NDLI: Use of a virtual-reference concept to interpret active crop canopy sensor data

Content Provider	Springer Nature Link
Author	Holland, Kyle H. Schepers, James S.
Copyright Year	2012
Abstract	Active crop canopy sensors make possible in-season fertilizer nitrogen (N) applications by using the crop as a bio-indicator of vigor and N status. However, sensor calibration is difficult early in the growing season when crops are rapidly growing. Studies were conducted in the United States and Mexico to evaluate procedures to determine the vegetation index of adequately fertilized plants in producer fields without establishing a nitrogen-rich reference area. The virtual-reference concept uses a histogram to characterize and display the sensor data from which the vegetation index of adequately fertilized plants can be identified. Corn in Mexico at the five-leaf growth stage was used to evaluate opportunities for variable rate N fertilizer application using conventional tractor-based equipment. A field in Nebraska, USA at the twelve-leaf growth stage was used to compare data interpretation strategies using: (1) the conventional virtual reference concept where the vegetation index of adequately fertilized plants was determined before N application was initiated; and (2) a drive-and-apply approach (no prior canopy sensor information for the field before initiating fertilizer application) where the fertilizer flow-rate control system continuously updates a histogram and automatically calculates the vegetation index of adequately fertilized plants. The 95-percentile value from a vegetation-index histogram was used to determine the vegetation index of adequately fertilized plants. This value was used to calculate a sufficiency index value for other plants in the fields. The vegetation index of reference plants analyzed using an N-rich approach was 3–5 % lower than derived using the virtual-reference concept.
Starting Page	71
Ending Page	85
Page Count	15
File Format	PDF
ISSN	13852256
Journal	Precision Agriculture
Volume Number	14
Issue Number	1
e-ISSN	15731618
Language	English
Publisher	Springer US
Publisher Date	2012-12-18
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Real-time sensors Algorithm Sufficiency index Nitrogen Vegetation index Agriculture Soil Science & Conservation Remote Sensing/Photogrammetry Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences Meteorology/Climatology
Content Type	Text
Resource Type	Article
Subject	Agricultural and Biological Sciences

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