An Integrated Growth and Yield Simulator For Predicting Loblolly Pine Dry Weight Pulp Yields


  • Emily B. Schultz
  • Thomas G. Matney


Growth and yield simulator, neural network, single tree dry weight pulp yield, wood chip thickness


Growth and yield simulators are a valuable tool for forest managers in predicting future stumpage yields and selecting the economically best management strategies and rotation ages. These projections are appropriate for the sellers of stumpage but may not be appropriate for the producers of forest products who also own and manage the raw resource. To identify the most desirable management strategies for landbased mills, the yield model must be capable of making good estimates of final product yields, such as dry weight of pulp, lineal feet of veneer, and size and grade distribution of lumber. The Mississippi State University loblolly pine (Pinus taeda L.) growth and yield simulator has a dry weight pulp yield model fully integrated in the program. Dry weight pulp yields were estimated from stand and tree characteristics using a neural network model for predicting the distribution of wood chip weight by thickness class and a single tree dry weight pulp yield model. These models were embedded in the profile function based tree volume estimator of a cutover site-prepared plantation loblolly pine growth and yield simulator. The resulting model produced estimates of dry weight pulp yields comparable to actual yields. The Windows application growth and yield simulator generates harvested volumes by stumpage class, dry weight pulp yield, and net present values for user selected management regimes and merchandizing standards. It is available at (loblolly). Both stumpage sellers and pulp producers can use the software to place a value on chips from stands according to their expected stumpage and dry weight pulp yields or to select management strategies to maximize yields.


Becker, E. 1992. The effects of chip thickness and kraft cooking conditions of kraft pulp properties. TAPPI Pulping Conference, Book2:561-565.nBorlew, P. B., and R. L. Miller. 1970. Chip thickness: A critical dimension in kraft pulping. TAPPI J.53(11):2107-2111.nChristie, D. 1987. Chip screening for pulping uniformity. TAPPI J.70(4):113-117.nClark, III, A., and R. F. Daniels. 2000. Estimating moisture content of tree-length roundwood In 2000 TAPPI Pulping/Process and Product Quality Conference, Boston, MA. http// (February 10, 2006).nDubois, M. R. 1994. Timber management and wood procurement guidelines for linerboard production in northcentral Arkansas. Dissertation, Mississippi State University, Mississippi State, MS. 195 pp.nDubois, M. R., W. F. Watson, and F. G. Wagner. 1991. Sawmill chip survey in the U. S. South: An analysis of processes and chip quality. Report presented to the Production and Management Issues Committee, Southeastern Lumber Manufacturer's Association, October 1991. Mississippi State University, Mississippi State, MS. 56 pp.nFlowers, R. K., W. F. Watson, B. K. Wharton, M. L. Belli, and B. J. Stokes. 1992. Utilization and yield of chips from loblolly pine in central Arkansas. TAPPI Pulping Conference, Book2:467-471.nKleppe, P. J. 1970. The process of, and products from, kraft pulping of southern pine. Forest Prod. J.20(5):50-59.nKoger, J. L. 1994. Distributional properties of individual wood chips from loblolly pine plantations in central Arkansas. Dissertation, Mississippi State, MS: Mississippi State University, 152 pp.nKoger, J. L., D. J. Leduc, T. G. Matney, W. F. Watson, A. A. Twaddle, and B. J. Stokes. 1993. Distributional properties of individual wood chips from loblolly pine plantations in central Arkansas. TAPPI Conference, Book2: 741-748.nLedbetter, J. R., T. G. Matney, and A. D. Sullivan. 1986. Tree profile and volume ratio equations for loblolly pine trees on cutover site-prepared lands. S. J. Appl. Forestry10(4):241-244.nMatney, T. G., and R. M. Farrar, Jr. 1992. A thinned/unthinned loblolly pine growth and yield simulator for planted cutover site-prepared land in the mid-gulf South. S. J. Appl. Forestry16(2):70-75.nSchultz, E. B., and T. G. Matney. 2002. Prediction of Pulp Yields from Loblolly Pine Stand and Tree Characteristics. 2002 TAPPI Fall Technical Conference, September 11, 2002, San Diego, CA. (February 10, 2006).nSchultz, E. B., T. G. Matney., and J. L Koger. 1999. A neural network model for wood chip thickness distributions. Wood Fiber Sci.31(1):2-14.nTasissa G., and H. E. Burkhardt. 1998. Modeling thinning effects on ring specific gravity of loblolly pine (Pine taeda L.). Forest Sci.44(2):212-223.nTikka, P., H. Tahkanen, and K. Kovasin. 1993. Chip thickness vs. kraft pulping performance, Part 2: Effect of chip thickness screening on cooking, oxygen delignification and bleaching of softwood kraft batch pulp. TAPPI Pulping Conference, Book2:833-838.nTong, Q. J., S. Y. Zhang, and M. Thompson. 2005. Evaluation of growth response, stand value, and financial return for pre-commercially thinned jack pine stands in Northwestern Ontario. Forest Ecol. Mgmt.209(3):225-235.nTwaddle, A. A., and W. F. Watson. 1990. Survey of disc chippers in the southeastern USA, and their effects on chip quality. TAPPI Pulping Conference, Book1:77-86.nUelmen, R. L. 1993. Mill cut chip quality improvement program. TAPPI Pulping Conference, Book2:725-733.nWorster, H. E., D. L. McCandless, and M. E. Bartels. 1977. Some effects of chip size on pulping of southern pine for linerboard. TAPPI J.60(2):101-103.nZobel, B. J., R. C. Kellison, M. F. Matthias, and A. V. Hatcher. 1972. Wood density of the southern pines. Technical Bulletin. No. 208. North Carolina Agricultural Experiment Station. 56 pp.n






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