National Agricultural Library
A multi-trophic study to assess ecosystem recovery following energy development for oil and gas extraction in northern U.S. Great Plains rangelands is reported. Soil factors, plant species composition and cover, and nematode trophic structuring between reclaimed oil and gas well sites are compared.
The purpose of this tool is to estimate latitude and longitude from a user inputted zip code. This tool has been useful in collecting latitude and longitude data for users within the US that may not have known their corresponding latitude and longitude information.
The purpose of the SolarCalQ Version 1 JAVA model is to simulate the spectral quality of incident solar radiation for any location on the globe, down to one minute time steps.
The Ogallala Agro-Climate Tool is a Visual Basic application that estimates irrigation demand and crop water use over the Ogallala Aquifer region.
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.
GPFARM (Great Plains Framework for Agricultural Resource Management) is a simulation model computer application. It incorporates state of the art knowledge in agronomy, animal science, economics, weed science and risk management into a user-friendly, decision support tool. Producers, agricultural consultants, action agencies and scientists can utilize GPFARM to test alternative management strategies that may in turn lead to sustainable agriculture, a reduction in pollution, or maximum economic return. GPFARM Express contains default projects to allow users to quickly set up their operations.
The Nitrogen Index is a tool written in the programming language Java that is used to calculate nitrogen uptake and leaching in farming techniques.
An interactive computer program was developed to simulate the interactions among the above factors. It shows how changing one factor impacts the outcome of the other factors for a single growing season. The user selects a climate, a crop, and soil characteristics from menu lists, and then sets the water table depth and quality, irrigation (river or well) water quality and then develops an irrigation schedule. On execution, the relative yield reductions due to over irrigation, under irrigation, and salinity, water table rise or fall and surface runoff are shown numerically for the growing season. Soil water content, soil salinity, water table depth changes and rain and irrigation events during the season are also shown graphically.
A new process-based cotton model, CPM, has been developed to simulate the growth and development of upland cotton (Gossypium hirsutum L.) throughout the growing season with minimal data input. CPM predicts final cotton yield for any combination of soil, weather, cultivar and sequence of management actions.