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21/10/2015
1
OBERTHÜR, Thomas
Director South East Asia Program, International Plant Nutrition Institute
Plantation Intelligence® Analysis of Commercial Data for Yield and Fertilizer Management in Oil Palm
1 Conceptual
Background
21/10/2015
2
IPNI 4R Nutrient Stewardship ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
Decision Making Uncertainty
Complex
interactions in an
agronomic system
render outcomes of
any management
decision
Uncertain
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
3
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)
Decision Making Uncertainty
Example:
ROI in
Fertilizer
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
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.”
Business Intelligence ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
4
http://www.bireports.co.uk/blog/tag/hans-peter-luhn/
Business Intelligence ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
System is Monitored in Extraordinary Detail
Plantation Intelligence® ®
21/10/2015
5
Devise
specific
performance
intervention
options
(EVALUATE)
Organize
existing
performance
data
(VISUALIZE)
Quantify
performance
change for
management
(DECIDE)
Generate
performance
indicators and
metrics
(ANALYSE)
Plantation Intelligence®
Exogenous
Exogenous
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
Plantation Intelligence®
An adaptive learning process
based on the analysis of
plantation data
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
6
Measure
Performance Plantation
Intelligence®
Business
Opportunity PALMSIM
Model
Continuous
Improvement Best Management
Practices
Estate
Networking The
Benchmark Club
Plantation Intelligence® ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
2 Application
Examples
21/10/2015
7
Current Protocols
Yield Age
Profiling
Naïve Gross
Margins
Yield Trends Yield Soil Climate
Interactions
Yield Labor
Interactions
Yield Soil
Interactions
Fertilizer Response
Analyses 7 ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
0
40
30
20
50
60
3 4 11 9 7 5 13 14 15
10
6 8 10 12 TREEAGE
FF
B (
t/h
a)
Yield Age Profiling ®
21/10/2015
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TREEAGE
0
40
30
20
50
60
10
FF
B (
t/h
a)
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
FF
B (
t/h
a)
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
®
21/10/2015
9
Avera
ge n
aïv
e g
ross m
arg
in in U
SD
per
hecta
re
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”
®
Avera
ge n
aïv
e g
ross m
arg
in in U
SD
per
hecta
re
Individual Block
0
4000
3000
2000
5000
1000
3500
2500
1500
4500
5500
500
Naïve Gross Margins ®
21/10/2015
10
Avera
ge n
aïv
e g
ross m
arg
in in U
SD
per
hecta
re
Individual Block
0
4000
3000
2000
5000
1000
3500
2500
1500
4500
5500
500
Naïve Gross Margins ®
3 Response to
Fertilizer
21/10/2015
11
NPKMg
8~10 BREAK–EVEN
kg kg
point
fresh fruit bunches per kg nutrients
Return on Investment ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
2.5 years to 0.5 year before harvest
Sum of NPKMg
Return on Investment
NPKMg
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
12
20
15
10
25
30
100 300 1100 900 700 500
5
600 800 1000 1200
NPKMg3yW_IN
Fre
sh
fru
it b
un
ch
es in
to
ns p
er
he
cta
re
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
Fre
sh
fru
it b
un
ch
es in
to
ns p
er
he
cta
re
NPKMg3yW_IN
y=22.233 + (0.005*x) y=12.908 + (0.011*x)
Plateau : Palm age from 6-13
Tree Age Effects ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
10
34
30
26
22
18
14
Fre
sh
fru
it b
un
ch
es in
to
ns p
er
he
cta
re
NPKMg3yW_IN
12
32
28
24
20
16
Annual Response 2012
360 400 640 600 560 520 480 440 340 380 620 580 540 500 460 420 680 660
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
13
10
34
30
26
22
18
14
Fre
sh
fru
it b
un
ch
es in
to
ns p
er
he
cta
re
NPKMg3yW_IN
12
32
28
24
20
16
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
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
NPKMg3yW_IN
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
Fre
sh
fru
it b
un
ch
es in
to
ns p
er
he
cta
re
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
14
NPKMg3yW_IN
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
Fre
sh
fru
it b
un
ch
es in
to
ns p
er
he
cta
re
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.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
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’
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
15
2013 2014
Visualizing Local Response
1.40
0.00
-0.75
Contrast in t FFB
per ha per year
relative to yield
without fertilizer
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
2013 2014
Visualizing Local Response
1.40
0.00
-0.75
Contrast in t FFB
per ha per year
relative to yield
without fertilizer
®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
16
4 “Disclaimer”
10
15
5
30
25
20
40
35
15 45 25 35 5 10 20 30 40
45
50
55
Harvest Man days
Fre
sh
Fru
it B
un
ch
Yie
ld in
t p
er
ha
2003
2004
2005
2006
2006
2007
2008
2009
2010
2011
2012
Confounding Effects ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
17
10
15
5
30
25
20
40
35
15 45 25 35 5 10 20 30 40
45
50
55
Expected yield level
Fre
sh
Fru
it B
un
ch
Yie
ld in
t p
er
ha
2003
2004
2005
2006
2006
2007
2008
2009
2010
2011
2012
Harvest Man days
Confounding Effects ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
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
Fre
sh
Fru
it B
un
ch
Yie
ld in
t p
er
ha
2003
2004
2005
2006
2006
2007
2008
2009
2010
2011
2012
Harvest Man days
Confounding Effects ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
21/10/2015
18
VS.
Yield Taken
Yield Made EXPECTATION
REALITY
Confounding Effects ®
OberthÜr et al.
IFA Crossroads Asia-Pacific
Kuala Lumpur, Malaysia
4WA
IPNI Southeast Asia Program
IFA Crossroads Asia-Pacific
20-22 October 2015
Kuala Lumpur, Malaysia
