Abstract
The present study aimed to evaluate the indirect selection and establishment of improvement areas, using the basic wood density-productivity character of Eucalyptus clones in four environments located in the state of Rio Grande do Sul, Brazil (Cambará, Fortaleza, Capivara and São João). The test was conducted in the areas of CMPC Celulose Riograndense. In 2007, a network of clonal tests with 864 clones of Eucalyptus was deployed. At three years of age, the characters diameter at breast height (DBH), total height and volume were measured. The depth of Pilodyn penetration was used, for indirect measurement of wood basic density (Bd). A DBHxBd index of wood weight was created. The results showed individual heritability ranging from 0.0770 to total height and 0.5928 for Bd. The genetic correlation between DBH characters and volume was high (0.97). Thus, the efficiency of indirect selection was calculated (1.05). Therefore, it is advantageous to obtain indirect gains in volume through selection by DBH. The genetic correlation between environments ranged from 0.4014 to 0.9315 for the traits. The DBHxBd index showed significant genotype x environment interaction with genetic correlation of 0.6743 between the four environments. So, the establishment of improvement areas was performed for this character. From the interaction analysis of the environments in pairs, two improvement areas were defined for the character (Cambará-Fortaleza-São João and Capivara). Accurate measurement of DBH with the basic wood density in DBHxBd index was crucial to obtain only two improvement areas without the use of the characteristic volume. Thus, there was genotype selection optimization, since the measurement of DHB is faster and more accurate in relation to volume, which involves, in addition to DBH, the total height character.
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Nunes, A. C. P., Santos, G. A., Resende, M. D. V., Silva, L. D., Higa, A., & Assis, T. F. (2016). Estabelecimento de zonas de melhoramento para clones de eucalipto no Rio Grande do Sul. Scientia Forestalis/Forest Sciences, 44(111), 563–574. https://doi.org/10.18671/scifor.v44n111.03
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