Estimating breakeven prices for Douglas-fir veneer quality logs from stiffness graded stands using acoustic tools.
Although tree dimensions and external quality characteristics (such as branch size, sweep, and scarring) may have traditionally been sufficient to specify a log-sort, consideration is now being given to specifying such wood properties as density, stiffness, micro fibril angle, spiral grain, extractives content, and consumption of energy for processing. More frequently, these internal wood "attributes" are being taken into consideration as important influences on the estimation of timber value. Additional specifications required by wood buyers add extra complexity to the already complex task of log producing and sorting. It has been shown that, without any premium prices and incentives, such requirements for log grades can reduce the total value for the forest owner. Seven second-growth Douglas-fir stands of similar age class in Western Oregon were sampled, totaling 1,400 trees and more than 3,000 logs. Various measurements were taken and several parameters calculated, including acoustically estimated stiffness and mill veneer recovery, revenues, and costs. A general methodology for estimating relative breakeven prices of Douglas-fir peeler logs that a mill or any other log purchaser could afford to pay based on acoustic assessment of veneer stiffness differences is presented.
Green veneer was the largest source of revenue averaging about 80 percent as compared to that from chippable material and unpeeled cores combined. Smaller trees incurred higher manufacturing costs, up to a 40 percent difference between the largest and smallest delivered average-size log. The sample with the greatest net revenue ($1,145 per thousand board feet) was 3 percent higher than the next one and more than 16 percent higher than the lowest one. These results show that stand stiffness grading based on acoustic velocity measurements of Douglas-fir peeler logs could be used as a surrogate measure for potential net returns and hence a premium price could be requested on logs from such stands.
Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var. menziesii) is one of the most important raw material resources for the forest products industries of the United States, Canada, New Zealand, and parts of Europe (Gartner et al. 2002). The unique attributes (appearance, strength, and machinability) of its wood have established and maintained the Pacific Northwest as a major factor in domestic and international markets for forest products. International and U.S. wood product markets, especially high-quality structural lumber and veneer markets, are likely to continue to demand Douglas-fir logs (Schuler and Craig 2003).
Over the last several decades, however, as demand for high-quality timber has been rapidly increasing, the availability of old-growth Douglas-fir and other softwoods has been diminishing across North America and timber resources have gradually shifted to intensively managed young growth stands (Adams et al. 2002, Zhang et al. 2004). Due to the higher proportion of juvenile wood, younger stands usually yield lower quality timber (Gartner 2005) with greater variability in product performance (Carter et al. 2006). As global forest products markets are becoming increasingly competitive and complex, the successful transformation of managed second-growth stands into quality products is crucial for the existence of a robust forest industry (Kellogg 1989, Barbour and Kellogg 1990, Eastin 2005). Good measurements and predictions of both the external and internal properties of the wood in each stem are essential for optimally matching logs to markets (Clarke et al. 2002). Assessing a forest stand's quality (Acuna and Murphy 2006), determining its most appropriate use, time of harvest, and the processing technique to be used, and consequently distributing the products to the right location are all important management decisions for achieving reduced costs and increased product values (Murphy et al. 2005).
Wood modulus of elasticity (MOE), also known as stiffness, is one of the most important mechanical properties and is the most frequently used indicator of the ability of wood to resist deflection and distribute loads in a structure. Despite its high variability which is dependent upon site, genetics, silviculture, and location within the tree and stand, MOE has long been recognized as a critical product variable in both solid wood and pulp and paper processing (Eastin 2005). It is a particularly important parameter in the conversion of raw timber material into veneer and plywood products requiring high stiffness wood. With the ever growing use of engineered wood products, including roof trusses and laminated veneer lumber (LVL), the demand for lumber and veneer with high MOE values has increased.
For many years, the sawmilling industry has utilized acoustic technology for lumber assessment. Stress wave nondestructive testing (NDT) methods are currently used for veneer grading programs, and strong correlations have been reported between stress wave velocity and wave attenuation and the corresponding mechanical properties of LVL (Brashaw et al. 2004). Commercially, longitudinal stress wave techniques have allowed LVL manufacturers to translate mechanical veneer characteristics, such as stiffness and strength, into LVL material with low variability and predictable strength properties (Kunesh 1978). NDT instruments that are compact and easy to operate and are based on acoustic principles have been developed for measuring stiffness of logs and standing trees (Dickson et al. 2004). Acoustic NDT methods have been successfully used for evaluation of mechanical properties of various wood products (structural lumber, poles, and pulp logs) and species as well as in tree selection and breeding based on stiffness (Huang et al. 2003). Past research has indicated a high correlation between yield of structural grades of lumber and acoustic velocity of standing trees (Wang et al. 2001, Lindstrom et al. 2002, Grabianowski et al. 2006, Lasserre et al. 2007, Wang et al. 2007a) and processed logs (Ross et al. 1997, Joe et al. 2004, Wang et al. 2007b, Waghorn et al. 2007, Amishev and Murphy 2008c). But, it is important to note that acoustically evaluated stiffness is influenced by other wood characteristics such as density and microfibril angle (Huang et al. 2003), knots and distorted grain (Briggs et al. 2008), moisture content (MC) (Amishev and Murphy 2008b), and temperature (Carter et al. 2005).
