Content uploaded by Dean Satchell
Author content
All content in this area was uploaded by Dean Satchell on Oct 05, 2015
Content may be subject to copyright.
Evaluating profitability of
solid timber production from
15 year old pruned and thinned
Eucalyptus nitens (Deane & Maiden)
in Canterbury
A thesis submitted in fulfilment of the requirements for the
Degree of Master of Forestry Science
at the School of Forestry, University of Canterbury
By Stuart Dean Satchell
May 2015
ii
iii
Abstract
This case study investigated profitability of a small stand of fast-grown
Eucalyptus nitens in Canterbury for sawn timber production. This stand was pruned
and thinned and then harvested at 15 years old. An estimate of per-hectare log yields
and diameters was made from the stand. Sample logs were sawn, dried and profiled,
then products quantified. Log prices were estimated using the residual value method.
Prices were summed for sawn products from each log, from which processing
expenses and sawmill profit were deducted for an estimate of log value. In the
absence of market prices for sawn E. nitens products empirical estimates of price
were derived from market survey data. Predictive models were produced from
estimated stand log yields along with predicted product revenues and processing costs
from sample logs. These were used for estimating per-hectare log residual values
from the case study stand trees. Financial returns to the grower were then calculated
as discounted cash flows from the estimated log residual values per hectare, taking
into account grower costs along with harvesting and transport costs. Best-practice
processing methods were identified from the literature and applied as a productivity
benchmark. Methods were developed with the view to standardising data across
research efforts that seek to improve grade recoveries for E. nitens. A range of factors
were investigated that potentially influenced E. nitens log residual value in this case
study, including log diameter and log position. Outcomes included a reasonably
favourable return on investment for the grower. However, this depended on a number
of factors such as land price, distance from processor, product prices, grading
methods, drying methods and level of sawmill profit. The application of
contemporary best practice small-scale processing methods indicates that E. nitens
has potential as a profitable plantation species for solid timber production.
iv
Acknowledgements
Firstly I would like to sincerely thank John Fairweather for his faith in me to
be able to complete this project. John provided the initial encouragement to embark
on this project, he supported me all the way through with his time, his advice, his
feedback, his friendship, his logs, his equipment and anything else I required. This
project would not have happened without him and his wonderful wife Robyn.
Many thanks to the staff at the School of Forestry at Canterbury University
and my supervisors David Evison and Euan Mason.
A special thanks to SCFNZ Ltd for their generous scholarship that allowed me
to undertake this study full time.
I would like to acknowledge and thank those who provided me support and
advice, including John Moore, Mark Bloomberg, James Turner, Bruce Manley, Doug
Gaunt, Heidi Dungey, Trevor Innes and Robin Curtis.
Lastly I would like to give special thanks to my partner Ruth who has been
supportive and forgiving and held my family together while I completed this thesis.
v
Table of Contents
Table of Figures ............................................................................................... xi!
List of Tables ................................................................................................. xii!
Chapter 1!Introduction ................................................................................. 1!
1.1!Introduction ........................................................................................... 1!
1.2!Background ........................................................................................... 1!
1.3!Research Problem and Objectives ........................................................ 3!
1.3.1!Research questions ......................................................................... 4!
1.4!Conclusions ........................................................................................... 4!
Chapter 2!Literature Review: Estimating the profitability of growing E.
nitens........................ ...................................................................................................... 5!
2.1!Introduction ........................................................................................... 5!
2.1.1!Studies of E. nitens residual value ................................................. 7!
2.2!Sawmill Productivity and Profitability ............................................... 11!
2.3!Log Quality ......................................................................................... 13!
2.4!Silviculture and Log Value ................................................................. 14!
2.5!Log Position and Log Value ............................................................... 16!
2.6!Sawmilling Systems and Factors Influencing Value Recovery .......... 16!
2.6.1!Traditional processing of ash eucalypt ........................................ 17!
2.6.2!Improvements to traditional processing methods ........................ 18!
2.6.3!Contemporary sawmill technologies ............................................ 19!
2.7!Factors influencing grade recoveries and sawmill efficiency ............. 21!
2.7.1!Sawing pattern ............................................................................. 21!
2.7.2!Growth stresses ............................................................................ 25!
2.7.3!Log end splitting and log length .................................................. 28!
2.7.4!Knot defect ................................................................................... 29!
2.7.5!Summary and proposed methods ................................................. 30!
2.8!Drying Degrade and Log Value .......................................................... 31!
2.8.1!Drivers of checking degrade ........................................................ 32!
2.8.2!Log position and checking ........................................................... 34!
vi
2.8.3!Steam reconditioning and checking ............................................. 35!
2.8.4!Collapse degrade and steam reconditioning ................................ 36!
2.8.5!Summary and approach to drying ................................................ 37!
2.9!Air Drying of E. nitens ........................................................................ 38!
2.10!Price of sawn timber and residual value ............................................. 40!
2.10.1!Pricing E. nitens sawn timber products ........................................ 41!
2.10.2!Market recognition ....................................................................... 42!
2.10.3!Product substitution and price ...................................................... 42!
2.10.4!Product differentiation ................................................................. 43!
2.10.5!Species comparisons .................................................................... 43!
2.10.6!Product profiles ............................................................................ 45!
2.10.7!Residual value approach for pricing products ............................. 47!
2.11!Conclusions ......................................................................................... 48!
Chapter 3!Methods ..................................................................................... 51!
3.1!Introduction ......................................................................................... 51!
3.2!Case Study Trees ................................................................................. 52!
3.2.1!Inventory and plots ...................................................................... 52!
3.2.2!Case study logs ............................................................................ 53!
3.2.3!Volumes and weights ................................................................... 54!
3.3!Sawmilling .......................................................................................... 54!
3.4!Timber Drying .................................................................................... 57!
3.5!Timber Processing .............................................................................. 58!
3.6!Grading Procedure and Data Inventory .............................................. 59!
3.7!Grading ............................................................................................... 60!
3.7.1!Grading assumptions .................................................................... 61!
3.7.2!Grading flooring product to Australian standards ....................... 62!
3.7.3!Grading flooring product to Farm Forestry Timbers standards ... 63!
3.7.4!Grading of 50 mm and 75 mm nominal width boards ................. 65!
3.7.5!Grade interpretations and modifications ...................................... 65!
3.7.6!Defect groups ............................................................................... 66!
3.7.7!Collapse ........................................................................................ 67!
3.7.8!Checks .......................................................................................... 68!
3.7.9!Grading to reflect no collapse ...................................................... 69!
3.8!Methods for Assessing Production Costs ........................................... 69!
vii
3.8.1!Harvesting costs ........................................................................... 70!
3.8.2!Labour .......................................................................................... 70!
3.8.3!Sawmill costs ............................................................................... 70!
3.8.4!Sawmill asset costs ...................................................................... 70!
3.8.5!Sawmill operating costs ............................................................... 71!
3.8.6!Timber drying costs ..................................................................... 72!
3.8.7!Timber processing costs ............................................................... 74!
3.8.8!Steam reconditioning scenario ..................................................... 75!
3.8.9!Marketing, management and overhead cost ................................. 75!
3.9!Drying Experiment .............................................................................. 75!
3.9.1!Board prices used for drying experiment ..................................... 76!
3.9.2!Statistical analysis ........................................................................ 76!
3.10!Revenues ............................................................................................. 77!
3.10.1!Sawn timber revenues .................................................................. 77!
3.10.2!Product residual values - laminated panels .................................. 77!
3.10.3!Sample log sawn timber revenue ................................................. 79!
3.10.4!Secondary product revenues ........................................................ 79!
3.11!Predicting Plot Log Costs and Revenues ............................................ 79!
3.12!Cash Flows .......................................................................................... 80!
3.12.1!Grower revenues .......................................................................... 80!
3.12.2!Growing and harvesting costs ...................................................... 80!
3.13!E. nitens physical properties ............................................................... 81!
3.13.1!Dry board and log density assessment ......................................... 81!
3.13.2!E. nitens sample physical properties ............................................ 81!
3.14!Scope and Limitations of the Study .................................................... 83!
3.14.1!The case study stand .................................................................... 83!
3.14.2!Secondary products ...................................................................... 84!
3.14.3!Pulpwood vs. firewood ................................................................ 85!
3.14.4!Processing .................................................................................... 85!
3.14.5!Harvesting, loading and logging .................................................. 86!
3.14.6!Products ........................................................................................ 87!
3.14.7!Product pricing ............................................................................. 88!
3.14.8!Laminated panels ......................................................................... 88!
3.14.9!Grades and grading ...................................................................... 89!
3.14.10!Degrade .................................................................................... 89!
viii
3.14.11!Definition of checking degrade ................................................ 89!
3.14.12!Grading to ignore collapse ....................................................... 90!
3.14.13!Wood physical properties ........................................................ 90!
3.15!Conclusions ......................................................................................... 90!
Chapter 4!Results ........................................................................................ 92!
4.1!Case Study Stand Inventory ................................................................ 93!
4.1.1!Plot log volumes .......................................................................... 94!
4.2!Production Results .............................................................................. 96!
4.2.1!Sample log volumes and weights ................................................. 96!
4.2.2!Product quantities from sawlogs .................................................. 96!
4.2.3!Sawmill efficiency ....................................................................... 96!
4.2.4!Sawn product quantities ............................................................... 98!
4.2.5!Processing costs ........................................................................... 99!
4.2.6!Production volume ..................................................................... 100!
4.2.7!Defect in sawn boards ................................................................ 100!
4.2.8!Grade recoveries ........................................................................ 101!
4.3!Drying Experiment ............................................................................ 102!
4.4!Price Estimates for Board Profiles .................................................... 104!
4.4.1!Price estimates for laminated panel feedstock ........................... 106!
4.5!Log Pricing Models and Residual Values ......................................... 106!
4.5.1!Sawn timber revenues ................................................................ 106!
4.5.2!Marketing, management and processing overheads .................. 109!
4.5.3!Processing costs ......................................................................... 109!
4.5.4!Total processing costs ................................................................ 111!
4.5.5!Residual values .......................................................................... 112!
4.5.6!Discounted cash flows ............................................................... 113!
4.5.7!Net present value ........................................................................ 115!
4.6!Sensitivity Analysis .......................................................................... 115!
4.6.1!Land price .................................................................................. 115!
4.6.2!Pulpwood price .......................................................................... 116!
4.6.3!Logging and transport ................................................................ 117!
4.6.4!Sawn timber value ...................................................................... 118!
4.6.5!Drying degrade ........................................................................... 119!
4.6.6!Sawmill Overheads .................................................................... 120!
ix
4.7!Log Position as a Driver for Log Residual Value ............................. 120!
4.7.1!Density and hardness ................................................................. 121!
4.7.2!Movement in service .................................................................. 123!
4.7.3!Defect and drying degrade ......................................................... 124!
Chapter 5!Discussion and Conclusions ................................................... 128!
5.1!Introduction ....................................................................................... 128!
5.2!Core Results ...................................................................................... 128!
5.2.1!Sawn timber recoveries and values ............................................ 128!
5.2.2!Drivers of profitability ............................................................... 129!
5.2.3!Comparison with Previous Studies ............................................ 132!
5.3!Study Design Issues .......................................................................... 134!
5.3.1!Improvements to case study methods ........................................ 134!
5.3.2!Towards a standardised methodology ........................................ 135!
5.3.3!Sawn timber physical properties ................................................ 135!
5.4!Factors influencing grade recoveries from logs ................................ 136!
5.4.1!Sawmill efficiency ..................................................................... 136!
5.4.2!Log Position ............................................................................... 138!
5.4.3!Log diameter .............................................................................. 140!
5.4.4!Half-log deflection ..................................................................... 141!
5.4.5!Crook .......................................................................................... 142!
5.4.6!End splits .................................................................................... 142!
5.4.7!Box ............................................................................................. 143!
5.4.8!Drying Degrade .......................................................................... 144!
5.5!Product Selection and Pricing ........................................................... 145!
5.5.1!Grading methods and end uses .................................................. 145!
5.5.2!Product selection ........................................................................ 146!
5.6!Products and Market Value ............................................................... 146!
5.6.1!Flooring product pricing ............................................................ 146!
5.6.2!Panel product pricing ................................................................. 150!
5.6.3!Slab firewood ............................................................................. 150!
5.7!Processing and Scale Efficiency ....................................................... 151!
5.8!Sawmill Profit ................................................................................... 151!
5.9!Conclusions ....................................................................................... 152!
5.9.1!Residual value method ............................................................... 152!
x
5.9.2!Sawn recoveries ......................................................................... 153!
5.9.3!Net present value ........................................................................ 154!
Appendix A :!Costs and Assumptions ..................................................... 162!
A 1:!Grower Costs .................................................................................... 162!
A 2:!Product price assumptions ................................................................ 163!
A 3:!Product residual values ..................................................................... 164!
A 4:!Flooring timber residual value .......................................................... 165!
A 5:!Production costs ................................................................................ 166!
A 6:!Drying costs: ..................................................................................... 169!
A 7:!Processing costs ................................................................................ 170!
Appendix B :!Scale Diagram of Case Study Stand and Plots ............... 172!
Appendix C :!Sawmill Pattern ................................................................. 173!
Appendix D :!Sawn timber prices ............................................................ 174!
Appendix E :!Glossary of Terms ............................................................. 177!
xi
Table of Figures
Figure 1. E. nitens case study stand individual trees, height and diameter. .... 93!
Figure 2. Plot and sample trees showing heights and diameters. .................... 94!
Figure 3. Estimated volume recoveries per hectare as diameter categories. .. 95!
Figure 4. Nominal sawn timber recoveries according to log small end
diameter. ...................................................................................................................... 97!
Figure 5. Sawmilling cost per nominal sawn cubic metre of production (not
including log cost). ....................................................................................................... 97!
Figure 6. Collapse defect levels and standard deviations for collapse defect in
boards for trees and logs according to drying treatment. ......................................... 103!
Figure 7. Checking levels and standard deviations of checking levels as a
score for trees and logs according to drying treatment. ............................................ 104!
Figure 8. Average sawn timber value according to SED. .............................. 107!
Figure 9. Average sawn timber value per log cubic metre according to SED,
Ignoring collapse defect. ............................................................................................ 108!
Figure 10. Sawmilling costs per log cubic metre. .......................................... 110!
Figure 11. Yard drying costs per log cubic metre. ......................................... 110!
Figure 12. Machining costs per log cubic metre. ........................................... 111!
Figure 13. Residuals, averaged between pricing and grading profiles. ........ 112!
Figure 14. Residuals, averaged between pricing and grading profiles. ........ 113!
Figure 15. Density at test according to log position from single sample tests.
.................................................................................................................................... 121!
Figure 16. Hardness according to log position from single sample tests. ..... 122!
Figure 17. Density for each log per cubic metre. .......................................... 123!
Figure 18. Long term movement in service according to log position. .......... 124!
Figure 19. Level of end-splits present in boards according to log position. . 125!
Figure 20. Surface check levels on profiled product as a score. ................... 125!
Figure 21. Percentage of knot defect in all boards, graded to Australian
Standards. .................................................................................................................. 126!
Figure 22. Percentage of board volume as defect caused by collapse. ......... 126!
Figure 23. Levels of collapse on un-reconditioned kiln-dried boards. .......... 127!
xii
List of Tables
Table 1 Nominal and Dressed Board Widths .................................................. 59!
Table 2 Plot and Stand Data ............................................................................ 94!
Table 3 Plot Data ............................................................................................. 95!
Table 4 Product Recoveries as Percentage of Sawn Volume for Nominal 100
mm, 125 mm and 150 mm Widths from Unpruned Headlogs (Logs 3 - 5) .................. 98!
Table 5 Product Recoveries by Volume for 75 mm and 50 mm Widths from
Unpruned Headlogs (logs 3 - 5) .................................................................................. 98!
Table 6 Product Recoveries as Percentage of Sawn Volume for Nominal 100
mm, 125 mm and 150 mm Widths from Pruned Buttlogs (Logs 1 - 2) ......................... 98!
Table 7 Product Recoveries by Volume for 75 mm and 50 mm Widths from
Pruned Buttlogs (logs 1 - 2) ......................................................................................... 99!
Table 8 Defect as Percentage of Nominal Sawn Recoveries for All Logs ..... 100!
Table 9 Grade Recoveries for 100 mm, 125 mm and 150 mm widths as
Percentage of Nominal Recoveries for All Logs ........................................................ 101!
Table 10 Grade Recoveries for 50 mm and 75 mm widths as Percentage of
Nominal Recoveries for All Logs ............................................................................... 102!
Table 11 Prices per Nominal Cubic Metre for Sawn Timber Profiles based on
Graded-pairs Pricing Method .................................................................................... 105!
Table 12 Prices per Nominal Cubic Metre for Sawn Timber Profiles based on
Constant-Sum Allocation Pricing Method ................................................................. 105!
Table 13 Residual Product Values per Nominal Cubic Metre for 75 mm and
50 mm Width Product ................................................................................................ 106!
Table 14 Predicted Sawn Timber Revenue According to Log SED ............... 107!
Table 15 Mean Sawn Timber Revenue per Log Cubic Metre ........................ 108!
Table 16 Sawn Timber Revenues per Hectare ............................................... 109!
Table 17 Total processing costs per hectare ................................................. 111!
Table 18 Sawn Timber Residual Value per Hectare ...................................... 112!
Table 19. Revenue per hectare from Secondary Products ............................. 113!
Table 20 Sawn Timber Residual Value per Hectare at Year 0 ...................... 114!
Table 21 Cash Flows per Hectare From Secondary Products, Discounted to
Year 0 ......................................................................................................................... 114!
Table 22 Growing Costs per Hectare, Discounted to Year 0 ........................ 114!
Table 23 Net Present Value per Hectare at Year 0 ....................................... 115!
Table 24 Net Present Value per Hectare at Year 0 with Land Price of $20,000
per Hectare ................................................................................................................ 116!
Table 25 Net Present Value per Hectare at Year 0 with Land Price of $5,000
per Hectare ................................................................................................................ 116!
xiii
Table 26 Net Present Value per Hectare at Year 0 with Pulpwood Stumpage of
$31 per Tonne ............................................................................................................ 117!
Table 27 Net Present Value per Hectare at Year 0 with Pulpwood Stumpage of
$0 per Tonne .............................................................................................................. 117!
Table 28 Net Present Value per Hectare assuming Logging and Transport
Costs of $58 per Tonne .............................................................................................. 118!
Table 29 Net Present Value per Hectare assuming Logging and Transport
Costs of $77 per Tonne .............................................................................................. 118!
Table 30 Net Present Value per Hectare after Increasing Revenue from Sawn
Timber by 20% ........................................................................................................... 119!
Table 31 Net Present Values per Hectare after Decreasing Revenue from
Sawn Timber by 20% ................................................................................................. 119!
Table 32 Net Present Values per Hectare After Removing Drying Defect .... 119!
Table 33 Net Present Value per Hectare According to Sawmill Overheads . 120!
Table 34 Log residual value comparisons between studies ........................... 133!
Table 35 Wholesale Prices for Flooring Profiles, Graded-Pairs Comparison
Pricing ........................................................................................................................ 174!
Table 36 Wholesale Prices for Flooring Profiles, Constant-Sum Allocation
Pricing ........................................................................................................................ 175!
Table 37 Wholesale Prices for Panel-Laminating Profiles as Residual Values
.................................................................................................................................... 176!
1
Chapter 1
Introduction
1.1 Introduction
This study examines the economic viability of growing Eucalyptus nitens for
solid timber products using discounted cash flow analysis. Because E. nitens has not
been processed or marketed in New Zealand to date the approach was to value
sawlogs based on residual value to the grower, which involves subtracting processing
costs from sawn timber revenues.
A small stand of pruned and thinned 15-year-old trees was available in
Canterbury for harvesting, as was a small-scale processing operation that was recently
set up specifically for processing eucalypt for solid timber. This provided the
opportunity for assessing revenues and expenditures as a case study to estimate profit
to the grower.
