Abstract. Title of the paper: Index construction with restrictions in random regression models to change the pattern of the growth curve
Random regression models provide estimated breeding values (EBV) for the complete growth curve for any target age. The animal-specific curves can be described as the weighted sum of continuous covariates with random regression coefficients. By using the covariance matrix K of the additive genetic regression coefficients the response to index selection can be calculated for any age or time of the test period. In this study selection indexes with equality restrictions based on the eigenvectors of matrix K were used to modify the growth curve of the population. In order to demonstrate the index construction a matrix K was used, estimated from repeated measurements for body weight of bulls by using Legendre polynomials as covariates. Indexes for high and low growth rate until age at the reflection point were derived subject to the restriction of zero gain for initial and final body weight. Selection strategies for improving body weight at the end of the test period while holding the daily gain in a certain time interval on a desired level were compared. By using so-called "restrictive economic values", an aggregate breeding value for body weight was derived from EBV for individual growth curve.