Skip to main content
ARS Home » Research » Publications at this Location » Publication #231534

Title: Development of an integration sensor and instrumentation system for measuring crop conditions

Author
item Lan, Yubin
item ZHANG, HUIHUI - TEXAS A&M UNIV
item LACEY, RON - TEXAS A&M UNIV
item Hoffmann, Wesley
item WU, WENFU - JILIN UNIV

Submitted to: International Agricultural Engineering Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2008
Publication Date: 4/1/2009
Citation: Lan, Y., Zhang, H., Lacey, R., Hoffmann, W.C., Wu, W. 2009. Development of an integrated sensor and instrumentation system for measuring crop conditions. International Agricultural Engineering Journal. XI:IT-081115.

Interpretive Summary: Precision agriculture requires accurate, site-specific information about several factors that characterize crop development. New approaches are needed to rapidly detect, record, and process multiple forms of crop-related data for use in precision agriculture. A computerized crop monitoring system was developed that combined data from a global positioning system with other instruments that measured crop height, canopy structure, biomass, and crop physiological indicators. The integrated crop monitoring system was able to simultaneously accept inputs from all of these instruments in real-time as the tractor-mounted instruments moved through the field. Farmers will be able to use the integrated crop monitoring system to assess the growth stage and health of their crop while performing other farming operations, and for making timely crop management decisions.

Technical Abstract: Precision agriculture requires reliable technology to acquire accurate information on crop conditions. Based on this information, the amount of fertilizers and pesticides for the site-specific crop management can be optimized. A ground-based integrated sensor and instrumentation system was developed to measure real-time crop conditions including Normalized Difference Vegetation Index (NDVI), biomass, crop canopy structure, and crop height. Individual sensor components has been calibrated and tested under laboratory and field conditions prior to system integration. The integration system included crop height sensor, crop canopy analyzer for leaf area index, NDVI sensor, multispectral camera, and hyperspectral radiometer. The system was interfaced with a DGPS receiver to provide spatial coordinates for sensor readings. The results show that the integration sensor and instrumentation system supports multi-source information acquisition and management in the farming field.