<p>Dr. Kevin Bronson provides this unique nitrogen and water management in wheat agricultural research dataset for compute. Ten irrigation treatments from a linear sprinkler were combined with nitrogen treatments. This dataset includes notation of field events and operations, an intermediate analysis mega-table of correlated and calculated parameters, including laboratory analysis results generated during the experimentation, plus high resolution plot level intermediate data tables of SAS process output, as well as the complete raw sensors records and logger outputs. </p>
<p>This data was collected during the beginning time period of our USDA Maricopa terrestrial proximal high-throughput plant phenotyping tri-metric method generation, where a 5Hz crop canopy height, temperature and spectral signature are recorded coincident to indicate a plant health status. In this early development period, our Proximal Sensing Cart Mark1 (PSCM1) platform supplants people carrying the CropCircle (CC) sensors, and with an improved view mechanical performance result.</p>
<p>See included README file for operational details and further description of the measured data signals.</p>
<p>Summary:
Active optical proximal wheat canopy sensing spatial data and including additional related metrics such as thermal 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, where the first cluster sensor bracket design and rickshaw inspired operator's handle were successfully employed.
SAS and GIS compute processing output tables, including Excel formatted examples are presented, where intermediate 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.<br>
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.</p>
Research Science - Compute simulation modeling creation or validation. Spatial high frequency sampling and agronomic data numerical analysis. Support agricultural research in phenotyping of plants generally. Example nitrogen management and / or irrigation management of cotton for decision support or experimental parameterization. Example proximal plant phenotyping data. Provide statistical modeling opportunity understanding high resolution proximal terrestrial datasets. Support best practice production of cotton fiber in a climate uncertain future environment. Support remote sensing ground truth with gridded numerical data integrations. Support establishment of successful high-throughput proximal plant sensing methodologies conducted in the field environment.
Use limitations
Research grade data numerical public usages, including the high frequency active optical reflectance and agronomic operations conducted around soil fertility and cotton production, note that these specific experimental results may not be representative of other plant species or geographic locations.