On-farm Evaluation of Optical Sensor Technology for Variable Rate N Application to Corn in Ontario and Quebec Bao-Luo Ma, and Nicolas Tremblay Eastern.

Slides:



Advertisements
Similar presentations
Do In and Post-Season Plant-Based Measurements Predict Corn Performance and/ or Residual Soil Nitrate? Patrick J. Forrestal, R. Kratochvil, J.J Meisinger.
Advertisements

Missouri algorithm for N in corn
Determine seeding rate and hybrid effects on: Phenotypical and physiological plant measurements Canopy and leaf sensor measurements A goal in precision.
FIELD-SCALE N APPLICATION USING CROP REFLECTANCE SENSORS Ken Sudduth and Newell Kitchen USDA-ARS Translating Missouri USDA-ARS Research and Technology.
EVALUATION OF GREENSEEKER FOR NITROGEN FETILIZATION IN COTTON ALABAMA REPORT 1 Evaluation of Green Seeker for Nitrogen Fertilization in Cotton – Preliminary.
Sensor Orientation to maize canopy row and estimating biomass and Nitrogen Status Paul Hodgen, Fernando Solari, Jim Schepers, John Shanahan, Dennis Francis.
Using aerial photography & fertigation to fine-tune N management
May 6, Drought tolerant Miller ComparisonsEfawLCB Grain Yield (bu/ac) Drought tolerant vs. Non-drought tolerant Monsanto vs. Pioneer
Sensor research and algorithm development for corn in ND L.K. Sharma, D.W. Franzen, H. Bu, R. Ashley, G. Endres and J. Teboh North Dakota State University,
Comparison of Active Optical Sensors
Precision Agriculture in Europe Olga S. Walsh BIOEN/SOIL 4213 Spring 2007.
GreenSeekerTM Variable Rate Applicator Equipment and Applications
Comparison of Commercial Crop Canopy Sensors Ken Sudduth Newell Kitchen Scott Drummond USDA-ARS, Columbia, Missouri.
Integrating Weather and Soil Information With Sensor Data Newell Kitchen USDA ARS Cropping Systems and Water Quality Research Unit Columbia, Missouri.
NUE Workshop: Improving NUE using Crop Sensing, Waseca, MN
Residue Biomass Removal and Potential Impact on Production and Environmental Quality Mahdi Al-Kaisi, Associate Professor Jose Guzman, Research Assistant.
Nitrogen Use Efficiency Workshop Canopy Reflectance Signatures: Developing a Crop Need-Based Indicator for Sidedress Application of N Fertilizer to Canola.
Corn Plot Overview Jared Shippey Ben Logan. General Information  Planted 5/30/08  Hybrid – Pioneer 38B87 – 94 days  Planted population 35,000  Manure.
GreenSeeker® Handheld Crop Sensor
Determining the Most Effective Growth Stage in Corn Production for Spectral Prediction of Grain Yield and Nitrogen Response Department of Plant and Soil.
Presented by: Keri D.Brixey
Use of Alternative Concepts for Determining Preplant and Mid-Season N rates.
Are NDVI Readings Sensors Dependent? Tremblay, N., Z. Wang, B. Ma, C. Bélec and P. Vigneault St-Jean-sur-Richelieu, Quebec.
Remote sensing of canopy reflectance on a field scale has been proposed as a useful tool for diagnosing nitrogen (N) deficiency of corn plants. Differences.
Optimizing Nitrogen and Irrigation Timing for Corn Fertigation Applications Using Remote Sensing Ray Asebedo, David Mengel, and Randall Nelson Kansas State.
Active-Crop Sensor Calibration Using the Virtual-Reference Concept K. H. Holland (Holland Scientific) J. S. Schepers (USDA-ARS, retired) 8 th ECPA Conference.
GreenSeeker ® Applicator Mounted Crop Vigor Sensors.
Variable-Rate N Fertilization of Wheat and Corn in the Mid-Atlantic Variable-Rate N Fertilization of Wheat and Corn in the Mid-Atlantic Wade Thomason,
Automated Calibration Stamp Technology for Improved In-Season Nitrogen Fertilization K. Freeman, R. Teal, C. Mack, K. Martin, B. Arnall, K. Desta, J. Solie,
Figure 3. Concentration of NO3 N in soil water at 1.5 m depth. Evaluation of Best Management Practices on N Dynamics for a North China Plain C. Hu 1, J.A.
