| Issue |
BIO Web Conf.
Volume 43, 2022
International Scientific and Practical Conference “VAVILOV READINGS-2021” (VVRD 2021) dedicated to the 101st anniversary of the discovery of the law of homological series and the 134th anniversary of the birth of N. I. Vavilov
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|---|---|---|
| Article Number | 01020 | |
| Number of page(s) | 7 | |
| Section | Basic Research in the Field of Plant and Microbial Studies | |
| DOI | https://doi.org/10.1051/bioconf/20224301020 | |
| Published online | 19 January 2022 | |
Use of Factor Analysis in Grain Sorghum Breeding
1 Federal State Budgetary Scientific Institution Russian Research and Design Technological Institute of Sorghum and Corn Rossorgo, 410050, Saratov Region, Saratov, 1st Institutskiy proezd, 4, Russian Federation
2 Volga Research Institute of Breeding and Seed Production named after P.N. Konstantinov, branch SamNTsRAN, 446442, Samara region, Kinel, urban-type settlement Ust-Kinelsky, 76, Shosseinaya street, Russian Federation
* Corresponding author: viktoria_starchak@rambler.ru
The article presents the results of calculating factor loads for 2015-2018 obtained by the method of principal components of grain sorghum varieties. Field studies were laid and carried out in the fields of the Federal State Budgetary Scientific Institution RosNIISK Rossorgo. The objects of the study were grain sorghum plants of the Institute's selection, as well as samples presented by the VIR world collection. 25 economically valuable indicators in 32 samples were analyzed. The main role in selection of indicators for inclusion in the correlation model is assigned to the expert approach in assessing breeding material. Effective and combinational groupings of correlation coefficients by hypothetical factors are very important tools in solving the issue of selecting indicators in a correlation model of interrelationships of selectively valuable indicators of various plant populations. Grouping the correlation coefficients makes it possible to assess the general nature of the interaction of the indicators included in the experimental data matrix. Calculations of the loads on hypothetical factors in the experiment made it possible to identify factors whose contribution to the accumulated variance is more than 5 %.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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