Worldwide forest harvesting has become increasingly mechanized over the last several decades. This is especially true in areas where the harvested tree size is decreasing and the capability of one or two machines to fell, delimb, buck, and sort a tree or a group of trees is an appealing advantage. Drivers for this shift from manual to mechanical harvesting systems generally include productivity/cost improvement goals or labor-related issues. Additionally, mechanization also provides a platform for innovative measurement systems which could lead to improved log segregation based on a wider range of wood properties (Murphy 2003). In recent years, mills and markets have begun to include additional characteristics to specify the logs they require with consideration now being given to such wood properties as stiffness, strength, density, spiral grain, extractives content, and consumption of energy for processing (Andrews 2002, So et al. 2002, Young 2002).
Readily available tree (e.g., diameter at breast height [DBH]) and stand growing (age, spatial location) conditions were found to have limited or no predictive capability regarding the quality of the resulting veneer (Amishev and Murphy 2008b, 2008c). New technologies have been evaluated and implemented for measuring internal wood properties. Segregation of logs, based on hand-held acoustic tools that measure stiffness, is already being used by some forest companies to improve the value of lumber recovery (Green and Ross 1997, Matheson et al. 2002). Internal wood properties of logs are likely to be more commonly measured and specified by markets in the near future. Amishev and Murphy (2008c) have demonstrated that acoustic technology could be a promising and valuable tool for in-forest assessment of veneer-grade Douglas-fir log stiffness early in the supply chain even on a whole-tree basis. Moreover, Amishev and Murphy (2008a) have determined and investigated some issues and opportunities associated with installing resonance-based acoustic technology on a processor/harvester head and evaluated suggested working procedures based on feasibility and productivity considerations. Two forest products companies in the Pacific Northwest have expressed to the authors of this paper their inclination to impose stiffness requirements if such technology was commercially available.
Although wood producers are already sorting logs according to both external and internal properties (Jappinen 2000, Matheson et al. 2002), there is scarce evidence of markets paying premium prices for logs with superior internal characteristics, such as high stiffness. The economic importance of different wood properties varies with the products recovered from a tree or log, the grading methods applied, and the price structure used (Aubry et al. 1998). Only a few comprehensive veneer recovery reports on Douglas-fir have been published in the literature (Lane et al. 1973, Fahey 1974, Fahey and Willits 1991, Fahey et al. 1991), and even fewer studies were found that link wood characteristics and their effect on product value (Green and Ross 1997, Willits et al. 1997). Such studies are crucial sources of information in estimating the effect of different wood characteristics on economic value. Although product standards, mill equipment, and the size and quality of the resource have changed since these comprehensive studies were performed, relationships reported in them are still useful in financial analyses.
Acuna and Murphy (2007) have performed a financial analysis to estimate the premium price that markets would be willing to pay for Douglas-fir sawlogs and pulp logs with different wood densities. No studies have estimated relative premium prices for Douglas-fir peeler-grade logs based on stiffness differences assessed using acoustic technology. In other words, if a forest owner or a contractor invests additional resources and effort into acoustically segregating Douglas-fir peeler logs for stiffness, the breakeven premium price that a log purchaser could afford to pay for those logs has not been previously estimated. This article, therefore, reports the results from a financial analysis focused on estimating relative breakeven prices of Douglas-fir peeler logs that a mill or any other log purchaser could afford to pay based on acoustic assessment of veneer stiffness differences.
Materials and methods
Seven second-growth Douglas-fir stands (A through G) of similar age class (50 to 70 years) chosen to cover a range of elevations and tree sizes were harvested. Two hundred trees from each stand were sampled totaling 1,400 trees and more than 3,000 logs. Only veneer-grade lengths were cut (18, 27, and 35 ft or 5.5, 8.2, and 10.7 m, respectively); no sawlogs or pulp logs were produced. The average log length was 9.2 m, the average log acoustic velocity was 3.77 km/s (12,363 ft/s), ranging from 2.73 to 4.69 km/s (8,957 to 15,387 ft/s). Detailed site description and statistics may be found in Amishev and Murphy (2008c).
Measurements included total tree-length, merchantable length, DBH, biggest branch diameter on each 20-foot (6. l-m) segment of the tree, acoustic velocity of the standing tree (using the Director ST300[R] tool), acoustic velocity of the whole stem with and without the branches (using the Director HM200[R] tool), and acoustic velocity of each log made out of the stem. After the in-forest measurements on the logs were completed, they were transported to a veneer mill, debarked, cut into 8-foot (2.4-m) bolts, kiln-heated, shape scanned, and peeled into veneer sheets. They were then scanned for defects and moisture, sorted into moisture classes, dried, and sorted into several veneer grades based on in-line acoustic measurement of wood stiffness using the commercial mill conveyor system's Metriguard[R] model 2800 DME Ultrasonic/RF/IR veneer tester. It ultrasonically transmits stress waves longitudinally through the wood. The average wave velocity is calculated for each veneer, and the veneer is then categorized into predetermined strength and stiffness grades (G1, G2, G3, AB, C+, C, D, X, and XX) that correspond to the wave velocity of each piece (Metriguard, Pullman, WA). Percent veneer recovery for all of the grades was calculated.