1.2 Background
Eucalyptus nitens is a fast growing and cold-hardy eucalypt species grown in
cooler regions of New Zealand (McKenzie, Turner, & Shelbourne, 2003, p. 63). The
species is commonly found on farms and in small plantations throughout rural
Canterbury, Otago and Southland, with some stands pruned in anticipation of solid
timber processing. The Southland Plantation Forest Company Ltd has established
approximately 10,000 hectares of E. nitens in Southland for hardwood chip/fibre. E.
nitens is considered to be a well-suited plantation eucalypt species for cooler climates
because of frost tolerance, and good growth and form (Beadle et al., 2008, p. 46;
Washusen et al., 2008, p. 4).
2
E. nitens is being managed for solid timber production in other countries, with
approximately 30,000 hectares of Tasmania’s eucalypt plantations (primarily E. nitens
and E. globulus) being pruned and thinned (Washusen, 2011) in anticipation of
processing of solid timber products. In Chile pruning and thinning of E. nitens is also
a common practice (Beadle et al., 2008, p. 46), with approximately 25,000 hectares
being pruned and thinned for solid timber production (Valencia, 2014).
Pinus radiata is the dominant plantation forestry species grown in New
Zealand with 90% of the plantation forest area in this species, followed by Douglas fir
holding 6% of the plantation forest area (NEFD 2011). There may be a case for
diversifying plantation timber species to reduce risk (Nolan, Greaves, Washusen,
Parsons, & Jennings, 2005, p. 83). Species diversification may also provide specialty
forest products that are quality differentiated and additional to those being currently
produced from radiata pine, with opportunities both for export and import substitution
that could improve the total revenue produced from forest products.
E. nitens timber has good strength properties and appearance characteristics,
but is considered to be very difficult to saw and season. If E. nitens were to yield
adequate recoveries of good quality solid-wood products this species could earn a
wider role in New Zealand plantation forestry (McKenzie et al., 2003, p. 64).
Published studies to date have demonstrated low sawn timber grade-recoveries from
the species.
It is well known that investors are cautious of start up forest industries (Nolan
et al., 2005, p. 83). Because plantation forestry involves longer time frames than other
crops, investors would require a comparatively higher level of confidence in projected
returns from forest plantation ventures before considering commitment of capital,
3
especially for ‘emerging’ species lacking a solid history of production, improvement
and research.
Hardwood products are mostly imported into New Zealand with negligible
domestic production. Historically, hardwood products sourced from old-growth
tropical rainforests have been abundant and inexpensive. With chain of custody,
legality and sustainability certification of forest products now common practice,
assurance of supply and stability of prices are uncertain for hardwood products from
old growth and tropical forest origin.
For an industry to develop around plantation hardwood products, log values
must reflect both an adequate return to the grower, along with product returns that
both cover the costs of production and generate a profit (Nolan et al., 2005, p. 83).
Serious growers and investors who would develop an industry of a size that takes
advantage of scale efficiencies would require some knowledge of expected returns,
even if only returns from operating at a scale in proportion to an emerging industry.
1.3 Research Problem and Objectives
Because of serious processing degrade of sawn timber products, profitability
has not been adequately demonstrated to date from growing E. nitens for solid timber.
The objective was to assess economic returns to the tree grower for 15 year-
old E. nitens that were pruned and thinned, using best practice contemporary
processing methods.
To achieve this overall research objective it was necessary to also examine
stand characteristics, wood processing costs, sawn timber grade recoveries, product
pricing, novel products and wood degrade issues. Contemporary best practice
4
processing methods using small-scale processing equipment were applied in an
attempt to produce grade recoveries sufficient for a profit to the grower.
1.3.1 Research questions
For 15 year old case study E. nitens:
1. What are the financial returns to the grower?
2. What factors determine financial returns to the grower?
3. What methods are needed to best estimate financial returns to the grower?
1.4 Conclusions
This study documented the economic viability of growing E. nitens for solid
timber production from a small stand of trees near Rangiora, Canterbury. A range of
issues have limited the success of processing E. nitens into sawn appearance products
to date. If quality sawn appearance products could be produced in sufficient quantities
and at a reasonable cost, the opportunity could emerge for profitably growing E.
nitens for solid timber production. The challenge for processing E. nitens is to
minimise costs and maximise sawn production while also minimising degrade. The
challenge for growing E. nitens is to produce logs that yield the highest sawn timber
value per hectare.
The literature review will examine the trade-offs and issues with processing E.
nitens and log issues that influence the returns generated from production of sawn
timber.
Readers are advised that there is a glossary of terms in Appendix E.
5
Chapter 2
Literature Review: Estimating the profitability of
growing E. nitens
2.1 Introduction
This study aimed to estimate the profitability of growing E. nitens for solid
timber products as a case study using discounted cash flow analysis. Discounted cash
flow analysis is based on the theory of compound interest and brings all future costs
and revenues into the present by adjusting these to take into account interest over the
number of years required for the cost or revenue to be realised (Brown, 2000, p. 54).
Discounted cash flow analysis is generally recognised as the accepted method of
forest valuation in New Zealand (Bloomberg, Bigsby, & Sedcole, 2002, p. 27).
Estimating profitability requires pricing of logs and trees. A method
commonly used for appraising log values is the residual value method (Fairfax &
Yale, 1987, p. 125). The residual value method requires price estimates for final
products and deducts processing costs and required profits to determine the residual
log price (Fairfax & Yale, 1987, p. 125; Liggett, 1995, p. 84). This price represents
the maximum amount the sawmill would pay for the log (Mbugua, 2003, p. 24).
The residual value approach has been used since the turn of the 20th century in
Western U.S.A. for appraisal of log values (Fairfax & Yale, 1987, p. 125).
Historically U.S.A. Forest Service appraisals involved estimating sales value of
timber products from a price index of past sales (Fairfax & Yale, 1987, p. 125), with
gross product values determined by the grade volumes multiplied by the lumber
prices (Nagubadi, Fight, & Barbour, 2003, p. 2). Transactional evidence is now
6
favoured over residual value methods in the U.S.A. for valuing logs of species where
comparable sales data for logs is available (Nagubadi et al., 2003, p. 1).
In New Zealand, the residual value method has been used for calculating
radiata pine log grade prices that were used to explain regional variation in sawlog
prices according to their attributes (Bloomberg et al., 2002). In Australia, Innes at al.
estimated log values for plantation E. nitens using the residual value method (Innes,
Greaves, Nolan, & Washusen, 2008).
Neither log price data, nor product sales price data for sawn products is
available for E. nitens in New Zealand. In the absence of sales price data, alternative
methods were required to price sawn timber products for determining log residual
value. This chapter describes methods for estimating prices in the absence of market
data.
In addition to sawn timber product values, it is necessary to consider other
factors which affect E. nitens log residual value. Residual value is directly influenced
by processing costs and, by its nature, the process of producing sawn timber involves
many steps and outcomes can vary. It is important to consider the nature of timber
processing in order to assess how best to maximise residual value. Important factors
affecting log residual value are the quality of the sawn wood products as grade
recoveries, the volumes of sawn timber produced and the costs involved in production
of these. Grade recoveries are influenced by silviculture, log position, log diameter
and sawmilling methods. Sawn volumes and costs are influenced by log diameter, log
length and sawmilling methods. Each of these factors is considered. First, however,
attention is given to the application of residual value methods to E. nitens.
7
2.1.1 Studies of E. nitens residual value
There are clear inconsistencies between production, grading and pricing
methods used in contemporary studies that sought to quantify levels of defect,
degrade and product recoveries for E. nitens sawn timber in order to estimate log
residual value. The need for relevant research was identified by Nolan et al. (2005, p.
v) when they made recommendations for improving production efficiency for sawn E.
nitens, stating:
Work in these areas should be deliberate comparative studies, operating
across species to a standard methodology that integrates growing and
milling results, and provides improved assessment data for plantation
inventory and economic modeling.
There have been subsequent studies on this topic but they have not met the
standards recommended by Nolan et al.
Innes et al. (2008) assessed product recoveries from three production methods
in order to estimate log residual values for E. nitens. However, the three production
methods could not be adequately compared because grading methods, green sawn
thickness, product values and methods for quantifying defect and degrade all differed
between them. Furthermore, pricing of timber products was based on assumptions that
were arbitrary, producing an average log value delivered to the sawmill of only A
$72.37 per cubic metre. The conclusion that growing and processing thinned and
pruned E. nitens was uneconomic may have resulted from both poor study design and
poor application of grading and pricing methods that led to underestimating log
revenues, discussed in more detail below.
Although this study compared returns from three processing methods, grading
was not consistent between processing methods (Innes et al., 2008, p. 8). Only one
method (Gunns Lindsay Street) produced straightened and machined final products
8
for grading while another method (ITC Newood) did not allow for edge distortion,
thus artificially elevating the recovery results for this method (Innes et al., 2008, p.
19). ITC Newood boards were not edged, but board faces were dressed to final
product thickness for grading. In the third method (ITC Heyfield) dry boards were
edged but faces were only skim dressed. These skim dressed boards were then
assessed for surface checking to determine product value, despite acknowledgement
that this has lower accuracy compared with grading final products (Innes et al., 2008,
p. vi). This is because skip and other sizing defects are difficult to accurately assess
and grade for until boards are sized to final product dimensions. Furthermore,
dressing to final product dimensions exposes measurable levels of internal checking
to the board surface for grading, beyond those exposed during skim dressing. Innes et
al. (2008, p. 10) then downgraded select and medium-feature boards to high-feature
grade in proportion to observed levels of internal checking for the two methods that
involved dressing board faces to final product thickness. However, such downgrading
was not undertaken on the technique involving skim-dressing board faces because an
assessment of internal checking was not made. It was not explained why levels of
checking from the two methods where board faces were dressed to final product
thickness were artificially elevated according to levels of internal checking. It could
be argued that the apparently arbitrary allowance given for internal checking would
have had an unnecessarily high negative impact on grade recoveries from these two
processing methods, despite this allowance being described by Innes et al. as a
significant loss in value (2008, p. 38). Moreover, because high-feature grade held
only one third of the value of Medium-feature grade in this study (2008, p. 10) the
impact of study design on log residual value would have potentially resulting in a
9
serious underestimate of profitability. The level of this discount was not discussed nor
justified and appears to be arbitrary.
These shortcomings illustrate the importance of methods that produce grades
that infer end products that can be priced, rather than grading and pricing quality
levels in an arbitrary manner. Furthermore, accurate comparison of the three
sawmilling methods was not possible because of serious inconsistencies in design and
implementation of the experiment.
Innes et al. acknowledged that total product values were not consistent
between processing methods being compared (Innes et al., 2008, pp. 19, 28).
Although the differences in sawmilling methods were highlighted in this report by
comparing recoveries (2008, pp. 18, 28), this result was clearly confounded by
significant differences (Innes et al., 2008, p. 8) in grading procedures between the
three production techniques used. Other inconsistencies in assessing log values from
the three different production methods used by Innes at al. (2008) included:
1. Not specifying green sawn thickness for two of the three sawing methods reported
(2008, pp. 4, 6). The third method produced 32 mm green thickness material for a
dry skim-dressed board nominal thickness of 25 mm (2008, p. 3). There are clear
inconsistencies in sizing that would confound comparisons between recoveries
from the different sawing systems.
2. A minimum allowable board length of 1.8 m was reported (2008, p. 9) for Gunns
Lindsay Street while a discounted value was allowed for lengths shorter than 1.8
m for ITC Heyfield (2008, p. 28). Furthermore, there was no reject grade for ITC
Newood (Innes et al., 2008, pp. 9, 28).
10
These differences highlight grading methods that varied significantly between
treatments. A minimum allowable board length of 1.8 m for one processing method
would very likely significantly underestimate comparative profitability and bias the
results. Furthermore, the 1.8 m length selected from which to apply discounts was not
justified by any market information, nor was the discount level justified.
Another recent Australian study illustrates inconsistencies between reports and
between sawing and processing treatments that were applied. Washusen et al.(2008, p.
23) in estimating sawn product recovery from E. nitens, reported that boards were
skim dressed on the face and back to the nominal size but edges were not dressed.
Washusen et al. (2008, p. 24) used the same wholesale prices as Innes et al.(2008) for
the three grades used, namely select, standard and high feature grades as specified in
Australian standard 2796.1 (Washusen et al., 2008, p. 23). However it was not
reported whether grading was undertaken on both faces, or only on the best face. In
addition to the grade rules specified in the standard, it was decided arbitrarily that
select and standard grades were to also be free of surface checking, sapwood and skip
on the skim-dressed surfaces (Washusen et al., 2008, p. 32). Where surface checking
or sapwood was present, boards were downgraded from select and standard to high-
feature grade (2008, p. 34). Surface checking was recorded as present only if total
length of checks on the graded face of the board exceeded 20 mm (2008, p. 44).
Furthermore, “a discount of 10 per cent was applied to boards of Select and Standard
grades > 1.8 m and < 3.0 m and a discount of 50 per cent was applied to select and
standard grade boards < 1.8 m” (Washusen et al., 2008, p. 23). The resulting recovery
of select and standard grades was low, as were product values (Washusen et al., 2008,
p. 32), resulting in only A$169 average sawn timber revenue per log cubic metre.
11
There are clear inconsistencies between production, grading and pricing
methods used in the available contemporary studies that sought to quantify levels of
defect, degrade and product recoveries for E. nitens sawn timber in order to estimate
log residual value. Grade recoveries combine with prices as sawn timber revenue, a
key component of log residual value. Improved methods would be consistent between
all variables except the one being tested and would have a logical basis.
In the absence of product sales data for E. nitens sawn products, improved
estimates of log residual value would consider product prices according to product
grades and sizes based on product applications, market demand and market
competition. Careful product grading into profiles and pricing of these according to
market requirements would provide credibility to an economic analysis of E. nitens
profitability using the residual value method of pricing logs.
Standardising of grading methods would allow comparisons between studies
or treatments to be undertaken by researchers. Standardised methods would also need
to be objective in terms of well-defined grade criteria and product profiles that can be
priced from market data.
2.2 Sawmill Productivity and Profitability
Sawmill productivity is largely dictated by the suitability of the processing
equipment for the logs being sawn. A successful processing operation will cost-
effectively utilise as much of the log volume as possible (Nolan et al., 2005, p. 82).
Maximising revenue from production of sawn timber requires knowledge of products
and pricing of these to target products that produce the highest revenue. However, the
full range of products and by-products being produced contribute to overall
12
profitability, including high value products along with lower value products produced
at low cost (Nolan et al., 2005, p. 81).
Producing higher grades of timber in lower volumes might be preferable to
simply maximizing volume production (Nolan et al., 2005, p. 81). The tradeoff
between higher volume production of lower value products and lower volume
production of higher quality products at higher cost requires skilled judgment calls by
the processor. Good decisions would be based on experience and knowledge gained
over time from marketing a range of products and from a good understanding of
species log characteristics such as propensity for degrade.
The influence degrade has on product quality and value is largely determined
by product application. For example, high-value cabinetry and furniture applications
require material free of internal checks, whereas product value for tongue and groove
flooring will not be affected by internal checks unless these are exposed on the
profiled surface (Blakemore & Northway, 2009, p. 4). Clearly there are many factors
that influence target sawn product preference and sawmilling decisions on log
utilisation.
For this case study, sawn products selected were assumed to be those most
suitable for sawing from the case study logs. Assumptions were required on products
that would yield greatest returns from the logs. In consultation with industry expertise
these were selected as:
• Solid timber flooring from nominal 100 mm, 125 mm and 150 mm widths;
and
• panel-lamination stock from 75 mm and 50 mm widths.
13
Although there is not an established market for E. nitens logs in New Zealand,
by estimating sawn timber prices and log revenue, processing costs could be deducted
for log residual value. The approach taken in this case study was to employ best
practice processing methods identified from the literature, assuming that industry
players could reproduce an equivalent productivity on average if they were to utilise
these methods. Cost-efficiency improvements would be expected from this
benchmark in future as methods improve, with this case study representing average
best current practice.
2.3 Log Quality
Log quality is an important factor that determines sawmill profitability.
Average log quality needs to be good enough to produce sufficient volumes of higher-
grade material for returns to exceed the cost of production (Nolan et al., 2005, p. 83).
As log quality increases, production of higher quality appearance grades increases per
cubic metre of log processed (Nolan et al., 2005, p. 82). Therefore, sawmills should
be prepared to pay more for logs where improved quality is definable and returns
justify the higher log price. This is the reasoning behind residual log value. For
example, hardness ratings appear to increase with tree age in E. nitens (Farrell &
Mihalcheon, 2009, p. 11), suggesting that older trees are more suitable for
applications such as flooring where surface hardness is desired. If flooring timber
were to fetch a price premium in the market, so too could older logs that produce
higher quality flooring timber.
Log quality is partly a function of external log quality characteristics such as
diameter and form (Alzamora & Apiolaza, 2010). However, other characteristics
potentially affecting E. nitens log quality may not be visible, such as diameter of
14
knotty core inside pruned logs. Other measurable descriptors that are not visible but
may identify quality include tree age, log position and hardness.
Quality characteristics that could potentially influence grade recoveries and
therefore log value may not even be detectable in a freshly cross-cut sawlog, such as
propensity for end splits, movement, checking and collapse. If such properties were
measurable prior to purchase or processing and a relationship could be established
between log revenue and these characteristics, log price could potentially be predicted
empirically from such characteristics. If log value could be predicted based on quality
descriptors, growers could potentially improve their profit by targeting improved log
quality.
2.4 Silviculture and Log Value
Market demand for timber products influences prices obtained for the grades
supplied. Greatest market demand and value for hardwood timber is as clearwood
(Nolan et al., 2005, p. iv). Select grade timber (graded to Australian standards), with
its low level of feature, dominates Australia’s appearance hardwood market and
fetches the highest price premium (Nolan et al., 2005, p. 7). This suggests that
growers should target production of clearwood from their trees and logs. Two
silvicultural practices facilitate production of clearwood from trees, pruning and
thinning.
The purpose of pruning trees is to improve wood quality and thus value of the
resulting crop. It is well documented that pruning and thinning of plantation eucalypts
is necessary for adequate recoveries of clear appearance grade timber (Shield, 1995,
p. 135).
15
Pruning does not necessarily produce high recoveries of clearwood. Innes et
al. reported that “Grade and overall recovery from thinned and pruned butt logs of 26
year old E. nitens was no better than from unpruned top logs from the same trees”
(2008, p. 19). The logs were described as pruned too late and with a larger knotty core
than would be expected from early-pruned stems (Innes et al., 2008, p. 38). In contrast
McKenzie et al. (2003, p. 62) reported that the knotty core in E. nitens was effectively
restricted by pruning in four lifts to 2, 4, 6, and about 8 m at ages 2, 3, 4, and 6 years
respectively (2003, p. 65). Recovery of knot-free timber averaged 50% of log volume
(McKenzie et al., 2003, p. 72). The implication is that pruning must be practiced
properly for high recoveries of clearwood.
As log diameter decreases, the percentage of the log taken up by defect core
increases, leading to lower recoveries of higher grades from smaller pruned logs
(Washusen et al., 2008, p. 6). Thinning is practiced to reduce crop stocking and
increase remaining tree diameters. Washusen et al. (2009, p. 52) found that sawn
recoveries as a percentage of volume increased with larger tree diameters and
suggested that thinning regimes targeting larger diameters might improve grade
recoveries (p. 50).
Silvicultural practices potentially increase sawn timber recoveries and grade
recoveries and therefore could improve returns to the grower. Final crop stocking for
sawn timber production should be low enough to ensure pruned logs mature into
diameters large enough to maximise log residual value. However, to date no attempts
have been made to optimise final crop stocking and rotation length for solid timber
production from pruned E. nitens for specific processing equipment. This study aimed
to produce costs and revenues along with graded sawn recoveries for the range of tree
diameters present in the case study stand.
16
2.5 Log Position and Log Value
The literature points to a number of factors that could influence grade
recoveries according to log position, suggesting that log position appears to be an
important variable for predicting revenue from logs.
