Annual/Termination Reports:

[03/01/2007] [03/10/2008] [02/19/2009] [03/09/2010] [05/22/2011]

Report Information

Participants

Bullock, Don (University of Illinois), dbullock@uiuc.edu;
Burris, Eugene (Louisiana State University), eburris@agcenter.lsu.edu;
Clay, David (South Dakota State University), david.clay@sdstate.edu;
Ehsani, Reza (University of Florida), ehsani@ufl.edu;
Erickson, Bruce (Purdue University), berickso@purdue.edu;
Ferguson, Richard (University of Nebraska), rferguson1@unl.edu;
Francis, Dennis (USDA-ARS, Lincoln, Nebraska), dfrancis1@unl.edu;
Franzen, David (North Dakota State University), david.franzen@ndsu.edu;
Heiniger, Ronnie (North Carolina State University), ron_heiniger@ncsu.edu;
Khosla, Raj (Colorado State University), raj.khosla@colostate.edu;
Kitchen, Newell (USDA-ARS, Missouri), kitchen@missouri.edu;
Lee, Wonsuk Daniel (University of Florida), wslee@ufl.edu;
Lund, Eric (Veris Tech), lunde@veristech.com;
Morris, Keith (Louisiana State University), kmorris@agcenter.lsu.edu;
Mulla, David (University of Minnesota), mulla003@umn.edu;
Reetz, Harold (Foundation for Agronomic Research), hreetz@ppi-far.org;
Parks, Sid (Growmark), sparks@growmark.com;
Pierce, Fran (Washington State University), fjpierce@wsu.edu;
Rudolph, William (TeeJet Industries), wrudolph@mid-tech.com;
Saraswat, Dharmendra (University of Florida), saraswat@ufl.edu;
Schueller, John (University of Florida), schuejk@ufl.edu;
Sethuramasamyraja, Balaji (Cal Poly Fresno), balajis@csufresno.edu;
Shanahan, John (USDA-ARS Lincoln, Nebraska), jshanahan1@unl.edu;
Stanford, Jill (John Deere, Inc), StanfordJillM@JohnDeere.com;
Stombaugh, Tim (University of Kentucky), tstomb@bae.uky.edu;
Sudduth, Ken (USDA-ARS Columbia, Missouri), sudduthk@missouri.edu;
Thelen, Kurt (Michigan State University), thelen3@msu.edu;
Tian, Lei (University of Illinois), lei-tian@uiuc.edu;
Ting, K. C. (University of Illinois), kcting@uiuc.edu;
Upadhyaya, Shrini (University of California-Davis), skupadhyaya@ucdavis.edu;
Watermeier, Nathan (Ohio State University Extension), watermeier.2@osu.edu;
Westfall, Dwayne (Colorado State University), dwayne.westfall@colostate.edu;
Willers, Jeff (USDA-ARS, Mississippi), jlwillers@ars.usda.gov;
Wollenhaupt, Nyle (AGCO Global Tech), nyle.wollenhaupt@agcocorp.com;

Brief Summary of Minutes

Minutes of NCERA-180 (Site-Specific Management)
Kissimmee, Florida
January 4-6, 2007
Hosts: John Schueller and Wonsuk Daniel Lee

Members of the Committee spent January 4 touring a tangerine juice processing plant, the University of Florida Citrus Research and Education Center, a citrus grove with automated harvest equipment, and a supermarket food distribution warehouse.

The remaining time, from January 5-6, was spent by committee members in technical and business meetings discussing Site-Specific Management activities.

Friday, January 5, 2007

John Schueller and Daniel Lee opened the meeting and described the agenda.

Jeff Willers (USDA-ARS, Mississippi) presented his research on Spatial Information and the Design and Analysis of Site-Specific Experiments in Commercial Cotton Fields. He introduced methods for testing the efficiency of Site-Specific Management (SSM) in commercial fields using remote sensing, GIS and topological relationships between spatial data layers. Experimental units for analysis were delineated by the intersection of rate of cotton plant growth regulator applied and management zones. A statistical model was developed to model yield as a function of treatment effects, spray path, planter path, harvester path, and topography.

Jim Jones (University of Florida) presented his thoughts on the application of crop simulation modeling to Site-Specific Management (SSM). There have been few papers published on the use of crop simulation models in SSM. Batchelor and Paz (1999) calibrated a CERES model to soil moisture for an Iowa field and used it to predict soybean yield along a transect. Basso et al. (2001) used remote sensing to identify management zones and used crop simulation modeling to predict yield in each zone. Batchelor and Paz (2000) used inverse modeling to estimate spatial variability in input factors for a model of soybean yield. Fraisse et al. (2001) used the CERES model to study variations in yield as a function of topsoil depth in claypan soils of Missouri. Miao et al. (2006) used crop simulation modeling to evaluate nitrogen fertilizer management strategies for management zones in Illinois. New approaches were discussed for obtaining spatially variable model inputs, including remote sensing, inverse modeling, sensors, geostatistics, Kalman filtering and principal components analysis.

K. C. Ting (University of Illinois) gave the Administrators Report. NCERA-180 was renewed for another 5 years (2006-2011), and is set up to integrate education, research and teaching. Within 60 days of meeting (March 7) the SAES-442 form must be submitted to the NIMSS online system. Committee participants can be contacted using the NIMSS website: http://www.nimss.umd.edu

David Mulla (University of Minnesota) and Raj Khosla (Colorado State University) discussed the upcoming 2008 International Conference on Precision Agriculture (ICPA). The venue for the conference is being changed to Colorado for at least 2008 and 2010 (probably Denver). David Mulla discussed the rationale for moving the conference. The NCERA-180 committee was asked to make suggestions for improving the conference. It was felt that the A to Z portion of the conference was weaker than the rest of the program. The strength of the conference is in multidisciplinary technical papers, but there is a need to attract a wider diversity of scientists and limit the number of concurrent sessions. It was felt that the conference should meet at a time which doesnt conflict with ASABE or SWCS. It was felt that NCERA-180 could assist the process of putting on the ICPA by developing a conference planning committee.

Don Bullock (University of Illinois) talked about Residuals and the Year to Year Variable in Precision Agriculture Research. He asked the question: How long do we need to run an experiment? More specifically: How does uncertainty in true nitrogen (N) fertilizer rate change over time?, and What is the cost of not knowing the true N fertilizer rate? To answer these questions he analyzed data from 21 years of small plot fertilizer rate trials in continuous corn conducted in Monmouth, IL. Using all the data, the mean optimum N rate was 173 kg/ha, with a standard deviation of 86 kg/ha. Monte Carlo simulation was used to pick 2, 4, or 12 years of data at random. Results showed that standard deviations of optimum N rate decreased as the number of years increased. Roughly five years of data were needed to adequately estimate the uncertainty in optimum N rate.

Don Bullock also talked about the importance of compensating for spatial correlation of residuals from field trials. He compared ordinary least squares (OLS), nearest-neighbor (NN), spatial auto-regressive (SAR) approaches (lag vs queen), and SAS PROC MIXED models. OLS failed to adequately compensate for spatial correlation of residuals based on semivariograms of residuals. NN methods were better at compensating for spatially correlated errors. SAR lag and queen models were better than NN methods.

Richard Ferguson (University of Nebraska) talked about Management Zone Delineation using example datasets for iron chlorosis in Nebraska soybean fields. He described four experiments where Pioneer cultivar 33V08 was tested for its resistance to iron chlorosis. Normalized Difference Vegetative Indices (NDVI), electrical conductivity (EC), soil pH and historical yield were best at delineating zones susceptible to iron chlorosis. It was difficult to separate the effects of water stress from iron chlorosis. There were few differences in yield between susceptible and tolerant varieties.

Eric Lund (Veris Tech) talked about a Near Infrared (NIR) spectrophotometer that collects data in 8 nm bands from 500-900 nm and from 1100-2200 nm. Light and dark references are collected automatically. NIR is used to estimate soil organic carbon, N, C/N, pH, Ca, Mg, P, K, CEC and moisture. It is best at measuring C, but is not as accurate for P and K.

William Rudolph (TeeJet Tech) talked about Centerline Guidance Devices and Field Pilot Automatic Steering Systems. He also talked about Swath Manager to turn on and off boom sections depending on whether the area was previously sprayed. TeeJet is developing a controller area network (CAN) based on ISO BUS ISO 11783 open standard to control all these devices.
Tony DiPollina (GeoAgro) talked about GIS software for precision agriculture in Brazil and Argentina. The software allows Word or Excel documents to be georeferenced by polygons on a map. The software allows GPS data to be displayed and stored. They also have a Conservation Planner designed to access NRCS conservation data from any wireless location.

Nyle Wollenhaupt (AGCO Global Tech) talked about ISO BUS standardized hardware (plugs and cables) and software (type and method of data exchange) protocols. AGCO is developing virtual terminals, ISO connectors, CAN BUS (ISO 11783), tractor electronic control unit (ECU), and task controller (defines how data moves). They also have an implement BUS which is used to compile fuel consumption and wheel slip.

Harold Reetz (Foundation for Agronomic Research) talked about the reorganization of PPI into the International Plant Nutrition Institute. IPNI has 17 charter members and covers N, P, K and all other plant nutrients. FAR provides funding for IPNI, and works with universities on multi-state research, special initiatives and corporate directed projects. It also is involved in educational conferences, computer training, tours and the Info Ag conference. FAR is seeking cooperators and partnerships with universities, to help build research teams, coordinate research and leverage contributions. FAR currently has a NRCS-CIG project on fertilizer BMPs with N. Dakota, Illinois, New York, Kansas, Idaho and Arkansas. FAR is trying to raise funds to support agronomic research.

Newell Kitchen (USDA-ARS, Missouri) talked about Division A-8 Integrated Ag Systems as a venue for symposia and papers on precision agriculture at the annual meetings of the Agronomy Society of America (ASA). Div. A-8 (David Clay- S. Dakota) is organizing a symposium on precision agriculture at the upcoming ASA meetings in New Orleans Nov 4-8, 2007.

Tim Stombaugh (University of Kentucky) talked about the PM-54 committee of ASABE, which usually has 75 papers on precision agriculture. The next meeting of ASABE is June 17-20, 2007 in Minneapolis. They have worked on new standards, including yield monitor test protocols for the laboratory and field. They are also working on a GPS position accuracy standard for moving units, as well as standards for autosteer accuracy.

Saturday, January 6, 2007

John Schueller (University of Florida) led a group discussion on the mission of NCERA-180. He raised several questions: Why is the adoption of Site-Specific Management (SSM) so slow? How can we provide better leadership in SSM? What synergistic activities in SSM are possible? Reactions to these questions included: We have too much data, how can we make it more useable and cheaper? The science of SSM is lagging technology. Farmers are asking what time it is, but were telling them how a clock works. Funding for SSM research (USDA-IFAFS) has declined.

There was concern that conservation programs and practice standards at USDA-NRCS doesnt support precision agriculture as a BMP. It was suggested that a representative from NRCS should be invited to attend the NCERA-180 meeting to address this issue. Keith Morris (Louisiana) said that their state conservationist approved cost-sharing for grid sampling and yield monitoring. A two page proposal was developed for a new 590 practice standard. Newell Kitchen (Missouri) said that their state provides $20/ac for EM38, management zones and variable rate N management.

Recommendations to improve the functioning of NCERA-180 were discussed. It was felt that NCERA-180 members could write a how-to-manual for data analysis in precision agriculture, develop science statements or white papers on precision ag in the same fashion as CAST, and could develop a high profile web site coupled to the CropLife Precision Ag Institute and a monthly newsletter produced by Bruce Erickson (Purdue University).

One of the recommendations concerned the annual turnover in NCERA-180 leadership. It was felt that the productivity of NCERA-180 could be improved by developing sub-committees with long-term membership to work on various research, education and outreach tasks. The Chair of the overall committee would continue to rotate, with a primary function of organizing the annual meetings, but membership on sub-committees would continue for 3-5 years.

Five major sub-committees and their initial membership were recommended during the discussion. These include:

Visioning
National Strategy Committee (Raj Khosla, John Schueller, David Mulla)
Research RFPs (Fran Pierce, Shrini Upadhyaya)

Evaluation and Promotion of Precision Ag Technologies (David Franzen, Don Bullock, Balaji Sethuramasamyraja, Jeff Willers, Ronnie Heiniger, Dennis Francis)

Collaborative Arrangements
Precision Ag Associations (Sid Parks, John Shanahan)
NRCS (Keith Morris, Raj Khosla, Eugene Burris, Eric Lund, Fran Pierce)

Communications and Outreach
Web site (Bruce Erickson, Wonsuk Lee, David Franzen, William Rudolph, Tim Stombaugh, Ronnie Heiniger, Nathan Watermeier, Jill Stanford, Lei Tian)
Books (David Clay, Ken Sudduth, Fran Pierce, David Franzen)
Training (Nathan Watermeier, Bruce Erickson)

Meetings
NCERA (Ronnie Heiniger, John Schueller)
International Precision Ag Conference (David Mulla, Raj Khosla)
ASA (David Clay, Kurt Thelen)
ASABE (Shrini Upadhyaya, Ken Sudduth, Tim Stombaugh, Balaji Sethuramasamyraja, William Rudolph)

David Mulla (University of Minnesota) led a discussion about plans for the annual meeting of NCERA-180 during January 2008. After some discussion about conflicts with other meetings, it was decided to hold the 2008 meeting of NCERA-180 from Jan 9-11 in Minneapolis, MN.

The program would be focused on sub-committee activities (see previous section) and progress during 2007. An interim steering committee consisting of John Schueller, David Mulla and Ronnie Heiniger was selected to oversee the initial development and establishment of action sub-committees.

It was agreed that there would not be any state reports at the 2008 meeting. There will be a few technical sessions on applications of precision agriculture in biofuel production. A tour to an ethanol production facility will be organized.

An election was held to select the Chair for the 2009 NCERA-180 meeting. Ronnie Heiniger of North Carolina State University was unanimously elected, and agreed to hold the 2009 meeting of NCERA-180 in Raleigh, NC.

Newell Kitchen (USDA-ARS Missouri) led a discussion on the relationship between NCERA-180 and the International Conference on Precision Agriculture (ICPA).

There is a critical need for dissemination of Precision Ag science and technology. ICPA has been very effective at fulfilling this need. Since David Mulla at the University of Minnesota has asked Raj Khosla at Colorado State University to organize the next ICPA, what role can NCERA-180 play in helping make this transition? It was agreed to establish a committee from NCERA-180 (Newell Kitchen, David Mulla, Raj Khosla, Dwayne Westfall, John Schueller, and Ronnie Heiniger) to work out the details for how NCERA-180 can help sponsor and organize ICPA. The committee was asked to consider issues such as location, timing, organization, and audience for ICPA.

Fran Pierce (Washington State University) finished editing the publication on GIS in Precision Agriculture by CRC Press. This is the first in a series of books on GIS in agriculture. It is envisioned to have 1-2 volumes each year, on topics such as invasive species, IPM, precision conservation, agribusiness, etc.

He asked whether there was interest in updating the book State of Site-Specific Management which appeared 10 years ago. Perhaps it could be updated by having symposia on precision ag at ICPA, ASA and ASABE in 2008.

Fran described several new funding initiatives coming out of CSREES, one on vegetable crops and another on robotics.

David Clay (South Dakota State University) presented research on Carbon Maintenance Rates in South Dakota. It is difficult to predict carbon storage at different landscape positions. A graphical technique was illustrated in which additions of organic carbon were related to the rate of change in soil organic carbon. The intercept on the graph could be used to estimate maintenance rates of soil organic carbon (no net change in carbon). Two factors control maintenance rates: 1) root/shoot ratios which vary across the landscape and 2) how much carbon is being added (measured with yield monitor and harvest index).

David Mulla (University of Minnesota) talked about Hyperspectral Remote Sensing for N Deficiencies in Corn. Small plot research was conducted in a corn-corn and a corn-soybean rotation with 18 different nitrogen management strategies. These included several rates of pre-plant application, and several methods and rates for in-season application of nitrogen. Hyperspectral imagery collected from an airplane at V-9 were compared with in-field data collected using SPAD meter, Green Seeker and Crop Circle sensors. Several promising hyperspectral indices based on red edge effects were identified that accurately identified N deficiencies in the corn-corn rotation. Identification of N deficiencies in the corn-soybean rotation was more difficult due to carryover of fixed N from the soybean crop.

Janos-Kriston-Vizi (Kyoto University) talked about Multi-spectral Reflectance Data for Leaf Water Potential in Mandarin Fruit Tree Orchards. There is a relationship between sugar accumulation and water stress in Mandarin fruits. A multi-spectral camera was used to collect data from fruit tree orchards. Reflectance and leaf water potential data were compared statistically. Green reflectance was higher from water stressed trees than un-stressed trees. Infrared thermography of fruit tree canopies was used to show a 2.8 C difference between water stressed and un-stressed trees, and a 0.48 MPa difference in water potential. Hyperspectral imaging from 400-1000 nm showed that water stress effects showed up best at 560 nm.

John Schueller (University of Florida) officially adjourned the 2007 annual meeting of NCERA-180.

Accomplishments

Activities and Outputs:<br /> <br /> <br /> 1. A significant number of NCERA-180 participants studied nitrogen fertilizer requirements using remote sensing techniques or sensor technologies (MN, SD, MO, IN, CO, CA, FL, NC, AR). This research is motivated in part by the rising cost of N fertilizers as oil and gas prices continued upward over the last two years. It is also motivated by concern over excess nitrate-N carried to the Gulf of Mexico from the Mississippi River. There is a critical need to improve the efficiency of nitrogen use in agricultural crops within the Mississippi River Basin to reduce water quality impacts.<br /> <br /> <br /> Remote sensing techniques studied by NCERA-180 participants show great promise for detecting leaf N deficiencies in spring for sidedress applications of N fertilizer. Remote sensing techniques also show promise for estimating spatial variability in soil properties that influence N requirements, and in helping to delineate fertilizer management zones. <br /> <br /> <br /> Publications resulting from these studies are listed below:<br /> <br /> <br /> Bajwa, S. G. 2006. Modeling rice plant nitrogen effect on canopy reflectance with partial least square regression. Transactions of the ASAE 49(1): 229-237.<br /> <br /> <br /> Bajwa, S. G., and M. Mozaffari. 2006. Response of cotton canopy reflectance to nitrogen fertilization. In. N. A. Slaton (Ed.) Wayne E. Sabbe Arkansas Soil Fertility Studies 2005, p.18-21, Research Series 525, Arkansas Agricultural Experiment Station, Division of Agriculture, Fayetteville, AR.<br /> <br /> <br /> Balasundram, S. K., P. C. Robert, and D. J. Mulla. 2006. Relationship between oil content and fruit surface color in oil palm (Elaeis guineensis Jacq.). Journal of Plant Sciences. 1(3):217-227.<br /> <br /> <br /> Clay, D.E. K. Kim, J. Chang, S.A. Clay, and K. Dalsted. 2006. Characterizing water and nitrogen stress in corn using remote sensing. Agron. J. 98:579-587.<br /> <br /> <br /> Hornung, A. Khosla, R. Reich, R. Inman, D. Westfall, D.G. 2006. Comparison of site-specific management zones: soil-color-based and yield-based. Agronomy Journal. 98(2): 407-415. <br /> <br /> <br /> Humburg, D. S., P. Thanapura, C. Ren, and D.E. Clay. 2006. Sugarbeet quality<br /> correlation to Landsat canopy data from a large GIS database. Transactions of the ASABE. 49(3) 775-782.<br /> <br /> <br /> Jahn, B. R. and Upadhyaya, S. K. 2006. Development of mid-infrared-based calibration equations for predicting soil nitrate, phosphate, and organic matter concentrations. American Society of Agricultural and Biological Engineers Paper No. 06-1058, St. Joseph, MI 49085.<br /> <br /> <br /> Kane, K. E., W. S. Lee. 2006. Spectral sensing of different citrus varieties for precision agriculture. ASAE Paper No. 061065. St. Joseph, Mich.: ASAE.<br /> <br /> <br /> Kim, H.J., Sudduth, K.A., and Hummel, J.W. 2006. Sensing nitrate and potassium ions in soil extracts using ion-selective electrodes. Journal of Biosystems Engineering 31(6):463-473. <br /> <br /> <br /> Mercuri P. A., B.A. Engel and C. J. Johannsen. 2006. Evaluation and Accuracy Assessment of High-Resolution IFSAR DEMs in Low-Relief Areas. International Journal of Remote Sensing. 27 (13): 2767-2786.<br /> <br /> <br /> Miao, Y., D. J. Mulla, P. C. Robert and J. A. Hernandez. 2006. Within-Field Variation in Corn Yield and Grain Quality Responses to N Fertilization and Hybrid Selection. Agron. J. 98:129-140.<br /> <br /> <br /> Min, M., W. S. Lee, Y. H. Kim, and R. A. Bucklin. 2006. Nondestructive detection of nitrogen in Chinese cabbage leaves using VIS-NIR spectroscopy. HortScience 41(1): 162-166.<br /> <br /> <br /> Min, M., and W. S. Lee. 2006. Design of a hyperspectral nitrogen sensing system for citrus. ASAE Paper No. 061061. St. Joseph, Mich.: ASAE.<br /> <br /> <br /> Roberts, D.R., Kitchen, N.R., Scharf, P.C., and Sudduth, K.A. An environmental assessment of sensor-based variable-rate nitrogen management in corn. In Proc. North Central Extension-Industry Soil Fertility Conf., Des Moines, IA, Nov. 7-8, 2006. Potash and Phosphate Institute, Brookings, SD. 2006.<br /> <br /> <br /> Scharf, P.C., S.M. Brouder, and R.G. Hoeft. 2006. Chlorophyll meter readings can predict nitrogen need and yield response of corn in the North-Central USA. Agron. J. 98:655-665.<br /> <br /> <br /> Sripada, R.P., R.W. Heiniger, J.G. White, and A.D. Meijer. 2006. Aerial color infrared photography for determining early in-season nitrogen requirements for corn. Agron. J. 98:968-977.<br /> <br /> <br /> 2. NCERA-180 participants are very active in helping to organize or participate in International, National and Regional Conferences on Precision Agriculture. These Conferences reach large numbers of scientists, ag industry professionals and producers, and help disseminate the latest advances in Precision Agriculture, thereby accelerating the adoption of Precision Agriculture. <br /> <br /> <br /> A partial listing of these Conferences is given below:<br /> <br /> <br /> Organized the 2006 International Conference on Precision Agriculture in Minneapolis, MN. Conference was attended by 400 scientists and practitioners from 30 countries, and nearly 300 papers were presented on a wide array of Precision Agriculture topics.<br /> <br /> <br /> Organized Precision Agriculture technical sessions for the 2007 International Meeting of the American Society of Agricultural and Biological Engineers in Minneapolis, MN. Technical sessions include roughly 75 papers on soil sensors, automated guidance, remote sensing and GIS and spatial technologies.<br /> <br /> <br /> Organized a special symposium on Precision Agriculture at the 2007 Annual Meeting of the American Society of Agronomy through Division S-8. Approximately 50-60 papers on Precision Agriculture are presented at this Symposium.<br /> <br /> <br /> Organized the Info-Ag Conference on Precision Agriculture for over 500 producers and ag industry professionals during July, 2007 in Springfield, IL. <br /> <br /> <br /> Organized the 2007 Precision Agriculture Data Management, Analysis and Decision Making Workshops in Ohio.<br /> <br /> <br /> 3. Future activities of NCERA-180 participants will focus on on five major areas. The first is visioning. NCERA-180 members will meet with agricultural and environmental agency leaders to help identify priority topics for Precision Agriculture research and education. The second is evaluation of Precision Agriculture technologies. NCERA-180 members will form teams to write white papers on emerging technologies used in Precision Agriculture. The third is networking with conservation agencies. NCERA-180 members will work with USDA-NRCS staff to help write 590 Practice Standards for cost-sharing of conservation practices that involve Precision Agriculture (for example, grid sampling for soil nutrients). Fourth is communications and outreach. NCERA-180 members will partner with the ag industry and work to enhance the dissemination of Precision Agriculture research results through extension newsletters, web sites, and training sessions. Fifth is conferences and workshops. NCERA-180 members will continue to be involved in planning and organization of major conferences, symposia and workshops on Precision Agriculture through a variety of Professional Societies and venues.

