PROVISION OF CONDITIONS OF COMPARABILITY OF RESULTS IN FIELD BIOTECHNOLOGICAL RESEARCH USING A COMPUTER EXPERIMENT - Gorbunov, Leonid; Larintseva, Nadiia; Zviahintseva, Oksana (Bulletin of the National Technical University "KhPI". Series: Chemistry, Chemical Technology and Ecology, 2021)
When conducting biotechnological field studies using plant objects, there is a problem of taking into account the heterogeneity of the results, the imperfection of methods leads to the need for multiple repetitions of experiments, but the issue of reproducibility and comparability of research results is not resolved, therefore, the use of mathematical models in research makes it possible not only to identify, but also to explain the obtained patterns. The subject of the study in the article is a simulation model for estimating the mass of corn grains taking into account their genotype and growing conditions. The model is based on an analytical expression that reflects the main reasons for the growth of corn seeds after pollination of the plant. The mass of corn grains depends on a number of biological factors (genotype), technological – soil structure (its fertility and methods of cultivation), and climatic conditions (humidity, light intensity). The aim of the study is to create a simulation model to ensure the comparability of the results obtained when growing corn for grain in different conditions. Biological (cultivation) and mathematical (simulation model) methods were used as methods for obtaining and constructing results. The discrepancy in the estimation of the mass of grain of the same genotype grown in different research farms of different climatic zones of Ukraine and obtained by calculation was not more than 18 % and obtained experimentally up to 64 %. A feature of the model is the independence of the heterogeneity of the bioobject (studied lines and hybrids) from the conditions of their cultivation (soil structure and climatic conditions). The application of mathematical modeling makes it possible to reduce the differences in the studied indicators up to 25 times, which were obtained in different experiments, thereby significantly reducing time, money and provide a condition for comparability of results to obtain a reliable result.