Genetic control of productivity and genotypes by environments interaction for Eucalyptus dorrigoensis in southern Brazil

Abstract

Background: Eucalyptus dorrigoensis withstands cold weather and the occurrence of frost, making it a potential species for improvement programs in Southern Brazil where such conditions occur. However, the use of the species is still uncommon and its genetic variability remains poorly understood.d. Results:For site called Sertão Santana, the narrow sense heritability ranged from 0.46 (H) to 0.64 (MAI) and for Lavras do Sul it ranged from 0.38 (H) to 0.47 (MAI). The coefficient of genetic variation varied from 8.1% (H) to 26.1% (MAI). There is significant genetic correlation between DBH and MAI, reaching a value of 0.97. The GxE interaction was significant and mostly complex (78.7%). The best genetic materials for each environment, along with the most stable genetic materials, were identified. In addition, a thinning simulation was performed and the genetic gains for Sertão Santana and Lavras do Sul were 12.62 and 7.43%, respectively. Conclusion:The studied populations have genetic variability that can be used in breeding programs by selecting among progenies and individuals within progenies. The GxE interaction is complex, and as such, the best genetic material should be selected independently for each site. The results of this study have practical implications for the companies and offer advances in knowledge of the species for breeding programs.

Growth of Clones of Eucalyptus urophylla in Two Contrasting Soil Conditions in Plantations of Southeastern Mexico

“…These values are common in field trials due to the difficulty in controlling the effects of the environment [66]; in volume per hectare, they are considered expected values since this trait is a result of diameter, height, and survival; thus, it accumulates the environmental variation in these characteristics [67]. Our values were similar to those of clonal trials of Eucalyptus in South America [25,67,68].…”

“…The values of variance for the diameter, height, and volume per hectare were estimated for each soil type separately (Equation ( 5)), and for both together (Equation ( 6)), using the restricted maximum likelihood (REML) procedure [23], for which a linear mixed-effects model was fitted using the package "lme4" in R [20]. Clonal line and the interaction genotype × environment were considered as random effects [24], while soil type and replicate were considered as fixed effects [25,26].…”