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Hand-Held Sensor For Measuring Crop Reflectance And Assessing Crop Biophysical Characteristics
1
J. S. Schepers,
2
K. H. Holland
1. USDA _retired
2. Holland Scientific, Inc.
Crop vigor is difficult enough to define, let alone characterize and conveniently quantify. The human eye is particularly sensitive to green light, but quantifying subtle differences in plant greenness is subjective and therefore problematic in terms of making definitive management decisions. Plant greenness is one component of crop vigor and leaf area index or the relative ability of the crop to capture solar energy is another. It is well documented that reflectance of red light is a good way to quantify plant chlorophyll content until the canopy approaches closure. Once the canopy closes, red light reflectance remains very low and thus is no long responsive to changes in plant chlorophyll content. Reflectance in the red-edge region of the spectrum has been shown to be quite sensitive to canopy chlorophyll content over a wide range of biomass conditions. Canopy biomass is best quantified by measuring near infrared (NIR) reflectance. In a practical sense, NIR reflectance quantifies the size of the photosynthetic factory while red and red-edge reflectance collectively characterize how fast the factory can operate. The three-band (red, red-edge, and NIR) hand-held RapidSCAN CS-45 crop canopy sensor was developed to address these needs. The basic optical design was brought forward from the active three-band Holland Scientific Crop Circle ACS-430 sensor. The hand-held version provides a long-life lithium battery, internal GPS, large display and data storage capacity, and convenient data transfer into Microsoft Excel. Additionally, the versatility and autonomy of the RapidSCAN sensor has extended its usefulness to other applications such as unmanned aerial vehicles (UAV). Internally, the software calculates red, red-edge and NIR reflectance, NDVI and NDRE vegetation indices and various statistical values for scanned plant canopies as well as calculating plant biophysical properties or computing nutrient rates based on mathematical models. In practice, the sensor makes it possible for producers and consultants to scan crops to make fertilizer N recommendations, assess forage biomass, estimate yield, estimate crop leaf area and geospatially map agricultural landscapes.
Keyword
: Active sensor, N recommendation, RapidSCAN, NDVI, NDRE, side-dress, red-edge, chlorophyll
J. S. Schepers
K. H. Holland
Proximal Sensing in Precision Agriculture
Oral
2014
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