Andrew Van Burgel

Analysis Issues in Precision Agriculture
Farmer Friendly Experiments
Andrew van Burgel
Department of Agriculture and Food, Albany, WA
15 July 2011 - Australian Applied Statistical Conference

WA Biometrics Update
• Jane Speijers retired 16 June 2010
• 38 years of service
• part time consulting
• Current Biometrics unit – Mario & I
• Advertised for another biometrician.

Family Update
• 2005 Thredbo – 1 st child
• 2006 Victor Harbour – 2 nd child
• 2008 Marysville – 3 rd child
• 2011 Cairns – sorry no 4 th child!

Precision Agriculture
• Advances in GPS guidance technology around the year 2000.
• Adoption by farmers of auto-steering farm machinery.
• Variable rates of inputs applied across a paddock to better match
different soil types.
• Harvester automatically measures yield at small intervals (meters).

Farmer Friendly Experiments
• Large scale using typical farmer equipment for minimal disruption
• Above modern air seeder has width of 60 feet (18 meters)
• Below autosteer harvester has width of 36 feet (11 meters)
• Seeder in Action
Insert partner logo

Typical design on WA farms
• Treatment strips within a
paddock that may have
variable rates
Aims:
1.Is there a treatment effect
2.Is the treatment effect
different between zones

Case study
Treatments:
• 4 Gypsum rates
9375
4375
1875
625
Treatment Strips
• ~40m by 500m

Case study
Treatments:
• 4 Gypsum rates
9375
4375
1875
625
Treatment Strips
• ~40m by 500m
No. Harvesters: 2
(showing harvest runs ~10m apart)

Statistical Challange
• Design:
• no replication (or only a control treatment is repeated)
• small number of parallel treatment strips
• Question:
• What is a statistically sound yet simple analysis method
(requiring minimal steps, software, statistical skills)
• Feedback welcome on the approach presented or alternatives.

Yield data – Machine 2
End4 4:21pm30th
1min stop
2min stop
1min stop
4min stop
5min stop
2min stop
Start3 7:44am30th
End2 11:55pm29th
Start2 11:25pm29th
3min stop
1min stop
End3 8:02am30th
End1 10:50pm29th
Start4 10:13am30th
1min stop
1min stop
Start1 7:31pm29th

A clean run...
End4 4:21pm30th
1min stop
2min stop
1min stop
4min stop
5min stop
2min stop
Yield (t/ha)
Speed (m/s)
5
4.5
4
Start3 7:44am30th
End2 11:55pm29th
Start2 11:25pm29th
3min stop
3.5
3
2.5
1min stop
End3 8:02am30th
End1 10:50pm29th
Start4 10:13am30th
Start1 7:31pm29th
2
1.5
1
0.5
0
1min stop
1min stop
0 50 100 150 200 250 300
Consequtive yield monitor points

Harvestor stop
End4 4:21pm30th
1min stop
2min stop
1min stop
4min stop
5min stop
2min stop
Yield (t/ha)
Speed (m/s)
10
9
8
Start3 7:44am30th
End2 11:55pm29th
Start2 11:25pm29th
3min stop
1min stop
7
6
5
End3 8:02am30th
End1 10:50pm29th
Start4 10:13am30th
Start1 7:31pm29th
4
3
2
1
0
1min stop
1min stop
0 20 40 60 80 100 120
Consequtive yield monitor points

Already harvested patches
End4 4:21pm30th
1min stop
2min stop
1min stop
4min stop
5min stop
2min stop
Yield (t/ha)
Speed (m/s)
5
Start3 7:44am30th
End2 11:55pm29th
Start2 11:25pm29th
3min stop
4
3
1min stop
End3 8:02am30th
End1 10:50pm29th
Start4 10:13am30th
2
1min stop
Start1 7:31pm29th
1
0
1min stop
0 20 40 60 80 100 120
Consequtive yield monitor points

Run effects
• Large run effects: Run 30 is >0.5t/ha (or 20%) more than Run 31
• Machine & direction effects (rows 22-44, but not elsewhere)
3.8
Machine 1 North Machine 1 South Machine 2 South Machine 2 North Treatment Strips
3.7
3.6
3.5
Yield (t/ha)
3.4
3.3
3.2
3.1
3
0 10 20 30 40 50
Run Number

Analysis – Treatment main effects
• Spatial trend – compare paddock yields either side of treatment
area and adjust only if necessary.
• AOV
• experimental unit – run means
• blocking for harvest direction and machine effects (if present)
• Case Study:
Analysis of variance
Variate: Yield
Source of variation d.f. s.s. m.s. v.r. F pr.
Run_Type stratum 2 0.325462 0.162731 39.94
Run_Type.*Units* stratum
Gypsum 3 0.026041 0.008680 2.13 0.198
Residual 6 0.024447 0.004075
Total 11 0.375950
Tables of means
Gypsum 625 1875 4375 9375
3.335 3.451 3.433 3.439
Least significant differences of means (5% level)
l.s.d. 0.1275

Variance
Variance
Analysis – Treatment by Zone interaction (1)
• Run effects cancel out ☺
• Calculate average yield in 20m cells in each strip
• individual points are not independent
• Variogram:
0.20
0.175
~20m
0.150
0.15
0.125
0.100
0.10
0.075
0.05
0.050
0.025
0.00
0.000
0 50
100
150
200 250
0 10 20
30 40
50
Lag Distance
Lag Distance

Analysis – Treatment by Zone interaction (2)
• AOV
• experimental unit – 20m cell means
• blocking for adjacent cells
• treatment = gypsum*zone
• Case Study:
Analysis of variance
Variate: Yield
Source of variation d.f. (m.v.) s.s. m.s. v.r. F pr.
Block stratum
Zone 1 5.42704 5.42704 103.82

Alternative Design
• Strips and run directions perpendicular
• Advantages
• run effects do not interfere with
treatment main effects
• simpler data setup and analysis
• Disadvantages
• may not suit farmer
• more impacted by ‘lag effect’

Farmer advice
• Use single harvester (and same direction if possible)
• Avoid stopping within trial area and try maintain constant speed.
• Same treatment for each end strip (to help assess spatial trend)

Feedback / Discussion
• Suggested improvements to analysis (while keeping it simple!)
• Appropriate cell size from Variogram
• Improvements to design (that farmers will accept)
• Other...
Thank you for your time!