Publications

Journal Publications<br /> <br /> <br /> Adamchuk, V.I., M.T. Morgan, and S.M. Brouder. 2006. Analysis of variability in automated soil pH measurements. Trans. ASAE. 22(3): 335-344.<br /> <br /> <br /> Bajwa, S. G. 2006. Modeling rice plant nitrogen effect on canopy<br /> reflectance with partial least square regression. Transactions of the ASAE<br /> 49(1): 229-237.<br /> <br /> <br /> Bajwa, S. G., and E. Vories. 2007. Spatial analysis of cotton (Gossypium<br /> hirsutum L.) canopy responses to irrigation in a moderately humid area.<br /> Irrigation Science DOI# 10.1007/s00271-006-0058-4 (Online First).<br /> <br /> <br /> Bajwa, S. G., and M. Mozaffari. 2006. Response of cotton canopy<br /> reflectance to nitrogen fertilization. In. N. A. Slaton (Ed.) Wayne E. Sabbe<br /> Arkansas Soil Fertility Studies 2005, p.18-21, Research Series 525, Arkansas<br /> Agricultural Experiment Station, Division of Agriculture, Fayetteville, AR.<br /> <br /> <br /> Balasundram, S. K., P. C. Robert, and D. J. Mulla. 2006. Relationship between oil content and fruit surface color in oil palm (Elaeis guineensis Jacq.). Journal of Plant Sciences. 1(3):217-227.<br /> <br /> <br /> Balasundram, S. K., P. C. Robert, D. J. Mulla and D. L. Allan. 2006. Relationship between oil palm yield and soil fertility as affected by topography in an Indonesian plantation. Communications in Soil and Plant Analysis. 37(9-10):1321-1337.<br /> <br /> <br /> Balasundram, S. K., P. C. Robert, D. J. Mulla and D. L. Allan. 2006. Spatial variability of soil fertility variables influencing yield in oil palm (Elaeis guineensis Jacq.). Asian Journal of Plant Sciences. 5(2):389-400.<br /> <br /> <br /> Balasundram, S. K., D. J. Mulla, P. C. Robert and D. L. Allan. 2006. Accounting for spatial variability in a short-term fertilizer trial for oil palm. Int. J. Soil Sci. 1(3): 184-195.<br /> <br /> <br /> Bogrekci, I., and W. S. Lee. 2006. Effects of soil moisture content on<br /> absorbance spectra of sandy soils in sensing phosphorus concentrations<br /> using UV-VIS-NIR spectroscopy. Trans. ASABE 49(4): 1175-1180.<br /> <br /> <br /> Cabot, P.E. Pierce, F.J. Nowak, P. Karthikeyan, K.G. 2006. Monitoring and predicting manure application rates using precision conservation technology. Journal of Soil and Water Conservation. 61(5):282-292.<br /> <br /> <br /> Chung, S.O., and Sudduth, K.A. 2006. Soil failure models for vertically operating and horizontally operating strength sensors. Transactions of the ASABE 49(4):851-863. <br /> <br /> <br /> Chung, S.O., Sudduth, K.A., and Hummel, J.W. 2006. Design and validation of an on-the-go soil strength profile sensor. Transactions of the ASABE 49(1):5-14. <br /> <br /> <br /> Clay, D.E., C.G. Carlson, S.A. Clay, C. Reese, Z. Liu, and M.M. Ellsbury. 2006. Theoretical derivation of new stable and non-isotopic approaches for assessing soil organic C turnover. Agron. J. 98:443-450.<br /> <br /> <br /> Clay, D.E. K. Kim, J. Chang, S.A. Clay, and K. Dalsted. 2006. Characterizing water and nitrogen stress in corn using remote sensing. Agron. J. 98:579-587.<br /> <br /> <br /> Clay, S.A., B. Kruetner, D.E. Clay, C. Reese, J. Kleinjan. 2006. Spatial distribution, temporal stability, and yield loss estimates for annual grasses and common ragweed in corn/soybean production field over nine years. Weed Sci. 54:380-390.<br /> <br /> <br /> Clay, S.A., K. Banken, M.M. Ellsbury, and F. Forcella. 2006. Influence of yellow foxtail on corn growth and yield. Comm. Soil Plant Anal. 37:1421-1435.<br /> <br /> <br /> Gandonou, J., C.R. Dillon, S.A. Shearer, and T. Stombaugh. 2006. Precision Agriculture Equipment Ownership versus Custom Hire: A Break-even Land Area Analysis. Journal of the American Society of Farm Managers and Rural Appraisers 69(1):106-116.<br /> <br /> <br /> Hong, N., Scharf, P.C., Davis, J.G., Kitchen, N.R., and Sudduth, K.A. 2006.<br /> Economically optimal nitrogen rate reduces soil residual nitrate. Journal of Environmental Quality 36: 354-362. <br /> <br /> <br /> Hornung, A. Khosla, R. Reich, R. Inman, D. Westfall, D.G. 2006. Comparison of site-specific management zones: soil-color-based and yield-based. Agronomy Journal. 98(2): 407-415. <br /> <br /> <br /> Humburg, D. S., P. Thanapura, C. Ren, and D.E. Clay. 2006. Sugarbeet quality<br /> correlation to Landsat canopy data from a large GIS database. Transactions of the ASABE. 49(3) 775-782.<br /> <br /> <br /> Iqbal, J., P. Owens, and I Ali. 2006. Application of Remote Sensing Data to Assess Weed Infestation in Cotton. Agricultural Journal 1(4): 186-191.<br /> <br /> <br /> Jahn, B. R., Linker, R., Upadhyaya, S. K., Shavis, A., Slaughter, D. C. and Shmulevi, I. 2006. Mid-infrared spectroscopic determination of soil nitrate content. Biosystems Engineering 94(4):505-515.<br /> <br /> <br /> Jang, G.S., Sudduth, K.A., Hong, S.Y., Kitchen, N.R., and Palm, H.L. 2006.<br /> Relating hyperspectral image bands and vegetation indices to corn and soybean yield. Korean Journal of Remote Sensing 22(3):183-197. <br /> <br /> <br /> Jiang, P., Anderson, S.H., Kitchen, N.R., Sadler, E.J., and Sudduth, K.A. 2006. Landscape and conservation management effects on hydraulic properties on a claypan-soil toposequence. Soil Science Society of America Journal. Accepted.<br /> <br /> <br /> Jung, W.K., Kitchen, N.R., and Sudduth, K.A. 2006. Relationship of soil profile strength and apparent soil electrical conductivity to crop yield. Korean Journal of Soil Science and Fertilizer 39(2):109-115. <br /> <br /> <br /> Jung, W.K., Kitchen, N.R., Sudduth, K.A., and Anderson, S.H. 2006.<br /> Spatial characteristics of claypan soil properties in an agricultural field. Soil Science Society of America Journal 70: 1387-1397. <br /> <br /> <br /> Khosla, R. Westfall, D. Reich, R. Inman, D. 2006. Temporal and Spatial Stability of Soil Test Parameters Used in Precision Agriculture. Communications in Soil Science and Plant Analysis. 37(15-20): 127-2136. <br /> <br /> <br /> Kim, H.J., Sudduth, K.A., and Hummel, J.W. 2006. Sensing nitrate and potassium ions in soil extracts using ion-selective electrodes. Journal of Biosystems Engineering 31(6):463-473. <br /> <br /> <br /> Lambert, Dayton, J. Lowenberg-DeBoer and Gary Malzer. (2006). Economic Analysis of Spatial-Temporal Patterns in Corn and Soybean Response to Nitrogen and Phosphorous. Agronomy Journal 98:43-54. <br /> <br /> <br /> Liu, Y., S. M. Swinton, and N. R. Miller. 2006. Is Site-specific Yield<br /> Response Consistent over Time? Does it Pay? American Journal of<br /> Agricultural Economics 88(2):471-483.<br /> <br /> <br /> Martin, N., Bollero, G., Kitchen, N.R., Kravchenko, A.N., Sudduth, K.A., Wiebold, W.J., Bullock, D. 2006. Two classification methods for developing and interpreting productivity zones using site properties. Plant Soil 288: 357-371. <br /> <br /> <br /> Mercuri P. A., B.A. Engel and C. J. Johannsen. 2006. Evaluation and Accuracy Assessment of High-Resolution IFSAR DEMs in Low-Relief Areas. International Journal of Remote Sensing. 27 (13): 2767-2786.<br /> <br /> <br /> Miao, Y., D. J. Mulla, P. C. Robert and J. A. Hernandez. 2006. Within-Field Variation in Corn Yield and Grain Quality Responses to N Fertilization and Hybrid Selection. Agron. J. 98:129-140.<br /> <br /> <br /> Miao, Y., D. J. Mulla and P. C. Robert. 2006. Spatial Variability of Soil Properties, Corn Quality and Yield in Two Illinois, USA Fields: Implications for Precision Corn Management. Prec. Agric. 7:5-20.<br /> <br /> <br /> Miao, Y., D. J. Mulla, W. D. Batchelor, J. O. Paz, P. C. Robert and M. Wiebers. 2006. Evaluating Management Zone Specific Optimal N Rates with a Crop Growth Model. Agron. J. 98:545-553..<br /> <br /> <br /> Miao, Y., D. J. Mulla and P. C. Robert. 2006. Identifying Important Factors Influencing Corn Yield and Grain Quality Variability using Artificial Neural Networks. Prec. Agric. 7(2):117-136.<br /> <br /> <br /> Min, M., W. S. Lee, Y. H. Kim, and R. A. Bucklin. 2006. Nondestructive<br /> detection of nitrogen in Chinese cabbage leaves using VIS-NIR<br /> spectroscopy. HortScience 41(1): 162-166.<br /> <br /> <br /> Myers, D.B., Kitchen, N.R., Sudduth, K.A., Miles, R.J., and Sharp, R.E. Soybean root distribution related to claypan soil properties and apparent soil electrical conductivity. Crop Science. (accepted)<br /> <br /> <br /> Omonode, R.A., and T. Vyn. 2006. Spatial dependence and relationships of electrical conductivity to soil organic matter, phosphorus, and potassium. Soil Science 171(3):223-238.<br /> <br /> <br /> Papiernik, S.K., W.C. Koskinen, L. Cox, P.J. Rice, S.A. Clay, N.R. Werdin-Pfisterer, and K.A. Nordberg. 2006. Sorption-desorption of imidacloprid and its metabolites in soil and vadose zone materials. J. Agric. Food Chem. 54:863-870.<br /> <br /> <br /> Pena-Yewtukhiw, E.M., G.J. Schwab and L.W. Murdock. 2006. Univariate Distribution Analysis to Evaluate Variable Rate Fertilization. Agron J. 98:554-561.<br /> <br /> <br /> Pydipati, R., T. F. Burks, and W. S. Lee. 2006. Identification of citrus<br /> disease using color texture features and discriminant analysis.<br /> Computers and Electronics in Agriculture 52(1): 49-59. <br /> <br /> <br /> Roel, A., H. Firpo and R.E. Plant. Why Do Some Farmers Get Higher<br /> Yields? Multivariate Analysis of a Group of Uruguayan Rice Farmers.<br /> Computers and Electronics in Agriculture. In press.<br /> <br /> <br /> Scharf, P.C. Kitchen, N.R., Sudduth, K.A., and Davis, J.G. 2006. Spatially variable corn yield is a weak predictor of optimal nitrogen rate. Soil Science Society of America Journal 70:2154-2160. <br /> <br /> <br /> Scharf, P.C., S.M. Brouder, and R.G. Hoeft. 2006. Chlorophyll meter readings can predict nitrogen need and yield response of corn in the North-Central USA. Agron. J. 98:655-665.<br /> <br /> <br /> Souza, E., Scharf, P., Sudduth, K.A., and Hipple, J.D. 2006. Using a field radiometer to estimate instantaneous sky clearness. Brazilian Journal of Agricultural and Environmental Engineering 10(2):369-373. <br /> <br /> <br /> Sripada, R.P., R.W. Heiniger, J.G. White, and A.D. Meijer. 2006. Aerial color infrared photography for determining early in-season nitrogen requirements for corn. Agron. J. 98:968-977.<br /> <br /> <br /> Sudduth, K.A., Chung, S.O., Andrade-Sanchez, P., and Upadhyaya, S.K. Field comparison of two prototype soil strength profile sensors. Computers and Electronics in Agriculture. (accepted).<br /> <br /> <br /> Thomson, S.J., L.A. Smith, and J.E. Hanks. 2007. An Instrumentation<br /> Platform and GPS Position Latency Issues for Remote Sensing on<br /> Agricultural Aircraft. Transactions of the ASABE. 50(1): 13-21.<br /> <br /> <br /> Books<br /> <br /> <br /> Clay, D.E., N. Kitchen, C.G. Carlson, J. Kleinjan, and J. Chang. 2007. Using historical management to reduce soil sampling errors. Pg 49-64. In: Pierce, F. and D.E. Clay (eds). GIS Applications in Agriculture. CRC Press, Boca Raton, FL. <br /> <br /> <br /> Clay, D.E., S.A. Clay, and C.G. Carlson. 2006. Site-specific management from a cropping systems perspective. Pg. 431-462. In Srinivasan, A. (ed) Precision farming  A global perspective. Haworth Press, Inc. <br /> <br /> <br /> Johannsen, C.J. 2006. Land Remote Sensing Applications for Human Welfare Support: Food Security. Contributions of Remote Sensing for Decisions about Human Welfare Workshop, National Research Council, Washington, DC. Appendix A 4 pp.<br /> <br /> <br /> Kitchen, N.R., Goulding, K.W.T., and Shanahan, J.F. Proven practices and innovative technologies for on-farm crop nitrogen management. In Nitrogen in the Environment. Elsevier Science, Amsterdam, Netherlands. (accepted)<br /> <br /> <br /> Kleinjan, J., D.E. Clay, C.G. Carlson, and S.A. Clay. 2007. Developing productivity zones from multiple years of yield monitor data. Pg. 65-80. In: Pierce, F. and D.E. Clay (eds). GIS Applications in Agriculture. CRC Press, Boca Raton, FL.<br /> <br /> <br /> Pierce, F. and D.E. Clay (editors). 2007. GIS Applications in Agriculture. CRC Press, Boca Raton, FL. 203 pg.<br /> <br /> <br /> Roel, A., G.S. Pettygrove, and R.E. Plant. 2006. Site-specific rice management. Handbook of Precision Agriculture, Principles and Applications. A. Srivivasan, ed. Haworth Press, New York, NY, 319-340. In press.<br /> <br /> <br /> Proceedings<br /> <br /> <br /> Adamchuk, V.I., Sudduth, K.A., Ingram, T.J., and Chung, S.O. 2006. Comparison of two alternative methods to map soil mechanical resistance on-the-go. Paper No. 061057. In: ASAE Annual Intl. Meeting Technical Papers. ASAE, St. Joseph, MI (available at: http://asae.frymulti.com/request.asp?JID=5&AID=20587&CID=por2006&T=2). <br /> <br /> <br /> Bajwa, S. G., and M. Mozaffari. 2006. Effect of petiole nutrients in<br /> cotton on vegetative indices. ASAE Paper No. 061170. St. Joseph, MI: ASAE.<br /> <br /> <br /> Bajwa, S. G., and E.D. Vories. 2006. Spectral response of cotton canopy<br /> to water stress. ASAE Paper No. 061064. St. Joseph, MI: ASAE.<br /> <br /> <br /> Bajwa, S. G., and M. Mozaffari. 2006. Correlating vegetative index with<br /> nitrogen treatments in cotton. Summaries of Arkansas Cotton Research 2005,<br /> Research Series. 533, p. xx. Arkansas Agricultural Experiment Station,<br /> Division of Agriculture, Fayetteville, AR. <br /> <br /> <br /> Bogrekci, I., and W. S. Lee. 2006. The effect of particle size on<br /> sensing phosphorus by Raman spectroscopy. ASAE Paper No. 063048. St.<br /> Joseph, Mich.: ASAE. <br /> <br /> <br /> Chinchuluun, R., and W. S. Lee. 2006. Citrus yield mapping system in<br /> natural outdoor scenes using the Watershed transform. ASAE Paper No.<br /> 063010. St. Joseph, Mich.: ASAE. <br /> <br /> <br /> Chung, S.O., Sudduth, K.A., Lee, K.S., and Motavalli, P.P. 2006.<br /> Characterization of cone index to define compaction management parameters. In: Proc. ISTRO 17th Triennial Conf., p. 395-400. Kiel, Germany, August 28  September 3, 2006. <br /> <br /> <br /> Clay, S.A. 2006. Use of remote sensing for weed management. Eighth International Precision Ag. Conference. A to Z Session. Minneapolis, MN July 2006.<br /> <br /> <br /> Clay, S.A. 2006. Developing weed management zones for site specific farming application. Eighth International Precision Ag. Conference. A to Z Session. Minneapolis, MN July 2006.<br /> <br /> <br /> Clay, S.A., J. Kleinjan, and D.E. Clay. 2006. Weed emergence by landscape position. International Precision Ag. Conference. Minneapolis, MN July 2006.<br /> <br /> <br /> Conrad, E., C.R. Dillon and J. Gandonou. Variable Rate Fertilization Profitability on High-Oil Corn Production. Paper presented at the 8th International Conference on Precision Agriculture, Minneapolis, Minnesota, July 23-26, 2006.<br /> <br /> <br /> Dillon C., J. Gandonou, B. Koostra, T. Stombaugh, T. Mueller. Evaluating the Economic Impact of Field Area Measurements. Poster presented at the 8th International Conference on Precision Agriculture, Minneapolis, Minnesota, July 23-26, 2006.<br /> <br /> <br /> Erickson, B., and J. Lowenberg DeBoer. Will Higher Fertilizer Prices Drive Adoption of Precision Fertilizer Management? Purdue Agricultural Economics Report, April, 2006. http://www.agecon.purdue.edu/extension/pubs/paer/2006/april/paer0406.pdf<br /> <br /> <br /> Erickson, Bruce. Economics of Precision Agriculture: Implications for Sugar Cane Production, presented at the Colombian Association of Sugar Cane Technologists National Conference, Cali, Colombia, September 2006.<br /> <br /> <br /> Gandonou, J. and C.R. Dillon. Precision Timing and Spatial Allocation of Economic Fertilizer Application. Paper presented at the 8th International Conference on Precision Agriculture, Minneapolis, Minnesota, July 23-26, 2006.<br /> <br /> <br /> Griffin, Terry, J. Lowenberg-DeBoer and R.J.G.M. Florax, Improving Farm Management Decision Making: Experiences from Spatial Analysis of Yield Monitor Data from Field Scale On-Farm Trials, Paper presented at the 8th International Precision Agriculture Conference, Minneapolis, MN, July, 2006. <br /> <br /> <br /> Griffin, T.W., J.M. Lowenberg-DeBoer and R.J.G.M. Florax, "Improving Farm Management Decision Making: Experience from Spatial Analysis of Yield Monitor Data from Field-Scale On-Farm Trials," presented at the 8th International Precision Agriculture Conference, Minneapolis, MN, July 23-26, 2006. <br /> <br /> <br /> Humburg, D. S. 2006. Correlation of sugarbeet quality to canopy and field variables using Landsat data and a large GIS database. In Proceedings of the 8th International Conference on Precision Agriculture. July 23-26, 2006. Minneapolis, MN.<br /> <br /> <br /> Jahn, B. R. and Upadhyaya, S. K. 2006. Development of mid-infrared-based calibration equations for predicting soil nitrate, phosphate, and organic matter concentrations. American Society of Agricultural and Biological Engineers Paper No. 06-1058, St. Joseph, MI 49085.<br /> <br /> <br /> Jang, G., Sudduth, K.A., Hong, S.Y., Kitchen, N.R., and Palm, H.L. Relating image-derived vetetation indices to crop yield. In: Proc. 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment (unpaginated cd-rom). Am. Soc. for Photogrammetry and Remote Sensing, Bethesda, MD. 2006.<br /> <br /> <br /> Kane, K. E., W. S. Lee. 2006. Spectral sensing of different citrus varieties for precision agriculture. ASAE Paper No. 061065. St. Joseph, Mich.: ASAE.<br /> <br /> <br /> Lambert, Dayton M., R.J.G.M. Florax, and Kevin McNamara.. Multiplicative Heteroskedastic-Spatial Process Models: Monte Carlo Experiments and an Empirical Example, proceedings of the 53rd Annual North American Meetings of the Regional Science Association, November 16-18, 2006, Toronto, Canada.<br /> <br /> <br /> Lowenberg-DeBoer, J., Terry Griffin, R.J.G.M. Florax, Use of Cross Regression to Model Local Spatial Autocorrelation in Precision Agriculture, Paper presented at the 8th International Precision Agriculture Conference, Minneapolis, MN, July, 2006.<br /> <br /> <br /> Lowenberg-DeBoer, J., and B. Erickson. Economics of Innovative Technologies in Precision Agriculture Nutrient Management, presented at the American Society of Agronomy International Meetings, November, 2006.<br /> <br /> <br /> Min, M., and W. S. Lee. 2006. Design of a hyperspectral nitrogen sensing<br /> system for citrus. ASAE Paper No. 061061. St. Joseph, Mich.: ASAE.<br /> <br /> <br /> Nistor, Adela, Jason Brown, Raymond Florax, and Jess Lowenberg-DeBoer. Spatial Modeling of Yield Monitor Data: Implications for Crop Yields with Drainage Water Management, proceedings of the 53rd Annual North American Meetings of the Regional Science Association, November 16-18, 2006, Toronto, Canada.<br /> <br /> <br /> Reese, C. L., D. E. Clay, D. Beck, J. Kleinjan, C. G. Carlson and S. Clay. Lessons learned from implementing management zones and participatory research in production fields. Eighth International Conference on Precision Agriculture. 23  26 July 2006. Marriott Hotel, Minneapolis, Minnesota. <br /> <br /> <br /> Roberts, D.R., Kitchen, N.R., Scharf, P.C., and Sudduth, K.A. An environmental assessment of sensor-based variable-rate nitrogen management in corn. In Proc. North Central Extension-Industry Soil Fertility Conf., Des Moines, IA, Nov. 7-8, 2006. Potash and Phosphate Institute, Brookings, SD. 2006.<br /> <br /> <br /> Salim, J., C. Dillon, and J. Gandonou. (2006). Profit maximization under risk reducing behavior using variable cutting timings for Kentucky alfalfa. Paper presented at the 2006 Precision Agriculture Conference in July 23-26, 2006, Minneapolis, MN.<br /> <br /> <br /> Shockley, J., S.Saghaian, C. Dillon, and L.Maynard. A Logit Analysis of Precision Agriculture Adoption in Kentucky. Paper presented at the 8th International Conference on Precision Agriculture. Minneapolis, Minnesota. July 23-26, 2006.<br /> <br /> <br /> Smith, L.A. and S.J. Thomson. 2006. Performance of an Aerial<br /> Variable-Rate Application System With a Hydraulically Powered Chemical<br /> Pump and Spray Valve. NAAA/ASAE Paper No. AA05-009, National<br /> Agricultural Aviation Association, Washington, D.C.<br /> <br /> <br /> Sudduth, K.A., and Kitchen, N.R. Increasing information with multiple soil electrical conductivity datasets. Paper No. 061055. In: ASABE Annual Intl. Meeting Technical Papers. ASABE, St. Joseph, MI (available at: http://asae.frymulti.com/request.asp? JID=5&AID=21088&CID=por2006&T=2). 2006. <br /> <br /> <br /> Sudduth, K.A., Chung, S.O., Drummond, S.T., and Kitchen, N.R. Relating spatial variations in soil compaction to soil physical properties and crop yield. In Proc. 8th Intl. Conf. on Precision Agriculture, Minneapolis, MN, July 23-26, 2006 (in press). 2006.<br /> <br /> <br /> Sudduth, K.A., Chung, S.O., Drummond, S.T., and Kitchen, N.R. Relating spatial variations in soil compaction to soil physical properties and crop yield. In Proc. 8th Intl. Conf. on Precision Agriculture, Minneapolis, MN, July 23-26, 2006 (in press). 2006.<br /> <br /> <br /> Sudduth, K.A., Jang, G., Lerch, R.N., and Sadler, E.J. Hyperspectral reflectance sensing of reservoir water quality. In: Proc. 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment (unpaginated cd-rom). Am. Soc. for Photogrammetry and Remote Sensing, Bethesda, MD. 2006.<br /> <br /> <br /> Thompson, J.A., E.M. Pena-Yewtukhiw and J.H. Grove. 2006. Soil-landscape modeling across a physiographic region: Topographic patterns and model transportability. Geoderma. 133:57-70.<br /> <br /> <br /> Thomson, S.J. and L.A. Smith. 2006. Dynamic testing of GPS on agricultural aircraft for remote sensing and variable rate aerial application. In Proceedings of the IEEE/ION Position, Location and Navigation Symposium (PLANS 2006). CD-ROM: 1067- 1070. <br /> <br /> <br /> Thomson, S.J. and P.V. Zimba. 2006. Application of hyperspectral imagery and digital videography to manage algal blooms in aquaculture systems: Current status. Proceedings of the 20th Biennial Workshop on Aerial Photography, Videography, and High Resolution Digital Imagery for Resource Assessment. CD-ROM. American Society of Photogrammetry and Remote Sensing (ASPRS), Bethesda, MD.<br /> <br /> <br /> Upadhyaya, S. K., Shafii, M. S. and Garciano, L. O. 2006. Development of an impact type electronic weighing system for processing tomatoes. American Society of Agricultural and Biological Engineers Paper No. 06-1190, St. Joseph, MI 49085.<br /> <br /> <br /> Extension Publications<br /> <br /> <br /> Armstrong, S., and P. Owens. Spatial Variability of Nutrients in Soils Following Long-Term Poultry Litter Applications. SSMC Newsletter, December, 2006. <br /> <br /> <br /> Kleinjan, J., D.E. Clay, C.G. Carlson, and S.A. Clay. 2006. Developing productivity zones from multiple years of yield monitor data. Site Specific Management Guidelines. 45. Published by Potash and Phosphate Institute.<br /> <br /> <br /> Erickson, B., and J. Lowenberg-DeBoer. Will Higher Fertilizer Prices Drive Adoption of Precision Fertilizer Management? SSMC Newsletter, January, 2006. <br /> <br /> <br /> Erickson, B. The Use of Information Technology in Danish Agriculture. SSMC Newsletter, May 2006.<br /> <br /> <br /> Erickson, B. On-Farm Testing, Robotics, and Guidance Featured at the 2006 Top Farmer Crop Workshop. SSMC Newsletter, July, 2006. <br /> <br /> <br /> Erickson, B. Precision Agriculture in Colombian Sugar Cane. SSMC Newsletter, September, 2006.<br /> <br /> <br /> Erickson, B. A Comprehensive New Resource: Handbook of Precision Agriculture. SSMC Newsletter, October, 2006.<br /> <br /> <br /> Fulton, J.P., M.W. Veal and S.A. Shearer. Performance Assessment of Variable Rate Fertilizer Technology. SSMC Newsletter, April, 2006.<br /> <br /> <br /> Griffin, T., C. Dobbins, and J. Lowenberg-DeBoer. Whole Farm Profitability Impact from Implementing and Harvesting On-farm Trials: A Linear Programming Model. SSMC Newsletter, August, 2006. <br /> <br /> <br /> Lowenberg-DeBoer, J. and T. Griffin. Potential for Precision Agriculture Adoption In Brazil. SSMC Newsletter, June 2006. <br /> <br /> <br /> Lowenberg-DeBoer, J. Effect of Higher Energy and Fertilizer Prices on Precision Ag Adoption. SSMC Newsletter, February, 2006.<br /> <br /> <br /> Owens, P.R., J. Iqbal and D.M. Miles. Using Geostatistics to Determine Spatial Variability of Nutrients Within a Poultry House. SSMC Newsletter, March, 2006.<br /> <br /> <br /> Sripada, R.P., R.W. Heiniger, J.G. White, C.R. Crozier, and A.D. Meijer. 2006. Attempt to validate a remote sensing-based late-season corn nitrogen requirement prediction system. Online. Crop Management doi:10.1094/CM-2006-0405-01-RS. <br /> <br /> <br /> Struthers, R., and B. Erickson. The Modifiable Areal Unit Problem in Precision Agriculture. SSMC Newsletter, November, 2006.<br /> <br /> <br /> Staff Papers<br /> <br /> <br /> Whipker, Linda, and Jay Akridge, 2006 Precision Agricultural Services: Dealership Survey Results. Staff Paper No. 06-10, Center for Food and Agricultural Business, Department of Agricultural Economics, Purdue University, West Lafayette, IN, USA, August 2006.<br /> <br /> <br /> Trade Articles<br /> <br /> <br /> Erickson, B. Equipped to Succeed. CropLife, March 2006, pp 19-20.<br /> <br /> <br /> Erickson, B. Fertilizer and Precision, pp. 12-13 in 2006 Technology Tune-Up, supplement to February 2006 editions of CropLife, American Vegetable Grower, CottonGrower, and Western Fruit Grower.<br /> <br /> <br /> Whipker, Linda and Jay Akridge. A New Future, CropLife. June 2006, pp 10-15.<br /> <br />

