Ann. For. Sci. 53 (1996) 123-136
DOI: 10.1051/forest:19960109

Nombre optimal de ramets par clone dans deux tests clonaux

H Muranty, F Santi, LE Pâques and J Dufour

Station d'amélioration des arbres forestiers, Inra-Orléans, 45160 Ardon, France

Résumé - Le nombre optimal de ramets par clone dans des dispositifs de tests clonaux a été étudié à l'aide de tirages aléatoires dans des données réelles de vigueur, de forme et de qualité du bois. Ces données provenaient d'un essai de 32 clones de merisier (Prunus avium) répliqué sur trois sites et âgé de 7 ans et d'un essai monostationnel de 96 clones de mélèze hybride (Larix x eurolepis) âgé de 8 ans. La précision d'estimation des valeurs génétiques et des paramètres génétiques de variance-covariance approche son maximum vers six à huit ramets par clone. Pour estimer les gains génétiques correspondant aux différentes situations pour le nombre de ramets, on a considéré que le nombre d'arbres en test était constant et que le nombre de génotypes étudiés augmentait quand le nombre de ramets par clone diminuait. Dans ce cadre, avec six ramets par clone, l'espérance de gain pour des caractères d'héritabilités comprises entre 0,20 et 0,70 est de 20 % plus importante que celle obtenue avec 18 ramets par clone, nombre de ramets par clone utilisé fréquemment dans les tests clonaux. Les résultats obtenus pour un index multilocal sont similaires à ceux obtenus pour des caractères étudiés dans un seul site.

Abstract - Optimal number of ramets per clone in two clonal tests. Many forest tree breeding programmes are now based on clonal tests with the purpose of selecting improved genotypes for clonal forestry. Of course, manpower, budget and space for tests are limited and it is important to obtain the best selection efficiency within these constraints. The present paper reports a study of optimization of statistical efficiency in clonal tests. The goal is to maximize genetic gain. We examined the consequences of trade-offs between the number of ramets per clone (ie, accuracy of evaluating genotype means) and the number of clones tested (ie, selection intensity), when the total number of trees tested is held constant. The data originated from a test of 32 clones of wild cherry (Prunus avium) aged 7 years and repeated on three sites, and from a test of 96 clones of hybrid larch (Larix x eurolepis), aged 8 years and planted on only one site. Characteristics studied were height increments, girth, branching parameters, wood quality and form notations. Clonal variability was significant at a 0.1% level for all traits, and broad sense heritabilities varied between 0.2 and 0.7 (table I). n (2 to 16) ramets per clone were randomly extracted from the whole data sets to obtain simulated data. The simulations showed that accuracy of genotype evaluation, as measured by R ² (or CD: average square of correlation between evaluated genotype mean and true genotype mean), increases with the number of ramets per clone and tends to a maximum which is the R² obtained with the whole data sets (figs 1 and 2). But with six or eight ramets, the accuracy is only 3 to 10% less than the maximal accuracy (fig 2). This results in a few changes in the ranking of clones (fig 2), but the correlation between the ranks obtained with the whole data and those obtained with each simulation remains high (table III). Variations of genetic gain with the number of ramets per clone was investigated. As an example, figure 4 shows this variation for height increment of wild cherry observed in one site: its maximum is at four ramets per clone. For many characteristics, the maximum estimated genetic gain is obtained with two ramets per clone (table III). With six to eight ramets per clone, accuracy of genotype means evaluation is sufficient and genetic gain is predicted to be 20 to 30% higher than genetic gain obtained with 18 ramets per clone, the number of ramets currently used in clonal tests. Precision of genetic variances and covariances evaluation was also investigated: it increases with the number of ramets and tends to the precision obtained with the whole data sets (fig 5). With six ramets per clone or more, this precision is still quite good.

Key words: clonal selection / optimization / genetic gain / prediction of clonal value / genetic parameters estimation

Mots clés : sélection clonale / optimisation / progrès génétique / prédiction des valeurs génétiques / estimation des paramètres génétiques