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European challenges for the agri-food system:
implications for research
Krijn J. Poppe AISA, Bolzano, Italy
Wageningen UR February 2018
Wageningen University & Research
 Academic research & education, and applied research
 5,800 employees (5,100 fte)
 >10,000 students (>125 countries)
 Several locations
 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
Challenges for EU Agri-Food and implications for research
Krijn J. Poppe
 Business economist, EUR 1981
 Chief Policy Analyst Wageningen Economic Research
 Rli – Council for the Environment & Infrastructure:
member of the council (1 day / wk)
 Fellow and former Secretary-General of the EAAE
● Involved in its journal management (ERAE, EuroChoices)
 Member South Holland Council for Environmental Advise
 Member of the Governing Board of SKAL
 EU Projects; SCAR-AKIS 1-3 and Chair Experts Food2030
Content
 Societal challenges and innovation areas
 Need for a food system approach
 The role of ICT – and why now
 Changes in our AKIS
 Key innovation challenges
 Implications for public policy: CAP and FP9
Five major challenges
 Food and nutrition security and safety
 Climate change and water & energy use
 Reducing ecological impacts (biodiversity)
 Healthy diet for a lifelong healthy lifestyle
 Inequality
Five major innovation areas
 Genetics
 Digitalisation and big data
 Energy and bio-based transitions
 Redesigning the food chain
 Social innovations
Five misunderstandings
 ‘There is a crisis in agriculture’
 ‘It is wrong for the organisation of
the food chain to be so industrialised’
 ‘Agriculture is the main solution
for rural areas’
 ‘International trade is harmful’
 ‘The CAP is expensive and leads
to overproduction’
Food chain: 2 weak spots – opportunity?
Input industriesFarmerFood processorConsumer Retail
• Public health issues –
obesity, Diabetes-2 etc.
• Climate change asks for
changes in diet
• Strong structural change
• Environmental costs
need to be internalised
• Climate change (GHG)
strengthens this
Is it coincidence that these 2 are the weakest groups?
Are these issues business opportunities / market failure?
Or system failure and lack of transformative capacity?
The role of ICT – and why now?
Based on work with WUR team (Sjaak Wolfert, Cor Verdouw, Lan Ge, Marc
Jeroen Bogaardt, Jan Willem Kruize and others)
tijd
Mate van verspreiding
van technologische revolutie
Installatie periode
Volgende
golf
Uitrol periode
Draai-
punt
INDRINGER
EXTASE
SYNERGIE
RIJPHEID
Door-
braak
Werkeloosheid
Stilstand oude bedrijfstakken
Kapitaal zoekt nieuwe techniek
Financiele bubble
Onevenwichtigheden
Polarisatie arm en rijk
Gouden eeuw
Coherente groei
Toenemende externalities
Techniek bereikt grenzen
Marktverzadiging
Teleurstelling en gemakzucht
Institutionele
innovatie
Naar Perez, 2002
Crash
2008
1929
1893
1847
1797
time
Degree of diffusion of the
technological revoluton
Installation period
Next
wave
Deployment
period
Turning
point
IRRUPTION
FRENZY
SYNERGY
MATURITY
Big Bang
Unemployment
Decline of old industries
Capital searches new techniques
Financial bubble
Decoupling in the system
Polarisation poor and rich
Golden age
Coherent growth
Increasing externalities
Last products & industries
Market saturation
Disappointment vs
complacency
Crash
2008
1929
1893
1847
1797
Institutional
innovation
Based on Perez, 2002
The opportunity for green growth
1971 chip ICT
1908 car, oil, mass production
1875 steel
1829 steam, railways
1771 water, textiles
Disruptive ICT Trends:
 Mobile/Cloud Computing – smart phones, wearables,
incl. sensors
 Internet of Things – everything gets connected in the
internet (virtualisation, M2M, autonomous devices)
 Location-based monitoring - satellite and remote sensing
technology, geo information, drones, etc.
 Social media - Facebook, Twitter, Wiki, etc.
 Block Chain – Tracing & Tracking, Contracts.