General price estimation procedure
The final set of breakeven relative log purchase prices for the seven stands sampled was estimated by determining the residual stand values (total revenues minus processing costs) and applying them on a per net thousand board foot ($/MBF) basis. The particular sequence of steps needed to estimate those prices for each of the seven stands was as follows:
1. Calculate and summarize the amount of veneer (3/8-in. basis) produced in each grade including full sheets (54 in. by 8 ft), half sheets (27 in. by 8 ft), strips, and fish tails.
2. Determine the proportion and actual amounts of veneer, peeler core, and chippable material based on previously published veneer recovery reports.
3. Calculate revenue acquired from veneer, chippable material, and cores based on prices and costs updated to year 2007.
4. Determine the breakeven log purchase price based on the sample residual value and investigate their relationship with stand average log acoustic velocity.
Veneer recovery, prices, and revenues
Nine veneer grades, plus waste, were used in this study (AB, G1, G2, G3, C+, C, D, X, and XX). The prices used were green veneer prices from Random Lengths Publishing Inc. (2007) converted to a 3/8-inch basis and are used only for illustration of relative trends, reflecting the normal ratio of values for each grade. For each site, the veneer produced in each grade was multiplied by its respective price, and a total site veneer revenue was calculated and further converted to a sample plot revenue per thousand [ft.sup.2], 3/8-inch basis ($/M 3/8). At the time of generating the veneer yield reports, a portion of the veneer sheets were still in process without assigned grade. That volume was allocated to specific grades in each site respective to the percent recovery in each grade. The average cost (41 $/M 3/8) of processing logs into green veneer was estimated using values reported in Spelter (1989) and Mitchell (pers. comm.) and updated using a sawmill producer price index to 2007 values (PPI 2008). A single veneer manufacturing cost regardless of the log size, however, would not accurately reflect the differences associated with handling different size material. Briggs and Fight (1992) have developed an equation for estimating veneer manufacturing costs based on small end diameter inside bark (d.i.b.) (in.). Using that equation with its reported coefficients, however, yielded unrealistically high estimates (nearly four times higher than the reported average cost of 41 $/M 3/8). Hence, this reported cost was applied to site G as the basis and the ratios between costs calculated using Briggs and Fight's equation for the other six study sites were applied to the average updated costs above to account for the log size differences. No profit allowance was included in revenue calculations.
Chip and core recovery, prices, and revenues
Not all of the logs produced and measured on site were transported to the same mill where they were converted into veneer as part of this study. From logger/truck ticket information, which provided data on the total number of logs, their weighted average diameter (inches) and length (feet), as well as gross Scribner Decimal C volume (Northwest Log Rules) in MBF, it was determined that some logs were left in the forest or transported elsewhere (Table 1). It was also determined that the veneer produced and reported from each study site was not the yield of the total logs delivered, but came from a portion of them. This is attributed to limitations on available kiln volumes and the need for a separate kiln load for each study site. Unfortunately, except for site G, there was no information regarding the exact number of logs and their respective volume (MBF) used for the reported yield of produced veneer. The distribution of the delivered and processed logs in terms of size and stiffness quality was assumed to be representative of those produced on site. For this reason, veneer and chip recovery models from previous studies had to be used in conjunction with the already available produced veneer volumes and delivered log summary statistics, e.g., number of logs and their respective volume (MBF) utilized for the produced veneer from sites A to F was determined on the basis of the respective ratio between average delivered log diameters and lengths of sites A to F and those of site G.
The following steps were carried out. Fahey et al. (1991) have established percent cubic recovery equations for green veneer (GV):
GV = 101.2 - 360.8/D - 1.6 x [LLAD.sup.2]
and core (C):
C = -6.7 + 252.7/D
D = small-end diameter (in.) and
LLAD = the large limb average diameter (in.) which is assumed to be 2.5 inches in this study.
In deriving these equations they utilized a 5.6 inch constant size of the unpeeled core while in our study this size was approximately 3 inches. Hence using these equations to estimate core recovery would not be correct. Regardless of the unpeeled core size, however, the volume of the core and produced veneer summed should be the same for a log with known diameter and length. Hence, from Fahey et al. (1991) combined equations (GV + C = 94.5 - 108.1/D 1.6 x [LLAD.sup.2]), total cubic recovery percent of veneer and core together and the percent chippable material recovered were calculated (Chip = 100 - GV - C). The core only recovery percent from Fahey et al. (1991) model was calculated again and using the quadratic ratio of the core diameters (3 to 5.6 in.) percent unpeeled core recovery was adjusted and veneer recovery percent was calculated by subtracting adjusted percent core from the total. Since the actual veneer volume produced is known (from the square footage), the total net log volume input in cubic meters is calculated as well as the cubic volumes for core and chippable material. Also, using core diameter (3 in.), average log length, and the calculated adjusted core volume, the number of logs that were used for the veneer production was estimated. With that information, the total net MBF log input using "[m.sup.3] to MBF" conversion factors
(1,000/((10.16 - 0.04 x D - 88.18/D + 290.58/[D.sup.2]) x 35.31)
from Spelter (2002) was calculated for each stand.
