This was presented in Jammu Conference

1. Artificial Intelligence for
Food & Environment Sustainability
Prof. Nazir A Ganai
Vice Chancellor, SKUAST-Kashmir
The Indian Ecological Society International Conference 2022

2. Indian Agriculture: Key Strengths
• Largest source of livelihood
• 23% of national GDP
• 70% of rural households depend on agriculture
• 58% population engaged in agriculture
Despite this…
(FAO, 2022)

3. Food Insecurity Prevails
43 crore people affected
31.6% (2019)
52 crore people affected
38.4 % (2021)
120 million tons of
grain in storage
Despite having
(FAO et al., 2021)

4. Agricultural Land in India
(Million Hectare)
180.88
179.86
179.2
179.4
179.6
179.8
180
180.2
180.4
180.6
180.8
181
2018 2050
Agricultural Land

5. Kashmir
Agricultural land decreasing @19675 ha/yr.
Greater Kashmir, 2021

6. CURRENT
1.30 billion
2nd most populous country
INDIA
2050
1.64 billion
2nd most populous country
G r ow i n g
Po p u l at i o n
(UNO, 2019)

7. • ¼ world’s hungry people in India
• >190 million undernourished people
INDIA RANKS:
• Global Food Security Index: 76th
(among 113 countries)
• Global Hunger Index: 103rd
(among 119 countries)
Image credits: Pixabay
(von Grebmer et al., 2013)

8. • 20% global greenhouse gas emissions
• Inefficient burning of fuels: Pollution
• Health Hazard
Environment Degradation
(Yale School of Environment, 2018)
(Mousavi-Avval et al., 2018)

9. Land Degradation in India
(Million Hectare)
94.53
97.85
92
93
94
95
96
97
98
99
2003-05 2018-19
Degraded Land

10. Developed
Countries
One Step
Ahead

11. 90
3
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Israel India
Water Recycling (%)
Water Recycling Non Recycled

12. 4.4X
Milk Production (kg)
(India v/s ISRAEL)
0
5
10
15
20
25
30
35
Israel India
33
7.15
Milk/Cow/Day

13. 0
50
100
150
200
250
300
350
Israel India
Production
Tomato production Citrus Fruits

14. 2
40
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Israel India
Post Harvest losses(%)
Post Harvest Loss
Hegazy, 2016

15. Important Reasons
Resource
intensive
agriculture
Regionally biased
Increased stress
on water
resources
Desertification
and land
degradation
Uncertainty and
risks
Increasing in
complexity
(industry and
urbanization)
Poor market
discovery
Lack of open
agriculture data &
standards
Poor access to
credit and
information
Poor
mechanization of
farms
Pest infestation
and diseases
Changing crop
patterns
Poor resource
utilization
Wastage in supply
chain
Exploitation of
farmers by
intermediaries
(UNO, 2022)

16. • 82% : small & marginal
• Average Land hold: 1.2 hectares
• 20% : landless
Special challenge
(HLPE, 2013)
Image credits: Pixabay
Farmers’ Status:

17. Sustainability can be achieved
By ensuring
Affordability----- Availability-----Quality----- Safety
of food as well as
----Sensitivity-----
towards the environment

18. Dire Need for
Intensification of Agriculture
For efficient and optimum resource utilization and loss minimization

19. The challenges faced by agriculture are outliving the
existing solutions because alone they are
outdated or ineffective

20. Use of
Artificial Intelligence
for
Precision Agriculture
to ensure
Food & Environment Sustainability
A Potential Solution

21. AI to tackle challenges in Agriculture
(Talaviya et al., 2020)
By ensuring Affordability, Availability, Quality, Safety, Sensitivity

22. 1. Monitoring
• Crop/ Soil
• Animal health and production
• Farm profits and losses
• Farm Surveillance
• Ecosystems
(Neethirajan, 2020)

