Breeding for Wood Quality; Acoustic Tools and Technology 2007 AFG & IUFRO SPWG Joint Conference Hobart, Tasmania – April 2007 Peter Carter – Chief Executive, Fibre-gen 1
Contents • Why acoustics? • How acoustics work • Results, tricks and traps • Who’s doing it? • Conclusions 2
Why? Global developments • Resource wood quality is changing, target of value improvement – Global emphasis on structural and appearance qualities – Age of clearfall declining, log quality more variable – Tree breeding has improved volume more than quality • Increased attention to quality standards eg NZ Standard 3622 – Development of ‘verified visual’ grading (sample proof tested) – Price differential in lumber and engineered wood markets – Mills sensitive to stiffness of smaller diameter young wood • New tools – Structural and LVL mills can now measure stiffness Breeding for stiffness will enhance business returns 3
Why? Financial values What is stiffness worth – a couple of examples • Verified visual grading – batch pass/fail – VSG8 lumber premium is NZ$100/m 3 ($450 vs $350) – At 55% conversion, 80% structural, equates to $36/m 3 log – At 600m 3 /ha, 70% sawlog, 27 yrs, 8%, equates to $1,893/ha • MSG lumber – incremental benefit – MGP8 lumber premium is NZ$250/m 3 – 0.1km/sec gives 5% more MGP8, worth $12.50/m 3 – At 600m 3 /ha, 70% sawlog, 27 yrs, 8%, equates to $657/ha Breeding for stiffness will enhance business returns 4
Why? Financial values What is stiffness worth – more examples • Sitka Spruce – United Kingdom – Structural £150, Industrial £100 • Spruce – Sweden – MSR 1,450kr, Visual structural 1,350kr • Douglas fir – Oregon, USA – MSR $350, Visual structural $310 – LVL $350, Ply $230 • Southern Yellow Pine – Arkansas – MSR $195, Visual structural $178 Absolute differences vary with market conditions – premiums remain Breeding for stiffness will enhance business returns 5
Why? Financial values Other values are significant too • Microfibril angle – R 2 in range 0.8 – 0.9 – MFA is key predictor of solid wood stability and fibre stiffness • Pulp & Paper properties – Fibre length and paper strength – Coarseness and sheet quality – Energy consumption and yield • Eucalypt stiffness • Ash group Eucalypt internal collapse Breeding for stiffness will enhance business returns 6
Why? Feasibility Hitman ST300 • New tools are quick, non-destructive, easy and efficient – Less than 1 minute/tree for testing – Wireless, with no cables to tangle or fail – Quick and easy insertion and removal of probes – No cores needed – No significant damage to young trees • Mechanical and software enhancements improve precision • Variability and heritability are high • Breeding program on 10,000ha/annum could deliver >$10m/annum Sonic speed provides an attractive breeding opportunity 7
Why? Feasible and valuable Hitman ST300 • Variability and heritability are high Normal Distribution • Example mean 3.2 km/sec with 14% SD 0.2 12% 10% • Top 10% mean is 3.5 km/sec 8% • Top 2% mean is 3.63km/sec 6% 4% • With heritability of 60%, 2% delivered gain is 0.18 and 0.26 0% 2.6 2.7 2.8 2.9 3 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 respectively Velocity (km/sec) • MSG example values this at $1,180 and $1,700/ha NPV at time of planting 8
HM200, LM600 – how they work Stiffness = density x (velocity) 2 • • Velocity is derived from resonant frequency (2 nd harmonic) and length • Sensor/microphone detects frequency from hammer blow • Green density is relatively constant ≈ 2 stiffness density x velocity length velocity = 2 x length / time 3.3 9
Hitman ST300, PH330 – how they work • ‘Time of flight’ outerwood velocity measure – higher than log measure • Ruggedised, waterproof, wireless, auto-distance, audible and visual output, interface to PDA • Velocity correlates strongly with log velocity at stand level Acoustic speed - standing tree vs log 14000 HM200 on log (Director) (ft/s) 13000 12000 Sitka spruce Juvenile Wood Juvenile Wood 11000 Western hemlock 10000 Jack pine White birch 9000 Ponderosa pine 8000 R 2 = 0.925 7000 6000 6000 8000 10000 12000 14000 16000 15 yrs 15 yrs 25 yrs 25 yrs 35 yrs 35 yrs ST300 prototype on tree (ft/s) Source: X Wang et al, University of Minnesota 10