Once the volume of chippable material is known, the net pulp value (NPV) per cubic meter of pulp was calculated using the methodology presented by Briggs and Fight (1992) and later used by Acuna and Murphy (2007):
NPV = BD x Y x (SP - NWC - FC x (BDN/BD))
Various sources were used to retrieve input values and all of the values were updated to 2007 values using either consumer or producer price indices. The TD Bank Financial Group reports a pulp selling price (SP) of $720/mt (metric ton) (TD Bank Financial Group 2008). Nonwood costs (NWC) and fixed costs (FC) were acquired from Briggs and Fight (1992) and updated (NWC = $263/mt, FC = $173/mt). Yield (Y) was assumed as 0.5, and the "normal" basic density (BDN) was estimated as the widely accepted species average (450 kg/[m.sup.3]) from Bowyer et al. (2003). Stand average basic densities (BD) were calculated from the disks collected from a subsample of trees in each stand using the water displacement method (Saranpaa 2003).
The unpeeled cores could be used for either fence posts or even stud grade lumber (Fahey and Willits 1991) or chipped and included in the chippable volume. The latter option was chosen for the current study.
Of the total 3,077 logs produced from the seven study sites, 80 percent were actually delivered to the mill (Table 1) and an estimated 57 percent of them went through the entire veneer production process, ranging from less than 43 percent of the site D logs to about 74 percent of the logs in site B (Table 2). Because of size and length differences of the delivered logs, the estimated input of logs in terms of volume ranged from 133.6 [m.sup.3] from site D to 218.3 [m.sup.3] from site G and corresponding Scribner volumes of 17,337 BF to 34,060 BF, respectively. Assuming that the estimated log input is representative of the stand log distribution produced on site, the average basic density ranged from 480 kg/[m.sup.3] in site C to 523 kg/[m.sup.3] in site G.
Figure 1 shows the estimated proportion of logs from each stand associated with green veneer, chippable product, and unpeeled core section. The processed logs from site G had the largest proportion of green veneer recovered (68%) while site E had the lowest recovery with a little over 56 percent of the logs converted into green veneer. The proportion of the unpeeled core section, however, was greatest in site E with almost 14 percent while site G had less than 7 percent. Chippable material was more or less constant across the stands, ranging from 26 percent in site G to almost 30 percent in site E. These values are in agreement with previous studies on veneer yields from similar sized resource (Fahey and Willits 1991, Fahey et al. 1991, Ross et al. 2004)
[FIGURE 1 OMITTED]
Not only was the proportion of green veneer recovered different, but the quality of the veneer among the stands was different as well (Table 3). As with any other product, quality certainly matters considering the difference in market prices buyers are willing to pay for a better quality product. In this case, the best quality veneer (AB) is worth more than twice as much as that which is mediocre (C and D), while the G grades are in between. As previously mentioned, the green veneer "In process" was proportionally allocated to the respective veneer grades within each stand. While around 50 percent of the green veneer produced from stands A, B, D, and E was in the more valuable and "desirable" AB, G1, and G2 grades, the proportion of these grades in sites F and G was less than 40 percent and only 27 percent in site C. The proportion of green veneer in the G3 grade, which is worth only 6 percent less than G2, however, was substantially higher in sites D, E, F, and G than in the other three sites. Site G yielded the largest volume amount of green veneer produced (153,399 [ft.sup.2], 3/8-in. basis) while sites D and E yielded only about 60 percent of that amount.
Green veneer was the largest source of revenue as compared to that from chippable material and unpeeled cores (Fig. 2). Although AB, G1, and G2 veneer grades were worth the most, revenue from the lower-value grades may be a large contributor to the gross return from these stands; revenue from G3, C+, and C veneer grades combined accounted for 37, 45, and 48 percent of the total veneer revenue in sites E, F, and C, respectively. Greater amounts of higher density chippable material can also substantially increase a stand's value and partially overcome mediocre veneer characteristics; while revenue from chips and cores (which were also considered chippable) from most sites averaged 16 percent of the total gross return, they accounted for more than 20 percent in site E, providing a 6.5 percent increase in gross revenue ($/M 3/8) over the "runner-up" site D.
Smaller trees incurred exponentially higher manufacturing costs, up to a 40 percent difference between the largest delivered average-size log from stand G and the smallest from site E (Table 4). The manufacturing costs seem to level off at a log diameter of around 20 inches. The cost difference, however, was not enough to offset the greater gross revenues, and site E (1144.79 $/MBF) was still 3 percent higher in net revenues than the second largest site D and more than 16 percent higher than the lowest site C (960.77 $/MBF). The net revenue values are in fact the estimated breakeven prices that a log purchaser could afford to pay for Douglas-fir peelers from those stiffness graded stands using a resonance-based acoustic technique. Furthermore, investigating the relationship between those estimated breakeven log prices and the average stand log acoustic velocity revealed a fairly strong relationship with a coefficient of correlation [R.sup.2] of 0.62 (Fig. 3). Also, as Acuna and Murphy (2007) have reported, pulp as an end product was more sensitive to variations in basic density of logs than lumber and veneer. Smaller sized logs, which are usually associated with higher manufacturing costs, yield larger corresponding proportions of unpeeled core and chippable material and, provided it has higher basic density, their potential revenue contribution may offset those costs to a large extent.
