• Login
    • Login
    Advanced Search
    View Item 
    •   Maseno IR Home
    • Theses & Dissertations
    • Masters Theses
    • School of Mathematics, Statistics and Actuarial Science
    • View Item
    •   Maseno IR Home
    • Theses & Dissertations
    • Masters Theses
    • School of Mathematics, Statistics and Actuarial Science
    • View Item
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Screening new strains sugarcane by augmented block design and randomized complete block design

    Thumbnail
    View/Open
    OTULO, W C0001.pdf (21.92Mb)
    Publication Date
    2013
    Author
    OTULO, Wandera Cyrilus
    Metadata
    Show full item record
    Abstract/Overview
    Of the three pillars in which the Kenya vision 2030 is anchored, agriculture is a key sector. Over the past few years the challenges to sugar production i.e. the choice of the variety to plant, soil nutrients variation and market competition amongst others have greatly affected sugar production. This project has effectively and efficiently employed the technique of experimental design to ascertain family selection by comparing augmented block designs and Randomized complete block designs.The augmented block design is widely used in breeding programs, particularly in screening and selection of large number of germ-plasm lines with non- replicated test treatments and replicated control treatments to estimate the experimental errors. The study establishes a relationship between augmented block designs in screening and completely randomized block design in screening new strains of Sugarcane. The data used in this study were generated from IASRI resource server. In the two designs analyzed, we consider 5 test treatments and 2 control treatments for augment design and the same number of treatments for Randomized Complete Block Design. In the event of screening new sugarcane varieties, attempts were made to find the effectiveness of augmented block designs (ABD) and completely randomized block designs (R.C.B.D) in test families vs. control checks where the results reveal that Augmented Block Design is 11.86 times more efficient than a RCBD in standard error cij=N(O,l)and drops through to 1.8lfor error term cij=N(O,25). In the conclusion of this study in chapter five, we have shown that Augmented Block Design is better suited when the plots are limited and Randomized Complete Block Design is better suited when treatments are many.
    Permalink
    https://repository.maseno.ac.ke/handle/123456789/4127
    Collections
    • School of Mathematics, Statistics and Actuarial Science [81]

    Maseno University. All rights reserved | Copyright © 2022 
    Contact Us | Send Feedback

     

     

    Browse

    All of Maseno IRCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

    My Account

    LoginRegister

    Statistics

    View Usage Statistics

    Maseno University. All rights reserved | Copyright © 2022 
    Contact Us | Send Feedback