Increment cores can provide improved predictive capabilities of the modulus of elasticity (MOE) of sawn boards. Multiple increment cores collected at different heights in a tree provide marginally increased accuracy over a single breast-height core, with higher labour costs. Approximately 50% of the variability of the static bending MOE of individual boards is explained by the predicted MOE obtained from a single increment core taken at breast height.
Context Prediction of individual board MOE can lead to accurate optimisation of the value extracted from forest resources, and enhanced decision-making on the management and allocation of the resource to different processors, and improve the processors ability to optimise grade allocation.
Aims The objective of this study is to predict the MOE of individual sawn boards from the MOE measured from cores collected from standing trees.
Methods A five-parameter logistic (5PL) function and radial basis function interpolants are used to obtain a continuous distribution of MOE throughout a log. By developing a “virtual sawing” methodology, we predict the individual board MOE for sixty-eight trees consisting of locally developed F1 and F2 hybrid pines (Pinus caribaea var. hondurensis × Pinus elliottii var. elliottii).
Results Moderate correlations for individual board predictions are observed, with R2 values ranging from 0.47 to 0.53. Good correlations between average predicted board MOE and average measured MOE are also observed, with R2 ≈ 0.83. A pseudo-three-dimensional approach, accounting for variation in height in the tree, affords marginally greater accuracy and predictive capability at the cost of increased data collection and processing. By using a single breast-height core, we can obtain a similar level of prediction of individual board MOE.
Conclusion We have presented a novel non-destructive evaluation approach to predict the MOE of individual boards sawn from trees. This approach can be adapted to other wood properties, and other wood products obtained from trees.
Non-destructive evaluation (NDE); Wood quality; Modulus of elasticity; Queensland southern pines; Sawn boards
Psaltis, S., Kumar, C., Turner, I. et al. A new approach for predicting board MOE from increment cores. Annals of Forest Science 78, 78 (2021). https://doi.org/10.1007/s13595-021-01093-w
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The datasets generated during and/or analysed during the current study are available from the University of the Sunshine Coast Research Bank, https://doi.org/10.25907/00007
The custom code and/or software application generated during and/or analysed during the current study are available from the corresponding author on reasonable request.