[FIGURE 2 OMITTED]
[FIGURE 3 OMITTED]
Discussion and conclusions
This research has primarily focused on the use of acoustic technology for evaluating internal properties on Douglas-fir veneer-grade logs. Provided that this technology could be implemented at the time of harvest, it is more than likely that veneer mills and LVL plants would require that delivered peeler logs are acoustically segregated for stiffness. The objective of this study was to estimate relative breakeven prices of Douglas-fir peeler logs that a mill or any other log purchaser could afford to pay based on acoustic assessment of veneer stiffness differences. It was shown that this task is achievable and although markets do not yet pay a premium for higher stiffness peeler logs, log purchasers could afford to pay such prices. Based on the results of this study, it is suggested that stand stiffness grading based on acoustic velocity measurements on Douglas-fir peeler logs at the time of harvest could be used as a surrogate measure for potential net returns from that harvested forest stand and hence for a premium price to be afforded on such stands.
A previous study has shown that the requirement of minimum levels of basic density for log grades can reduce the total value by as much as 40 percent (Acuna and Murphy 2005). It was also shown that it is possible to estimate relative Douglas-fir log prices based on wood density (Acuna and Murphy 2007). Therefore, it is important to develop techniques to allow log purchasers to estimate relative log prices they could afford to pay for logs with different internal characteristics (wood stiffness, density, etc.), especially with the promising potential of newer technologies (acoustics, NIR) to accurately measure those features. The authors are unaware of any studies or ongoing research efforts that have tried to estimate breakeven premium prices that log buyers could afford to pay for logs with higher stiffness as measured using acoustic tools. No studies have been published on analyzing the economic effects of optimal log bucking based on stiffness grade differentiated prices.
It is important to emphasize that this research is associated with several limitations influencing its power and scope of inference:
* due to the commercial nature of the operation and the resulting time and logistics constraints involving several production entities and project tasks, analysis was possible and performed only on a stand average level in terms of the green veneer recovery;
* only an unknown estimated portion of the sampled trees was actually followed through the full process of veneer production while stiffness grading of the logs was performed on the full sample;
* only three peeler log lengths were used throughout the study and no other product recovery from those stands was targeted;
* the market was assumed to be "supply-constrained";
* only green veneer and chips (since unpeeled cores were added to the chippable portion) were considered as end products to calculate net returns;
* equations to calculate the proportion of green veneer, chippable material and cores were extracted from a previous study (Fahey et al. 1991) performed with different mill equipment, size and quality of the resource;
* the non-linear character of the Scribner volume measure presents difficulties in accurately transforming costs and revenues from one unit to another;
* basic density was calculated from a small subsample; and
* all of the logs were converted into veneer for the purposes of the study, in practice logs below a set threshold for veneer quality may have been converted into alternative products.
Future research in this area should strive to perform a similar analysis with data, resulting from closer tracking of sampled material until its end-product conversion not only on stand average level, but even on tree and log-by-log level; it is possible that the averaging effect of log velocity at each site both increased the [R.sup.2] value and reduced the slope coefficient for the net revenue vs. velocity relationship shown in Figure 3. This might be a challenging task to perform especially with proper consideration given to productivity and efficiency constraints. Also, a wider range of end products and market scenarios should be considered when analyzing the effect of acoustically measured stiffness on net revenue. The impact of additional internal and external wood characteristics on those revenues should be evaluated.
In conclusion, despite the assumptions and limitations of this study, the results presented indicate the potential impacts of perceived future market requirements and the way future forest product industry decision-making could be affected by them. The shift of wood markets toward new end product characteristic requirements is already taking place on a smaller scale in some places and future global market change should be expected.
Thanks are extended to Roseburg Forest Products and especially the Oregon Logging Manager Donald Persyn, for providing the stands, equipment, tools, and personnel to assist with this study. The authors are grateful to the OSU College of Forestry for providing a stand in the College Research Forests, as well as funding for equipment and personnel. Funding for this study came from a USDA CSREES Center for Wood Utilization grant CO338B FIFL (In-forest log segregation technologies).
Acuna, M.A. and G.E. Murphy. 2005. Optimal bucking of Douglas-fir taking into consideration external properties and wood density. New Zealand J. of Forestry Sci. 35(2):139-152.
--and--. 2006. Geospatial and within tree variation of wood density and spiral grain in Douglas-fir. Forest Prod. J. 56(4):81-85.
--and--. 2007. Estimating relative log prices of Douglas-fir through a financial analysis of the effects of wood density on lumber recovery and pulp yield. Forest Prod. J. 57(3):60-65.
Adams, D.M., R.R. Schillinger, G. Latta, and A. Van Nalts. 2002. Timber harvest projections for private land in Western Oregon. Research Contribution 37. Oregon State Univ., Forest Res. Lab. 44 pp.
Amishev, D.Y. and G.E. Murphy. 2008a. Implementing resonance-based acoustic technology on mechanical harvesters/processors for real-time wood stiffness assessment: Opportunities and considerations. Inter. J. of Forest Eng. 19(2):49-57.