23. Hair (lactate, organic
compounds) Ear tag (Accelerometer,
temperature sensors
Environment
(Respiration rate,
volatile organic
compounds e.g., Phenol,
p-cresol, emissions etc.)
Saliva (Cortisol, miRNA,
lactate, hormones)
Halter/ Neck Collar
(humidity, sound sensor,
pressure, temperature,
Accelerometer sensor)
Sweat (tattoo sensor,
textile sensor,
cortisol, lactate,
miRNA, biomarkers)
Holter (Heart rate
(HR), HR variability)
Leg (Pedometer,
Accelerometer)
Rumen (pH sensor,
temp, Accelerometer)
Tail (Accelerometer)
Vagina (Temperature,
pH, heat)
Computer Vision (identify,
detect, health)
Various sensors for animal monitoring
Example 1:

24. Plant health
monitoring
Weed detection
Computer vision:
identification
Farm
surveillance
Yield mapping
Remote monitoring
Carbon dioxide
emissions
Temperature
Sunlight
Humidity
Soil moisture
Plant Monitoring
Energy usage
Farm emissions
Smart Scouting:
stress detection
Example 2:

25. Monitoring All
Aspects of Food
Gas (Ethylene)
Ripeness
Leak
Microbial
Spoilage
Humidity
Time-Temperature
Sensors for Monitoring Packaged Food
Computer Vision for Nutrition
Monitoring
ValidateMyMeal
24g 9g 7g 4g
Fat Protein Carbs Fiber
Spanish
Egg
Olive oil
Tomato
Your Lunch
Example 3:

26. Forecasts
and
Predictions
Wildlife
migratory
patterns Yield and
production
Genetic
merits
Demand &
Supply of
renewable
energy
Market
changes
Future
prices
Outbreaks
Pests and
diseases
Plant &
animal
requirement
Environment
Degradation
2. Predictive
Analytics
(Liakos et al., 2018)

27. Averting Natural Disasters
By leveraging remotely sensed geospatial data from satellites
Example: Google's flood forecast

28. 3. Decision Making
Big Data Decision
Data Analytics
Trade route &
shipping
Irrigation
Feed and
fodder
Soil nutrition
levels
Sowing time
Artificial
insemination
Selection &
culling
Sale &
procurement
Conserve &
optimize
resources
Optimize
energy
(Somali et al., 2020)
Optimization of:

29. 4. Automation
Using agribots, IoT & smart farm appliances
--- labor free --- hyper efficient --- Fast --- Accurate --- Hygienic --- Resource effective ----
(Adetunji et al., 2022)

30. Remote control
Harvesting
Weed control
Mowing
Seeding
Spraying
Sorting and smart packaging
Livestock tracking and monitoring
Irrigation
Health scanning
Surgeries in animals
Optimization of energy and resources
Robotic Tasks
(Saiful et al., 2020)
Example:

31. AI as a Change Agent
• Help achieve 79% sustainable development goals
• Greenhouse gas emissions: ↓1.5 – 4.0% (2030)
• Energy usage: ↓ 2.2% (2030)
• Self-driving tractors ↑50% speed of farm work
(Vinuesa et al, 2020)

32. Food
Security
30%
Yield Post Harvest Loss
30-
(Mishra and Panday, 2021)
Artificial
Intelligence

33. Economic Improvement
(Markets and Markets Report, 2019)
• India’s income by 2035: ↑15%
• Global dairy farming: from $1.9 to $8 billion (2023)
• AI market: $ 1.0 (2020) to $4.0 billion (2026)

34. Popularizing AI in India
Driven by
• Low data cost
• Increasing smartphone
penetration
Smartphones and
internet: popularize AI
among rural and
marginalized farmers
(Mahindru, 2019)
KANTAR IMRB I-Cube Report (2017,2018)

