![Page 1: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/1.jpg)
Integrating Weather and Soil Information With Sensor Data
Newell KitchenUSDA ARS Cropping Systems and Water Quality Research Unit
Columbia, Missouri
![Page 2: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/2.jpg)
• What factors should an algorithm account for when generating an N fertilizer recommendation?
![Page 3: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/3.jpg)
Calculation for N fertilizer Rate
Missouri NRCS Agronomy Technical Note MO-35: Corn Variable-Rate Nitrogen Fertilizer Application for Corn Using In-field Sensing of Leaves or Canopy
1
2
3
![Page 4: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/4.jpg)
Optimal N Rate as a Function of Canopy Reflectance
N Ra
te fo
r Max
. Eco
n. Y
ield
(kg
N ha
-1)
1
23
![Page 5: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/5.jpg)
The Soil Factor
![Page 6: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/6.jpg)
Precipitation
![Page 7: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/7.jpg)
Abundant and
Well-Distributed Rainfall
![Page 8: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/8.jpg)
What Factors Should Be Considered?
• Crop• Stage of crop• Sensor specific• Soil
• Soil water holding capacity• Mineralizable N• N Loss vulnerabilities
• Weather• Poor health, poor stand, no stand• Hybrid• Farmer intuition (Max and Min)• Economics
Robustness Ease of Use
![Page 9: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/9.jpg)
What Tool(s) and Supporting Algorithm(s) Captures the Important Factors and Performs Best?
Universal Farm/Field Specific
![Page 10: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/10.jpg)
Regional NUE Project• Results confounded by
• Varied methods of sensing• Varied N management practices• Varied other cultural practices
![Page 11: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/11.jpg)
Needed: Datasets for evaluation and validation, over a wide range of soil and weather scenarios, the yield and economic performance of model and plant sensing decision tools for determining the amount of N fertilizer to be applied to corn.
![Page 12: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/12.jpg)
Performance and Refinement of In-season Corn Nitrogen Fertilization Tools
![Page 13: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/13.jpg)
Data from ProjectPerformance and Refinement
of In-season Corn Nitrogen Fertilization Tools
Evaluate DuPont Pioneer
proprietary products and decision aids
Evaluate public-domain decision aid tools, develop
agronomic science for improved crop N
management, train new scientists, and publish results
University
![Page 14: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/14.jpg)
Tools Assessment• Yield and soil measurements from these
plot studies will provide N response functions that will be used to reference each of the decision tool methods to be evaluated.
• The N rate that would have been recommended by a tool will be matched with the optimal N-rate. Performance of the tool can be for yield, profitability, NUE, N loss, etc.
![Page 15: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/15.jpg)
Standardized Protocols• Site Selection• Site characterization• Treatment implementation• Weather data collection• Equipment• Soil and plant sampling• Management notes• Data management
![Page 16: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/16.jpg)
16 Sites in 2014
![Page 17: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/17.jpg)
Integrating Weather and Soil Information With Sensor Data
Newell KitchenUSDA ARS Cropping Systems and Water Quality Research Unit
Columbia, Missouri
![Page 18: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/18.jpg)
How might soil EC help characterize in-season corn N fertilizer rate both within field and across the cornbelt?
![Page 19: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/19.jpg)
0 10 20 30 40 50 60 70
Soil Electrical Conductivity (mS/m)
Rela
tive
Prod
uctiv
ity
Sand Loam Clay
Infiltration goodPAWC poor
Infiltration goodPAWC good
Infiltration poorPAWC poor
![Page 20: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/20.jpg)
504530 504540 504550 504560 504570 504580 504590 504600 504610 504620
4587670
4587680
4587690
4587700
4587710
4587720
4587730
4587740
4587750
4587760
4587770
6.08.010.012.014.016.018.020.022.024.026.028.030.032.034.036.038.040.042.044.046.048.050.052.054.0
506260 506280 506300 506320 506340 5063604587840
4587860
4587880
4587900
4587920
4587940
6.08.010.012.014.016.018.020.022.024.026.028.030.032.034.036.038.040.042.044.046.048.050.052.054.0
6.08.010.012.014.016.018.020.022.024.026.028.030.032.034.036.038.040.042.044.046.048.050.052.054.0
Clay
Sand
Site Soil EC Maps
![Page 21: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/21.jpg)
0 10 20 30 40 50 60 70
Soil Electrical Conductivity (mS/m)
Rela
tive
Prod
uctiv
ity
Sand Loam Clay
IL BRTIL URB
NE BRD NE SCAL
IA AMES
WI WAUWI STU
IA MC
IN SAND IN LOAM
ND DUR (+110) ND AMEN
MO TRTMO BAY
MN ST CH MN New Rich
![Page 22: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/22.jpg)
0 10 20 30 40 50 60 70
Soil Electrical Conductivity (mS/m)
Rela
tive
Prod
uctiv
ity
Sand Loam Clay
Infiltration goodPAWC poor
Infiltration goodPAWC good
Infiltration poorPAWC poor
![Page 23: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/23.jpg)
Why Regional Investigation of this kind?
• Breadth. More comprehensive story when a wider range of soil, weather, and cultural norms are included using standardized procedures
• Balance. Build on the unique perspectives and strengths each investigator brings (both with critical and creative thinking), and perhaps also it helps neutralize individual’s biases
• Strengthens and Weaknesses. Side-by-side testing of the tools will allow for better understanding of where and when they work best
![Page 24: Integrating Weather and Soil Information With Sensor Data](https://reader030.vdocuments.mx/reader030/viewer/2022032414/568132ff550346895d99bb01/html5/thumbnails/24.jpg)