plantation intelligence
TRANSCRIPT
Plantation Intelligence® Analysis of Commercial Data for Yield
and Fertilizer Management in Oil Palm
XVIII Conferencia Internacional Sobre Palma de Aceite 18th International Oil Palm Conference
Oberthür, Chua, Cook, Donough, Cock, Lim, Mohanaraj, Rachel & Kam
22 al 25 de Septiembre de 2015 Cartagena de Indias, Colombia
1Conceptual Background
Cook et al. Better Crops 97, 17 - 20 (2013) !OberthÜr et al.
18th International Oil Palm Conference. Cartagena de las indias Cartagena de las indias
IPNI 4R Nutrient Stewardship ®
Cook et al. Better Crops 97, 17 - 20 (2013) !OberthÜr et al.
18th International Oil Palm Conference. Cartagena de las indias Cartagena de las indias
Decision Making Uncertainty
Complex interactions in an
agronomic system render outcomes of any management
decision
Uncertain
®
STRUCTURAL Uncertainty from internal factors that influence fertilizer efficiency, e.g. EFB applications
TRANSLATIONAL Uncertainty from external factors that reduce fertilizer performance, e.g. harvest, mill and transport efficiency
TEMPORAL Uncertainty about
timing of fertilizer applications, e.g.
drought interference
METRIC Uncertainty about rate & placement of
fertilizer to support a yield target
Cook et al. Better Crops 97, 17 - 20 (2013) !OberthÜr et al.
18th International Oil Palm Conference. Cartagena de las indias Cartagena de las indias
Decision Making Uncertainty
Example:
ROI in Fertilizer
®
10
15
5
30
25
20
40
35
15 45 25 35 5 10 20 30 40
45
50
55
Harvest Man days
Fres
h Fr
uit B
unch
Yie
ld in
t pe
r ha
2003 2004 2005 2006 2006 2007 2008 2009 2010 2011 2012
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Decision Making Uncertainty ®
10
15
5
30
25
20
40
35
15 45 25 35 5 10 20 30 40
45
50
55
Expected yield level
Fres
h Fr
uit B
unch
Yie
ld in
t pe
r ha
2003 2004 2005 2006 2006 2007 2008 2009 2010 2011 2012
Harvest Man days
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Decision Making Uncertainty ®
10
15
5
30
25
20
40
35
15 45 25 35 5 10 20 30 40
45
50
55
Fruit is grown but not harvested
Only with enough labor, all fruit is harvested
Expected yield level
Fres
h Fr
uit B
unch
Yie
ld in
t pe
r ha
2003 2004 2005 2006 2006 2007 2008 2009 2010 2011 2012
Harvest Man days
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Decision Making Uncertainty ®
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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VS.
Yield Taken
Yield Made EXPECTATION
REALITY
Decision Making Uncertainty ®
Hans Peter Luhn, IBM Journal, 1958 A Business Intelligence System
http://www.bireports.co.uk/blog/tag/hans-peter-luhn/!
(business) intelligence is “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.”
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Business Intelligence ®
http://www.bireports.co.uk/blog/tag/hans-peter-luhn/!
