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Legacy Phosphorus and Potassium Correlation Experiments: Qulin, Missouri

    Correlation experiments for P and K were conducted from 1968-1973 at a research farm in Qulin, Missouri to better define the relationships between soil tests, crop yields, and fertilizer treatments. Three crop rotations each were conducted for P and K trials (ranges C, D, E, F, G, and H), and included corn, soybean, wheat, cotton, and sorghum.

    The Bronson Files, Dataset 6, Field 13, 2014

      Dr. Kevin Bronson provides a unique nitrogen and water management in cotton agricultural research dataset for compute, including notation of field events and operations, an intermediate analysis mega-table of correlated and calculated parameters, and laboratory analysis results generated during the experimentation, plus high-resolution plot level intermediate data analysis tables of SAS process output, as well as the complete raw data sensor recorded logger outputs.

      The Bronson Files, Dataset 5, Field 105, 2014

        Active optical proximal wheat canopy sensing spatial data and including additional related metrics such as 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 the 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 2014 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 Mark1, 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. Ten levels gradient irrigation application from linear move sprinkler system were applied. Soil physical texture and fertility chemistry results are available. Durum wheat data includes in-season biomass and plant N content, final total biomass, grain yield, grain nitrogen, and yellow berry assessment.

        UGA Variety Testing Soybean Evaluations 2016-2019: ARDN products

          ARDN (Agricultural Research Data Network) annotations for UGA Variety Testing Soybean Evaluations 2016-2019. This data was collected and published by University of Georgia's Statewide Variety Testing program from 2016-2019. It consists of experimental (non-regulated) and commercially-released soybean germplasm entered by seed companies, universities and USDA breeding programs.

          UGA Variety Testing Corn Silage Evaluations 2016-2019: ARDN products

            ARDN (Agricultural Research Data Network) annotations for UGA Variety Testing Corn Silage Evaluations 2016-2019. This data was collected and published by University of Georgia's Statewide Variety Testing program from 2014-2019. It consists of experimental (non-regulated) and commercially-released corn hybrids entered by seed companies.

            The Bronson Files, Dataset 4, Field 105, 2013

              Active optical proximal wheat canopy sensing spatial data and including additional related metrics such as 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 the 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 Mark1, 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. Ten levels gradient irrigation application from linear move sprinkler system were applied. Soil physical texture and fertility chemistry results are available. Yield and seed information is presented.

              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.

                The Bronson Files, Dataset 2, Field 17, 2013

                  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. Lint and seed yields, first open boll biomass, and nitrogen uptake were also determined. Soil profile nitrate to 1.8 m depth was determined in 30-cm increments, before planting and after harvest. Nitrous oxide emissions were determined 20 or more weeks in the season with 1-L vented chambers (samples taken at 0, 12, and 24 minutes). Nitrous oxide was determined by gas chromatography (electron detection detector).

                  UGA Variety Testing Corn Grain Evaluations 2014-2019: ARDN products

                    ARDN (Agricultural Research Data Network) annotations for UGA Variety Testing Corn Grain Evaluations 2014-2019. This data was collected and published by University of Georgia's Statewide Variety Testing program from 2014-2019. It consists of experimental (non-regulated) and commercially-released corn hybrids entered by seed companies.

                    Alfalfa Response to Potassium Rate and Timing of Application

                      Alfalfa production is a key component of livestock production in Tennessee. Alfalfa has the ability to take up luxury amounts of potassium, which can lead to high plant tissue K concentrations and lower concentrations of other nutrients. The objectives of this research were to determine 1) whether Tennessee K recommendations for alfalfa were sufficient and accurate, and 2) if splitting K applications impacted alfalfa yield.