Source: UNIVERSITY OF NEBRASKA submitted to
APPLICATION OF GEOSPATIAL AND PRECISION TECHNOLOGIES
Sponsoring Institution
National Institute of Food and Agriculture
Project Status
TERMINATED
Funding Source
Reporting Frequency
Annual
Accession No.
0190201
Grant No.
2001-52103-11303
Project No.
NEB-12-286
Proposal No.
2001-04773
Multistate No.
(N/A)
Program Code
(N/A)
Project Start Date
Sep 15, 2001
Project End Date
Aug 14, 2006
Grant Year
2001
Project Director
Dobermann, A.
Recipient Organization
UNIVERSITY OF NEBRASKA
(N/A)
LINCOLN,NE 68583
Performing Department
AGRONOMY & HORTICULTURE
Non Technical Summary
Fertilizer is traditionally applied at uniform rates across fields because of time and cost considerations. However, because of the spatial variability of most landscapes, not all areas in the fields require the same levels of fertilizer. Both under- or over-application of nutrients affect the profitability of farming in corn-based cropping systems. Excessive nitrogen use on corn may result in elevated levels of N in ground and surface waters and increased emission of nitrous oxide into the atmosphere. The overall goal of this project is to increase the efficiency of site-specific management of primary plant nutrients and other soil properties and thereby increase the profitability of farming and decrease negative environmental impact. This project consists of two strategies. Soil-based approaches will focus on developing on-the-go sensors and advanced geostatistical techniques for soil mapping at high spatial resolution. Crop-based N management will focus on developing canopy reflectance thresholds for triggering in-season N applications and field testing of sensor/applicator systems in combination with imagery from satellites and aircraft. Interdisciplinary on-farm research will be conducted at several sites in Nebraska in close collaboration with producers, crop consultants, and data providing or engineering companies to ensure practicality of the developed tools and methods. The project will document acceptance of the technology, impacts on farm practice, and improvements in fertilizer use efficiency.
Animal Health Component
40%
Research Effort Categories
Basic
60%
Applied
40%
Developmental
(N/A)
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
1021510209030%
2057210106030%
9036030303010%
4045310202030%
Goals / Objectives
Develop technology for improved mapping of physical and chemical soil properties and quantify the costs and errors associated with different strategies. Develop objective procedures for integration of multiple layers of site-specific data for defining finite management elements (zones). Develop algorithms for triggering N applications on corn based on in-season canopy reflectance data in combination with N-adequate reference strips. Demonstrate the ability of high-clearance applicator systems to be a practical means for farmers to reduce total N applications. Assess the performance of site-specific management strategies and currently used techniques in research and commercial fields. Disseminate the developed tools and educate public and private sector professionals and producers in the science and engineering of site-specific nutrient management.
Project Methods
This project consists of two strategies: (a) improved acquisition and usage of thematic soil maps and (b) in-season nitrogen management of corn based on crop sensing. In years 1 and 2, research focuses on developing and validating (a) sensors for on-the-go mapping of soil properties, (b) geostatistical methods for uni- and multivariate mapping of soil properties and management zones at high spatial resolution, and (c) algorithms for triggering N applications on corn based on canopy reflectance. In years 3 and 4, developed tools and site-specific management strategies will be tested at several on-farm sites in Nebraska.

