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Bio-Informatics & High
Performance Computing (HPC)
for Realization & Advancement
of Precision Agriculture
Kudang B. Seminar
e-mail: [email protected]
Head of Bio-informatics Engineering Laboratory Fateta IPB
Honorary Member of AFITA
Member of ASICTA
Honorary Member HIPI
Member of PERTETA
The creation and
development of
advanced
information and
computational
techniques for
solving problems
in biology
https://www.osc.edu/press/ohio_supercomputer_center_ralph_regula_s
chool_to_power_choose_ohio_first_bioinformatics
http://www.babraham.ac.uk/our-research/science-
services/bioinformatics/
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The use of super computers and parallel
processing techniques for solving complex
computational problems
1. Fundamental Concepts
"I think the next century will be the century of complexity"
Stephen Hawking (January 2000), The Newton Professor of Physics at Cambridge:
George Rzevski: www.rzevski.net
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http://www.necsi.edu/projects/mclemens/cs_char.gif
What is Complexity?
It consists of a large number of diverse components
engaged in unpredictable interaction (Variety and Uncertainty)
Its global behaviour emerges from the interaction of
local behaviours of its components (Emergence)
It self-organises to accommodate unpredictable external or internal events and therefore its global behaviour is “far from equilibrium” or “at the edge of chaos” (Adaptability and Resilience)
It co-evolves with its environment (Irreversibility)
George Rzevski: www.rzevski.net
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Dramatic Change!
Biology has changed
dramatically and high-
throughput experimental
methods such as produce
masses of data.
Superlinear Grow &
Challenging Problems
The bioinformatics
databases grow
superlinearly!
The masses of data
led to numerous
challenging
bioinformatics
problems &
solutions http://www.benjaminwicks.com/portfolio/
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Big Data Analysis & Optimism Tens of thousands of ESTs (Expressed
Sequence Tags) available for study
Most methods to study message
distributions are low throughput AND
time consuming
“Genomics” necessitates the large scale
study of gene expression
Optimism: Biology is finite…
~30,000 human genes; ~1000 protein superfamilies
…but computers speeds keep increasing => HPC
Future Extension of Bio-informatics
Genotype
Data
Phenotype
Data
Gographical
Indication
Data
Integrated
Data
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Why Integration is needed?
Genotype: genetic constitution of an
individual organism
Phenotype: expressed physical traits of
an individual organism.
Geographical indication (GI): specific
characters (signature) of an individual
organism that correspond to a specific
geographical location or origin.
Relating Genotype & Phenotype Data
Leaf Tuber
Chromosome
DNA
Genotype
data
Phenotype
data
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cDNA Collections (Libraries)
• Various tissues are collected from the plant,
and messages are extracted
Leaf
Messages
Tuber
Messages
Unifying GI,Phenotype,
Genotype Data
Genotype +
Phenotype
Data
Origin
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What about
Precision Agriculture (PA)?
An agricultural system that provides precise
treatments to all agribusiness chain from
upstream (onfarm) to downstream (off farm).
agribusiness
chain
from
Field
To
Table
Complex behavior & attributes
Why is Precision Agriculture hard?
Non-Life
Systems
Life Systems
Simple behavior & attributes
Involve genetics Do not involve genetics
Autonomous Non-autonomous
CNC BDA
(Computer Numerical Control) (Biosistem-Derived Algorithm)
Fuzzy control Genetic algorithm
Photosynthetic algorithm
Immune system algorithm
Expert system
Finite Element System Fractals
Pattern recognition
Artificial Neural Network
Adaptive System
Ant Colony Algorithm
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General Model of
Precision Agriculture
Bio-Process
Control System
Complex
Computation &
Decision Making
Bio-Products
Related Values
Timely &
Conditionally
Valuable Data
Environment
Related Values
Tecnology
for specific
bioproducts
Agro-products
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
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Food Chain/Network
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
Tools for
making
transparency
& precision
work?
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
Tools for Transparency &
Precision Support
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Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
ICT Cloud to Support PA
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.`
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Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
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Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
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Linking production with Consumers
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
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Gerhard Schiefer. 2014. Transparency for Sustainability: Food chain challenge & Future Internet opportunities, AFITA Conference 2014.
Plant Health Monitoring and Control
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Tomato Grading
Grading Technology
Precision Agriculture (Off Farm): Minimizing Loss in Tomato Ketchup Supply Chain
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THE DEVELOPMENT OF IDENTIFICATION SYSTEM AND GENOME ANALYSIS
SINGLE NUCLEOTIDE POLYMORPHISM UNTUK PEMULIAAN
SOYBEAN PLANT
Tim Peneliti:
Dr. Wisnu Ananta Kusuma (Ilmu Komputer, IPB)
Dr. Agus Buono (Ilmu Komputer, IPB)
Dr. Ir. I Made Tasman (BB Biogen)
Habib Rijzaani (BB Biogen)
Mukhlis Hidayat, M.Kom (Matematika, Unsyiah)
Research Contributions
•Creation of superior strains
• Utilization of genomic analysis for
breeding
•Utilization of information
technology to support the analysis of
genomic-based breeding
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Kudang B. Seminar Herry Suhardiyanto
UIJI Seminar, 23-25 July 2011, Ehime University
Dept. of Mechanical & Biosystem Eng. Bogor Agricultural University
The Supervised Multi-Agent Systems for Greenhouse-Based Crop
Industry
A Large Scale Crop Production Plant
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Concurrent Engineering for Environment and Plant Control
USER
U S E R I N T E R F A C E
USER’S PREFERENCE SELECTION MODULE
Modes of
control
Parameters of control
Optimality Criteria
Control Knowledg
e
Supervisory Control Engine
Crop Knowledg
e
Climatic Knowledge
I/O Knowledg
e
Greenhouse Controllers
Greenhouses
Greenhouse Controllers
Greenhouse Controllers
Array of Controller
s
SUPERVISORY AGENT
Supervised
Agents
CONCLUDING REMARKS (1)
The role of bio-informatics & HPC is
becoming very crucial and strategic to the
realization and advancement of precision
agriculture (PA).
intergrating and interelating the knowledge
of genotype, phenotype and GI will be very
useful for formulating and establishing better
paradigms, solutions and tools for better &
smarter agricultural system particularly in
Indonesia
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CONCLUDING REMARKS (2)
Collaborative & interdisciplinary research
can be extended coherently towards
better & competitive agriculture
production through PA & bioinformatics
There have been many applications of
bioinformatics for agriculture, partcularly
food production but there are more
challenging research & applications due to
biosystem diversity & complexity
CONCLUDING REMARKS
CONCLUDING REMARKS (3)
The applications of bioinformatics heavily
rely on the advancement of HPC (High
Performance Computing Technology) &
that of superintelligent computations.
The development & use of bio-derived
computational algorithms will be more
aggresive due to nature of bio-systems.
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THANK YOU