--and--. 2008b. Pre-harvest veneer quality evaluation of Douglas-fir stands using time of flight acoustic technique. Wood and Fiber Sci. 40(4):587-598.
--and--. 2008e. In-forest assessment of veneer grade Douglas-fir logs based on acoustic measurement of wood stiffness. Forest Prod. J. 58(11):42-47.
Andrews, M. 2002. Wood quality measurement-son et lumiere. New Zealand J. For. 47(3):19-21.
Aubry, C.L., W.T. Adams, and T.D. Fahey. 1998. Determination of relative economic weights for multitrait selection in coastal Douglas-fir. Can. J. Forest Res. 28:1164-1170.
Barbour, R.J. and R.M. Kellogg. 1990. Forest management and end-product quality: A Canadian perspective. Can. J. Forest Res. 20:405-414.
Bowyer, J.L., R. Shmulsky, and J.G. Haygreen. 2003. Forest Products and Wood Sci.: An Introduction. 4th ed. Iowa State Univ. Press, Ames, IA. 554 pp.
Brashaw, B.K., X. Wang, R.J. Ross, and R.F. Pellerin. 2004. Relationship between stress wave velocities of green and dry veneer. Forest Prod. J. 54(6):85-89.
Briggs, D.G. and R.D. Fight. 1992. Assessing the effects of silvicultural practices on product quality and value of coast Douglas-fir trees. Forest Prod. J. 42(1):40-46.
--, G. Thienel, E. Turnblom, E. Lowell, D. Dykstra, R.J. Ross, X. Wang, and P. Carter. 2008. Estimating wood stiffness along the trees to product chain: Tools, relationships and silviculture influences. In: Proc. of the Western Forestry and Conservation Assoc. Wood Quality Workshop: Current Research and Developments in Wood Stiffness and Other Key Properties, May 28, 2008, Vancouver, WA. pp. 85-102.
Carter, P., X. Wang, R.J. Ross, and D. Briggs. 2005. NDE of logs and standing trees using new acoustic tools: Technical application and results. In: Proc. of the 14th Inter. Symp. on Nondestructive Testing of Wood, May 2-4, 2005. Univ. of Applied Sciences, Eberswalde, Germany. pp. 161-169.
--, S.S. Chauhan, and J.C.F. Walker. 2006. Sorting logs and lumber for stiffness using Director HM200. Wood and Fiber Sci. 38(1):49-54.
Clarke, C.R., R.D. Barnes, and A.R. Morris. 2002. Effect of environment on wood density and pulping of five pine species grown in Southern Africa. Presented at the 2002 Tech. Assoc. of the Pulp and Paper Industry of Southern Africa Conference, Durban, South Africa, October 2002. http://tappsa.co.za/archive/APPW2002/Title/ Effect_of_environment_on_wood_/effect_of_environment_on_wood_. html. (Accessed March 2006.)
Dickson, R.L., A.C. Matheson, B. Joe, J. Ilic, and J.V. Owen. 2004. Acoustic segregation of Pinus radiata logs for sawmilling. New Zealand J. of Forestry Sci. 34(2): 175-189.
Eastin, I. 2005. Does lumber quality really matter to builders? In: Productivity of Western Forests: A Forest Products Focus, C.A. Harrington and S.H. Schoenholtz, Eds. Gen. Tech. Rept. PNW-GTR-642. USDA Forest Serv., PNW Res. Sta., Portland, OR. pp. 131-139.
Fahey, T.D. 1974. Veneer recovery from second-growth Douglas-fir. Res. Pap. PNW- 173. USDA Forest Serv., PNW Res. Sta. 22 pp.
--and S. Willits. 1991. Veneer recovery of Douglas-fir from the coast and Cascade ranges of Oregon and Washington. Res. Pap. PNW-439. USDA Forest Serv., PNW Res. Sta., Portland, OR. 32 pp.
--, J.M. Cahill, T.A. Snellgrove, and L.S. Heath. 1991. Lumber and veneer recovery from intensively managed young growth Douglas-fir. Res. Pap. PNW-RP- 437. USDA Forest Serv., PNW Res. Sta., Portland, OR. 25 pp.
Gartner, B.L. 2005. Assessing wood characteristics and wood quality in intensively managed plantations. J. of Forestry 100(2):75-77.
--, M.N. North, G.R. Johnson, and R. Singleton. 2002. Effects of live crown on vertical patterns of wood density and growth in Douglas-fir. Can. J. Forest Res. 32:439-447.
Grabianowski, M., B. Manley, and J. Walker. 2006. Acoustic measurements on standing trees, logs and green lumber. Wood Sci. Technol. 40:205-216.
Green, D.W. and R. Ross. 1997. Linking log quality with product performance. Role of wood production in ecosystem management. In: Proc. of the Sustainable Forestry Working Group at the IUFRO All Div. 5 Conf., Pullman, WA, July 1997. pp. 53-58.
Huang, C.-L., H. Lindstrom, R. Nakada, and J. Ralston. 2003. Cell wall structure and wood properties determined by acoustics--a selective review. Holz als Roh- und Werkstoff 61:321-335.
