India-Japan Joint Research Laboratory Programme
2015 SICORP Collaborative Hub for International Research Program between
Japan and India

Data Science-based Farming Support System for
Sustainable Crop Production under ClimaticChangePIThe University of Tokyo
Indian Institute of Technology Hyderabad

Seishi Ninomiya
Uday Desai

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Background and Objectives of the Project• Drastic increase of food demand by growing populationand increase of middle class people in India• 80% of Indian arable land is in semi-arid areao Total arable land is the 2nd largest in the world
o Vulnerable under climatic change and risk for stable productivity isincreasingo 50 million tons of grain yield reduction took place in India bydrought. The amount is equivalent to 20% of total annual grain tradein the worldo Chronic water shortage and pests/diseases
o 50% of the population are farmers and improvement of theirbenefits is an urgent and critical issue3

Current issues in semi-arid farmingo Decision support information for optimal and effective
crop managements is very poor
• chemical applications and water usageo Breeding for climatic change is delayed• Drought tolerance, pest tolerance, high yield, high qualityo Knowledge transfer to each farmer is rather poor
• Personalized information is needed• Monitoring each farmer is necessary5Research objectives• Improvements of cropping in semiarid area
accelerated by information sciences andtechnologies
o To provide decision support systems particularly for bettercrop managements in semi-arid area such as efficientwater useo To accelerate crop breeding based on data science forsemi-arid area under climatic changeo To provide a method for efficient and effective
personalized knowledge transfer to agricultural
stakeholders
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Data Science-based Farming Support System for Sustainable Crop Production under Climatic Change
Establishment of bilateral Joint Laboratory for research to support sufficient and environmentallyfriendly production of safe and quality crops under climatic changeFarmers & agriculture stakeholders••••

Efficient Knowledge Transfer

Optimal Crop Management

High Performance Breeding

Mobile based systems
JP,IN
Personalized knowledge transfer IN
Diagnostic knowledge-bases JP,IN
Next generation farm KIOSKIN• Water management
IN,JP• Pest & disease management IN• Weather-based crop managementIN• High-throughput phenotyping JP,IN• Genomic selection modelJP,IN• G X E X M modelling
JP

Agricultural Applications for Farmer & Agriculture Stakeholder
IT platform for Big Data based Smart Farming Supports
IoT/ Field Sensors• IoT based field sensor nodedevelopment
IN,JP• Crowd sensingIN• Drone sensing using IoT
JP,IN• IoT Backhaul
IN

AI/Deep Learning

Database for Big Data••••

Data modelingJP
Data integration platforms IN,JP
Utilization of DIAS
JPAPI design
IN,JP

•••
•
•

Big data analytics
Deep Learning
Image/video analysis
Data fusionDecision support engines

IN,JPIN,JPJP, ININ
JP,IN

Research Group• The University of Tokyoo Graduate School f Agriculture and Life Scienceso Graduate School of Information Science and Technology
o Institute of Industrial Science• Indian Institute of Technology Hyderabad• Indian Institute of Technology Bombay (IITB)• Proferssor Jayashankar Telangana State Agricultural
University (PJTSAU)• International Institute of Information Technology
Hyderabad (IIITH)
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Bilateral research project Geo-ICT and Sensor Network based Decision
Support Systems in Agriculture and Environment Assessment （2008～2011）o Strategic Japanese-Indian Cooperative Programme on “Multidisciplinary
Research Field, which combines Information and Communications Technologywith Other Fields supported by JST and DSTo Team• National Agriculture and Food Research Organization (NARO) and UT• IITB and ANGRAU

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Test beds in Hyderabad
Acharya N G Ranga Agricultural University, Hyderabad

Interaction with farmers

Key factors in the project under synergy ofinformation sciences and agricultural sciences• Element technologies
ooooooDevelopment of field sensors usable under severe environmental condition in semi-arid India
Monitoring of environments
High throughput phenotyping
Crowd sensing
Big data and database technologies
Models for prediction and optimization, artificial intelligence• Optimal water usage in croppingo Crop status monitoring and crop modeling• Acceleration of breedingo From empirical breeding to designed breedingo Prediction of crop performance by G X E modeling• Identification of individual farmers’ issues and efficient and appropriate
knowledge transfer to each farmero Mobile tools

12Big Data collection & utilization for crop production by multi-layer IOT
DIASSatellites
Drones

Big data in Cloud

National statistics
Legacy data
Back-end servers

Machinery

Ground sensors
Crowd sensing

Low cost fully autonomous soil moisture sensors• Data taken by SenSprout pro is uploaded to cloud server

Server(Cloud)Uploads data toservers

インドでも試験中

Data
uploaderzigbeesensor

利用者
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3D reconstruction of fields byCameradroneimages
Position#15

3D reconstruction of fields by drone images

Estimation of canopy coverage of paddy rice

Plant Coverage Ratio

Days after transplanting

R2=0.99, Overall

Time and date17

Detection of heading of sorghum by drone images

Unpublished, Collaborated with CSIRO, Australia18

Acceleration of breeding by genomic selection

Selection byobservations

Field tests
Watanabe et al. (2005)
Ann Bot. 95:1131

Prediction by DNA information + assumed environmental condition？

Selection bypredictions

Next Generation Sequencer（NGS）

Selection without cultivation

stnd
1 stage to 2 stage
1st Stage (2016-2021) JL
Research & development
Practical test beds
Training and education

2nd Stage (2021-2026) JL.
Research & development
Societal implementation
Training and education

Scientific Impacts

Japan Side/JST

Tight collaboration among academia,governments and private sectors••Japan Side/JST• University of Tokyo, NARO,
Nagoya U., Chubu U., Kyoto U.,
Hokkaido U., AIST, NII, etc•••

India Side/DST• IITH, IITB, IIITH, PJTSAU,ICRISAT, ICAR,Social Impacts•University of Tokyo
Grad. Schl. Agric. Life Sci.
Grad. Schl. Engineering
Grad. Schl. Info. Sci. Tech.
Inst. Industrial Sci.

India Side/DST••••IIT Hyderabad
IIT Bombay
IIIT Hyderabad
PJTSAU

Social Impacts
••••
•
•

Stable crop supply
Higher productivity
Efficient water usage
Low environmental impact
Safety food
Farmers' benefits

Societal Implementations•••

DOA/MAFF, Extension services
TCS, INFOSYS, WIPRO, ITC,Fujitsu, Kubota, NEC, NTT, KDDI, Soft
Bank, etc.

•••••••

Acceleration of bilateralmulti-disciplinary researchand education
IOT technology for farming
Analytics on crop related
data
Designed cultivation
Designed breeding
Efficient use andenrichment of DIAS

Stable food supply
Higher productivity
Better water usage
efficiency
Quality and safety
Low environmental impact
Higher income of farmers

Expected impacts of the project• Exchange of young students/scientist of two countries
o To understand each end and to promote the next generation international
collaboration• Scientific Impactso Acceleration of bilateral multi-disciplinary research and educationo IOT technology for farmingo Analytics on crop related datao Designed cultivation and cultivation control
o Designed breedingo Efficient use and enrichment of DIAS

• Social Impacts
o Stable food supplyo Higher productivity
o Better water usage efficiency
o Quality and safetyo Low environmental impacto Higher income of farmers
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Kick-off Meeting at IITH in December 201622

Thank you very much
For a fruitful project23