35. Major Areas of Technology Application in India
Data backed
credit risk
assessment
Personalized
mobile based
decision support
systems
Tech-enabled
agri-extension
workers
Precision
farming using
IoT & remote
sensing data
Promotion of
innovations
Technology
infrastructure
E-price
discovery &
e-marketing
Track & trace
through
supply chain

36. Block chain for Improving Agriculture in
India
Overseeing Farm
Inventory
Greater Accountability
for Multinationals
Enhancing Agricultural
Supply Chains
Modernizing Farm
Management Software
AgTech IoT
Optimization
Fair Pricing
Agricultural
Subsidies Oversight
Community-
Sponsored Agriculture
Mobile Remittance
for Small Farmers
Incentivizing
Sustainable Practices
(FAO, 2019)

37. NITI Aayog’s National strategy on AI
Promote applied
research
• Focus on creation of
commercializable
products (COREs and
ICTAIs)
Guide innovation
• ‘Moonshot
Challenges’ to guide
research and start-up
ecosystems to solve
for most pressing
government concerns
Facilitate application
• Skilling and
education of the
workforce Cloud
based AI hardware
infrastructure
(AIRAWAT)
(Mahindru, 2019)

38. NITI Aayog: initiatives
and policies
• Mobile based recommender systems and expert systems
• AI based automatic grading & sorting for vegetables and fruits
• AI auto-translation to Indian languages
• Compute infrastructure:
• Nationalized domain specific annotated data sets
• Improved access for existing data
• Domain specific expertise to design solutions
• AIRAWAT cloud compute platform for developers to train
algorithms & host large data sets
• Application focused research institutes for inter-sectoral
linkages

39. Some Other Endeavors
• National-level schemes for data digitization
• Pradhan Mantri Fasal Bima Yojana: using remote sensing imagery, AI
and modeling tools to reduce claim settlement times
• 20 million farmers involved

40. EA For Digital Agriculture
• India Digital Ecosystem of Agriculture (IDEA) under Digital Agriculture Mission
• AgriStack / National Agri Data Stack :
• Collection of technology-based interventions in agriculture
• Primary data layer for agri-focussed, data driven solutions with
Unified Farmer Service Interface
• Implementation: Public-Private Partnership (PPP)
(IBEF, 2022)

41. Digital Agriculture Mission
(2021–2025)
• Support and accelerate projects based on
new technologies
• AI, blockchain, GIS, drones, robots etc …
Implementation in J&K:
• Underway (Steering committee formed)
(Beriya, 2022)

42. • 30% increase in Yield
• Good Harvest
• Better Financial
Returns
> 3,000 farmers
ICRISAT-Microsoft
Partnership
Sowing App
Success Story of AI in India

43. Applications
Of Digital
Agriculture
Gather, visualize and assess crop and soil health
conditions at all stages of production,
Convenient and cost-effective
Rapidly identify and deal with challenges through
real-time actionable insights
Tamper-proof and precise data
Quick and secure transactions, and food tracking

44. Implementation of Digital Agriculture In India
Low-cost technology Portable hardware
Academic support
Renting and sharing
platforms

45. SKUAST-Kashmir
India’s 1st Innovation Driven University
N o t e w o r t h y I n n o v a t i o n s

46. $mart Sheep Breede₹©
© Hamadani and Ganai
AI and IoT based Decision Support
System (Web & Android App) for
farm automation, real time decision
support, e-commerce and more
(Hamadani and Ganai, 2021)
 Increases Precision
 Decreases Labour
 Increases Production
1. Animal Sciences:

47. Weather Alerts
& Forecasting
Disease & Pest
Prediction
Macro & Micro
Soil Health Test
Smart Irrigation Plant Experts
Apple Decision Support System
(Bhat, 2021)
2. Agricultural Sciences:

48. Artificial intelligence is the next big
thing in agriculture which can
potentially lead India towards food
and environment sustainability
Conclusion

49. Farmers have relied on fate so far.
AI can help them stay lucky!
Thank You