Progress 04/01/04 to 09/30/09
Outputs
OUTPUTS: Considering the multiple approaches being evaluated for generating nitrogen recommendations, I will cover outputs of each individual area independently using headings. Sensor-Based Algorithm An output of this research effort is the development of a functional algorithm that is currently being used on-farm in the Midwest. Multiple presentations have been given both nationally and regionally on this research effort (Mullen et al., 2006a; Mullen, 2009). Two proceedings articles have also resulted from this research (Mullen et al., 2006b; Mullen et al., 2008). Funding has also been secured from private foundations (Fluid Fertilizer Foundation) and state funds (CIG) to further this research effort. Presidedress Soil Nitrate Test Several outputs have resulted from this particular suite of studies. Several extension presentations have been made based upon this new information at both the state and regional level. Additionally, an editor-reviewed article has been published in Crops and Soils discussing the results of this work (Mullen, 2009). A proceedings article has also been published on the subject. Finally, a M.S. student completed her thesis within this research project (Bast, 2009). New Economic-Based Nitrogen Recommendation As a result of the data generated from the 130 research trials conducted, a Microsoft Excel spreadsheet has been developed that delineates Ohio State University's new economic-based recommendations. This is the primary tool accessible to state clientele to make N rate decisions. Additionally, the new economic-based recommendations have been presented at multiple Extension meetings (>60) held throughout the state of Ohio. Evaluation impacts measured at the Conservation Tillage and Technology Conference held every February in Ada has revealed that attendees are using the new recommendation model and consequently the average respondent has stated that the N rates being used today are slightly lower (~20 pounds per acre) than they were historically. PARTICIPANTS: Individuals Laura Bast - Masters student Ohio State Clayton Dygert - Research associate Ohio State David Henry - Masters student Ohio State Keith Diedrick - Ph.D. student Ohio State Newell Kitchen - Research scientist USDA-ARS Columbia, MO William Raun - Regents professor Oklahoma State University Partner organizations Oklahoma State University University of Missouri University of Nebraska Virginia Tech University University of Minnesota STAR Lab Ohio State University Purdue University Michigan State University TARGET AUDIENCES: Sensor-Based Algorithm Much of the information from this research effort was shared with fellow research scientists and industry individuals researching this area as well. Communication occurred at national meetings and a regional meeting assembled specifically for researchers in this area. Although, some of the information has been shared at university sponsored extension meetings, it has been more common for this information to be shared at more advanced workshops. Presidedress Soil Nitrate Test and New Economic-Based Nitrogen Recommendation The primary audience for this information has been state crop producers, state agency personnel, and other research scientists. Multiple presentations have provided across the state of Ohio and neighboring states regarding the information collected from these two research efforts. The obvious goal has been to change producer mindset and ultimately their decision making as it relates to managing nitrogen inputs for corn production. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.
Impacts
Considering the multiple approaches being evaluated for generating nitrogen recommendations, I will cover outputs of each individual area independently using headings. Sensor-Based Algorithm The outcome of this research effort was the development of a new algorithm for generating nitrogen recommendations using remotely sensed information. The algorithm was developed over several site years of research data and has performed relatively well. As a result of research effort, several industry individuals are utilizing our algorithm to generate nitrogen recommendations for corn. Presidedress Soil Nitrate Test Our re-evaluation of PSNT for generating N recommendations for corn has resulted in a new, definitive critical level that has been disseminated to state agencies and directly to state clientele. Our research has determined that PSNT levels above 30 ppm nitrate-N are unlikely to be responsive to additional N, thus N should be applied at significantly lower rates or avoided completely if this condition exists. This information has and will continue to be used by state agencies when developing nutrient management plans for crop producers that utilize animal manures as a nutrient resource. New Economic-Based Nitrogen Recommendation As a result of our research effort in this area, Ohio State University now has a new economic-based recommendation model for corn. This new model is available online for download, and it has been downloaded over 1600 times in the past two years. This new approach in generating N recommendations for corn represents a dramatic shift from the traditional approach. As evidenced by the number of downloads to this point, it is being accepted by our state clientele.
Publications
- Mullen, R.W. 2009. PSNT, ISNT, SPAD, etc. What does it all mean. Crops and Soils. Vol. 42:4,8-9.
