Oklahoma State University Precision Agriculture / Soil Fertility / Soil Nutrient Management Why should Nitrogen Use Efficiencies be improved? What technologies have been developed to increase Nitrogen Use Efficiency? Some of the advanced technologies developed by OSU for improved fertilizer management are 1. By-Plant N Fertilization 2. GreenSeeker ® and 4 Band Sensor 3. N-Rich Strip and N-Ramp Calibration Strip International Extension Activities Who has employed recent graduate students from Soil Fertility? Over the past 15 years, Soil Fertility graduate students have been involved in international programs and workshops to extend technologies developed at OSU. To date, graduate students have traveled to Argentina, Australia, Canada, China, India, Mexico, Turkey, Uzbekistan, and Zimbabwe. World wide nitrogen use efficiency (NUE) for cereal grains is only 33%. Oklahoma State University’s Precision Agriculture Team employs a wide array of techniques and equipment in an effort to improve NUE. Some of these techniques include the use of the GreenSeeker ® and 4 band sensors, both developed at OSU. When either of these are used in conjunction with a N-Rich Strip or a N-Ramp Calibration Strip, it allows producers to make accurate midseason fertilizer applications based on crop needs. The benefits of implementing these methods results in more accurate N rates, providing producers the same yield with less fertilizer; thereby, reducing over application of fertilizer. Less N is lost to runoff, leaching, volatilization, etc., resulting in a net savings for producers. It’s been calculated that a 20% increase in NUE world wide would result in a savings of US$10,000,000,000 for producers. In addition, these techniques benefit the environment. By reducing runoff from agricultural lands, we can reduce the estimated US$1,000,000,000 worth of fertilizer flowing down the Mississippi River each year. The Precision Agriculture Team at OSU continues to refine and develop new technologies for improving NUE. Technologies to Increase Nitrogen Use Efficiency Mexico 2002 Canada 2004 China 2004 India 2005 Uzbekistan 2008 Zimbabwe 2008 Sensor Based N-Rate Calculator N-Rich Strip The amount of N the environment delivers changes from year to year. So, why do you apply the same N fertilizer rate every year? N-Rich Strips indicate how much N the environment delivers. Using the web-based, Sensor Based Nitrogen Rate Calculator, proper recommendations of additional mid-season N fertilizer to be applied to achieve maximum yields can be obtained. How is this technology established? Using the GreenSeeker ® hand-held sensor, actual wheat or corn grain yield potential can be estimated using the NDVI readings (value output from the sensors) from the Nitrogen Rich Strip compared to the Farmer Practice and the number of days where growing degree days are greater than zero (GDD>0) or days from planting to sensing. Essentially, the NDVI value from the hand- held sensor outputs “total biomass.” For readings collected between January and March (regardless of when the wheat was planted), we can estimate “biomass produced per day.” This value is used to predict the wheat grain yield obtainable. With these numbers, the yield and the need for additional N can be predicted accurately. This approach is established for other crops too. What can I expect from using this technology? This method determines the ideal top-dress N rate. From research conducted by OSU, this method is worth over US$10.00 per acre. When fertilizers are applied in excess of that needed for maximum yields, the potential for surface and subsurface nitrate contamination of water supplies increases. The amount of N that the environment delivers is considered with this approach; therefore, the recommendation obtained accurately estimates the additional N required, if any, by the crop for the current growing season to produce maximum yields. This approach can be used in other crops as well, i.e. sorghum, cotton, bermudagrass, etc. GreenSeeker ® Sensor 4 - Band Sensor The GreenSeeker ® sensor is an active, optical sensor that measures crop status. From these measurements, a fertilizer recommendation can be made based on the crop's N requirements. The sensor works by using light emitting diodes (LED) to generate red and near infrared (NIR) light. The light generated is reflected off the crop and measured by a photodiode located at the front of the sensor head. Yield potential for a crop is identified using a vegetative index known as NDVI (Normalized Difference Vegetative Index) and an environmental factor. GreenSeeker ® calculates NDVI using