With the exception of end-splitting, which was observed to increase in the
second log, Washusen et al. reported that upper logs posed fewer processing issues
than did buttlogs (2009, p. 52). This implies that upper, unpruned logs might produce
profitable sawn grade recoveries. Height in tree was also found to influence both
surface and internal checking levels, with less checking occurring at 6 m height than
0.5 m above the ground (Blakemore et al., 2010, p. 32). Collapse has consistently
been found to be worse lower in the tree (McKenzie et al., 2003, p. 72; Purnell (1988)
as cited in Shelbourne et al., 2002, p. 360). Deflection (movement off the saw),
however, was reported by Washusen et al. (2008) to be higher from second logs than
from buttlogs (p. 41). Washusen et al. also found that radial shrinkage increased
significantly from the first pruned log to the second pruned log (2009, p. 49) and
suggested this could result in more skip in boards sawn from the second log.
Because log position appears to be an important variable for predicting
revenue from logs, there is a need to examine the effect log position has on
recoveries.
2.6 Sawmilling Systems and Factors Influencing Value Recovery
Investigating best practice processing methods that maximise sawn timber and
grade recoveries while also minimising production costs would be required to
demonstrate economic value from E. nitens sawn timber production.
17
To date, research into production of solid timber from E, nitens has primarily
examined wood quality issues, processing systems and the relationship between these
two. Although a range of studies have quantified sawn recoveries and grade-limiting
defects from young, pruned plantation E. nitens in both New Zealand and Australia,
to date only Innes at al. (2008) published estimates of product value per cubic metre
of sawlog and per hectare for plantation E. nitens in the public domain.
Innes et al. (2008, p. 1) reported on the profitability of using existing
traditional and contemporary Australian native forest eucalypt sawing and drying
systems as a first step in exploring utilisation of sawn plantation E. nitens. However,
Innes et al. identified a range of shortcomings in the production techniques used in
their study that resulted in high levels of checking, knots, collapse and distortion
(2008, p. 23), thus generating low overall product values (2008, p. 39).
Best practice sawmill methods are those that have been documented to
minimise degrade in sawn products. However, there is little published research that
reports improvements in economic value from processing E. nitens into solid timber
products from best practice methods. In order to identify methods most suitable for
producing greatest returns from E. nitens sawn timber, this section will consider
traditional processing methods, then improvements to these before considering
contemporary methods.
2.6.1 Traditional processing of ash eucalypt
Cold climate eucalypt species such as the ash group have a set of processing
challenges that if not carefully managed result in low grade recoveries, particularly
with smaller log diameters such as from the Australian second growth resource.
18
Conventional single sawing methods, as traditionally practiced on old growth
Australian native ash species, can have high processing costs and low nominal sawn
recoveries. Washusen (2011, p. 8) attributed these inefficiencies primarily to large
saw kerfs, large allowances for green board oversizing and slow throughput because
of reciprocating carriages and regular log turning. These inefficiencies are
compounded as log diameter and length is reduced (2011, p. 8).
In order to avoid skip and undersizing of products, conventional processors of
native forest ash eucalypts in Australia target a mean green board thickness as high as
31 mm to produce dried boards with a nominal thickness of 25 mm (Washusen et al.
2006, cited by Washusen, 2011, p. 8). This oversizing of green board thickness is
practiced to eliminate the presence of skip on the faces of boards dressed to nominal
sizes, but has the consequence of reducing nominal recoveries as a percentage of the
log volume.
Issues with traditional processing are exacerbated with production of
appearance timber from plantation E. nitens. Washusen et al. (2009, p. 53) practiced
conventional ash sawmilling methods on E. nitens and attributed high levels of sawn
board defects to shortcomings in conventional processing practices, including poor
sawing accuracy, inappropriate weighting of drying stacks, lack of control of drying
rate in ambient conditions and steam reconditioning applied at sub-optimum moisture
contents. Washusen et al. (p. 53) concluded that both sawing and drying strategies
needed to be improved for the plantation resource.
2.6.2 Improvements to traditional processing methods
Washusen (2011, pp. 1, 23) suggested that improvements to sawing strategies
should include better sawing accuracy and sawmill efficiency, together with “correct
19
oversizing” of green sawn boards. Suggested improvements to drying strategies
included better control over moisture gradients in the boards, optimised steam
reconditioning and correct weighting of drying stacks (Washusen, 2011, pp. 1, 23).
Innes et al. (2008, p. vi) concluded that for high value sawn products to be
produced from E. nitens plantations, the sawing equipment would need to be
optimised for the plantation resource, with specific processing techniques required to
control distortion, collapse and checking. Innes et al. observed that dry recoveries
varied considerably between sawmilling technologies (2008, pp. 18, 38) and
concluded that for economic production of sawn appearance grade timber from
plantation pruned and thinned E. nitens, both sawing and drying techniques would
need to be improved to provide greater control over distortion and checking (2008, p.
41).
2.6.3 Contemporary sawmill technologies
Washusen suggested that sawmill efficiencies could be improved from
traditional methods as practiced on old-growth ash eucalypt by utilising twin and
multi saws to symmetrically release stresses on opposite sides of the log or flitch at
once (Washusen, 2011, p. 9). Currently available sawmill systems utilising this
technology are restricted to small maximum log diameters, including 45 cm for
Whittaker’s Timber Products small log line (Washusen, 2011, p. 10), 25cm for the
Hewsaw R200 and 34 cm for the Hewsaw R250 (Washusen, 2011, p. 12). However,
small sawlog diameter has been identified as a factor that reduces sawn timber and
grade recoveries.
In an attempt to improve processing systems for E. nitens, Blakemore et al.
(2010) applied contemporary sawing, drying and reconditioning schedules to E. nitens
20
timber. Boards were sawn on a Hewsaw, a multi-saw linear flow system designed for
softwood sawmilling that produces flatsawn boards (Washusen, 2011, p. 16). The
Hewsaw removes wood simultaneously from around the log by using chippers ahead
of symmetrically oriented multiple circular saws, allowing production of long-length
(5 m) flatsawn timber. Sawing longer lengths reduces end splitting as a proportion of
green sawn timber (Washusen, 2011, p. 14) and sawing costs are low (Table 1,
Washusen, 2011, p. 16), provided an operating log throughput of 120,000 cubic
metres per annum is available (Washusen, 2011, p. 12). However, because the sawing
pattern cannot be altered for logs of varying diameters, mean green sawn recoveries
were reported to be less than 40% for the flatsawing strategy (Blakemore et al., 2010,
p. 2), with percentage recoveries reducing as log diameters increased.
Washusen (2011) reported that no attempt was made to evaluate grade
recoveries as a percentage of log volumes from two Hewsaw trials sawing E. nitens,
despite acknowledging that a large proportion of the boards produced would contain
pith, which is associated with drying degrade (2011, p. 15). Grade recoveries were not
quantified, nor were product values assessed against production costs in these trials.
Issues with the Hewsaw system include limited grade recoveries because of
proportionally large defect cores from the small log diameters, the wide flatsawn
boards would be subject to cupping and checking defect and because centre boards
contain pith, these would be severely devalued for appearance applications.
Furthermore, for production efficiency to be optimised the log diameter range is very
narrow.
Satchell and Turner reported low levels of defect and high grade recoveries
from sawmilling and sizing 18 year old Eucalyptus regnans, using a sawmilling
method developed for small diameter eucalypt (Satchell & Turner, 2010, p. Results).
21
The method involved accurate placement of logs for initial saw cuts, skilled judgment
calls by the sawyer, predefined log lengths according to diameters, sawing faces
before edges and accurate edging for grade recoveries based on visual cues on board
faces. The technique involved cutting narrow quartersawn boards in preference to
wide flatsawn boards.
Controlling for defect and degrade appears to be essential to achieve adequate
grade recoveries from E. nitens and study design requires attention to minimising
avoidable defect and implementing sawmilling methods that maximise log revenue
and minimise costs. By identifying then applying methods that are current best
practice, this study approached profitability as a performance benchmark, with cost
and grade recovery results that any processor using the case study equipment and
methods could expect.
Specific methods applied to sawing eucalypt have been studied and the
literature identifies a range of issues with these and how they influence production
efficiency and recoveries.
2.7 Factors influencing grade recoveries and sawmill efficiency
To efficiently convert E. nitens logs into sawn timber product, the literature
draws attention to three main issues: sawing pattern, growth stresses and log end-
splitting. Each of these is considered in turn.
2.7.1 Sawing pattern
Sawmill pattern will determine the quantities produced of two distinct types of
boards, quartersawn and flatsawn. Strategies tend to target one type of board or the
other.
22
There is widespread disagreement among Australian researchers on the
comparative merits of quartersawing versus flatsawing as processing strategies.
In Australia native forest ash eucalypt is generally quartersawn to minimize
drying defects and improve the resulting products’ stability in service (Blakemore &
Northway, 2009, p. 4; Washusen et al., 2008, p. 7). Conventional sawmills prefer log
mid-diameters greater than 40 cm for quartersawing (Washusen et al., 2009, p. 41)
and “it is well understood that quarter-sawing is a poor sawing strategy for small
diameter eucalypts” (Washusen, 2011, p. 6).
McKenzie et al. (2003, p. 71) reported that for a mean log diameter of 480
mm, recovery of quartersawn E. nitens timber averaged 50% (2003, p. 72). Although
these recoveries are high relative to Australian studies, the methods used for
measuring recoveries were poorly reported and it is not clear whether the recoveries
were green sawn, nominal or dry, or whether recoveries included end-splits.
Straightening cuts were applied in Mckenzie et al. to remove crook when ripping
boards from slabs (2003, p. 75). The log length was 5m which required application of
regular face cuts to the residual log. Slabs were then reduced to half that length prior
to ripping (2003, p. 72). This strategy yielded high sawn recoveries but costs were not
reported.
Cost-efficiency is an important consideration when assessing profitability of a
sawmilling method because marginal revenue needs to exceed the marginal cost of
implementing improvements in recoveries in order to maximise log residual value.
Strategies consider the tradeoff between increasing the cost of sawing for higher
recoveries and the value of sawn timber recovered.
23
Flatsawing is a lower cost strategy than quartersawing but the risk is lower
grade recoveries. The additional cost of quartersawing may be justified if returns are
improved. Although Nolan et al. suggested E. nitens should be quartersawn even as
small diameter logs (2005, p. 28), there has been a strong preference to flatsaw E.
nitens among contemporary Australian researchers, primarily because flatsawing
produces a consistently higher green-sawn percentage recovery from small diameter
logs (Blakemore & Northway, 2009, p. 4). However, producing larger volumes at
lower cost may not result in higher revenue. Washusen et al. (2008, p. 2) reported that
product values were significantly higher per cubic metre of log sawn using a
quartersawing strategy, despite lower volumes produced. This was because a high
incidence of surface checking significantly devalued the flatsawn timber.
Another issue influencing sawn timber value is board width. For a given log
diameter a flatsawing strategy produces a greater proportion of wider boards
(Washusen et al., 2008, p. 7). As log diameter decreases, quartersawing becomes less
cost-efficient (Washusen et al., 2008, p. 30), while quartersawn boards also become
narrower. Based on the perception that value per cubic metre increases with board
width (Washusen et al., 2008, p. 7), Washusen et al. chose a strategy of flatsawing the
widest boards possible from pruned plantation E. nitens in an attempt to maximize
both board width and board grade, therefore value (2008, pp. 2, 17). However, wide
flatsawn boards are subject to cupping (Washusen et al., 2008, p. 42), which then
results in skip defect. Washusen et al. (2009, p. 53) reported that flatsawn boards from
buttlogs had mean cupping of over 2mm. To remove this level of cupping from both
the face and back of a board, 5mm of wood would have required to be removed from
the thickness (Washusen et al., 2009, p. 53). This would have reduced the product
volume significantly and therefore log revenue. It is notable that cupping has less
24
impact on dressed board thickness in both narrower flatsawn boards and quartersawn
boards than in wide flatsawn boards.
Tasmanian plantation E. nitens timber has approximately twice the amount of
tangential shrinkage than radial shrinkage (Innes et al., 2008, p. 41). As a result,
flatsawn boards are much more likely to cup during the drying process and move in
service when exposed to moisture variation than quartersawn boards (Blakemore &
Northway, 2009, p. 4; Kingston and Risdon, as cited in Nolan et al., 2005, p. 28).
Washusen et al. (2008, p. 43) found that width shrinkage was significantly lower in
quartersawn E. nitens boards than in flatsawn boards. This anisotropic shrinkage leads
to greater stresses on flatsawn board faces than on quartersawn board faces, resulting
in checking and cupping in flatsawn boards (Blakemore & Northway, 2009, p. 4).
Furthermore, restraining this cupping potential in the drying stack could lead to an
increase in these tension stresses, causing further surface checking (Blakemore &
Northway, 2009, p. 4). The implication is that narrow flatsawn boards, with greater
freedom to move and lower stresses at work on the board face, might check less
during drying than wider flatsawn boards.
Collapse on the face of flatsawn boards is likely to be expressed as checking
(Blakemore & Northway, 2009, p. 4). Although collapse can be severe on
quartersawn board faces, this is likely to be expressed as washboarding rather than
checking (Blakemore & Northway, 2009, p. 4). Checking is a serious value-limiting
defect, whereas collapse has no impact on value if removed when profiling the timber.
A range of issues need to be considered in the design of sawmilling methods
that minimise degrade, maximise production volumes, minimise costs and produce a
quality sawn product. Although quartersawn boards are likely to have lower levels of
checking than flatsawn boards and are more stable in service, log diameter affects the
25
cost efficiency and production efficiency with which quartersawn boards can be
produced. Study design should use methods that take into account the tradeoff
between sawn board quantity and sawn board quality from the log in order to
maximise residual value from the sample sawlogs.
Satchell and Turner (2010) evaluated a hybrid pattern (See Appendix C) and
reported relatively low costs and high grade recoveries for the scale applicable to this
study from small-diameter E. regnans. Average small end diameter was 31.8 cm with
a diameter range of 25 – 43 cm. This method was selected as the most suitable for
sawing the case study E. nitens logs because:
• E. nitens has a propensity for high levels of surface checking. Quartersawn
output was desirable and innovations allowed cost-efficient production of
quartersawn output; and
• average log diameters from the case study stand (32.94 cm) were smaller than
required for traditional quartersawing patterns (>40 cm).
2.7.2 Growth stresses
The outer section or periphery of a eucalypt log is in longitudinal tension, with
a stress distribution progressing to longitudinal compression in the core (A. N.
Haslett, 1988, p. 12). Sawing of eucalypt logs and release of stresses results in bent
flitches and curvature in the residual log. Regular face cuts may be necessary to
produce even thickness flatsawn boards, while edge cuts are necessary to produce
straight quartersawn boards. These additional saw cuts result in recovery losses
(McKenzie et al., 2003, p. 63) and increased costs.
McKenzie et al. (2003, p. 72) reported that recoveries of quartersawn timber
were inversely related to growth stresses in the logs. Larger growth stresses resulted
26
in more distortion of sawn surfaces. Therefore to produce straight boards,
straightening cuts removed greater curve from slab edges, consequently reducing
sawn timber recoveries.
The radius of curvature (also called ‘deflection’) tends to be greater when
sawing smaller diameter logs because stress gradients decrease as diameter increases
(Nolan et al., 2005, p. 29; Shield, 1995, p. 134; Washusen et al., 2009, p. 6).
When producing quartersawn material, as log length increases more wood is
removed from both edges to straighten the resulting board or cant from ‘spring’
curvature. Sawn recoveries reduce per log cubic metre as log diameter declines,
provided log length is constant (Nolan et al., 2005, p. 30). Reducing log length
counteracts the effect movement has on recoveries from smaller diameters. However,
the consequence is that sawing costs increase because there is more handling for a
given volume of logs.
As log length increases, producing even thickness flatsawn material with a
single saw requires face cuts of increased thickness on the residual log, flitch or cant
to straighten the face. The tradeoff is that production efficiency improves by
flatsawing longer logs.
Some contemporary sawing systems such as twin or multiple sawing lines can
overcome thickness variation in flatsawn boards by sawing simultaneously on
opposite sides of the log (Shield, 1995, p. 136) to symmetrically release stresses on
both faces. This allows longer flatsawn lengths to be milled without requiring face
cuts, thus improving sawmill efficiency. Crook distortion on edges of quartersawn
material is not overcome (Innes et al., 2008, p. 24), because only stress on board faces
is relieved by symmetrical cuts. Edge straightening cuts of quartersawn boards over
27
long lengths remain at “the expense of substantial recovery loss” (Blakemore et al.,
2010, p. 26).
Washusen et al. (2008, p. 41) reported that slabs quartersawn from the centre
to the periphery distorted significantly more than the half log from which the slab was
cut. The explanation given by Washusen et al. (2008, p. 41) was that “distortion
increases as the sawing process continues”. A more plausible explanation is that half
logs do not undergo full stress release between the pith and the periphery
perpendicular to the saw cut halving the log. This is because half-log deflection
induces counteractive stresses at the peripheries adjacent to the saw cut that were not
under tension in the direction of the deflection. This resulting counteractive stress
would constrain the full release of tension. Once slabs from this central area are sawn
from the residual log they release their tension freely. As the width of a quartersawn
slab increases, the stress gradient will be steeper, resulting in increased curvature
expressed as crook (Nolan et al., 2005, p. 29). Sawmilling strategies can take
advantage of counteractive stresses by releasing these into slabs before applying
straightening cuts, thereby increasing production efficiency.
It is important to understand that the radius of deflection is not influenced by
log length. However, the level of deflection does increase as the log gets longer. The
length tradeoff is therefore between:
• value lost from short logs caused by short board lengths, higher sawing costs
and end-splits; and
• value lost from long logs as sawn recovery lost from straightening cuts.
In summary, distortion resulting from stress release does have a negative
impact on log residual value. Removing distortion to produce a high quality
28
straightened sawn product reduces sawn percentage recoveries and increases
production costs because of the larger number of cuts required. This is a ‘fact of life’
with eucalypt sawmilling and indirectly influences log residual value because there
are costs and benefits with different sawmilling approaches.
As log diameter decreases, resulting lower sawn recoveries and higher costs
imply an increasingly negative impact on log residual value, compounded by the
shorter log lengths required for adequate sawn recoveries.
To ensure sawn recovery remains high as a percentage of the log, log length
must be restricted in proportion to the diameter because quartersawn slabs experience
edge curvature and with single saws flatsawn slabs experience face curvature. Larger
diameter logs, because these move less in proportion to their diameter, can be sawn at
longer lengths.
The sawmill method described in Satchell and Turner (2010) produces
straightened boards by first sawing slabs and then edging these. Although log length
could potentially be optimised according to diameter for greatest residual value, for
this case study log length was set to 3.0 m as industry best practice for the diameter
range being sawn. Movement off the saw can be easily measured with this sawmill
pattern because logs are halved before other saw cuts are made. This offered the
opportunity to quantify the effect movement had on sawn recoveries according to log
diameter and log position at a standard length of 3.0 m and movement was measured
for each sample log.
2.7.3 Log end splitting and log length
Increased levels of log end splitting reduce grade recoveries. Factors
influencing levels of end-splits have been reported in the literature.
29
Sawn timber volume losses from end splitting have been found to be greater in
flatsawn boards than in quartersawn boards and to increase progressively with tree
height (Washusen et al., 2008, p. 40).
Longer log lengths can reduce volume losses attributable to board end splitting
(Blakemore et al., 2010, p. 2). Washusen reported only 1.2 – 2.9% loss in green sawn
recovery caused by board end-splits from sawing 5 m log lengths with a Hewsaw
(Washusen et al. cited by Washusen, 2011, p. 14).
Satchell and Turner (Satchell & Turner, 2010, p. Results) reported end
splitting losses of only 1.4% of nominal sawn recovery, from machine harvested
small diameter 6m E. regnans logs, cross cut in half to an average log length of 3 m
immediately prior to sawing and sawmilled within 28 days of harvesting.
End-splits increase with time after cross cutting of logs. If logs are sawn
immediately after cross cutting, end splits are not likely to impact on recoveries to any
significant extent, regardless of log length. Therefore best practice is to saw logs as
soon as practicable after harvest, to avoid defect resulting from end-splits that would
otherwise impact on log residual value.
