4 research outputs found
Forest biomass: linking energy to forest health
Presented at the Can forests meet our energy needs? The future of forest biomass in Colorado conference, February 21, 2008, Colorado State University, Fort Collins, Colorado.Dr. Kurt Mackes is an Assistant Professor at Colorado State University. He received both his B.S. and M.S. Degrees in Wood Science and Technology, concentrating in wood engineering from Colorado State University and a Ph.D. in Forestry and Forest Products from Virginia Tech. He is currently conducting a variety of research projects and extension work related to forest products and wood utilization in Colorado and the Rocky Mountain Region. Kurt also has over 10 years of small business sales and production experience with companies that produced wood and plastic products. He teaches Forest Products Marketing and Wood Products courses at Colorado State University and has authored a number of publications on marketing opportunities for wood products
The Effect of Aspen Wood Characteristics and Properties on Utilization
This paper reviews characteristics and properties of aspen wood, including anatomical structure and characteristics, moisture and shrinkage properties, weight and specific gravity, mechanical properties, and processing characteristics. Uses of aspen are evaluated: sawn and veneer products, composite panels, pulp, excelsior, post and poles, animal bedding, animal food supplements, fuel applications, and novelties. Aspen is a preferred species for paneling, veneer products including matchsticks and chopsticks, waferboard and oriented strandboard (OSB), fiberboard, pulp, excelsior, research animal bedding, animal food supplements, and tourist or gift items
Estimating Biomass Yield for Sub-Merchantable Ponderosa Pine of Northcentral Colorado
Volume, mass, and moisture content data were collected for 28 sub-merchantable ponderosa pine trees harvested in northcentral Colorado. The average green bulk density of these trees was 280 kg/m3. The average oven-dry bulk density was 169 kg/m3. Average green moisture content (oven-dry mass basis) was 91%. A multiple regression analysis was conducted using diameter at breast height (DBH), tree height, and crown vigor class to identify which of these variables could be used to predict biomass yield (oven-dry tree mass). Based on an analysis of variance at α = 0.05 level-of-significance, only DBH was a significant predictor of oven-dry tree mass. Therefore, oven-dry mass estimates were calculated based on a regression line fitted to ln(oven-dry mass) vs ln(DBH) data. The R-square value for the regression line was 0.897. Although differences between actual and predicted oven-dry tree mass ranged up to 57.8%, the average difference was 2.9%