Agriculture Reference
In-Depth Information
to the advanced stages, will have been assessed over
several years (and in many of these years, assessment
will have been carried out at a number of different
locations). Therefore the amount of data storage space
needed for each record will depend on the stage that has
been reached in the breeding scheme.
Germplasm databases have several differences com-
pared to plant breeding databases. Germplasm
databases hold information on a wide range of differ-
ent genotypes. However, unlike a breeding database,
new accessions (or records) are added but very rarely
are records deleted. Information stored in a germplasm
database will have been collected over years and sites but
not all accessions will have been assessed in a common
environment. It is therefore necessary to rate accessions
(e.g. ona1to9scale or A, B, C, etc.) so that com-
parisons can be made. It is vary rare that actual yield
data (e.g. t/ha) are stored on a germplasm database it is
more likely that a particular accession will be rated as a
particular 'score' for yield.
Irrespective of the type of database, each record (test
entry or accession) will be assessed for a number of char-
acters or traits of interest. Variates can be of two forms,
numerical (e.g. disease rating of 2, yield of 25.32 t/ha)
or character (e.g. alpha/numeric character string like
'Yellow flowers'). In addition the different database
types will hold other information not related to sim-
ple assessment, for example, an alpha/numeric string
to identify the particular genotype (e.g. PI.23451 or
89.BW.11.2.34) and parentage of the line. Germplasm
databases may store information not usually stored on
a database for example, species name, ploidy level,
source of origin of seed, age of seed, amount of seed
available etc.
When a particular genotype entry is introduced into
a plant breeding programme it is usually identified by
an alpha/numeric code. For example, cultivars will have
specific names 'Jack's Wonder'. Genotypes, which have
derived from other germplasm collections, will have an
accession number. For example USA plant introduction
lines all have PI numbers (e.g. PI.12342).
Different genetic lines, which have derived from a
breeding scheme, will generally have similar identifying
codes. Genotype codes can be assigned in numerical
order (e.g. line 1, line 2, etc.). It is more useful to assign
an identifying code, which provides some information
regarding the background of a specific genotype. For
example in a specific rapeseed/canola breeding group
all crosses made are assigned a code identifier which
includes the year of crossing, a two letter code of the pur-
pose behind the cross and a numerical number. A cross
identified by 93.WI.123 would indicate the 123rd cross
made in 1993, with the purpose of developing a winter
industrial (WI) type.
Specific individual genotypic selections from the
cross would have different trivial numbers (e.g.
93.WI.123.23, 93.WI.123.69, etc.). If some form of
pedigree selection scheme is used then additional trivial
numbers can be added to indicate the number of within
population selections made.
In setting up a suitable database the user must decide
on a suitable database structure . This will determine
the number of entries, which are to be tested in each
trial, the number of locations where evaluations will be
carried out at each stage and the number (and type) of
data that is to be stored.
Irrespective of the type of database or form of
data storage the primary aim is the same, to make
information available for inspection in a clear and
concise form.
Field plan design
Field trials and experiments are of major importance
in a successful plant breeding programme. The ability
to use computers for randomization has been realized
for many years and most programmes use some form
of computer generation of field trials. These pack-
ages use entered information such as type of design,
experiment title, number of entries, number of repli-
cates etc. and produces a randomization along with a
map representation of how the plots will appear in the
field.
Once a computer has generated a field design it is
possible to store all the trial details, number of entries,
entry codes, actual randomization, on a database sys-
tem. This information can be retrieved later for analysis
of data or producing plot labels.
Clerical operations
Despite advances made in database management, the
ability to carry out complex selection strategies or anal-
ysis using computers the simplest and most useful task
a computer can do for a plant breeding programme is
to perform as many of the routine clerical operations as
possible. Several years ago, all plant breeding schemes
 
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