Impact Statements

1. Organized the 2006 International Conference on Precision Agriculture in Minneapolis, MN. Conference was attended by 400 scientists and practitioners from 30 countries, and nearly 300 papers were presented on a wide array of Precision Agriculture topics.
2. Conducted the 2006 Survey of Crop Retailers showing that 81% of respondents used precision agriculture technologies of one type or another in their business. Much of this success in adoption is due to research and outreach activities of the NCERA-180 committee.
3. Organized Precision Agriculture technical sessions for the 2007 International Meeting of the American Society of Agricultural and Biological Engineers in Minneapolis, MN. Technical sessions include roughly 75 papers on soil sensors, automated guidance, remote sensing and GIS and spatial technologies.
4. Organized the 2007 Precision Agriculture Data Management, Analysis and Decision Making Workshops in Ohio.
5. Conducted precision agriculture research on several major US and international commodity crops, including corn, soybeans, sugar beets, cotton, citrus, tomatoes, rice, oil palm and cabbage. This research has led to improved crop productivity, greater efficiency of crop inputs and environmental benefits. For instance, over one-half of the sugar beet acreage in the Upper Midwest now uses Precision Agriculture techniques for crop management. A substantial proportion of corn growers in the Upper Midwest use Precision Agriculture to save on fertilizer, fuel or time. A substantial proportion of cotton growers in the Southern US use Precision Agriculture to management plant growth regulators applied before harvest.
6. Conducted precision agriculture research on several new sensors including on-the-go soil pH sensor, on-the-go soil nutrient sensors, crop remote sensing sensors, soil compaction sensor, crop chemical flow control sensors, and GPS sensors for autoguidance. These sensors have been commercialized in many cases, thereby stimulating the economy. They are also being used for more efficient management of agricultural inputs, including fertilzers and crop protection chemicals.
7. Scientists and industry personnel from NCERA-180 are working together to develop electronic communication and interoperability standards (ISOBUS 11783) for equipment used in Precision Agriculture. These standards will help standardize hardware (plugs/cables) and software (type and method of data exchange) used in Precision Agriculture.
8. Organized a special symposium on Precision Agriculture at the 2007 Annual Meeting of the American Society of Agronomy through Division S-8. Approximately 50-60 papers on Precision Agriculture are presented at this Symposium.
9. Organized the Info-Ag Conference on Precision Agriculture for producers and ag industry professionals during July, 2007 in Springfield, IL.

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Report Information

Participants

Bullock, Don (University of Illinois), dbullock@uiuc.edu;
Clay, David (South Dakota State University), david.clay@sdstate.edu;
Clay, Sharon (South Dakota State University), Sharon.clay@sdstate.edu;
Erickson, Bruce (Purdue University), berickso@purdue.edu;
Ferguson, Richard (University of Nebraska), rferguson1@unl.edu;
Francis, Dennis (USDA-ARS, Lincoln, Nebraska), dfrancis1@unl.edu;
Fixen, Paul (International Plant Nutrition Institute), Pfixen@ipni.net;
Franzen, David (North Dakota State University), david.franzen@ndsu.edu;
Heiniger, Ronnie (North Carolina State University), ron_heiniger@ncsu.edu;
Johnson, Gregg (University of Minnesota), johns510@umn.edu;
Khosla, Raj (Colorado State University), raj.khosla@colostate.edu;
Kitchen, Newell (USDA-ARS, Missouri), kitchen@missouri.edu;
Lund, Eric (Veris Tech), lunde@veristech.com;
Morris, Keith (Louisiana State University), kmorris@agcenter.lsu.edu;
Mulla, David (University of Minnesota), mulla003@umn.edu;
Pierce, Fran (Washington State University), fjpierce@wsu.edu;
Rudolph, William (TeeJet Industries);
Saraswat, Dharmendra (University of Arkansas), dsaraswat@uaex.edu;
Sethuramasamyraja, Balaji (University of California, Fresno), balajis@csufresno.edu;
Shanahan, John (USDA-ARS Lincoln, Nebraska), jshanahan1@unl.edu;
Stombaugh, Tim (University of Kentucky), tstomb@bae.uky.edu;
Sudduth, Ken (USDA-ARS Columbia, Missouri), sudduthk@missouri.edu;
Thelen, Kurt (Michigan State University), thelen3@msu.edu;
Tian, Lei (University of Illinois), lei-tian@uiuc.edu;
Ting, K. C. (University of Illinois), kcting@uiuc.edu;
Wienhold, Brian (USDA-ARS, Lincoln, Nebraska), bwienhold1@unl.edu

Brief Summary of Minutes

Minutes of NCERA-180 (Site-Specific Management) Roseville, Minnesota January 9-11, 2008 Host: David J. Mulla

The theme of this years meeting was Opportunities in Biofuel Production and Precision Agriculture. In light of that emphasis, members of the Committee spent January 9 touring POET ethanol and Soymor biodiesel plants near Albert Lea, Minnesota.

Thursday, January 10, 2008

Dr. David Mulla welcomed the participants and discussed the agenda covering various topics related to using site-specific management to enhance crop quality for biofuel production.

Dr. Mulla and Ryan Roggenbuck (University of Minnesota) presented research on Spatial Variation in EONR for crop yield and quality in Southern Minnesota. They covered methods for determining economic optimum nitrogen rates (ENOR) and the relationships between ENOR, crop yield and crop quality. They discussed their observations that spatial variability iin crop quality was often related to variability in soil properties and that managing crop quality using site-specific technologies was likely to result in significant gains in the efficiency of biofuel production.

Dr. Kurt Thelen (Michigan State University) presented information on Spatial Variability in Energy Crop Quality Components: Does It Matter?. He showed data indicating the importance of spatial variability in soil properties in determining the amount of oils, sugars, and starch produced by various crops. Clearly, spatial variability in soil properties is an important factor in regulating the amount of energy produced by an acre of land. He then discussed methods for using site-specific management to enhance crop yield and quality.

Dr. Newell Kitchen (USDA-ARS, Columbia Mo.) then presented an overview of the emerging technologies for land energy production on marginal soils. While many of these technologies are still years away from fruition there appears to be a good opportunity to use site-specific management practices in conjunction with these technologies to improve energy production.

The focus of the sessions then shifted to using site-specific management to improve carbon sequestration and enhancing that aspect of biofuel production. Dr. Brian Wienhold (USDA-ARS, Lincoln, NE) presented research on the effects of crop residues on soil properties in a spatially variable field. Differences in soil texture, nutrient status, and topography were shown to influence the effectiveness of crop residues in improving soil carbon and structure. Dr. David Clay (South Dakota State University) then talked about determining site-specific carbon requirements for spatially variable fields. He detailed site-specific methods for measuring soil carbon.

The final presentations of the day covered crop performance at different landscape positions and the role of precision agriculture in the future of biofuels. Dr. Gregg Johnson (University of Minnesota) presented his research on crop yield at different landscape positions. He findings indicate that different crops would be better suited to different landscape positions and that a diversity of biofuel crops is needed to maximize energy production. Dr. Paul Fixen (International Plant Nutrition Institute) then summarized the current research in biofuels and precision agriculture and presented his thoughts on the role that precision agriculture could play in improving the efficiency of energy production from biofuels.

Friday, January 11, 2008

K. C. Ting (University of Illinois) gave the Administrators Report. He encourage the participants to highlight the pieces of the NCERA-180 mission that are important. In particular, need to emphasize the education, extension, and research mission with a focus on information exchange. Within 60 days of meeting (March 11) the SAES-442 form must be submitted to the NIMSS online system and that the impact statement must be revised for the mid-term review. He also spoke about funding for specialty crop research and BP grants covering chemical transformations in bioscience and energy solutions from field to processing.

Dr. Ronnie Heiniger (North Carolina State University) lead a group discussion on the upcoming plans for the 2009 meeting which will be held in Portsmouth, VA. The focus of that meeting will be on using precision agriculture to mitigate the impact of global climate change.

An election was held to select the Chair for the 2010 NCERA-180 meeting. Tim Stombach of the University of Kentucky was unanimously elected, and agreed to hold the 2010 meeting of NCERA-180.

Raj Khosla (Colorado State University) discussed the upcoming 2008 International Conference on Precision Agriculture (ICPA). The venue for the conference is being changed to Colorado and will be held at the Hyatt Regency Tech Center in Denver, Co. Over 300 abstracts from 25 countries have been received and are being processed. The conference has been organized by theme areas including traceability, robotics, precision conservation, education, and a possible area to include biofuels. There will be graduate student awards to encourage their participation at the conference. The A to Z portion of the conference will continue with stronger support and speakers. NCERA-180 is assisting in the process of putting on the ICPA by being a strong part of the conference planning committee and will be staffing the conference sessions.

Dr. Fran Pierce (Washington State University) finished editing the publication on GIS in Precision Agriculture by CRC Press. This is the first in a series of books on GIS in agriculture. It is envisioned to have 1-2 volumes each year, on topics such as invasive species, IPM, precision conservation, agribusiness, etc. The next volume on GIS applications in agriculture will focus on invasive species with Sharon Clay as the lead author. Fran asked about other topics. The group identified several topics including Conservation Planning, Nutrient Management, Integrated Pest Management, GIS Applications in Agriculture Businesses, and Biofuels. NCERA-180 will provide the leadership with Dr. Pierce in developing these additional books.

Dr. Bruce Ericson from Purdue talked about the NCERA-180 taking leadership in developing connections with NRCS to work on guidelines for using EQUIP funds for precision technologies. He suggested that the NRCS program used in Missouri could be used as a model for efforts in this area. The group agreed to develop a team to work on guidelines for equip funds and to make contacts with NRCS to discuss implementing this program. It was suggested that an NRCS representative be at the 2009 meeting to present their side of the story.

Dr. Adamchuk (University of Nebraska) presented a demonstration on using GIS to understand the principals of precision farming. The current problem in implementing site-specific management practices lies in the high cost of GIS software that is not adequate for farm situations. He showed how programs presented over the internet could be used to train growers in the use of GIS applications using the software Maniforld 7x Personal and Surface Tools. Currently, the University of Nebraska offers five lessons in GIS Applications in Farming including 1) How to download data, 2) putting boundary data into a project, 3) processing yield data (including the use of yield editor and yield check), 4) visualization of soil data, and 5) prescription map development. The site is located under the University of Nebraska

Eric Lund (Veris Tech) talked about two instruments under development the first being the Veris MSP-ph which is a unit that measures pH in real-time. This unit has been improved with a continuing improvement in accuracy. The other unit is the Veris VIS-NIR a Near Infrared (NIR) spectrophotometer that collects data in 8 nm bands from 500-900 nm and from 1100-2200 nm. Light and dark references are collected automatically. NIR is used to estimate soil organic carbon, N, C/N, pH, Ca, Mg, P, K, CEC and moisture. This unit is being used in a USDA stover removal project to measure carbon sequestration and other soil properties. This unit could provide the data needed to quantify the impact of using various management practices on carbon accumulation.

William Rudolph (TeeJet Tech) talked about Centerline Guidance Devices and Field Pilot Automatic Steering Systems. He also talked about Swath Manager to turn on and off boom sections depending on whether the area was previously sprayed. TeeJet is developing a controller area network (CAN) based on ISO BUS ISO 11783 open standard to control all these devices.

Dr. Newell Kitchen (USDA-ARS, Missouri) talked about Division A-8 Integrated Ag Systems as a venue for symposia and papers on precision agriculture at the annual meetings of the Agronomy Society of America (ASA). Div. A-8. The focus topic is using precision agriculture to balance the impacts of rising demand for food, fiber, and fuel and crop production practices. The Div. A3 session on crop and soil modeling using remote sensing, A4 on sensor technology, A9 on fertilizer maps, S4 on nutrient management, and S6 on water issues in biofuel and plant rooting and soil carbon in the profile are also a possible venues for research from the NCERA-180 group.

