AN EMPIRICAL COMPARISON OF DIFFERENT METHODS OF SIRE SELECTION: A BREEDING VALUE APPROACH 2916
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Date
2019-08
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
JAU, JUNAGADH
Abstract
A total of 323 daughters of 44 sires maintained for first lactation records and
833 daughters of 44 sires maintained for all lactation records at Cattle Breeding Farm,
Junagadh Agricultural University, Junagadh from 1988-2017 were analysed to
compare various sire evaluation methods for 300-DMY, LL and CI. Sire evaluation
was done using conventional indices (viz. Modified Simple Daughter Average index,
Equiparent index, Norton index, Rice index, Tomar index, Corrected Daughter
Average index, Contemporary Comparison method and Corrected Contemporary
Comparison method), Least Squares method (LS), Best Linear Unbiased Prediction
(BLUP) and Average Information Restricted Maximum Likelihood Method
(AIREML).
BLUP and AIREML models were constructed using univariate models,
repeatability models, multivariate models using three traits in all possible combination
for first lactation records as well as all lactation records. Criteria for comparison of all
the models involved error variance to measure the efficiency of models, additionally,
coefficient of determination (%) (R
2
values) and coefficient of variation (CV%) were
used to measure the accuracy and stability of models respectively for LS, BLUP and
AIREML.
The results indicated that the I-1 model and LS models were found to be quite
satisfactory looking % relative efficiency (99.25), error variance (2566.31 kg2
), range
(420.13 kg) and % proportion of sires having equal or more breeding values than
average for 300-DMY. For LL, AF-23 model was found satisfactory looking to
ABSTRACT% relative efficiency (100%), error variance (752.44 days2
), range (293.24 days) and
% proportion of sires having equal or more breeding values than average (52.27%)
followed by models AF-123 and I-1 & LS with nearby result with AF-23. For CI, AF 23 model was found satisfactory looking to % relative efficiency (100), error variance
(463.76 days2
), range (251.77 days) and % proportion of sires having equal or more
breeding values than average(68.18). The next best models were BF-123 with 98.25%
and I-1 & LS with 89.40% relative efficiency. The rank correlation among all
conventional indices and Least Square were found positive and highly significant for
300-DMY and CI under study except the rank correlation of I-1 for LL.
For 300-DMY, AF-12 was inferred as the most efficient model of sire
evaluation with the least variance, while LS and I-1 were found next best models with
2566.31kg2
error variance. LS with relative accuracy 97.87% was observed as next
best accurate models after BF-13 (100%). LS model had their lower CV% as
compared to other models. LS had highest stability for 300-DMY. The sires having Id
5, 24, 27 and 37 out of top ten sires were commonly selected by the most efficient,
accurate & stable models AF-12, BF-13 and LS, respectively.
For LL, AF-23 model was found the most efficient model with least within
sire variance (752.44 days2
) while, LS and I-1 had 98.27% relative efficiency. BF-12
was more accurate with 83.2% R2
value and was considered as the most accurate
method, followed by LS and I-1. AF-12 had highest stability in LL with lowest CV%.
The sires having Id 24, 29 & 35 out of top ten sires were commonly selected by the
most efficient, accurate and stable models AF-23, BF-12 and LS, respectively.
For CI, AF-23 showed least error variance and thus was inferred as the most
efficient method, while, LS had 89.40% relative efficiency. BF-23 had the highest
accuracy with R2 (92.45%) among all the models. The next best accurate model was
BF-123. Looking to the stability criteria, LS had lower CV% among all models
showing. Thus, LS was inferred as most stable model. None of the sires out of top ten
were commonly selected by the most efficient, accurate and stable models AF-23,
BF-23 and LS, respectively, but sire Id 29 and 36 were selected as common by AF-23
and BF-23 models.
It is clear that all first lactation models (F-models) had lower R2
values, had
higher CV% and error variance values than their corresponding all lactation models (A-models). Thus use of all lactation records leads to increase in accuracy, stability
and efficiency of predicting breeding values for 300-DMY, LL and CI.
For 300-DMY AF-12, BF-13 and LS proved to be most efficient, most
accurate and most stable model, respectively, while. AF-23, BF-12 and AF-12 proved
to be most efficient, most accurate and most stable model, respectively for LL. For CI
AF-23, BF-23 and LS proved to be most efficient, most accurate and most stable
model, respectively. Use of models incorporating all lactation records instead of those
incorporating first lactation records for sire evaluation provided more accuracy,
stability and efficiency for all traits. Hence, sire evaluation must be done considering
all the available lactation records of the animal