Agriculture Reference
In-Depth Information
randomize each individual head-row, but randomiza-
tion at this early generation stage can greatly increase
efficiency. One option is to utilize nested designs. For
example, say that a canola breeding programme has 200
cross combinations to evaluate and that there are 100
individual single plant selections taken at the F
3
stage.
Therefore there would be 2000 F
4
head-row plots that
would be planted in the field. A randomized complete
block (with control entries) would be very large. In
addition, from a practical aspect, it is often difficult
to examine a single row plot, on-its-own. As an alter-
native the 200 crosses could be randomized into five
replicate blocks, and the 100 single plant selections are
grown as rows within cross blocks. Each cross, there-
fore, would be represented by five sub-blocks (groups)
of 20 head-row plots (grown adjacent), and replicated
five times throughout the whole trial.
If control entries are arranged in a systematic order
it will be possible to make direct comparisons of indi-
vidual test entries to the nearest control plot, which
can have advantages. For example, it makes possible the
analysis of the data collected using
nearest neighbour
techniques, where plot values are adjusted according to
the performance of appropriate surrounding test entries.
(a)
Randomization, no controls
5
31
43
14
26
53
11
22
40
32
56
9
20
39
50
18
7
29
45
51
46
47
38
41
55
48
17
15
34
28
10
12
27
6
15
36
3
37
54
44
23
4
52
49
19
35
2
21
33
24
25
1
30
42
13
8
(b)
Randomization, systematic controls
38
33
C.1
40
42
20
C.1
13
C.3
21
8
12
C.3
7
C.1
1
39
2
C.1
34
22
41
24
23
C.3
35
28
14
29
4
C.2
15
3
37
C.2
5
C.4
36
16
19
C.4
6
C.2
18
26
27
C.2
25
17
32
30
9
C.4
11
31
10
Figure 9.2
Randomized single replicate plot designs
without control entries (top) and with control entries
arranged systematically throughout (bottom).
•
Randomized designs with control entries, where the
test entries are randomly allocated plot positions
within the trial (Figure 9.2 (b)). Control entries can
also be randomized throughout the design (and often
replicated in more than one plot) or they can be
arranged in a systematic order (e.g. every 5th plot)
with again the option of having replication only for
the control entries.
Randomized designs
It is possible to obtain an estimate of error variance from
single replicate designs which have multiple entries of
chosen control cultivars. However, it is more common,
if possible, to replicate both test lines and control cul-
tivars in order to have a better estimate of the average
performance of each entry, along with the variance in
its performance, and also to obtain a better and more
representative overall estimate of error variance.
The efficiency of evaluation trials will always be
increased by randomization, and non-randomized trials
should be avoided if at all possible. Similarly, it would
be very unwise to organize any breeding evaluation tri-
als without including any control entries against which
the test lines will be compared. Without these consid-
erations the trials are generally uninformative and often
misleading.
In the early generations of a plant breeding scheme,
there may be many hundreds or thousands of geno-
types to be tested, each with only a limited amount of
planting material. In many breeding programmes, the
first 'actual' field trials are conducted on head-row plots,
where each plot has resulted from a single plant selec-
tion the previous year. Where thousands of lines are to
be tested, it may be extremely difficult to completely
Completely randomized designs
If there is no knowledge of fertility gradients or other
environmental variation, which exists within a test area,
many suggest that complete randomization be used to
identify superior breeding lines. In such a design each
of the test and control entries are allocated at random
to specific plot positions (Figure 9.3 (a)). Each entry is
repeated a number of times according to the required
number of
replicates
. The error variance is estimated
from the variance between replicate test entries.