Big Data - Web of Data, Linked Open Data, Big data
algorithms
High Potential for unprecedented innovations!
everywhere
anything
anywhere
everybody
Drones, Big Data and
Agriculture 13
IoT in Smart Farming
cloud-based event
and data
management
smart sensing
& monitoring
smart analysis
& planning
smart control
Virtual Box
Location A Location B
Location
& State
update
Location &
State
update Location
& State
update
IoT in Agri-Food Supply Chains
14
Drones, Big Data and
IoT and the consumer
15
Drones, Big Data and Agriculture
Source: Hisense.com
Smart Farming
Smart Logistics
tracking/& tracing
Domotics Health Fitness/Well-being
Towards smart autonomous objects
Source: Deloitte (2014), IT Trends en Innovatie Survey
Tracking &
Tracing
Monitoring
I am thirsty: water
me within 1 hour!
I am product X at
locatie L of Z
My vaselife is
optimal at a
temperature of
4,3 °C.
I am too warm:
lower the
temperature by
3 °C
Event
Management
I am too warm: I lower
the cooling of my truck
X by 2 °C.
I don’t want to
stand besides
that banana!
I am thirsty!
I am warm!
Optimalisation
Autonomy
Grand challenges: tomorrow’s business
Input industries
Farmer
Food processor Retail / consumerSoftware
provider
Logistic solu-
tion providers
Collaboration and Data Exchange is needed!
Food & nutrition
security
Climate
change
Healthy diet
for a healthy
life
Environmental
issues
There is a need for
ABCDEFs:
Agri-Business
Collaboration & Data
Exchange Facilities
• Large organisations have
gone digital, with ERP
systems
• But between organisations
(especially with SMEs) data
exchange and
interoperability is still poor
• ABCDEF platforms help
• Our focus: data governance
law & regulation
innovation
geographic
cluster
horizontal
fulfillment
Vertical
Chain organisation changes (©Gereffi et al., 2005)
inputsEndproduct
PRICE
Shops
Complete
Integration
Lead
company
Lead
company
Turnkey
supplier
Relational
supplier
Market Modular Relational Captive Hierarchy
Low Degree of explicit coordination and power asymmetry High
Lead
company
Farmers
Europe towards
2030
3 scenarios to
explore the future
of EU agriculture +
implications for
Agricultural
Knowledge and
Innovation
Systems
 HighTech: strong influence new technology owned by
multinationals. Driverless tractors, contract farming and a
rural exodus. US of Europe. Rich society with inequality.
Sustainability issues solved. Bio-boom scenario.
 Self-organisation: Europe of regions where new ICT
technologies with disruptive business models lead to self-
organisation, bottom-up democracy, short-supply chains,
multi-functional agriculture. European institutions are weak,
regions and cities rule. Inequalities between regions,
depending on endowments.
 Collapse: Big climate change effects, mass-migration and
political turbulence leads to a collapse of institutions and
European integration. Regional and local communities look
for self-sufficiency. Bio-scarcity and labour intensive
agriculture. Technology development becomes dependent on
science in China, India, Brazil.
Scenario 1: High Tech
multinationals, clean technology, strong EU
(c) Toshiba
Scenario 2: Self organisation
new business models, regions and cities rule, diversify
Tempelhof, Berlin (c) Kasper Jensen
Scenario 3: Collapse
climate change, migration, breaking up of the EU
Effects on AKIS
(Ag. Knowledge & Innovation System)
 HighTech: International players in agribusiness, direct
access to best universities for own labs and extension
programs. EU-Public Private Partnerships. Product and
technology oriented. Upskilling of specialised AKIS staff.
Small role regional government.
 Self-organisation: Regional orientation, food and non-
food. New (local) actors like NGO and cities. EU: connect
the dots. Multi-skills of AKIS staff.
 Collapse: Local orientation, food oriented. Problems of
soil and water are main focus. Fragmentation of AKIS,
strong emphasis on extension. Donors play a big role,
fundamental research is done in China or India.
Emphasis on basic skills of AKIS staff.
Key
Innovation
Challenges
Misunderstandings in social debate: one
as a solution of everything, -where??
Productivism paradigm
 Focus on more supply
 Calories for the world
 Eco-efficiency per kg
Sufficiency paradigm
 Food is more than calories
 Changes in menu needed
for sustainability
 Local effects, emissions
per ha count too.