Progress 09/15/01 to 08/14/06

Outputs
Key outputs of this project were: 1. Two soil sensor platforms: (a) A tractor-based Integrated Soil Physical Properties Mapping System consisting of a mechanical sensor to detect spatial and depth variability of soil strength, a capacitor sensor to identify spatial changes in soil water content, and an optical sensor to address soil organic matter variability; Three different concepts were used while developing the mechanical components, including three in-line blades operating at different depth and two blades instrumented with strain gage arrays designed to sense soil profiles represented as a second-order polynomial, or assumed to change linearly with depth. (b) A modified Veris Mobile Sensor Platform (available commercially since 2003) equipped with a module for integrated direct or agitated (solution-based) measurement of soil pH, potassium and nitrate contents along with apparent electrical conductivity. A series of laboratory and field evaluation experiments was conducted to quantify precision and accuracy of the sensors developed and to determine their applicability for improved soil-based site-specific crop management. 2. A prototype high clearance tractor, configured with an active sensor system, and controller interfaced with sensors and electronic valves to deliver real time application of spatially variable fertilizer N rates to corn as determined by sensor readings. The active sensor used in this work is the Crop Circle model ACS-210, developed in collaboration with Holland Scientific (http://www.hollandscientific.com/). It measures crop canopy reflectance in two wavebands, amber (590 nm +/- 5.5 nm) and near infrared or NIR (880 nm +/-10 nm). Our results showed that sensor readings, expressed as chlorophyll index (index = ((NIR/Amber)-1), collected from corn canopies receiving varying amounts of N were highly correlated with independent chlorophyll meter assessment of canopy N status, when readings were collected after canopy closure and prior to tasseling. Sensor readings were also highly associated with grain yield. A sensor algorithm was developed that can be used in determining the appropriate spatially variable rate of in-season N based on sensor determined crop need. This alternative scheme was shown to reduce total N application vs. a traditional corn N management approach, utilizing uniform preplant application of N. 3. New algorithms for spatial data processing for precision farming: (a) a complete sequence of methods for processing yield maps into yield-based, spatially contiguous management zones; (b) algorithms for fine-resolution mapping of soil properties based on optimized sampling and spatially dense, readily available secondary information; (c) a new algorithm for spatially constrained classification of categorical and continuous soil properties that can be used to form contiguous management zones. 4. Field testing of variable rate N application based on fine-resolution maps of soil organic matter and yield goals determined by management zones resulted in increased N use efficiency of high-yielding, irrigated corn, but only modest gains in yield and overall profitability.

Impacts
The techniques, decision tools and management strategies developed in this project will allow producers to acquire better spatial information of their fields and fine-tune applications of production inputs such as lime or nitrogen fertilizers within a field, both in terms of pre-plant as well as in-season applications. Results were disseminated to producers, crop consultants, students and industry professionals through field days, eight extension training courses on precision agriculture, an undergraduate course on site-specific crop management taught at UNL, and a series of precision agriculture extension publications. Soil and crop sensor development work was done in close collaboration with the private sector.

