MATHEMATICAL MODELS OF HIGH-STARCH MAIZE HYBRIDS OF DIFFERENT GROUND GROUPS

Abstract

The article presents the results of mathematical modeling based on the construction and usage of different images of an object, process or system. The research expected to study the dependence of the productivity level and the economically valuable features of corn hybrids in the form of mathematical models. Field studies were carried out during 2011-2017 at the field of research of the Department of Plant, Selection and Bioenergy Crops of SE EF “Kordelivske” of IP NAASU of Vinnytsia National Agrarian University under the conditions of the Forest-Steppe of the Right-Bank, in accordance with the recommendations presented in the Methodology Of The Maize Field Study. The soils in the study variants are represented by black earth soil of deep medium loamy on the loessial soil. The humus content (according to Tiurin) in the tilth soil was 4.60%. Soil reaction - pH (salt) 5.7. The soils contain lightly hydrolyzed nitrogen (according to Kornfield) 106 mg per 1 kg of soil, mobile phosphorus and exchangeable potassium (according to Chirikov) 186 and 160 mg per 1 kg of soil, respectively. The experiments established the economic and biological evaluation of corn hybrids depending on the sowing period, the size of the fraction and the depth of seed wrapping, foliar fertilizers by micro fertilizers. The plot area for hybrids was 10.5 m2. Repeatability in experiments for hybrids is 3 times. Placement of plots is by the method of randomized blocks. An ecological-genetic model of quantitative features was used to study the phenotypic productivity of maize hybrids and to establish the influence on the formation of their traits. The model construction is based on the hierarchy of production traits demonstration in ontogeny and the correspondence of their manifestation in organogenesis. The model consists of three modules of features, i.e. the resultant and two components which reflecting the phenotypic implementation of the genetic formula. Resulting features are those that have an environmentally stable relationships and the highest total contribution to the intended property, yield. As a result of the conducted research, the mathematical models of the duration of the growing season of early-maturing maize hybrids allowed us to determine that the biggest influence does sums of effective temperatures (≥ + 10° C) for May, June, August and September over correlation rate at r = -0.62 and r = -0.51, r = 0.59 and r = 0.39, respectively. Also precipitation amount significantly influenced on the duration of the growing season and the correlation coefficient was r = -0.44, and the influence of the HTI was at the level of r = -0.34. For middle-early hybrids the sum of effective temperatures (≥ + 10° C) in May and June r = -0.46 and r = -0.28, respectively, and also the sum of effective temperatures (≥ + 10° C) in August – r = 0.18 had a strong effect. However, for medium-maturing maize hybrids, the duration of the growing season was determined by the sum of effective temperatures (≥ + 10° C) for May, June and July – r = -0.37, r = -0.34 and r = -0.28, and the sum of effective temperatures (≥ + 10° C) in August – r = 0,18. It is also possible to note the influence and the total sum of effective temperatures (≥ + 10° C) during vegetation at the level of correlation coefficient r = -0.51. According to the research results of mathematical models of the influence of weather conditions on the formation of phenotypic productivity of maize hybrids of different maturity groups both general biological regularities and group differences of features formation were established. Thus, if we analyze the differences between groups of early-ripening and middle-early corn hybrids, their growth and development in general are influenced by the sum of the effective temperatures, rainfall and HTI. In fact, the studied groups of ripeness differ slightly and the main differences are observed only in the variability of the studied features or their close relationship with each other. However, middle-aged hybrids respond somewhat differently to environmental factors, which allow developing the elements of adaptive growing technology for each of the maturity groups. Key words: corn, hybrid, phenotype, mathematical model, productivity, economic and valuable features.