@SCAR 3rd foresight
• Put fewer forks on the table –
Thomas Maltus (1798, An
essay on the principles of
population)
• Bake a bigger pie - Marquis
de Condorcet
• Teach everyone better table
manners – William Godwin
© Warren Belasco: Meals to come – a
history of the future of food
INPUT
INDUSTRY
FOOD
PROCESSING
FARMERS ICT
RETAIL
& OUT
of
HOME,
Food
Procesng
Health
sector
+ Cities
CONSU-
MERS
Less animal
based:
• Reduce GHG cattle
• Improve sustainb.
pigs and poultry
• New (lab) meat
and feed (insects,
algae etc.)
More plant based:
• Improve soil management
• Cope with climate change (water)
• Less chemicals, more biodiversity
• Improve factory farming
CIRCULAR PRINCIPLES
• Less waste
• More resource efficiency
• Close P-cycle
Help
Consumers
Change:
* personalised
nutrition
Green,
Healthy
Cities
Peri-urban
multifunctional
farms with short
supply chains
Help Empty
Rural Regions
Climate
change
Healthy diet
for a
healthy life
Transforming the CAP into a
Common Agricultural and Food Policy
Five examples of a Common Agricultural
and Food Policy
 Make our diets more healthy and sustainable
with a price that factors in true costs
 Incorporate climate change agreements
in farm decisions
 Align incentives in the food chain
 Install smart instruments for environmental
management
 Support disruptive innovation in the
urban food system and bio-economy
Transforming the CAP into a CAFP
Pillar A
INCOME
SUPPORT
Pillar B
ECOSYSTEM
SERVICES
Pillar C
RURAL
DEVELOPMENT
Pillar D
FOOD
& HEALTH
Pillar E
MONITORING
& RESEARCH
Pillar C: rural development
Innovate for
competitiveness
Pillar E: monitoring reflection and research
By the deployment of reflective citizen science
in support of adaptive governance
Food2030: 4 themes ?
EU’s Framework Programme #9 (FP 9)
Thanks for your
attention
krijn.poppe@wur.nl
www.wur.nl

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Challenges for EU Agri-Food and implications for research

  • 1. European challenges for the agri-food system: implications for research Krijn J. Poppe AISA, Bolzano, Italy Wageningen UR February 2018
  • 2. Wageningen University & Research  Academic research & education, and applied research  5,800 employees (5,100 fte)  >10,000 students (>125 countries)  Several locations  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. Krijn J. Poppe  Business economist, EUR 1981  Chief Policy Analyst Wageningen Economic Research  Rli – Council for the Environment & Infrastructure: member of the council (1 day / wk)  Fellow and former Secretary-General of the EAAE ● Involved in its journal management (ERAE, EuroChoices)  Member South Holland Council for Environmental Advise  Member of the Governing Board of SKAL  EU Projects; SCAR-AKIS 1-3 and Chair Experts Food2030
  • 5. Content  Societal challenges and innovation areas  Need for a food system approach  The role of ICT – and why now  Changes in our AKIS  Key innovation challenges  Implications for public policy: CAP and FP9
  • 6. Five major challenges  Food and nutrition security and safety  Climate change and water & energy use  Reducing ecological impacts (biodiversity)  Healthy diet for a lifelong healthy lifestyle  Inequality
  • 7. Five major innovation areas  Genetics  Digitalisation and big data  Energy and bio-based transitions  Redesigning the food chain  Social innovations
  • 8. Five misunderstandings  ‘There is a crisis in agriculture’  ‘It is wrong for the organisation of the food chain to be so industrialised’  ‘Agriculture is the main solution for rural areas’  ‘International trade is harmful’  ‘The CAP is expensive and leads to overproduction’
  • 9. Food chain: 2 weak spots – opportunity? Input industriesFarmerFood processorConsumer Retail • Public health issues – obesity, Diabetes-2 etc. • Climate change asks for changes in diet • Strong structural change • Environmental costs need to be internalised • Climate change (GHG) strengthens this Is it coincidence that these 2 are the weakest groups? Are these issues business opportunities / market failure? Or system failure and lack of transformative capacity?