Publications

  • Adamchuk, V.I., M.T. Morgan, and S.M. Brouder. 2006. Analysis of variability in automated soil pH measurements. Applied Engineering in Agriculture 22(3): 335 344.
  • Adamchuk, V.I., E. Lund, B. Sethuramasamyraja , M.T. Morgan, A. Dobermann, and D.B. Marx. 2005. Direct measurement of soil chemical properties on-the-go using ion-selective electrodes. Computers and Electronics in Agriculture 48(3): 272-294.
  • Adamchuk, V.I., J.W. Hummel, M.T. Morgan, and S.K. Upadhyaya. 2004. On-the-go soil sensors for precision agriculture. Computers and Electronics in Agriculture 44(1): 71 91.
  • Adamchuk, V.I. and P.T. Christenson1. 2005. An integrated system for mapping soil physical properties on-the-go: the mechanical sensing component. In: Precision Agriculture: Papers from the Sixth European Conference on Precision Agriculture, Uppsala, Sweden, 9-12 June 2005, 449-456. J. Stafford, ed. Wageningen, The Netherlands: Wageningen Academic Publishers.
  • Adamchuk, V.I. 2006. Characterizing soil variability using on-the-go sensing technology. Site-Specific Management Guidelines SSMG-44. Norcross, Georgia: Potash and Phosphate Institute.
  • Adamchuk, V.I. and J. Mulliken. 2005. Site-specific management of soil pH (FAQ) Precision Agriculture Extension Circular EC 05-705. Lincoln, Nebraska: University of Nebraska Cooperative Extension.
  • Adamchuk, V.I., A. Dobermann, and J. Ping. 2004. Listening to the story told by yield maps. Precision Agriculture Extension Circular EC 04-704. Lincoln, Nebraska: University of Nebraska Cooperative Extension.
  • Dobermann, A., Ping, J.L., V.I. Adamchuk, G.C. Simbahan, and R.B. Ferguson. 2003. Classification of yield variability for site-specific management. Agron. J. 95, 1105-1120. Dobermann, A., and J.L. Ping. 2004. Geostatistical integration of yield monitor data and remote sensing improves yield maps. Agron. J. 96, 285-297.
  • Martin, K.L., P.J. Hodgen, K.W. Freeman, R. Melchiori, D.B. Arnall, R.K. Teal, R.W. Mullen, K. Desta, S.B. Phillips, J.B. Solie, M.L. Stone, O. Caviglia, F. Solari, A. Bianchini, D.D. Francis, J.S. Schepers, J. L. Hatfield, and W.R. Raun. 2005. Plant-to-plant variability in corn production. Agron. J. 97:1603-1611.
  • Ping, J.L., and A. Dobermann. 2003. Creating spatially contiguous yield classes for site-specific management. Agron. J. 95: 1121-1131.
  • Ping, J.L. and A. Dobermann. 2005. Processing of yield map data. Precision Agric. 6, 193-212.
  • Ping, J.L., and A. Dobermann. 2006. Variation in the precision of soil organic carbon maps due to different laboratory and spatial prediction methods. Soil Sci. 171, 374-387.
  • Raun, W.R., J.B. Solie, M.L. Stone, K.L. Martin, K.W. Freeman, R.W. Mullen, H. Zhang, J.S. Schepers, and G.V. Johnson. 2005. Optical sensor based algorithm for crop nitrogen fertilization. Commun. Soil Sci. Plant Anal. 36:2759-2781.
  • Schepers, A., J.F. Shanahan, M. A. Liebig, J.S. Schepers, S. Johnson, and A. Luchiari. 2004. Appropriateness of management zones for characterizing spatial variability of soil properties and corn yields across years. Agron. J. 96:195-203.
  • Schepers, J. S. and J. F. Shanahan. 2005. Variable-rate nitrogen management: One option for better profits. Fluid J. 13:20-23.
  • Schlemmer, M.S., D.D. Francis, J.F. Shanahan, and J. S. Schepers. 2005. Remotely measuring chlorophyll content in corn leaves with differing N. Agron. J. 97: 106-112.
  • Shanahan, J.F., K. Holland, J.S. Schepers, D.D. Francis, M.R. Schlemmer, and R. Caldwell. 2003. Use of crop reflectance sensors to assess corn leaf chlorophyll content. p. 129-144. In (ed. T. VanToai, D. Major, M. McDonald, J. Schepers, and L. Tarpley) Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology. ASA Special Pub. 66. ASA, Madison, WI.
  • Siefken, R.J., V.I. Adamchuk, D.E. Eisenhauer, and L.L. Bashford. 2005. Mapping soil mechanical resistance with a multiple blade system. Applied Engineering in Agriculture 21(1): 15-23.
  • Simbahan, G.C., A. Dobermann, and J.L. Ping. 2004. Screening yield monitor data improves grain yield maps. Agron. J. 96, 1091-1102.
  • Simbahan, G.C., A. Dobermann, P. Goovaerts, J.L. Ping, and M.L. Haddix. 2006. Fine-resolution mapping of soil organic carbon based on multivariate secondary data. Geoderma 132, 471-489.
  • Simbahan, G.C., and A. Dobermann. 2006. Sampling optimization based on secondary information and its utilization in soil carbon mapping. Geoderma 133, 345-362.
  • Simbahan, G.C., and A. Dobermann. 2006. An algorithm for spatially constrained classification of categorical and continuous soil properties. Geoderma. (in press).


Progress 10/01/04 to 09/30/05

Outputs
Completed strip trials on evaluating different strategies for site specific management at three on-farm sites. Treatments focused on variable rate plant density in combination variable rate N and P management. Our results showed that only small gains in yield, nutrient use efficiency and profit can be achieved through common site-specific management concepts that focus on managing of spatial variability alone. A combination of managing spatial variability and temporal variation in crop demand is required. Demonstrated new approaches for increasing the accuracy of soil attribute maps through the use of spatially-dense secondary information. Continued development and testing of on-the-go soil sensors (pH, nitrate, potassium, compaction) and on-the-go crop N sensors for variable rate N application. Numerous technical issues were resolved and laboratory and field testing is ongoing.