Jappinen, A. 2000. Automatic sorting of sawlogs by grade. PhD thesis. Dept. of Forest Management and Products, Swedish Agri. Univ., Uppsala, Sweden.
Joe, B., R. Dickson, C. Raymond, J. Ilic, and C. Matheson. 2004. Prediction of Eucalyptus dunnii and Pinus radiata timber stiffness using acoustics. Publication No. 04/013. Rural Industries Research and Development Corp. (RIRDC), Kingston, Australia. 121 pp.
Kellogg, R.M. 1989. Second growth Douglas-fir: Its management and conversion for value. Spec. Publ. SP-32. Forintek Canada Corp., Vancouver. 173 pp.
Kunesh, R.H. 1978. Using ultrasonic energy to grade veneer. In: Proc. 4th symposium on non-destructive testing of wood. Washington State Univ., Pullman, WA. pp. 275-278.
Lane, P.H., R.O. Woodfin, Jr., J.W. Henley, and M.E. Plank. 1973. Veneer recovery from old-growth coast Douglas-fir. Res. Pap. PNW-162. USDA Forest Serv., PNW Res. Sta., Portland, OR. 44 pp.
Lasserre, J.P., E.G. Mason, and M.S. Watt. 2007. Assessing corewood acoustic velocity and modulus of elasticity with two impact based instruments in 11-year-old trees from a clonal-spacing experiment of Pinus radiata D. Don. For. Ecol. Manage. 239:217-221.
Lindstrom, H., P. Harris, and R. Nakada. 2002. Methods for measuring stiffness of young trees. Holz als Roh- und Werkstoff 60:165-174.
Matheson, A.C., R.L. Dickson, D.J. Spencer, B. Joe, and J. Ilic. 2002. Acoustic segregation of Pinus radiata logs according to stiffness. Ann. For. Sci. 59:471-477.
Mitchell, W.L. 2008. Personal communication. The Beck Group An international planning, consulting, and benchmarking firm to the forest products industry, Portland, OR.
Murphy, G.E. 2003. Worldwide experiences with mechanisation and value recovery: worldwide experiences. In: Proc. of the Wood for Africa 2002 Conf., July, 2002, Pietermaritzburg, South Africa. College of Forestry, Forest Engineering Dept., Oregon State Univ., Corvallis, OR. pp. 23-32.
--, H.D. Marshall, and A.W. Evanson. 2005. Production speed effects on log-making error rates and value recovery for a mechanized processing operation in radiata pine in New Zealand. Southern African Forestry J. 204:23-35.
Producer Price Index (PPI). 2008. Producer price index industry (sawmill) data. Bureau of Labor Statistics, Washington, DC.
Random Lengths Publications Inc. 2007. Random Lengths Publications Inc. Weekly. Random Lengths Publications Inc., Eugene, OR.
Ross, R.J., K.A. McDonald, D.W. Green, and K.C. Schad. 1997. Relationship between log and lumber modulus of elasticity. Forest Prod. J. 47(2):89-92.
--, J.R. Erickson, B.K. Brashaw, X. Wang, S.A. Verhey, J.W. Forsman, and C.L. Pilon. 2004. Yield and ultrasonic modulus of elasticity of red maple veneer. Forest Prod. J. 54(12):220-225.
Saranpaa, P. 2003. Wood density and growth. In: Wood Quality and its Biological Basis, J.R. Barnett and G. Jeronimidis, Eds. Blackwell Publishing Ltd., Oxford, UK. pp. 87-117.
Schuler, A. and A. Craig. 2003. Demographics, the housing market, and demand for building materials. Forest Prod. J. 53(5):8-17.
So, C.L., L.H. Groom, T.G. Rials, R. Snell, S. Kelley, and T. Meglen. 2002. Rapid assessment of the fundamental property variation of wood. In: Proc. of the 11th Biennial Southern Silvicultural Research Conference, K.W. Outcalt, Ed. Gen. Tech. Rept. SRS-48. USDA Forest Serv., Southern Res. Sta. 622 pp.
Spelter, H. 1989. Plywood manufacturing cost trends, excluding wood, in Western U.S. mills: 1975-1988. FPL-GTR-64. USDA Forest Serv., Forest Products Lab., Madison, WI. 12 pp.
--. 2002. Conversion of board foot scaled logs to cubic meters in Washington State, 1970-1998. Gen. Tech. Rept. FPL-GTR-131. USDA Forest Serv., Forest Products Lab., Madison, WI. 6 pp.
TD Bank Financial Group. 2008. TD Commodity price report, April 2008. www.td.com/economics. (Accessed April 2008.)
Waghorn, M.J., E.G. Mason, and M.S. Watt. 2007. Influence of initial stand density and genotype on longitudinal variation in modulus of elasticity for 17-year-old Pinus radiata. Forest Ecol. Manage. 252:67-72.
Wang, X., R.J. Ross, and M. McClellan. 2001. Nondestructive evaluation of standing trees with a stress wave method. Wood and Fiber Sci. 33:522-533.
--and P. Carter. 2007a. Acoustic evaluation of wood quality in standing trees. Part I. Acoustic wave behavior. Wood and Fiber Sci. 39(1):28-38.
