Abstract
Multistage selection based on the covariates of the breeding value is studied in non-normal large populations. Expressions for expectation and variance of the target variable are given for retained sub population in the case of lognormal, skew normal and pareto distributions. Numerical illustration for optimum level of cullings for fixed overall intensity of selection is discussed. Sri Lankan Journal of Applied Statistics 2015;16(3): 149-159
Highlights
In plant and animal breeding breeder saves for reproduction a fraction of the population through truncation selection
Gopinath Rao and L.S.Singh representations of characters like weight, height and density than is normal distribution since these traits take only non-negative values (Johnson, Kotz and Balakrishnan, 1994). Another distribution to deal with non-normal data with the problem of moderate skewness is skew-normal distribution (Azzalinni and Dalla Valle, 1996; Arnold and Beaver, 2000)
The improvement is measured through genetic gain which is the difference between the means of breeding values in the selection group and the population as a whole
Summary
In plant and animal breeding breeder saves for reproduction a fraction of the population through truncation selection. The distribution of the target variable and the other traits are assumed to be multivariate normal (Bhat, 1990; Malhotra, 1973; and Young, 1974). In such cases the expression for genetic gain on the assumption of normality is not strictly applicable. M. Gopinath Rao and L.S.Singh representations of characters like weight, height and density than is normal distribution since these traits take only non-negative values (Johnson, Kotz and Balakrishnan, 1994). Gopinath Rao and L.S.Singh representations of characters like weight, height and density than is normal distribution since these traits take only non-negative values (Johnson, Kotz and Balakrishnan, 1994) Another distribution to deal with non-normal data with the problem of moderate skewness is skew-normal distribution (Azzalinni and Dalla Valle, 1996; Arnold and Beaver, 2000).
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