Genotype by environment interactions affecting grain sorghum. III. Temporal sequences and spatial patterns in the target population of environments
Authors: Chapman S. C. , Hammer G. L. , Butler D. G. , Cooper M. 
Published: September 2002

The variable nature of rainfall in north-eastern Australia confounds the
process of selecting sorghum hybrids that are broadly adapted. This paper uses
a crop simulation model to characterise the drought environment types (ET)
that occur in the target population of environments (TPE) for dryland sorghum.
Seventy seasons (1921–1990) of simulations of the yield of a sorghum
genotype and the associated within-season sequence of a stress index were
conducted for a small TPE of 6 locations and also for a large TPE of 211
locations that attempted to represent the entire sorghum region.
Previously, using the small dataset of 6 locations, pattern analysis enabled
us to group seasonal stress indices from each trial into major ETs: ‘low
terminal stress’ (ET1), severe terminal stress (ET2), and intermediate
mid-season/terminal stress (ET3) in the ratio 33 : 38 : 29. When the
dataset was broken into a sequence of 16 multi-environment trials (METs), each
of 3 years and 6 locations, the ratios of ET1 : ET2 : ET3 differed greatly
among METs, i.e. any single MET was not randomly sampling the TPE. Hence, for
any MET, the average yield (GVu)
was not the same as the overall mean of the entire 70-year dataset. If the
trial yields were weighted according to the ratio of ET1 : ET2 : ET3 in the
overall TPE, then GVw (s.d.
= 0.13) for a single MET was much closer to the overall mean than was
GVu (0.38). For different METs,
the values of GVw were up to
30% higher or 15% lower than
GVu. Across METs, the difference
between GVu and
GVw was positively correlated
(r = 0.88, n = 16,
P < 0.05) with the frequency of ET1 (‘low
terminal stress’) encountered within the MET and negatively correlated
(r = −0.82) with the frequency of ET2. The
value of weighting was confirmed by its ability to verify that two simulated
genotypes had the same mean yield over many trials, even though they differed
in their specific adaptation to the different ETs.
The large TPE consisted of more than 15 000 simulations and was classified in
2 stages (within/among locations), repeated for each of 3 soil types. In
years in which the simulation sowing criteria were met, the ratios of ET1 :
ET2 : ET3 were about 4:2:4, 4:5:1, and 6:3:1 in the shallow, intermediate, and
deep soils, respectively. Hence, over all soil types and locations, the
sorghum TPE for northern Australia consists of at least 30% each of low
terminal stress (ET1) or severe terminal stress (ET2) and these environment
types need to be sampled. The incidence and nature of the ‘intermediate
midseason/terminal stress’ environment type (ET3) varies with soil
type and location.
Weighting genotype performance should improve the precision of the estimate of
its broadly adapted value, and be of practical use in breeding programs in
these variable environments. Although the ‘boundary conditions’ of
the TPE are not yet resolved, this paper also shows that simulation and
pattern analyses can be used to determine the structure of the abiotic TPE.
Taking other factors into account (e.g. soil type distribution, shire
production levels, and farm profit), selection trials could be weighted to
improve selection for narrow or broad adaptation, depending on the purpose of
the breeding program.