Impacts
The techniques, decision tools and management strategies developed in this project will allow producers to fine-tune applications of production inputs such as nitrogen within a field, both in terms of pre-plant as well as in-season applications. Results are disseminated in extension events and publications.

Publications

  • Adamchuk, V.I., E. Lund, B. Sethuramasamyraja, M.T. Morgan, A. Dobermann, and D.B. Marx. 2005. Direct measurement of soil chemical properties on-the-go using ion-selective electrodes. Computers and Electronics in Agriculture 48, 272-294.
  • Adamchuk, V.I., A.V. Skotnikov, J.D. Speichinger, and M.F. Kocher. 2004. Technical note: Development of an instrumented deep-tillage implement for sensing of soil mechanical resistance. Transactions of the ASAE 47(6):1913-1919.
  • Adamchuk, V.I. and P.T. Christenson. 2005. An integrated system for mapping soil physical properties on-the-go: the mechanical sensing component. In: Precision Agriculture: Papers from the Sixth European Conference on Precision Agriculture, Uppsala, Sweden, 9-12 June 2005, 449-456. J. Stafford, ed. Wageningen, The Netherlands: Wageningen Academic Publishers
  • Lund, E.D., V.I. Adamchuk, K.L. Collings, P.E. Drummond, and C.D. Christy. 2005. Development of soil pH and lime requirement maps using on-the-go soil sensors. In: Precision Agriculture: Papers from the Sixth European Conference on Precision Agriculture, Uppsala, Sweden, 9-12 June 2005, 457-464. J. Stafford, ed. Wageningen, The Netherlands: Wageningen Academic Publishers.
  • Adamchuk, V.I. and J. Mulliken. 2005. Site-specific management of soil pH (FAQ) Precision Agriculture extension circular EC 05-705. Lincoln, Nebraska: University of Nebraska Cooperative Extension.
  • Ping, J.L. and A. Dobermann. 2005. Processing of yield map data. Precision Agric. 6, 193-212.
  • Sethuramasamyraja, B., V.I. Adamchuk, D.B. Marx, and A. Dobermann. 2005. Evaluation of ion-selective electrode based measurement methodology for integrated on-the-go mapping of soil chemical properties (pH, K & NO3). ASAE paper no. 05-1036.
  • Simbahan, G.C., A. Dobermann, P. Goovaerts, J.L. Ping, and M.L. Haddix. 2006. Fine-resolution mapping of soil organic carbon based on multivariate secondary data. Geoderma. doi:10.1016/j.geoderma.2005.07.001
  • Simbahan, G.C., and A. Dobermann. 2006. Sampling optimization based on secondary information and its utilization in soil carbon mapping. Geoderma. doi:10.1016/j.geoderma.2005.07.020
  • Schlemmer, M.R., D.D. Francis, J.F. Shanahan, and J.S. Schepers. 2005. Remotely measuring chlorophyll content in corn leaves with differing nitrogen levels and relative water content. Agron. J. 97:106-112
  • Siefken, R.J., V.I. Adamchuk, D.E. Eisenhauer, and L.L. Bashford. 2005. Mapping soil mechanical resistance with a multiple blade system. Applied Engineering in Agriculture 21(1):15-23.
  • Stamtiadis, S., C. Tsadilas, and J.S. Schepers. 2004. Real-time crop sensors. p. 128-135. In Remote Sensing for Agriculture and the Environment. S. Stamadiadis, J.M. Lynch, and J.S. Schepers, (eds.) Peripheral Editions, Larissa Greece
  • Schepers, J.S. 2004.Integrating remote sensing and ancillary information into management systems. p. 254-259. In Remote Sensing for Agriculture and the Environment. S. Stamadiadis, J.M. Lynch, and J.S. Schepers, (eds.) Peripheral Editions, Larissa Greece


