Sc. Chapman et al., Genotype by environment interactions affecting grain sorghum. III. Temporal sequences and spatial patterns in the target population of environments, AUST J AGR, 51(2), 2000, pp. 223-233
The variable nature of rainfall in north-eastern Australia confounds the pr
ocess of selecting sorghum hybrids that are broadly adapted. This paper use
s a crop simulation model to characterise the drought environment types (ET
) that occur in the target population of environments (TPE) for dryland sor
ghum. Seventy seasons (1921-1990) of simulations of the yield of a sorghum
genotype and the associated within-season sequence of a stress index were c
onducted for a small TPE of 6 locations and also for a large TPE of 211 loc
ations that attempted to represent the entire sorghum region.
Previously, using the small dataset of 6 locations, pattern analysis enable
d 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 wa
s broken into a sequence of 16 multi-environment trials (METs), each of 3 y
ears 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 (GV(u)) 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 GV(w) (s.d. = 0.13) for
a single MET was much closer to the overall mean than was GV(u) (0.38). For
different METs, the values of GV(w) were up to 30% higher or 15% lower tha
n GV(u). Across METs, the difference between GV(u) and GV(w) was positively
correlated (r = 0.88, n = 16, P < 0.05) with the frequency of ET1 ('low te
rminal stress') encountered within the MET and negatively correlated (r = -
0.82) with the frequency of ET2. The value of weighting was confirmed by it
s ability to verify that two simulated genotypes had the same mean yield ov
er many trials, even though they differed in their specific adaptation to t
he 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 'int
ermediate midseason/terminal stress' environment type (ET3) varies with soi
l 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 sel
ection for narrow or broad adaptation, depending on the purpose of the bree
ding program.