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2017 Projects: Active Crop Sensor Use for Corn and Sorghum

Can Active Crop Sensors Predict Yield of Corn and Sorghum and Improve Nitrogen Use Efficiency?

Crop sensing is a promising approach for predicting corn and sorghum yield. The first step in the development of an algorithm (set of equations) for variable rate N applications using proximal sensing is the development of an equation to estimate end-of-season yield from midseason spectral canopy measurements. Variable rate application of N fertilizer using spectral radiance sensors can be used for performing mid-season corrections of N deficiencies, managing field variability, and reducing spatial variation in end-of-season yield.

The GreenSeeker is an active sensor that emits a red light to provide illumination on the crop. In a commercial setting, the sensors are tractor mounted and used to quantify NDVI, an algorithm computes the estimated yield, calculates the optimum N rate to apply, and the variable rate applicator system adjusts the sidedress N application rate. On-the-go sensing with active sensors like the GreenSeeker, directly followed by variable rate N application, has the significant advantage of no post NDVI collection processing needs. However, the operator is only able to use the algorithm programed into the unit. In addition, use of active sensors is restricted to smaller areas and it requires recalibration with an N-rich strip in each management zone.

If you are interested in participating, contact Quirine Ketterings (qmk2@cornell.edu or 607-255-3061). You can also write to: Quirine Ketterings, Nutrient Management Spear Program, Department of Animal Science, Cornell University, 323 Morrison Hall, Ithaca NY 14853.

Goals

The principal objective of our research is to determine the corn and sorghum final gain and biomass yields and N needs with the in-season crop scanning. With this purpose, different parameters are being evaluated in the scanning process: (1) sensor height; (2) sensor head direction; (3) time of sensing; and (4) methods for representing sensing data.

Funding Sources

New York Farm Viability Institute, Inc., Duport-Pioneer, Cornell Cooperative Extension, Federal Formula Funds

Additional Resources

Farmer Impact Stories

Fact Sheets

Extension Articles

Journal Articles

  • Tagarakis, A.C., and Q.M. Ketterings (2017). In-season estimation of corn yield potential using proximal sensing. Agronomy Journal 109:107-114 doi: 10.2134/agronj2016.12.0732
  • Tagarakis, A.C., Q.M. Ketterings, S. Lyons, and G. Godwin (2017). Proximal sensing to estimate yield of brown midrib forage sorghum. Agronomy Journal 109 (in press). doi: 10.2134/agronj2016.07.0414