2008 Joint Annual Meeting (5-9 Oct. 2008): A Centralized Regional Database for Winter Cover Crops in Annual Cropping Systems in the Midwest.

684-5 A Centralized Regional Database for Winter Cover Crops in Annual Cropping Systems in the Midwest.



Tuesday, 7 October 2008
George R. Brown Convention Center, Exhibit Hall E
Thomas C. Kaspar1, Eileen Kladivko2, Donald L. Wyse3, E. Anne Verhallen4, Alan Sundermeier5, Dale R. Mutch6 and Dean G. Baas6, (1)USDA-ARS, National Soil Tilth Laboratory, 2150 Pammel Dr., Ames, IA 50011-4420
(2)Agronomy Dept., Purdue University, 915 W State Street, West Lafayette, IN 47907-2054
(3)University of Minnesota, St. Paul, MN 55126
(4)Ontario Ministry of Agriculture, Food and Rural Affairs, OMAFRA, PO Box 400, Ridgetown, ON N0P 2C0, Canada
(5)Ohio State University - OARDC, 639 S Dunbridge Road Ste 1, Bowling Green, OH 43402
(6)W.K. Kellogg Biological Station, Michigan State University Extension, 3700 E. Gull Lake Drive, Hickory Corners, MI 49060
Winter cover crops have the potential to reduce erosion, minimize losses of nitrogen and phosphorus, and increase soil carbon in annual cropping systems in the Midwest. Public support, however, for incentives to farmers to adopt cover crops is minimal. Therefore, development of location specific recommendations and documentation of cover crop environmental benefits are needed to facilitate adoption and to increase public support for cover crops in the Midwest. To begin to accomplish this, a centralized regional database will be established with cover crop growth, management, and environmental benefit information collected from multiple past and present winter cover crop trials and demonstrations across the region. Although data from many locations will focus on cereal rye cover crops, data on other cover crops, including other small grains, legumes, brassicas, and grasses, will be included in the database as available. By necessity the database will be structured to allow input of information from locations with comprehensive data sets and from locations with minimal information, including farmers’ fields.  The preliminary database framework is described and example data presented.