both red and NIR light. Red light is absorbed by plant chlorophyll as an energy source during photosynthesis. Therefore, healthy plants absorb more red light and reflect larger amounts of NIR than unhealthy plants. NDVI is an excellent indicator of biomass (amount of living plant tissue), and is used in conjunction with growing degree days greater than zero (GDD>0) or days from planting to accurately project yield potential. Nitrogen is then recommended based on yield potential and the responsiveness of the crop to additional nitrogen. Using the GreenSeeker ® has yielded significant savings. The 4-band sensor utilizes four wavelength bands (670nm, 780nm, 870nm, and 970nm) to determine crop status. Another useful feature of the 4-band sensor is its ability to determine plant tissue temperature. The 4-band sensor is currently being utilized as an aid to plant breeders in addition to its utilization for nutrient management. 1. By-Plant N Fertilization 3. N-Rich Strip and N-Ramp Calibration Strip N-Ramp Calibration Strip The N-Ramp Calibration Strip (RCS) allows the producer to visually determine the appropriate mid-season N fertilizer rate. Although use of the hand-held GreenSeeker ® sensor is not required for evaluation, using the sensor offers the opportunity to sense the entire "RAMP" and thus accurately determine where the peak in NDVI exists over the range of N rates applied. Without the sensor, farmers can simply walk from one end of the RAMP to the other and stop where they no longer see any differences in vegetative growth to determine the appropriate mid-season N application rate. Whether determined visually, or with a hand-held sensor, the point where differences no longer exist is the TOPDRESS N Rate for mid-season application. What was found? In some years, zero N check plots can produce near maximum yields. Where check plots (0-N) produced near maximum yields, a RCS would have visibly illustrated limited differences between the zero N segment and plots in the RCS receiving N. As a result, in-season observation would have recognized limited or no demand for additional N fertilizer. 2. GreenSeeker ® and 4-Band Sensor Since 1992, 64 students have completed or are currently pursing a Master of Science (M.S.) or Doctorate of Philosophy (Ph.D.) degree through the Soil Fertility program at OSU. A few of the companies recent graduates are employed with and the graduates employed there is listed below. Current Students: Olga Walsh, Daniel Edmonds, Cody Daft, Birehane Desta,Yumiko Kanke, Emily Ruto, Jake Vossenkemper, Jerry May, Guilherme Torres Former StudentEmployed ByFormer StudentEmployed By Dr. Brian ArnallOkla. StateJason LawlesWest. Equip. Dr. Brenda TubañaLSUClint DotsonPioneer Dr. Byungkyun ChungMcNeese StateStarr HoltzMonsanto Dr. Kefyalew GirmaOkla. StateClint MackMonsanto Dr. Kyle FreemanMonsantoKyle LawlesMonsanto Dr. Robert MullenOhio StateBrandon EnglandFSA Dr. Paul HodgenMonsantoShambel MogesAccurate Labs Dr. Jagadeesh MosaliNoble FoundationPam TurnerDEQ Dr. Kent MartinKansas StateKeri BrixeyNRCS Dr. Wade ThomasonVirginia TechCody DaftMonsanto Dr. Steve PhillipsIPNIDoug CosseyServiTech Dr. Fred KanampiuCIMMYTJeremy DennisNRCS Dr. Edgar AscencioCAREJeff BallEstes Chem. Dr. F. Gavi-ReyesUniv. ChapingoCurt WoolfolkSST O K L A H O M A S T A T E U N I V E R S I T Y With an increase in precision farming practices and improved remote sensing technology, the ability to evaluate physiological differences at the by-plant level, and on-the-go is now a reality. This is increasingly important following the findings from on-farm, by-plant yield data collected in Argentina, Mexico, Iowa, Nebraska, Ohio, Virginia, and Oklahoma. Over all sites in all countries and states, plant-to-plant variation in corn grain yield averaged 44.1 bu/ac. In other words you can expect one corn plant to differ from the other “on-average” by more than 44 bu/ac, yet farmers apply the same rate to each plant. Furthermore, the yield range (maximum corn grain yield minus the minimum corn grain yield per row) was found to increase with increasing yield level. Regardless of yield level, plant-to-plant variability in corn grain yield can be expected. Averaging yield over distances 1.5 ft removed the extreme by-plant variability, thus, the scale for treating other factors affecting yield should be less than 1.5ft. Oklahoma State University has developed an applicator that can effectively sense and treat every 1.5 feet in corn fields on-the-go at 5 mph. The future of precision agriculture will ultimately end up at the by-plant level since this is where the major yield differences exist.