Contents - Index
Diallel Data Analysis
Diallel crosses have been used in genetic research to determine the inheritance of a trait among a set of genotypes and to identify superior parents for hybrid or cultivar development. Conventional analysis of diallel data is limited to partitioning the total variation due to the crosses into general combining ability (GCA) of each parent and specific combining ability (SCA) of each cross. The SCA effects are just residuals not explained by the GCA effects; they are crosses specific and do not help in understanding the parents.
The biplot approach of diallel data analysis introduced in this chapter allows better understanding of the parents, in addition to being graphical. For a given set of data, the following information can be easily visualized:
1) the GCA effects of the parents,
2) the SCA effects of the parents;
3) the heterotic groups;
4) the best crosses; and
5) the best testers for identifying parents with high GCA.
Treating a diallel data as an entry by tester two-way table, Points 1, 2, 3 can be achieved by the Mean vs. Stability view of the GGE biplot; Point 4 can be achieved by the which-won-where view of the GGE biplot, and Point 5 can be achieved by the Discrimination vs. representativeness view of the GGE biplot.