Forest & Wood Products Australia (FWPA) has published new research to improve the accessibility and accuracy of wood quality information for Australia’s softwood growers and processors. The research uses Resi technology, a new type of technology that provides precise predictions of wood properties and yields for the early selection of harvest-age density and modulus of elasticity (MoE).
Resi technology refers to a resistance drilling method used to assess wood properties, particularly in softwood plantations. It rapidly measures the resistance encountered when a drill bit penetrates the wood, correlating with the density and stiffness of trees, logs and forest plots. The Resi tool is noted for its efficiency, being three times faster than other methods like the ST300 acoustic velocity measures, and has been standardised for operational use to improve the accuracy and reliability of wood quality assessments.
The project has underpinned a transformation in the easy access to information about wood quality for softwood growers and processors. Resi data from pre-harvest assessments can accurately predict mill site-mean board stiffness in sawing studies across multiple sites in Australia. It’s now a routine tool for many companies. The project is strongly aligned with the FWPA Strategic Plan and the focus on improving the resource base and increasing productivity and utilisation along the value chain.
“I’m proud to have led a project that directly connects field-based log quality with the experiences of processors, delivering tangible benefits to the forest industry,” according to Associate Professor David Lee from the University of Sunshine Coast – the lead author of the research.
The research showed that simulated mid-rotation Resi measurements can reliably estimate harvest age quality, aiding in informed decisions regarding rotation lengths. The study also addressed various sources of error between Resi instruments and techniques, establishing that these variances are negligible at a commercial scale, thereby fostering confidence in the consistency of Resi measurements.
“This research can help us enhance our operations and planning. With improved predictive modelling, we can make informed decisions about longer term resource planning and better understand timber production outputs.”
Rebecca Cherry, Wood Quality Engineer at Hyne Timber.
Wood Central understands that key benefits for the industry include:
- Successful predictions of mill site-mean board stiffness across multiple locations have improved wood flow between growers and processors and have the potential to inform favourable log pricing structures.
- Enhanced decision-making capabilities regarding rotation lengths, stocking, breeding objectives, and overall wood quality through predictive modelling.
- Over thirty Resi instruments were adopted by growers and processors for routine inventory and log supply management.
- Integration of wood quality predictions with yield estimates in YTGen software and enhancements to the Resi Processor software for better prediction of stiffness and density.
Key findings from the project include:
- A confirmed relationship between pre-harvest measurements and mill production quality, demonstrating that Resi data can predict mill output at a compartment level.
- Enhanced understanding of radial and longitudinal wood quality variation allows for tailored silvicultural practices.
- Improved algorithms were developed and incorporated into the new version of the Resi web trace processor, ensuring ongoing access to cutting-edge predictive models.
Looking ahead, the project recommends that Resi technology be further used to strengthen grower-processor communication, optimise wood flow, and enhance the value of plantations. Extensive, estate-wide datasets will be used to pursue a deeper understanding of how site, climate, management, and genetics affect MoE and structural grade percentages.
- For more information and to download the project report, please click here.
