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Data from: Development of an optical flow through detector for bubbles, crystals and particles within oils

    The characterization of bubbles or particles in an oil poses some unique challenges. In contrast to water solutions, the use of electrochemical detection approaches is more difficult in an oil. However, optical sensing systems have considerable potential in this area. Here we use a flow through channel approach and monitor the light propagation through this structure in an optical transmission sensor arrangement (OTS).

    iStitch: GUI-based Image Stitching Software

      GUI-based software coded in PYTHON to automate image stitching and alignment processes from a set of tile images for the high throughput image analytics by implementing a series of algorithms.

      Agricultural land use by field: Upper Mississippi River Basin 2010-2020

        This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.

        The Bronson Files, Dataset 3, Field 107, 2013

          Small dataset describing a unique rubber bush, in the context of greater published research Active optical proximal cotton canopy sensing spatial data and including additional related metrics canopy thermal and height are presented. Agronomic nitrogen and irrigation management related field operations are listed. Unique research experimentation intermediate analysis table is made available, along with raw data. The raw data recordings, and annotated table outputs with calculated VIs are made available. Plot polygon coordinate designations allow a re-intersection spatial analysis. Data was collected in the 2013 season at Maricopa Agricultural Center, Arizona, USA. High throughput proximal plant phenotyping via electronic sampling and data processing method approach is exampled. Acquired data using USDA Maricopa first mobile platforms, such as the Proximal Sensing Cart Mark 1. SAS and GIS compute processing output tables, including Excel formatted examples are presented, where data tabulation and analysis is available. The weekly proximal sensing data collected include canopy reflectance at six wavelengths, ultrasonic distance sensing of canopy height, and infrared thermometry. Limited soil sampling and final harvest information is included.

          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.

            Agricultural land use by field: Nebraska 2010-2020

              This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.

              Agricultural land use by field: Illinois 2010-2020

                This database is structured around individual farm fields as the unit of record, providing a framework that enables land use to be assessed at the same scale that agricultural land uses shift, at an annual time step, and at the scale at which conservation practices are implemented. It is beneficial to document agricultural land cover and its rates of change to understand responses of watershed, landscape, and agroecosystem processes to changes in land use and to identify viable approaches that can be customized for local adoption and mitigate environmental impacts from agricultural production.