Scientific Journal of KubSAU

Polythematic online scientific journal
of Kuban State Agrarian University
ISSN 1990-4665
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Name

Chilashvili Irakliy Mihaylovich

Scholastic degree

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Academic rank

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Honorary rank

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Organization, job position

State Scientific Institution All-Russian Rice Research Institute
   

Web site url

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Email

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Articles count: 3

478 kb

ASSESSMENT OF THE NEW SOURSE MATERIAL FOR BREEDING EARLY AND AVERAGE MAIZE HIBRIDS

abstract 0791205001 issue 79 pp. 1 – 16 31.05.2012 ru 1927
The article presents the result of correlation analysis of harvest structural elements. They have been analyzed for their effect on the biological yield inbred lines. The distribution of inbred lines in terms of manifestation of each trait separately was made. The final step was the evaluation of hybrids and calculation of economic efficiency of their implementation. As a result of the work, three hybrid combinations of corn were selected, and studying in further strain testing was suggested
342 kb

ESTIMATION OF COMBINING ABILITY OF THE BEST INBREEDING LINES AND OBTAINING OF HIGH-HETEROSIS HYBRIDS OF MAIZE

abstract 0801206005 issue 80 pp. 51 – 69 30.06.2012 ru 2292
The article reflects the results of experimental studies in heterosis breeding of corn. We defined the common (CCA) and specific (SCA) combining ability of the new material. We also obtained the valuable inbreeding lines and testers of corn, created based on these new hybrids. The final step was the evaluation of hybrids and calculation of economic efficiency of their implementation. As a result of the work, it was allocated the three hybrid combinations of corn and suggested to examine them in strain testing
130 kb

THE ESTIMATION OF ECOLOGICAL YELDABILITY AND STABILITY OF NEW HYBRIDS OF MAIZE WITH QUICK DRY DOWN OF GRAIN AT MATURITY

abstract 0881304021 issue 88 pp. 331 – 340 30.04.2013 ru 1333
The article reveals the issues concerning the results of the research of estimation of new early lines of maize with quick grain dry down in two areas of growing. The regression analysis which based on derived data identified intensive hybrids and the most sustainable hybrid combinations by yield and harvesting moisture of grain
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