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Evaluating a selection index for improving body weight and egg production in a simulated population of broilers.Tempest, Justine Claire. January 2009 (has links)
The most successful method used for improving the growth rate of broilers is genetic
selection. Improvements in nutrition, housing and disease resistance have been
impressive, yet genetic selection is purported to have contributed the majority of the
tremendous increase in growth rate that has taken place over the past 50 years (McKay,
2008). Many selection strategies are available, but not all are suitable, as the choice is
dependent on the objective of the breeder. Selection strategies are bound to change over
time as different traits become more important, and this has been the case in the broiler
industry: focus was initially placed predominantly on growth rate, but the negative genetic
correlation that exists between growth rate and reproductive and liveability traits has
forced breeders to change their position, especially as growth rate has almost reached its
upper limit and reproductive traits lag behind. This has resulted in a change from single
trait to multiple trait selection.
In the exercise reported here, four selection strategies commonly used for single trait
selection, namely individual, between family, within family and family-index selection, were
applied to a simulated broiler population using the Monte Carlo method of simulation, and
constructed with the use of genetic parameters obtained from the literature. Theoretical
and simulated methods of the four selection strategies were compared. A fifth selection
strategy, index selection, was applied to represent multiple trait selection. The relative
merit of each selection procedure was then compared, as well as the results obtained
from the theoretical and simulated methods. Construction of the selection index was
complex in comparison to single trait selection, as each trait included in the index had to
be assigned an economic value. This value is representative of the relative importance of
that trait to the overall profitability, or ability to save costs in the operation. Therefore traits
favourable to profitability, or having the ability to reduce production costs, are given a
heavier weighting and will consequently achieve a relatively larger improvement when
applied to the selection index. A model was constructed using production rates, income
and costs to represent the current overall economic situation in the industry. This was
then used to determine cost economic values, which represent the saving in cost per unit
improvement in each of the economically important traits, and revenue economic values,
calculated as the value of each unit improvement attained in each of the economically
important traits. Body weight remains the most profitable trait in a broiler enterprise; however breeder egg
production is equally important as the industry would fail without sufficient day-old broilers.
Therefore, it would be beneficial to determine whether current egg production levels could
be maintained, or even improved, whilst improvement is made to the growth rate of the
progeny.
The above statement was found to be possible with the use of index selection. This
multiple trait selection strategy proved capable of defying the negative genetic correlation
that exists between body weight and egg production by improving egg production to 60
weeks by eight eggs, and body weight at 35 days by 259 grams. Furthermore, in some
cases index selection was able to achieve improvements in some traits greater than those
attained with single trait selection, whilst simultaneously improving certain negatively
correlated traits. Index selection has illustrated its superiority over single trait selection
strategies and its relative value to the poultry industry. / Thesis (M.Sc.Agric.)-University of KwaZulu-Natal, Pietermaritzburg, 2009.
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Development of computer models of different selection strategies on poultry egg production.De Guisti, Jonathan. 18 October 2013 (has links)
Poultry have many behavioural, structural and biological features that are ideal for domestication
and for meat and egg production (Appleby et al., 1992). Because of the importance of poultry
meat and eggs to the human population, breeders and farmers are always looking for ways of
improving these traits. Artificial selection is the primary method of trait improvement, and
involves selecting individuals with the highest breeding values as parents in each generation.
There are a number of different methods of artificial selection, including: individual selection,
between family selection, within family selection, family-index selection and index selection.
In order to maintain a good response to selection breeders are constantly striving to improve the
effectiveness and accuracy of the different methods of artificial selection for traits of economic
importance. One method of achieving this goal is the use of computer models. Computer
models can be used to simulate selection strategies and to predict what strategy will be the most
appropriate for the improvement of a particular trait. This is important as all traits are influenced
by many different genetic and environmental factors (Falconer and Mackay, 1996).
This investigation was designed to compare the effectiveness of five different artificial selection
strategies, namely individual selection, between family selection, within family selection, family index
selection and index selection. Five computer models were developed using Microsoft
Excel 2000 and these models were then used to compare the efficiencies of the five selection
strategies for four different traits. The selection techniques were applied to an artificially,
randomly generated population of 500 chickens. The four traits were egg weight with a
heritability of 0.51, egg production with a heritability of 0.22, age at first egg with a heritability
of 0.41 and body weight with a heritability of 0.55. Firstly, each of these traits were selected for
independently using the first four selection methods and secondly the traits were selected for two
at a time using index selection. The most significant results obtained from the single trait simulations were that for all traits
family-index selection produced the best response to selection in the initial generations and
between family selection produced the best response in the later generations. The traits with a
higher heritability (egg weight and body weight) responded better to individual selection than
they did to within family selection and between family selection in the initial generations.
However, within family selection and between family selection proved to be more effective for
traits with a low heritability such as egg production. Individual selection and family-index
selection resulted in a very rapid decline in the standard deviation of all the traits. Between
family selection resulted in the slowest drop in the standard deviation of all the traits, which is
why this technique produced the best responses to selection in the later generations. The impact
of the correlations between the economically important traits were evident from the results of
index selection. For example, egg production is negatively correlated with egg weight making it
difficult to gain a correlated response in both these traits simultaneously. Furthermore, egg
production is negatively correlated with age at first egg implying that early maturing birds will
lay more eggs, however, these eggs will be lighter.
The majority of the results obtained were to be expected. Family-index selection takes all the
information about an individual's breeding value into account resulting in this method of
selection consistently identifying the most desirable individuals being selected. It is therefore the
preferred method of selection under all circumstances. It is, however, often not economically
and practically efficient to incorporate this technique and the use of another method of selection
usually proves to be more beneficial. Individual selection proved to be most effective when
applied to traits with high heritabilities, due to the fact that this method selects individuals based
on their own phenotypic values. For traits with a high heritability, an individual with a good
phenotypic value will have a good breeding value. Between family selection and within family
selection proved better for traits with lower heritabilities. For traits with a low heritability the
phenotypic value of an individual is a poor indicator of its breeding value. Information from a
number of relatives may thus improve the accuracy of prediction of the breeding value by
accounting for the influence of environmental effects. The use of computer models to simulate the selection techniques proved very successful in
illustrating the effectiveness of the different selection techniques under various genetic and
environmental conditions. The models may also prove to be very effective from an educational perspective. / Thesis (M.Sc.)-University of Natal, Pietemaritzburg, 2003.
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