Variability and Genetic Parameter Analysis in Eucalyptus grandis Population for Growth and Wood Properties at North Sumatera

Abstract

Indonesia is the 9th largest pulp producer in the world and is able to supply the world's pulp needs of 3 percent of the world's total capacity. The wood of Eucalyptus grandis used as a raw material for charcoal, firewood, pulp products from wood fiber and wood-working. The increment of wood supply is determinant as guarantee this pulp production and it’s supported by the improvement of genetic materials. In tree improvement activities, estimation of genetic parameters for several traits needs to be carried out before selection activities due the phenotype of a plant is determined by genetic and environmental factors. Plant growth and productivity, wood basic density and pulp yield are important traits to know in order to determine the efficiency of using raw materials in producing pulp. For estimating the wood properties, it requires nondestructive testing to keep the plant growing like its original population. Pulp yield character can be estimated by using an NIR (Near Infrared), while the wood basic density traits can be estimated using a resistograph which calculates the amount of resistance when drilling wood from the bark to the bark of the wood. For wood properties evaluation, preciously modelling is necessary. A population of E. grandis at North Sumatera, Indonesia at 1800 m altitude was analysed for growth and wood properties in this work. Pulp yield (PY) traits were assessed using microNIR and wood basic density (BD) traits using resistoraph. Wood basic density modelling using resistograph was carried out with 315 trees consisting of 158, 139, and 18 trees of Eucalyptus grandis, E. urophylla, and eucalyptus hybrid urograndis. Pulp yield prediction data were analysed with the model developed by PT. Riau Andalan Pulp and Paper Wood Technology Department using microNIR. Wood basic density modelling was analysed with linear regression analysis. Variability and genetic parameter analysis for E. grandis population were carried out with restricted maximum likelihood (REML) and the retraction of genotypes was used best linear unbiased prediction (BLUP) analysis with different selection simulations. The result from wood basic density modelling showed that basic density traits had a variability inside the tree, intra-, and interspecific species. There were found the whole tree’s basic wood density of 379.9 kg/m3 , 400.5 kg/m3 , and 440.6 kg/m3 at 44 months old for E. grandis, hybrid urograndis, and E. urophylla, respectively. The model developed had a good correlation for predicting wood basic density at 1.3 m and whole tree basic density with the coefficient of determination (R2 ) were in a range of 0.56 to 0.74 for 1.3 m wood basic density prediction, 0.66 to 0.79 to predict whole tree wood basic density and 0.65 to 0.76 to predict average wood basic density. Combined data from all species shows the best model with R2 0.74 to 0.79. After modelling the assessment for wood basic density using resistograph and pulp yield using the microNIR was carried out. The variability analysis for growth character showed individual heritability for growth character with Height (HT) and diameter breast height (DBH) traits was 043 and 0.36, for wood properties character (BD and PY) were 0.41 and 0.39. The family level of heritability for growth character (HT and DBH) were 0.86 and 0.87, and for wood properties character (BD and PY) were 0.87 and 0.77. There were found positive and negative significant genetic and phenotypic correlations between traits. Individual selection shows a slight variation using different selection methods between mass, best linear unbiased prediction (BLUP), and block selection. BLUP selection gives the middle gain and the lowest number of effectiveness (Ne). The family selection gives the lowest gain and the lowest Ne. The selection based on individual performance as BLUP, mass, and block selection showed better results in genetic gain and number of effective size (Ne) compared to family level selection.