Simulation of Bioeconomy System using Agent-based Model in the Case of Smart, Green, and Conventional Farming

International Conference on Green
Agro-industry and Bioeconomy
(ICGAB)
18-20 September 2018, Malang, Indonesia 1
Simulation of Bioeconomy System
using Agent-based Model in the
Case of Smart, Green, and
Conventional Farming
S Viridi*, P Premadi, P Aditiawati, ES Maqdir,
T Suheri, J Halid, KN Sari, US Pasaribu,
NM Sudaryani, N Latifah, S Rahimah
*dudung@fi.itb.ac.id
20180917_1

Outline
• Introduction
• Model
• Result s and discussion
• Summary
• Acknowledgments
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..

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Introduction

Conventional farming
• Compared to organic farming will differ in
affecting soil condition on
– soil erosion (Reganold et al., 1987)
– soil fertility and biodiversity (Mäder et al., 2002),
– soil quality (Flieβbach et al., 2007)
• Required higher input labour about 15 %
(Pimentel et al., 2005)
(ICGAB)

Smart farming
• Using information and communication
technology in advancing farming system, from
controlling the plant environment to
managing the market of the farming product
(Wolfert et al., 2017)
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Types of farming
• Types to be compared
– Conventional farming (CF)
– Organic farming (OF)
– Smart farming (SF)
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Model

Agent-based model (ABM)
• Agent can have (Abdou et al., 2012)
– perception of their environment (and also other
agents),
– performance in the form of moving, communi-
cating with other agents and interacting with their
environment
– memory for their previous actions and states, and
– policy in the form of a set of rules, heuristics or
strategies to overcome their present situation
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Why ABM?
• It is able to accomodate a holistic approach in
economy (Farmer & Foley, 2009)
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0
0.02
0.04
0.06
0.08
0.1
0 10 20 30 40
pT
T (°C)
Temperature occurence
• (Zhang et al., 2011)
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( ) ( )







 −
−= 2
2
2
exp
2
1
T
T
T
T
T
Tp
σ
µ
πσ
μT = 20, σT = 4,
Tmin = 0, Tmax = 40,
ΔT = 1

0
0.02
0.04
0.06
0.08
0.1
0.12
0 10 20 30 40 50
pI
I (mm / h)
• (Zhang et al., 2011)
Precipitation occurence
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I∞ = –3, Imin = 0,
Imax = 50, ΔI = 1
( )
( ) ( ) 





−






−−−
=
∞∞∞ IIIIII
IpI
1
lnln
1
minmax

0
0.2
0.4
0.6
0.8
1
0 10 20 30 40
GT
T (°C)
Plant growth (temperature)
• (Hatfield & Prueger, 2015)
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( )
( )
( )
( )
( )
( )

















<
≤<−
−
+−
≤≤+−
<≤−
−
+−
<
=
,,0
,,
1
,,1
,,
1
,,0
2
2
2
2
2
2
TT
TTTTT
TT
TTc
TTTTTc
TTTTT
TT
TTc
TT
TG
H
HHOH
HHO
OHO
HOLOO
LOLL
LLO
OLO
L
T
TL = 10,
TH = 38,
TO = 27,
c2 = –0.0084

Plant growth (water)
• (Hanks, 1974)
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0
0.2
0.4
0.6
0.8
1
0 10 20 30 40 50
GH
H (cm)
( )









<
≤≤
−
−
<
=
,,1
,,
,,0
HH
HHH
HH
HH
HH
TG
H
HL
LH
L
L
H
HL = 20,
HH = 40

0
0.2
0.4
0.6
0.8
1
0 10 20 30 40 50
S
t (d)
0
0.2
0.4
0.6
0.8
1
0 10 20 30 40 50
ΔG0
t (d)
Plant growth
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( ) 0, GHTGG ∆=∆ ( ) ( )[ ]tStSG −=∆ 10
A = 1,
b = 0.4,
t0 = 15
( ) ( )0
1 ttb
e
A
tS −−
+
=

Growth decay due to soil condition
(ICGAB)
( ) SORP /τtt
e −−
( ) ( )
corr
/
0 /, SORP
AeGHTGG tt τ−−
∆=∆
τSO = 180,
Acorr = 2.4875
SF: G ≈ 1 → Acorr

Interactions
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Results and discussion

Parameters
• μT = 20, σT = 4, Tmin = 0, Tmax = 40, ΔT = 1,
NT = 40, I∞ = –3, Imin = 0, Imax = 50, ΔI = 1,
NI = 50, TL = 10, TH = 38, TO = 27,
c2 = –0.0084, HL = 20, HH = 40, b = 0.4, A = 1,
t0 = 15, τSO = 180, Acorr = 2.4875
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Temperature and precipitation
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Plant size (in a year)
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Plant size (for 10 years)
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Simulator
(ICGAB)
https://rawcdn.githack.com/dudung/butiran/master/app/abm_bioeconomy.html

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Summary

Summary
• Simulation of three types of farming, i.e. CF,
OF, and SF, has been conducted using ABM
• SF type shows most promissing result
compared to the other two
• CF and OF depend heavily on the weather
condition (temperature and precipitation)
• CF requires replanting schedule with special
treatment for the soil condition
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Acknowledgments

Acknowledgments
• P3MI ITB in presenting this work
• UB in arranging this event
• DIPI in providing the field trip to meet the
initial problem
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(ICGAB)
Thank you

(ICGAB)
https://osf.io/5axpf/

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