  • 10. The role of ICT – and why now? Based on work with WUR team (Sjaak Wolfert, Cor Verdouw, Lan Ge, Marc Jeroen Bogaardt, Jan Willem Kruize and others)
  • 11. tijd Mate van verspreiding van technologische revolutie Installatie periode Volgende golf Uitrol periode Draai- punt INDRINGER EXTASE SYNERGIE RIJPHEID Door- braak Werkeloosheid Stilstand oude bedrijfstakken Kapitaal zoekt nieuwe techniek Financiele bubble Onevenwichtigheden Polarisatie arm en rijk Gouden eeuw Coherente groei Toenemende externalities Techniek bereikt grenzen Marktverzadiging Teleurstelling en gemakzucht Institutionele innovatie Naar Perez, 2002 Crash 2008 1929 1893 1847 1797 time Degree of diffusion of the technological revoluton Installation period Next wave Deployment period Turning point IRRUPTION FRENZY SYNERGY MATURITY Big Bang Unemployment Decline of old industries Capital searches new techniques Financial bubble Decoupling in the system Polarisation poor and rich Golden age Coherent growth Increasing externalities Last products & industries Market saturation Disappointment vs complacency Crash 2008 1929 1893 1847 1797 Institutional innovation Based on Perez, 2002 The opportunity for green growth 1971 chip ICT 1908 car, oil, mass production 1875 steel 1829 steam, railways 1771 water, textiles
  • 12. Disruptive ICT Trends:  Mobile/Cloud Computing – smart phones, wearables, incl. sensors  Internet of Things – everything gets connected in the internet (virtualisation, M2M, autonomous devices)  Location-based monitoring - satellite and remote sensing technology, geo information, drones, etc.  Social media - Facebook, Twitter, Wiki, etc.  Block Chain – Tracing & Tracking, Contracts. Big Data - Web of Data, Linked Open Data, Big data algorithms High Potential for unprecedented innovations! everywhere anything anywhere everybody
  • 13. Drones, Big Data and Agriculture 13 IoT in Smart Farming cloud-based event and data management smart sensing & monitoring smart analysis & planning smart control
  • 14. Virtual Box Location A Location B Location & State update Location & State update Location & State update IoT in Agri-Food Supply Chains 14 Drones, Big Data and
  • 15. IoT and the consumer 15 Drones, Big Data and Agriculture Source: Hisense.com Smart Farming Smart Logistics tracking/& tracing Domotics Health Fitness/Well-being
  • 16. Towards smart autonomous objects Source: Deloitte (2014), IT Trends en Innovatie Survey Tracking & Tracing Monitoring I am thirsty: water me within 1 hour! I am product X at locatie L of Z My vaselife is optimal at a temperature of 4,3 °C. I am too warm: lower the temperature by 3 °C Event Management I am too warm: I lower the cooling of my truck X by 2 °C. I don’t want to stand besides that banana! I am thirsty! I am warm! Optimalisation Autonomy
  • 17. Grand challenges: tomorrow’s business Input industries Farmer Food processor Retail / consumerSoftware provider Logistic solu- tion providers Collaboration and Data Exchange is needed! Food & nutrition security Climate change Healthy diet for a healthy life Environmental issues
  • 18. There is a need for ABCDEFs: Agri-Business Collaboration & Data Exchange Facilities • Large organisations have gone digital, with ERP systems • But between organisations (especially with SMEs) data exchange and interoperability is still poor • ABCDEF platforms help • Our focus: data governance law & regulation innovation geographic cluster horizontal fulfillment Vertical
  • 19. Chain organisation changes (©Gereffi et al., 2005) inputsEndproduct PRICE Shops Complete Integration Lead company Lead company Turnkey supplier Relational supplier Market Modular Relational Captive Hierarchy Low Degree of explicit coordination and power asymmetry High Lead company Farmers
  • 20. Europe towards 2030 3 scenarios to explore the future of EU agriculture + implications for Agricultural Knowledge and Innovation Systems
  • 21.  HighTech: strong influence new technology owned by multinationals. Driverless tractors, contract farming and a rural exodus. US of Europe. Rich society with inequality. Sustainability issues solved. Bio-boom scenario.  Self-organisation: Europe of regions where new ICT technologies with disruptive business models lead to self- organisation, bottom-up democracy, short-supply chains, multi-functional agriculture. European institutions are weak, regions and cities rule. Inequalities between regions, depending on endowments.  Collapse: Big climate change effects, mass-migration and political turbulence leads to a collapse of institutions and European integration. Regional and local communities look for self-sufficiency. Bio-scarcity and labour intensive agriculture. Technology development becomes dependent on science in China, India, Brazil.
