Effect of Different Progeny Test Strategies in the Performance of Eucalypt Clones

Abstract

The objective of the present study was to investigate whether the performance of an individual in clonal testing was affected by the location of the initial selection. The study also evaluated the effect of mass selection and BLUP (Best Linear Unbiased Prediction) on the performance of individuals in the progeny test and the clonal test. In the progeny test, 62 half-sib E. grandis families, 68 half-sib E. urophylla families and 62 full-sib families between E. grandis and E. urophylla, plus four checks were evaluated totaling 196 treatments. The experiments were carried out at three sites: Aracruz and São Mateus, in Espírito Santo State and Caravelas, Bahia State, Brazil. The 1000 best individuals were classified by mass selection and BLUP. In the clonal tests 257 clones were evaluated in two locations: Aracruz and Caravelas. In both the progeny test and the clonal test, two years after planting, the circumference at breast height and basic wood density were measured and the sum of standardized variables (Z) was estimated for simultaneous selection of both characteristics. The results indicated that the origin of the individual in a progeny test had a small effect on the performance of the clone when evaluated in other environments; the estimates of realized heritability and the linear regression coefficient were small in all the selection strategies. Thus, the correlation between the performance of trees selected in progeny tests and their respective clones in the clonal test was small.

Twelve Years into Genomic Selection in Forest Trees: Climbing the Slope of Enlightenment of Marker Assisted Tree Breeding

“…If final deployment of improved genetic material is by clonal propagation, the route will depend whether the track record of the breeding program has shown that the individual tree performance in a progeny trial is a good predictor of its performance as a clone. This has been shown not to be always the case in the few studies that examined this issue in tropical hybrid eucalypts, for example [87,88]. If the correlation of individual performance versus its clone is high, the genomic expected genotypic values (GEGV) of the candidates are estimated and selection practiced using a model that takes into account non-additive effects.…”

Realized genomic selection across generations in a reciprocal recurrent selection breeding program of Eucalyptus hybrids

“…Although the EGVs were calculated from the trees’ observed performances, rank position at the extremes of the distribution might be impacted by additional non-additive variation unaccounted by the model. In fact, it has been reported that the correlation of growth performance of a eucalypt “urograndis” hybrid ortet and its clonal ramets is typically poor ( Furtini et al., 2012 ; Van Den Berg et al., 2015 ). Only a replicated field clonal trial of a more generous selected proportion of top GEGV ranked individuals might ultimately capture the top EGVs ranked trees.…”

Implications of the population effect in the selection of soybean progeny

“…In soybean breeding, the use of the effect of the population for the estimation of genetic and phenotypic components is often neglected. However, the use of this information in forest breeding (Cappa et al., ; Furtini, Ramalho, Abad, & Aguiar, ) and animal improvement (Daetwyler, Kemper, Van Der Werf, & Hayes, ; Keller & Waller, ; Li et al., ) helps to improve the accuracy of estimates and hence the selection of superior genotypes. Duarte and Vencovsky () point out that the inclusion of population information can change the ranking of progeny, even in balancing and orthogonality conditions and hence the genetic and phenotypic components, as observed in this study.…”