Dr. Tim Stombaugh (University of Kentucky) talked about the next meeting of ASABE in Providence, RI. Possible sessions included GPS testing and accuracy, tractor guidance performance guidelines and application accuracy. All of these would welcome input from the NCERA-180 group.

David Mulla then lead a discussion on future activities of the NCERA-180 group. One key issue was the need for a website to communicate what the group is doing and to provide information about research, extension and outreach projects that the group is involved in. Bruce Ericson from Purdue University will develop a website for the group and host it. There was discussion about a funding source to support Dr. Ericsons efforts and the decision was made to contact CERESS about E-extension funding. This item will be discussed at Portsmouth, VA in 2009. The group asked for more information on the adoption of precision agriculture in the United States and other parts of the world. What is limiting adoption and how can these limitations be overcome so that farmers can benefit from precision technologies? Dr. Ericson presented some information from the SSMC group a Purdue showing the rate of adoption. It was decided that more on-line education information was needed. There will be a short course on spatial variability presented on the extension website at the University of Nebraska in February that could be used as a template for other efforts in education and extension.

Dr. David Mulla thanked everyone for coming and officially adjourned the 2008 annual meeting of NCERA-180.

Accomplishments

RESEARCH<br /> <br /> 1: Improvement in the Efficiency of Nutrient Use:<br /> <br /> Research by several institutions including the University of Minnesota (UMN), University of Nebraska (UNL), North Dakota State University (NDSU), North Carolina State University (NCSU), University of Missouri (UM), South Dakota State University (SDSU), Purdue (P), University of Arkansas (UArk), University of Florida (UNF), Michigan State University (MSU) and others have resulted in the development of technologies and site-specific techniques for applying fertilizers that have resulted in an improvement in the efficiency of nutrient use. Technologies developed include sensors for measuring crop nutrient status (UNL and UM), high clearance automated applicators (UNL), and algorithms for sensor output (UNL, UM, NCSU, SDSU, UArk) that help determine the amount and location of the application. Techniques developed include delineation of nutrient management zones (NDSU, P), new sampling techniques and technologies (UNL, NCSU, UM, UMN, NDSU), better analysis of sample information (all institutions), and other methods for determining where nutrients are needed and how crop yield responds to these nutrients. The results have been an improvement in the use of site-specific technologies with correlated reductions in nutrient loss. Measured outcomes include a 45% reduction in N use in Nebraska (UNL), increase in farm income of $7,000 to $33,000 using controlled drainage to manage nutrient loss (P, NCSU), increase in use of site-specific management to control N applications (NDSU, NCSU, UMN, UM, UNL)(for example: an increase in North Dakota of 500,000 in 2007), and a measured decline in fertilizer use nationwide largely accompanied by the use of site-specific technologies.<br /> <br /> 2. Precision Conservation Planning and Identification of Critical Resources<br /> Member institutions developed technologies and methods for measuring critical soil properties such as soil carbon, erosion potential, pH, etc. for use in better conservation planning and in developing inventories of soil resources. Examples include 1) research identifying erosion potential by micro-scale landscape features resulting in the identification of field zones with high erosion losses (UMN), 2) soil mapping to improve soil survey information (ND), 3) mapping of total carbon and impact of residue on soil carbon by landscape position (MSU), 4) mapping microbial activity in farm fields (UNL), and 5) hydrological GIS applications (P). These efforts have provided NRCS with important information and guidance in reducing soil erosion, nutrient loss, and enhancing soil carbon sequestration.<br /> <br /> 3. Development of New Guidance Technologies<br /> Member institutions have been leaders in developing guidance technology that has been rapidly and widely adopted by farmers. Studies include examination of visual sensors for guidance (UNL), analysis of guidance patterns, and the development of sensors and standards for guidance systems. More than 60% of the farmers in the US now have automated guidance systems on their equipment with the potential of reducing fertilizer and chemical use by 25% nationwide.<br /> <br /> 4. NCERA-180 participants are very active in helping to organize or participate in International, National and Regional Conferences on Precision Agriculture. These Conferences reach large numbers of scientists, ag industry professionals and producers, and help disseminate the latest advances in Precision Agriculture, thereby accelerating the adoption of Precision Agriculture. <br /> A partial listing of these Conferences over the past three years is given below: <br /> <br /> Organized the 2006 International Conference on Precision Agriculture in Minneapolis, MN. Conference was attended by 400 scientists and practitioners from 30 countries, and nearly 300 papers were presented on a wide array of Precision Agriculture topics. <br /> <br /> Organized Precision Agriculture technical sessions for the 2007 International Meeting of the American Society of Agricultural and Biological Engineers in Minneapolis, MN. Technical sessions include roughly 75 papers on soil sensors, automated guidance, remote sensing and GIS and spatial technologies. <br /> <br /> Organized a special symposium on Precision Agriculture at the 2007 Annual Meeting of the American Society of Agronomy through Division S-8. Approximately 50-60 papers on Precision Agriculture are presented at this Symposium. <br /> <br /> Organized the Info-Ag Conference on Precision Agriculture for over 500 producers and ag industry professionals during July, 2007 in Springfield, IL. <br /> Organized the 2007 Precision Agriculture Data Management, Analysis and Decision Making Workshops in Ohio. <br /> <br /> Organizing Precision Agriculture technical sessions for the 2008 International Meeting of the American Society of Agricultural and Biological Engineers in Providence, RI. <br /> <br /> Organizing a special symposium on Precision Agriculture at the 2008 Annual Meeting of the American Society of Agronomy through Division A-8.<br /> Collaborated on developing a book series entitled: GIS Applications In Agriculture. First book published in 2007 with the second book due for publication in 2008<br /> <br /> EXTENSION<br /> <br /> 5. Work by NCERA-180 member institutions was critical in the adoption of new technologies and techniques. This is being done through innovative extension programs featuring on-line education courses using state-of-the-art software. Examples of the extension efforts include: 1) The Nebraska Agricultural Technologies Association provides research based information on site-specific crop management, 2) Precision agriculture services survey by Purdue has been instrumental in guiding agribusinesses as they consider adopting precision technologies, Site-Specific user clubs in North Dakota started through extension programming, 3) Currently, the University of Nebraska offers five lessons in GIS Applications in Farming including 1) How to download data, 2) putting boundary data into a project, 3) processing yield data (including the use of yield editor and yield check), 4) visualization of soil data, and 5) prescription map development. The site is located under the University of Nebraska (http://bse.unl.edu/adamchuk/manifold), 6) UArk and NCSU conduct on-farm demonstrations of remote sensing and yield monitors, and 7) all member institutions produce a wide array of extension publications and materials covering all aspects of precision agriculture.<br /> <br /> EDUCATION<br /> <br /> 6. All of the NCERA-180 member institutions have developed educational course and training shortcourses to teach site-specific management techniques and technologies to todays farmers and tomorrows generation of agriculturalists. Outcomes in this area include: 1) Arkansas GeoSpatial Newsletter, 2) university courses at all of the major institutions (i.e. AOM 4434 Precision Agriculture (UNF)), and 3) on-line courses (i.e. Spatial Variability in Soils (UNL) http://www. Agronomy.unl.edu/prospective/distanced/agro896-1.html)<br /> <br /> FUTURE PLANS<br /> <br /> 7. Future activities of NCERA-180 participants will continue to focus on on five major areas. The first is visioning. NCERA-180 members will meet with agricultural and environmental agency leaders to help identify priority topics for Precision Agriculture research and education. The second is evaluation of Precision Agriculture technologies. NCERA-180 members will form teams to write white papers on emerging technologies used in Precision Agriculture. The third is networking with conservation agencies. NCERA-180 members will work with USDA-NRCS staff to help write 590 Practice Standards for cost-sharing of conservation practices that involve Precision Agriculture (for example, grid sampling for soil nutrients). Fourth is communications and outreach. NCERA-180 members will partner with the ag industry and work to enhance the dissemination of Precision Agriculture research results through extension newsletters, web sites, and training sessions. Fifth is conferences and workshops. NCERA-180 members will continue to be involved in planning and organization of major conferences, symposia and workshops on Precision Agriculture through a variety of Professional Societies and venues.<br /> <br /> NOTEABLE OUTPUTS<br /> <br /> Franzen, D.W., 2007. Grid sampling project on two Illinois fields. North Dakota State University. http://www.soilsci.ndsu.nodak.edu/franzen/franzen.html.<br /> <br /> Pierce, F.W. 2007. GIS Applications in Agriculture. CRC Press.<br /> Refer to the publications list for all publications relating to NCERA-180 member activities<br />

Publications

Adamchuk, V.I. and P.T. Christenson. 2007. An instrumented blade system for mapping soil mechanical resistance represented as a second-order polynomial. Soil Tillage and Research 95(1): 76-83.<br /> <br /> <br /> Adamchuk, V.I., E.D. Lund, T.M. Reed, and R.B. Ferguson 2007. Evaluation of on-the-go technology for soil pH mapping. J. Prec. Ag. 8:139-149<br /> <br /> <br /> Adamchuk, V.I., D.B. Marx, A.T. Kerby, A.L. Samal, L.K. Soh, R.B. Ferguson, and C.S. Wortmann. 2007. Guided soil sampling for enhanced analysis of georeferenced sensor-based data. In: U. Demsar, ed. Proceedings of the Ninth International Conference on Geocomputation 2007 Conference, Maynooth, Ireland, 3-5 September 2007. National University of Ireland.<br /> <br /> <br /> Adamchuk, V.I., R.M. Hoy, G.E. Meyer, and M.F. Kocher. 2007. GPS-based auto-guidance test program development. In: Precision Agriculture: Papers from the Sixth European Conference on Precision Agriculture, Skiathos, Greece, 3-6 June 2007, 425-432. J. Stafford, ed. Wageningen, The Netherlands: Wageningen Academic Publishers.<br /> <br /> <br /> Bajwa, S. G., and E. D. Vories. 2007. Spatial analysis of cotton canopy response to irrigation in a moderately humid area. Irrigation Science 25(4): 429-441. <br /> <br /> Bajwa, S. G., and M. Mozaffari. 2007. Effect of N treatments on vegetative index of cotton canopy  A spatial regression approach. Transactions of the ASABE 50(5):1883-1892.<br /> <br /> <br /> Balasundram, S.K., D. J. Mulla and P. C. Robert. 2007. Spatial data calibration for site-specific phosphorus management. International Journal of Agricultural Research 2:888-899.<br /> <br /> <br /> Bogrekci, I., and W. S. Lee. 2007. Comparison of ultraviolet, visible, and near infrared sensing for soil phosphorus. Biosystems Engineering 96(2): 293-299.<br /> <br /> <br /> Boomsma, C.R., and T.J. Vyn. 2007. Plant-to-Plant Uniformity is Essential for Optimum Yield in No-Till Continuous Corn. Purdue Extension AY-329-W.<br /> <br /> <br /> Bullock, David, and J. Lowenberg-DeBoer, Using Spatial Analysis to Study the Values of Variable Rate Technology and Information, Journal of Agricultural Economics, 58:3 (2007), p. 517-535.<br /> <br /> <br /> Chinchuluun, R., W. S. Lee, and R. Ehsani. 2007. Citrus yield mapping system on a canopy shake and catch harvester. ASABE Paper No. 073050. St. Joseph, Mich.: ASABE.<br /> <br /> <br /> Cohen, M. J., R. Mylavarapu, I. Bogrekci, W. S. Lee, and M. W. Clark. 2007. Reflectance Spectroscopy for Routine Agronomic Soil Analyses. Soil Science 172(6): 469-485. <br /> <br /> <br /> Cugati, S.A., W.M. Miller, J.K. Schueller, A.W. Schumann, S. Buchanon, and H.K. Hostler. 2007. Benchmarking of dynamic performance of two commercial variable-rate controllers and components. Transactions of the ASABE. 50(3):795-802.<br /> <br /> <br /> Ferguson, R.B., T. Kyaw, V.I. Adamchuk, D.D. Tarkalson, and D.L. McCallister. 2007. Site-specific management of pH-induced iron chlorosis of maize. In: J. Stafford (ed). Precision Agriculture: Proceedings of the 6th European Conference on Precision Agriculture, Siakthos, Greece, 3-6 June 2007. pp 151-156. Wageningen Academic Publishers.<br /> <br /> <br /> Griffin, T.W., Craig Dobbins and J. Lowenberg-DeBoer, Spatial analysis of On-farm Experiments and Subsequent Farm Management Decision Making: A Case Study, Selected Paper, American Agricultural Economics Association Annual Meeting, Portland, OR., USA, July, 2007 (http://agecon.lib.umn.edu/cgi-bin/pdf_view.pl?paperid=26241&ftype=.pdf).<br /> <br /> <br /> Grigera, M.S., R.A. Drijber, K.M. Eskridge, and B.J. Wienhold. 2006. Soil microbial biomass relationships with organic matter fractions in a Nebraska corn field mapped using apparent electrical conductivity. Soil Science Society of America Journal 70:1480-1488.<br /> <br /> <br /> Grigera, M.S., R.A. Drijber, and B.J. Wienhold. 2007. Redistribution of crop residues during row cultivation creates a biologically enhanced environment for soil microorganisms. Soil and Tillage Research 94:550-554.<br /> <br /> <br /> Grigera, M.S., R.A. Drijber, and B.J. Wienhold. 2007. Increased abundance of arbuscular mycorrhizal fungi in soil coincides with the reproductive stages of maize. Soil Biology and Biochemistry 39:1401-1409. <br /> <br /> <br /> Grigera, M.S., Drijber, R.A., Shores-Morrow, R.H., and Wienhold, B.J. 2007. Distribution of Arbuscular Mycorrhizal Biomarker C16:1cis11 Among Neutral-, Glygo-, and Phospho-Lipids Extracted from Soil During the Reproductive Growth of Corn. Soil Biol. Biochem. 39:1589-1596.<br /> <br /> <br /> Hager, B.R., S. Brantley, J. Bloxham, R. Eisner, A. Goetz, C.J. Johannsen, J. Kirchner, W. Rose, H. Shah, D. Smit, H. Zebker and M. Zuber. 2007. Solid-Earth Hazards, Natural Resources, and Dynamics, Earth Science Systems, Chapter 8, In Andres, R.A., B. Moore III, et al. (Editors), Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, pp 217-255, National Research Council, National Academy Press, Washington, DC.<br /> <br /> <br /> Hemmat, A., V.I. Adamchuk, and P. Jasa. 2007. On-the-go soil strength sensing using an instrumented disc coulter. In: Proceedings of the International Agricultural Engineering Conference (IAEC-2007), Bangkok, Thailand, 3-6 December, 2007. Pathumthani, Thailand: Asian Association for Agricultural Engineering (CD publication, 8 pages).<br /> <br /> <br /> Huang, X., S. Senthilkumar, A. Kravchenko, K. Thelen, and J. Qi. 2007. Total carbon mapping in glacial till soils using Near Infrared Spectroscopy, Landsat Imagery, and topographical information. Geoderma 141:34-42.<br /> <br /> <br /> Kane, K. E., and W. S. Lee. 2007. Multispectral imaging for in-field green citrus identification. ASABE Paper No. 073025. St. Joseph, Mich.: ASABE.<br /> <br /> <br /> Lambert, D.M., J. Lowenberg-DeBoer, and G. Malzer, Managing Phosphorous Soil Dynamics over Space and Time, Agricultural Economics 37 (2007), p. 43-53.<br /> <br /> <br /> Lee, K.H., M. R. Ehsani, and J.K. Schueller. 2007. Forward Movement Synchronization of Two Vehicles in Parallel Using A Laser Scanner. Journal of the Applied Engineering in Agriculture. 23(6): 827-834.<br /> <br /> <br /> Miao, Y., D. J. Mulla, G. W. Randall, J. A. Vetsch and R. Vintila. 2007a. Predicting chlorophyll meter readings with aerial hyperspectral remote sensing for in-season site-specific nitrogen management of corn. pp. 635-641. In: J. V. Stafford (ed.), Precision Agriculture 07. Wageningen Acad. Publ. The Netherlands.<br /> <br /> <br /> Miao, Y., D. J. Mulla, J. A. Hernandez, M. Wiebers and P. C. Robert. 2007b. Potential impact of precision nitrogen management on corn yield, protein content and test weight. SSSAJ 71:1490-1499.<br /> <br /> <br /> Nistor, Adela and J. Lowenberg-DeBoer, Drainage Water Management Impact on Farm Profitability, Journal of Soil and Water Conservation, Nov./Dec. 2007, 62:6, p. 443-446.<br /> <br /> <br /> Okamoto, H., W. S. Lee, and K. E. Kane. 2007. Hyperspectral imaging for green citrus fruit detection. 6th European Conference in Precision Agriculture and 2nd European Conference on Precision Livestock Farming, June 3-6, 2007, Skiathos, Greece.<br /> <br /> <br /> Pantaleoni, E., B.A. Engel and C.J. Johannsen. 2007. Identifying Agricultural Flood Damage Using Landsat Imagery. Journal of Precision Agriculture, Vol. 8:27-36.<br /> <br /> <br /> Robertson, G. P., L. W. Burger Jr., C. L. Kling, R. Lowrance and D. J. Mulla. 2007. New approaches to environmental management research at landscape and watershed scales. pp. 27-50. In: (M. Schnepf and C. Cox, eds.), Managing Agricultural Landscapes for Environmental Quality. Soil and Water Conservation Society. Ankeny, IA.<br /> <br /> <br /> Schueller, J.K. 2007. Intelligente Landtechnik in den USA. Forschung für intelligente Landtechnik. (Festveranstaltung zur Emeritierung von Prof. Dr. Dr. habil. Hermann Auernhammer.) VDI-Seminare am Wissenschaftszentrum. Technischen Universität München. Munich. July 19.<br /> <br /> <br /> Sripada, R.P., D.C. Farrer, R. Weisz, R.W. Heiniger, and J.G. White. Aerial color infrared photography to optimize in-season nitrogen fertilizer recommendations in winter wheat. Agron. J. 99:1424-1435.<br /> <br /> Smith, D.R., P.R. Owens, A.B. Leytem and E.A. Warnemuende. 2007. Nutrient losses from manure and fertilizer app lications as impacted by time to first runoff event. Environmental Pollution.147:131-137. <br /> <br /> <br /> Solari, F., J. Shanahan, R. Ferguson, J. Schepers and A.A. Gitelson. 2007. Active sensor reflectance measurements of corn nitrogen status and yield potential. Agron. J. (in-press).<br /> <br /> <br /> Urcola, Hernan, J. Lowenberg-DeBoer, A Stochastic Dominance Method for Incorporating Yield Monitor Data into the Hybrid and Variety Decisions of Argentinean Farmers, Computers and Electronics in Agriculture, 58:1 (Aug., 2007), p. 4-12.<br /> <br /> <br /> Varvel, G.E., W.W. Wilhelm, J.F. Shanahan, and J.S. Schepers. 2007. An algorithm for corn nitrogen recommendations using a chlorophyll meter based sufficiency index<br /> Agron. J. 99:701-706.<br /> <br /> <br /> Varvel, G.E., W.W. Wilhelm, J.F. Shanahan, and J.S. Schepers. 2007. Nitrogen fertilizer applications for corn based N sufficiency index calculations. Agron. J. 99: 701-706.<br /> <br /> <br /> Weisz. R., R.P. Sripada, R.W. Heiniger, J.G. White, and D.C. Farrer. 2007 In-season tissue testing to optimize soft red winter wheat nitrogen fertilizer rates: Influence of biomass. Agron. J. 99:511-520.<br /> <br /> <br /> Williams, J.D., C.R. Crozier, J.G. White, R.W. Heiniger, R.P. Sripada, and D.A. Crouse. 2007. Illinois soil nitrogen test predicts southeastern U.S. corn economic optimum nitrogen rates. Soil Sci. Soc. Am. J. 71: 735-744.<br /> <br /> Whipker, Linda and Jay Akridge. A Midwestern Precision Update. CropLife. June 2007, pp 10-14.<br /> <br /> Whipker, Linda and Jay Akridge. Biofuels: Future Challenges and Opportunities. CropLife. June 2007, pp 16-18.<br />

Impact Statements

1. 1. Conducted the 2007 Survey of Crop Retailers showing that 75% of respondents used precision agriculture technologies of one type or another in their business. Much of this success in adoption is due to research and outreach activities of the NCERA-180 committee.
2. 2. Organized Precision Agriculture technical sessions for the 2007 International Meeting of the American Society of Agricultural and Biological Engineers in Minneapolis, MN. Technical sessions include roughly 75 papers on soil sensors, automated guidance, remote sensing and GIS and spatial technologies.
3. 3. Organized the 2007 Precision Agriculture Data Management, Analysis and Decision Making Workshops in Ohio.
4. 4. Largely because of the work of the NCERA-180 institutions over 3 million acres of crops in the represented states were managed using site-specific technologies and techniques in 2007-08.
5. 5. Nebraska recorded a 45% reduction in N used when precision technologies were used to make N applications
6. 6. 30% of cotton growers in the Southern US use Precision Agriculture to management plant growth regulators applied before harvest resulting in a 58% reduction in the amount of growth regulator applied.
7. 7. Conducted precision agriculture research on several new sensors including on-the-go soil pH sensor, on-the-go soil nutrient sensors, crop remote sensing sensors, soil compaction sensor, crop chemical flow control sensors, and GPS sensors for autoguidance. These sensors have been commercialized in many cases, thereby stimulating the economy. They are also being used for more efficient management of agricultural inputs, including fertilzers and crop protection chemicals.
8. 8. Scientists and industry personnel from NCERA-180 are working together to develop electronic communication and interoperability standards (ISOBUS 11783) for equipment used in Precision Agriculture. These standards will help standardize hardware (plugs/cables) and software (type and method of data exchange) used in Precision Agriculture.
9. 9. Organized a special symposium on Precision Agriculture at the 2007 Annual Meeting of the American Society of Agronomy through Division S-8. Approximately 50-60 papers on Precision Agriculture are presented at this Symposium
10. 10. Organized the Info-Ag Conference on Precision Agriculture for producers and ag industry professionals during July, 2007 in Springfield, IL.

