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1
Breeding for Wood Quality;
Acoustic Tools and
Technology
2007 AFG & IUFRO SPWG Joint Conference
Hobart, Tasmania – April...
2
Contents
• Why acoustics?
• How acoustics work
• Results, tricks and traps
• Who’s doing it?
• Conclusions
3
Why? Global developments
• Resource wood quality is changing, target of value improvement
– Global emphasis on structura...
4
Why? Financial values
What is stiffness worth – a couple of examples
• Verified visual grading – batch pass/fail
– VSG8 ...
5
Why? Financial values
What is stiffness worth – more examples
• Sitka Spruce – United Kingdom
– Structural £150, Industr...
6
Why? Financial values
Other values are significant too
• Microfibril angle
– R2 in range 0.8 – 0.9
– MFA is key predicto...
7
Why? Feasibility
Hitman ST300
• New tools are quick, non-destructive, easy and efficient
– Less than 1 minute/tree for t...
8
Why? Feasible and valuable
Hitman ST300
• Variability and heritability are
high
• Example mean 3.2 km/sec with
SD 0.2
• ...
9
HM200, LM600 – how they work
• Stiffness = density x (velocity)2
• Velocity is derived from resonant
frequency (2nd harm...
10
Hitman ST300, PH330 – how they work
• ‘Time of flight’ outerwood velocity measure – higher than
log measure
• Ruggedise...
11
Improved Precision
Hitman ST300
• Mechanical and software enhancements improve
precision
– Calibration against absolute...
12
Standing tree sampling – single trees
• Measure is a single sample of outerwood velocity
• Sampling procedure and inten...
13
Standing tree sampling – single trees
• Eyrewell study – radiata pine, age 28
• Correlation between standing tree and l...
14
Standing tree sampling – single trees
• Sawlog study –
radiata pine
• Correlation
between standing
tree and log
velocit...
15
Standing tree sampling – single trees
• Sawlog studies –
radiata pine
• ST vs HM
relationship is
stable, new vs old
• S...
16
Standing tree sampling - stands
• More extensive sampling – large block genetic gain
trials
• Stand average measure
– C...
17
Target Velocities – NZ example
• Dynamic MOE of 8GPa is indicative of VSG8 production and
would require
– Average log v...
18
Results – effect of temperature on velocity
In general
• Acoustic velocity is higher at lower temperatures
But
• Rate o...
19
Results –velocity within stem – butt to top
• Acoustic velocity varies from butt to top although
greatest variation is ...
20
Location of boards in the log
Average
stiffness of
wood in
boards up
the stems
Average stiffness of lumber cut from
som...
21
Results – velocity and MoE correlate with age
In general
• Acoustic velocity increases with increasing age
But
• Other ...
22
Conclusions
• Highly significant values are at stake
• Variation and heritability are high
• New tools are available th...
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Breeding for wood quality april 2007

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Breeding for Wood Quality;
Acoustic Tools and Technology
2007 AFG & IUFRO SPWG Joint Conference
Hobart, Tasmania – April 2007
Peter Carter – Chief Executive, Fibre-gen

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Breeding for wood quality april 2007