Improved Precision Hitman ST300 • Mechanical and software enhancements improve precision – Calibration against absolute standard – Filters enhance precision TOF vs Distance (Brass Bar) Recorded Time of Flight Variation (SD 3.5 vs 7.5) 500 500 450 480 400 Time of Flight (micro-sec) 460 350 TOF (us) 440 300 420 250 400 200 380 150 360 100 340 50 320 0 300 0 500 1000 1500 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 y = 0.2941x + 0.2476 Distance (mm) Sample number R 2 = 0.9997 11
Standing tree sampling – single trees • Measure is a single sample of outerwood velocity • Sampling procedure and intensity must match need • Single tree - intensive sampling – Variation around stem – Knot location – Transverse – Compression wood – Hit variability • 1-3 sets of 10 hits, in each of 2-4 locations around stem • High productivity (>60 sample sets/hour) – faster than density coring 12
Standing tree sampling – single trees • Eyrewell study – radiata pine, age 28 • Correlation between standing tree and log velocity improves as sample intensity increases R 2 Location/s on tree taps Upper side 3 0.44 Upper side 3 0.48 Upper side 3 0.43 Upper side (A) 9 0.50 Lower side (B) 9 0.45 Random side (D) 9 0.60 Mean A+B 18 0.61 Mean A+D 18 0.62 Mean A+B+D 27 0.67 13
Standing tree sampling – single trees • Sawlog study – radiata pine Correlation vs number of samples • Correlation 1.00 between standing 0.80 2 ) Correlation (R tree and log 0.60 Rx 0031 velocity improves Rx 0035 0.40 as sample 0.20 intensity increases 0.00 0 10 20 30 40 50 Number of samples Standing Harvesting Stem Log Log Deck Lumber or >>>>>>> >>>>>>> >>>>>>> >>>>>>> >>>>>>> Tree Processor to Mill Veneer 14 ST300 PH330 HM200 HM200 LM600 Grader
Standing tree sampling – single trees • Sawlog studies – radiata pine McVicars Validation HM vs ST • ST vs HM 5.0 ST velocity (km/sec) 4.8 relationship is 4.6 4.4 4.2 stable, new vs old 4.0 3.8 • ST velocity is 3.6 3.4 higher than 3.2 3.0 ‘generic’ field 2 2.5 3 3.5 4 y = 1.4316x - 0.2893 HM velocity (km/sec) R 2 = 0.5121 oscilloscope Rx0031 Rx0035 Generic relationship based dataset Version 1 ST300 (cap) Linear (Rx0035) Linear (Rx0031) Linear (Generic relationship) Linear (Version 1 ST300 (cap)) 15
Standing tree sampling - stands • More extensive sampling – large block genetic gain trials • Stand average measure – Cover the stand – plots of 5+ trees – Cover diameter range – Variability between trees > within – Sample as many trees as possible in least time • 1 set of 10 hits/tree on 50+ trees/stand • Productivity dependent upon terrain and vegetation 16
Target Velocities – NZ example • Dynamic MOE of 8GPa is indicative of VSG8 production and would require – Average log velocity 2.8km/sec (allowing 0.1km/sec for SE of mean) – Green density 1000kg/m 3 • 8GPa target velocity could vary 2.70 - 3.00 km/sec average • Equivalent standing tree velocities 3.6 - 4.0 km/sec average at harvest • Towards end of juvenile wood formation, target 2.8 km/sec although 2.6 may be adequate for structural minimum (5.6 GPa) 17
Results – effect of temperature on velocity In general • Acoustic velocity is higher at lower temperatures But • Rate of change is most significant around freezing • Moisture content changes may compensate on logs, but not in trees Temperature Effect on Acoustic Velocity of Green Board Density (MC ) adjusted acoustic speed 4000 5 3800 Stack 6 (50 boards) 3600 Stack 2 (50 boards) 3400 V = 2365 - 41.42T (T ? 0 °C) 4.5 3200 Acoustic Wave Velocity (m/s) 3000 Series1 2800 Series2 2600 4 Series3 V = 2365 - 17.69T (T ? 0 °C) 2400 Series4 2200 Series5 2000 Series6 3.5 Series7 1800 Series8 1600 Series9 1400 3 Series1 0 1200 Series1 1 1000 Series1 2 800 600 2.5 400 200 0 2 -20 -15 -10 -5 0 5 10 15 20 -25 -20 -15 -1 0 -5 0 5 1 0 1 5 20 25 Board Temperature (C) Source: X Wang, University of Minnesota Source: P Harris, IRL Source: L Bjorklund, VMR, SDC 18
Results –velocity within stem – butt to top • Acoustic velocity varies from butt to top although greatest variation is between stems • Highest velocity logs are in mid section of stem • Variation follows pattern of microfibril angle R adiata Pine - Log velocity within stem 4.00 Velocity (km/ sec) Average 3.2 km/ sec 3.50 Average + 2 x SD Average - 2 x SD 3.00 Stand Mean 3.2 2.50 0 5 1 0 1 5 20 25 30 Distance up stem (m) Source: X Wang et al, University of Minnesota 19
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