Refinement of the Missouri Corn Nitrogen Algorithm Using Canopy Reflectance Newell Kitchen, Ken Sudduth, and Scott Drummond USDA-Agricultural Research.
Precision Agriculture an Overview. Precision Agriculture? Human need Environment –Hypoxia –$750,000,000 (excess N flowing down the Mississippi river/yr)
N Fertilization in Colorado Raj Khosla Colorado State University May 19 th & 20 th Oklahoma State University Raj Khosla Colorado State University May 19.
Demonstration of In-Season Nitrogen Management Strategies for Corn Production John Sawyer John Lundvall Jennifer Hawkins Department of Agronomy Iowa State.
Sensor Based Technologies in Mexico CIMMYT (Dr. Ivan Ortiz-Monasterio ) Oklahoma State University (Yumiko Kanke)
Three Alternative Nitrogen Management Strategies for Cereal Grain Production Brian Arnall Brian Arnall Plant and Soil Sciences Department Oklahoma State.
Locations Efaw Lake Carl Blackwell Haskell Years2005, 2006 Objectives: 1)To determine the minimum preplant N fertilizer needed to achieve maximum yield.
Generalized Algorithm for Variable Rate Nitrogen Application on Cereal Grains John B. Solie, Regents Professor Biosystems and Agri. Engineering Dept. William.
NFOA for Wheat and Corn. Yield Potential Definitions INSEYIn Season Estimated Yield = NDVI (Feekes 4 to 6)/days from planting to sensing (days.
Theory of Predicting Crop Response to Non-Limiting Nitrogen.
Where do Enhanced Efficiency Nitrogen Fertilizers and Split N Applications Fit? Cynthia Grant and Alan Moulin AAFC - Brandon Research Centre Nicolas Tremblay.
Drew Tucker and Dave Mengel KSU Agronomy An update on Kansas sensor based N recommendations.
DEPARTMENT OF ENVIRONMENTAL SCIENCE & TECHNOLOGY Laboratory for Agriculture and Environmental Studies Sensor Based Variable Rate N Management in Mid-Atlantic.
Regional Project Objectives  To evaluate the performance of sensor-based N recommendation algorithms across a wide range of soil and climate conditions.
Exploratory Research in Corn
Variable Rate Nitrogen Application in Corn Production
Developing Sidedress N Recommendations for Corn in Central PA
NDVI Active Sensors in Sugarbeet Production for In-Season and Whole Rotation Nitrogen Management.
Recent Work on Oat and Canola N Management Projects in ON, Canada
Evolution of OSU Optical Sensor Based Variable Rate Applicator
Development of a Response Index for Corn
Crop-based Approach for In-season N Application
Evaluation of Pre-Side Dress Nitrate Test for Corn in Minnesota
Sensing Resolution in Corn
EVOLUTION OF NITROGEN REFERENCE STRIPS
Strategies for Split N Applications for Corn
G. V. Johnson and W. R. Raun Dept. Plant & Soil Sciences
Evaluation of Midseason UAN Application Depth in Winter Wheat
E.V. Lukina, K.W. Freeman,K.J. Wynn, W.E. Thomason, G.V. Johnson,
Sensors and Fertility Management
REVIEW.
Landscape Position Zones and Reference Strips
Annual ASA Meeting, Indianapolis
UNL Algorithm for N in Corn
Objective: To discuss the current regional project and identify improvements needed for conducting future collaborative sensor-based research.
Late-Season Prediction of Wheat Grain Yield and Protein
Gyles Randall and Jeff Vetsch University of Minnesota
Eric Miller August 3rd, 2010 Dr. Camberato & Dr. Nielsen
Tastes Great. Less Filling
Variability in Corn Response to N Fertilizer along a 1000-ft Hillslope
Presentation transcript:

On-farm Evaluation of Optical Sensor Technology for Variable Rate N Application to Corn in Ontario and Quebec Bao-Luo Ma, and Nicolas Tremblay Eastern Cereal and Oilseed Research Centre, Ottawa, ON 613-759-1521, mab@agr.gc.ca Canada

