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dc.contributor.authorBu, Honggang
dc.description.abstractRemote sensing is one possible approach for improving crop nitrogen use efficiency to save fertilizer costs, reduce environmental pollution, and improve crop yield and quality. Feasibility and potential of using remote sensing tools to predict crop yields and quality as well as to detect nitrogen requirements, application timing, rate, and places in season were investigated based on a two-year (2012-2013) and four-crop (corn, spring wheat, sugar beet, and sunflower) study. Two ground-based active optical sensors, GreenSeekerTM and Holland Scientific Crop CircleTM, and the RapidEyeTM satellite imagery were used to collect sensing data. Highly significant statistical relationships between INSEY (NDVI normalized by growing degree days) and crop yield and quality indices were found for all crops, indicating that remote sensing tools may be useful for managing in-season crop yield and quality prediction.en_US
dc.publisherNorth Dakota State Universityen_US
dc.rightsNDSU policy 190.6.2
dc.titleYield and Quality Prediction Using Satellite Passive Imagery and Ground-Based Active Optical Sensors in Sugar Beet, Spring Wheat, Corn, and Sunfloweren_US
dc.typeThesisen_US
dc.date.accessioned2018-01-26T20:35:18Z
dc.date.available2018-01-26T20:35:18Z
dc.date.issued2014
dc.identifier.urihttps://hdl.handle.net/10365/27329
dc.rights.urihttps://www.ndsu.edu/fileadmin/policy/190.pdf
ndsu.degreeMaster of Science (MS)en_US
ndsu.collegeAgriculture, Food Systems and Natural Resourcesen_US
ndsu.departmentSoil Scienceen_US
ndsu.departmentSchool of Natural Resource Sciencesen_US
ndsu.programSoil Scienceen_US
ndsu.advisorFranzen, Dave


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