Keynote presentation for the opening of the academic year at CIHEAM institute for Mediterranean agricultural research in Zaragoza. It is about how IoT and Big Data are transforming Agriculture in Europe and what the main challenges are: governance, business models and open infrastructures. This is illustrated from several use cases in the Internet of Food and Farm 2020 (IoF2020) project.

1. Bridging the skills gap
How IoT and Big Data are transforming Agriculture in Europe
Sjaak Wolfert, CIHEAM, Zaragoza, 25 Sep. 2017

2. Wageningen University & Research: Two Partners
Wageningen University & Wageningen Research

3. Wageningen University & Research
 Academic research & education, and applied research
 5,800 employees (5,100 fte)
 >10,000 students (>125 countries)
 > 30 locations in NL, China, Chile, Ethiopia & Saudi Arabia
 Turnover about € 650 million
 Number 1 Agricultural University for the 4th year in a row
(National Taiwan Ranking)
To explore the potential of nature to improve the quality of life

4. Advancements in Farming
BIG
DATA
CONTROL
SENSING
& MONITORING
ANALYSIS
& PLANNING
SMART
SMART
SMART

5. Involving entire supply chain and beyond
Smart Farming
Smart Logistics
tracking & tracing
Domotics Health
Fitness/Well-being

6. INTERNET OF FOOD & FARM 2020
19 USE CASES IN 5 TRIALS
6
MEAT
ARABLE
VEGETABLES
FRUITS
DAIRY

7. IOF2020 IN BRIEF
7
16
COUNTRIES
4 YEARS
Start = January
2017
€35 MILLION
BUDGET
(€30 million co-funded
under EU H2020
programme)
71 PARTNERS
ORGANISATIONS

8. Real-time monitoring and control of water supply and crop protection of table
grapes and predicting shelf life
FRESH TABLE GRAPES CHAIN
Yield +15% | Crop value +10% | Water usage -20% | Shelf life +20%
Harvest rejection -20% | Post-harvest rejection -10%

9. SENSING AND MONITORING

10. Management Information Layer
Operations Execution Layer
Production Control Layer
Physical Object Layer
Actuate Sense
Analyse Fertiliser
Pesticide Need
Plan Crop
Protection
Farm Control
Monitor Crop
Growth and
Postharvest
Predict Yield (only
for crop growth)
Plan
Harvesting
Definition
Management
Detailed
Scheduling
Execution
Management
Data
Collection
Data Analysis
Control Spraying
Machine
Sense Crop
Growth
Control irrigation
system
Fertilisers and
Pesticides Growing Crops
Irrigation
System
FieldSpraying
machine
Farmer Agronomic
Engineer
machine settings
task instructions field sensor dataIrrigation system data
machine requirements
task
definition
aggregated data
Post Harvest
System
Weather
station
Sense
Weather
Control Post
Harvest
task instructions
Sense Chemical and
Physical Parameters
postharvest system
data

11. Use case Partners

12. Value chain and quality innovation by mid-tech horticulture greenhouses
CHAIN-INTEGRATED
GREENHOUSE PRODUCTION

13. 13

14.  Governance
● power relations, new players, etc.
 Business models
● fair share, new opportunities
 Infrastructure
● open versus closed
...which are often intertwined!
Implications and challenges

15. Redefining Industry Boundaries
3. Smart, connected product
+
+
+
2. Smart Product
1. Product
Adapted from: Porter and Heppelmann, Harvard Business Review, 2014

16. 5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system
Adapted from: Porter and Heppelmann, Harvard Business Review, 2014

17. 5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system
Your company

18. 5. System of systems
farm
management
system
farm
equipment
system
weather
data
system
irrigation
system
seed
optimizing
system
field
sensors
irrigation
nodes
irrigation
application
seed
optimization
application
farm
performance
database
seed
database
weather data
application
weather
forecasts
weather
maps
rain, humidity,
temperature sensors
farm
equipment
system
planters
tillers
combine
harvesters
4. Product system
Your company
Farmer:
How many platforms must
I use?
Developer:
On how many platforms
should I offer my
solution?
Platform owner:
How many connections do
I need to maintain?

19. The battlefield of IoT, Big Data and Farming
Tech
Companies
Tech
Start-ups
Tech
Start-ups
Farm
Farm
Farm
Farm
Farming
Agri-
Business
Ag Tech
Farm
Venture
Capitalists
Data
Start-ups
Data
Start-ups
Farm
Source: Wolfert et al. (2017), Big Data and Smart Farming, Ag. Systems 153

20. Ag Start-ups in the USA
20

21. Collaborative infrastructure
Scenario: get expert advice for spraying to
handle disease on tomatoes
State AuthorityFranz Farmer Ed Expert
Spraying
(follow advice)
Create
Advice
Approval
Request
Advice
CollaborativeBusinessProcess
1
2
3
FIspace App
‘Weather
Information’
FIspace App
‘Spraying
Expert Advice’
FIspace App
‘Spraying
Certification’
Back-EndSystems
Farm
Management
Systems
Sensor Network
in the Greenhouse
Agronomist
Expert System
Regulations &
Approval
System
product type, etc.
sensor data
(access details)
suggested
chemical
advice details
certification
details
21

22. Governance and business issues
22
Code of Conduct

23. Basic data sales
How does it work?
- A ‘box’ collects all data
- Data is stored in a cloud
- Data is being marketed/invested
- Farmer gets a share of profit
“Farmers think their trust is violated”
Their data goes to multinationals that promise
high future yields based on big data,
while farmers have to pay for everything

24. Value Chain Integration: FieldScripts
PRESCRIPTIVE FARMING
based on PRECISION
AGRICTULTURE

25. Wrap-up and conclusions
 Agri-Food chains become more
technology/data-driven
 Probably causes major shifts in
roles and power relations among
different (new) players in agri-food
chain networks
 Governance and Business Models
are key issues
 There is a need for a facilitating
open infrastructure (scenario 2)
Two extreme scenarios:
1. Strong integrated supply chain
2. Open collaboration network
Reality somewhere in between!

26. ECOSYSTEM & COLLABORATION SPACE
ProjectCoordination&
Management
Our Approach...
Trials/Use Cases: Knowledge & App development
Lean multi-actor approach
3. EVALUATION
1. CO-DESIGN
2. IMPLEMENTATION
P1
P2
LARGE
SCALE
P3
Technical Integration
Business Modelling &
Governance
Ecosystem Development

27. Thanks for your
attention
sjaak.wolfert@wur.nl
nl.linkedin.com/in/sjaakwolfert/
Twitter: @sjaakwolfert
http://www.slideshare.net/SjaakWolfert
www.IoF2020.eu
27