2.7.4 Knot defect
Although pruning is considered to be essential to overcome defects associated
with branches and to produce high value appearance clearwood from plantation
buttlogs (Washusen, 2011, p. 3), pruned logs do not necessarily produce high
recoveries of clearwood.
Innes et al. (2008, p. 23) reported the presence of knots to be the primary
reason for downgrading boards from pruned logs. Inclusion of knotty core in boards
30
from pruned logs can be seen in plates 5-8 (Innes et al., 2008), indicating that edging
was not practiced properly to target clearwood from pruned material.
Grade sawing involves a tradeoff between volume production and higher
grade recoveries. Sawmilling best practice involves judgment calls aimed at
producing grade recoveries that maximise the value of sawn timber produced from the
log. Where practicable, sawmilling methods should exclude knotty core from boards.
This can be achieved by visually assessing where slabs are to be edged and taking
care to edge out knotty core for production of clearwood.
Edging of unpruned logs also requires similar judgment calls to target higher
grades by excluding corewood and where practicable excluding knot defect.
Sometimes knot defect can be excluded by edging and other times this is best
docked out from the board length. Knot defect inevitably reduces grade recoveries
from headlogs, however the impact knots and pruning have on E. nitens log value is
not well understood. By examining relationships between levels of knot defect in
boards and log attributes such as log position and log diameter, improved forest
management practices could result that lead to higher log prices for the grower.
2.7.5 Summary and proposed methods
A range of methods are available to the sawmiller that can potentially reduce
defect in the resulting sawn timber. Sawmilling pattern can affect volume recovery,
costs and grade outcomes along with levels of checking that develop during drying.
Growth stresses and end splits can reduce sawn timber recoveries and increase costs
for producing these. Shorter log lengths reduce recovery losses caused by growth
stress, but at the expense of increased sawing costs. End splits are unavoidable but
31
defect resulting from these can be minimised by sawmilling soon after cross cutting
logs.
This study aimed to use best practice methods identified in the literature for
converting case study logs into sawn timber, in order to maximise log residual value
and therefore returns to the grower. Sawmilling method as practiced in Satchell and
Turner (2010) was selected, with 3 m long lengths sawn soon after cross cutting to
length to minimise defect from end splits.
This study also aimed to quantify knot defect present in boards from pruned
buttlogs and unpruned headlogs, along with recoveries of sawn timber to examine the
effect knots have on grade recoveries and log residual value.
2.8 Drying Degrade and Log Value
In order to produce high-quality appearance hardwood products from
plantation E. nitens logs, significant levels of defect must not develop in the drying
process (Washusen, 2011, p. 18). To avoid levels of drying degrade that impact
seriously on economic value of sawn products, E. nitens timber must be dried slowly
and with care (Nolan et al., 2005, p. 31), particularly in the early stages (Nolan et al.,
2005, p. 32).
Washusen rated checking as the drying defect having the greatest impact on
product quality (2011, p. 19). Blakemore and Northway (2009, p. 45) identified
checking as “the major limitation for processing pruned plantation grown E. nitens
into appearance grade products”.
32
2.8.1 Drivers of checking degrade
Initial drying that takes place too rapidly has been associated with increased
internal checking and collapse in E. nitens (Nolan et al., 2005, p. 31).
Normal shrinkage (i.e. shrinkage not associated with collapse) across a
tangential board face can cause high levels of stress to develop, leading to surface
checking (Washusen, 2011, p. 19). Jacobs (as cited in McKenzie et al., 2003, p. 63)
reported that collapse in the flatsawn face of a board can “show as heavy open checks
with distortion of the surface as well”.
Collapse shrinkage, unlike normal shrinkage that occurs below fibre saturation
point, is also implicated in much of the surface and internal checking experienced in
low to medium density eucalypt species (Blakemore & Northway, 2009, p. 9;
McKenzie et al., 2003, p. 63; Washusen, 2011, p. 19).
Shelbourne et al. (2002, p. 378) reported that checking in kiln dried E. nitens
disks was representative of checking in sawn boards and found that:
• Checking levels appear to be variable more at the individual tree level than
provenance or site, with a large range of checking levels evident between trees
(2002, p. 373);
• checking levels decrease with tree height (2002, p. 378); and
• checking was more frequent in the transition wood zone (2002, p. 371).
Internal checking in E. nitens may not be related to tree age, with high levels
of checking reported by Yang and Waugh (as cited in Shelbourne et al., 2002, p. 360)
in 15, 25 and 29 year old trees.
Levels of internal checking in dry E. nitens boards increase with board
thickness (Blakemore et al., 2010, p. 18). Blakemore et al. (as cited in Washusen,
33
2011, p. 22) reported that thin section quartersawn E. nitens could be processed to be
virtually free of surface and internal checking. As board thickness decreases,
earlywood collapse may express as washboarding rather than internal checking
(Blakemore & Northway, 2009, p. 4).
Washusen et al., using conventional native forest ash eucalypt processing
strategies, found the incidence of surface checking to be high (2008, p. 45). Haslett &
Young reported high levels of checking in quartersawn boards from 30 year old E.
nitens timber kiln-dried after what they described as “careful air drying” (T. Haslett &
Young, 1992, p. 8). However, Haslett and Young (1992, p. 9) reported that twisting of
boards during drying was also a serious problem, suggesting that drying was not
practiced carefully. This is because twisting is preventable and well known to be
caused by either not weighting the stack properly or drying the wood too fast.
Because no detailed description of the drying process was outlined in the report,
neither the timber nor the level of care can be clearly implicated as causing these poor
results.
Innes et al. proposed further research to address the drying of E. nitens (2008,
p. vii) because using current Australian industry drying methods, 15-40% of boards
from pruned and thinned E. nitens buttlogs contained significant levels of internal
checking (2008, p. 40). However, review of subsequent literature has not revealed any
clear understanding of drivers that cause checking, nor methods to prevent the
problem. Indications from the literature are that to limit checking to levels that do not
impact heavily on economic value, current best practice includes:
• Slow drying of timber, especially during the early stages of drying;
• quartersawing where practicable; and
• limiting board and product thickness.
34
This study did not seek to develop specific methods for reducing checking, nor
to quantify impact on economic value of tree age or variation between individual trees
for the species. The intention was to undertake best practice methods identified in the
literature, then assess their influence on case study log and stand residual value.
This study practiced methods that were intended to minimise levels of
checking given what is currently understood of the issue. Product thickness was sawn
to 28 mm and timber was slow air-dried.
2.8.2 Log position and checking
Checking of sawn timber from E. nitens buttlogs has been reported as the most
serious value-limiting defect in several studies (Innes et al., 2008; McKenzie et al.,
2003, p. 76; Washusen, 2011; Washusen et al., 2008, 2009). Innes et al. (2008, p. 23)
reported that levels of checking were higher in pruned buttlogs (the primary reason
for downgrade in 25-30% of boards) compared with unpruned upper logs (the primary
reason for downgrade in 8-10% of boards) from the same trees. Blakemore et al.
(2010, pp. 3, 31) reported that levels of both surface and internal checking decreased
with height in the sawlog and also found that unpruned buttlogs yielded greater levels
of internal checking than pruned buttlogs, especially before reconditioning. Washusen
et al. (2008, p. 2) found that upper pruned logs produced significantly higher product
values per cubic metre of log input than lower pruned logs, primarily because of
reduced surface checking.
The importance of log position has been clearly identified in the literature as
influencing levels of checking. This study aimed to quantify levels of checking
according to log position to examine the impact log position has on log residual value.
35
2.8.3 Steam reconditioning and checking
Traditional processing of Australian native forest eucalypt involves steam
reconditioning once the moisture level within the boards reaches fibre saturation point
(Washusen et al., 2008, p. 20). Contemporary reconditioning strategies have been
developed in Australia where greater collapse recovery is achieved by reconditioning
at lower moisture contents than traditionally used (Blakemore & Langrish, 2007).
Blakemore et al. (2010, pp. 31, 42) reported that the prevalence of visible
internal checking was dramatically reduced from that reported previously by
reconditioning only once board moisture content was below 20% (2008, p. 18) or
fibre saturation point (2008, p. 20). However, closed checks (i.e. those that were not
visible) were not reported (Blakemore et al., 2010).
Checks can be ‘closed’ by steam reconditioning, which makes them less
visible (Blakemore et al., 2010, p. 2). However, although the visibility of checks can
be significantly reduced (Blakemore et al., 2010, pp. 41, 42), “The impacts of closed
checks in reconditioned sawn boards from plantation-grown E. nitens in a range of
downstream manufacturing processes and in product service needs to be determined.”
(Blakemore et al., 2010, p. 3). Closed checks on the surface of a board are visible in
finished products and “the closed-up hairline cracks remain” (Blakemore et al., 2010,
p. 44). These could open up later in service or ‘feather’ during secondary processing,
resulting in defective product (Blakemore & Northway, 2009, p. i). The impact closed
surface checks could have on appearance product values has not yet been studied, but
closed surface checks could potentially be a worse problem than open surface checks
which are clearly visible and result in downgrading of the material (Blakemore &
Northway, 2009, p. i). Washusen (2011, p. 1) identified this issue as an important
36
knowledge gap in need of further research. Blakemore and Northway (2009, p. 16)
described it as follows:
Conventional industry wisdom is that such closed checks pose a serious
problem, in that if exposed when machining or moulding is undertaken,
they will result in a feathering effect on the surface of the product. This
may not be a significant problem for products such as quartersawn
flooring, but it is a problem for backsawn products and cabinetry
components such as high-value kitchen cupboard doors.
It can be concluded that reconditioning does not actually remove checking
degrade but does confound attempts to measure levels of checking in research
experiments. A standardised approach to quantifying levels of checking would allow
future research to potentially compare conflicting results and isolate the causes of
checking.
Direct comparisons of checking degrade between processing studies would
require either an identical reconditioning process or none at all. By describing closed
checks as “not visible” (Blakemore & Northway, 2009, p. 16), this implies that closed
checks may not be visible to graders or researchers. Thus true levels of checking
degrade resulting from the processing treatment being tested would not be
measurable. In contrast, by not steam reconditioning timber, levels of degrade caused
by surface checking such as length and width of checks or their prevalence could be
accurately measured and quantified. However, assumptions would need to be made on
levels of skip caused by collapse.
2.8.4 Collapse degrade and steam reconditioning
Collapse shrinkage, unlike normal shrinkage that occurs below fibre saturation
point, is considered to be severe ‘abnormal shrinkage’ because it occurs in timber
above fibre saturation point (Blakemore & Northway, 2009, p. 9).
37
Collapse shrinkage of E. nitens can be recovered by steam reconditioning. Up
to 95% of collapse shrinkage in air-dried boards can be recovered (Blakemore &
Northway, 2009, p. 13), effectively reducing the levels of shrinkage in the board. This
allows green sawn sizing to be reduced without an increase in skip defect, resulting in
increased nominal sawn recoveries. The extent to which boards should be oversized in
the sawing process would thus be dependent on whether the boards were to be steam
reconditioned. The cost of steam reconditioning should be economically justifiable by
the improved nominal recovery and value that results from reduced green sizing.
The case study timber was not steam reconditioned. This allowed for accurate
measurement of levels of checks on profiled surfaces. Although the green thickness of
28 mm was selected as industry best practice for eucalypt species in New Zealand, the
optimum thickness for highest residual value for unreconditioned E. nitens was
unknown. Therefore a scenario was designed to enable an economic comparison to be
made between residual value for unreconditioned and reconditioned timber, assuming
that all collapse would have been recovered sufficiently if reconditioned to have been
profiled without exhibiting skip.
This approach also allowed for an evaluation of skip defect on the profiled
case study boards given the chosen green thickness, while also allowing for the
importance of steam reconditioning to be quantified in economic terms.
2.8.5 Summary and approach to drying
In conclusion the literature is not currently clear about the degree to which
levels of checking can be predicted or explained in sawn E. nitens timber. This study
aimed to develop and document methods for measuring checks suitable for
standardising and applying to future research, to facilitate improved research methods
38
examining causes of checking. To date methods for defining or measuring checks
have not be standardised.
Methods selected as best practice to minimise levels of checking were to saw
the timber to 28 mm green thickness and air dry the timber as slowly as practicable.
This study aimed to:
• Apply best practice drying methods to reduce levels of checking as much as
practicable;
• quantify levels of checks on unreconditioned profiled surfaces and examine
their impact on sawn timber value; and
• assess the economic impact of steam reconditioning on log residual value.
2.9 Air Drying of E. nitens
Two drying methods are applied to drying appearance hardwood timber.
These are:
• Air drying followed by kiln drying; or
• kiln drying from green.
Air-drying is the predominant method used in Australia for drying eucalypt
species that are known to require slow drying (T. Innes, pers. comm.).
McKimm et al. (as cited in Shelbourne et al., 2002, p. 360) found air drying of
20 year old E. nitens followed by kiln drying resulted in less internal checking than
kiln drying from green.
The largest sawmill in Australia processing ash eucalypt (Heyfield, Victoria)
exclusively uses air-drying and wraps stacks with permeable cloth in warmer periods
of the year (T. Innes, pers. comm.). Air flow, temperature and humidity all influence
39
the rate of drying and during drier, warmer periods of the year wrapping freshly sawn
timber stacks slows the rate of drying and avoids excessive degrade (T. Innes, pers.
comm.). Air-drying appeals to producers because it is low cost and does not require
energy nor high capital input (T. Innes, pers. comm.). Priest et al. (as cited in Bekele,
1995, p. 5) reported that 25 mm thick Eucalyptus grandis air dried with less degrade
than kiln dried material and produced a more uniformly dry material when finished in
a kiln than material dried from green in a kiln. Gough (as cited in Bekele, 1995, p. 5)
also found that best results were obtained from finishing air-dried Eucalyptus timber
in a solar kiln. In contrast Washusen et al. (2000, p. 7) reported that slow air-drying of
40 mm thick E. globulus produced high levels of degrade similar to E. globulus that
was slow kiln-dried from green. McKimm et al. (as cited in Shelbourne et al., 2002, p.
360) found air drying of 20 year old E. nitens followed by kiln drying resulted in less
internal checking than kiln drying from green.
The literature points to conflicting results in the few reports available that
compare the two standard methods for drying eucalyptus timber. It was decided that
the risk was too high to dry the case study timber from green in a kiln and to use
Australian industry standard practice methods for ash eucalypt and slow air dry the
timber, followed by finishing in a kiln.
The three elements that control drying rate are air temperature, relative
humidity and airflow across the timber surfaces (Langrish & Walker, 2006, p. 1).
Unlike temperature and humidity, controlling air flow can be achieved at low cost,
such as by wrapping with permeable cloth.
Two methods were available for air drying the case study timber, either drying
in a protected environment such as a ventilated shed, or drying outdoors. No literature
was available suggesting which would produce the better grade recoveries or pointing
40
to which method would produce higher log residual value. It was assumed that
wrapping of stacks would benefit the drying process and it was decided that both air-
drying methods should be tested in order to compare resulting sawn timber value.
2.10 Price of sawn timber and residual value
Price is one of the main determinants of profitability in an investment analysis.
Because Eucalyptus nitens is not sawn commercially in New Zealand, market
transaction data for sawn timber is not currently available for estimating log value.
Satchell and Turner (2010) used the residual value method for estimating log
values for 18 year old E. regnans in New Zealand from sawn timber products,
because there was not an established market in New Zealand for sawlogs. Board
prices were estimated from those for more commonly available eucalypt species.
In Australia, Innes et al. (2008) utilised the residual value method for
estimating E. nitens plantation profitability using native forest eucalypt sawing and
drying systems. More recently Forestry Tasmania produced a commercial in
confidence report on profitability of plantation E. nitens using the residual value
approach to value sawlogs (Pearn et al., 2013). Price data for similar available species
were used for the appraisals in these studies because E. nitens timber was not yet
available on the market in Australia from which to derive prices.
E. nitens is not a recognised hardwood species in New Zealand timber
markets. Consequently, market prices for products are not available. Issues and
opportunities for pricing E. nitens sawn products are outlined below.
41
2.10.1 Pricing E. nitens sawn timber products
Hardwood solid timber product values have traditionally been linked to grade,
board thickness, width and length (Nolan et al., 2005, p. 7). Innes et al. used product
prices for native regrowth ash eucalypt in assessing the economic viability of
processing plantation E. nitens, with high arbitrary discounts applied to lengths
shorter than 1.8m when pricing E. nitens timber (2008, pp. iv, 9, 10). Another
published Australian study on economic viability of E. nitens solid timber products
discounted board lengths of less than 3m by 10% while boards of less than 1.8 m were
discounted 50% from current hardwood wholesale prices (Washusen, 2011, p. 14). No
basis for these discounts were provided in the reports and no evidence is available to
suggest that the market discounts lengths less than 1.8 m to these levels. Sawn
appearance timber is usually available in New Zealand in random lengths, meaning
that short lengths are mixed with longer lengths in the packet of timber. Although this
suggests that average piece length may be more important to customers than discounts
for shorter lengths, the level to which length influences price for appearance timber
products is not evident in the literature, nor in the market. Arbitrary discounts do not
adequately reflect true market value for the levels of the quality being discounted,
suggesting that empirical methods in use for pricing of quality characteristics in
products new to market could be adopted as an improved method for pricing E. nitens
timber.
In an attempt to produce credible estimates of market prices for the range of
products sawn, market survey methods were developed by Satchell (2015) to estimate
market prices for E. nitens sawn products in the absence of market sales data. These
methods were designed to overcome some of the inadequacies of previous work
examining profitability of growing E. nitens.
42
2.10.2 Market recognition
Plantation E. nitens timber is not currently available, nor marketed in New
Zealand. Plantation ash eucalypt is available inconsistently and only in small
quantities. A recent survey of specialty timber merchants and users by Future Forests
Research (unpublished, 2012) described market recognition and availability of
plantation ash eucalypt in New Zealand as negligible.
A well known and established species in the marketplace tends to hold
consumer preference. This preference generates price premiums and is based on the
perception of suitability for purpose (Nolan et al., 2005, p. 8). Established products
and species can be resilient and hold strong loyalties, while new products may be
accepted only slowly (Nolan et al., 2005, p. 80). For example, hardwood has
traditionally been available in long clear lengths but these are likely to become
increasingly difficult to obtain into the future (Innes et al., 2008, p. iv). Substitution of
long lengths for shorter lengths might meet market resistance because of the
perception that installation costs increase. Market penetration and product acceptance
could be slow, even if end matching of short floorboard lengths offered low
installation costs. Intangible qualities such as reputation could potentially be
estimated as price discounts or premiums. Satchell (2015) surveyed flooring timber
experts in New Zealand and asked them to quantify the influence on price of four
intangible qualities of flooring timber.
2.10.3 Product substitution and price
High quality logs of extant old-growth hardwood timber species are expected
to become increasingly scarce into the future (Sandy Chen & Matt Wood, 2011, p. i).
Although opportunities might arise for product substitution based on demand for old
43
growth timber not being fully supplied, estimating such demand over time would
remain speculative.
Market acceptance, demand and price of a product new to market might best
be predicted by comparing quality with established products and soliciting market
feedback on suitability for purpose.
2.10.4 Product differentiation
Products with quality differentiation tend to hold higher value in the market
along with less price volatility than commodity products (Nolan et al., 2005, p. 80).
Seasoned appearance hardwood products are differentiated and include those used for
decorative structural applications (Nolan et al., 2005, p. 5).
Both physical and appearance characteristics determine whether a species or
product is suitable for a differentiated end-use. Matching wood quality characteristics
with technical requirements for specific timber products would be necessary to offer
quality differentiated E. nitens products (Nolan et al., 2005, p. 91). Physical properties
such as movement in service for appearance products, surface hardness for flooring
products and strength/stiffness for structural products, could each influence market
price of E. nitens timber for the differentiated application. These quality
characteristics could also be compared between species when pricing a product new
to market.