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Report Information

Participants

Provided in Meeting Minutes.

Brief Summary of Minutes

Accomplishments

NCERA-180 Summary of Accomplishments<br /> 2008-2009<br /> <br /> Research<br /> <br /> NCERA-180 activities and the relationships formed through these activities have facilitated many research and extension accomplishments over the past year. The following is a brief summary of some of these activities as reported by participants from Arkansas, California, Florida, Kentucky, Michigan, Nebraska, North Carolina, and North Dakota.<br /> <br /> Various Projects in Arkansas: Researchers in Arkansas have been working on problems related to soil compaction, in-season site-specific determination of plant nutrient needs, and statistical site-specific evaluation techniques for grain and cotton crops. They are also evaluating the utility of variable-rate lime application for validating lime recommendation rates. Their research also extends beyond traditional grain and cotton production to the nursery industry where they are evaluating methods of inventorying field-grown shade trees.<br /> <br /> Planting-site-specific application in orchards. The goal of this research was to use recent advances in the global positioning system and computer technology to apply just the right amount of fumigant where it is most needed (i.e., in the neighborhood of each tree planting site or tree-planting-site-specific application) to decrease the incidence of replant disease, and achieve the environmental and economical benefits of reducing the application of these toxic chemicals. In this study we retrofitted a shank type chemical applicator with a high-performance global positioning system receiver (accuracy in the range of 10 to 20 cm), an embedded controller to read GPS data, a Pulse Width Module (PWM) and solenoid actuated nozzles to provide precision rate on demand. Extensive testing indicated that the new system had a RMS error of less than 15 cm. The system was field tested in three almond orchards in California during the Fall of 2007. The system performed well in all three locations.<br /> <br /> Precision Weed Control System for Processing Tomatoes. The goal of this research was to develop an automated system for control of weeds in the seedline of direct seeded processing tomato plants. The system is based upon two main components, a hyperspectral imaging system for weed species identification, and a precision thermal weed treatment system for targeted application of a lethal high temperature organic oil application. In 2008 significant progress was made toward the development of both the weed species identification system and the thermal weed control system. We successfully conducted an outdoor test of the system where weeds in the seedline were automatically detected, identified, and treated by the system. Test results show that 95.8% of black nightshade and 92.7% of pigweed plants automatically treated by the heated oil spray were dead 15 days post application. Only 2.4% of the tomato seedlings accidentally sprayed by the system were killed. Nearly all (97.6%) of the tomato plants in the seedline were alive and had a dry mass not significantly (a=0.05) less than that of the untreated control tomato plants at 15 days post treatment.<br /> <br /> Pistachio Yield Monitor: A yield monitoring system has been developed for studying the yield behavior of pistachio trees to improve orchard productivity, field management and to investigate the mechanisms that cause alternate bearing. Two pistachio yield monitoring system sets developed and fabricated by UCD were enhanced for the 2008 harvesting season. These sets were retrofitted on two pistachio catch-frame harvester sets that were capable of maintaining nearly commercial harvesting field capacity. An automated, DGPS based row identification system, has been designed and developed to map tree locations inside mature orchards. An algorithm was developed to use real-time sensed odometric information to localize the trees inside the orchard canopy. In 2008, approximately 20,000 tree yields obtained from 64 ha of a young and a mature orchard were recorded and have been analyzed separately by UCD and Paramount Farming Co, CA. Seven-year yield data of very carefully monitored 4288 trees have been analyzed for alternate bearing studies. The accuracy of the tree yield data independently measured by the grower and this analysis supports the successful development of the current design. <br /> <br /> Olive Yield Monitor: In Oct 2008 experimental data were obtained using a harvester provided by Dave Smith Engineering (DSE), a modified Korvan prototype, while working on Manzanillo cultivars at the Rocky Hill Ranch, CA. Field trials were conducted to evaluate our design specifications to improve machine performance on a 3-acre area of mature trees planted on a 11 x 26 ft spacing. To monitor machine efficiency and field capacity the DSE picking head olive harvester prototype was retro-fitted with a UCD Bio-automation Lab (BAL) custom built yield monitoring system (OYMO8) and an AgLeader Insight monitor unit. The OYMO8 logged the signal from a custom built bin scale mounted on the harvester. The Insight yield monitor was able to measure picking head speeds (rpm) and record GPS position data. The OYM08 successfully recorded selected variables: date, UTC time, latitude, longitude, ground speed (GPS) and yield. Results of 2008 olive harvest trials are being evaluated. <br /> <br /> Various Projects in Florida: Researchers in Florida contributed work related to NCERA-180 objectives. Under the leadership of Dr. Wonsuk Daniel Lee, research continues on yield mapping of unripe green citrus. A new NIR camera from the Electrophysics was tested for the feasibility of detecting green citrus. However, in field tests it did not reliably distinguish green citrus from green canopies. <br /> <br /> Daniel Lee, working with Reza Ehsani and others, developed a new machine vision system to detect the amount of trash (leaves and twigs) resulting from mechanical harvesting with a continuous canopy shake and catch harvester. The system consisted of two digital color cameras, four halogen lamps, a laptop, and a DGPS receiver. Due to the catastrophic citrus greening disease (Huanglongbing or HLB), citrus growers want to know how much trash is generated from mechanical harvesting, so that the growers could prepare how to remove the disease infected trash.<br /> <br /> Work on citrus interpretation from satellite or aerial imagery continued under the leadership of L. Gene Abrigo. Evaluation of NDVI changes showed the decline of citrus blocks affected with Sudden Death in Brazil, and then their recovery as trees were replanted over a 7 year monitoring period. NDVI values were higher at the end of the period than before the disease indicating the better condition due to a higher density and installation of irrigation in the replanted blocks. In another comparison using multispectral data from aerial imaging, 62% of the variation in yield was correlated with percentage of ground area covered by citrus trees and the NDVI of those trees for a group of 53 Valencia orange blocks.<br /> <br /> Arnold Schumann and Kevin Hostler redesigned a popular optical sensor-based controller used for applying fertilizer and pesticides in Florida citrus orchards. By adding substantial GPS speed-regulated, microcontroller-based look-ahead capacity, the canopy sensors could be mounted to the front of the tractor instead of to the applicator, thus allowing multiple applicator devices to share the same control system and reduce costs. A PocketPC-based GUI software interface with Bluetooth wireless connects to the controller for advanced setup and monitoring. The new control system is now being commercialized for the benefit of all interested tree crop growers.<br /> <br /> Reza Ehsani is beginning a new major USDA-funded project working on autonomous tractors with Carnegie Mellon University, Cornell University and John Deere entitled "Integrated Automation for Sustainable Specialty Crop Farming". The goal of this 3-year project is to deploy, operate, and evaluate a networked fleet of autonomous tractors performing variable rate fertilizer and spraying applications, yield estimation, mowing, plant status monitoring and scouting in a large south Florida commercial citrus groves. The project brings the value of autonomous tractors (24/7 operation and reduced labor) and precision agriculture (maximizing profit) together. It also involves an extension effort to transfer the technology to other fruit and vegetable crops.<br /> <br /> John K. Schueller is concentrating on promoting the international sharing of precision agriculture technologies, including chairing Section III: Equipment Engineering for Plant Production of the International Commission of Agricultural Engineering.<br /> <br /> Advanced Machine Control Technologies. Researchers in Kentucky have focused heavily on advanced machine control technologies to increase productivity. Autosteer and lightbar technologies have been shown to greatly increase field and input use efficiency and to facilitate new management strategies such as strip tillage and precise input placement. Automatic section control has been shown to reduce input usage as much as 15% in irregularly shaped fields.<br /> <br /> Standardized Testing of Precision Agriculture Technologies. Researchers at Kentucky and Nebraska continue to refine procedures and facilities for testing GNSS receivers, autosteer systems, and yield monitors. As a result of these activities, one ISO standard has been initiated and nearly completed, another ISO standard will begin the evaluation process this year, and one ASABE standard has been completed.<br /> <br /> Site-specific cover crop management. Cover crops generate important benefits to agro-ecosystems and their importance will further increase if above ground biomass is removed for biofuel production. Better understanding of how variations in topography and soil properties affect cover crops will contribute to increased cover crop adoption, allowing producers to tailor cover crop management to site-specific features of their fields. We are studying a range of issues that need to be addressed prior to site-specific cover crop implementation. The issues include tools available for quick non-destructive assessment of cover crop growth patterns and biomass production; analysis of soil and topographical factors that affect cover crops on an agricultural field scale; and assessment of spatial variability in the amounts of biomass and nutrient inputs contributed by cover crops to the subsequent main crop and how it affects variability in the main crop performance. We are working with 8 agricultural fields that are part of Scale-up portion of the Kellogg Biological Station Long Term Ecological Research site experiment located in southwest Michigan. The fields are in organically managed corn-soybean-wheat rotation with red clover cover crop used in wheat years. We collect cover crop biomass data several times during the season and prior to cover crop incorporation, monitor performance and yield of the following main crops, examine topographical and soil characteristics of the studied fields. A range of statistical and geostatistical techniques, including but not limited to multiple regression, random coefficient regressions, hierarchical mixed models, regression kriging and cokriging are used for data analyses. Preliminary results were reported at the 9th International Conference on Precision Agriculture (Denver, CO) and will be reported at the Joint International Agricultural Conference 2009 (Wageningen, Netherlands).<br /> <br /> Spatial Variability in Energy Crop Quality Components. A better understanding of how soil and landscape features affect energy crop quality component yield is necessary to maximize efficiency in bioenergy cropping systems. Bioenergy crop quality components including ethanol production in corn grain and methyl ester profile and oil content in biodiesel crops were evaluated. State-wide data (2006) indicate a trend for increasing corn grain ethanol quality component (g ethanol produced per g of grain) with increasing latitude. On a within field basis, corn grain quality component yield was found to vary as much as 13% across a 50 ha field. Corn grain ethanol quality component yield was positively correlated with corn grain yield, rotational soybean yield, and soil carbon. Conversely, corn grain ethanol quality component yield was inversely correlated with elevation. Soybean biodiesel methyl ester profile was also found to vary spatially within a 50 ha field. The cumulative levels of fully saturated methyl esters (palmitic 16:0 and stearic 18:0) was significantly correlated with soil conductivity measurements. Levels of other soybean biodiesel quality components including oleic methyl esters (18:1) and the cumulative unsaturated methyl esters (linoleic 18:2 and linolenic 18:3), varied across the field landscape but were not significantly correlated with field or crop yield parameters.<br /> <br /> Various Projects in North Dakota. Use of site-specific technologies, tools, and management continue to increase in North Dakota. The increased cost of inputs and crop prices this past growing season resulted in a surge of demand for site-specific services from providers. Site-specific based businesses in the region have hired additional people to help service the demand. A number of these businesses have recently banded together to form the Alliance of Site-Specific Providers. The group will serve to enhance the ability of the mostly entrepreneurial members to work together through improved interaction.<br /> <br /> Two major site-specific projects were completed in 2008; The NRCS terrain modeling project, and the summary of 40 years of grid sampling in two Illinois fields. The summaries of both projects are available on Dave Franzens web page.<br /> <br /> An attempt to secure funding for cooperative work between NDSU and several site-specific businesses in the state and region through a state Center of Excellence proposal for about $1,000,000 in total funding was not successful.<br /> <br /> Three site-specific circulars- What is Site-Specific Agriculture?; Zone Sampling; and Yield Mapping; were published in 2008 and are available on the web. These are major updates of their 1998 publication.<br /> <br /> Crop and Soil Management Systems for Water Quality Protection and Agricultural Sustainability. Development of the Crop Circle active sensor system and protocols for sensor use was finalized through a cooperative research development agreement (CRADA) with Holland Scientific. Holland Scientific has in turn signed an agreement with Ag Leader Technology (Ames, IA), a leading manufacturer of precision farming technologies and Ag Leader announced May 1, 2008 that it has become the exclusive distributor in 2009 for Holland Scientifics second generation active light reflectance sensor products for use in production agriculture. Our research results showed that sensor readings acquired during vegetative growth and expressed as chlorophyll index (CI), (CI= sensor NIR / sensor visible  1) would have the greatest potential for assessing canopy N content and directing spatially variable in-season N applications. An algorithm for converting sensor readings to variable N applications was developed and was evaluated in on-farm field studies. Preliminary results from field studies show a potential for savings in N application from 20 to 50% compared to traditional N management practices. <br /> <br /> Integrated Soil Sensing for Site-Specific Crop Management. The process of targeted (also called guided or smart) sampling proposed to enhance the use of on-the-go soil sensing data has been analyzed. An objective function that accounts for representing the entire range of sensor data, spreading across the field and local homogeneity was developed. Constrained categorical separation and Latin hypercube sampling were used to simultaneously address all established criteria for multiple data layers while prescribing a random set of targeted sampling locations. A MatLab program was written to implement the method developed. In the spatial clustering research, we were able to combine univariate observations into groups based on values of the multivariate normal likelihood. The spatial location of these observations is taken into account in the variance-covariance matrix in the likelihood itself. With involvement of partner external scientists and industry representatives, the concept for integrated sensor platform has been established. Substantial resources have been pulled together to invest in a new Veris Mobile Sensor Platform and Trimble RTK-level GPS/GLONASS equipment. Both pieces integrated with the instrumented tractor and other sensors developed at UNL will serve as a platform for continued research in this area. Substantial funding has been secured to implement sensor fusion approach to manage soil acidity in Eastern Nebraska. Several large datasets were obtained using optical crop canopy sensors and recently added ultrasonic distance sensor during summer months. The analysis of sensor density effect has been accepted for publication in a refereed journal. The analysis of potential for in-season N management that is based on soil maps obtained using on-the-go soil sensor and aerial imaging platforms (in addition to the optical crop canopy sensing) is in progress. Also, the relationship between measured corn height and detected chlorophyll level status is studied with respect to the potential improvement of in-season N-management algorithm developed. Once implemented, the method presented will allow users unbiased prescription of optimized targeted soil sampling schemes necessary to build data calibration models. Further, successful implementation of the new clustering approach will allow users delineation of field areas that require differentiated treatments and are based on several calibrated self-generated data sources. <br /> <br /> Extension<br /> <br /> NCERA-180 participants are working toward the development of an eXtension web site on site-specific management. Several meetings have already taken place and the project seems well on its way to fruition. This is an extensive effort involving many different researchers and industry personnel. In addition, participants have conducted extension workshops on GIS, utilizing digital imagery, profitability, precision agriculture, ecosystem management, automatic section control, precision guidance, variable rate application equipment, greenseeker technology, and the use of software tools for nutrient management and yield data manipulation. Several states have also developed grower groups to help facilitate organized on-farm research and educational activities.<br />

Publications

Impact Statements

1. Organized the 9th International Conference on Precision Agriculture in Denver, CO on July 20-23, 2008. There were over 450 participants, with 250 oral and poster papers from over 40 countries, in 34 concurrent sessions.
2. Organized Precision Agriculture technical sessions at the 2008 International meeting of the American Society of Agricultural and Biological Engineers. There were roughly 75 papers on various engineering aspects of precision agriculture.
3. Initiated development of an eXtension web site on precision agriculture.
4. Completed an ASABE standard on field evaluation of yield monitor performance.
5. Initiated work on a new text book on GIS Applications in Agriculture - Nutrient Management for Improved Energy Efficiency.
6. Conducted evaluations of field equipment innovations that will save farmers as much as 15% in input costs in irregularly-shaped fields.
7. Continuted development of ISO standards on evaluation of dynamic GNSS accuracy and accuracy of autosteer systems on agricultural machinery.

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Report Information

Participants

Brief Summary of Minutes

January 6,2010 (Field Tour)

A field tour was organized as per the following schedule:

10:00 Leave Campbell House Inn
10:30 - 11:30 Main Chance Research Farm (GPS test facility, Sensors research)
11:30 - 12:00 Lunch at Main Chance
12:00 - 12:30 Travel to Woodford Reserve Distillery
1:00 - 2:30 Woodford Reserve tour and tasting
3:00 - 4:00 Three Chimneys horse farm tour
4:15 - 5:15 Animal Research Center
5:30 - Buffalo Trace Distillery tour and dinner

January 7, 2010 (Summary by Dr. Sreekala Bajwa, University of Arkansas)

Meeting started at 8 am with registration and continental breakfast. At 8.30 am, Tim Stombaugh, the committee chair, called the meeting to order and welcomed all participants.

Tim invited Dr. Nancy Cox, Associate Dean of the College of Agriculture to welcome the group. Dr. Cox welcomed everyone to the University of Kentucky campus, provided a brief history of Goodbarn, talked about the college, and the State's agriculture programs.

The chair reminded that it is time to renew the committee. The incoming chair will have to take the responsibility for renewing the committee. These are the suggestions made for writing the proposal to renew the committee:

It was suggested that the incoming officers collect a list of research, extension and educational objectives for the next 5 years and use that information to develop the committee's goals and objectives.

Address the 5 challenge areas (climate change, food security, childhood nutrition and obesity, sustainable energy, food safety) for grant funding through AFRI program in the proposal.

K. C. Ting, advisor to the committee, clarified that it is not a regional committee but a national committee and therefore, annual meetings can be held anywhere. However, the reporting has to go through the north-central region.

Invited Speakers

There were five speakers, who gave presentations. The first three presentations were made in the morning and the last two in the afternoon. Tim Stombaugh introduced each speaker to the group prior to their presentation. A summary of the presentations is given below.

1. Title: Precision Farming Adoption in Ohio
Marv Batte, Fred N. VanBuren Professor of Farm Management, Department of Agricultural, Environmental and Developmental Economics, The Ohio State University.

Marv talked about the precision farming adoption survey his group conducted in 1999, 2003 and 2007. In 2003, approximately 2500 farmers were contacted and 58% responded. The survey indicated that precision agriculture systems were reported as more beneficial in 2003 and 2007 than in 1999. He also reported that small farmers were as likely to be pleased with precision agriculture systems as large farmers. A suggestion was given to him that efficiency improvement in farming should be considered as a precision agriculture practice, which was not included in the previous surveys.

2. Title: Precision Agriculture collaboration: Agronomic, Engineering & Economics
Bruce Erickson, Purdue Univ. & Terry Griffin, University of AR

Bruce emphasized the need for other scientists to develop early collaboration with economists. During discussion it was pointed out that economists can address people's behavioral change with economics, social dimensions of change and the benefits of risk aversion. In the proposal writing stage, a collaborator from economics may be able to provide the value of proposition in a grant proposal.

3. Title: Seed Technology: Discovering, Delivering, Yielding
Glenn Murphy, Monsanto

This talk focused on past yield fluctuations and the future need for growth in food production and crop productivity. Among many factors that may enhance yield, the speaker talked about Monsanto's goal and progress on development of breeding new varieties with desirable genetics and traits. A question was raised about the need for developing management strategies appropriate for the moving target of crops (with different productivity and input requirements) since most PA practices that are developed assume a stationary target for crop performance.

4. Equipment and Technology Concept for Nutrient Management
Larry Hendrickson, John Deere & Co presented

The talk focused mainly on fertilizer management as a mechanism to increase crop yield to meet the fast-growing future demand. One of the main themes in the talk was N application, including pros and cons of anhydrous ammonia versus urea and field conditions where one fertilizer may be beneficial over the other to reduce N volatilization. He pointed out that application of anhydrous ammonia in wetter low lying areas and urea in drier higher elevation areas can reduce N volatilization. He also indicated that N2O release from fertilized fields is a major concern.


5. Input Application: Accuracy and Precision
Scott Shearer, University of Kentucky

Scott talked about speed variations between ends while turning and the resulting errors in application rate, issues of double application in overlapping areas, and the importance of boom section control and autoguidance.

After lunch, there was a tour of two labs at the University of Kentucky, the yield monitor testing lab, and the Milk Tracking and Security lab.

Text Books & eXtension

At the conclusion of all the presentations, Fran Pierce provided an update on the text books that are being planned or under development. The "GIS Application in Agriculture" series is planning to have 3 books published.

Bruce Erickson gave an update on eXtension project.

Future meeting location & timing

Tim Stombaugh announced that the 2011 meeting will be held at Little Rock, Arkansas. This announcement was followed by a discussion on the timing of the 2011 meeting. The group agreed that January-February is not a good time for a majority of the people due to grant proposal submission deadlines, Beltwide meeting and AETC meeting. There was a consensus among the attendees that the meeting time should be moved to either late March or first week of March. Spring break may be a good time to have the meeting. The meeting should end on Friday and shouldnt go into Saturday. It was suggested that the meeting should be held from Wednesday through Friday.

The meeting was adjourned around 4.40 pm.

January 8 (Summary from notes prepared by Tim Mueller, University of Kentucky)

KC Ting provided information about NCERA-180 deadlines and requested to write proposal (issues, justification). Scott shearer agreed to be default administrative advisor, but will look for others who have a passion for this. He mentioned about the new changes that will be in place regarding the selection of administrative advisor and committee members, respectively. The following members were identified:
Annual report writing: Pedro Andrade, Dharmendra Saraswat, Tim Stombaugh-will lead this effort
Write Project - David Clay, Tom Mueller, Pedro Andrade, Bruce Ericson, Larry Hendrickson

After discussions, new title of the project was suggested as "Precision technologies for food, fiber, and energy production". Some ideas were put forth by Francis Pierce (Fran) to include material in the perspective of global climate. It was suggested that mission statement should link to global challenges such as
o global food security and hunger
o climate change,
o food safety, etc.
Fran mentioned about the science article that discusses how the rate of change of food projection is dropping. Tim Stombaugh agreed to provide a link to the article on the website. Fran also mentioned about sending some notes for the new proposal to Tom Mueller for the development of the proposal.

