4 - Central Institute of Brackishwater Aquaculture

Natlonal Workshop-cum-Tralning on Blointwmatlo and Inf0~8th Management In Aqwcuitum
Use of SAS in Rohu selective breeding program-case study
In the rohu selective breeding program, individual tagging was done to identify
fishes of different fullsib families in the communal pond. After fishes attained
taggable size i.e. 10-15 g they were tagged with Passive Integrated Transponder
(PIT) tags and stocked in communal rearing ponds for further grow out
experiment. Before tagging, initial body weight of fishes was noted and during
final sampling also final individual body weights were noted.
7. Adjustment of fixed effects
All recorded data need to be carefully edited to eliminate errors during recording.
Special attention was paid to the outliers (too small or too large value for trait or
an ID) and individual having same ID.
As selection index procedure is used to calculate breeding value, the data need
to be preadjusted for fixed effects i.e, pond. Multiplicative adjustment is applied
in the rohu-breeding program.
Estimation of breeding value
After adjustment of pond effect, corrected body weights are being considered for
the estimation of breeding values. It is estimated using following formula
Where
I = Predicted breeding value
P, = Adjusted phenotypic record on the individual
Pf, = Adjusted phenotypic mean of n-fullsibs, PI included in Pf,
Ph, = Adjusted phenotypic mean of mn halfsibs, P, included in Phs and m is the
number of dams nested to each sire.
P,= Adjusted population mean
bl b2 b3=the weight s given to each source of information
The mixed procedure
The mixed procedure fits mixed linear models (models with both fixed and
random effects). A mixed model is a generalization of the standard linear model
used in the GLM procedure. One can analyze the data with several sources of
variation instead of just one.
Some features of MIXED model are as follows,
Covariance structures, including simple random random effects, compound
symmetry, unstructured data
GLM type grammar using .MODEL, RANDOM and REPEATED statements for
model specification and CONTRAST, ESTIMATE AND LSMEANS statement for
inferences
Appropriate standard errors for all specified estimable linear combinations of
fixed and random effects and corresponding t- and F test.