ESTIMATE OF GENETIC COMPONENTS OF BIRTH WEIGHT USING MULTI-BREED MODELS WITH DIFFERENT PEDIGREE STRUCTURES IN MESTIZO SHEEP

The objectives of this paper were to verify the influence of the multi-breed model and pedigree structure in the estimates of the genetic components to birth weight in a mestizo herd. Using 1234 birth weight records in two ways, one dataset with complete pedigree information (n = 1028) and another with incomplete pedigree information (n = 1234). The pedigree was composed for 10 sires, 366 and 448 dams for complete and incomplete pedigree, respectively. Used for analysis the maximum restricted likelihood method about the animal model, considering the birth weight trait, for a dataset with or not complete pedigree, used the WOMBAT program. The direct heritability coefficients in both datasets did not present large difference, 0.06 and 0.09 to best models in the complete and incomplete pedigree, respectively. However, in the incomplete pedigree, the maternal heritability was 0.29. The residual variance, which on the best model of the dataset with complete pedigree presented 0.51 and 0.35 for the best model of the dataset with incomplete pedigree. Concluding, we find the influence of de multi-breed model only in the dataset with complete pedigree, that considered the direct and breed effects. In the dataset with incomplete pedigree, the better model was that considered the direct and maternal additive effects.

Backcross Aiming at the Resistance of Passion Fruit to Soil Pathogen

Brazil is the world's largest producer of passion fruit, however, the crop suffers from serious phytosanitary problems, as well as those caused by soil fungi. Thus, the objective of the present work was to estimate the genetic parameters and to select genotypes resistant to Fusarium solani species complex—FSSC in a segregating population from the first generation of backcross among P. edulis and interspecific hybrids, aiming at advancing generation in the genetic improvement program of passion fruit. The Interspecific Hybrid was used (IH) UNEMAT 142 resistant to colon rot, for generation advancement and to cultivate BRS Sol do Cerrado (Passiflora edulis Sims). In order to evaluate the resistance of the 27 genotypes of the first generation of backcrosses, inoculation with the FSUNEMAT 40 (F. solani) inoculum was performed. To estimate the components of variances, the method of maximum restricted likelihood (REML) was used and to select the best genotypes by the non-addicted linear prediction (BLUP). The variables that showed the highest heritability values were the survival period and the area under the lesion length expansion curve. The three families of backcrosses presented genotypes resistant to the fungus F. solani, however, by the methodology of mixed models REML/BLUP, only the genotypes BC1-22/1, BC1-22/2, BC1-22/3, BC1-22/4, BC1-22/6, BC1-22/7, BC1-113/3, BC1-113/7 and BC1-113/8, were selected to advance the generation of the UNEMAT passion fruit breeding program, therefore, they presented among the ten placed, mainly for the variable survival period (SP).

Spatial scan statistics can be dangerous

Spatial scan statistics are widely used tools for the detection of disease clusters. Especially, the circular spatial scan statistic proposed by Kulldorff along with SaTScan software has been used in a wide variety of epidemiological studies and disease surveillance. However, as it cannot detect non-circular, irregularly shaped clusters, many authors have proposed non-circular spatial scan statistics. Above all, the flexible spatial scan statistic proposed by Tango and Takahashi along with FleXScan software has also been used. However, it does not seem to be well recognized that these spatial scan statistics, especially SaTScan, tend to detect the most likely cluster, much larger than the true cluster by absorbing neighboring regions with nonelevated risk of disease occurrence. Therefore, if researchers reported the detected most likely cluster as they are, it might lead to a criticism to them due to the fact that some regions with nonelevated risk are included in the detected most likely cluster. In this paper, to avoid detecting such undesirable and misleading clusters which might cause a social concern, we shall propose the use of the restricted likelihood ratio proposed by Tango and illustrate the procedure with two kinds of mortality data in Japan.

Stability and adaptability for wood volume in the selection of Eucalyptus saligna in three environments

The objective of this work was to evaluate the genotype x environment (GxE) interaction in open-pollinated Eucalyptus saligna progenies for simultaneous selection for greater stability and adaptability for wood volume, as well as to compare the selection strategies through combined and individual analyses in three environments. Three experiments were conducted in a randomized complete block design, with four replicates and six plants per plot, with 102 to 122 progenies. Three years after planting, survival rate and wood volume were evaluated. The genetic parameters were estimated by the maximum restricted likelihood and best linear unbiased prediction (REML/Blup) methods, and the stability and adaptability analysis was conducted using the harmonic mean of the relative performance of genetic values (HMRPGV). The highest survival rate (82%) was observed in Sabinópolis and the highest volume (120 m³ ha-1) in Lençóis Paulista. The mean heritability of progenies for the two analyzed variables was considered high, and the genetic correlations between survival rate and volume were weak for all sites. The G×E interaction was significant and of the complex type, with genotype correlation between sites of 47%, indicating that the ranking of the best progenies differed in each studied environment. The analysis of stability and adaptability indicated the possibility of selecting progenies with good performance in the three environments; however, to improve the quality of the evaluated characteristics, it is necessary to select specific progenies for each environment.