Newell Kitchen summarized the history of tri socities- CSSA, ASA, and SSSA. He discussed plans for restructuring to make these societies more responsive.

Rak Khosla spoke about the organization of 10th International Conference on Precision Agriculture in Denver, Colorado during July 18-21. He also mentioned about the creation of International Society of Precision Agriculture (ISPA). He provided following additional details concerning ISPA:

o three functions to begin with
1) conference
ispss -
EuropeanConference on Precision Agriculture - they want to do this
acpa- is very interested but not confirmed
proceedings
awards and recognitions
2) Web portal
quarterly e-newsletter,
world wide directory,
virtual office
3) Scientific Journal
the international journal of precision agriculture will become the society journal,
maybe about 28 journals
4) Membership

- included with conference registration
- fee based for new-conference attendee
- online access to international journal for precision agriculture (1.92 impact factor)
- discounted hard copy subscription
- world wide reach to people/members
- conference (discounted registration fee)
- society awards and registration

- the fee would be about $50 per year , but that would be included as part of the attendance fee for the conference
- infrastructure
- by-laws have been written but have been simplified over time, very simple now

Slava Adamchuk informed about the IUSS working group on proximal soil sensing. He further informed about the publication of a book on the topic and a website dedicated to the cause (www.proximalsoilsensing.org) is available. Two workshops on high resolution digital soil sensing and mapping is scheduled in 2011.
Progress on ASABE standards were submitted as follows:

ASABE -standards
x573 - procedures for evaluating variable rate granular material application accuracy (John Fulton) - under development ,
x578 - yield monitor performance test (Scott Shearer) - published,
x579 yield monitor field test engineering procedure (Randy Taylor, voted and official ,
x587 - dynamic testing of global positioning devices used in agriculture (Tim Stombaugh) ISO 12188-1 (FDIS),
x605 gps based auto-guidence system testing (Slava Adamchuk),
x611 - standard for mapping yield and associated data (Alex Thomasson) - under early development

Accomplishments

NCERA-180 Summary of Accomplishments 2009-2010 <br /> <br /> Research <br /> <br /> NCERA-180 activities and the relationships formed through these activities have facilitated many research and extension accomplishments over the past year. The following is a brief summary of some of these activities as reported by participants from Arkansas, Florida, Missouri, Nebraska, and North Dakota. <br /> <br /> Research Projects reported from Arkansas: <br /> <br /> Researchers in Arkansas have continued working on problems related to soil compaction, in-season site-specific determination of plant nutrient needs, and statistical site-specific evaluation techniques for grain and cotton crops. They are also evaluating the utility of variable-rate lime application for validating lime recommendation rates. Their research also extends beyond traditional grain and cotton production to the nursery industry where they are evaluating methods of inventorying field-grown shade trees. <br /> <br /> Research Projects reported from Florida: <br /> <br /> Variable Rate Controller performance testing on a hoop sprayer was carried out at the Citrus Research and Education Center (CREC) and in commercial groves. The controller performance can be seen on a short video available at - http://128.227.177.113/pa/Video.html. Hoop sprayers are ideal for profitable caretaking of young solidest citrus plantings such as in new Advanced Citrus Production System (ACPS) blocks because the agrochemical savings could be greater compared to a conventional air blast sprayer. Additionally because the application is not low- or ultra low-volume, nutrient supplements can be included in the spray as part of a comprehensive Integrated Pest Management (IPM) program. The controller is being adapted and tested for variable rate or spot spraying of weeds. Efficient weed sensing is crucial to the success of this application, and initial results from using a small color digital camera looked promising when green color pixels were extracted to identify weed positions on the ground. Two simple software programs have been developed and posted online to assist growers when setting up their variable rate fertilizer spreaders: http://128.227.177.113/pa/Software.html. The sensor angle program will calculate the best angle to use when adjusting the sensor eyes so that they detect the required canopy size of the trees. <br /> <br /> A machine vision based trash removal system has been designed to quantify the amount of trash materials such as leaves and twigs generated during harvesting by a continuous citrus canopy shake and catch harvester. Two de-stemmers with different lengths of rollers (0.61 m and 0.91 m) were compared for their trash removal efficiency. The extended de-stemmer removed more trash materials than the regular de-stemmer based on a t-test conducted. <br /> <br /> Citrus greening disease (Huanglongbing or HLB) detection algorithms were developed using aerial hyperspectral imageries. Different hyperspectral image processing algorithms were used such as image-derived spectral library, mixture tuned match filtering (MTMF), spectral angle mapping (SAM), and spectral feature fitting (SFF), and spectral analyst tool in a hyperspectral imaging software (ENVI, ITT VIS). Various vegetation indices and spectral features were calculated using the spectral library and validated against their ideal values using ground measurement. Analysis of variance (ANOVA) was carried out to extract the significant bands at which the healthy and HLB infected pixels could be separated. ANOVA was further carried out to extract significant bands which would separate the false positives from the truly infected pixels. Since verification and validation of result required more accurate ground truth information, a tree based visual check approach was adopted instead of a pixel based approach for better interpretation of the results. <br /> <br /> Research Projects reported from Missouri:<br /> <br /> Crop reflectance sensing to guide corn nitrogen application: A project has been initiated to assess the ability of optical sensors to determine the most profitable N rates in corn. Sensor-based variable-rate N fertilizer application generated an increase in returns ranging from $5 to $50 per acre, depending on soil type. Also, as fertilizer cost increased relative to the price of corn grain, the economic value of using canopy sensors for N management improved. The results of this study are being used to develop procedures and decision rules that can be used with commercial computer-controlled machines that apply variable N rates. <br /> <br /> Near-infrared reflectance estimates of key soil profile properties: Few studies have been conducted to apply optical reflectance sensing of surface soils in the visible and near infrared (NIR) wavelength bands of soil profile. A laboratory visible-NIR reflectance measurement was obtained for surface and profile soil samples from five Midwestern states, and analyzed to find relationship with the soil physical and chemical properties. Good results were obtained for soil carbon, clay, cation exchange capacity, and calcium. The study identified appropriate spectral ranges and calibration techniques to improve accuracy. <br /> <br /> Estimating topsoil depth using apparent electrical conductivity: Three commercial EC sensors were used on two fields in Missouri. The EC data was used to investigate relationship with topsoil depth using two different methods, one using statistical analysis and another one using calculations based on the theoretical response functions of the sensors. It was found that topsoil depth estimates by two methods were very similar and that the EC sensors with medium measurement depths gave the best results. It was also found that better estimates could be obtained when combining data from multiple sensors. <br /> Crop sensing to estimate mid-season nitrogen need for cotton: High N application in cotton could result in increased cost in pesticides, growth regulator, and defoliant, as well as environmental problems through leaching and runoff of N-rich water. Reflectance sensors were used to diagnose N needs immediately and translate the diagnosis into a real-time, variable-rate application of N. Nitrogen rate experiments were conducted in Missouri for two years on various soils to develop recommendations based on reflectance measurements to support variable-rate fertilization. Sensors gave good predictions of optimal N rate, suggesting that variable-rate N applications to cotton based on real-time reflectance measurements are feasible. <br /> <br /> Research Projects reported from Nebraska:<br /> <br /> Crop Canopy Sensors: Results from canopy sensor studies in 2009 indicated that the chlorophyll index (CI) based on canopy reflectance in visible and near-infrared wavelengths ((NIR/VIS)-1) was highly correlated with crop canopy height, and both have similar ability to detect crop N status in the absence of other sources of stress. Crop canopy reflectance and canopy height were also significantly influenced by previous crop, with uniformly greater values for corn following soybean than for corn following corn. Additional studies in 2009 evaluated two canopy sensor threshold values for controlling N fertilizer applications. These thresholds limit N application rates when crop canopy reflectance drops to certain limits, at which canopy density or crop color is low enough that further N application will not increase yield potential  ie with planter gaps, eroded areas, etc.<br /> <br /> Soil Sensors: The integration of multiple spatial data layers to define targeted sampling sites and delineate potential areas for differentiated management was pursued. An objective function to make comprehensive comparison among different sets of targeted sampling sites was developed. A set of equations to conduct spatial clustering using the likelihood function were derived. New projects were initiated to optimize use of irrigation water and variable rate liming. For the optimized water use project, thematic soil maps have been used to develop a wireless network providing real-time capability to monitor spatially variable water needs in an experimental site. For a variable rate liming project, several Nebraska sites have been mapped and treatments comparing various liming strategies have been developed. <br /> Various Projects in North Dakota: Use of site-specific technologies, tools, and management continue to increase in North Dakota. <br /> <br /> Extension <br /> <br /> The participants conducted extension workshops on GIS, field demonstration of advanced sensors, developed fact sheets, podcast, and radio talks, newsletters, and the use of software tools for nutrient management and yield data manipulation. NCERA-180 participants continued to work toward the development of an eXtension web site on site-specific management. <br /> <br /> <br />

Publications

Allred, B., B. Clevenger, and D. Saraswat. 2009. Application of GPS and Near-Surface Geophysical Methods to Evaluate Agricultural Test Plot Differences. FastTimes. 14(3): 15-24.<br /> <br /> Bajwa, S. G., A. R. Mishra, and R. J. Norman. 2009. Canopy reflectance response to plant nitrogen accumulation in rice. Precision Agriculture DOI: 10.1007/s11119-009-9142-0<br /> <br /> Balasundaram, D., T. F. Burks, D. M. Bulanon, T. Schubert, and W. S. Lee. 2009. Spectral reflectance characteristics of citrus canker and other peel conditions of grapefruit. Postharvest Biology and Technology 51(2): 220-226. <br /> <br /> Bora, G. and R. Ehsani. 2009. Evaluation of a self-propelled citrus fruit pick-up machine. Applied Engineering in Agriculture. 25(6).<br /> <br /> Chinchuluun, R., W. S. Lee, and R. Ehsani. 2009. Machine vision system for determining citrus count and size on a canopy shake and catch harvester. Applied Engineering in Agriculture. 25(4): 451-458.<br /> <br /> Chinchuluun, R., Lee, W., Bhorania, J., and Pardalos, P. M. 2009. Clustering and classification algorithms in food and agricultural applications: A survey. In Papajorgji, P. and Pardalos, P. M. (eds.), Advances in Modeling Agricultural Systems. Berlin: Springer: pp. 433-454. <br /> <br /> Ehsani, R., T. E. Grift, J. M. Mari, and D. Zhong. 2009. Two fruit counting techniques for citrus mechanical harvesting machinery. Journal of Computers and Electronics in Agriculture. 65. 186-191.<br /> <br /> Hemmat A., A. Khorsandy, A. Masoumi and V.I. Adamchuk. 2009. Influence of failure mode induced by a horizontally-operated single-tip penetrometer on measured soil resistance. Soil Tillage and Research 105(1): 49-54. <br /> <br /> Hodgen, P., J. Schepers, W. Raun, J. Shanahan and R. Ferguson. 2009. Uptake of point source depleted 15N fertilizer by neighboring corn plants. Agron. J. 101:99-105.<br /> <br /> Holan, S., Wang, S., Arab, A., Sadler, E.J., and Stone, K.C. 2008. Semiparametric geographically weighted response curves with application to site specific agriculture. Journal of Agricultural, Biological, and Environmental Statistics 13(4):424-439. <br /> <br /> Jiang, P., He, Z., Kitchen, N.R., and Sudduth, K.A. 2009. Bayesian analysis of within-field variability of corn yield using a spatial hierarchical model. Precision Agriculture 10: 111-127. <br /> <br /> Kim, H.J., Sudduth, K.A., and Hummel, J.W. 2009. Soil macronutrient sensing for precision agriculture. Journal of Environmental Monitoring 11: 1810-1824.<br /> <br /> Kim, D. G., T. F. Burks, A.W. Schumann, M. Zekri, X. Zhao, and J. Qin. 2009. Detection of Citrus Greening Using Microscopic Imaging. Agricultural Engineering International: the CIGR Ejournal XI(2009): 17.<br /> <br /> Kitchen, N.R., Sudduth, K.A., Drummond, S.T., Scharf, P.C., Palm, H.L., Roberts, D.F., and Vories, E.D. 2010. Ground-based canopy reflectance sensing for variable-rate nitrogen corn fertilization. Agronomy Journal 102:71-84. <br /> <br /> Kulkarni, S.S., S. G. Bajwa. 2009. Investigation on effects of soil compaction in cotton. Transaction of ASAE. Conditionally Accepted.<br /> <br /> Lee, K. H. and R. Ehsani. 2009. A laser scanner based measurement system for quantification of tree geometric characteristics. Applied Engineering in Agriculture. 25(5): 777-788.<br /> <br /> Lee, K.S., Lee, D.H. Sudduth, K.A., Chung, S.O., Kitchen, N.R., and Drummond, S.T. 2009. Wavelength identification and diffuse reflectance estimation for surface and profile soil properties. Transactions of the ASABE 52(3): 683-695. <br /> <br /> Lee, W., Bogrekci, I. and Min, M. 2009. Modeling in nutrient sensing for agricultural and environmental applications." In Papajorgji, P. and Pardalos, P. M. (eds.), Advances in Modeling Agricultural Systems. Berlin: Springer: pp. 297-315.<br /> <br /> Maja, J. M. and R. Ehsani. 2009. Development of a Yield Monitoring System for Citrus Mechanical Harvesting Machines. Journal of Precision Agriculture. (Accepted) Available on line: http://www.springerlink.com/content/v577402666302186/?p=2d7e4643059446f08127127c457bac06&pi=8<br /> <br /> Okamoto, H., and W. S. Lee. 2009. Green citrus detection using hyperspectral imaging. Computers and Electronics in Agriculture 66(2): 201-208.<br /> <br /> Roberts, D.F., V.I. Adamchuk, J.F. Shanahan, R.B. Ferguson, and J.S. Schepers. 2009. Optimization of crop canopy sensor placement for measuring nitrogen status in corn. Agronomy Journal 101(1): 140-149.<br /> <br /> Roberts, D.F., Kitchen, N.R., Scharf, P.C, and Sudduth, K.A. 2010. Will variable-rate nitrogen fertilization using corn canopy reflectance sensing deliver environmental benefits? Agronomy Journal 102:85-95. <br /> <br /> Roberts, D.F., V.I. Adamchuk, J.F. Shanahan, R.B. Ferguson, J.S. Shepers. 2010. Estimation of surface soil organic matter using a ground-based active sensor and aerial imagery. J. Precision Agriculture (in press).<br /> <br /> Scharf, P.C., and Lory, J.A. 2009. Calibrating reflectance measurements to predict optimal sidedress nitrogen rate for corn. Agronomy Journal. 101:615-625.<br />

Impact Statements

1. Continued development of an eXtension web site on precision agriculture.
2. Published an ASABE standard on yield monitor performance test.
3. ASABE standard on yield monitor field test engineering procedure voted and finalized.
4. Three books in The "GIS Application in Agriculture" series on way to publication.
5. Significant spectral bands to detect citrus greening disease (Huanglongbing or HLB) were identified through multivariate statistical analyses. It was found that different vegetation indices could be used to separate healthy and infected tree pixels as a preliminary step and thereby increase accuracy of detecting infected trees.
6. Based on research by University of Missouri and ARS scientists, Missouri NRCS included variable-rate N management based on crop canopy sensing as an Environmental Quality Incentives Program (EQIP) strategy in 2007-2009.
7. North Dakota reported increase in the use of site-specific technologies during 2009, partly due to grower response to increased input costs.

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Report Information

Participants

Saraswat, Dharmendra (dsaraswat@uaex.edu);
Barbosa, Roberto (rbarbosa@agcenter.lsu.edu);
Andrade, Pedro (pandrade@ag.arizona.edu);
Kulkarni, Subodh (skulkarni@uaex.edu);
Shaver, Tim (tshaver2@unlnotes.unl.edu);
Lund, Eric (lunde@veristech.com);
Bajwa, Sreekala (sgbajwa@uark.edu);
Lee, Wonsuk (wslee@ufl.edu)
Grove, John (jgrove@uky.edu);
Ehsani, Reza (rehsani@ufl.edu);
Bora, Ganesh (ganesh.bora@ndsu.edu);
Phillips, Steve (sphillips@ipni.net);
Monfort, Scott (smonfort@uaex.edu);
Terry Griffin, Terry (tgriffin@uaex.edu);
Stombaugh, Timothy (tss@uky.edu);
Upadhyaya, Shrinivasa (skupadhyaya@ucdavis.edu);
Kelley, Van C. (van.kelley@sdstate.edu);
Khosla, Raj (raj.khosla@colostate.edu);
Tian, Lei (lei-tian@illinois.edu);
Hernandez, Jose (jahernan@umn.edu);
Espinoza, Leo (lespinoza@uaex.edu);
Mueller, Tom (mueller@uky.edu);
Stevens, Steve (sstevens714@aol.com);
Burton, Jim (jim@agrobotics.com);
Burton, Jeffrey (jeff@agrobotics.com);
Young, Nancy (nancy.young@ar.usda.gov);
Schmoldt, Daniel (dschmoldt@nifa.usda.gov);
Nowatzki, John (john.nowatzki@ndsu.edu);
Traywick, Deano (dtraywick@uaex.edu);

Brief Summary of Minutes

March 23, 2011 (Field Tour)

A field tour to the Nordex USA Inc. plant in Jonesboro, AR. was organized as per the following schedule:

12:00 p.m. Leave Crowne Plaza Hotel
02.45 p.m.  4.30 p.m.Tour Nordex USA Inc. plant at Jonesboro, AR
07.15 p.m.  Return Crowne Plaza Hotel

March 24, 2011

Meeting started at 7.45 a.m. with registration and continental breakfast. At 8.15 a.m., Dharmendra Saraswat, the committee chair, called the meeting to order.

Dharmendra invited Dr. Rick Cartwright, Associate Director (Agriculture and Natural Resources),University of Arkansas Division of Agriculture Cooperative Extension Service to welcome the group. Dr. Cartwright welcomed everyone to the State of Arkansas, provided a brief overview of challenges facing agriculture, and exhorted the group to provide appropriate solutions.

Invited Speakers
A total of eight invited speakers, four in the forenoon and four in the afternoon made presentations. A title of the presentations along with the speakers is given below.

1. Title: Make the Most of Spatial Technologies- An Ag Retailers Perspective
Clint Jayroe, Jimmy Sanders Inc.

2. Title: Incentives and Barriers to Site Specific Farming- A Farmers Perspective
Steve Stevens, Chair, Arkansas Cotton Support Committee

3. Title: Specialty Crop Development for Small Farms
Dr. Reza Ehsani  University of Florida, Citrus Research and Extension Center

4. Title: MRBI: Challenges and Opportunities
Nancy Young, NRCS Arkansas State Resource Conservationist

5. Title: Optic Mapper
Eric Lund, Veris Technologies


6. Title: Soil Sampling Probe
Jim and Jeffrey Burton, AgRobotics Autoprobe

7. Title: Precision Agriculture Status and Needs in Arkansas
Dr. Sreekala Bajwa, University of Arkansas

8. Title: BioChar
Dr. David Clay- South Dakota State University (Presented by Dr. Van Kelley). Dharmendra thanked Dr. Kelley for becoming Administrative Advisor to the group.

Jim and Jeffrey Burton conducted demonstration of Soil Sampling Probe and answered questions. Tim Stombaugh provided an update on standard activities and also briefed the group on discussions that took place on data format standardization during Ag Connect meeting in Atlanta.

The meeting was adjourned around 5.00 p.m.

March 25
Daniel Schmoldt joined via video conferencing and made a presentation about funding opportunities available for the group. He answered questions by the group. Dharmendra initiated a discussion on the needs and new approaches to be pursued by the group. It was decided that a database of participants will be made available at the new website being maintained by Tom Mueller. Jose Hernandez from Minnesota agreed to provide support to Tom for the website. The group took a note of dwindling participation from the Industry and discussed ways to encourage their participation. A sub committee was formed consisting of incoming chair, Pedro Andrade and Timothy Stombaugh to come up with a plan in this regard. It was suggested that besides equipment manufacturers, data management companies should also be extended an invitation to become a part of the group. Van Kelley provided an update about the new proposal and requested everyone to provide a brief report on accomplishments, publications, and impact statement to Pedro at the earliest.

Raj Khosla provided an updated on ICPA and ISPA (International Society of Precision Agriculture) activities. He informed the group about the successful organization of Indo-US workshop on precision agriculture. He went through features of ISPA, which is now a legal entity in the state of Illinois. ISPA has members from 38 countries and has 26 country representatives. He informed that the group should make use of the ISPA website (http://www.internationalsocietyofprecisionagriculture.org/) for new announcements such as job related postings. In addition, the ISPA site will serve as a platform to receive donations and post pictures of precision ag activities as well as announcements of new venues. Raj informed on the upcoming the European and Asian Precision Ag. Meetings (in Japan and Prague) in July 2011. He discussed possible dates for organization of ICPA at Indianapolis, IN during 2012. Raj also informed about a new book being put together by David Clay and Fran Pierce with Springer on the state of precision farming, and collected information about potential topics and contributors, along with contact information for passing on to David and Fran. Raj Khosla reminded the audience of the ASA symposium in precision ag. in 2012.

Pedro informed that 2012 meeting will be organized in Phoenix , AZ during the month of March. The dates of the meeting will be decided after soliciting inputs from the group. A discussion followed in regards to topics/general concepts for the 2012 meeting (such as Advanced Technologies) and industry/academics participation in future NCERA-180 annual meetings. Pedro Andrade volunteered to construct a questionnaire and distribute among industry people (mostly farm equipment companies, but make sure to extend it to new small data management companies). The objective of the questionnaire will be to determine their interests and what would they like to obtain from us. To increase participation one idea that circulated was to meet during the InfoAg meeting in Springfield IL on July 12-14 and use this time to talk to key players in precision agriculture from industry, academics, and regulatory agencies about our work in NCERA-180. We discussed about possible reasons for diminishing participation among academics; limited funding is one reason, and refocus on a multi-disciplinary approach should help to re-capture the interest in our project among academics.

