Submitted to: Agricultural Systems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: June 8, 2006
Publication Date: December 11, 2006
Repository URL: http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6T3W-4KGX8G5-1&_user=209810&_coverDate=03%2F31%2F2007&_rdoc=12&_fmt=full&_orig=browse&_srch=doc-info(%23toc%234957%232007%23999069998%23639048%23FLA%23display%23Volume)&_cdi=4957&_sort=d&_docanchor=&_ct=12&_acct=C000014439&_version=1&_urlVersion=0&_userid=209810&md5=c3911e3bc1dd946883a8bb73e287abdd
Citation: Corson, M.S., Rotz, C.A., Skinner, R.H. 2006. Evaluating warm-season grass production in temperate-region pastures: A simulation approach. Agricultural Systems. 93(1-3):252-268. Interpretive Summary: Many farmers in the northeastern US are returning to pasture grazing to lower the costs of dairy or beef production and to reduce the environmental impacts of their farms. Most pastures in these regions contain only cool-season forage species, which grow slowly during hot summers. To increase summer forage availability, farmers can plant pastures with warm-season grasses. Field studies have demonstrated that some warm-season grass species can be grown in the Northeast, but their economic value to the producer has not been shown. Computer simulation is a cost-effective way of evaluating their use over many years of weather and different management strategies. A whole-farm simulation model was modified to allow prediction of warm-season grass growth in pastures. This model will help producers and researchers determine how warm-season grasses influence the profitability and environmental impacts of dairy or beef farms in the Northeast.
Technical Abstract: The pasture subroutine of the Integrated Farm System Model (IFSM) was modified to simulate a warm-season grass monoculture. Predictions of grass yield and nutritive value were calibrated and evaluated with field data from switchgrass (Panicum virgatum) pastures in Pennsylvania, USA. Uncertainty analysis of initial and post-harvest biomass amounts showed strong sensitivity in predicting first-cut yield to initial biomass and strong sensitivity in predicting subsequent yields to post-grazing biomass. Sensitivity analysis showed that predicted switchgrass yield was most sensitive to physiological and morphological parameters such as proportion of photosynthate partitioned to shoots, specific leaf area, structural growth per unit carbohydrate, leaf photosynthetic efficiency, and the light extinction coefficient. Sensitivity of yield to maximum rooting depth increased during periods of drought. Predicted annual yields were within ±42% of observed values, with better accuracy in predicting crude protein, neutral detergent fiber, and neutral detergent fiber digestibility. Further refinement of the model is necessary to improve predictions of seasonal biomass production. The whole-farm model with a warm-season grass component provides a useful research and teaching tool for evaluating the long-term economic and environmental sustainability of dairy and beef production systems in temperate and subtropical regions.