Alexandre C. Rocateli, Plant and Soil Sciences, Oklahoma State University, Stillwater, OK, Charles P. West, Texas Tech University, Texas Tech University, Lubbock, TX, Amanda J. Ashworth, USDA - United States Department of Agriculture, Fayetteville, AR, Michael Popp, Agricultural Economics, University of Arkansas, Fayetteville, AR, Kristofor R. Brye, Crop, Soil and Environmental Sciences, University of Arkansas, Fayetteville, AR and James R. Kiniry, USDA-ARS Grassland Soil & Water Research Lab, Temple, TX
An accurate growth model for switchgrass (Panicum virgatum L.) is needed to support decision-making on timing of harvest to predict biomass yield as a function of soil and weather conditions and to maximize resource-use efficiency. The aim was to enhance ALMANAC model capabilities for simulating seasonal changes in biomass yield by enhancing logic for incorporating new logic for N removal simulation in harvested biomass. New algorithms were developed based on data collected in six sites located in two distinct Arkansas ecoregions, Ozark Highlands and Bottom Land and Terrace. The model performance of simulating Alamo switchgrass yield and nutrient removal after incorporation of the new algorithms was tested by comparing simulated and observed values, i.e. model verification and validation. The new algorithm correctly simulated N removal in subsequent years at the same location where it was developed; however it was not validated for other locations. More research is needed to elucidate factors affecting N removal which were not elucidated by the available data.