Tom Muller volunteered to help Pedro in the organization of next years meeting. The general theme will turn around whats useful to the producers and the interests for industry to fill in.

Lei Tian, University of Illinois, Urbana Champagne (UIUC) was unanimously elected to be chair for 2013. Lie Tian provided an update on continuous imaging approach being used at UIUC.

Timothy Stombaugh provided updates on precision ag sessions in ASABE International meeting.

Terry Griffin provided an update on USDA-ARMS (farm level) survey and CropLife survey. He informed that Purdue University led CropLife survey could not be conducted in 2010 due to a variety of reasons.
John Nowatzki joined via video conferencing from North Dakota and requested the group to contribute actively for eXtension initiative on precision agriculture. Moreover a discussion followed on trends in federal funding (i.e. less formula funding) and the need to increase multi-state multi-disciplinary participation. In this discussion it was suggested that NCERA-180 members should communicate with their respective Stakeholders to pressure Congress for more appropriation funds that will benefit research and extension in agriculture.
Tom Muller informed that the new NCERA-180 proposal was submitted in Nov 2010. Approval is pending, but the comments received were favorable.
Pedro Andrade will take on the responsibility of writing the 2010 NCERA report and file it within 60 days. The state representatives will send information on proposals, accomplishments, impact statements and publications to Pedro to be compiled in the report.

Towards the end, Dharmendra thanked everybody associated with the organization of this meeting including his team at the University of Arkansas Division of Agriculture Cooperative Extension Service. The group appreciated Dharmendra for his efforts in successfully organizing the meeting in Arkansas. The meeting ended at 12.30 pm.

Accomplishments

Accomplishments in Research by State:<br /> Arizona<br /> 1. Precision canopy and water management of specialty crops through sensor-based decision making. This project uses proximal sensors mounted on a mobile platform to provide the information desired by stakeholders. These include information on canopy architecture and light interception using Pohtosynthetically Active Radiation (PAR) sensors, plant-soil water status using a sensor suite consisting of a thermal IR gun, ambient temperature, humidity and wind speed sensors. Moreover, this project aims to develop a data visualization software and a decision support system to assist with management decisions. <br /> <br /> 2. Assessment of hail damage in cotton using active-light spectral sensors. This project is about using sensor technology to make a quick assessment of the amount of canopy and rate of recovery after a simulated hail event. This project will give information on sensor-based spectral indices that can represent the extent of damage of cotton plants and generate savings to the crop insurance industry. <br /> <br /> 3. Field distribution of soil and plant variables affecting wheat grain protein content and yield: A field-scale study to improve farm management. The purpose of this study is to relate certain soil and plant characteristics measured before harvest to durum protein content and yield on a field-scale. We will study the relationships among 1) soil nitrogen, texture, and electrical conductivity, 2) plant nitrogen content and growth, 3) grain yield, and 4) grain protein content. <br /> <br /> 4. Characterization of spatial variation in wheat yield and protein using soil and plant sensors. An improved scheme of field-level research will be carried out with particular attention to capturing the dynamics of soil/plant Nitrogen. This will be achieved with soil/plant sampling for laboratory analysis of N status at tillering, jointing, booting, and flowering of durum wheat; along with spectral measurements of the crop using hand-held instruments. <br /> <br /> 5. Improving Arizona tree crop weed management. This project will evaluate newly registered pre-emergence herbicides to determine how many post-emergence herbicide sprays can be eliminated annually and to develop herbicide programs that minimize the risk of developing herbicide resistant weeds by measuring the light reflectance characteristics of the orchard floor and obtain the technical data needed to develop a more robust automatic spot spraying system. <br /> <br /> 6. Soil compaction reduction of date yields. Date palms have a shallow root system that differs from most tree crops. This projects aims at characterizing the dynamics of soil strength and root growth through the growing season, and establish the nature of the relationship between compaction levels and yield components, especially date quality.<br /> <br /> 7.Characterizing plant height, canopy temperature and reflectance for high-thruput phenotyping. We are doing extensive testing of proximal sensing techniques with high-clearance ground systems for field-based high-thruput phenotyping. We are collaborating in this project with scientists of the USDA-ALARC.<br /> <br /> 8. Cotton yield monitoring in commercial fields. For the 2010 cotton harvest season we used a commercially available yield monitoring system installed in a 6-row John Deere cotton picker. The system required interfacing GPS and micro-wave sensors to a controller located in the cab. We collected geo-referenced yield data in several fields in Buckeye and Paloma AZ.<br /> <br /> Arkansas<br /> Detection of charcoal rot in soybean with remote sensing<br /> <br /> Charcoal rot is soybean disease that causes significant economic losses. It often strikes the plant when the plant is already stressed due to lack of water and nutrients, or during reproduction. Hence it is difficult to detect. Some of the cultivars of soybean have shown some resistance to this disease. If the onset of disease can be detected with remote sensing in multiple cultivars with different degree of resistance, that would save a lot of time and effort on the part of the grower. The part of this multistate project that I focus on is to identify whether remote sensing is an effective tool to monitor the disease, especially early during the infestation. We (I in collaboration with John Rupe) have conducted two years of micro-plot experiment with 4 different cultivars (with different degree of resistance), two levels of disease treatment, and two levels of water stress. The plants were monitored for canopy reflectance, stomatal conductance, canopy temperature, disease rating, etc. Unfortunately, the excessively wet 2008 season was not favorable for active disease proliferation. We are still analyzing the data from 2009.<br /> <br /> California<br /> Precision Canopy and Water Management of Specialty Crops through Sensor-Based Decision Making<br /> <br /> There is a need to develop and deploy farm-based, reconfigurable, sensors and/or sensor suites that can be retrofitted to a mobile platform and associated decision support tools to assist growers in making better management decisions to improve crop quality and increase production efficiency and farm profitability, while reducing their environmental footprint. To address these issues we have developed a multi-state, cross disciplinary project with specific objectives: (i) Measure canopy architecture and PAR absorption; (ii) Detect soil and plant water status; (iii) Develop a Universal Navigation Computer (UNC); (iv) Develop a visualization and decision support system; (v) Develop a variable rate water application system; (vi) Conduct economic analysis; (vii) Evaluate social implications. The development and refinement of a PAR measurement system (obj#1), sensor suite for plant water status (obj#2), autonomous vehicle (obj#3), and wireless network for irrigation management (obj#5) will occur during year 1 of the study. These devices/systems will be field tested during year 2 of the study. Extensive data collection will also occur during the second year. The decision support system (DSS) will be developed during the first year (obj#4). DSS will be implemented during the second year. During year 1 growers will be identified for socio-economic analysis (Obj #6 and 7). Some preliminary data collection will occur. During the second year majority of the data would be collected and analyzed. Data collection and analysis will continue into year 3 of the project. Outreach activities will start with the second year of the project. Webinars detailing the progress of the project will be developed during year 2. Main emphasis during year 3 will be presentations and demonstrations during field days, and development of instructional videos that detail most promising technologies developed for grower audience. Four states in the western region  Arizona (pecans), California (almonds, grapes, and walnuts), Oregon (hazelnuts), and Washington (apples and grapes)  will participate in this project. The expected outputs of this project are  (i) field verified sensors mounted on mobile platforms for measuring canopy architecture and plant water status, (ii) a decision support system to implement canopy management and irrigation management based on sensor data, (iii) development of a technology to apply water to individual or block of trees based on soil and plant water status, and (vi) determination of socio-economic implications of the developed technologies. Canopy management and irrigation management of orchard and vineyard crops were identified as the most critical needs of the special crops industry. Four states in the western region  Arizona (pecans), California (almonds, grapes, and walnuts), Oregon (hazelnuts), and Washington (tree-fruits and grapes)  are collaborating to address these major issues. The expected outcomes of this project are  (i) field verified sensors mounted on mobile platforms for measuring canopy architecture and plant water status, (ii) a decision support system to implement canopy management and irrigation management based on sensor data, (iii) development of a technology to apply water to individual or block of trees based on soil and plant water status. Better canopy management is expected to results in increased light absorption and yield, while improved irrigation management is expected to help conserve precious water resource in the dry western region.<br /> <br /> Colorado<br /> Rates of dissipation of Atrazine and Metolachlor across different soil management zones<br /> <br /> The objectives of a recently completed study were to compare the rates of dissipation of atrazine and metolachlor across different soil management zones from three dryland no-tillage fields under laboratory incubation conditions and determine if rapid dissipation of atrazine and/or metolachlor occurred in dryland soils. Herbicide dissipation was evaluated at time points between 0 and 35 days after soil treatment using a toluene extraction procedure with GC/MS analysis. <br /> Our findings indicate that differential rates of atrazine and metolachlor dissipation occur across soil zones on two of three fields that we evaluated. In addition, accelerated atrazine dissipation occurred in soil from all fields of this study with half-lives ranging from 1.8 to 3.2 days in the laboratory. The rapid atrazine dissipation rates found were likely attributed to the history of atrazine use on all fields investigated in this study. Metolachlor dissipation was not considered accelerated and exhibited half-lives varying from 9.0 to 10.7 days in the laboratory. While, accelerated dissipation of atrazine as exhibited on all fields of our study has been reported previously. Our study, however, is among the first to report such high rates of atrazine dissipation in soil from semi-arid dryland cropping environments (1.8 to 3.2 days, as compared to previously reported half-lives for atrazine ranging from 45  180 days previously reported in literature). Further work under field conditions needs to be performed to confirm the results of this research and to determine the agronomic significance (i.e., effects on weed control) of the different rates of herbicide dissipation. <br /> <br /> Florida<br /> 1. Autonomous vehicles offer additional labor-saving benefits for farms of the future. In 2010 we completed the design and fabrication of a variable rate orchard sprayer controller for use with John Deere autonomous tractors currently being tested at Southern Gardens grove. The difference between the conventional controller and the sprayer controller for driverless autonomous tractor use is the additional sensors that are required to detect faults, monitor spray operations, and interface with the autonomous tractor computer. The controller system therefore consists of sensors for monitoring flows, system pressure, tank level, filter clogging, PTO, fan, agitator and tire pressure and actuators for motorized on-off valves. During 2010 the ability to independently regulate chemical flow in the 20 spray nozzles of the precision sprayer was added by redesigning and building a more sophisticated circuit board with 13 embedded microcontrollers. Performance tests (spray coverage) were conducted using Surround (kaolin) in commercial citrus trees of varying size and canopy densities.<br /> <br /> 2. A number of sensing techniques were investigated for stress detection in citrus. The different sensing techniques that were investigated are summarized as follows:<br /> MID-INFRARED SPECTROSCOPY: Mid-infrared spectroscopy was applied for detection of Huanglongbing (HLB) disease and nutrient-deficiency in citrus leaves. The basis behind the detection of disease and its differentiation from healthy and nutrient-deficient leaves was the identification of starch accumulation that specifically occurs in diseased leaves. This method showed potential in the detection of disease even in asymptomatic stages, during which the accumulation of starch begins. This method of HLB detection showed potential to identify the disease in asymptomatic stages based on starch accumulation. When the citrus tree is infected with disease, the starch begins to accumulate even before the symptoms appear. The detection of HLB in asymptomatic stages is critical as it would reduce the spread of disease through identification and removal of infected trees in early stages. The method showed a classification accuracy of 90% and higher<br /> VISIBLE-NEAR INFRARED SPECTROMETRY: This is a non-destructive, field-based method of stress detection Visible-near infrared spectrometry was applied for detection of HLB in asymptomatic and symptomatic stages, and nutrient-deficiency in leaves. As this region of electromagnetic spectra is sensitive to the light changes, a large set of data (in hundreds) was collected to account for the variability in field condition. Preliminary analysis indicated that this method is suitable for disease detection in symptomatic stages. Further investigations on the sensor applicability for disease detection during asymptomatic stages and nutrient-deficiencies in leaves are ongoing. Through experimentation, it was established that the leaves with HLB symptoms can be clearly differentiated from that of healthy leaves using this method. This method is further being investigated to reduce the cost of the sensor system and further improve the efficiency and accuracy of the system<br /> FLUORESCENCE SPECTROSCOPY: A portable field-based active fluorescence sensor was used for disease and nutrient-deficiency detection in leaves. Field and laboratory fluorescence data have been collected from Hamlin and Valencia varieties and are currently being processed to validate the suitability of the method. In addition to these techniques, other sensors or sensing techniques that were investigated are: multi-band sensors for citrus canopy anomaly detection (active four-band sensor and passive five band sensor with auto-calibration abilities), hyperspectral imaging, fluorescence imaging for detection of citrus diseases (citrus variegated chlorosis, HLB, canker, etc), visible-near infrared-based sensing for Laurel Wilt detection in Avocado, and application of high-resolution aerial imaging for stress detection in citrus, nursery, sugarcane and apples.<br /> <br /> 3. A continuous citrus canopy shake and catch harvester has been modified by exchanging a regular de-stemmer with an extended de-stemmer for more efficient elimination of debris (also known as trash materials such as leaves, twigs and branches) from harvested citrus fruits. An extended de-stemmer with a set of ten 36 inch long rollers was used at a citrus grove for conducting experiments. A modified catch frame of the harvester using a longer de-stemmer was tested to remove petioles from harvested fruit, and its efficiency was 80%. The trash removal efficiency of the catch frame de-stemmer was 99.86% of the total trash. During 2010 harvesting season, we have tested a longer de-stemmer for a continuous canopy shake and catch harvester and found that the longer de-stemmer was more effective in removing trash materials during harvesting. This longer de-stemmer can be implemented on all mechanical harvesters for more efficient debris removal. <br /> <br /> 4. An algorithm for automatically estimating mass of debris in a citrus canopy shake and catch harvester using machine vision was investigated. An experimental test bench was set up to train and to validate the image processing algorithm. It included steps of image rectification, overlapped area removal, morphological operations and removal of undesired debris on the ground using a novel Parse and Add algorithm. A representative set of 180 images were processed with the algorithm and the debris objects were identified. The results from the machine vision algorithm for estimating debris mass showed that the coefficient of determination (R-squared) between the pixel area and debris mass for calibration was 0.946 and R-squared between actual and estimated mass for validation set from the test bench was 0.815 with an RMSE of 1.88 kg. For the field experiment, the R-squared between the actual and estimated debris mass for individual images was 0.78, and the RMSE was 0.02 kg. The error between total actual and estimated mass for the field experiment was 25.3%. The debris mass estimates were also correlated with GPS data to create a geo-referenced map of the debris gathered. The developed debris mass estimation system could play a crucial role in solving the problem of safe and economical disposal of diseased leaves and twigs. For the green citrus fruit detection algorithm, 75.3% of the actual fruits were successfully identified using the proposed algorithm for the validation set. <br /> <br /> 5. For a rapid detection of the citrus greening disease, an aerial hyperspectral image in 457-921 nm with 128 bands was acquired from an HLB infected citrus grove in December 2009 in Florida. A multispectral image with 4 bands (red, green, blue, and NIR) in 480-830 nm with 40 nm bandwidth was also acquired. Polymerase chain reaction (PCR) test based ground truthing had been carried out where the infected tree canopy coordinates were recorded. An image derived spectral library was built and categories of Healthy and HLB infected pixels were created based on the PCR results and locations of the infected trees. Ground measurements were obtained for Healthy and HLB infected citrus trees with their degrees of infection. HLB infected areas were identified using image-derived spectral library, the mixture tuned matched filtering (MTMF), the spectral angle mapping (SAM), and linear spectral unmixing (LSU). A new set of aerial images of HLB infected groves has been acquired on December 3, 2010 at two different sites using three camera systems (color, multispectral and hyperspectral cameras) with the cooperation of the USDA ARS group in Texas. The first grove was located near Clewiston in Hendry County and the second was at the CREC (North 40 and CREC) in Lake Alfred in Polk County. Reflectance of healthy and infected canopies were measured and their coordinates were also recorded using an RTK GPS receiver. For aerial hyperspectral HLB detection, it was observed that accuracy of MTMF method was greater than the other methods. The accuracy of SAM using multispectral images was comparable to the results of the MTMF and also gave higher accuracy when compared to SAM analysis on hyperspectral images. A fairly high detection accuracy of 80% was achieved using MTMF on hyperspectral image. SAM with multispectral images also gave a very high detection rate of 87%. A better estimate of accuracy can be achieved with more PCR results and a more comprehensive ground survey. This would help in the quantization of false positives in the result.<br /> <br /> 6. A machine vision algorithm was developed to detect and count immature green citrus fruits in natural canopies using color images. Color, circular Gabor texture analysis and eigenfruit approach were used for green citrus detection. A shifting sub-window was classified three times by eigenfruit approach using intensity component, eigenfruit approach using saturation component, and circular Gabor texture. <br /> <br /> Minnesota<br /> Fusion of hyper-spectral and thermal images for evaluating Nitrogen and water status in potato fields for variable rate application.<br /> <br /> Field experiments are being conducted (2010-2011) at the University of Minnesota Sand Plain Research Farm near Becker, MN. In 2010 experiments were conducted on two potato varieties (Russet Burbank & Alpine Russet), with two irrigation rates (conventional irrigation and water stressed), and with five different N treatments. Each treatment was replicated four times in a randomized split-split plot design. Petiole and leaflet samples and chlorophyll meter readings were taken five times throughout the growing season. Chlorophyll readings were taken with a Minolta SPAD-502 chlorophyll meter. Leaf area index (LAI) was measured with a LAI-2000 plant canopy analyzer on five dates throughout the growing season. Ground measurements for reflectance were taken on six dates with an MSR16R Cropscan on the same day or within two days of the SPAD readings. Soil matric tension was measured with granular matrix soil moisture sensors (Watermark Model 200) in and below the root zone. Data loggers were located in four locations and each recorded matric potential (kPa) in one of four plots. Leaf canopy temperature was measured with infrared radiometers (Apogee Model SI-111). For measurement of soil water NO3 concentration, lysimeters were installed 120 cm vertically below the third hill of each Russet Burbank plot. Soil water samples were collected weekly or following any significant rain event in which drainage was suspected to occur. Samples will also be collected after ground thaw in the spring of 2011. Finally, aerial hyperspectral and thermal remotely sensed images were acquired with an AISA Eagle VNIR hyperspectral imaging sensor and a FLIR Systems ThermaCam SC640, respectively, by the Center for Advanced Land Management Information Technologies (CALMIT) at the University of Nebraska-Lincoln, USA. Analyses are being carried out for the 2010 season and the 2011 experiment will begin in May 2011.<br /> <br /> <br /> Accomplishments in Extension<br /> Extension bulletins:<br /> Things to know about applying precision agriculture technologies in Arizona. Andrade-Sanchez, P., and Heun, J. T. 2010. Things to know about applying precision agriculture technologies in Arizona. Cooperative Extension Service, University of Arizona, Bulletin AZ1535 In Press.<br /> <br /> Understanding technical terms and acronyms used in precision agriculture. Peer-reviewed. Andrade-Sanchez, P., and Heun, J. T. 2010. Understanding technical terms and acronyms used in precision agriculture. Cooperative Extension Service, University of Arizona, Bulletin AZ1534 In Press.<br /> <br /> Integrating variable rate technologies for soil-applied herbicides in Arizona vegetable production. Peer-reviewed. Nolte, K. D., Siemens M. C., and Andrade-Sanchez, P. 2010. Integrating variable rate technologies for soil-applied herbicides in Arizona vegetable production. Cooperative Extension Service, University of Arizona, Bulletin AZ1538 In Press.<br /> <br /> Workshops and training:<br /> "Using precision technologies to increase efficiency in cotton production" Cotton Early Season Meetings. Maricopa Agricultural Center, 2/23/2010; Marana AZ 3/2/2010, 2010.<br /> <br /> Demonstration on cotton close cultivation with RTK autoguidance. Field and machinery provided by Grower Tom Clark, Marana, AZ. 6/13/2010.<br /> Talk with the title: "Potential use of soil and plant sensors to improve in-season management" Cotton Mid Season Meetings. Safford Agricultural Center, 7/15/2010; Parker, AZ, 8/13/2010.<br /> <br /> Demonstration on variable rate injection of fertilizer in cotton production. MAC Annual Field Day. Maricopa Agricultural Center, 10/19/2010.<br /> "Potential use of soil and plant sensors to improve in-season management" Cotton Mid Season Meetings. Safford Agricultural Center, 7/15/2010; Parker, AZ, 8/13/2010.<br /> <br /> Saraswat, D., J.L. Peterson, J. Salle, M. Smolen, and R. Faucette. 2010. Introduction to GIS/GPS Tools for Agriculture, Natural Resources, 4-H, and Watershed Management. Tulsa, April 12, 13 attendees. <br /> Saraswat, D. 2010. Introduction to GPS. Marianna, AR, March 17, 7 attendees.<br /> Radcliffe, D., D. Saraswat, J. L. Peterson, R. Faucette, S.S. Panda, and T. Sweeney. 2010. Introduction to GIS/GPS Tools for Agriculture, Natural Resources, 4-H, and Watershed Management. Hilton Head, February 25, 32 attendees.<br /> <br /> Saraswat, D. 2010. Introductory ArcGIS. Little Rock, AR, February 17, 8 attendees.<br /> <br /> Saraswat, D. 2010. Google Earth applications for crop consultants. In Arkansas Crop Management Conference, Little Rock, January 21. 31 attendees.<br /> <br /> Saraswat, D. K.Prasanna, and J.L. Peterson. 2010. Google Earth Workshop. 65 pp.<br /> <br /> Saraswat, D. 2010. Introductory ArcGIS 9.3.1. 87 pp.<br /> Robbins, J., D. Saraswat, R. Ehsani, J. Maja, S. Doane, J. Owen, and J. Kupillas. 2010. Multi-rotor systems prove beneficial for inventory data collection. Nursery Management, November 18 issue. Available at http://www.nurserymanagementonline.com/nmpro-1110-nursery-picture-this-tools.aspx Accessed January 10, 2011.<br /> <br /> Accomplishments in Grant Proposals:<br /> A multistate, cross disciplinary project, Precision Canopy and Water Management of Specialty Crops through Sensor-Based Decision Making was written and submitted to USDA, NIFA for funding under SCRI grant funding opportunity. This is a multi-state project lead by Dr. Shrinivasa Upadhyaya (UCDavis). It includes NCERA-180 members from California, Arizona, and Washington. It also included participants from Oregon State, and Industries such as Trimble Navigation Ltd. and VERIS Technologies Inc. The above proposal was funded and is currently active. It started on Sepetmebr 1, 2010 and will end on August 31, 2013 (USDA-SCRI- 2010-01213)<br /> <br /> A USDA Specialty Crop Research Initiative (SCRI) Research Planning Proposal titled, Improving the profitability of blueberry production with a comprehensive precision agriculture program was funded in 2009. On February 9-10, 2010, a research proposal planning meeting has been held in Orlando, Florida and a full research proposal development has been discussed. A total of 17 people from industries, grower organizations, and universities from multiple states and Canada have participated. A full proposal was developed and submitted to the USDA SCRI funding program in January 2011. <br /> <br /> ND Corn Council, relate active optical sensors (Greenseeker and Holland Crop Circle) with corn N status, funded April 2010-March 2012. Franzen, PI.<br /> <br />

