Principles of Plant Genetics and Breeding

esources available (land, seed, labor), and the statistical
design used. Replications increase the precision of the
experiment and help the plant breeder more effectively
evaluate the genotypes to identify superior ones.
Minimizing operator errors Data collection and analysis
provide opportunities for human errors to occur.
Computer software such as MSTAT (a statistical package
developed by Michigan State Crops and Soil Science
Department) will allow the breeder to generate a customized
data collection book. Where a machine or
equipment is to be used, it should be properly serviced
(cleaned, calibrated).
The plots should be planted uniformly and managed
uniformly (i.e., uniform spacing, fertilizing, irrigating).
Border rows should be planted uniformly. Each plot is
not enclosed in border rows. The plants at the end of
rows have a competitive advantage over those in the
inner part of the rows. Mechanized harvesting usually
starts at the first plants of the middle row and proceeds
to the last plants. This may introduce yield inflation and
may require adjustment of plot yields.
Principles of experimental design
There are many experimental designs used to allocate
treatments to experimental units. However, they are all
based on three basic principles – replication, randomization,
and local control.
1 Replication. The principle of replication is critical
for estimating experimental error, as previously indicated.
It is also used for reducing the magnitude of
error in an experiment.
2 Randomization. This is the principle of assigning
treatments to experimental units such that each unit
has an equal opportunity of receiving each treatment.
This action eliminates bias in the estimation of
treatment effects and makes the experimental error
independent of treatment effects – a requirement
for a valid test of significance of effects. Systematic
arrangement allocates treatments to experimental
units according to a predetermined pattern.
3 Local control. Sometimes, researchers find it more
efficient to impose restrictions on randomization to
further minimize experimental error. This is appropriate
when there is a gradient in an environmental
factor (e.g., fertility, moisture). Fertility is different at
the top of a slope than at the bottom as mentioned
before. Rather than ignoring this obvious variation,
a technique called blocking may be used to divide
PERFORMANCE EVALUATION FOR CROP CULTIVAR RELEASE 429
the field into distinct areas, maximizing the variation
between blocks and increasing the homogeneity
within blocks. Statistical analysis is then used to
extract interblock variation, thereby reducing the
total error in the experiment.
Field plot designs
Plant breeders use experimental designs to arrange
genotypes in a trial to minimize experimental error. The
designs vary according to the purpose of the evaluation,
the nature of the genotypes (e.g., segregating or nonsegregating),
the number of genotypes, the stage of a
breeding program (e.g., preliminary or advanced yield
trials), and resources.
Evaluating single plants
No design arrangement
Breeders using certain methods may select among segregating
plants, starting in the F2 generation, on a single
plant basis. Generally plants are spaced in a completely
random arrangement.
Advantages
1 Inexpensive and easy to conduct.
2 Large number of genotypes can be evaluated at any
one time.
Limitations
1 If a large land area is involved, the chance of soil heterogeneity
effect increases. Inferior plants growing in
fertile soil may outperform superior plants growing in
less fertile spots in the field.
2 It is suitable for evaluating plants on the basis of traits
with high heritability but less effective for evaluating
traits with low heritability.
Modifications It is helpful to plant rows of standard
cultivars in adjacent plots for comparison, to aid in
efficient and effective selection of superior genotypes.
Grid design
First proposed by C. O. Gardener, the grid design entails
subdividing the land into smaller blocks. The rationale is
that smaller blocks are likely to be more homogeneous
than larger blocks. Plants are selected based on comparison
among plants within each block only.