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United States Department of Agriculture

Agricultural Research Service



2012 Annual Report

1a. Objectives (from AD-416):
The overall objective of this study is to develop an integration sensor and instrumentation system for measuring crop conditions. The specific objectives are: 1) develop an optoelectronic sensor for measuring crop conditions; 2) design an interface module to linking all the sensors and instruments with a PC; 3) use multisensor data fusion technology for data analyses; and 4) develop software for data acquisition and data analyses.

1b. Approach (from AD-416):
An integrated sensor and instrumentation system will be developed to measure real-time crop conditions including normalized difference vegetative index (NDVI), biomass, crop canopy structure, and crop height. Individual sensor components will be calibrated and tested under laboratory and field conditions prior to system integration. The integration system includes crop height sensor, crop canopy analyzer for leaf area index and Photosynthetically Active Radiation (PAR), NDVI sensor, multispectral camera, and a hyperspectral radiometer. The system will be interfaced with a DGPS receiver to provide spatial coordinates for all sensor readings. Data will be imported into a GIS for georeferencing purposes. The experimental design will be a randomized complete block with treatments arranged as split-split plots. The SAS Proc Glimmix will be used for data analyses. Multisensor data fusion will integrate and analyze data from these sensors to provide an assessment of crop structure and environment.

3. Progress Report:
The goal of this project is to develop instrumentation-based methodology for more accurate assessment of the overall health and productivity of important southern agricultural crops. In FY 2012, project scientists developed an integrated multi-sensor instrumentation system that can be used for measuring crop growth conditions. The system was used to measure crop nitrogen status and to differentiate species of plants. A multisensor data fusion technique was used for analysis of sensor data and for combining the sensor data with aerial imaging data for improved results. Work under this project, as it progresses, will develop important new technology and protocols for monitoring the overall health status of important agricultural crops in real time. Such information will drive management practices to maximize crop yields and quality while minimizing inputs.

4. Accomplishments

Last Modified: 08/20/2017
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