  1. 1. 1 Breeding for Wood Quality; Acoustic Tools and Technology 2007 AFG & IUFRO SPWG Joint Conference Hobart, Tasmania – April 2007 Peter Carter – Chief Executive, Fibre-gen
  2. 2. 2 Contents • Why acoustics? • How acoustics work • Results, tricks and traps • Who’s doing it? • Conclusions
  3. 3. 3 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
  4. 4. 4 Why? Financial values What is stiffness worth – a couple of examples • Verified visual grading – batch pass/fail – VSG8 lumber premium is NZ$100/m3 ($450 vs $350) – At 55% conversion, 80% structural, equates to $36/m3 log – At 600m3/ha, 70% sawlog, 27 yrs, 8%, equates to $1,893/ha • MSG lumber – incremental benefit – MGP8 lumber premium is NZ$250/m3 – 0.1km/sec gives 5% more MGP8, worth $12.50/m3 – At 600m3/ha, 70% sawlog, 27 yrs, 8%, equates to $657/ha Breeding for stiffness will enhance business returns
  5. 5. 5 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
  6. 6. 6 Why? Financial values Other values are significant too • Microfibril angle – R2 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
  7. 7. 7 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
  8. 8. 8 Why? Feasible and valuable Hitman ST300 • Variability and heritability are high • Example mean 3.2 km/sec with SD 0.2 • Top 10% mean is 3.5 km/sec • Top 2% mean is 3.63km/sec • With heritability of 60%, delivered gain is 0.18 and 0.26 respectively • MSG example values this at $1,180 and $1,700/ha NPV at time of planting Normal Distribution 0% 2% 4% 6% 8% 10% 12% 14% 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 Velocity (km/sec)
  9. 9. 9 HM200, LM600 – how they work • Stiffness = density x (velocity)2 • Velocity is derived from resonant frequency (2nd harmonic) and length • Sensor/microphone detects frequency from hammer blow • Green density is relatively constant 3.3 length velocity = 2 x length / time stiffness densityx velocity≈ 2
  10. 10. 10 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 6000 7000 8000 9000 10000 11000 12000 13000 14000 6000 8000 10000 12000 14000 16000 ST300 prototype on tree (ft/s) HM200onlog(Director)(ft/s) Sitka spruce Western hemlock Jack pine White birch Ponderosa pine R2 = 0.925 Source: X Wang et al, University of Minnesota Juvenile Wood 15 yrs 25 yrs 35 yrs Juvenile Wood 15 yrs 25 yrs 35 yrs
  11. 11. 11 Improved Precision Hitman ST300 • Mechanical and software enhancements improve precision – Calibration against absolute standard – Filters enhance precision TOF vs Distance (Brass Bar) y = 0.2941x + 0.2476 R2 = 0.9997 0 50 100 150 200 250 300 350 400 450 500 0 500 1000 1500 Distance (mm) TOF(us) Recorded Time of Flight Variation (SD 3.5 vs 7.5) 300 320 340 360 380 400 420 440 460 480 500 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Sample number TimeofFlight(micro-sec)
  12. 12. 12 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
  13. 13. 13 Standing tree sampling – single trees • Eyrewell study – radiata pine, age 28 • Correlation between standing tree and log velocity improves as sample intensity increases Location/s on tree taps R 2 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
  14. 14. 14 Standing tree sampling – single trees • Sawlog study – radiata pine • Correlation between standing tree and log velocity improves as sample intensity increases Correlation vs number of samples 0.00 0.20 0.40 0.60 0.80 1.00 0 10 20 30 40 50 Number of samples Correlation(R 2 ) Rx 0031 Rx 0035
  15. 15. 15 Standing tree sampling – single trees • Sawlog studies – radiata pine • ST vs HM relationship is stable, new vs old • ST velocity is higher than ‘generic’ field oscilloscope based dataset McVicars Validation HM vs ST y = 1.4316x - 0.2893 R 2 = 0.5121 3.0 3.2 3.4 3.6 3.8 4.0 4.2 4.4 4.6 4.8 5.0 2 2.5 3 3.5 4 HM velocity (km/sec) STvelocity(km/sec) Rx0031 Rx0035 Generic relationship Version 1 ST300 (cap) Linear (Rx0035) Linear (Rx0031) Linear (Generic relationship) Linear (Version 1 ST300 (cap))
  16. 16. 16 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
  17. 17. 17 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/m3 • 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)
  18. 18. 18 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 0 200 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 2600 2800 3000 3200 3400 3600 3800 4000 -20 -15 -10 -5 0 5 10 15 20 Board Temperature (C) AcousticWaveVelocity(m/s) Stack 6 (50 boards) Stack 2 (50 boards) V = 2365 - 17.69T (T ? 0 °C) V = 2365 - 41.42T (T ? 0 °C) Density(MC) adjustedacousticspeed 2 2.5 3 3.5 4 4.5 5 -25 -20 -15 -10 -5 0 5 10 15 20 25 Series1 Series2 Series3 Series4 Series5 Series6 Series7 Series8 Series9 Series10 Series11 Series12 Source: L Bjorklund, VMR, SDCSource: P Harris, IRLSource: X Wang, University of Minnesota
  19. 19. 19 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 Source: X Wang et al, University of Minnesota Radiata Pine - Log velocity within stem 2.50 3.00 3.50 4.00 0 5 10 15 20 25 30 Distance upstem(m) Velocity(km/sec) Average 3.2 km/ sec Average + 2 x SD Average -2 x SD Stand Mean 3.2
  20. 20. 20 Location of boards in the log Average stiffness of wood in boards up the stems Average stiffness of lumber cut from some 60 trees. Note the low stiffness at the base of the tree, in the butt logs. Why not cut a short, 2.5 m butt log? 1st log 2nd log 3rd log Ping Xu, 2002 Results – log velocity within stem – pith to bark Source: J Walker, University of Canterbury
  21. 21. 21 Results – velocity and MoE correlate with age In general • Acoustic velocity increases with increasing age But • Other factors affect velocity and MoE • Wide range of velocities within stands • Strategy – set appropriate breeding targets for different ages Log age vs. average acoustic velocity R 2 = 0.66 2.50 2.60 2.70 2.80 2.90 3.00 3.10 3.20 3.30 3.40 3.50 18 20 22 24 26 28 30 32 34 Log age (years) Stand Linear (Stand) VelocityvsStand Age 2.80 2.90 3.00 3.10 3.20 3.30 3.40 3.50 3.60 3.70 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 Age (years) Velocity(km/sec) Mean Velocity (50% oldest age) = 3.43 Mean Velocity (50% highest V) = 3.37 Benefit = 0.06km/sec
  22. 22. 22 Conclusions • Highly significant values are at stake • Variation and heritability are high • New tools are available that are easy to use, efficient, and precise • Breeding applications include clonal ranking, progeny trials, and genetic gain studies • For supporting information peter.carter@fibre-gen.com www.fibre-gen.com

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