Open AccessEnvironmental adaptive cultivar model development methods on the spring triticale example
Author(s) -
И. Г. Гребенникова,
А. Ф. Чешкова,
П. И. Степочкин,
A. F. Aleynikov,
D. I. Chanyshev
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/839/3/032041
Subject(s) - triticale , adaptability , variety (cybernetics) , selection (genetic algorithm) , computer science , ecology , artificial intelligence , agronomy , biology
Usage of the optimization algorithms for the service of requests for repair in certain examples. The methodology for developing a model of an ecologically plastic variety of agricultural crops is based on an integrated approach and is built using the following mathematical and software-algorithmic methods: multifactorial correlation and cluster analyzes, calculating the integral assessment coefficient of samples depending on the share contributions of valuable traits, assessing the stability of genotypes by the value of the selection index methods of static and dynamic concept. The general provisions of the method are determined, the results of which make it possible to determine the criteria for a future variety, a complex of qualitative, quantitative, morph-physiological and technological characteristics. A database was created based on the results of field tests for 2018-2020. three varieties of spring wheat and four forms of spring triticale. The database contains digitized data of phenological observations and structural analysis of the studied samples for the period of research and serves to identify the relationships of characters, determine their contribution to productivity and retrospective analysis of breeding data. In accordance with the stages of modeling with the help of the developed software, the elements of the model of an ecologically plastic variety of spring triticale were determined by 14 features. The proposed optimal parameters of the model will increase the efficiency of selection of economically valuable genotypes and targeted selection for adaptability to the conditions of the region to create new high-yielding varieties of spring triticale.