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Business Intelligence ®
System is Monitored in Extraordinary Detail
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Plantation Intelligence® ®
Devise specific
performance intervention
options (EVALUATE)
Organize existing
performance data
(VISUALIZE)
Quantify performance change for
management (DECIDE)
Generate performance
indicators and metrics
(ANALYSE)
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Plantation Intelligence®
Exogenous
Exogenous
®
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Plantation Intelligence®
An adap've learning process based on the analysis of
planta'on data
®
2Application Examples
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Current Protocols
Yield Age Profiling
Naïve Gross Margins
Yield Trends Yield Soil Climate Interactions
Yield Labor Interactions
Yield Soil Interactions
Fertilizer Response Analyses 7
®
0
40
30
20
50
60
3 4 11 9 7 5 13 14 15
10
6 8 10 12 TREEAGE
FFB
(t/ha
)
Yield Age Profiling ®
TREEAGE 0
40
30
20
50
60
10
FFB
(t/ha
)
3 4 11 9 7 5 13 14 6 8 10 12
Yield Age Profiling
15
®
TREEAGE
PALMSIM Model Agricultural Systems, 131:1-10 (2014) The Planter, 91: 81-96 (2015)
0
40
30
20
50
60
10
FFB
(t/ha
)
3 4 11 9 7 5 13 14 6 8 10 12
Yield Benchmarking
15
1. Average yield profile mirrors that of potential
2. Yield gap between average and potential
3. Blocks approach yield potential
4. Blocks above potential require further assessment
®
Aver
age
naïve
gro
ss m
argi
n in
USD
per
hec
tare
Individual Block 0
4000
3000
2000
5000
1000
3500
2500
1500
4500
5500
500
Naïve Gross Margins
Cost = 500 $US per ha per year “i.e. a favorable benchmark”
®
Aver
age
naïve
gro
ss m
argi
n in
USD
per
hec
tare
Individual Block 0
4000
3000
2000
5000
1000
3500
2500
1500
4500
5500
500
Naïve Gross Margins ®
Aver
age
naïve
gro
ss m
argi
n in
USD
per
hec
tare
Individual Block 0
4000
3000
2000
5000
1000
3500
2500
1500
4500
5500
500
Naïve Gross Margins ®
3Response to Fertilizer
NPKMg
8~10 BREAK–EVEN
kg kg
point
fresh fruit bunches per kg nutrients
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Return on Investment ®
2.5 years to 0.5 year before harvest Sum of NPKMg
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Return on Investment
NPKMg
®
20
15
10
25
30
100 300 1100 900 700 500
5
600 800 1000 1200
NPKMg3yW_IN
Fres
h fru
it bu
nche
s in
tons
per
hec
tare 35
Steep Ascent : Palm age from 3-5
200 400
25
20
15
30
35
10
40
300 400 800 700 600 500 550 650 750 850 350 450
45
Fres
h fru
it bu
nche
s in
tons
per
hec
tare
NPKMg3yW_IN
y=22.233 + (0.005*x) y=12.908 + (0.011*x)
Plateau : Palm age from 6-13
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Tree Age Effects ®
10
34
30
26
22
18
14
Fres
h fru
it bu
nche
s in
tons
per
hec
tare
NPKMg3yW_IN
12
32
28
24
20
16
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Annual Response 2012
360 400 640 600 560 520 480 440 340 380 620 580 540 500 460 420 680 660
®
10
34
30
26
22
18
14
Fres
h fru
it bu
nche
s in
tons
per
hec
tare
NPKMg3yW_IN
12
32
28
24
20
16
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Annual Response 2012
360 400 640 600 560 520 480 440 340 380 620 580 540 500 460 420 680 660
y=21.142 + (-0.003*x)
y=32.489 + (-0.015*x) y=14.481 + (0.024*x)
y=36.217 + (-0.022*x)
SMG A SMG B SMG C SMG D
®
NPKMg3yW_IN
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Annual Response 2014
8
30
26
22
18
14
12
32
28
24
20
16
10
34
360 400 600 560 520 480 440 340 380 620 580 540 500 460 420
Fres
h fru
it bu
nche
s in
tons
per
hec
tare
®
NPKMg3yW_IN
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Annual Response 2014
8
30
26
22
18
14
12
32
28
24
20
16
10
34
360 400 600 560 520 480 440 340 380 620 580 540 500 460 420
Fres
h fru
it bu
nche
s in
tons
per
hec
tare
y=3.256 + (0.036*x)
y=50.634 + (-0.054*x) y=13.470 + (0.025*x) y=13.972 + (0.025*x)
SMG A SMG B SMG C SMG D
®
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Yield Response (t FFB ha y) = F1 (PV1, PV2, … PVN, PVNPKMg) Yield Response (t FFB ha y) = F2 (PV1, PV2, … PVN) Response Contrast (t FFB ha y) = F2 – F1
Visualizing Local Response
‘Contrast Method’
®
2013 2014
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Visualizing Local Response
1.40 0.00
-0.75
Contrast in t FFB per ha per year relative to yield
without fertilizer
®
2013 2014
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Visualizing Local Response
1.40 0.00
-0.75
Contrast in t FFB per ha per year relative to yield
without fertilizer
®
Measure Performance
Plantation Intelligence®
Business Opportunity
PALMSIM Model
Continuous Improvement
Best Management Practices
Estate Networking
The Benchmark Club
OberthÜr et al. 18th International Oil Palm Conference. Cartagena de las indias
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Systems Solutions ®
4WA
IPNI Southeast Asia Program
XVIII Conferencia Internacional Sobre PALMA DE ACEITE
18th International Oil Palm Conference
22 al 25 de Septiembre de 2015 Cartagena de las Indias, Colombia