Agriculture Reference
In-Depth Information
a breeding programme where high yield is the major
selection criteria?
lastly D (the same order as when only the means were
used).
If this were an actual breeding scheme, however, it
may be several years before a selected genotype from any
of these crosses becomes a commercial cultivar in agri-
culture. It may therefore be wise to set our target higher
than the controls as it might be expected that in several
years time then newer and higher yielding lines will be
available. As the variance of the controls is available we
can use this to set a target value which is the mean of
the controls plus the standard error of the controls (i.e.
21.0
Cross
mean
Genetic
variance
A
20.0
24.135
B
22.0
8.111
C
21.5
19.245
D
18.0
26.051
2.74) which would be approximately 24 t/ha.
With this target value we have A
+
=
20.90%, B
=
24.20%, C
11.90%. Now there
has been a change in the cross rankings (in parenthe-
sis, Table 7.11) with cross C now giving the highest
probability of a lines exceeding 24 t/ha. Cross B is now
ranked second but there is little difference between the
probabilities of cross B and cross A.
If the target value is further increased (say to the
control mean plus twice the control standard error, we
would have a target value approximately equal to 26.
With this target value the ranking of the four crosses is
C, A, B and D. Now cross A has a higher probability
of a genotype exceeding the target value (11.12%) than
cross B (8.08%).
In conclusion therefore, univariate cross prediction
is based on the mean and genetic variance of a cross.
When target values are relatively close to the progeny
mean values then not surprisingly the mean of each cross
will be a large factor in the cross prediction. As target
values are increased then the genetic variance becomes
a more important factor in determining the probability
of desirable recombinants. Finally, in the above example
it should be noted that it is the genetic standard error
(
=
28.42% and D
=
First it should be decided if selection is based only
on the mean performance of the crosses. If this is the
case then the answer is quite simple. Greatest emphasis
should be made with cross B, followed by cross C. The
remaining two crosses perhaps should be discarded as
their average performance is less than the average of the
control cultivars.
It should be noted that the four crosses have different
mean yield values but also there are large differences
in the genetic variance (
g
. Would our decision now
change if we consider the '
best
' cross based on the mean
and variance?
First it is necessary to set a target value on which
the prediction is to be based. As there were a number
of commercial cultivars included in the cross prediction
trial it may be useful to use as the target value the average
performance of the controls (21 t/ha).
When this target value is used the four crosses were
estimated to have A
σ
)
=
=
=
42.4%, B
63.7%, C
=
54.4% and D
27.8% of their progeny to be greater
(or equal) to the mean of the control entries. Again
if these were the criteria used then greatest emphasis
should be put on cross B, followed by cross C, A and
that is used in the estimate and not the genetic
variance (
σ
g
)
g
σ
)
. Even when there are large differences
Table 7.11
Progeny mean, genetic variance and genetic standard deviation of progeny
from four different parent cross combinations, and the probability that a genotypes chosen
at random from each cross will exceed a specific target yield.
g
σ
σ
g
=
=
=
Cross
Mean
T
21
T
24
T
26
A
20.3 (3)
24.13
4.91
0.424 (3)
0.209 (3)
0.111 (2)
B
22.0 (1)
8.11
2.85
0.637 (1)
0.242 (2)
0.081 (3)
C
21.5 (2)
19.24
4.38
0.544 (2)
0.284 (1)
0.153 (1)
D
18.0 (4)
20.05
5.10
0.278(4)
0.119 (4)
0.058 (4)
