Using the Achievements of Genetics in the Selection of Grapes
Authors: Ali A. Zarmaev
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The article is devoted to the history of the emergence, formation and development of genetics of grapes, both abroad and in our country. It is concluded that thanks to genetics, it became possible to develop the selection of grapes at a new molecular-genetic level. It is shown that the origins of the development of this science were such outstanding domestic scientists as Academician Nikolai Ivanovich Vavilov and Professor Alexander Mikhailovich Negrul who made a great contribution to the genetics of grapes in our country.
It is especially noted that the following features are typical for the genetic system of grapes that are found in various forms of grapes in various combinations: a) allogeneity – cross pollination, b) parthenocarpy and, possibly, in some forms apomixis, c) vegetative reproduction, d) diploidity – polyploidy, e) chimeras – "vegetative" heterogeneity. Completely new possibilities in selection of grapes can open a method of tissue culture and individual cells. Especially tempting is the production of plants from pollen, primarily in remote hybrids.
An additional source of source material in selection can be induced mutagenesis and experimental polyploidy. It is reported that the Institute of Grape and Wine "Magarach" is one of the leading centers for the selection of grapes in the CIS countries. It is pointed out that the genetics of grapes is inseparable from selection, and the selection department, genetics of grapes and ampelography of the institute make a big contribution to this process.
It is emphasized that molecular genetic methods are the most modern technology for improving and stabilizing the achievements of crop production. They make it possible to overcome many difficulties in the study of cultivated plants, such as the length of time for selection of the source material, the lack of the possibility of carrying out analysis for the detection of heterozygous loci, the search for optimal parental pairs for generative selection.