  • 22. Scenario 1: High Tech multinationals, clean technology, strong EU (c) Toshiba
  • 23. Scenario 2: Self organisation new business models, regions and cities rule, diversify Tempelhof, Berlin (c) Kasper Jensen
  • 24. Scenario 3: Collapse climate change, migration, breaking up of the EU
  • 25. Effects on AKIS (Ag. Knowledge & Innovation System)  HighTech: International players in agribusiness, direct access to best universities for own labs and extension programs. EU-Public Private Partnerships. Product and technology oriented. Upskilling of specialised AKIS staff. Small role regional government.  Self-organisation: Regional orientation, food and non- food. New (local) actors like NGO and cities. EU: connect the dots. Multi-skills of AKIS staff.  Collapse: Local orientation, food oriented. Problems of soil and water are main focus. Fragmentation of AKIS, strong emphasis on extension. Donors play a big role, fundamental research is done in China or India. Emphasis on basic skills of AKIS staff.
  • 27. Misunderstandings in social debate: one as a solution of everything, -where?? Productivism paradigm  Focus on more supply  Calories for the world  Eco-efficiency per kg Sufficiency paradigm  Food is more than calories  Changes in menu needed for sustainability  Local effects, emissions per ha count too. @SCAR 3rd foresight • Put fewer forks on the table – Thomas Maltus (1798, An essay on the principles of population) • Bake a bigger pie - Marquis de Condorcet • Teach everyone better table manners – William Godwin © Warren Belasco: Meals to come – a history of the future of food
  • 28. INPUT INDUSTRY FOOD PROCESSING FARMERS ICT RETAIL & OUT of HOME, Food Procesng Health sector + Cities CONSU- MERS Less animal based: • Reduce GHG cattle • Improve sustainb. pigs and poultry • New (lab) meat and feed (insects, algae etc.) More plant based: • Improve soil management • Cope with climate change (water) • Less chemicals, more biodiversity • Improve factory farming CIRCULAR PRINCIPLES • Less waste • More resource efficiency • Close P-cycle Help Consumers Change: * personalised nutrition Green, Healthy Cities Peri-urban multifunctional farms with short supply chains Help Empty Rural Regions Climate change Healthy diet for a healthy life
  • 29. Transforming the CAP into a Common Agricultural and Food Policy
  • 30. Five examples of a Common Agricultural and Food Policy  Make our diets more healthy and sustainable with a price that factors in true costs  Incorporate climate change agreements in farm decisions  Align incentives in the food chain  Install smart instruments for environmental management  Support disruptive innovation in the urban food system and bio-economy
  • 31. Transforming the CAP into a CAFP Pillar A INCOME SUPPORT Pillar B ECOSYSTEM SERVICES Pillar C RURAL DEVELOPMENT Pillar D FOOD & HEALTH Pillar E MONITORING & RESEARCH
  • 32. Pillar C: rural development Innovate for competitiveness
  • 33. Pillar E: monitoring reflection and research By the deployment of reflective citizen science in support of adaptive governance
  • 34. Food2030: 4 themes ? EU’s Framework Programme #9 (FP 9)

Hinweis der Redaktion

  1. better monitoring of production (resource use, crop development, animal behaviour) better understanding of the specific farming conditions (e.g. weather and environmental conditions, emergence of pests, weeds and diseases) Those sensors, either wired or wireless, integrated into an IoT system gather all the individual data needed for monitoring, control and treatment on farms located in a particular region.
  2. Risk management, Compliance, Goods monitoring and control, Portfolio enrichment, Trade
  3. SW: through smart production (farming) and logistics food ends at the consumers plate Smart tracking and tracing is necessary to provide the right information about the product (contents, freshness, etc.) This information can be related to other (IoT) domains such as: Domotics (recipes, shopping, etc.) Health (allergies, obesitas, etc.) Fitness/Well-being (calorie-metering, healthy ingredients, etc.)
  4. Note that for most of these
  5. 18
  6. Characterised by the key words.
  7. Characterised by the key words.
  8. Characterised by the key words.