2.10.5 Species comparisons
Innes et al. used product values derived from native regrowth ash eucalypt for
valuing plantation E. nitens timber and considered plantation E. nitens to have the
potential to meet market requirements currently satisfied by Australian native forest
ash eucalypt (Innes et al., 2008, p. iv). Washusen et al. also considered plantation E.
44
nitens timber suitable for meeting market requirements currently satisfied by
Australian native forest ash eucalypt (2008, p. 4). However, Blakemore et al.
considered the appearance of plantation E. nitens timber to vary from Australian
native forest ash eucalypt because of wider annual growth rings (2010, p. 44).
Differences in appearance if quantified as a comparative premium or discount might
provide some credibility to an estimate of price for a new species if empirical
methods were employed. Assessing the effect appearance has on price could involve
market feedback mechanisms: The value individuals place on appearance could be
compared between two species, revealing preference and willingness to pay for the
species being compared.
Beadle et al. suggested that quality and performance of a product new to
market would need to meet or exceed those for the species being substituted (Beadle
et al., 2008, p. 53). It might be more plausible however, to assume that levels of a
quality, if lower in a substitute product, would not meet outright market rejection but
instead be discounted. Surface hardness for Tasmanian plantation E. nitens, at around
4.5 to 5.3 kN (Janka hardness), was considered by Blakemore et al. to be marginal for
flooring applications (2010, p. 44). Consumer preference for a harder species only
means the consumer is willing to pay less for the softer species.
Price premiums or discounts could be measured for different levels of quality
characteristics. Price adjustments from the product being substituted could represent
the different levels in the new product being priced.
Comparisons were used by Satchell (2015) to produce price estimates for E.
nitens as a timber species new to the market. Comparisons were made by survey
respondents for different levels of quality characteristics between species. Price
discounts and premiums were determined for 15 year old E. nitens compared with
45
Victorian ash based on appearance, hardness and movement in service levels.
(Satchell, 2015).
2.10.6 Product profiles
Both grade and size of hardwood appearance sawn products influence their
value to the consumer (Nolan et al., 2005, p. 7). Nolan et al. measured unweighted
average market prices of wholesale eucalypt hardwood flooring product profiles, with
prices measured relative to a benchmark grade, width and thickness (2005, p. 7).
Prices were found to increase with higher grades (i.e. less feature) along with thicker
and wider boards (Nolan et al., 2005, p. 7). Nolan et al. also stated that longer boards
attract a price premium over shorter boards (2005, p. 7) but did not quantify this.
For results of an investment analysis to be credible where the products are not
yet available and sold in the market, methods should attempt to accurately estimate
what buyers in the market would be willing to pay for each product based on grade,
width and length levels.
Quantifying sawn timber revenue from a log requires prices for the full range
of profiles produced. In response to the need for market prices for E. nitens timber to
establish log residual values, Satchell (2015) reported price estimates as discounts and
premiums for levels of width, length and grade quality characteristics for E. nitens
flooring timber.
Satchell (2015) performed a market survey to elicit respondents’ judgements
of price for the E. nitens flooring product profiles. These were represented as
discounts and premiums for the levels of quality characteristics produced in this case
study.
46
Two value-based social survey methods were employed by Satchell (2015) to
price the E. nitens flooring product profiles produced in this case study:
1. Dollar metric pricing of utility and part worth utilities using the graded-pairs
comparison approach.
2. Constant-sum allocation pricing of part-worth utilities.
Both methods are self-explicated stated preference approaches that directly
estimate utilities for each product profile.
Satchell (2015) quantified discounts and premiums for the different levels of
quality characteristics that made up each product profile.
Results were a monetised numeric estimation of maximum acceptable price to
the consumer relative to the given price of a reference product (Monroe, 1990, p.
122). Rather than assuming that E. nitens and Australian ash eucalypt hold equivalent
economic value, by taking differences in appearance, hardness and movement in
service into account, price for E. nitens substitute products were estimated without
market prices being available. By directly comparing quality attributes, including
appearance, Satchell (2015) prompted survey respondents to use normal consumer
behaviour in comparing price and levels of attributes between species and products in
deciding a maximum acceptable price they would be willing to pay for each E. nitens
product.
This case study utilised Satchell’s survey discounts and premiums (2015) for
quality levels to price the E. nitens sawn flooring products in order to estimate log
revenue for both survey pricing methods.
47
2.10.7 Residual value approach for pricing products
The residual value method can be applied to infer price for a product used to
manufacture other products (Kengen, 1997, p. 44). Such indirect pricing offers an
alternative to arbitrary discounts for quality characteristics not readily priced in the
market such as board length. For example, short floorboard lengths could be priced by
estimating the value of a finished floor laid from short lengths, from which
installation costs would be deducted to result in the price for the raw product. By
comparing with a floor laid from long lengths and with a known price, a discount for
the new product could be estimated.
Glue-lamination and finger-jointing of short length appearance hardwood may
offer opportunities for product innovations such as pre-finished laminated parquet
flooring and laminated panels (Shield, 1995, p. 137). Where price for an innovative
manufactured product is not yet available from sales data because it is has not
achieved market penetration, market surveys offer an option for empirically
estimating product prices. By deducting costs for a residual value, products such as
timber ‘shorts’ that are traditionally perceived to be of low value, could then
potentially be priced from the manufactured product.
This study estimated some product values by taking into account innovations
and changes underway in the market because of the long time frames involved with
growing trees and because products and prices establish log residual values.
Product residual value was selected for pricing short floorboard lengths.
Satchell (2015) priced short lengths of solid flooring E. nitens from their appearance
as a finished floor by comparing the appearance with a floor made from longer
lengths and asking survey respondents to judge utility. Costs of producing and
48
installing end-jointed and end-matched product were estimated and subtracted for
residual product values for two levels of short lengths.
Product residual value was selected for pricing case study boards of widths too
narrow for standard flooring but suitable for laminating into panels (75 mm and 50
mm widths). Sample panels were produced and sold and production costs were
quantified.
2.11 Conclusions
The literature reviewed in this chapter indicates that any study that seeks to
estimate profitability of growing E. nitens for solid timber products needs to consider
a wide number of factors. While the concept of residual value is straightforward, its
application to the process of sawing and producing timber products necessitates the
consideration of many factors, including the application of best practice sawmilling
and drying methods for converting logs into sawn timber products.
Important components identified in the literature review relating to residual
value include: Processing costs, grade recoveries and defect levels, log diameter, log
position, checking, collapse, end-splits and movement. The literature also shows
factors that have the potential to improve residual value and profitability such as
application of best-practice silvicultural methods, best-practice sawmill and drying
methods and selection of highest-value products to saw. These factors and their
influence on residual value will inevitably change as improvements are made over
time.
The general research objective of this study is to estimate the profitability of
growing E. nitens for solid timber products as a case study. The case study was a
small woodlot of well managed E. nitens, grown for 15 years, pruned to 6.5 m and
49
thinned for solid timber production. To achieve this general objective, methods were
also developed that could be applied consistently in future studies assessing log
residual value for E. nitens.
Taking into account the findings of the literature review suggests the
following specific research questions:
1. What is the estimated residual value and resulting net present value for E.
nitens in this case study?
2. What is the impact of degrade and defect on sawn timber value?
3. Is it likely to be profitable to grow E. nitens under the case study scenario?
4. What effect does drying method have on wood product quality and value?
5. Does log position in the tree affect wood product quality, and if so, case study
log residual value?
6. Does log diameter affect processing costs and sawn timber value, and if so,
case study log residual value?
A design to address these research questions was developed and the key
features of the design are:
• To apply sawmilling method as practiced in Satchell and Turner (2010) , with
3 m long lengths sawn soon after cross cutting to length to minimise defect
from end splits and sawn to 28 mm thickness;
• to apply best practice drying methods to reduce levels of checking as much as
practicable;
• to quantify levels of checks on unreconditioned profiled surfaces and examine
their impact on sawn timber value;
50
• to assess the economic impact of steam reconditioning on log residual value.
• to trial two methods of air drying that offer different costs to compare the
outcomes in economic terms. The study compared air drying outdoors with the
more expensive option of air drying indoors in a ventilated drying shed;
• selection of products to saw that represented the least risk and greatest value.
Solid timber strip flooring was selected as the target product for processing
from case study logs for the purpose of determining log residual value. This
was assumed to be the most marketable and least risky product to produce and
price. The market for solid strip flooring is negligible for flooring board
widths under 100 mm, so the product selected for 75 mm and 50 mm board
widths was laminated appearance panels;
• selection of methods for pricing final products that represented how the
market would value these. Prices for products produced in this research were
identified as an important component that determines economic viability of
growing E. nitens for sawn timber. Methods for pricing product profiles as
accurately as possible were identified and selected for estimating prices for
sawn products. These were discounts and premiums according to product
profiles for both the graded pairs and constant sum allocation methods
reported by Satchell (2015), modified for short timber lengths as residual
product values in the graded-pairs method. Panel laminating stock was priced
according to residual product values.
The next chapter considers in detail how this study design was put into
practice.
51
Chapter 3
Methods
3.1 Introduction
Methods for processing logs into sawn product were required that minimised
degrade, minimised costs and maximised grade recoveries to represent current
industry best practice in converting E. nitens logs into profiled timber products. Prices
for grade profiles were required in order to estimate sawn timber revenue for each
sample log, as were detailed costs for each production process.
The methods chapter is divided into:
1. Methods to estimate sawlog volumes from the case study stand in order to
estimate per-hectare volumes according to log categories, including sawlogs
as diameters and according to log position, along with volumes of
pulpwood/firewood logs.
2. Methods for processing logs and estimating production costs.
3. Methods for quantifying and categorising sawn timber grade recoveries and
defect.
4. Methods of assessing and analysing log physical properties.
5. Methods for assessing costs for growing, harvesting and processing of logs.
6. Testing two drying methods and comparing the results between these.
7. Methods for estimating sawn timber revenues.
8. Methods for calculating residual log value and cash flows for the case study.
9. Scope and limitations for the case study.
52
3.2 Case Study Trees
The case study comprised a small stand of 55 E. nitens trees in two distinct but
immediately adjacent areas, that were planted by farm forester Patrick Milne near
Rangiora on a reasonably well drained but moist fertile Canterbury plains site
exposed to the west. These trees were planted at 3 m x 3 m spacing and were pruned
and thinned in expectation of solid timber production. The trees were 15 years old at
harvest. All trees in the case study stand were measured for diameter at breast height
(DBH) and height. Height measurements were recorded with a vertex III hypsometer.
The exact position of each tree in the stand was mapped (see Appendix B).
3.2.1 Inventory and plots
Because the case study stand was not a contiguous area of trees, two plots,
each 28 m x 8 m, were placed on the scale diagram to avoid edge trees and to provide
plots that held representative stockings for a larger hypothetical stand (Appendix B).
An inventory of tree heights and tree diameters at breast height over bark (DBHOB)
was produced from these two plots. Values for the two plots were averaged.
A Volume and Taper Equation for New Zealand Grown Eucalyptus nitens
(Gordon, Hay, & Milne, 1990) provided volume and taper equations used for
estimating plot log volumes, stem volumes and estimates of log SEDs. Log volumes
and diameters were estimated from 0.3 m upward based on 3 m log lengths.
Logs were allocated to categories according to small-end diameter under bark
(SEDUB):
• Waste = 0-10cm;
• pulp logs = 10-25cm; and
• sawlogs > 25cm.
53
Logs 1 and 2 from every tree were also classified as ‘pruned buttlog’. Logs
above 3 were classed as ‘unpruned headlog’.
Average plot tree numbers were scaled to a per hectare value, along with basal
area, stem volumes, average diameters (DBHOB).
3.2.2 Case study logs
Trees harvested for sawmilling were selected to avoid edge trees and to
represent the range of diameters present inside the stand. The other selection criteria
requested by the owner was to production thin in order to evenly open up the stand
and encourage further growth in remaining trees. This did not involve any specific
selection criteria except that trees were harvested from throughout the stand and
represented the full range of diameters. Trees were harvested manually using a
chainsaw and logs were immediately cross cut to 3 m lengths. Tree and log position
numbers were marked on the logs and these were loaded onto a self-loading truck.
Each of three log loads were weighed at a weighbridge and gross weight recorded.
The empty truck was also weighed and total log weight calculated. Log specifications
were to cross cut to a small end diameter of 25cm, however these were in most cases
cut to 30 cm. Trees were reported as pruned to approximately 6.5 m, therefore the
first two logs were classified as pruned buttlogs and above log two were classified as
unpruned headlogs. No more than five logs were extracted from any one tree. Eight
trees were harvested from which thirty-two sample logs were milled.
Each log was painted on both ends with a base colour to represent the tree.
Log positions were represented with a matrix of dots painted over the base colour
with different colours representing each log position.
54
Logs were not debarked prior to sawmilling. The ends of each log were
measured soon after cross cutting. Due to the oval nature of many of the logs,
diameter was measured twice at each end from two perpendicular positions. These
two measurements were averaged to produce an estimate for each end diameter. The
log volume was then estimated using Smalian’s formula.
Individual sample log volumes were summed for a total sample log volume.
3.2.3 Volumes and weights
Tare was deducted from gross weight of each truckload and net weights were
summed for total weight of sawlogs.
Total volume for logs was calculated by summing the volume of each log.
Average green density per log cubic metre was calculated by dividing total weight for
the logs by their total volume.
Slabwood was reloaded on the truck after sawmilling was completed and this
was weighed four days after completion of sawmilling.
Board green weight was calculated by multiplying board green volume by
weight per cubic metre.
Sawdust weight was assumed to be the difference between total weight and
board weight plus slabwood weight.
3.3 Sawmilling
All logs were milled within five days of harvesting. This time frame was
considered to be adequate to minimise defect in boards caused by end splits, but
realistic for operational implementation. Although end-splits became evident on log
ends over this time these were not severe in any logs.
55
Sawmilling took place on 29 November 2012 to 2 December 2012.
All logs were milled using exactly the same pattern (see Appendix C).
Slabbing was undertaken with a Woodmizer LT 40 horizontal bandsaw with a 3mm
kerf. Logs were first cut through the pith after raising the log small end so the pith
was parallel with the bed. Where necessary, measurements were taken from the bed to
ensure the pith was level before making the first cut. Immediately after the first cut
was made, measurements of deflection were taken at each end of the log and
averaged. The log was kept intact and the two halves together turned 90 degrees.
Again the small end was raised so the pith was level with the bed. The log was then
slabbed at 28 mm thickness with each pair of slabs removed from the log on the
return of the saw head. These dropped directly onto rollers that stockpiled slabs
beside the Woodmizer twin-blade edger. Once approximately half of the log was
removed as slabs, the two remaining cants were rotated 180 degrees and slabbed to
the bed.
The Woodmizer twin blade edger operated simultaneously with the bandsaw
for an efficient workflow so that as slabs were fed to the edger from the bandsaw
these were edged. A separate operator ran the edger who both edged slabs and fillet
stacked edged boards. Fillets were dry E. nitens with a thickness of 19mm and width
of 25mm. Seven fillets were placed at 0.5m distances apart over each layer of boards
and directly above the previous row of fillets, including at both ends of the stack. For
each log, the time it took to slab, from loading the log on to the bed to the completion
of slabbing, was measured in minutes. The stockpile of slabs waiting to be edged was
observed to not increase during the slabbing process for each log and thus it was
decided that recording the time the second operator was edging and stacking was not
necessary, this being equal to the time recorded for slabbing.
56
Boards were edged to the following green widths:
• 150 mm nominal = 165 mm green
• 125 mm nominal = 133 mm green
• 100 mm nominal = 108 mm green
• 75 mm nominal = 82.5 mm green
• 50 mm nominal = 57 mm green
Units of electricity and fuel were recorded per hour of operation along with
prices for these (see Appendix A5).
Edging was based on judgement calls aimed at optimising value in preference
to volume. This ‘grade sawing’ was undertaken by eye with no laser guidance. Slabs
were first flipped and degrade was visually assessed on both faces prior to a decision
on target board width and where to edge the slab for maximum value recovery. The
pith was always removed and judgement calls were made on how much of the knotty
core would be removed. The edge closest to the periphery was usually removed as
close to the periphery as possible. The Woodmizer twin-blade edger uses rollers to
feed the slab through two circular saw blades, producing straight parallel edges at the
width set by the operator. The slab is presented to the rollers freestyle with no fence
for guidance.
The corewood was observed to have a contrasting colour to the surrounding
sound wood when freshly sawn and was only present adjacent to the pith in
quartersawn slabs containing central wood. In pruned logs this was always contained
inside the pruning wounds. Unpruned logs had a corewood zone of similar size, but
with knots extended outside of this. Where possible, corewood adjacent to the pith
57
was edged out from slabs, regardless of whether the corewood was from pruned or
unpruned logs.
3.4 Timber Drying
Fresh sawn boards were each randomly allocated to two stacks for the drying
experiment. Stacks were assembled on pallets designed for drying timber that
provided airflow underneath, the first layer of sawn timber positioned 15cm from the
ground or the stack below. These two stacks were shifted by forklift immediately on
completion of sawmilling.
Both stacks were wrapped with a single layer of microclima cloth, a semi-
permeable white-coloured cloth used for reducing air flow through the stack. A single
1800 kg concrete slab was placed on top of each stack to weight it.
One stack (the ‘yard drying’ treatment) was positioned outdoors in the drying
yard adjacent to the sawmill, sheltered from prevailing winds and on compacted
gravel. This stack was positioned between two other timber stacks each of
approximately equal height, with a 30 cm gap between stacks to limit air movement.
The two ends were open to air movement with no adjacent stacks present. Positioning
of stacks simulated a production situation where stacks would be held in reasonably
close proximity.
The other stack was positioned inside a drying shed with a concrete floor,
corrugated iron roof and slatted walls. The slats covered half the wall area and were
installed to limit air flow through the shed. The stack was wrapped with a single layer
of microclima cloth and a single 1800 kg concrete slab was placed on top of the stack
to weight it.
58
Both stacks were air dried for 4 months. On April 20th 2013 ten randomly
selected boards on the outside of the stacks were measured for moisture content with
a Trotec T500 Multi-board Measure Professional resistance method hand-held
moisture-measuring instrument. This averaged 19.9% for the shed dried material and
18.73% for the yard dried material. Although it was decided the timber was dry
enough to finish drying in the Solarola solar kiln at this point, because of unrelated
production constraints the timber was not transferred into the kiln until 20 October
2013. Both stacks were positioned in the kiln as a single charge. The timber stacks
were removed from the kiln on 19 November and placed in a fully enclosed concrete
floored shed used for storing dry timber.
Steam reconditioning was not performed on the timber.
Boards were measured for moisture content immediately prior to dressing
(blanking and profiling) using a Trotec T500 Multi-board Measure Professional
resistance method hand-held moisture-measuring instrument. Ten randomly selected
boards from both stacks were tested for moisture content, which averaged 12.6%.
This moisture content was deemed appropriate for dressing and grading the timber.
3.5 Timber Processing
The nominal 100 mm, 125 mm and 150 mm timber was dressed in two stages,
blanking then profiling. Blanking took place on 20th and 21st November 2013 through
a Logosol PH 260 four sider to 23 mm thickness and widths to the dimensions in
Table 1.
All boards were dressed straight using a straight edge fence. Any crook was
edged out by feeding boards through the machine with the concave edge against the
fence, removing all crook at the risk of causing skip. Where crook was anticipated to
59
be excessive and likely to result in loss of value as edge skip when profiled, the board
was docked to provide shorter lengths for dressing straight. Where knots were
observed to cause board distortion, the knot was docked out of the board prior to it
being dressed.
Table 1
Nominal and Dressed Board Widths
Board Nominal Width (mm)
Blanked Width (mm)
Profiled Width (mm)
150
155
128
125
125
109
100
96
83
75
72
--
50
48
--
Blanked boards of nominal sizes 100mm, 125mm and 150mm were dressed
with a second pass into tongue and groove flooring profile at 19 mm thickness. Each
blanked board was evaluated and a decision made on how to feed into the machine,
based on levels of surface checking and collapse depth on both faces in an attempt to
profile the best surface to the top (exposed) surface of the board. Where possible,
excessive collapse or checking on the blanked board was turned down to the bottom
face.