- Mullen, R.W. 2009. Variable rate nitrogen-on the go. InfoAg Meeting. Springfield, IL, July 14-16, 2009.
- Mullen, R.W., G. Schwab, W. Thomason, W.R. Raun, J. Schepers, N. Kitchen, J. Shanahan, D. Francis, S. Phillips, K. Freeman, P. Hodgen, B. Arnall, R. Teal, C. Dygert, G. Randall, and J. Vetsch. 2006b. Evaluation of optical sensor based nitrogen algorithms for corn using sidedress liquid applications. Fluid Fertilizer Forum Proceedings. Scottsdale, AZ, February 2006.
- Bast, L.E. 2009. Evaluation of nitrogen recommendations for corn based on soil analysis and remotely sensed data. M.S. Thesis, Ohio State University, Columbus, OH.
- Mullen, R.W., W.R. Raun, J.S. Schepers, N. Kitchen, G. Randall, G. Schwab, W.E. Thomason, S.B. Phillips, J. Shanahan, D. Francis, and J. Vetsch. 2006a. Can optical sensing identify the right N rate for corn In Agronomy Abstracts. ASA, Madison, WI.
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Progress 01/01/08 to 12/31/08
Outputs
OUTPUTS: Ohio State University continues to promote and develop the economic based nitrogen rate calculator. This tool has been made available online for producers, and it is updated annually. Additionally, this coming year Ohio State University will join Iowa State, University of Illinois, Purdue University, University of Wisconsin, and University of Minnesota as a suite of universities that provide their recommendations on the same webpage. Our total number of sites included in our model is currently 125. Extension/outreach efforts continued throughout the past year, and we provided training regarding these new recommendations at 9 venues and reached over 965 total state/regional clientele. This past year we collaborated with Environmental Defense Fund to conduct on-farm research in the Lake Erie Basin with funding from the State Conservation Innovation Grant. This project contributed another 25 sites to our nitrogen recommendation model. Producers that cooperated with us on this trial (and some that had not) were brought into a meeting this winter where the results were disseminated in an outreach fashion. We continue to work on the remote sensing approach to making nitrogen applications. Research results from this project were disseminated at an international conference held in Manhattan, KS by a graduate student included in the project. We also provided training on the use of remote sensing at another international conference held in Denver, CO. As the result of these efforts we have developed an algorithm (equation for making nitrogen applications based upon sensor readings) that is being used in the Corn Belt. We will be conducting on-farm evaluation this coming year of our algorithm here in the state of Ohio with the Environmental Defense Fund. This project will involve five cooperators from the Lake Erie Basin. PARTICIPANTS: Clayton Dygert - my field technician that is primarily responsible for collecting sensor measurements and establishing/maintaining field experiments Keith Diedrick - Ph.D. student who has been working on a specific component of our algorithm Laura Bast - graduate student that is evaluating the use of remote sensing in manure management situations Partner Organizations/Collaborators USDA-ARS, Oklahoma State University, University of Illinois, Purdue University, Virginia Tech University, University of Minnesota, CIMMYT (International Wheat and Maize Improvement Center), Kansas State University, Colorado State University, Michigan State University, Iowa State University, Agriculture and Agri-Food Canada, University of Nebraska, University of Missouri TARGET AUDIENCES: The primary audience for our remote sensing approach up to this point has been scientists, industry personnel, certified crop advisors, and more progressive producers. Our non-remote sensing approach has been primarily targeted to producers, industry personnel, certified crop advisors, Extension personnel, and state agency personnel. PROJECT MODIFICATIONS: Not relevant to this project.
Impacts
As it relates to our new economic-based nitrogen recommendations, adoption of our recommendations has increased based upon a poll conducted at a single major educational event that convenes every February (that typically has over 500 attendees). We have been asking producers what their plans were for nitrogen applications in 2006, 2007, and 2008 as a gauge of our educational efforts. In 2006, when these new recommendations were implemented, 65% of the attendees reported that they were going to decrease nitrogen application rates by an average of 24 pounds per acre. In 2007, 29% responded that they were going to decrease nitrogen application rates by an average of 19 pounds per acre. In 2008, 41% responded that they were going to reduce nitrogen application rates by an average of 22 pounds. This is an indication that the message regarding nitrogen use efficiency is being heard by our clientele. Our work with optical sensors has resulted in the development of an algorithm (equation for making nitrogen applications based upon sensor readings) that is being used in the western Corn Belt. This new algorithm incorporates new parameters to improve our ability to predict sidedress nitrogen rates for corn.
