Purple threeawn (Aristida purpurea) is native perennial grass which had been causing grazing problems in Western United States. This grass species is catalogued as undesirable to cattle production because posses low quality forage coupled with a low palatability. Fire is one of the management tools that have been used to control it on infested grasslands. The objective of this study was to develop a regression equation to predict purple threeawn biomass production during each phenological stage using a non-destructive method. This research was conducted in the Texas Tech University, Native Rangeland, Lubbock, TX. During 2010 growing season 65 purple threeawn plants were randomly selected regarding to plant size on vegetative, reproductive and post-reproductive phenological stages. Threeawn plants were clipped and weighted individually to determine biomass production; then we correlated that biomass with some morphological variables. Those variables were Area at 7.5 cm plant height, area at 50% plant length, basal area, and plant length. As a result each phenological stage we develop a regression model to determine biomass production. Our multilinear regression models were efficient to predict biomass of threeawn plants at each phenological stage. However, even in the same growing season it is necessary built a specific model for each phenological stage. These models can be used to estimate fuel density before applied prescribed burning.
Oral presentation and poster titles, abstracts, and authors from the Society for Range Management (SRM) Annual Meetings and Tradeshows, from 2013 forward.