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Prediction of wood stiffness, strength, and shrinkage in juvenile wood of radiata pine |
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| Authors: | Milo? Ivkovi? Washington J Gapare Aljoy Abarquez Jugo Ilic Michael B Powell Harry X Wu |
| Institution: | 1. CSIRO Plant Industry, P.O. Box E4008, Canberra, ACT, 2604, Australia 2. Forest and Wood Products Australia, P.O. Box 69, World Trade Centre, Melbourne, VIC, 8005, Australia 3. Southern Tree Breeding Association Inc, P.O. Box 1811, Mt. Gambier, SA, 5290, Australia |
| Abstract: | Development of optimal ways to predict juvenile wood stiffness, strength, and stability using wood properties that can be measured with relative ease and low cost is a priority for tree breeding and silviculture. Wood static modulus of elasticity (MOE), modulus of rupture (MOR), radial, tangential, and longitudinal shrinkage (RS, TS, LS), wood density (DEN), sound wave velocity (SWV), spiral grain (SLG), and microfibril angle (MFA) were measured on juvenile wood samples from lower stem sections in two radiata pine test plantations. Variation between inner (rings 1–2 from pith) and outer (rings 3–6 from pith) rings was generally larger than that among trees. MOE and MOR were lower (50%) in inner-rings than in outer-rings. RS and TS were higher (30–50%) for outer-rings than inner-rings, but LS decreased rapidly (>200%) from inner-rings to outer-rings. DEN had a higher correlation with MOR than with MOE, while MFA had a higher correlation with dry wood MOE than with MOR. SLG had higher significant correlation with MOE than with MOR. DEN and MOE had a weak, significant linear relationship with RS and TS, while MOE had a strong negative non-linear relationship with LS. Multiple regressions had a good potential as a method for predicting billet stiffness (R 2 > 0.42), but had only a weak potential to predict wood strength and shrinkage (R 2 < 0.22). For wood stiffness acoustic velocity measurements seemed to be the most practical, and for wood strength and stability acoustic velocity plus core density seemed to be the most practical measurements for predicting lower stem average in young trees. |
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