Agriculture Reference
In-Depth Information
Selection
Understanding data and interpreting results from multi-
location trials are a great aid in selection from such
trials. Factors of importance in selection will include
genotypic stability (or lack of ) and correlation between
characters over environments and between traits within
a single location.
Finally, efficient selection with the very large data sets
that are common in the advanced selection stages can be
helped by inspection of performance ranking. Indeed
it has been shown that summing the rank of individual
traits (or single traits over environments) will produce
similar results to multi-variate probabilities. Summing
ranks can be considerably easier to compute than find-
ing the area under an
n
-dimensional normal frequency
distribution.
Low inefficiency is, in part, the result of:
The inaccuracy of selecting on small plots (often
single plants) because of the error variance and sam-
pling variation along with competition effects of
surrounding plots. This is not helped by the inabil-
ity to adequately replicate and/or randomize the vast
number of genotypes involved at the earliest selection
stages
•
•
Selection under atypical conditions which do not
mimic plant spacing etc. that would be common in
commercial production
•
Selection amongst highly heterozygous lines where
genotypic worth can be severely masked by domi-
nance effects (inbreeding species only)
Selection in the early stages is most ineffective for
quantitatively inherited traits such as yield, quality and
durable disease resistance. If early generation selection
is purely a random (or near-random) reduction in the
number of lines which are to be tested at the intermedi-
ate stage then it is questionable whether this operation
will merit the time and resource to complete the task. It
has therefore been suggested that a more effective proto-
col would result from growing fewer breeding lines and
doing no selection at the earliest stages. The reduced
effort and resource at the early generation stage could
therefore be used more efficiently to screen more geno-
types at the intermediate stage (where efficiency due to
replication and larger plots is more effective).
An alternative method of reducing the numbers
involved in early to intermediate selection is available.
This procedure involves the identification of the most
attractive cross combinations from the many that would
be possible, assuming that there is greater probability of
obtaining a successful cultivar from the most desirable
cross combinations. Having identified the '
best
' crosses
then maximum effort and resource can be directed to
screening individual recombinants from within these
lines, while the '
poorer
' crosses are completely discarded.
This process is called
cross prediction
.
CROSS PREDICTION
The number of breeding lines discarded in a plant breed-
ing programme is inversely proportional to the number
of selection rounds. In the early stages there are many
thousands of lines evaluated with a low proportion that
are selected for testing at the intermediate stage. At the
advanced stage a few surviving lines are tested with great
intensity with only a few lines being discarded after each
selection stage.
A number of researchers have shown that selection
in the initial stages (that period where the greatest pro-
portion of genotypes, and hence the greatest genotypic
variation are discarded) is the most ineffective stage
at identifying the most desirable lines. At the early
generation stage, selection has been shown to result
in, at best, only a random reduction in the num-
ber of genotypes within the breeding scheme. Some
advances (particularly for qualitatively inherited traits)
have shown a response to initial selection although some
have shown a negative response where the best phe-
notypes under conditions of early generation selection
have been shown to be those least likely to become
commercial cultivars.
Therefore, the early generation selection stage of a
plant breeding programme is often very ineffective in
terms of selection. This inefficiency is in part simply due
to low heritability in performance in the early selection
stages compared with those in more advanced levels.
Univariate cross prediction
As we noted briefly earlier, methods of predicting the
properties and distribution of recombinant inbred lines
(derived by inter-mating homozygous parents) using