Publications
- Mullen, R.W., N.R. Kitchen, S.B. Phillips, W.R. Raun, J.S. Schepers, and W.E. Thomason. 2008. Developing nitrogen algorithms for corn production using optical sensors. International Conference on Precision Agriculture. Denver, CO, July 20-July 23, 2008.
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Progress 01/01/07 to 12/31/07
Outputs
OUTPUTS: In terms of the precision agriculture/remote sensing approach to improving nitrogen use efficiency of corn production in Ohio, this past year we had three experimental sites evaluating and developing sensor-based algorithms. The information collected was disseminated at a couple Extension/outreach events and at an international scientific conference. I was also asked to discuss the results of our research efforts on remote sensing at an international precision ag conference held in Illinois. Ohio State University also acted as the university host for an international meeting on sensor-based nitrogen management this past summer. As far as our non-remote sensing approach, we had a number of small-plot and on-farm experimental sites that have been incorporated into our new nitrogen recommendation strategy. The database for our new economic nitrogen recommendations has grown to 94 sites and that decision tool has been made available through our soil fertility webpage
(http://agcrops.osu.edu/fertility/). This new strategy has been disseminated at several local, state, and regional meetings/conferences/workshops. These meetings/conferences/workshops were targeted primarily to state clientele that can benefit directly from the new approach, but county level personnel and state agency personnel were targeted for education to act as multipliers to speed dissemination.
PARTICIPANTS: Individuals Clayton Dygert - my field technician that is primarily responsible for collecting sensor measurements and establishing/maintaining field experiments Laura Bast - graduate student that is evaluating the use of remote sensing in manure management situations Partner Organizations/Collaborators USDA-ARS, Oklahoma State University, University of Illinois, Purdue University, Virginia Tech University, University of Minnesota, CIMMYT (International Wheat and Maize Improvement Center), Kansas State University, Colorado State University, Michigan State University, Iowa State University, Agriculture and Agri-Food Canada, University of Nebraska, University of Missouri
TARGET AUDIENCES: The primary audience for our remote sensing approach up to this point has been scientists, industry personnel, certified crop advisors, and more progressive producers. Our non-remote sensing approach has been primarily targeted to producers, industry personnel, certified crop advisors, Extension personnel, and state agency personnel.
Impacts
From our precision ag field research, we did identify and disseminate a new sensor-based algorithm that will be employed this coming year at on-farm locations. This new algorithm is built upon a previous algorithm, but through our investigations and subsequent analysis, we have identified a new methodology for computing a specific parameter. The parameter altered was how in-season responsiveness was calculated using canopy remote sensing. This new approach results in a much better correlation with response measured at harvest than our previous, published equation.
Publications
- No publications reported this period
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Progress 01/01/06 to 12/31/06
Outputs
This year several field experiments were located across the state of Ohio at both OSU research facilities and on farmer's fields. The total number of sites added to the OSU nitrogen recommendation model was 20. The new economic nitrogen recommendations have been presented at 30 Extension meetings/CCA workshops reaching over 2300 individuals within the state of Ohio. Additional work focusing on the use of optical sensing to direct nitrogen application has proceeded with mixed results. In 2006, five small-plot research trials were conducted at OSU research stations, but the data reveals that more work is needed to refine the algorithms being evaluated.
Impacts
New nitrogen recommendations should positively impact agricultural production both economically and environmentally. Economic recommendations should result in slightly lower nitrogen application rates that should improve the bottom line for many producers facing higher nitrogen prices. As nitrogen application rates decrease, so too should the potential for environmental contamination of ground and surface waters with excess nitrogen.
Publications
- Sawyer, J, E. Nafziger, G. Randall, L. Bundy, G. Rehm, B. Joern, C. Laboski, R. Hoeft, R. Mullen, R. Killorn, and S. Brodeur. 2006. Concepts and rationale for regional N rate guidelines for corn. Published online at http://www.extension.iastate.edu/Publications/PM2015.pdf
- Viswakumar, V., A. Sundermeier, R.W. Mullen, and C.E. Dygert. 2006. Tillage and nitrogen application methodology affects corn grain yield. North Central Extension-Industry Soil Fertility Conference Proceedings Vol. 22.