Introduction - Nitrogen Fertilizer N represents the most costly input in grain cereal production, especially corn Producers have to balance crop N needs while minimizing N losses via leaching, emission and runoff NUE is low, about 50% Soil physical, chemical and biological conditions tremendously affect NUE N losses as NO3 to surface and ground water, as N2O and NH3 gases to the atmosphere As we know, fertilizer N represents the most costly input in grain cereal production, especially corn. So my talk will focus on corn N management while also mention other elated projects. Corn growers have to balance crop N needs to maximum NUE and yield, at the same time, to minimize gaseous N loss and NO3 leaching. In general, NUE, meaning N applied to the soil and ended up in the plant, is only about 50%. Soil physical, chemical and biological conditions have an large impact on NUE and yield N losses is the major concern for corn production Agronomic research on corn is thus focused on NUE, what is the mechanism of plant and soil factors associated with NUE? How can we improve NUE by improving soil physical, chemical and biological conditions?

Annual Quantitative N Cycle for Corn/Soil/Atmosphere (kg N/ha) Atmospheric N 10 24 10 Corn Crop N (Grain=123; Stover=61; Roots=22) 83 192 Soil Organic N (6000) 14 252 NO3-N - 120 HN4-N + 14 24 150 23 Fertilizer N Here is a diagram to show N transformation in a corn yield. Let’s starting with soil, on the top 30 cm of soil layer it contains typically 6000 kg of total N, assume 2% of which is released through N mineralization, it first in a form of NH4-N, which quickly converts to NO3-N through nitrification. So that majority of N uptake by plants is in the form of NO3 while only a small portion in NH4. Farmers usually apply 150 kg N /ha, of which 50% is taken up by plants, some of it is fixed into soil organic matter, a considerable amount of N is lost through volatilization, dinitrication, run off or leaching. Nutrient best management practices are aimed to increase NUE while reducing the loss of N to the environment. In the agricultural soils of tropical and temperate regions (except paddy rice fields) nitrate accounts for 70 to 90% of soil mineral N. Nitrate in the soil solution is 10 times more mobile than NH4+. Two reserves of soil NH4+ exist: a small portion of NH4+ is in the soil solution, and a large portion of NH4+ is adsorbed on soil colloids. Only water soluble NH4+ is available for plant uptake.

The basic relationship Chlorophyll Nitrogen Grain Yield As we know, chlorophyll is the factory for producing food, feed, fibre, and biofuels for mankind. It reflects plant healthiness and productivity. Over 70% of plant total N is in the chlorophyll. Under normal production conditions, these three parameters form a quantitative and stable relationship.

Canopy reflectance x Nitrogen Level > N > DW > LA= > reflectance 40 35 High N 30 25 Reflectance (%) 20 Low N 15 < N < chlorophyll= > reflectance 10 5 400 500 600 700 800 900 Wavelength (nm) Numerous studies have shown that canopy reflectance is closely related to leaf greenness and total biomass. At the red and green wavelength regions, leaf greenness is negatively correlated with leaf chlorophyll content while aboveground biomass is positively correlated with reflectance in the near infrared regions. By integrating these two, NDVI is able to reflect the overall plant N status in a field.

Critical levels 58,0 Y = 33,928 + 0,654x - 0,004x2 R2= 0,98 58,0 55,3 55,3 52,1 52,1 Spad 45,4 45,4 V3 V6 V10 Silking Development stages Figure 1 – Chlorophyll meter mesurements in four corn development stages(Argenta, 2001). When determine the critical levels of NDVI or SPAD, it is important to keep in mind that these values change rapidly from one growth stage to the next

Suficiency index (SI): NDVI in the field SI = = 0.95 NDVI in the high N reference strip Strip Corn field In practice, in a corn field, plant some strips with well fertilized corn as reference, by measuring canopy reflectance in different parts of the field in comparison with the reference strip, we will be able to derive a sufficiency index and decide how much N to be applied at sidedress.