--, --, R.J. Ross, and B.K. Brashaw. 2007b. Acoustic assessment of wood quality of raw forest materials a path to increased profitability. Forest Prod. J. 57(5):6-14.
Willits, S.A., E.C. Lowell, and G.A. Christensen. 1997. Lumber and veneer yields from small-diameter trees. In: Proc. of the Sustainable Forestry Working Group at the IUFRO All Div. 5 Conf., Pullman, WA, July 1997. pp. 73-79.
Young, G.G. 2002. Radiata pine wood quality assessments in the 21st century. New Zealand J. For. 47(3):16-18.
Zhang, S.Y., Y. Qibin, and J. Beaulieu. 2004. Genetic variation in veneer quality and its correlation to growth in white spruce. Can. J. Forest Res. 34:1311-1318.
Dzhamal Amishev *
Glen E. Murphy *
The authors are, respectively, Research Scientist, Scion, New Zealand Crown Research Inst., Rotorua, New Zealand (Dzhamal. Amishev@scionresearch.com); and Professor, Forest Engineering, Resources and Management Dept., Oregon State Univ., Corvallis, Oregon (Glen.Murphy@oregonstate.edu). This paper was received for publication in June 2008. Article No. 10497.
* Forest Products Society Member.
Table 1--Produced and transported log summary statistics for the seven research sites. Produced on site Study Log Log site count length total average (m) Site A 572 9.39 Site B 399 9.50 Site C 458 9.17 Site D 447 9.22 Site E 395 9.33 Site F 453 8.49 Site G 353 9.33 Overall 3,077 9.20 Transported to mill Study Log Log Small-end site count length diameter Scribner total average average volume (m) (mm) (Gross BF) Site A 357 8.57 244 35,690 Site B 397 9.22 223 38,430 Site C 310 8.29 243 30,720 Site D 447 8.95 237 49,120 Site E 389 9.05 190 27,710 Site F 379 8.23 234 37,410 Site G 168 10.52 312 34,060 Overall 2,447 8.87 234 253,140 Table 2.--Estimated number of logs and net volume (Scribner BF and cubic meter) input for the production of the veneer reported. Average stand basic density (BD) in kg/[m.sub.3] was calculated from discs collected from a subsample of trees. Estimated input for veneer production Log Study count Scribner Cubic Basic site total volume volume density (kg/) (Net BF) ([m.sub.3]) ([m.sub.3]) Site A 282 25,867 195.7 517 Site B 295 24,340 195.3 486 Site C 276 24,274 184.2 480 Site D 191 17,337 133.6 484 Site E 282 17,362 150.5 514 Site F 256 20,723 161.3 498 Site G 168 34,060 218.3 523 Total 1,752 163,963 1238.9 -- Table 3.--Veneer grades, prices in dollars per thousand [ft.sup.2], 318-inch basis ($1M 318), and percent recovery in each grade from the total veneer produced for each of the seven study sites. Veneer grades recovered from the trial stands Veneer Market grades prices ($/M 3/8) A B C AB 480 0.36 0.02 0.01 G1 270 23.57 19.86 6.86 G2 255 14.71 21.23 13.68 G3 240 4.10 5.70 7.34 C+ 225 4.59 8.63 4.26 C 195 18.27 20.63 26.16 D 180 6.29 3.76 14.20 X 105 2.41 3.10 3.69 XX 75 0.32 0.63 0.42 In process -- 25.38 16.44 23.38 Total 128169 123093 120416 volume (3/8) Veneer Veneer grades recovered grades from the trial stands D E F G AB 2.45 0.21 0.03 2.44 G1 19.13 23.54 8.36 7.08 G2 22.32 18.89 24.62 29.92 G3 12.55 10.67 13.53 14.42 C+ 1.11 6.24 5.47 3.03 C 8.87 17.52 22.31 16.80 D 9.02 5.63 8.38 12.11 X 7.75 3.31 4.57 12.42 XX 0.78 0.79 0.91 1.77 In process 16.01 13.21 11.82 0.00 Total 86533 87734 103808 153399 volume (3/8) Table 4.--Total gross revenue, veneer manufacturing costs, and net revenue calculated for each study site. Net revenue per net MBF ($/MBF) was calculated based on estimated input for veneer production. Study sites Revenues and costs A B C D Total revenue ($/M 3/8) 258.94 265.79 237.15 265.95 Manufacturing costs ($/M 3/8) 52.46 57.78 52.70 54.02 Net revenue ($/M 3/8) 206.48 208.01 184.45 211.93 Net revenue ($/net MBF) 1074.2 1104.6 960.8 1110.6 Average log velocity (km/s) 4.12 3.95 3.62 3.93 Study sites Revenues and costs E F G Total revenue ($/M 3/8) 283.25 259.24 248.69 Manufacturing costs ($/M 3/8) 67.49 54.91 41.00 Net revenue ($/M 3/8) 215.76 204.33 207.69 Net revenue ($/net MBF) 1144.8 1074.7 982.2 Average log velocity (km/s) 4.02 3.82 3.77
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|Author:||Amishev, Dzhamal; Murphy, Glen E.|
|Publication:||Forest Products Journal|
|Date:||Apr 1, 2009|
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