- Mullen, R.W., G. Schwab, W. Thomason, W.R. Raun, J. Schepers, N. Kitchen, J. Shanahan, D. Francis, S. Phillips, K. Freeman, P. Hodgen, B. Arnall, R. Teal, C. Dygert, G. Randall, and J. Vetsch. 2006. Evaluation of optical sensor based nitrogen algorithms for corn using sidedress liquid applications. Fluid Fertilizer Forum Proceedings. Scottsdale, AZ, February 2006.
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Progress 01/01/05 to 12/31/05
Outputs
This past year two trials were established to evaluate different optical sensor-based nitrogen algorithms. The experiments followed a regional protocol and evaluated four different algorithms. Field conditions for corn production were less than optimal, but the algorithms performed reasonably well. Considerable variation associated with the experiments makes meaningful statistical analysis difficult. In general, yields were not suppressed greatly at lower rates of nitrogen application. Two additional trials were conducted to evaluate nitrogen application timing on corn production. Again less than optimal field conditions make meaningful statistical analysis difficult due to large variability within the experiment. Unlike data collected in 2004, in-season estimation of crop response to applied N (using optical sensing) was not highly correlated with crop response measured at harvest. This is most likely due to low moisture conditions and high temperature during corn
flowering and grain fill. Considering the poor production environment noted for 2005, nitrogen recommendation schemes that allow for in-season assessment of apparent nitrogen mineralization still have merit and should be investigated further. Four additional trials are planned for next year. Even though experimental results were not as good as hoped, several states including Ohio have moved to a new nitrogen recommendation strategy. The new strategy is based on economics, and should have a positive impact on corn production within the state. This is especially true with current nitrogen prices. The new strategy utilizes corn price (dollars per bushel) and nitrogen cost (dollars per pound) to determine economic nitrogen recommendations based upon an average response curve (empirical model based on actual experimental observations). Yield goal or yield potential will no longer be included to determine nitrogen recommendations. A regional manuscript has been prepared to provide evidence
for the recommendation strategy. The manuscript has already been reviewed and will be published in early 2006.
Impacts
New nitrogen recommendations should positively impact agricultural production both economically and environmentally. Economic recommendations should result in slightly lower nitrogen application rates that should improve the bottom line for many producers facing higher nitrogen prices. As nitrogen application rates decrease, so too should the potential for environmental contamination of ground and surface waters with excess nitrogen.
Publications
- No publications reported this period
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Progress 01/01/04 to 12/31/04
Outputs
Initial data from one location (two experiments were established) revealed that in-season estimates of corn response to nitrogen (N) (measured with remote sensing techniques) is correlated with actual crop response measured at harvest. This information may provide a quantifiable estimate of crop response to N and allow for in-season adjustments of N application. Significant response to applied N was apparent at both locations. The use of the presidedress soil nitrate test (PSNT) was also evaluated at each site of the two sites. Maximum yields could be achieved without additional N if the PSNT value was 31 ppm or greater. Thus the current critical value of 30 ppm is of use and can provide producers an alternative method for determining if additional N is warranted or not. At a separate N evaluation experiment, the impact of previous crop history was apparent. Corn following soybean this past year (at a single location) showed no response to applied N indicating that N
contribution from the soil and previous soybean crop was enough to satisfy crop need. This is another indication that methods of determining temporal crop response can lead to significant economic return for producers as well as decreased environmental contamination of N fertilizers. Additional trials will be established this coming year to evaluate sensor-based algorithms as well as soil-based measures for making N recommendations for corn.
Impacts
Development and dissemination of new methods for determining N recommendations may have economic, environmental, and social impacts. Identifying better N rates both spatially and temporally may have significant impacts on the economic return associated with N fertilizers, specifically with current high N prices. Improved N application rates should also minimize the amount of N susceptible to loss and that can have a negative impact on the environment. Decreased N contamination of surface and ground-water sources may result in greater social acceptance of agricultural activities.
Publications
- No publications reported this period
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