Blanked boards of nominal sizes 50mm and 75mm were not dressed further
into profile.
3.6 Grading Procedure and Data Inventory
Grading was undertaken in February 2014. Boards were measured for
moisture content immediately prior to grading using a Trotec T500 Multi-board
Measure Professional resistance method hand-held moisture-measuring instrument.
60
Ten randomly selected boards from both stacks were tested for moisture content,
which averaged 11.75%.
Grading judgement calls took into account the value trade-off between
predetermined value assumptions for grade and piece length (see Chapter 3.7). Board
positions were marked where the board would be docked. Where possible timber was
"docked" to achieve lengths that met equivalent grades under both sets of grading
rules being employed.
For every board the following data was recorded:
• Board number;
• tree number;
• log number;
• drying treatment category;
• board nominal width;
• percentage of board length with checks present on the profiled surface;
• sum of length of checks present on the profiled surface; and
• end taper.
Individual boards were marked with a pencil into pieces, then each piece
length measured and categorised. Each piece length was allocated to a grade or defect
category. Grade and defect categories related to the width of the timber being graded
and the grade rules being employed.
3.7 Grading
Grading of boards was undertaken using two sets of rules, Australian
Standards AS 2796.2 – 2006 (AS) and Farm Forestry Timbers (FFT) grades as
published in Grade Revision 1.1 October 2013 (NZFFA, 2013).
61
Nominal 75 mm and 50 mm width boards were graded to Farm Forestry
Timbers Standards but not to Australian Standards. Profiled nominal 100 mm, 125
mm and 150 mm board lengths were graded to both Australian Standards and Farm
Forestry Timbers Standards.
Grading method was assumed to not influence price, with FFT Flooring clears
grade holding the same value as AS select grade, FFT Flooring standard grade
holding the same value as AS standard grade and FFT Flooring feature grade holding
the same value as AS high feature grade.
3.7.1 Grading assumptions
Grading was undertaken based on the following assumptions:
• FFT Flooring overlay is worth 90% of FFT Flooring over-joist grade with
the same length and width dimensions.
• Flooring product of 900mm - 1200 mm length is worth 90% of the price of
>1200 mm flooring per lineal metre of the same grade and width.
• Flooring product of 600mm - 900mm length is worth 75% of the price of
>1200 mm flooring per lineal metre of the same grade and width.
• Flooring product of 300 - 600 mm length is worth 25% of the price of
>1200 mm flooring per lineal metre of the same grade and width.
• 125 mm flooring is worth 75% of the price of 150 mm flooring for the same
grade and length.
• 100 mm flooring is worth 60% of the price of 150 mm flooring for the same
grade and length.
• Standard grade is worth 80% of the price of select or clears grade of the
same width and length.
62
• AS high feature grade is worth 50% of the price of AS select grade of the
same width and length.
• FFT Flooring feature grade is worth 50% of the price of FFT Flooring clears
grade of the same width and length.
• FFT Panel Laminating grade with length of 300 mm - 1500 mm is worth
50% of the price of >1500 mm length per lineal metre of the same width and
grade.
• FFT Panel Laminating grade with four faces clear is worth the same by
nominal volume as 150 mm wide FFT Flooring clears grade of the same
length.
• FFT Panel Laminating grade with two faces/edges clear is worth 80% of the
price of FFT Panel Laminating grade with four faces clear and of the same
length and width.
• FFT Panel Laminating grade with one edge clear is worth 70% of the price
of FFT Panel Laminating grade with four faces clear and of the same length
and width.
3.7.2 Grading flooring product to Australian standards
Profiled nominal 100 mm, 125 mm and 150 mm width boards were graded to
Australian Standards 2796.2 – 2006.
3.7.2.1 Defect categories for board pieces
Defect piece lengths were recorded in the following categories:
• End splits defect;
• box defect (Natural feature such as knots that do not meet grade
requirements);
63
• collapse defect (skip);
• skip from wane;
• skip from cupping, twist);
• machining voids and want;
• excessive checks defect;
• tongue defect resulting from straightening out crook from boards;
• tongue defect resulting from collapse shrinkage; and
• piece length within each grade and length category combination.
3.7.2.2 Grade categories for board pieces
Graded piece lengths were recorded and categorised according to the
following grades:
1. Select;
2. standard; and
3. high feature.
3.7.2.3 Piece length categories
Graded piece lengths were recorded in the following length categories:
• 300 mm – 600 mm;
• 600 mm – 1200 mm; and
• > 1200 mm.
3.7.3 Grading flooring product to Farm Forestry Timbers standards
Profiled nominal 100 mm, 125 mm and 150 mm width boards were graded to
FFT Flooring grades as published in grade revision 1.1 October 2013.
64
3.7.3.1 Defect categories for board pieces
Defect piece lengths were recorded in the following categories:
• End splits defect;
• box defect (natural feature such as knots that do not meet grade
requirements);
• collapse defect (skip);
• skip from wane;
• skip from cupping, twist;
• machining voids and want;
• excessive checks defect;
• grade category for each piece meeting a grade category (clears over joists,
standard over joists, feature over joists, clears overlay, standard overlay,
feature overlay); and
• piece length for each grade and length category.
3.7.3.2 Grade categories for board pieces
Graded piece lengths were recorded and categorised according to the
following grades:
• Clears over joists;
• standard over joists;
• feature over joists;
• clears overlay;
• standard overlay; and
• feature overlay.
65
3.7.3.3 Piece length categories
Graded piece lengths were recorded in the following length categories:
• 300 mm – 600 mm;
• 600 mm – 1200 mm; and
• > 1200 mm.
3.7.4 Grading of 50 mm and 75 mm nominal width boards
Blanked nominal 75 mm and 50 mm width boards were graded to either FFT
Panel Laminating grade as published in Grade revision 1.1 October 2013 or FFT
Joinery grade as published in Grade revision 1.1 October 2013.
Grade estimates were made based on expected defect upon final profiling.
Levels of checking and natural feature were not altered but skip was measured and an
estimate was made of its expected presence or absence on the profiled surface.
Sample boards were later dressed to profile immediately prior to laminating into
panels because freshly planed surfaces were required for glue adhesion.
3.7.5 Grade interpretations and modifications
Concealed surfaces were graded to meet the structural conditions in both AS
grades and FFT Over-joist grades.
Modifications to grade rules for the purposes of this study:
• AS select grade was downgraded to standard grade where checks were
present.
• Box included clear short lengths under 30 cm.
• End splits included end checks.
66
Where wane or skip was present on concealed surfaces this was deemed
acceptable provided it did not affect the stability of the boards or the tongue or groove
connection.
Where two or more defects were present on a piece to be graded, defects held
predetermined priorities. The following category priorities applied:
• End taper held priority over end splits or any other defect.
• End splits held priority over box, skip and other defect.
• Box held priority over skip and excessive checks.
• Excessive checks held priority over collapse defect.
End taper was not categorised as defect, but instead was deducted from green
sawn timber recovery and board lengths to be graded. Where end taper could not be
distinguished from skip caused by collapse, a judgment call was made and one
category selected. Where end taper could not be distinguished from taper caused by
machining out crook, a judgment call was made and one category selected.
Where structural requirements for AS grades were not met on concealed
surfaces the board or board piece was classed as box defect.
Where structural requirements for FFT Flooring graded over joists were not
met on concealed surfaces, the board or board piece was either classed as FFT
Flooring overlay or as box defect.
3.7.6 Defect groups
Defect was also divided into two groups:
1. Natural defect:
67
• Shakes or decay, knots, holes, encased bark, decay, kino and other natural
feature that did not meet grade rules (box).
2. Potentially avoidable defect:
• End splits;
• pith;
• mechanical damage (want);
• wane;
• skip resulting from collapse;
• skip resulting from cupping; and
• severe checking that did not meet grade rules.
3.7.7 Collapse
Collapse defect was recorded where exposed as skip on the profiled surface.
Excessive collapse on the edges of boards was classed as defect where this
would result in a weak tongue/groove connection under FFT grade rules. AS grade
requirements were specific for tongue and groove connections and levels of skip
allowed in tongues and grooves.
Collapse was allowed on the bottom surface of the flooring product where this
did not make the board unstable. Both edges of the bottom surface were required to be
free of skip.
Collapse skip was estimated on the profiled surface of panel laminating boards
because these were graded as a blanked product.
68
3.7.8 Checks
Boards or board pieces with levels of checks that did not meet grade rules
were classed as excessive checks defect.
Checking on concealed surfaces was not measured.
Because grading of boards did not explicitly quantify levels of checking in
boards, levels of checks were also measured on profiled exposed surfaces as:
• Percentage of the board length with checks present on the surface cross
section perpendicular to the edge.
• Lengths of individual checks, measured over the whole board length (3m)
and summed, then averaged per lineal metre.
A check score for each board was then calculated as the average between:
• the percentage of the board’s length with checks present; and
• the sum of check lengths per lineal metre.
3.7.8.1 Check score as percentage of log volume
Log volume with checks present was calculated by summing individual board
volumes with checks present from that log. The percentage of the log with checks
present was then calculated by dividing the total board volume from the log by the
volume with checks present.
Summed lengths of individual checks per metre were weighted by volume and
summed for each board in the log. Total board volume for the log was divided by this
quantity for a percentage value representing lengths of checks in that log.
The percentage values for checks present in the log and lengths of checks in
the log were averaged for a check score as a percentage of the log.
69
3.7.9 Grading to reflect no collapse
Grading was also performed to simulate product grades as if the boards had
been steam reconditioned to recover collapse. Where skip caused by collapse was
present this was ignored and grade recoveries were adjusted to reflect the scenario
where steam reconditioning would have eliminated collapse defect in profiled boards.
For AS grades ignoring collapse, the following data was recorded for every
100 mm, 125 mm and 150 mm board in addition to that recorded for AS grades:
• Tongue defect resulting from straightening crook;
• tongue defect resulting from collapse shrinkage;
• adjusted collapse defect;
• grade category for each piece (select, standard and high feature); and
• individual piece lengths (300 mm – 600 mm, 600 mm – 900 mm, 900 mm –
1200 mm, > 1200 mm.
For FFT grades ignoring collapse, the following data was recorded for every
board in addition to that recorded for FFT grades:
• Adjusted collapse defect;
• grade category for each piece (clears, standard and feature); and
• individual piece lengths (300 mm – 600 mm, 600 mm – 900 mm, 900 mm –
1200 mm and > 1200 mm.
3.8 Methods for Assessing Production Costs
Sawmill, drying and processing costs per sawn cubic metre are summarised in
Chapter 4.2.5. Methods for estimating processing costs are presented below.
70
3.8.1 Harvesting costs
Harvesting and logging costs were based on those provided in the Laurie
Forestry Ltd Canterbury pricing table (see Appendix A1).
3.8.2 Labour
Labour was classified into two categories, primary and secondary labour.
Primary labour was priced higher on the assumption that this person holds
responsibility and the secondary labour would hold a support role.
Labour costs were calculated per hour and summed for the labour units
participating in an operation (see Appendix A5).
Labour rates were gross per hour including holiday pay. Time for repairs and
maintenance was recorded in addition to sawmilling time.
3.8.3 Sawmill costs
Sawmill costs were all converted into per hour costs, except log handling
costs, which were estimated per log. Log handling costs included loading the log onto
the sawmill bed but not positioning the log on the bed. Positioning the log on the bed
and clamping in place were recorded within sawmilling time. Sawmill costs are
presented in Appendix A5.
3.8.4 Sawmill asset costs
Purchase prices for equipment were obtained from John Fairweather Specialty
Timbers, the case study operation. These were allocated annual straight line
depreciation rates as per the operation’s accounts. Annual rental costs for equipment
were quantified from depreciation plus interest on capital. Interest rate was set as the
71
discount rate used in the discounted cash flow analysis of costs and returns (See
Appendix A5).
Costs for sawmill yard were calculated as a rental per hour plus additional
costs for repairs and maintenance. Rental costs were converted to an hourly rental
cost by dividing annual cost by estimated annual operating hours (See Appendix A5).
3.8.5 Sawmill operating costs
Sawmilling time was recorded per log based on length of time for the
Woodmizer bandsaw to slab the log, including positioning of the log on the bed. Log
handling costs were recorded separately, as were the cost of band changes.
Two labour units (primary and secondary labour) were recorded as costs for
sawmilling, each labour unit operating separate equipment (the bandsaw and edger).
Electricity and fuel were priced per unit. Units consumed were measured for
one operating hour. Electricity and fuel costs were calculated per hour by multiplying
unit price by units consumed per operating hour.
Woodmizer bands were costed per hour based on $60 for the band, with five
sharpens before replacement and two hours service between sharpening.
Band sharpening costs were estimated per hour.
Edger blade costs were estimated based on 1000 operating hours between
sharpens and one hour to sharpen for the primary labour unit.
Band changes were estimated to take four minutes, once every two hours for
the primary labour unit. This cost was additional to actual sawmilling times recorded
for each log and assumes the secondary labour unit would continue with edging
during this period.
72
Hourly costs were converted to per log costs based on time measured to
sawmill each log.
Annual costs were allocated to individual logs by assuming 1832 working
hours per annum, then converting annual costs to hourly costs. Annual costs included:
• Costs for capital depreciation;
• interest (return on investment); and
• maintenance.
Interest was set as the discount rate. For depreciation rates see Appendix A5.
The sawmill site was converted to an annual expense by estimating the interest
payable on the capital value for the land area used (1/4 hectare) as a proportion of the
total land holding, plus the rates payable for the area of land used as a proportion of
the total land holding. See Appendix A5 for details on sawmill operating costs.
Sawmilling cost per nominal sawn cubic metre of production (not including log cost)
for each log is presented in Figure 5.
3.8.6 Timber drying costs
Drying costs were estimated per nominal sawn cubic metre of timber, for both
yard and shed drying. Log residual values were estimated based on yard drying
because this was the less expensive option and the results of the drying experiment
(see Chapter 4.3) revealed that no significant differences in quality were evident.
Costs recorded included:
• Shifting the filleted stack from the sawmill into position in the drying yard
and replacing the drying pallet beside the sawmill, measured as time for one
73
labour unit to complete the task, then converted to a cost per sawn cubic
metre;
• stack preparation (weighting and wrapping), measured as time for one
labour unit to complete the task, then converted to a cost per sawn cubic
metre;
• drying space as a rental for one year based on setup costs for compacted
gravel;
• repairs and maintenance of the drying yard;
• cost of fillets, pallets and concrete weights as a rental;
• cost of microclima wrapping cloth;
• solar kiln;
• site rental (based on capacity of the solar kiln); and
• forklift.
Site rental was calculated from the interest amount payable on the value of 0.5
hectares of land, plus land rates payable per hectare of land. Interest rate was set as
the discount rate used in the discounted cash flow analysis of costs and returns in this
study. Site rental as a cost per nominal sawn cubic metre of stack was then calculated
from the annual kiln capacity, and assuming each stack would be in place in the
drying yard for one year.
Drying space for yard drying was calculated as the capital expenditure for
constructing a level gravel foundation, as a depreciation expense for the space
required for one cubic metre of timber as a filleted stack for one year.
74
Drying space for shed drying was calculated as the capital expenditure for
constructing a drying shed, as a depreciation expense for the space required for one
cubic metre of timber as a filleted stack for one year.
Drying costs per nominal sawn cubic metre were summed and converted to a
cost per log based on the nominal sawn production from each log.
Timber drying costs are presented in Appendix A6.
3.8.7 Timber processing costs
Processing costs were estimated per nominal sawn cubic metre of timber, per
hour and per board lineal metre.
Costs recorded included:
• Shifting the stack into the processing shed (as a cost per cubic metre);
• labour, blanking (as a cost per lineal metre);
• labour, profiling (as a cost per lineal metre);
• labour, grading and docking (as a cost per lineal metre);
• labour, restacking (as a cost per lineal metre);
• despatch and product preparation (as a cost per lineal metre),
• knives, sharpening (as a cost per cubic metre);
• electricity (as a cost per hour and as a cost per lineal metre); and
• boron treatment (as a cost per cubic metre).
Boron treatment was not undertaken but the cost of this per cubic metre was
estimated and included for producing timber that meets market requirements.
Per cubic metre processing costs were converted to lineal metre costs for each
board width. Cost for blanking and profiling did not vary for different board widths
75
because this was based on a rate per lineal metre fed through the machine. Machining
costs were then calculated per log based on the lineal metres of sawn timber produced
from the log.
Timber processing costs are presented in Appendix A7.
3.8.8 Steam reconditioning scenario
Under this scenario steam reconditioning was assumed to have taken place.
The additional cost of steam reconditioning (see Appendix A6) was included as a
processing cost and defect from collapse was assumed to not be present on profiled,
graded surfaces.
3.8.9 Marketing, management and overhead cost
Marketing, management and overhead cost for the case study processing
operation was specified as 10% of sawn timber revenue. This cost represents profit
for the processing operation in addition to return on investment.
3.9 Drying Experiment
If drying outdoors produced no more drying degrade than shed drying, this
would be the preferable method in economic terms because of lower costs. An
experiment was designed to compare these two methods to determine best practice as
an economic analysis.
This study design was:
• For slow air drying from green with finishing in a solar kiln;
• to wrap stacks with permeable cloth to slow air flow through the stacks; and
• to compare sawn timber value from shed air drying with outdoors air drying.
76
Board prices resulting from two different drying methods, air drying outdoors
and air drying in a drying shed, were compared. Board grade recoveries could not be
directly compared because grading decisions are based on judgement calls that
consider the value compromise between shorter lengths of higher grades and longer
lengths of lower grades.
Individual board prices were calculated by summing the prices for each piece
within the board that met a grade. Pieces were priced according to the length of the
piece multiplied by the price of the profile allocated to the piece. The price for each
profile was determined by the grade, length and width categories.
Grading of boards was undertaken before board profiles were priced from
survey results. Therefore, arbitrary discounts and premiums for board profiles were
set in advance of grading, on which grading judgement calls were based.
3.9.1 Board prices used for drying experiment
Price discounts were set for board profiles based on a reference profile of
select grade, 150 mm width, > 1.2 m length. Price discounts were applied to board
lengths, widths and grades according to the assumptions used for grading the boards
(Chapter 3.7.1).
Discounts for each profile were summed from discounts for each characteristic
level present in the profile. The discount was then applied to the profile, revealing a
price per lineal metre for that profile.
3.9.2 Statistical analysis
Individual board prices were compared between the two drying treatments and
according to tree and log position. The R statistical software package was used for
77
analysis of variance (ANOVA). Because log position within tree is not a random
variable a mixed effects model was applied to determine probability of rejecting the
null hypothesis that there was no difference between drying treatments.
3.10 Revenues
Revenues were estimated for each sample log processed. Because sales data
was not available for E. nitens products in order to estimate revenues used for
calculating log residual value, an alternative approach was taken to estimate product
prices.
3.10.1 Sawn timber revenues
Satchell (2015) reported price discounts and premiums for levels of quality
characteristics corresponding to the same flooring timber categories that sawn timber
from this study was graded into. These discounts and premiums were aggregated into
prices per lineal metre of sawn timber, presented in Appendix D (Table 35 and Table
36). For sawn lengths less than 1.2 m, graded pairs comparison prices were further
discounted for residual product values as:
• The cost of end-jointing for 30 cm - 60 cm lengths (see Appendix A7); or
• the cost of end-matching for 60 cm - 120 cm lengths (See Appendix A7).
This produced product residual values for boards less than 1.2 m length for the
graded-pairs pricing method.
3.10.2 Product residual values - laminated panels
Two laminated panels were produced to generate residual value price
estimates for the 50 mm and 75 mm wide timber feedstock graded to FFT panel-
laminated and FFT joinery grades. Nominal 75 mm boards were laminated according
78
to the grades allocated to the blanked surfaces and the two length categories. Grading
was to Farm Forestry Timbers (FFT) panel laminating grade clear one face as
published in Grade revision 1.1 October 2013.
