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    • Masters Thesis
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    •   HSTUL IR
    • Faculty of Agriculture
    • Dept. of Genetics & Plant Breeding
    • Masters Thesis
    • View Item
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    STUDY ON SELECTION INDEX IN FINE RICE (Oryza sativa L.)

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    ZAKARIA SULEIMAN MOHAMAD STUDENT NO.: 1805183 SEASON: 2018-2019 (2.639Mb)
    Date
    2019-06
    Author
    MOHAMAD, ZAKARIA SULEIMAN
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    URI
    http://localhost:8080/xmlui/handle/123456789/937
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    • Masters Thesis
    Abstract
    An experiment was conducted at the research field of the Department of Genetics and Plant Breeding, HSTU, Dinajpur Bangladesh with nineteen genotypes collected from germplasm Bangladesh Rice Research Institute, (BRRI) Gazipur. Nineteen genotypes with three replications were evaluated in Randomized Completely Blocked Design during January to June (2018- 2019). The main objectives were to study variability, similarity among the fine rice varieties, to construct selection index and to select best combination of traits for indirect selection. Yield per plant alone considered 100% expected genetic grain and relative efficiency of other functions were calculated accordingly. Yield per plot (g), thousand grain weight (g), number of grains per panicle, panicle weight, number of Spike per panicle, panicle length, effective tiller per plant, plant height, days of heading, maturity days association would be more efficient for improvement due to the maximum expected genetic gain (425.34) and maximum relative efficiency (432.34%), net efficiency (332.34%) as found in selection index. But considering economic viability and practical condition, selection indices for the improvement of yield, the three character association yield per plot, thousand grain weight, and number of grains per panicle is better than others which is suggested. Comparison between relative selection criterion of all the characters of the studied rice genotypes based on the best selection index yield per plot, thousand grain weight, and number of grains per panicle (three character assiciation), with their total rank value genotype Chinnigura and genotype SALNA are the promising rice genotypes for further genetic improvement.

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