Progress 10/01/03 to 09/30/04

Outputs
The Mobil Sensor Platform (Veris Technologies) was equipped with monitoring and data acquisition equipment for field tests. Mapping of soil pH and EC was done in several fields. Time response of ion-selective electrodes was studied and an algorithm for response prediction based on the initial 10 s data was developed. Improved contact between ion-selective electrodes and soil was created using a newly designed electromechanical electrode holder. A new blade for mapping of soil mechanical resistance with depth was developed and tested in laboratory and field trials. A comparison between the integrated measurements of soil mechanical resistance and cone penetrometer resistance resulted in r2 = 0.95 for twelve treatments. A comprehensive agro-economical model for evaluating soil sensors and other precision farming technologies was completed. Evaluated geostatistical methods for fine-scale mapping of soil properties based on secondary information such as digital elevation models, satellite images, and on-the-go sensed soil EC. Simple kriging with varying local means outperformed ordinary kriging. However, the improvement depended on the correlation between primary and secondary variables and spatial structure of the residuals from the regression analysis. Developed an algorithm for spatially constrained cluster analysis using mixed categorical and numeric variables. Developed a new method for optimizing sampling based on secondary information. In this, secondary information is used for stratifying a field into contiguous spatial clusters and stratified sampling schemes are optimized by constrained spatial simulated annealing. This approach increased the precision of soil carbon maps with a reduction in sample size. In strip trials with different site-specific plant density x nutrient management strategies, there were no significant differences in yields and economic returns among the four treatments. However, differences existed among the yield goal zones established for each site. Analysis of corn yields from a production-scale on-farm trial showed agronomic benefits from in-season fertilizer applications, varying with location. Red-band and green-band GreenSeeker sensors, used to measure red NDVI and green NDVI, respectively, were evaluated. The orientation of the sensors relative to the corn plants had an effect on the reflectance readings obtained. Corn biomass was poorly predicted by green NDVI alone, but was predicted as a function of green NDVI and plant height. To use green NDVI for early season applications, a measure of plant height will be needed to augment the reflectance data. When collecting data using tractor-based plant reflectance sensors, sensor position and view direction relative to plant height and row direction should be recorded. Plant height sensors should be developed for systems that use green NDVI for N application early in the season. The nadir position appears superior to off-nadir positions. Our suggestion for the ACS-210 sensor is to work in the range between 60 and 110 cm above the canopy. Care must be taken to maintain a consistent distance or to understand the influence of variable distance on sensor readings.

Impacts
The techniques, decision tools and management strategies developed in this project will allow producers to fine-tune applications of production inputs such as nitrogen within a field, both in terms of pre-plant as well as in-season applications. A Nebraska Agricultural Technologies Association (NeATA) subcommittee was formed to oversee and direct our on-farm research activities. Monthly public Precisison Ag lunch meetings with topics on use of electrical conductivity data and crop modeling for site-specific management are held. Results are disseminated in extension events and publications.

