us to identify the specific responses of genotypes to abiotic stress and to pinpoint sources of productivity stability.
The average productivity of the studied families was 75.5 g/plant in 2023, whereas under drought conditions it decreased to 41.8 and 42.9 g/plant in 2024 and 2025, respectively. The highest resistance to adverse environmental conditions was observed in the offspring of the DK2815 × DK247MV combination. Thus, the decrease in productivity was only 11.5 %, whereas in the offspring of DK2835 × DK247MV this indicator reached 74.4 %. A comparison with the DK315SVZM standard confirmed the high breeding value of the new material: individual genotypes outperformed the standard by 41.7–71.6 % in terms of productivity, even under drought conditions.
The study found that productivity was influenced by a complex of interrelated traits. The closest positive correlations were found between productivity and 1,000-grain weight (r = 0.726), ear length (r = 0.604), number of grains per row (r = 0.557), ear insertion height (r = 0.534), and plant height (r = 0.523). According to the results of multiple regression analysis, ear length (β = 0.60; p = 0.03) and ear diameter (β = 0.29; p < 0.001) made a statistically significant independent contribution to yield, identifying them as the most effective criteria for selection.
Principal component analysis and cluster analysis allowed us to determine the structure of phenotypic variability and to identify groups of genotypes with an optimal combination of early maturity, productivity and adaptability.
