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The Bronson Files, Dataset 1, Field 17, 2012

https://agdatacommons.nal.usda.gov/ar...
7_2012/25212851

High-Throughput Cotton Phenotyping Dataset (2012) - Maricopa Research Water Management

Dive into a unique, comprehensive agricultural research dataset provided by Dr. Kevin Bronson, focusing on nitrogen and water management in cotton at the Maricopa Agricultural Center, Arizona, USA (2012 season).

This dataset is an exceptional resource for compute and analysis, originating from the early developmental period of the Maricopa terrestrial proximal high-throughput plant phenotyping tri-metric method.

Data Includes
Raw Sensor Outputs: Complete raw data recorded by sensors, including those mounted on the Proximal Sensing Cart Mark 1 (PSCM1), an early mobile platform that replaced handheld sensors (CropCircle).

Weekly Proximal Sensing:** High-resolution plot-level data recorded at 5Hz for:
Canopy Reflectance (6 wavelengths)
Canopy Height (ultrasonic distance sensing)
Canopy Temperature (infrared thermometry)
Agronomic Metrics: Lint and seed yields, first open boll biomass, and nitrogen uptake.

Soil & Emissions: Soil profile nitrate determined down to 1.8 m (in 30-cm increments) both pre-plant and post-harvest. Nitrous emissions were measured over 20+ weeks using 1-L vented chambers and gas chromatography.

Intermediate Analysis:
A mega-table of correlated and calculated parameters.
Annotated tables with calculated Vegetation Indices.
SAS process output and GIS compute processing tables (including Excel-formatted examples).

Metadata: Detailed notation of field events, operations, and plot polygon coordinate designations for re-intersection spatial analysis.

This dataset provides a prime example of a high-throughput proximal plant phenotyping approach, essential for researchers and students analyzing and water use efficiency in arid cotton production.

The video includes media that has been created using Generative AI. Special thanks to Google and NotebookLM. Content in this video is presented for entertainment and is not professional advice.

#cottonresearch #agriculturaldata #phenotyping #nitrogenmanagement #remotesensing #cropscience #agritech