Publications

  • Adamchuk, V.I., A. Dobermann, and J. Ping. 2004. Listening to the story told by yield maps. Precision Agriculture extension circular EC 04-704. Lincoln, Nebraska: University of Nebraska Cooperative Extension.
  • Adamchuk, V.I., J.W. Hummel, M.T. Morgan, and S.K. Upadhyaya. 2004. On-the-go soil sensors for precision agriculture. Computers and Electronics in Agriculture 44: 71-91.
  • Brouder, S.M., M. Thom, V.I. Adamchuk, and M.T. Morgan. 2003. Potential uses of ion-selective K electrodes in soil fertility management. Communications in Soils Science and Plant Analysis 34(19-20):2699-2726.
  • Christenson, P.T., V.I. Adamchuk, and M.F. Kocher. 2004. Instrumented blade for mapping soil mechanical resistance. Paper No. 04-1038. St. Joseph, Michigan: ASAE.
  • Dobermann, A., B.S. Blackmore, S.E. Cook, and V.I. Adamchuk. 2004. Precision farming: challenges and future directions. In T. Fischer et al. (ed.) New directions for a diverse planet. The Regional Institute Ltd, Gosford, NSW [CD ROM].
  • Dobermann, A., and J.L. Ping. 2004. Geostatistical integration of yield monitor data and remote sensing improves yield maps. Agron. J. 96, 285-297.
  • Ferguson, R.B., A. Dobermann, C.S. Wortmann, D.T. Walters, C.A. Shapiro, D. Tarkalson, and D.D. Baltensperger. 2004. Developing recommendations for site-specific nitrogen management of irrigated maize. In Proceedings of the 7th International Conference on Precision Agriculture and Other Resource Management, July 25-28, 2004, Bloomington, MN. ASA, CSSA, SSSA, Madison, WI [CD-ROM].
  • Ping, J.L., and A. Dobermann. 2004. Utilizing fine-scale secondary information for improving maps of soil attributes. In Proceedings of the 7th International Conference on Precision Agriculture and Other Resource Management, July 25-28, 2004, Bloomington, MN. ASA, CSSA, SSSA, Madison, WI [CD-ROM].
  • Simbahan, G.C., A. Dobermann, and J.L. Ping. 2004. Screening yield monitor data improves grain yield maps. Agron. J. 96: 1091-1102
  • Schepers, A., J. F. Shanahan, M. A. Liebig, J.S. Schepers, S. Johnson, and A. Luchiari. Agron. J. Appropriateness of management zones for characterizing spatial variability of soil properties and corn yields across years. Agron. J. 96:195-204. 2004.
  • Shanahan, J.F., K.H. Holland, J.S. Schepers, D.D. Francis, M.R. Schlemmer, and R. Caldwell. 2003. Use of a crop canopy reflectance sensor to assess corn leaf chlorophyll content. p. 129-144. In: Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology. ASA Special Pub. 66. ASA, Madison, WI.
  • Shanahan, J.F., J.S. Schepers, and R. Caldwell. 2004. Use of New Remote Sensing Technologies to Optimize Nitrogen Applications to Corn at Monitoring. In Proceedings of Science and Technology Symposium held from Sept. 20-24, 2004 in Denver, CO.
  • Shanahan, J. F., J.S. Schepers, D.D. Francis, R. Caldwell. Use of crop canopy reflectance sensor for in-season N management of corn. 2004. In Proceedings of Great Plains Soil Fertility Conference, March 2-3, 2004, Denver, CO. Potash and Phosphate Institute, Brookings, SD. 10:69-74.
  • Adamchuk, V.I., R.D. Grisso, and M.F. Kocher. 2004. Machinery performance assessment based on records of geographic position. Paper No. 04-1149. St. Joseph, Michigan: ASAE.
  • Adamchuk, V.I., C. Wang, D.B. Marx, R.K. Perrin, and A. Dobermann. 2004. Assessment of soil mapping value - potential profitability (Part II). In Proceedings of the 7th International Conference on Precision Agriculture and Other Resource Management, July 25-28, 2004, Bloomington, MN. CD-ROM. ASA, CSSA, SSSA, Madison,WI [CD-ROM].
  • Adamchuk, V.I., M.T. Morgan, and J.M. Lowenberg-DeBoer. 2004. A model for agro-economic analysis of soil pH mapping. Precision Agriculture, 5:109-127.


Progress 10/01/02 to 09/30/03

Outputs
An integrated soil physical properties mapping system was tested under field conditions, showing that soil mechanical resistance compensated for soil friction variation. A new data-acquisition system for recording outputs of four ion-selective electrodes simultaneously was developed and used to study electrode response. Several laboratory studies were conducted to evaluate the performance of ion-selective electrodes as potential on-the-go soil sensors. A stationary test on evaluation of pH, potassium, nitrate and sodium ion-selective electrodes was conducted using a pre-commercial prototype of the automated soil pH mapping system (Veris Technologies, Salina, Kansas). The program DM_Comp for soil sensors performance assessment was developed and used to analyze soil resistance maps. DM_Comp is a stand-alone software that can be used to combine various common sources of spatial data such as yield, soil laboratory analysis or electrical conductivity maps. Work continued on developing a procedure for post-processing of yield monitor data. A new algorithm of raw data screening improved the precision of interpolated yield maps by 5 to 10% as compared to only a basic filtering embodied in most commercial yield processing software packages. Techniques for geostatistical integration of yield monitor and remote sensing were evaluated, showing that the combined use of both data sources further increased map precision. Previously developed methods for yield data classification and mapping of yield zones were further evaluated and formed the basis for conducting strip trials with different site-specific plant density x nutrient management strategies at two sites. At the MSEA experimental site near Shelton, Nebraska, five experiments were conducted to study relationships between crop canopy reflectance, plant spacing and nitrogen rates in different corn hybrids and to evaluate different strategies for N management. Sensor data in June from the Rotation Study and the Plant Spacing study confirmed that green NDVI (gNDVI) is a better indicator of plant nitrogen status (as shown by SPAD meter readings) than red NDVI (rNDVI) during our target window for operation, i.e., between V10 and R2. We successfully demonstrated a simple, low-cost system for in-season N application based on sensing the crop's nitrogen need. In the system color infrared aerial photography was rectified and transformed to green NDVI. The average green NDVI observed within adequately fertilized areas was used as the denominator in an N sufficiency ratio calculated for the green NDVI values throughout the field. An outreach program on offering airborne imagery and its interpretation to producers was conducted in collaboration with NEATA.

