yield editor 2.0 yield maps made easy
DESCRIPTION
Yield Editor 2.0 yield maps made easy. Ken Sudduth, Scott Drummond, and Brent Myers USDA-ARS Cropping Systems and Water Quality Research Unit Columbia, MO. - PowerPoint PPT PresentationTRANSCRIPT
YIELD EDITOR 2.0YIELD MAPS MADE EASY
Ken Sudduth, Scott Drummond, and Brent MyersUSDA-ARS Cropping Systems and Water Quality Research UnitColumbia, MO
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
From Sensors to Yield Maps
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Why clean yield data? Yield data ALWAYS contain problems
Operational problems Data collection errors Calibration issues
Sensor system related problems Sensor failure, noise, accuracy issues Timing/filtering issues for individual sensors Multiple sensors can magnify problems
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
where k is used to account for unit conversion factors, and MC is a moisture correction factor based upon a crop specific market reference.
Basic yield calculation
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
VelocityWidthFlowMCYield
k
Rapid change in velocity
C orn Y ield(bu/ac)
174 to 2963 165 to 174 153 to 165 145 to 153 138 to 145 132 to 138 126 to 132 120 to 126 113 to 120 6 to 113
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Unknown swath width
Soybean Y ie ld(bu/ac) 29 to 54 28 to 29 26 to 28 25 to 26 25 to 25 24 to 25 23 to 24 22 to 23 18 to 22 0 to 18
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
where i = time for grain to reach moisture sensor j = time for grain to reach grain flow sensor
Yield calculation with latency
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
)Velocity()Width()Flow()MC()Yield(
ttjt itkt
Incorrect delay time(s)
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Corn Y ie ld(bu/ac)
124 to 180 110 to 124 101 to 110 95 to 101 89 to 95 83 to 89 76 to 83 68 to 76 52 to 68 30 to 52
Delay T im e = 9 s Delay T im e = 14 s
Ramping at crop edge
Corn Y ie ld(bu/ac)
124 to 207 110 to 124 102 to 110 95 to 102 90 to 95 84 to 90 77 to 84 69 to 77 55 to 69 1 to 55
No edge treatment Edge cleaned
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Ramping at crop edgeKriged
No edge treatmentKriged
Edge cleanedDifference
(bu/ac)
Mean = 106.4STD = 32.3
Mean = 108.1STD = 31.7
>10% affected bymore than 5 bu/ac
- 5
0
5
1 0
1 5
2 0
2 5
3 0
3 5
4 0
4 5
5 0
5 5
1 0
2 0
3 0
4 0
5 0
6 0
7 0
8 0
9 0
1 0 0
1 1 0
1 2 0
1 3 0
1 4 0
1 5 0
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Dealing with yield map errors All yield maps contain some errors that should
be removed before analysis Manufacturers’ software does a good job of
dealing with many simpler problems They have a tougher time with “trial-and-error”
type settings (i.e. delay time – set, view, adjust) Manual editing (point, transect, area, etc.) must
be done elsewhere (generally in a GIS) A software package was needed that provided
all of these tools in one placeTranslating Missouri USDA-ARS Research and Technology into Practice
A training session provided by USDA-ARS-CSWQRU, 10-11 October 2012, Columbia, MO
Yield Editorversion 1.0, developed 2003
Yield Editor has been widely used by farmers, students, researchers, consultants, and others
Total downloads of the software are now well over 3000Translating Missouri USDA-ARS Research and Technology into Practice
A training session provided by USDA-ARS-CSWQRU, 10-11 October 2012, Columbia, MO
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Yield Editorversion 2.0
In 2010 we began developing a new version of Yield Editor that would automate more of the yield data cleaning process Delay time Overlapped travel at end rows and partial
swaths Unrealistic point yield values “Smart” thresholds for other filtering
parameters Batch mode operationTranslating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Yield Editorversion 2.0
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Automated yield cleaning expert (AYCE)
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Delay time determination Using relative spatial consistency
Lee, D. H., K. A. Sudduth, S. T. Drummond, S. O. Chung, and D. B. Myers. 2012. Automated yield map delay identification using phase correlation methodology. Trans. ASABE 55(3): 743-752.
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Han’s bitmap overlap filter
Han, S., S.M. Schneider, S.L. Rawlins, and R.G. Evans. 1997. A bitmap method for determining effective combine cut width in yield mapping. Trans. ASAE 40(2): 485-490.Translating Missouri USDA-ARS Research and Technology into Practice
A training session provided by USDA-ARS-CSWQRU, 10-11 October 2012, Columbia, MO
Localized standard deviation filter
Localized STD Filter Settings:Grid Cell = 5 Header WidthsLimit = 3 Standard Deviations
Cell Results:Mean = 165 STD = 15Retain 120-210 in this cellCyan points removed
Crop Yield
31 58 86 113 141 168 196 223 Cell Results:
Mean = 172 STD = 9Retain 145-199 in this cellNo points removed
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO
Summary The new Yield Editor 2.0 automates
many common yield cleaning tasks Features from Yield Editor 1.0 are all still
available, in addition to a host of new automated features
Currently available for web download – just do a web search for “Yield Editor 2”
We encourage interested users to try it and give us feedback
Translating Missouri USDA-ARS Research and Technology into Practice A training session provided by USDA-ARS-CSWQRU, 10-11 October
2012, Columbia, MO