- Volume 42 Issue 2
Purpose: Precision agriculture includes determining the right amount of nitrogen for a specific location in the field. This work focused on developing and validating a model using variable rate nitrogen application based on the estimated SPAD value from the ground-based image sensor. Methods: A variable rate N application based on the decision making system was performed using a sensor-based variable rate nitrogen application system. To validate the nitrogen application decision making system based on the SPAD values, the developed N recommendation was compared with another conventional N recommendation. Results: Sensor-based variable rate nitrogen application was performed. The nitrogen deficiency level was measured using the image sensor system. Then, a variable rate application was run using the decision model and real-ti me control. Conclusions: These results would be useful for nitrogen management of corn in the field. The developed nitrogen application decision making system worked well, when considering the SPAD value estimation.
Supported by : Chungbuk National University
- Francis, D. D. and W. P. Piekielek. 1999. Assessing crop nitrogen needs with chlorophyll meters. The Potash and Phosphate Institute Site-Specific Management Guide #SSMG-12.
- Gitelson, A.A., Y.J. Kaufman and M.N. Merzlyak. 1997. Remote sensing of pigment content in higher plants:principles and techniques. In Proc. 3rd International Airborne Remote Sensing Conference and Exhibition, 657-664, Copenhagen, Denmark.
- Janos, K.V., U.M. Mikio, M.Kumi and F. Antal. 2003. Leaf Water Potential Measurement Method Using Computer Image Analysis in Satsuma Mandarin. In Proc. Annual International meeting of ASAE, Paper Number: 031050, LasVegas, Nevada.
- Mao, W., Y. Wang and Y. Wangl. 2003. Real-time Detection of Between-row Weeds Using Machine Vision. In Proc. Annual International meeting of ASAE, Paper Number: 031004, LasVegas, Nevada.
- McDonald, R.B. and F.G. Hall, 1980. Global Crop Forecasting. Science 208(May, No 4445):670-679. https://doi.org/10.1126/science.208.4445.670
- McWilliams, D.A., D.R. Berglund and G.J. Endres. 1999. Corn growth and management quick guide. NDSU Extension Service, A1173. North Dakota State University, Fargo, ND.
- Noh, H., Q. Zhang, B. Shin, S. Han and D. Reum. 2005. Dynamic Calibration and Image Segmentation Methods for Multispectral Imaging Crop Nitrogen Deficiency Sensors. Transactions of the ASAE. Vol. 48(1):393-401. https://doi.org/10.13031/2013.17933
- Robert, P.C., R.H. Rust and W.E Larson. 1995. Preface, In Proc. Site-Specific Mgmt. for Agric. Sys., 27-30, Minneapolis, Minn.: ASA-CSSA-SSSA.
- Schepers, J.S., M.G. Moravek, E.E. Alberts and K.D. Frank. 1991. Maize production impacts on groundwater quality. Journal of Environmental Quality 20:12-16.
- Tumbo, S.D., D.G. Wagner and P. H. Heinemann. 2001. On-the-go sensing of chlorophyll status in corn. ASAE paper No. 01-1175. St. Joseph, Mich.: ASAE.
- van Es, H.M, and N.M. Trautmann. 1990. Pesticide management for water quality: Principles and Practices. Cornell University Natural Resources Cooperative Extension Fact Sheet. http://www.pmep.cce.cornell.edu.
- Waskom, R.M., D.G. Westfall, D.E. Spellman and P.N. Soltanpour, 1996. Monitoring nitrogen status of corn with a portable chlorophyll meter. Communications in Soil Science and Plant Analysis 27(3&4):54 560.