Genetic parameters for growth, wood density and pulp yield in Eucalyptus globulus

Abstract

Genetic variation and co-variation among the key pulpwood selection traits for Eucalyptus globulus were estimated for a range of sites in Portugal, with the aim of improving genetic parameters used to predict breeding values and correlated response to selection. The trials comprised clonally replicated full-sib families (eight trials) and unrelated clones (17 trials), and exhibited varying levels of pedigree connectivity. The traits studied were stem diameter at breast height, Pilodyn penetration (an indirect measure of wood basic density) and near infrared reflectance predicted pulp yield. Univariate and multivariate linear mixed models were fitted within and across sites, and estimates of additive genetic, total genetic, environmental and phenotypic variances and covariances were obtained. All traits studied exhibited significant levels of additive genetic variation. The average estimated within-site narrow-sense heritability was 0.19 ± 0.03 for diameter and 0.29 ± 0.03 for Pilodyn penetration, and the pooled estimate for predicted pulp yield was 0.42 ± 0.14. When they could be tested, dominance and epistatic effects were generally not statistically significant, although broad-sense heritability estimates were slightly higher than narrow-sense heritability estimates. Averaged across trials, positive additive (0.64 ± 0.08), total genetic (0.58 ± 0.04), environmental (0.38 ± 0.03) and phenotypic (0.43 ± 0.02) correlation estimates were consistently obtained between diameter and Pilodyn penetration. This data argues for at least some form of pleiotropic relationship between these two traits and that selection for fast growth will adversely affect wood density in this population. Estimates of the across-site genetic correlations for diameter and Pilodyn penetration were high, indicating that the genotype by environment interaction is low across the range of sites tested. This result supports the use of single aggregated selection criteria for growth and wood density across planting environments in Portugal, as opposed to having to select for performance in different environments.

Appendices

Appendix 1

The wood samples for the estimation and prediction of pulp yield using NIR analysis were from 89 trees selected in different geographical regions in Portugal. These regions represented an ample range of site productivities and environmental conditions for growing E. globulus in the country. The age of the selected trees varied between 3 and 11 years old, with their distribution being generally uniform across the age classes. In addition, for a given age, trees varied in their phenotype for growth rate. For kraft pulp yield determinations, wood chips were produced from 50-cm long logs collected at four different height levels in each tree. The logs were cooked in an alkaline solution to a fixed Kappa index of 16 in a laboratory digester. These assessments provided a range for kraft pulp yield of 45.1% to 57.1% across trees, with an average of 52.2%. For NIR analysis, a portion (corresponding to a sampling level close to breast height) of the wood chips from each tree was ground to pass a 1-mm screen in a Cyclotec Model 1903 abrasion mill (Foss Tecator, Sweden). The wood meal samples were then kept in a controlled environment (i.e. constant temperature of 23° C and relative humidity of 50%) for stabilising their moisture content to approximately 10%. The NIR spectra were recorded on a 5-g sample of the wood meal for each tree, using a FT-NIR Bruker Vector 22/N instrument. The spectra were collected at 2-nm intervals over the wavelength range of 1100–2500 nm, with two spectra being recorded per sample. Fifty scans were accumulated per sample, and the results were averaged to produce one spectrum.

The set of 89 samples was split randomly into two subsets: one made of 65 samples (range from 45.9% to 56.2%) to construct a calibration model relating the kraft pulp yield determinations with the NIR spectral data, and the other made of 24 samples (range from 45.1% to 57.1%) for external validation (i.e. to assess the ability of the developed calibration model for predicting pulp yield in wood samples that are different from those used in the calibration group). The software Unscrambler (CAMO, Norway) was used for data analysis. Prior to modelling, the spectral data were converted to the second-derivative mode using the gap-segment algorithm (gap width of 20 nm) available in the software. Then, a calibration model relating kraft pulp yield with the second-derivative spectral data was constructed by applying partial least squares (PLS) regression, and using the minimum root mean square error of cross validation as a criterion to retain an optimum number of PLS regression factors in the model. The number of PLS factors retained was 6, and in terms of data fitting, the PLS calibration model performed well as indicated by a coefficient of determination of calibration of 0.96 and a standard error of calibration of 0.49%. When applied to the set of 24 independent samples, the PLS calibration model provided a standard error of prediction of 0.96% and led to a correlation between laboratory and NIR-predicted pulp yield of 0.92. These results suggested that NIR analysis could be used as a reasonably accurate predictor of pulp yield in unknown wood samples (such as those that were subsequently collected in the field trials).

Appendix 2

Table 8 Number of parents and clones within full-sib families in E. globulus trials with clonally replicated progeny from controlled crosses

Appendix 3

Table 9 Number of clones in E. globulus trials with unrelated clones