Agriculture and forestry

Palamarchuk Vitalii – Candidate of Agricultural Sciences, Associate Professor of the Department of Plant Production, Selection and Bioenergetic Crops (21008, Vinnytsia, Soniachna St. 3, е-mail: vd-palamarchuk@ukr.net).

Alieksieiev Oleksii Oleksandrovych – Candidate of Agricultural Sciences, Senior Lecturer of the Department of Ecology and Environmental Protection of Vinnytsia National Agrarian University (21008, Vinnytsia, Soniachna St. 3, e-mail: alekseev_oleksiy@ukr.net).

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.

1. Shmal'gauzen I. I. (1968). Faktory jevoljucii. Teorija stabilizirujushhego otbora [Factors of evolution. The theory of stabilizing selection]. M.: Nauka [in Russian].

2. Litun P.P., Kyrychenko V.V. & Petrenkova V.P. et al. (2004). Teoriia i praktyka selektsii na makrooznaky. Metodolohichni problem [The theory and practice of breeding on macro signs. Methodological problems]. X.: Instytut roslynnytstva im. V.Ya. Yurieva [in Ukrainian].

3. Litun P.P., Kirichenko V.V. & Petrenkova V.P. et al. (2007). Adaptivnaja selekcija. Teorija i praktika na sovremennom jetape [Adaptive selection. Theory and practice at the present stage]. Kh.: Institut rastenievodstva im. V.Ja. Jur'eva [In Russian].

4. Timofeev-Resovskij R. V. (1984). Genetika, jevoljucija i teoreticheskaja biologija. Biologija i informacija [Genetics, evolution and theoretical biology. Biology and information]. M.: Nauka [In Russian].

5. Litun P.P., Kyrychenko V.V., Petrenkova V.P. et al. (2007). Teoretychni osnovy bazovoi tekhnolohii selektsii. Shkola akademika V.Ya. Yurieva. Teoretychni doslidzhennia v Instytuti roslynnytstva za 1908-2008 roky [Theoretical foundations of basic breeding technology. School of Academician V. Ya. Yur’ev. Theoretical research at the Institute of Plant Growing for 1908-2008]. X.: Instytut roslynnytstva im. V. Ya. Yurieva [in Ukrainian].

6. Litun P.P., Proskurnin N.V. & Gopcij T.I. (1996). Metodika polevogo selekcionnogo jeksperimenta [Methods of field breeding experiment]. Kharkov [In Russian].

7. Palamarchuk V.D., Polishchuk I.S. & Yermakova L.M. et al. (2013). Biolohiia ta ekolohiia silskohospodarskykh Roslyn [Biology and ecology of agricultural plants]. Vinnytsia: FOP Danyliuk [in Ukrainian].

8. Mazur V. A., Palamarchuk V.D. & Polishchuk I. S. et al. (2017). Novitni ahrotekhnolohii u roslynnytstvi [The latest agrotechnology in crop production]. Vinnytsia [in Ukrainian].

9. Palamarchuk V., Honcharuk I. & Honcharuk T. et al. (2018). Effect of the elements of corn cultivation technology on bioethanol production under conditions of the right-bank forest-steppe of Ukraine. Ukrainian Journal of Ecology, 8(3), 47-53 [in English].

10. Palamarchuk V.D., Kalenska S.M. & Yermakova L. M. et al. (2015). Systemy suchasnykh intensyvnykh tekhnolohii u roslynnytstvi [Systems of modern intensive technologies in crop production]. Vinnytsia: FOP Rohalska I.O. [in Ukrainian].

11. Fisher R. A. (1918). The correlation between on the supposition of mendelian inheritance. (Vol 52). Edinburgh [in English].

12. Lebid Ye. M., Tsykov V. S. & Pashchenko Yu. M. (et al.) (2008). Metodyka provedennia polovykh doslidiv z kukurudzoiu [Method of conducting field experiments with corn]. Dnipropetrovsk [in Ukrainian].