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Growth and Yield Data for the Bushland, Texas Maize for Grain Datasets

    This dataset consists of growth and yield data for six seasons of maize grown for grain at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) for 1989, 1990, 1994, 2013, 2016, and 2018. Maize was grown on four large, precision weighing lysimeters, each in the center of a 4.44 ha square field. The entire datasets for individual season years consist of soil water content, weather, crop growth and yield, agronomic calendar, water balance (evapotranspiration, precipitation, dew/frost, irrigation), and lysimeter energy and water balance data. This dataset focuses on the maize growth and yield data.

    The Bushland, Texas Maize for Grain Datasets

      This parent dataset links to six seasons of datasets on maize grown for grain at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) for 1989, 1990, 1994, 2013, 2016, and 2018. Maize was grown on four large, precision weighing lysimeters, each in the center of a 4.44 ha square field. The datasets for individual season years consist of soil water content, weather, crop growth and yield, agronomic calendar, water balance (evapotranspiration, precipitation, dew/frost, irrigation), and lysimeter energy and water balance data.

      The Bronson Files, Dataset 8, Field 113, 2016

        Dr. Kevin Bronson provides this dataset representing the first of three consecutive years of cotton and nitrogen management experimentation in Field 113. Included, is an intermediate analysis mega-table of correlated and calculated parameters, 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 7, Field 13, 2015

          Dr. Kevin Bronson provides a second year of water management in cotton agricultural research experiment 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 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.