The Nitrogen Decision Aid is a computerized program that predicts the amount of N mineralized from planting to side-dress or 5-leaf growth-stage. By applying just enough N-fertilizer to reach the critical soil nitrate concentration it is possible reduce this waste. This model is designed for Northern climates that will have some frost in the soil during the winter.
West Texas Mesonet Agro-Climate Monitor shows the precipitation, temperature, weather forecast for mesonet stations in West Texas.
SHOOTGRO emphasizes the development and growth of the shoot apex of small-grain cereals such as winter and spring wheat (Triticum aestivum L.) and spring barley (Hordeum vulgare L.). To better incorporate the variability typical in the field, up to six cohorts, or age classes, of plants are followed using a daily time step.
Data from: Development of PLEAD: a database containing event-based runoff P loadings from agricultural fields
The P Loss in runoff Events from Agricultural fields Database (PLEAD) is a compilation of event-based, field-scale dissolved and/or total P loss runoff loadings from agricultural fields collected at various research sites located in the US Heartland and Southern US. The database also includes runoff…
Start exploring forest health in places of interest to you such as National Forests and Parks, Tribal Lands, and U.S. Fish and Wildlife units.
Data from: Data and analyses of woody restoration planting survival and growth as a function of wild ungulate herbivory
The data and analyses presented include: (1) planting density, survival and growth (two years post restoration) of riparian plantings along an ~11 km stream reach in northeastern Oregon as a function of herbivory treatment (protected/not protected from wild ungulate herbivory), habitat type, and planting species; and (2) abundance and height distributions of naturally occurring deciduous woody species along the restored stream reach two years post restoration.
Statistics at a Glance provides summary tables of the main data items currently covered by AMIS (Agricultural Market Information System). There are production, supply, utilization, trade and closing stocks. Users can select a country on the world map and specify their request by selecting one of the four AMIS crops: wheat, maize, rice, or soybeans. Alternatively, users can display aggregate values for total cereals and coarse grains.
The LDMI experiment (Low-Disturbance Manure Incorporation) was designed to evaluate nutrient losses with conventional and improved liquid dairy manure management practices in a corn silage (Zea mays) / rye cover-crop (Secale cereale) system. The improved manure management treatments were designed to incorporate manure while maintaining crop residue for erosion control. Field observations included greenhouse gas (GHG) fluxes from soil, soil nutrient concentrations, crop growth and harvest biomass and nutrient content, as well as monitoring of soil physical and chemical properties. Observations from LDMI have been used for parameterization and validation of computer simulation models of GHG emissions from dairy farms (Gaillard et al., submitted). The LDMI experiment was performed as part of the Dairy CAP.
The MAMA experiment (Manure Application Methods for Alfalfa-Grass), from the USDA-ARS research station in Marshfield, WI was designed to evaluate nutrient and pathogen losses with conventional and improved liquid dairy manure management practices for alfalfa-grass production. Observations from MAMA have also been used for parameterization and validation of computer simulation models of greenhouse gas (GHG) emissions from dairy farms.
The Sustainable Corn CAP (Cropping Systems Coordinated Agricultural Project: Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems) was a multi-state transdisciplinary project supported by the USDA National Institute of Food and Agriculture (Award No. 2011-68002-30190). Research experiments were located through the U.S. Corn Belt and examined farm-level adaptation practices for corn-based cropping systems to current and predicted impacts of climate change.