AGB 211: Livestock and Poultry Breeding (2+1)

SELECTION INDEX OR INDEX SELECTION OR TOTAL SCORE METHOD

• It is the most effective method of selection. Selection index is a single numerical value within the total scores given for each trait considered in the selection. Each trait is weighted, by giving score and an individual trait score is summed up to the total score for the each animal within the selection criteria. The individual specification for a number of traits can vary greatly and is combined into one value for the animal called a Total score or an Index. The high merit in one trait can certainly be used to compensate the deficiencies in other traits. An index is simply a means of putting a whole lot of different information into one value. The information and the score should be fixed based on
• Variation seen in each trait – the phenotypic standard deviation
• Heritability of the traits
• Phenotypic and genetic relationships (correlation) between the traits
• Relative economic value of the traits
• The aim in computing an index is to derive an estimate in which the various traits are approximately weighted to give the best prediction of the animal’s breeding value i.e. what it will produce when the animal breeds. An advantage of this index is suppose if one component is missing then benefit can be obtained by predicting the missing one from the others that are present.
• Index selection is predicted to be Ön times as efficient as independent culling levels where n is the number of traits involved. The greater the number of traits involved, the index becomes more reliable than the independent culling method.
• In dairy cattle, milk production is the most important economic trait, whereas the reproductive efficiency that is also important may not be as important in magnitude as milk production. Hence, higher economic value should be given to milk production and correspondingly lower economic value to the reproductive efficiency.

I = b₁X₁ + b₂X₂ + b₃X₃ + …….. + b_nX_n

Where,

I – Index value or genetic prediction

n – Number of traits of information

b₁ to b_n – coefficients obtained based on the relative importance of heritability of each trait and genetic relationships of the traits concerned.

X₁ to X_n – Measurement of each of the traits incorporated (phenotypic values)

• The animals are arranged based on index values and those with the highest scores are kept for breeding purposes and the animals with lower index values are eliminated from the breeding population. The net value of an animal is dependent upon several traits that may not be of equal economic value or that may be independent of each other. Hence, it is necessary to select more than one trait at a time. The desired traits will depend upon their economic value.
• This method of selection leads to most efficient improvement in livestock breeding. Selection indices are constructed with a view to making maximum improvement in the total performance. All the characters selected are combined into one figure.
• Index selection has been more widely used with sheep and swine than in beef and dairy cattle. Large volume of accurate data of population is necessary to provide information to compute the selection index. Indices computed from inadequate or erroneous information can be ineffective in selection. A trait that is highly heritable can be given adequate weightage than one with low heritability.
• In conclusion, the selection index is a total score that includes all the advantages and disadvantages of an animal for those traits considered for selection. The amount of weightage given to each trait depends on their relative economic value, heritability of the character and genetic correlation between characters. A trait, which is highly heritable, can be given greater score than a trait, which has a low heritability. The selection index method is the most efficient (best method) among the three (Tandem, Independent culling and Selection Index) methods because it results in better genetic improvement. The index is the best estimate of an animal’s breeding value. The only disadvantage is that the traits vary in importance from time to time and the index built at one time will not be applicable for all times. Hence, it has to be constructed and modified from time to time.