Please use this identifier to cite or link to this item: https://dl.ucsc.cmb.ac.lk/jspui/handle/123456789/690
Title: Development of Software to Analyze Mating Designs
Authors: Peiris, B.L.
Issue Date: 5-Nov-2013
Abstract: Geneticists, plant and animal breeders often use mating designs to obtain important genetic information about trait of interest from a fixed or randomly chosen set of parental lines. Estimates of genetic effects, variances and other population parameters provide essential information for the development of appropriate breeding and selection strategies. There are a number of mating designs that can be used to estimate genetic parameters in a population. Most commonly used mating designs are the diallel, North Carolina Design I and North Carolina Design II. The diallel design and its modifications have been used more extensively than any other mating design. A drawback to the diallel design is that it is relatively complex to analyze. The genetic effects are not readily separated and cannot easily be analyzed in a single execution of a linear model procedure in standard statistical software such as SAS, SPSS and MINITAB. A user-friendly object oriented statistical software (StatsMate) was developed to analyze commonly used mating designs. The software was written in Java programming language. A Graphical User Interface (GUI) for the software was developed using Java Swing. The software has a data editor and the user may enter data itself or import data from other software/programs. The software included functions such as data editing, data manipulating, opening/saving files, data transforming, and printing/saving data/output. All commands display in a menu bar and/or a tool bar for easy and fast access. The software can analyze North Carolina Design I, North Carolina Design II and Griffing’s diallel method for the diallel design with F1 crosses ( crosses of n parents). The software prints a descriptive analysis of data, an analysis of variance table, tables of means, general and specific combining abilities, estimates of genetic components of variances, and heritabilities. The output from the data analysis is easy to understand and interpret. The software was developed by the object oriented designing process and can be easily updated and maintained. The software has high potential for improving from the current status to more comprehensive software.
URI: http://hdl.handle.net/123456789/690
Appears in Collections:Master of Computer Science - 2006

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