Impacts
The techniques, decision tools and management strategies developed in this project will allow producers to fine-tune applications of production inputs such as nitrogen within a field, both in terms of pre-plant as well as in-season applications. A Nebraska Agricultural Technologies Association (NeATA) subcommittee was formed to oversee and direct our on-farm research activities. Monthly public Precisison Ag lunch meetings with topics on use of electrical conductivity data and crop modeling for site-specific management were held.

Publications

  • Adamchuk, V.I. 2003. Understanding the GPS data string. Part 1: Viewing and interpreting the data. GPS User Magazine 1(1):28-30
  • Adamchuk, V.I. and P.J. Jasa. 2002. On-the-Go Vehicle-Based Soil Sensors. University of Nebraska Cooperative Extension EC 02-178.
  • Adamchuk, V.I., Lund, E., Dobermann, A., Morgan, M.T., 2003. On-the-go mapping of soil properties using ion-selective electrodes. In: Stafford, J.V., Werner, A. (Ed.), Precision agriculture. Wageningen Academic Publishers, Wageningen, pp. 27-33.
  • Adamchuk, V.I., A.V. Skotnikov, J.D. Speichinger, and M.F. Kocher. 2003. Instrumentation system for variable depth tillage. Paper No. 03-1078. St. Joseph, Michigan: ASAE.
  • Casady, W.W. and V.I. Adamchuk. 2003. Global positioning system and GPS receivers in agriculture. In: Encyclopedia of Agricultural, Food, and Biological Engineering, 444-446. D.R. Heldman, ed. New York, New York: Marcel Dekker, Inc.
  • Dobermann, A., and J.L. Ping. 2004. Geostatistical integration of yield monitor data and remote sensing improves yield maps. Agron. J. (in press).
  • Dobermann, A, Ping, J.L., V.I. Adamchuk, G.C. Simbahan, R.B. Ferguson. 2003. Classification of yield variability for site-specific management. Agron. J. 95, 1105-1120.
  • Dobermann, A., Ping, J.L., Simbahan, G.C., Adamchuk, V.I., 2003. Processing of yield map data for delineating yield zones. In: Stafford, J.V., Werner, A. (Ed.), Proc. 4th European Conference on Precision Agriculture. Wageningen Academic Publishers, Wageningen, pp. 177-185.
  • Osborne, S.L., J.S. Schepers, D.D. Francis, and M.R. Schlemmer. 2002. Use of spectral radiance to estimate in-season biomass and grain yield in nitrogen- and water-stressed corn. Crop Sci. 42:165-171.
  • Osborne, S.L., J.S. Schepers, D.D. Francis, and M.R. Schlemmer. 2002. Detection of Phosphorus and Nitrogen Deficiencies in Corn Using Spectral Radiance Measurements. Agron. J. 94:1215-1221. Ping, J.L., and A. Dobermann. 2003. Creating spatially contiguous yield classes for site-specific management. Agron. J. 95: 1121-1131.
  • Schepers, J.S., S. Payton, D.D. Francis, and J. Shanahan. 2003. Improving nutrient management via evolving strategies and new technologies. Fluid J. 41:18-22.


