Principles of Plant Genetics and Breeding

genotype is reduced. This raises the important issue of
adaptation because a breeder’s selection in one environment
of superior performers may not hold true in
another environment. By measuring the G × E interaction,
the breeder will be better equipped to determine
the best breeding strategy to use to develop the genotype
that is most adapted to the target region.
Classification of G × E interactions
The type of G × E interaction influences the nature
of the cultivar the breeder eventually releases for the
production region. The environment, as previously
described, can be complex, and so can the genotype of
the plant. Consequently, the biological basis of G × E
interactions is complex by nature. Environmental factors
are constantly changing. The interaction between the
genotype (cultivar) and the environment is ongoing.
As the number of environments (n) and number of
genotypes (m) increase, the number of possible G × E
interactions is given by mn!/m!n! Of this, there is
theoretically only one genotype that is the best performer
under all environments, odds that make a search for it
futile. Allard and Bradshaw classified this interaction
into three common patterns using two genotypes (A, B)
and two environments (E 1 , E 2 ) for a graphic illustration
of the concept of G × E interaction. In statistical terms, a
G × E interaction has occurred when the difference in
performance between the two genotypes is inconsistent
over the environment:
Table 23.1 Demonstration of G × E interaction.
PERFORMANCE EVALUATION FOR CROP CULTIVAR RELEASE 421
A 1 − B 1 ≠ A 2 − B 2 [or A 1 − B 1 − (A 2 − B 2 ) ≠ 0]
A G × E interaction exists when:
A 1 − B 1 − A 2 + B 2 ≠ 0
Three basic types of G × E interaction – no interaction,
non-crossover interaction (quantitative interaction),
and crossover interaction (qualitative interaction) –
are recognized. A numerical example can be used to
distinguish these classes of interactions (Table 23.1). A
graphic illustration may also be used to demonstrate the
nature of these interactions (Figure 23.1). Consider two
genotypes, A and B, in a field trial analysis.
1 No G × E interaction. A no G × E interaction occurs
when one genotype (e.g., A) consistently performs
better than the other genotype (B) by about the same
amount across all the environments included in the test:
2 A non-crossover G × E interaction. A noncrossover
G × E interaction is said to occur when a
genotype (A) consistently outperforms genotype B,
across the entire test environment. However, the
differential performance is not the same across the
environment. That is, whereas there is no change in
rank, genotype A may exceed genotype B by 20 units
in one environment and 60 units in another.
3 A crossover G × E interaction. This is the most
important G × E interaction to plant breeders. A
crossover G × E interaction occurs when a genotype
(A) is more productive in one environment, but a
No interaction Environment 1 Environment 2 Difference
Genotype A 10 14 +4
Genotype B 16 20 +4
Difference +6 +6
Non-crossover interaction Environment 1 Environment 2 Difference
Genotype A 10 14 +4
Genotype B 16 24 +8
Difference +6 +10
Crossover interaction Environment 1 Environment 2 Difference
Genotype A 16 14 –2
Genotype B 10 20 +10
Difference –6 +6