Multi-environment trials (MET) are essential to variety evaluation and
cultivar recommendation. Typical MET data are in the form of a
genotype-by-environment-by-trait three-way table. MET data are expensive and
valuable; information contained in MET data should be maximally explored and
utilized. Analyzing MET data is like
harvesting fish in your fish farm. You have already paid everything and it's
time to harvest. The only thing you need is a net and GGEbiplot is the net
with exactly the right size!
A full
understanding of MET data includes understanding all the possible two-way
tables within it:
-
genotype-by-environment table for
any trait
-
genotype-by-trait table
in an environment, across a group of environments, and across all
environments (genetic correlations among traits)
-
environment-by-trait table for a genotype, across a group of genotypes, and
across all genotypes (environment correlations among traits)
-
a large
genotype-by-attribute table if each environment-trait combination is viewed
as an attribute (for genotype classification)
-
a large
phenotype-by-trait table if each genotype-by-environment combination is
viewed as a phenotype (phenotypic correlations among traits)
-
an extended
genotype-by-tester two-way table, with yield data from different
environments and genetic values of various traits are regarded as "testers" (interpreting GE using genetic covariables)
Don't be scared by
the complexities!!! GGEbiplot can read a genotype-by-environment-by-trait
3-way table all at once and
generate all possible two-way tables and corresponding biplots simply
by clicking a button.
Everything is just a mouse-click away!
Note:
-
Three-way data input and visualization is part
of the four-way data input and
visualization module.
-
GGEbiplot analyzes
ALL types of three-way data, not just genotype by environment by trait data.
You can generalize the genotype by environment by trait three-way data as
Factor1 by Factor2 by Factor3 three-way data.