Progress 10/01/01 to 09/30/02

Outputs
Soil sensing: A new mechanical soil resistance mapping unit has been developed and calibrated. Preliminary tests evaluating its field performance have been conducted. Fifteen soils from various locations in Nebraska were collected, and analyzed in several commercial soil laboratories to be used for sensor calibration. Sets of ion-selective electrodes (pH, K and NO3) have been obtained and tested in laboratory studies. Soil mapping: Exhaustive soil sampling was conducted in three production fields. All sites represent ridge-till irrigated maize systems, but with different soil types and topography. New geostatistical techniques for thematic high-resolution mapping of soil properties were evaluated. The use of spatially dense secondary information such as a digital elevation model (DEM) on-the-go sensed electrical conductivity (Veris sensor), bare soil imagery (either digital orthophotographs or IKONOS satellite images), and digital soil type maps in combination with destructive soil sampling greatly increased the obtainable precision of soil carbon (C) maps. At all sites, the best techniques increased the relative map precision by about 20 to 25% over commonly used ordinary kriging. A general procedure for post-processing of yield monitor data was developed and tested at two sites. The proposed new procedure involves (i) cleaning of yield monitor data of at least 5 years, (ii) standardization, (iii) interpolation to 4 m x 4 m cells, (iv) averaging across years, (v) classification using fuzzy-k-means or standard cluster analysis techniques, and (vi) post-classification spatial filtering to create yield zones. Crop-based N management: Fifty one datasets have been collected this year from Holland Scientific's passive crop canopy reflectance sensor system, a new experimental hyperspectral system, and the GreenSeeker active sensor system. The datasets were collected from a series of large-scale and small-scale field experiments. Color infrared aerial photography was acquired for the field experiments on three dates so far this year. A draft of the overall design and engineering requirements for the sensor/controller/fertilizer application system has been completed. A prototype system has been constructed in our lab for testing the performance of our hardware and software.

Impacts
A Nebraska Agricultural Technologies Association (NeATA) subcommittee was formed to oversee and direct our corn nitrogen research activities. Maps produced by the new yield mapping techniques will allow producers to spatially vary yield goals within a field, which is a major requirement for variable-rate prescriptions. The new carbon mapping techniques are expected to have large impact on monitoring of soil C sequestration at production scales.

Publications

  • Dobermann, A., and K.G. Cassman. 2002. Plant nutrient management for enhanced productivity in intensive grain production systems of the United States and Asia. Plant Soil 247:153-175.
  • Cassman, K.G., A. Dobermann, and D.T. Walters. 2002. Agroecosystems, nitrogen-use efficiency, and nitrogen management. Ambio 31:132-140.
  • Johnson, C.K., J.W. Doran, H.R. Duke, B.J. Wienhold, K.M. Eskridge, and J.F. Shanahan. 2001. Field-scale electrical conductivity mapping for delineating soil condition. Soil Sci. Soc. Am. 2001. 65:1829-1837.
  • Schepers, J.S., J.F. Shanahan, and A. Luchiari, Jr. 2001. Real-time sensors for crop stresses. Proceedings of the Third Internationals Conference on Geospatical Information in Agriculture and Forestry, November 5-7, Denver, CO. (conference proceedings on CD)
  • White, J.D., J.D. Corbett, and A. Dobermann. 2002. Insufficient geographic characterization and analysis in the planning, execution and dissemination of agronomic research? Field Crops Res. 76:45-54.
  • Adamchuk, V.I., D.B. Marx, and M.T. Morgan. 2002. Numeric Assessment of Soil Mapping Value: Part I. Error Evaluation. Proc. 6th International Conference on Precision Agriculture and Other Precision Resources Management, Minneapolis, Minnesota (in press).
  • Adamchuk, V.I., A. Dobermann, and M.T. Morgan. Feasibility of on-the-go mapping of soil nitrate and potassium using ion-selective electrodes. ASAE Meeting Paper No. 021183, ASAE, St. Jospeh, MI. Presented at the 2002 ASAE Annual International Meeting / CIGR World Congress, Chicago, IL


Progress 10/01/00 to 09/30/01

Outputs
Funds were received by late September and detailed planning of research has started. Final selection of three on-farm research sites was completed. Soil characterization work was initiated. The search for a PostDoctoral Scientist has been initiated.

Impacts
(N/A)

Publications

  • No publications reported this period