THE USE OF MULTIVARIATE STATISTICAL METHODS TO STUDY CHICKPEA VARIETIES AS SOURCE MATERIAL FOR BREEDING IN THE LOWER VOLGA REGION
2022
V.I. Zhuzhukin | Zh.N. Mukhatova | A.G. Subbotin | A.F. Sugrobov | A.F. Druzhkin
This article evaluates the economically valuable traits of chickpea varieties from the VIR collection: k-16 Kubansky 16; k-23 TURE 4; k-109 Nut bukharsky; k-163 Kubansky163; k-388; k-400 Sredneaziatsky 400; k-416; k-418; k-434; k-440; k-466; k-468; k-475; k-495; k-499; k-514; k-531 GARBANZAS; k-532; k-534; k-542; k-572; k-574; k-596; k-651; k-1201 Krasnogradsky 04. Different degrees of variation in vegetative and generative parameters were found. The greatest variability (V > 20.0%) was established by the stem thickness, the number of primary branches, the number of beans per plant, the thousand grain weight, the productivity of one plant, the number of seeds per plant, yield. We identified the chickpea varieties which differ by a great thousand grain weight (k-434, k-542), a significant stem length (k-163 Kubansky 163, k-400 Sredneaziatsky 400), and a larger number of seeds from one plant (k-574, k-596). The chickpea varieties were clustered by minimum Euclidean distances in the eighteenth iteration step (the Euclidean distance was 16.88). The clusters were grouped into seven ones that differ significantly at the 5 % level in the studied traits. A correlation coefficient matrix was calculated. It allowed the interpretation of 66 relationships, of which 17 were found to be significant at the 5% level. The use of factor analysis helped to identify the significant weights of the variables on the components.
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