Acacia plants are globally important resources in the wood industry, but particularly in Southeast Asian countries. In the present study, we compared the physical and mechanical properties of polyploid Acacia (3x and 4x) clones with those of diploid (2x) clones grown in Vietnam. We randomly selected 29 trees aged 3.8 years from different taxa for investigation. BV10 and BV16 clones represented the diploid controls; X101 and X102 were the triploid clones; and AA-4x, AM-4x, and AH-4x represented neo-tetraploid families of Acacia auriculiformis, Acacia mangium, and their hybrid clones. The following metrics were measured in each plant: stem height levels, basic density, air-dry equilibrium moisture content, modulus of rupture (MOR), modulus of elasticity (MOE), compression strength, and Young’s modulus. We found that the equilibrium moisture content significantly differed among clones, and basic density varied from pith-to-bark and in an axial direction. In addition, the basic density of AA-4x was significantly higher than that of the control clones. Furthermore, the MOR of AM-4x was considerably lower than the control clones, whereas the MOE of X101 was significantly higher than the control values. The compression strength of AM-4x was significantly lower than that of the control clones, but AH-4x had a significantly higher Young’s modulus. Our results suggest that polyploid Acacia hybrids have the potential to be alternative species for providing wood with improved properties to the forestry sector of Vietnam. Furthermore, the significant differences among the clones indicate that opportunities exist for selection and the improvement of wood quality via selective breeding for specific properties.

Acacia, including Acacia hybrids, are some of the most important species grown as part of the Vietnamese wood industry. Rapid methods to identify the variations in the wood properties of Acacia hybrids however, are a currently lacking and creating limits for their breeding programs. In this study, nine Acacia hybrid clones, including those that were diploid, triploid, and tetraploid were evaluated using near-infrared spectroscopy (NIR) and hyperspectral imaging (HSI). The standard normal variate (SNV) and second derivative (SP2D) were applied to compare the performances of NIR and HSI using partial least square regression. The HSI images were acquired at wavelengths from 1033 to 2230 nm and the SNV and SP2D described the variations in the wood properties. The NIR predicted the wood physical properties better than HSI, while they provided similar predictions for the mechanical properties. The mapping results showed low densities around the pith area and high densities near the bark. They also revealed that the air-dry moisture content changed at different positions within a disk and was dependent on its position within the tree. Overall, NIR and HSI were found to be potential wood property prediction tools, suitable for use in tree improvement programs.

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