Application de la théorie des indices de sélection à des caractères répétés. Exemple de la sélection sur la prolificité chez le porc

Abstract

RésuméPour des caractères répétés (production laitière, prolificité...), l'indice de sélection (1 . ) Example of the selection on prolificacy in pigsThe selection index (I.) which is classically used for repeated characteristics (e.g. milk production, prolificacy) is based on an average of n measurements and depends only on the coefficients of heritability (h z ) and repeatability (r) of the trait concerned. As an alternative, a combined index (I . ) i-suggested in which each observation is weighted by a coefficient calculated according to H AZEL ' S theory ; this takes into account genetic correlations (r.) between repeated performances. For a desired breeding goal (H), this index is compared to the conventional one by varying the number of observations made (1 to 5), the values of h 2 (0.1 to 0.6) and r G (0 to 1 in steps 0.1). For a given value of these parameters, the accuracy (correlation between H and I) and the efficiency (expected genetic improvement on H by selecting on I m and I c respectively) of I m and 1, are almost the same. The greatest loss of accuracy of 1 m relative to 1 . is 9 p. 100 ; the difference being more marked as r G is lower and n greater. The accuracy and efficiency of both I m and 1. are improved with increasing n and this is amplified by increasing r o and decreasing h 2 values. If the hypothesis of r! = 1 is wrong, the accuracy and the efficiency of selection may be overestimated ; this overestimation is all the larger as the number of measures is higher ; it also varies with heritability. For example, in the case of selection on prolificacy in pigs (h 2 = .10), overestimation of the expected genetic progress may be 300 p. 100. This character is discussed according to estimations of r G made in the literature ; these estimations are variable but lower than 1 and this may partly explain the discrepancies between theoretical expectations and the actual results obtained in selection experiments.

Estimação de parâmetros genéticos em tamanho de leitegada de suínos utilizando análises de características múltiplas

“…Assim, se esta última situação for verdadeira, uma análise multicaracterística deveria ser executada para o aumento da eficiência de seleção para tamanho de leitegada e a obtenção de predições não-viesadas da resposta genética esperada (Tartar & Bolet, 1984).…”