Accurate estimation of log MOE from non-destructive standing tree measurements

A novel non-destructive method has been developed to predict modulus of elasticity (MOE) logs using measurements taken from cores extracted discs. The trees were felled and cut into allow validation our method; however, similar results would be obtained if the standing trees. shows that a single core breast height is sufficient MOE logs, allowing early grading sorting for optimal use processing. Early estimation log allows efficient which can improve financial return reduce wastage wood. This work aims accurately on was predicted ultrasound conducted small segments two different approaches: segment average integral average. Sixty-eight locally F1 F2 hybrid pines (slash pine × Caribbean hybrids, Pinus elliottii var. P. caribaea hondurensis (PEE PCH cross)) validate results. Beam Identification by Non-destructive Grading (BING) used measure reference dynamic (BING-MOE) each log, this compared with estimated MOE. Strong correlations $$(r=0.79 \mathrm\ {to}\ 0.91)$$ between measured obtained. study revealed (1.3 m) tree good prediction Tree height, spacing, diameter had no significant effect prediction. under predicts BING-MOE, whereas provides very little bias in Furthermore, errors regression analysis all greater method. paper presented evaluation capable predicting whole combining data available breast-height approach. BING-MOE more lower other existing tools without any complex equipment, analysis, statistical calibration segregating out individual or stands. potentially species extended boards sawn log.