Efimov V. M., Tarakanov V. V., Naumova N. B., Kovaleva V. Y., Kutsenogiy K. P. Highly Inheritable Variable Components in the Clonal Plantation of Scots Pine
1 Institute of Cytology and Genetics, Russian Academy of Sciences, Siberian Branch
Prospekt Akademika Lavrent’eva, 10, Novosibirsk, 630090 Russian Federation
2 West-Siberian Department of V. N. Sukachev Institute of Forest, Russian Academy of Sciences,
Siberian Branch, Federal Research Center Krasnoyarsk Scientific Center, Russian Academy of Sciences,
Zhukovskiy str., 100/1, Novosibirsk, 630082 Russian Federation
3 Institute of Soil Science and Agrochemistry, Russian Academy of Sciences, Siberian Branch
Prospekt Akademika Lavrent’eva, 8/2, Novosibirsk, 630090 Russian Federation
4 Institute of Systematics and Ecology of Animals, Russian Academy of Sciences, Siberian Branch
Frunze str., 11, Novosibirsk, 630091 Russian Federation
5 Voevodsky Institute of Chemical Kinetics and Combustion, Russian Academy of Sciences, Siberian Branch
Institutskaya str., 3, Novosibirsk, 630091 Russian Federation
E-mail: vmefimov@ngs.ru, tarh012@mail.ru, nnaumova@mail.ru, vkova@ngs.ru, koutsen@kinetics.nsc.ru
Abstract
UDC 630*165.6+631.523.4
How to cite: Efimov V. M.1, Tarakanov V. V.2, Naumova N. B.3, Kovaleva V. Y.4, Kutsenogiy K. P.5 Highly inheritable variable components in the clonal plantation of Scots pine // Sibirskij Lesnoj Zurnal (Sib. J. For. Sci.). 2019. N. 6. P. 82–88 (in English with Russian abstract).
DOI: 10.15372/SJFS20190609
© Efimov V. M., Tarakanov V. V., Naumova N. B., Kovaleva V. Y., Kutsenogiy K. P., 2019
The variability of the data on elemental composition of needles from the clonal population of Scots pine Pinus sylvestris L., established on the long-term field experiment, was studied by principal components extraction from the normalized data matrix, and broad-sense heritability Н2, i.e. the contribution of clones to the total data variance was calculated both for the original variables and principal components. To find the linear combinations of variables with the highest heritability the discriminant analysis was performed. The results suggest the importance of multivariate statistics for forest genetics and selection in targeting search for genetic marker traits in the populations of woody plants, in assessing genetic differentiation among populations, identification of the best genotypes via their phenotypes, etc.