ETAA Project Objectives To develop a crop-based indicator for corn N management that accounts for spatial variability; To determine if the new vehicle based optical sensing technology is sufficiently robust and practical for on-farm use; To determine if variable rate N application based on spectral reflectance can improve NUE and corn performance on a farm scale. In 2005, a new project was support by the environment technology assessment for agriculture program through the Ontario Soil and Crop Improvement Association to demonstrate on farm evaluation of optical sensor technology to minimize environmental impacts and maximize production efficiency associated with N application in corn. So, the overall objectives were to determine

ETAA Variable Rate Nitrogen Study - 2005 960ft = 292.6 m 30ft * * * * 7 7 9 7 * * * * 9 * 17 * * 27 35 * * * * * 5 3 2 1 6 9 4 * 3 4 5 9 6 * 1 2 6 * 5 1 7 3 4 2 2 9 * 5 4 1 6 3 8 * 16 * * 26 34 * o +o o o * * * * 10 * 8 * * 10 10 * * * * * 30+60 7 15 25 33 o +o + +o + * o +o +o * 30+60 * 30+120 30+120 * 8 * o + * +o o + * +o o o o * + +o + 1 2 3 4 5 6 10 * 11 12 13 14 18 * 19 20 21 22 23 24 28 29 30 31 32 * 36 37 38 39 40 Rep 1 Rep 2 Rep 3 Rep 4 North Nitrogen Rates Hybrid Dimensions 1) 0 kg N/ha preplant Pioneer 39D 80 (2550 CHU) 12 rows per plot 2) 30 kg N/ha preplant (26.7 lb/acre) - (Roundup Ready + Poncho 250) 30" rowsplot width = 30 ft 3) 60 kg N/ha preplant (53.4 lb/acre) 4) 90 kg N/ha preplant (80.1 lb/acre) plot length = 80 m (for treatments 1-6), Nitrogen Type 5) 120 kg N/ha preplant (106.8 lb/acre) 6) 150 kg N/ha preplant (133.5 lb/acre) 1) Urea (46-0-0) broadcast preplant 20 m (for treatments 7-10) 7) 30 kg N/ha preplant + 30 kg N/ha sidedress at V6 2) Urea (46-0-0) sidedressed at V6 8) 30 kg N/ha preplant + 60 kg N/ha sidedress at V6 Total Area 9) 30 kg N/ha preplant + 90 kg N/ha sidedress at V6 10) 30 kg N/ha preplant + 120 kg N/ha sidedress at V6 2.34 ha = 5.8 acres * 30 kg N/ha preplant + variable rate N at V6 Revised June 29, 2005 Here is the diagram of the field layout. We had 6 rates of preplant N and 7 rates of preplant plus sidedressed N conducted in a 6 acre field.

Canopy reflectance of the field was mapped both with handheld GreenSeeker and vehicle-mounted N Sensor at the V6 stage.

Responses of NDVI_GS and NDVI_NS to fertilizer N rates   Applied N dose (kg N ha-1) Contrast analysis 30 60 90 120 150 Linear Quadratic Residual NDVI_NS a 30DAS 0.35 0.40 0.43 0.41 * (41%) b ** (57%) NS NDVI_GS a 26DAS 0.37 0.38 (18%) (58%) 33DAS 0.42 0.46 0.48 0.50 0.47 (47%) (44%)   This table shows the responses of canopy reflectance measured by both N Sensor and GreenSeeker shortly before sidedress in 2005 growing season. In general, there was a linear relationship between NDVI and preplant N rates, NDVI saturated between 90 and 120 kg N/ha, and both instruments had very similar results.

GreenSeeker measures canopy differences at pre-sidedress (2005) This slide shows the quantitative relationships between canopy reflectance and preplant applied fertilizer N rates.

Saturation index shows seasonal N needs (Qc data) Yield difference due to N (t/ha) In Quebec, Nicolas Tremblay found an relationship between yield difference due to applied N and leaf chlorophyll saturation index.

Grain yield * * * In 2005 growing season, we manually applied variable N. This slide shows the overall yield of each treatment. Last year, corn yield was exceptionally high, up to 14 t/ha was obtained with 30 plus 120 kg N treatment. when we compare these 3 treatments, of which all received 120 kg N/ha, but applied at different time, it clearly shows the advantage of N sidedress.