Publications

Sun, H., D. C. Slaughter, M. P. Ruiz, C. Gliver, S. K. Upadhyaya, and R. F. Smith. 2010. RTK GPS mapping of transplanted row crops. Computer and Electronics in Agriculture. 71:32-37.<br /> <br /> Upadhyaya, S. K., D. K. Giles, S. Haneklaus, and E. Schnug. 2010. Advanced engineering systems for specialty crops: A review of Precision Agriculture for water, chemical, nutrient application, and yield monitoring. Author and editor. vTi Special Issue 340. <br /> <br /> Jahn, B. R., and S. K. Upadhyaya. 2010. Determination of soil nitrate and organic matter content using portable, filter-based mid-infrared spectroscopy. Chapter 12. In Proximal Soil sensing. Edited by R. A. Viscarra Rosel et al. Progress in Soil Science 1. <br /> <br /> Udompetaikul,V, S. K. Upadhyaya, B. Lampinen, and D. Slaughter. 2010. Development of a sensor suite to determine plant water potential. ASABE paper 1009450. ASABE, St. Joseph, MI 49085. Also presented at the 10th International Conference of Precision Agriculture in Denver, CO. ICPA 10-391.<br /> <br /> <br /> Bajwa, S.G., A. R. Mishra, and R. J. Norman. 2010. Canopy reflectance response to plant nitrogen accumulation in rice. Precision Agriculture 11(5): 488-506. <br /> <br /> Kulkarni, S. S., and S.G. Bajwa. 2010. Investigation on effects of soil compaction in cotton. Transactions of the ASABE 53(3): 667-674. <br /> <br /> Bajwa, S.G., A. R. Mishra, and R. Norman. 2010. Plant nitrogen accumulation dynamics in rice (Oryza sativa L.) in response to nitrogen management. Communications in Soil Science and Plant Analysis 41(4): 454-471. <br /> <br /> Bajwa, S.G., and J. A. Apple. 2010. Non-linear modeling of quality of cooked ground beef patties with visible-NIR spectroscopy. In: Food Engineering, B. C.Siegler (Ed). Nova Science Publishers, Inc., Hauppauge, New York. ISBN 978-1-61728-913-2. <br /> <br /> Bajwa, S.G. and S. S. Kulkarni. 2010. Hyperspectral Data Mining. In:.Hyperspectral Remote Sensing of Vegetation, P.S. Thenkabail, J. G. Lyon and A.Huete (Eds). ISBN 978-1-4398453-7-0, CRC Press.<br /> <br /> Saraswat, D. 2010. Geospatial Technologies: Unlimited Possibilities for Outreach Education. Delivered before faculty, staff and graduate students of the Department of Food, Agricultural and Biological Engineering, The Ohio State University, Columbus, OH, October 15.<br /> <br /> Saraswat, D., L. Espinoza, S. Kulkarni, and Terry Griffin. 2010. Comparative Performance Evaluation of Open and Closed Loop System for Spinner Disc Control on Dry Fertilizer Spreader. In ASABE 2010 Annual International Meeting, Pittsburg, PA, June 20-23.<br /> <br /> Maja, J.M., R. Ehsani, D. Saraswat, and J. Robbins. 2010. A Tree Counting and Caliper Measurement System for Open Field Nursery Using Image Processing. In ASABE 2010 Annual International Meeting, Pittsburg, PA, June 20-23.<br /> <br /> Kulkarni, S.S, L.T. Barber, E. Barnes, T.W. Griffin, and D. Saraswat. 2010. Cotton Canopy Response to Nitrogen Treatments in Arkansas: Observations Using Crop Circle (ACS-470). In ASABE 2010 Annual International Meeting, Pittsburg, PA, June 20-23.<br /> <br /> Traywick, D. and D. Saraswat. 2010. Precision Agriculture Sensors used in Arkansas. In 2010 Teen Leader Conference. 4-H Center, Ferndale, AR, June 9.<br /> <br /> Saraswat, D. and T. Griffin. 2010. Delivering Solutions for Agriculture and Natural Resources through Geospatial Technologies. In 2010 Arkansas GIS User Forum Spring Meeting, Little Rock, AR, April 8.<br /> <br /> Espinoza, L., D. Saraswat, and M. Ismanov. 2010. Assessment of selected electrical conductivity sensors. In Beltwide Cotton Conference. New Orleans, LA, January 4-7.<br /> <br /> Saraswat, D. 2010. Remote sensing for tree counting. Presented before Oregon Nursery Association (ONA) members and nursery industry representatives, Portland, OR, September, 9.<br /> <br /> L. Espinoza, D. Saraswat, D. Traywick, M. Ismanov, and P. Ballantyne. 2010 Managing Spatial Variability in Crop Production in Arkansas. In Cotton Research Field Day, Marianna, AR, August 19.<br /> <br /> K. Prasanna and D.Saraswat. 2010 Geospatial Technology Website: Where Data Meets Your Need. In Rice Field Day, Stuttgart, AR, August 11.<br /> <br /> Saraswat, D., L. Espinoza, D. Traywick, M. Ismanov, and P. Ballantyne. 2010 Managing Spatial Variability in Crop Production in Arkansas. In Optical Sensing Nitrogen Use Efficiency Conference, Stillwater, OK, August 2-4.<br /> <br /> Saraswat, D., M. Daniels, and D. Traywick. 2010. Agritourism and Geospatial Technologies: An A-mazing Combination. In 7th Natural Resource Extension Professionals Conference, Fairbanks, AK , June 27-30.<br /> <br /> Khosla, R., Westfall, D., Reich, R., Mahal, J.S., and Gangloff, W.J. 2010. Spatial Variation and Site-specific Management Zones. In. Geo-statistical Applications in Precision Agriculture. (ed) M. Oliver. Springer Publishers, Netherlands. Pg 195-219. [Book Chapter]<br /> <br /> Krueger, E., Khosla, R., Kurtener, D., and Ermakov, R. 2010. Application of tool for fuzzy multi attributive comparison of different N management strategies. In. Applications of Soft Computing in Agricultural Researches (ed.) V.P. Yakushev, H. A. Torbert, D.A. Kurtener. Agrophysical Research Institute, St. Petersburg, Russia. [Book Chapter]<br /> <br /> Krueger, E., Kurtener, D., and Khosla, R. 2010. Application of Adaptive Neuro-Fuzzy Inference System for study of relation between Normalized Difference Vegetation Index, yield and soil color-based management zones in irrigated maize. In. Applications of Soft Computing in <br /> Agricultural Researches. (ed.) V.P. Yakushev, H. A. Torbert, D.A. Kurtener. Agrophysical Research Institute, St. Petersburg, Russia. [Book Chapter]<br /> <br /> Shaver, T., Khosla, R., Westfall, D.G. 2010. Evaluation of two ground-based active remote sensors for N variability determination in maize under greenhouse conditions. J. of Soil Sci. Soc. of Amer. 74:2101-2108.<br /> <br /> Schwartz, H., Gent, D.H., Fichtner, S.M., Khosla, R., Mahaffey, L.A., Camper, M.A., and Cranshaw, W.S. 2010. Spatial and Temporal Distribution of Iris yellow spot virus and Thrips in Colorado Onion Fields. J. of Plant Health Progress.<br /> <br /> Bausch, W., and Khosla, R. 2010. QuickBird satellite versus ground-based multispectral data for estimating nitrogen status of irrigated maize. J. of Preci Agri. 10: (6) 1-17.<br /> <br /> Khosla, R. 2010. Precision Agriculture and Resource Management for Livelihood Security in Small Agricultural Systems. In the Proceedings of the Indian Society of Agronomy Meetings in Bangalore, India. Dec 2010.<br /> <br /> Khosla, R. 2010. Precision Agriculture: Challenges and Opportunities in a Flat World. In the Proceedings of the 19th World Congress of Soil Science, Brisbane, Australia, August 2010.<br /> <br /> Moshia, M.E., Khosla, R., Davis, J., and Westfall, D.G. 2010. Precision Manure Management: It matters where you put your manure. In the CD-Rom Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO. <br /> <br /> Stromberger, M.E., Khosla, R., and Shaner, D. 2010. Spatio-Temporal Analysis of Atrazine Degradation And Associate Attributes In Eastern Colorado Soils. In the CD-Rom Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO. July 2010.<br /> <br /> Shaner, D., Khosla, R., and Stromberger, M.E. 2010. Spatial and Temporal Changes in Atrazine Degradation Rates in Soil. In the CD-Rom Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO. July 2010.<br /> <br /> Shaver, T., Khosla, R., Westfall, D.G. 2010. Development Of A Nitrogen Requirement Algorithm Using Ground-based Active Remote Sensors. In Irrigated Maize. In the CD-Rom Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO. July 2010.<br /> <br /> Krueger, E.D., Kurtener, D.A., Yakishev, V.P., and Ermakov, R.N., and Khosla, R. 2010. Evaluation of Different N Management Strategies Using A Tool For Fuzzy Multi Attributive Comparison Of Alternatives. In Irrigated Maize. In the CD-Rom Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO. July 2010.<br /> <br /> Miao, Y., Qiang, C., Cui, Z., Li, F., Dao, T.H., Khosla, R., and Chen, X. 2010. Quantifying Spatial Variability of Indigenous Nitrogen Supply for Precision Nitrogen Management in North China Plain. In the CD-Rom Proceedings of the 10th International Conference on Precision Agriculture, Denver, CO.<br /> <br /> Khosla, R. 2010. Precision Agriculture: Opportunities and Challenges in a Flat World. In the Proceedings of the Great Plains Soil Fertility Conference. Denver, CO.<br /> <br /> Khosla, R., Shaver, T., Westfall, D.G. 2010. Nitrogen and Water Management Across Site Specific Management Zones Using Active remote Sensing. In the CD-ROM Proceedings of the Fluid Fertilizer Foundation Conference, February, Scottsdale, AZ.<br /> <br /> Moshia, M.E., Khosla, R., Westfall, D.G., Davis, J., and Reich, R. 2010. Precision Manure Management Strategies Site Specific Management Zones for Enhancing Corn Grain Yield. In Abstracts of the Annual meetings of the American Society of Agronomy, Long Beach, CA. Nov., 1-5th.<br /> <br /> Shaner, D., Khosla, R., and Stromberger, M. 2010. How rapidly does enhanced atrazine degradation develop? In the Abstracts of the Annual meetings of the Weed Science Society of America, Denver, CO.<br /> <br /> Khosla, R., and Moshia, M.E. 2010. Precision Manure Management: It matters where you put your manure. In the Abstracts of the annual meetings of the Western Society of Soil Science, Las Vegas, NV, June 2010.<br /> <br /> Khosla, R., Shaner, D., Stromberger, M., Bosley, B., and Helm, A. 2010. Spatial Distribution of Enhanced Atrazine Degradation Across North Eastern Colorado: A Survey. In the Abstracts of the Annual meetings of the Western Weed Science Society of America, Big Island, HI, March, 2010.<br /> <br /> Bansal, R., W. S. Lee, R. Shankar, and R. Ehsani. 2010. Automated trash estimation in a citrus canopy shake and catch harvester using machine vision. ASABE Paper No. FL10-123. St. Joseph, Mich.: ASABE.<br /> <br /> Ehsani, R., and S. Sankaran. 2010. Sensors and sensing technologies for disease detection. Citrus Industry, June, 2010, pp. 14-17. 5. Ehsani, R., S. Sankaran, and C. Dima. 2010. Growers expectations of new technologies for applications in precision horticulture (AE467). Agricultural and Biological Engineering Department, Florida Cooperative Extension Service, Institute of Food and Agricultural Sciences, University of Florida.<br /> <br /> Jones, C. D., J. B. Jones, and W. S. Lee. 2010. Diagnosis of bacterial spot of tomato using spectral signatures. Computers and Electronics in Agriculture 74(2): 329-335.<br /> <br /> Kumar, A., W. S. Lee, R. Ehsani, L. G. Albrigo, C. Yang, and R. L. Mangan. 2010. Citrus greening disease detection using airborne multispectral and hyperspectral imaging. 10th International Conference on Precision Agriculture. July 18-21, 2010, Hyatt Regency Tech Center, Denver CO<br /> <br /> Lee, W. S., V. Alchanatis, C. Yang, M. Hirafuji, D. Moshou, and C. Li. 2010. Sensing technologies for precision specialty crop production. Computers and Electronics in Agriculture 74(1): 2-33.<br /> <br /> Mishra, A., R. Ehsani, G. Albrigo and S. Sankaran. 2010. Application of hyperspectral imaging for the detection of citrus greening, Paper No. 1009998, ASABE 2010 Annual International Meeting, Pittsburg, PA, June 20-23, 2010. <br /> <br /> Patil, R., W. S. Lee, R. Ehsani, and F. Roka. 2010. Elimination of debris using de-stemmers on a continuous citrus canopy shake and catch harvester. ASABE Paper No. 1008384. St. Joseph, Mich.: ASABE.<br /> <br /> Sankaran, S., Ehsani, R., and E. Etxeberria. 2010. Mid-infrared spectroscopy for detection of Huanglongbing (greening) in citrus leaves, Talanta, 83, 574-581. <br /> <br /> Sankaran, S., Mishra, A., Ehsani, R., and C. Davis. 2010. A review of advanced techniques for detecting plant diseases, Comput. Electron. Agric., 72 (1), 1-13. 3. <br /> <br /> Sankaran, S., R. Ehsani, and C. Dima. 2010. Development of ground-based sensor system for automated agricultural vehicle to detect diseases in citrus plantations, Paper No. 304, 10th International Conference Precision Agriculture, July 18-21, 2010, Denver, CO. <br /> <br /> Sankaran, S., and R. Ehsani. 2010. Optical methods for Huanglongbing (HLB) detection in citrus orchards, Florida Society Horticultural Society (FSHS) 2010 Annual Meeting, Paper No. C-25, June 6-8, Plantation Inn, Crystal River, FL. <br /> <br /> Sankaran, S., and R. Ehsani. 2010. Detection of Huanglongbing (greening) in citrus plantations using mid-infrared spectroscopy, Paper No. 1009199, American Society of Agricultural and Biological Engineers (ASABE) 2010 Annual International Meeting, Pittsburg, PA, June 20-23, 2010. <br /> <br /> Sankaran, S., R. Ehsani, and C. Dima. 2010. Development of ground-based sensor system for automated agricultural vehicle to detect diseases in citrus plantations, Paper No. 304, 10th International Conference Precision Agriculture, July 18-21, 2010, Denver, CO. <br /> <br /> Sankaran, S., and R. Ehsani. 2010. Detection of Huanglongbing (greening) in citrus plantations using mid-infrared spectroscopy, Paper No. 1009199 (Poster), American Society of Agricultural and Biological Engineers (ASABE) 2010 Annual International Meeting, Pittsburg, PA, June 20-23, 2010. <br /> <br /> Sankaran, S., and R. Ehsani. 2010. Optical methods for Huanglongbing (HLB) detection in citrus orchards, FSHS 2010 Annual Meeting, Paper No. C-25, June 6-8, Plantation Inn, Crystal River, FL. <br /> <br /> Griffin, T.W.; Dobbins, C.L.; Florax, R.J.G.M.; Lowenberg-DeBoer, J.M.; Vyn, T.J. 2010. Spatial Analysis of Precision Agriculture Data: Role for Extension. J. National Assoc. Agric. Agents. Available at: http://www.nacaa.com/journal/index.php?jid=40<br /> <br /> Lowenberg-DeBoer, J. and B. Erickson, 2010. Precision Agriculture in Africa. Georgetown Journal of International Affairs, 11(2) (2010), p. 107-116.<br /> <br /> Murrell, T.S., and T. J. Vyn. 2010. Precision management of root zone potassium for corn: Considerations for the future. Better Crops Vol. 94 (No. 4), p. 24-25. http://www.ipni.net/ppiweb/bcrops.nsf/$webindex/7C1B2FB0205F44F3852577EB00574F8F/$file/BC+4+2010+pg+24.pdf<br /> <br /> Erickson, Bruce J. Economics and Adoption of Precision Farming Technologies, Purdue Women in Agriculture Conference, February 2011, Jeffersonville, Indiana.<br /> <br /> <br /> Erickson, Bruce J., Terry Griffin, and David Waits. Technology & Equipment: The Logistics of Maximizing Yield, panel discussion at GROWMARK Grower Conference, January 2011, Peoria, Illinois.<br /> <br /> Erickson, Bruce J. Investments in Precision Agriculture and Other Farm Management Topics, Ohio State Agronomic Crops In-Service Training, January 2011, Columbus, Ohio.<br /> <br /> Erickson, Bruce J. Adoption of Precision Agriculture, Contemporary Trends, Central Ohio Agronomy Day December 2010, Newark ,Ohio.<br /> <br /> Erickson, Bruce J. Agronomic Input Trends, Informa Economics Fall Outlook Conference, November 2010, Memphis, Tennessee. <br /> <br /> Erickson, Bruce J. Economics and Adoption of Precision Farming Technology, Brazilian farmers group visit to Purdue University, August 2010.<br /> <br /> Erickson, Bruce J. Economics and Adoption of Precision Farming Technology, Argentina CREA Maria Teresa visit to Purdue University, August 2010.<br /> <br /> Erickson, Bruce J. Practical Applications of Precision Agriculture for Todays Grower, Heartland Technology Solutions Media Field Day, June 2010, Harlan, IA<br /> <br /> Erickson, Bruce J. Using Production Technology to Increase Food Security While Mitigating Climate Change, 2010 Rotary World Affairs Conference, March 2010. <br /> <br /> Erickson, Bruce J. Precision Agriculture Collaboration: Agronomic, Engineering and Economics, NCERA-180 Site-Specific Management Industry/Academic Annual Meeting, Lexington, KY, January 2010.<br /> <br /> Franzen, D., D. Long, A. Sims, J. Lamb, F. Casey et al., 2010. Evaluation of methods to determine residual soil nitrate zones across the northern Great Plains of the USA. Published on-line, November 2010 in Journal of Precision Agriculture<br /> <br /> Franzen, D.W. 2011. Collecting and analyzing soil spatial information using kriging and inverse distance. p. 61-80 In GIS Applications in Agriculture. Vol. 2 Nutrient Management for Energy Efficiency. D.E. Clay and J.F. Shanahan, eds. CRC Press, Boca Raton, FL<br /> <br /> Franzen, D.W., R. Ashley, G. Endres, J. Lukach, J. Staricka, and K. McKay. Revising nitrogen recommendations for wheat in response to the need for support of variable-rate nitrogen application. International Precision Ag Conference, Denver, CO, July, 2010.

Impact Statements

1. Many NCERA-180 members are active participants in the development of an eXtension website on precision agriculture
2. NCERA-180 members have founded the organizational basis of precision agriculture associations in the US. There is growth in participations of national and international meetings
3. Members of NCERA-180 are active in seeking federal funding for multistate projects. University of Florida and the University of California Davis have spearheaded two of USDA Specialty Crop Research Initiative (SCRI) research and planning proposals with NCERA-180 members participation
4. Dr. Sreekala Bajwa, University of Arkansas, reports progress in charcoal rot disease detection with remote sensing. This approach will be a powerful tool to map and identify diseases in large scale. This will allow the farmers and crop consultants to understand the yield impact (damage) caused by this disease, and to establish remedial measures in a site-specific fashion
5. Dr. Rajiv Khosla (Colorado State University) found high rates of herbicide (atrazine) dissipation in soil from semi-arid dryland cropping environments (1.8 to 3.2 days, as compared to previously reported half-lives for atrazine ranging from 45  180 days previously reported in literature). Such finding is of agronomic significance, current work is aimed at confirming these results
6. Researchers in Florida report significant progress in HLB disease detection from the 2010 season. Some methods include mid-infra-red spectroscopy, and image processing from aerial hyperspectral measurements
7. In Florida there are reports of progress in harvesting technology with the use of long de-stemmers for continuous canopy shake and catch to improve debris removal. Moreover, results in 2010 in machine vision algorithms for estimation of debris mass showed promising results
8. In North Dakota, Dr. David Franzeen has documented an increasing numbers of growers are using precision techniques for nutrient management as a result on extension efforts on how precision ag techniques can increase fertilizer use efficiency

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