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IMAP: Image Mapping & Analytics for Phenotyping

    A set of PYTHON programs to implement image processing of ground and aerial images by offering via graphical user interface (GUI) 1) plot-level metrics extraction through a series of algorithms for image conversion, band math, radiometric/geometric calibrations, segmentation, masking, adaptive region of interest (ROI), gridding, heatmap, and batch process, 2) GIS interface for GeoTIFF pixels to Lat/Lon, UTM conversion, read/write shapefile, Lat/Lon to ROI, grid to polygon, and 3) utility GUI functions for zooming, panning, rotation, images to video, file I/O, and histogram.

    Sustainable Corn CAP Research Data (USDA-NIFA Award No. 2011-68002-30190): ARDN Products

      ARDN (Agricultural Research Data Network) annotations for Sustainable Corn CAP Research Data (USDA-NIFA Award No. 2011-68002-30190). These data are a subset of the Sustainable Corn CAP (Cropping Systems Coordinated Agricultural Project: Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems) data specifically developed for Agricultural Research Data Network with csv and json files for easy ingestion into crop models.

      Breedbase

        The Breedbase system has evolved from the Sol Genomics Network (SGN) and Cassavabase and related sites (see RTBbase.org).Breedbase is striving to be a complete breeding management system, including field management, data collection, crossing utilities, and advanced trial analysis.

        LandPKS (Land Potential Knowledge System): Mobile App for Extension, Land-Use and Project Planning, M&E and On-Farm Research

          **LandPKS** comprises a free modular mobile phone app connected to cloud-based storage, global databases, and models, downloadable from Google Play or the iTunes App Store; a system for storing and accessing user data; and a system for sharing data, information and knowledge. LandPKS is being developed to help users determine the sustainable potential of their land, including its restoration potential, based on its unique soil, topography and climate. The land potential assessments will be updated based on new evidence regarding the success or failure of new management and restoration systems on different soils.

          GOSSYM

            GOSSYM is a dynamic, process-level simulation model of cotton growth and yield. GOSSYM essentially is a materials balance model which keeps track of carbon and nitrogen in the plant and water and nitrogen in the soil root zone. GOSSYM predicts the response of the field crop to variations in the environment and to cultural inputs. Specifically, the model responds to weather inputs of daily total solar radiation, maximum and minimum air temperatures, daily total wind run, and rainfall and/or irrigation amount. The model also responds to cultural inputs such as preplant and withinseason applications of nitrogen fertilizer, row spacing and within row plant density as they affect total plant population, and cultivation practices.

            SHOOTGRO

              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.

              PhenologyMMS

                PhenologyMMS is a simulation model that outlines and quantifies the developmental sequence of different crops under varying levels of water deficits, provides developmental information relevant to each crop, and is intended to be used either independently or inserted into existing crop growth models.

                WISDEM

                  WISDEM simulates the variation in multi-species weed populations over time in response to crop rotation, tillage system, and specific weed management tactics and the consequent crop yield loss due to weed competition. Population dynamics of individual weed species are predicted from a limited number of parameters that can be derived from literature sources and expert opinion.

                  USDA-ARS Colorado Maize Water Productivity Dataset 2012-2013

                    The USDA-Agricultural Research Service carried out an experiment on water productivity in response to seasonal timing of irrigation of maize (*Zea mays* L.) at the Limited Irrigation Research Farm (LIRF) facility in northeastern Colorado (40°26’ N, 104°38’ W) starting in 2012. Twelve treatments involved different water availability targeted at specific growth-stages. This dataset includes data from the first two years, which were complete years with intact treatments. Data includes canopy growth and development (canopy height, canopy cover and LAI), irrigation, precipitation, and soil water storage measured periodically through the season; daily estimates of crop evapotranspiration; and seasonal measurement of crop water use, harvest index and crop yield. Hourly and daily weather data are also provided from the CoAgMET, Colorado’s network of meteorological information.

                    IPM Images: The Source for Agriculture and Pest Management Pictures

                      A joint project of The University of Georgia - Warnell School of Forestry and Natural Resources and College of Agricultural and Environmental Sciences, The Center for Invasive Species and Ecosystem Health, USDA National Institute of Food and Agriculture, Southern Integrated Pest Management Center, Southern Plant Diagnostic Network, and USDA/APHIS Identification Technology Program, [IPM Images](https://www.ipmimages.org/) image categories include: Commodity Groups; Taxonomy; Biological Controls; Damage Types; and Diseases.