) Grain yield (Mg ha Fertilizer (kg N ha ) 15 y = -0.0002x -1 14 R 2 = 0.979 13 12 11 2 10 y = -0.0002x + 0.066x + 7.3 Grain yield (Mg ha 9 R 2 = 0.995 8 7 6 30 60 90 120 150 Fertilizer (kg N ha -1 ) Preplant 30+sidedress Response of grain yield to fertilizer N followed a quadratic function. Clearly, grain yield responded more to sidedressed N than preplant N: 77 kg of yield was produced for every kg of sidedressed N compared to 66 kg of yield.

This year the experiment was repeated in an adjacent farmer’s field with about 30 acres

Adjustable Sensor Mounting It was the first attempt to carry out the variable N rate application in Ontario and Quebec based on NDVI mapping using an RT200 system

Ottawa Equipment Ford 7610 tractor with modified hydraulic returns Yetter 2995 Bubble Fertilizer Coulters with rear Knife 250 liter tank with filter John Blue positive displacement piston pump with flow divider Rawson Accurate Controller Dickey John Radar Raven GPS GreenSeeker RT200

GreenSeeker Mapping June 26, 2006 REP AVG MAX MIN 1 .57 .78 .32 2 .51 .76 .25 3 .58 .83 .26 4 .66 .85 This is our GreenSeeker data taken 3 days before application. Scanned at 15’ wide, Mapped at 10’ wide NDVI Range below .3 to above .8 when mapped June12,14,26&29

Corn 32” to 36” high on Application Day, Ottawa

Ottawa Application Non-irrigated spring wheat with modified inputs gave a very reasonable application curve On application day the curve could not be manipulated to suite our rates because of high NDVI values. Only choice we had was to use the 16 point stepped (not interpolated) graph In StJean, the non-irrigated spring wheat was manipulated to give a very reasonable curve

Ottawa Rate Accurate controller settings: NDVI US gal/ac .2 .25 .3 .35 .4 .45 .5 .55 9.2 .6 35.9 .65 35.0 .7 33.1 .75 32.1 .8 28.5 .85 21.2 .9 11.0 .95 Accurate controller settings: 9.2 to 36.8 gal /ac was the preset range (30 kg N/ha to 120 kg N/ha) Controller works on percentage change from a mid point. 23 gal/ac as the mid point with 4 % increment giving .92 gal There are 32 increments. Based on the maximum NDVI value in the reference strip, saturation index was calculated; the value was then converted back to NDVI; and N rates were calculated based on N response curve derived from an earlier study with Nmin = 30 and Nmax = 120 kg /ha. The 16 points NDVI-N rates were used for variable rate application as we were unable to receive an updated version of the software. In our Quebec site, the rainfed spring wheat algorithm was tested to produce a reasonable response curve, and thus used.

Summary (2005) Very high grain yield in 2005; yield did not plateau; Yield was more responsive to sidedress (77 kg/kg N) than preplant (66 kg/kg N) fertilizer N; Canopy reflectance (NDVI) differentiate low from high soil N NDVI ranges are narrow, sensitive with crop growth stage Better economic return with sidedressed fertilizer N. But, further research is needed for variable N rate application. Year 2005 was Very high in grain yield; yield did not reach plateau. Yield was more responsive to sidedress (77 kg/kg N) than preplant (66 kg/kg N) fertilizer N. Canopy reflectance (NDVI) differentiated low from high soil N. Better economic return with sidedressed fertilizer N. But, further research is needed for variable N rate application

Summary (2006) First year of variable rate N application based on NDVI saturation index (SI) Canopy NDVI values change rapidly from V6 to V8 (plants 2.5-3 feet tall) and can be quickly saturated (NDVI >0.82). The rainfed spring wheat algorithm provided by the RT-200 GreenSeeker was used in Quebec where NDVIref <0.7 In Ottawa site, differences in canopy reflectance among preplant broadcast fertilizer N rates was confounded with poor seedling growth under high N rates due to low soil pH coupled with cool spring. Although such confounding effect was minimal around or after sidedress, it made difficult interpret the NDVI data. The maximum NDVI value was used to derive SI, and Nmin and Nmax were set at 9.2 and 36.8 gal/ac; variable N rate application was made using the 16 points algorithm. It is expected that a better NDVI-N requirement algorithm will be available or developed at site for use next year.

Acknowledgements Ontario Soil and Crop Improvement Association Lynne Evenson, Doug Balchin, Vivianne Deslauriers