One 3 m long panel was made from 3 m lengths graded to clear one face (i.e.
with no buttjoins in the panel). Thirty-eight full length (3m) blanked nominal 75mm
width boards graded to clear one face were marked on one end for the graded clear
edge and the best end. The intention was to produce a panel with the clear edge on the
exposed surface and with one end suitable for a defect-free appearance application.
The other 3 m long panel was made from 300 mm - 1500 mm lengths graded
to clear one face (i.e. with buttjoins exposed on the surface of the panel) and with the
clear edge marked for the exposed surface. The intention was to produce a lower
quality panel with a defect-free “clears” surface suitable for appearance applications
but with exposed joints on the surface.
The two panels were assembled by A. J. Wang, Christchurch. The boards were
dressed from 23 mm to 19 mm thickness and immediately glue-laminated into panels
according to the marks provided. The panels were sanded on both faces and two
panels were produced, each of 60 mm thickness. The panel made from 3 m lengths
was finished to 730 mm width and the panel made from short lengths was finished to
560 mm width.
Both panels were then coated with sanding sealer and sold.
Costs for preparing and laminating the panels were quantified for each panel
(See Appendix A3). The panels were sold to determine market prices for the two
panel products, each of different quality. Board prices were then calculated as a
79
residual value by subtracting costs from sale price and converting net revenue to a
per-lineal metre for the input timber product.
In calculating residual values for panels, price was assumed to not vary per
product cubic metre between panels of finished 60 mm and 40 mm thickness, nor
according to panel width. Price for FFT panel laminating clear two faces grade and
FFT Joinery clears grade was assumed to be the same as for FFT panel laminating
clear one face grade.
Prices for 75 mm and 50 mm width boards were calculated as residual values
from the sales prices of laminated panels and the costs of producing these. These
prices are presented in Appendix D (Table 37).
3.10.3 Sample log sawn timber revenue
Board piece prices were calculated by multiplying each graded board piece
length by the price allocated to its profile per lineal metre. These board piece
monetary values were then summed for the resulting board price. Sawn timber
revenue for each sample sawlog was calculated by summing board price estimates for
each log.
3.10.4 Secondary product revenues
Prices for sawdust and slab firewood were estimated as sawmill gate sales (see
Appendix A2). Quantities from sample logs were estimated as percentages of total log
volume.
3.11 Predicting Plot Log Costs and Revenues
The R statistical software package was used for predicting plot log costs and
revenues from the sample log values. A linear mixed effects model was fitted using
80
the lme class to take into account that log position number is not random. Where
percentages were the response variable these were normalised using arcsine
transformation. A quadratic (second degree) polynomial linear mixed effects model
provided a better fit than a straight linear model to explain nominal sawn recovery
according to SED, sawmilling cost per nominal sawn cubic metre of production
according to SED, sawmilling costs per log cubic metre and yard drying costs per log
cubic metre.
Where sawn timber revenues and sawn timber residual values were not
significantly different to the 5% significance level, the average value was used.
3.12 Cash Flows
The discount rate was set as 8.5% and this was also the rate of return on
processing capital. All costs and revenues were discounted to year 0 for a Net Present
Value (NPV).
3.12.1 Grower revenues
Pulpwood/firewood log sales occurred at the time of harvest (15 years from
planting).
Slab firewood and sawdust sales occurred at year 16.
Sawn timber revenue occurred at year 16.
3.12.2 Growing and harvesting costs
Site preparation, plant stock and planting costs were recorded for year 0,
releasing costs year 1, pruning costs year 3 and year 5, and thinning costs year 10.
Land rental and annual growing costs were recorded for year 1 through to year 15
(See Appendix A1).
81
Logging, loading and transport costs occurred at the time of harvest (15 years
from planting) and under the base scenario (see Appendix A1).
3.13 E. nitens physical properties
A range of physical properties were tested to examine the potential influence
these could have on sawn timber value for 15 year old E. nitens and to conduct
statistical comparisons between properties and other log characteristics that could
influence log value.
3.13.1 Dry board and log density assessment
Profiled tongue and groove kiln dried boards were weighed with Wedderburn
WS 201-10k scales (d=0.0005kg). Board volume was calculated as end cross section
area multiplied by length. Board length was noted and a length reduction was
estimated where wane was present.
Dry log density was estimated by summing board weights and dividing by
total board volume. Log dry densities were calculated for all logs.
3.13.2 E. nitens sample physical properties
A single sample section of 0.6 m length with no obvious feature was docked
from a randomly selected blanked 125 mm width board from each E. nitens log.
All samples were sent to Scion Rotorua and were tested for the following
physical properties:
• Density;
• hardness; and
• long term movement in service.
82
3.13.2.1 Hardness
Samples were all tested twice on one face for Janka hardness and these results
averaged.
3.13.2.2 Movement in service
All samples were tested for long-term dimensional stability. Long-term
movement is expressed as the percentage of movement occurring across the width of
the board when the moisture content changes from equilibrium at 85% RH to
equilibrium at 35% RH.
Samples were prepared into test samples that were 70 mm wide, 50 mm long
and 10 mm thick. Long-term movement was assessed by equalising standard sized
samples in conditions of 25°C and 85% relative humidity. When the samples were at
equilibrium (determined by having a stable mass) the samples were weighed and
width and length were measured. The samples were then exposed to conditions of
25°C and 35% relative humidity. When the samples again reached equilibrium they
were weighed and the width and length remeasured. The difference between the two
width measurements was calculated as a percentage of the width in the 35% humidity
conditions. The classification system categorises sum of radial and tangential
movements as:
• Small <3.0 %
• Medium 3.0 – 4.5 %
• Large >4.5 %
83
3.13.2.3 Sample densities
Density was measured for all samples at test by weighing a sample cut from
the test piece immediately after testing for hardness. The sample was oven dried at a
temperature of 103 degrees Celsius until the weight was constant. The samples were
weighed again and the weight loss was divided by the final oven dry weight and
expressed as percentage moisture content for the test samples at test.
3.14 Scope and Limitations of the Study
This case study was intended as a pilot investigation to explore potential
profitability of growing E. nitens for solid timber products from a 15-year-old pruned
and thinned stand of E. nitens grown in the Canterbury Plains near Rangiora. Methods
applied to this investigation into profitability of growing E. nitens for sawn timber
had a range of constraints that did not allow generalisations to be made for the
species. These limitations narrow the scope to that of a case study and are described
in this section.
3.14.1 The case study stand
Sawn wood quality and timber values were assessed from a sample of eight
trees. The small sample size is acknowledged as a limitation to applying sawn timber
production results wider than to the case study itself.
Tree and log volumes were estimated for every tree in the case study stand.
However, the small size of the stand (55 trees in two closely adjoining but not
contiguous areas) allowed for only two small plots (each 28 m x 8 m) that excluded
edge trees, for estimating quantities from a larger hypothetical stand. The small size
of this stand precluded standard methods for quantifying volumes per hectare from
84
sample plots and is acknowledged as a limitation to applying yield results wider than
to the case study stand itself.
Sample trees were selected for sawing to represent the range of diameters
present inside the stand. Although no bias in such selection was evident apart from
specific diameter requirements that represented the range of trees found within the
stand and avoidance of edge trees, because sample trees were not randomly selected,
these cannot strictly be generalised as representative of the stand population.
This study was intended to pilot methods for assessing E. nitens log residual
value that could be standardised in more comprehensive future research. Wood
properties would be expected to vary between trees, regions and even under different
site conditions within a region. Thus relationships observed from sample sawlogs
from this case study would need to be verified by additional research findings before
these could be generalised to a wider population.
3.14.2 Secondary products
Sawdust weight was estimated as the remainder from the total weight of all
logs after deducting the estimated weight of sawn boards (based on measured volume
production and estimated log density) and weight of slabwood. However, sawdust is
likely to be sold on a volume basis and estimating volumes from weight is
problematic because these rapidly change as the sawdust dries or compacts. Therefore
the volume estimate of sawdust produced in the study may not accurately reflect real
volumes.
Slabwood is automatically fed through a firewood-cutting machine as part of
the sawmilling operation. Although for the purposes of this study slabwood was put
aside and weighed to estimate its volume, a conversion factor (see Appendix A2) was
85
required from log volume estimates for then valuing the resulting firewood per
‘thrown’ cubic metre. This factor as practiced by the firewood industry could be
adjusted for applying to slab firewood from specific processing equipment because
average piece sizes of firewood produced from different equipment will produce
varying volumes of wood as a ‘thrown’ cubic metre of volume.
3.14.3 Pulpwood vs. firewood
Because Canterbury has no established hardwood chipwood market, E. nitens
logs are typically utilised for firewood only. Market prices are likely to vary
considerably between stumpages for firewood in Canterbury and in regions where a
hardwood chipwood market is in operation. In this economic evaluation, under the
base scenario logs under 25 cm diameter were priced and sold as firewood logs (see
Appendix A2).
3.14.4 Processing
All recoveries and values were for logs specifically cross cut to 3 m lengths.
Although assumed to be the optimal length for the processing equipment employed,
this length is arbitrary rather than optimised through specific research.
Sawmilling of logs was undertaken with one set of machinery, a Woodmizer
LT 40 horizontal bandsaw and Woodmizer twin-blade edger, both petrol-operated.
The equipment was selected for this study because it is suitable for efficient small
scale eucalypt processing (Satchell & Turner, 2010) and only requires investment to
the level required for the initial stages of emerging an industry.
The author performed all edging of slabs. The consequence of limited
experience at this task may have resulted in variability of grade-sawn output volumes.
86
A more experienced and skilled operator might have produced more consistent and
improved grade recoveries from those documented in this study.
The air-dry sawn timber from this case study was kiln dried using a Solarola
Mini-Pro Sun-dry Kiln (6 m3 capacity). This is the smallest of a range of commercial
kilns and the manufacturer subsequent to purchase of this kiln advised the owner that
the relatively low timber mass being dried limits this kiln’s effectiveness and reduces
its cost efficiency when compared with larger kilns in the Solarola range (J.
Fairweather pers. comm.). The kiln puts through six charges per year in Canterbury
conditions. Comparative cost per cubic metre of throughput could not be compared
for the Solarola range in Canterbury conditions.
Dressing of timber was undertaken using a Logosol PH 260 four-sider with
variable feed speed. Blanking and profiling was accomplished in two stages. This
machinery is considered marginal for commercial applications (J Fairweather, pers.
comm.) and has a slow feed speed compared with more expensive commercial
machines.
An attempt was made to record productivity and costs for the case-study
operation under normal operating conditions through all processing stages. This was
problematic because the operation itself was under development and was not yet
running at commercial capacity during the course of this study.
3.14.5 Harvesting, loading and logging
Harvesting, logging and loading and transport costs were extracted from
Laurie Forestry’s website (Laurie Forestry, 2014). Laurie Forestry Ltd are harvesting
and marketing managers based in Canterbury. Harvesting costs are stated on the
87
website to vary and the logging cost assumptions are to be taken as a guide only
(Laurie Forestry, 2014):
Logging and Loading costs are based on typical operations without
undue complexity, which could include the likes of poor wood quality
and all weather access being available. Cartage costs are based on
averaging of previous quarter.
Logging and Loading costs were based on terrain being easy flat and cartage
costs were based on a distance of 50 km from forest to sawmill.
Estimates of log volumes were converted to tonnages per hectare of sawlogs
and pulp/firewood logs based on a conversion factor calculated from the weights and
volume estimates of the sample logs. The accuracy of this conversion factor was not
verified. Because log weights were likely overestimated this would increase transport
costs per log cubic metre. All other results would not have been affected by this
assumption.
3.14.6 Products
Products assumed to be most profitable for producing from the case study 15
year old E. nitens timber were decided in advance. It is acknowledged that these
products and the resulting log residual value benchmark is somewhat arbitrary
because only over time would production and product choices be refined based on an
improved understanding of wood properties and market demand to yield greatest
returns.
Solid timber strip flooring was selected as the target product for processing
from case study logs for the purpose of determining log residual value. This was
assumed to be the most marketable and least risky product to produce and price. The
88
market is negligible for flooring board widths under 100 mm, so the product selected
for 75 mm and 50 mm board widths was laminated appearance panels.
Slabwood produced from sawmilling comprises over 50% of the log volume.
The firewood by-product produced by the case study operation is assumed to be the
most profitable product from slabwood. This is produced at low cost as part of the
operation.
3.14.7 Product pricing
In the absence of available market price data for E. nitens timber, product
value estimates were the proxy for market prices based on sales. These estimates were
from comparisons with existing similar products and accuracy could not be verified
because market prices were unavailable.
Consistency of supply is a prerequisite for market development of emerging
plantation eucalypt timbers (Shield, 1995, p. 136). For price estimates of E. nitens
timber to be based on an established species and market, consistency of supply
needed to be assumed. The importance of this assumption on market price for timber
would depend on the scale of an industry supplying E. nitens timber. A small industry
supplying a niche market would not need to supply timber consistently, whereas a
developing industry that requires growth in demand would need to consistently meet
that demand. This would be a challenge for growers. Market development, if not
steady, would likely result in price fluctuations and thus returns potentially lower than
estimated.
3.14.8 Laminated panels
Two laminated panels were produced and sold to ascertain costs and value of
the resulting case study product. Prices for the panel laminated timber stock were
89
based on the quality and prices of the two panels produced. These prices may not
reflect true market value for this product because of the small sample sold.
3.14.9 Grades and grading
Grades for 100 mm, 125 mm and 150 mm boards were assessed from profiled
tongue and groove product. Grades for 75 mm and 50 mm wide boards were
estimated from blanked surfaces. Blanked surfaces may not expose all defect or
degrade and resulting grades and prices would be less accurate than grading of
profiled surfaces.
3.14.10 Degrade
Where checking exceeded grade limits this was classed as defect, but any loss
in value caused by checking degrade was not specifically quantified. Future work
with a specific focus on reducing checking might require assignment of economic
value to checking degrade but this was outside the scope of this study.
3.14.11 Definition of checking degrade
Distinguishing internal checking from surface checking is subjective because
internal checks become surface checks if exposed during machining. Definitions of
what are surface checks and what are internal checks have not yet been standardised.
For example deep surface checks could be defined as internal checks. Definitions for
checking in this study are as follows:
• Surface checking: ‘Surface checking’ is defined as either shallow checks that
are seen on the surface of rough sawn timber and do not necessarily dress out
on profiling, or checks less than 2mm deep and less than 1mm wide on the
19mm profiled surface.
90
• Internal checking: ‘Internal checking’ is defined as where the check goes in
from the surface more than 2mm on the 19mm profiled product on the cross
section surface, or where the checks are inside the edge of the cross section
surface.
3.14.12 Grading to ignore collapse
The timber was not steam reconditioned. This was a deliberate approach to
facilitate accurate measurement of checking levels and defect from collapse, but
required assumptions on expected grade recoveries had the timber been steam
reconditioned as per standard practice in Australia for ash eucalypt. It was assumed
for the purposes of this study that steam reconditioning would have removed all
collapse from nominal 25 mm sawn timber sawn at a green size of 28 mm once
dressed to 19 mm. Based on this assumption graded timber was re-graded on the
premise that skip caused by collapse was not present. If this assumption were to be
refuted the methods used for estimating levels of checking would need to be revised.
3.14.13 Wood physical properties
Testing of E. nitens physical properties was undertaken from only one sample
per log due to budget constraints. The intention was to examine indicative
relationships that before being generalised as representative of the species, would
require further testing.
3.15 Conclusions
Methods were developed for estimating log volumes per hectare for the case
study stand according to log categories.
91
Methods were developed for quantifying production costs, sawn timber
recoveries, grade recoveries and defect from sample logs and sample trees. Grade
recoveries were priced to yield an estimate of revenue for each sample log. These
were categorised according to tree and log position in the tree. Residual values were
calculated for the sample logs.
Spreadsheets were developed and statistical tools used to model production
costs and log revenues according to log diameter and log position.
92
Chapter 4
Results
This section presents results from analysis of growth, production and pricing
data for E. nitens solid timber production from 15 year-old case study trees. Net
present value per hectare was calculated from estimates of sawlog residual values and
secondary product prices along with costs for the grower. The results are presented in
seven parts:
1. Case study inventory: Log volume and diameter profiles for the two plots in
the case study stand;
2. Product results: Sawn recoveries, product volumes, costs, grades, widths and
lengths and defect levels produced from the sample logs according to log
position;
3. Air-drying experiment: The relative influence on price of air drying in a
drying shed compared with drying outdoors;
4. Product profiles: Product value estimates from two survey pricing methods;
5. Log pricing models and cash flows: Cost and revenue estimates according to
log diameter from sample logs as log residual value and application of these to
inventory logs; Results and analysis of cash flows according to pricing and
grading methods;
6. Sensitivity analysis: Economic outcomes according to scenarios, including
exclusion of collapse defect, alternative secondary product price estimates and
land value; and
7. Improving grade recoveries: A summary of results that offer opportunities for
log position to become a driver of sawlog price for E. nitens.
93
Parts one through to three summarise the data used in part five for pricing
models. Part four tests the null hypothesis that air drying method does not influence
product prices. Parts five to seven provide an economic analysis of the data from parts
one to four. Part eight summarises data on grade recoveries and defect according to
log position.
4.1 Case Study Stand Inventory
Diameter and height measurements for all fifty-five trees in the Case Study
stand were measured and are presented in Figure 1.
Figure 1. E. nitens case study stand individual trees, height and diameter.
A scale diagram of the case study stand (See Appendix B) was produced on
which two plots of 224 m2 each (8 m x 28 m) were positioned that included a total of
21 trees and excluded edge trees. Plot data is presented in Table 2. Diameters and
heights of all plot trees are presented in Figure 2 along with the diameters and heights
of all sample trees that were harvested and processed.
24
26
28
30
32
34
36
38
0.2 0.3 0.4 0.5 0.6 0.7 0.8
Height (m)
Diameter (m)
Case
study
trees
94
Figure 2. Plot and sample trees showing heights and diameters.
4.1.1 Plot log volumes
Plots were positioned to avoid edge trees. Edge trees were observed to be
larger than trees within the stand and thus not representative of trees within a larger
stand for the purpose of deriving per hectare values. Table 2 presents comparisons of
selected values from stand trees.
Table 2
Plot and Stand Data
Average
Basal
Area per
Tree (m2)
Average
Stem
Volume per
Tree (m3)
Average
DBH Over
Bark (cm)
Average
Tree
Height (m)
Average
Sawlog
SED (cm)
Average
Sawlogs per
tree >25cm
SED
Plot Trees
0.124
1.50
43.03
31.24
32.94
3.87
Stand Trees
0.156
1.83
47.73
31.75
35.28
4.38
Table 3 presents quantities from the two plots and scales the plot average for
each value to per hectare estimates. Sawlogs were categorised as those logs larger
24
26
28
30
32
34
36
38
0.2 0.25 0.3 0.35 0.4 0.45 0.5 0.55
Height (m)
Diameter (m)
Plot trees
Sample
trees
milled
95
than 25 cm SED and pulp logs were categorised as logs between 10 cm and 25 cm
SED. All logs were 3 m length.
Table 3
Plot Data
Trees
Basal
Area
(m2)
Stem
Volume
(m3)
Merchantable
Volume (m3)
Buttlog
Volume
(m3)
Headlog
Volume
(m3)
Pulp-
wood
Volume
(m3)
Plot 1
11
1.34
15.92
15.55
7.17
4.43
3.94
Plot 2
10
1.27
15.47
15.15
6.78
4.90
3.47
Plot
Average
10.5
1.31
15.69
15.35
6.98
4.67
3.71
Per Hectare
469
58.29
700.54
685.20
311.46
208.29
165.45
Average as
Percentage
of Total
--
--
100 %
98 %
44.5 %
29.7 %
23.6 %
Log volume estimates averaged between plots and scaled to per-hectare values
and categorised according to SEDs in 5 cm increments are presented in Figure 3.
Figure 3. Estimated volume recoveries per hectare as diameter categories.
