Вавиловский журнал генетики и селекции (Jul 2019)
Use of S. Wright’s path coefficient method for statistical analysis of interrelated traits in rice
Abstract
S. Wright’s analysis of plant productivity is of great current interest. The research objective was to determine the pair correlation coefficients and S. Wright’s path coefficients for rice varieties and, on their basis, to identify the contribution of each of them to the plant productivity. Ten rice varieties were taken as the test material. The experiments were conducted in the irrigated experimental field of theInstituteofRiceof the National Academy of Agrarian Sciences ofUkrainein 2013, 2014 and 2016. Seeds were sown with an SKS-6A manual seeder; the seeding rate was 7.0 mln germinable seeds per hectare. The predecessor was alfalfa. The plot area was5 m2; the sowing distance was15 cm. The plants were analyzed for the following traits: plant productivity (grain weight), panicle weight, grain weight from side stems, productive tillering capacity, grain number per panicle, spikelet number per panicle, 1000-grain weight, grain weight per panicle, plant height, panicle length and density, empty spikelet number per panicle, and incidence of blind seed disease. Pair correlation coefficients were determined by B.A. Dospekhov’s method; path analysis, by S. Wright’s method. The correlations of productivity with 12 quantitative traits of rice were determined: the correlation was close with the grain weight from side stems and medium with the panicle weight and with the grain weight per panicle. Path analysis of the plant productivity established that the correlations of plant traits with the productivity depended both on direct and indirect effects of each trait on the productivity. The relative contribution of each of the studied 12 traits to the rice productivity was determined; both direct and indirect effects of their interactions with other traits were evaluated. This made it possible to discover causes and consequences of interrelations between the traits and, as a result, to choose valuable-for-selection traits, such as panicle weight and productive tillering capacity, which had the greatest direct effects on the productivity and significant correlations with it.
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