0
50
100
150
200
250
45-50cm 40-45cm 35-40cm 30-35cm 25-30cm 10-25cm
Total Log Volume per Hectare (Cubic Metres)
Log Small End Diameter Under Bark (SED UB)
Headlogs
Buttlogs
96
4.2 Production Results
Sample trees were harvested and cross cut into sample logs, which were
processed into sawn timber products. Results from the sample logs provided models
for predicting costs and revenues for plot trees and hypothetical values per hectare.
4.2.1 Sample log volumes and weights
Green log density at harvest was estimated from sawlog total volume using the
Smalian formula and recorded weight of the sample logs:
• Total weight of sample logs = 12.68 tonnes.
• Total volume of sample logs = 10.34 cubic metres.
• Estimated log density per cubic metre (green) = 1.23 tonnes.
4.2.2 Product quantities from sawlogs
Percentage of overall sawlog green weight allocated to products and by-
products was estimated as percentage of total weight (in green condition). Slabwood
weighed 38% of total green weight. Based on volume of sawn timber and estimated
volume per cubic metre, green weight of sawn boards was estimated to be 48% of
total green log weight. Assuming sawdust is the residue, sawdust by-product weight
was estimated as 14% of total green log weight.
Total nominal sawn timber production from sample logs was 4.06 m3, with
headlogs producing 42.72 % of sawn timber (1.74 m3) and buttlogs producing 57.28
% (2.33 m3) of sawn timber.
4.2.3 Sawmill efficiency
Sawn timber recovery as a percentage was found to have a statistically
significant relationship (P = 0.001) with log small end diameter for the Woodmizer
97
equipment and sample logs. The best fit was a second degree polynomial regression,
presented in Figure 4.
Figure 4. Nominal sawn timber recoveries according to log small end diameter.
Sawmilling cost per nominal sawn cubic metre held a statistically significant
relationship (P = 0.0012) with SED and the second degree polynomial regression
curve revealed an optimal diameter range of between approximately 35 cm SED and
42 cm SED for this equipment. The relationship is presented in Figure 5.
Figure 5. Sawmilling cost per nominal sawn cubic metre of production (not including
log cost).
y = -0.0007775x2 + 0.0564468x - 0.3295012
0%
10%
20%
30%
40%
50%
60%
27 29 31 33 35 37 39 41 43 45
Nominal recovery (%)
Log Small End Diameter (SED)
y = 0.8878x2 - 69.021x + 1530.2405
$100.00
$150.00
$200.00
$250.00
$300.00
$350.00
25 30 35 40 45 50
Sawmilling Cost per Sawn Cubic Metre
SED (cm)
98
4.2.4 Sawn product quantities
Product nominal lengths and widths produced from unpruned headlogs are
presented in Table 4 and Table 5. Product nominal lengths and widths produced from
pruned buttlogs are presented in Table 6 and Table 7.
Table 4
Product Recoveries as Percentage of Sawn Volume for Nominal 100 mm, 125 mm and
150 mm Widths from Unpruned Headlogs (Logs 3 - 5)
Product
Clears/Select Grade
Standard Grade
Feature/High
Feature Grade
300 - 600 mm
Length
2.25 %
0.14 %
0 %
600 - 1200 mm
Length
8.05 %
1.34 %
1.73 %
> 1200 mm Length
35.14 %
10.41 %
7.31 %
Table 5
Product Recoveries by Volume for 75 mm and 50 mm Widths from Unpruned
Headlogs (logs 3 - 5)
Product
Four Faces Clear
Two Faces Clear
One Face Clear
300 - 1500 mm Length
1.98 %
0 %
2.76 %
> 1500 mm Length
7.21 %
1.16 %
10.31 %
Table 6
Product Recoveries as Percentage of Sawn Volume for Nominal 100 mm, 125 mm and
150 mm Widths from Pruned Buttlogs (Logs 1 - 2)
Product
Clears/Select Grade
Standard Grade
Feature/High
Feature Grade
300 - 600 mm
Length
0.64 %
0.23 %
0 %
600 - 1200 mm
Length
2.95 %
1.35 %
0.66 %
> 1200 mm Length
62.7 %
3.39 %
2.42 %
99
Table 7
Product Recoveries by Volume for 75 mm and 50 mm Widths from Pruned Buttlogs
(logs 1 - 2)
Product
Four Faces Clear
Two Faces Clear
One Face Clear
300 - 1500 mm Length
0.12 %
0.2 %
0.05 %
> 1500 mm Length
4.86 %
0.23 %
1.78 %
4.2.5 Processing costs
Results from processing logs into sawn timber products are presented as
sawmill costs, drying costs and processing costs, each process being independent but
contributory to overall product costs and thus residual value.
Sawmill costs amounted to $89.75 per hour of operation. Sawmill costs per
sawn cubic metre are in Figure 5 and sawmill costs per log cubic metre are in Figure
10.
Drying cost estimates per nominal sawn cubic metre were:
• Yard air dried = $202.28.
• Shed air dried = $231.66.
• Steam reconditioning = $30.00.
Machining costs included both a fixed cost per nominal cubic metre of
production plus a variable cost per lineal metre (for all widths) of production:
• Cost per cubic metre = $73.86 (includes boron treatment)
• Cost per lineal metre = $0.41
100
4.2.6 Production volume
Volume of production influences costs per unit of volume output. Annual
production volume estimates for the case study sawmilling operation were based on a
full time operation, or 229 days per year at 8 hours per day. Annual production
volume estimates for the case study processing operation were:
• Sawmill production = 756.85 cubic metres; and
• Machining production = 171,750 lineal metres.
4.2.7 Defect in sawn boards
Table 8
Defect as Percentage of Nominal Sawn Recoveries for All Logs
Defect Category
Farm Forestry
Timbers
Grading
Farm Forestry
Timbers
Grading, Ignore
Collapse
Australian
Standards
Grading
Australian
Standards
Grading, Ignore
Collapse
End splits
3.60 %
3.60 %
3.60 %
3.60 %
Collapse
4.60 %
0.00 %
5.46 %
0.00 %
Wanea
0.07 %
0.07 %
0.07 %
0.07 %
Skipb
0.20 %
0.20 %
0.33 %
0.33 %
Wantc
0.20 %
0.20 %
0.20 %
0.20 %
Checksd
1.78 %
1.78 %
3.0 %
3.0 %
Boxe
3.59 %
3.59 %
3.81 %
3.81 %
Tongue Crook
0 %
0%
0.13 %
0.05 %
Tongue Collapse
0 %
0 %
0.86 %
0.00 %
Total
14.04 %
9.44 %
16.47 %
10.93 %
aWane: End Taper and End Wane was docked but not classed as recovered sawn
timber volume.
bSkip: Skip resulting from board cupping, edge wane, face wane and twist.
cWant: Want included machining voids such as chipping.
dChecks: Box defect caused by excessive checking not meeting grade rules.
eBox: Natural defect such as knots and holes that do not meet grade rules.
101
The level of defect present in sawn boards had an influence over log residual
value. Defect was quantified and categorised during grading and is presented in Table
8 as percentages of nominal sawn timber recoveries for each of the two grading
methods used, both including and excluding collapse defect.
4.2.8 Grade recoveries
Grade recoveries for all sawn timber widths as a percentage of total nominal
recoveries of sawn timber for Farm Forestry Timbers grades totalled to 85.94%, and
ignoring collapse defect totalled 90.53%.
Table 9
Grade Recoveries for 100 mm, 125 mm and 150 mm widths as Percentage of Nominal
Recoveries for All Logs
Grade and Length
Farm
Forestry
Timbers
Grade
Farm
Forestry
Timbers
Grade, Ignore
Collapse
Australian
Standards
Grade
Australian
Standards
Grade, Ignore
Collapse
Select/Clears 300 - 600 mm
1.31 %
1.15 %
1.72 %
1.53 %
Select/Clears 600 - 1200
5.12 %
5.26 %
5.61 %
5.58 %
Select/Clears >1200 mm
50.71 %
52.61 %
50.7 %
52.99 %
Standard 300 - 600 mm
0.21 %
0.14 %
0.25 %
0.22 %
Standard 600 - 1200 mm
1.29 %
1.33 %
1.28 %
1.3 %
Standard > 1200 mm
6.26 %
6.98 %
6.08 %
7.16 %
Feature/High Feature 300 -
600
--
--
0.03 %
0.03 %
Feature/High Feature 600 -
1200 mm
1.36 %
1.39 %
1.03 %
1.23 %
Feature/High Feature >
1200 mm
5.57 %
5.67 %
1.89 %
2.25 %
Total
71.83 %
74.53 %
68.59 %
72.29 %
Table 9 presents grade recoveries for 100 mm, 125 mm and 150 mm width
boards and Table 10 presents grade recoveries for 50 mm and 75 mm width boards.
102
Table 10
Grade Recoveries for 50 mm and 75 mm widths as Percentage of Nominal Recoveries
for All Logs
Length
FFT Panel Lam and
Joinery grade
FFT Panel Lam and Joinery
Grade, Ignore Collapse
Two Faces Clear 300 - 1500 mm
0.12 %
0.12 %
Two Faces Clear > 1500 mm
0.62 %
0.76 %
One Face Clear 300 - 1500 mm
1.21 %
1.10 %
One Face Clear > 1500 mm
5.43 %
6.13 %
Four Faces Clear 300 - 1500 mm
0.91 %
0.91 %
Four Faces Clear > 1500 mm
5.82 %
6.98 %
Total
14.11 %
16.0 %
4.3 Drying Experiment
Results from analysis of variance show no significant difference between
drying treatments and that the null hypothesis that the two treatments are equal cannot
be rejected (P=0.7531). Box and whisker plots are presented in Figure 6 for collapse
defect and Figure 7 for check scores on the profiled surfaces.
103
Figure 6. Collapse defect levels and standard deviations for collapse defect in boards
for trees and logs according to drying treatment (Y=yard drying, S= shed drying).
Collapsedefect
0
50
100
150
200
250
300
sy
2
1
sy
5
1
sy
8
1
sy
18
1
sy
20
1
sy
25
1
sy
32
1
sy
37
1
2
2
5
2
8
2
18
2
20
2
25
2
32
2
0
50
100
150
200
250
300
37
2
0
50
100
150
200
250
300
2
3
5
3
8
3
18
3
20
3
25
3
32
3
37
3
2
4
5
4
8
4
18
4
20
4
25
4
32
4
0
50
100
150
200
250
300
37
4
0
50
100
150
200
250
300
2
5
5
5
8
5
18
5
20
5
25
5
32
5
37
5
104
Figure 7. Checking levels and standard deviations of checking levels as a score for
trees and logs according to drying treatment (Y=yard drying, S=shed drying).
.
4.4 Price Estimates for Board Profiles
Prices per nominal cubic metre of graded timber were calculated for each
product profile and are presented in Table 11 for the graded pairs survey method and
Table 12 for the constant sum allocation method.
checkscore
0
100
200
300
sy
2
1
sy
5
1
sy
8
1
sy
18
1
sy
20
1
sy
25
1
sy
32
1
sy
37
1
2
2
5
2
8
2
18
2
20
2
25
2
32
2
0
100
200
300
37
2
0
100
200
300
2
3
5
3
8
3
18
3
20
3
25
3
32
3
37
3
2
4
5
4
8
4
18
4
20
4
25
4
32
4
0
100
200
300
37
4
0
100
200
300
2
5
5
5
8
5
18
5
20
5
25
5
32
5
37
5
105
Table 11
Prices per Nominal Cubic Metre for Sawn Timber Profiles based on Graded-pairs
Pricing Method
Length (mm)
Width
(mm)
Price for Select /
Clears grade
Price for Standard
Grade
Price for Feature /
High Feature
Grade
> 1200
150
$1309.33
$1101.33
$917.33
> 1200
125
$1235.20
$1040.00
$864.00
> 1200
100
$1184.00
$996.00
$832.00
600 - 1200
150
$1194.67
$986.67
$802.67
600 - 1200
125
$1100.80
$902.40
$729.60
600 - 1200
100
$1016.00
$828.00
$660.00
300 - 600
150
$717.33
$552.00
$405.33
300 - 600
125
$595.20
$438.40
$300.80
300 - 600
100
$460.00
$308.00
$176.00
Table 12
Prices per Nominal Cubic Metre for Sawn Timber Profiles based on Constant-Sum
Allocation Pricing Method
Length (mm)
Width (mm)
Price for Select /
Clears Grade
Price for
Standard Grade
Price for Feature
/ High Feature
Grade
> 1200
150
$1333.33
$1205.33
$1072.00
> 1200
125
$1286.40
$1155.20
$1024.00
> 1200
100
$1216.00
$904.00
$956.00
600 - 1200
150
$1149.33
$1021.33
$888.00
600 - 1200
125
$1100.80
$972.80
$838.40
600 - 1200
100
$1032.00
$1088.00
$772.00
300 - 600
150
$1037.33
$906.67
$776.00
300 - 600
125
$988.80
$860.80
$908.00
300 - 600
100
$920.00
$792.00
$660.00
106
4.4.1 Price estimates for laminated panel feedstock
The narrow-width boards (50 mm and 75 mm wide) were priced as a residual
value by estimating costs to produce a laminated panel product and subtracting these
from the sale price of two laminated panels, each produced from the two board length
categories. The results are presented in Table 13.
Table 13
Residual Product Values per Nominal Cubic Metre for 75 mm and 50 mm Width
Product
Length
(mm)
Width (mm)
Four Faces Clear
Two Faces /
Edges Clear
One Edge Clear
300-1500
50
$1080.00
$1080.00
$1080.00
>1500
50
$1900.00
$1900.00
$1900.00
300 - 1500
75
$1080.00
$1080.00
$1080.00
> 1500
75
$1900.00
$1900.00
$1900.00
4.5 Log Pricing Models and Residual Values
Cost and revenue estimates were produced for each plot log from predictive
models based on sample log data.
4.5.1 Sawn timber revenues
Revenues at the log level were calculated as the sum of board prices per log
for each grading and pricing method. The sample log data showed no statistically
significant differences below the 5% threshold between sawn timber revenue from the
sample logs according to log SED (Table 14).
107
Table 14
Predicted Sawn Timber Revenue According to Log SED
Grading and Pricing Profile
Intercept
Slope
P Value
Farm Forestry Timbers Grading, Graded-Pairs Pricing
634.9333
-5.0587
0.0636
Farm Forestry Timbers Grading, Constant-Sum Allocation
Pricing
661.8305
-5.2965
0.0505
Australian Standard Grading, Graded-Pairs Pricing
641.6792
-5.6025
0.0701
Australian Standard Grading, Constant-Sum Allocation
Pricing
671.3272
-5.9709
0.0545
The relationship between sawn timber revenue and SED, averaged between
grading and pricing profiles, is presented graphically in Figure 8 and ignoring
collapse defect in Figure 9.
Figure 8. Average sawn timber value according to SED.
$250.00
$300.00
$350.00
$400.00
$450.00
$500.00
$550.00
$600.00
$650.00
20 25 30 35 40 45 50
Sawn Timber Revenue per Log Cubic Metre
Log SED
108
Figure 9. Average sawn timber value per log cubic metre according to SED, Ignoring
collapse defect.
Differences according to log position were significant only between log 1 and
logs 2-5.
Table 15
Mean Sawn Timber Revenue per Log Cubic Metre
Grading and Pricing Profile
Log 1
Logs 2-5
Average Revenue All
Logs, Ignore Collapse
Farm Forestry Timbers Grading,
Graded-Pairs Pricing
$465.781
$504.31
$494.91
Farm Forestry Timbers Grading,
Constant-Sum Allocation Pricing
$416.492
$506.97
$520.10
Australian Standard Grading,
Graded-Pairs Pricing
$376.963
$480.07
$493.65
Australian Standard Grading,
Constant-Sum Allocation Pricing
$391.894
$497.84
$510.24
1. P= 0.014
2. P= 0.0134
3. P= 0.0132
4. P= 0.0106
$250.00
$300.00
$350.00
$400.00
$450.00
$500.00
$550.00
$600.00
$650.00
20 25 30 35 40 45 50
Sawn Timber Revenue per Log Cubic Metre
Log SED
109
There were no significant differences between all log positions under the
scenario where collapse defect was ignored (i.e. assumed to have been reconditioned).
Sawn timber revenue per log cubic metre (based on SED) for each scenario presented
in Table 15 were used to model sawn timber revenue per hectare (Table 16).
Table 16
Sawn Timber Revenues per Hectare
Pricing and
Grading Scenario
Farm Forestry
Timbers
Grading,
Graded-Pairs
Pricing
Farm Forestry
Timbers
Grading,
Constant-Sum
Allocation
Pricing
Australian
Standards
Grading,
Graded-Pairs
Pricing
Australian
Standards
Grading,
Constant-Sum
Allocation
Pricing
Not Reconditioned
$216,361
$225,114
$210,511
$218,452
Assumed
Reconditioned
$233,229
$241,057
$229,092
$236,764
4.5.2 Marketing, management and processing overheads
Processing overhead cost at 10% of sawn timber revenue averaged $21,760
per hectare between grading and pricing scenarios. This cost also represents sawmill
profit in addition to return on capital investment.
4.5.3 Processing costs
Processing costs comprised sawmill costs (Figure 10), drying costs (Figure 11)
and machining costs (Figure 12). Regressions for each processing cost contributing to
residual value were found to be statistically significant per log cubic metre based on
log SED. Second degree polynomial regressions were fitted for sawmill and drying
costs whereas machining costs were fitted as linear.
110
Figure 10. Sawmilling costs per log cubic metre (P=0.0285).
Figure 11. Yard drying costs per log cubic metre (P=0.0095).
y = 0.2213x2 - 18.1325x + 453.7335
$-
$20.00
$40.00
$60.00
$80.00
$100.00
$120.00
$140.00
25 30 35 40 45 50
Sawmill Cost per Log Cubic Metre
SED (cm)
y = -0.13149x2 + 9.29831x - 74.10049
$55.00
$65.00
$75.00
$85.00
$95.00
$105.00
$115.00
25 30 35 40 45 50
Drying Costs per Log Cubic Metre
SED
111
Figure 12. Machining costs per log cubic metre (P=2e-04).
4.5.4 Total processing costs
Summing processing overheads, sawmilling, drying and machining costs
produced total processing costs per hectare, presented in Table 17.
Table 17
Total processing costs per hectare
Pricing and
Grading Scenario
Farm Forestry
Timbers
Grading,
Graded-Pairs
Pricing
Farm Forestry
Timbers
Grading,
Constant-Sum
Allocation
Pricing
Australian
Standards
Grading,
Graded-Pairs
Pricing
Australian
Standards
Grading,
Constant-Sum
Allocation
Pricing
Not Reconditioned
$159,533
$160,408
$158,948
$159,742
Assumed
Reconditioned
$167,213
$167,996
$166,799
$167,566
y = -1.25445x + 151.12593
$70.00
$80.00
$90.00
$100.00
$110.00
$120.00
$130.00
25 30 35 40 45 50
Machining Cost per Log Cubic Metre
SED (cm)
112
4.5.5 Residual values
Predicted residual values per log cubic metre for each combination of pricing
and grading methods were estimated from predicted average sawn timber revenues
per cubic metre for log 1 and logs 2-5, less predicted sawmilling costs, drying costs,
processing costs and processing overheads per cubic metre. The residual value model
was applied to plot logs and scaled to per hectare residual values. Total residual value
per hectare was estimated for each pricing and grading scenario from sawn timber
production not including secondary products and is presented in Table 18.
Table 18
Sawn Timber Residual Value per Hectare
Pricing and
Grading Scenario
Farm Forestry
Timbers
Grading,
Graded-Pairs
Pricing
Farm Forestry
Timbers
Grading,
Constant-Sum
Allocation
Pricing
Australian
Standards
Grading,
Graded-Pairs
Pricing
Australian
Standards
Grading,
Constant-Sum
Allocation
Pricing
Not
Reconditioned
$67,196
$75,074
$61,931
$69,078
Assumed
Reconditioned
$76,384
$83,429
$72,661
$79,565
Figure 13. Residuals, averaged between pricing and grading profiles.