What will be the contributions of digital agriculture to the transition to bioeconomy?
Véronique BELLON-MAUREL Director of Evironmental Technology Department, IRSTEA, France Director of #DigitAg, Digital Agriculture Convergence Laboratory 28th of June, 2017 Introduc on
§ Would bioeconomy be a buzzword, refreshing the pain ng of agricultural and forestry biomass produc on ?
§ Or would it be something really new, ie a new way to consider those produc ons, within other sources of bio-components ? What is new in bioeconomy
ECONOMY ! From bioproduc on to bioeconomy
§ Be er produc on : « On-farm issues » Op mizing the produc on with regard to constraints, market and costs § Reducing expenses, ie reducing wasted inputs and useless opera ons § Be er use of natural func onali es agroecology § Recycling § Improving product quality with regard to the market & industrial requirements § Long-term thinking in farm management
§ Be er inclusiveness of farmers in the bioeconomy : « Off-farm issues » Acknowledging the role of farmers in territories and value chains § Farmers are paramount actors of the territories and related ecosystem services § Farmers are paramount actors of biomass produc on § More interconnec ons between farmers and other actors (F, C, B, A) are possible Once this has been said…
§ How to help farmers to embrace this transi on towards bioeconomy?
§ Would digital technologies / digital agriculture be a lever to boost this transi on? Digital Agriculture
One of the 4 levers iden fied in 2015, in the « Agriculture innova on 2025 » report to French Ministries of Research and of Agriculture, eg: Robo cs, Biocontrol , Biotechnologies, Digital Agriculture Digital Agriculture ó use of ICT in agriculture
= « On-farm » issues => a be er produc on : Data-driven agriculture: precision agriculture, high throughput phenotyping
= « Off-Farm » issues => a be er inclusiveness Data-sharing and digital network for improving interrela ons in value chains and in territories Outline
§ Introduc on
§ On-farm issues : Be er produc on § Precision agriculture § High throughput phenotyping
§ Off-farm issues : Inclusiveness § Related to territories § Related to value chains
§ Conclusion On-farm issues : Be er produc on Data driven Agriculture
Precision agriculture
Precision agriculture Cultural operations are adapted to present needs of plants (animals)
= sowing (variety, density) = fertilization (dose) = irrigation (dose) = crop protection (product type, dose) = weed management
DATA NEEDED !!! The data chain
Sensors ! The data chain
Data processing (big data, deep learning) The data chain
Data acquisition Data processing Decision aid systems
2.55
1.80
1.40
1.00
0.60
0 17 M 1:850
Recommendation / Control for - irrigation - fertilization
Multispectral zoning NDVI Oenoview – Montpellier Supagro Ex Farmstar
Now 0,8 M ha
Precision farming
- Saves fertilizer - Saves times - Saves money - Avoids over fertilizing and subsequent pollution due to nitrate High throughput Phenotyping
Crops are selected with regard to their traits expressed in a specific environment and their expected properties, with fast High throughput phenotyping
Allows companies to deliver
- Advices about which varieties are most appropriate to given soil/climate conditions;
- Advices about seeding with regard to intra-plot hetero- geneity (precision farming) = abiotic stress: water / nutriment stress - New varieties adapted to = biotic stresses Climate change = production quality (yield, composition)
Phenotyping – The TERRA*-Ref project
Using remote sensing to quantify plant traits eg plant architecture, carbon uptake, tissue chemistry, water use, etc, to predict the yield potential and stress resistance of 400+ diverse sorghum lines. *Transportation Energy Resources from Renewable Agriculture Phenotyping Reference Platform
13 sensors inside (mainly optical)
Lemnatec Field Sensors Off-farm issues : Be er inclusiveness for Agriculture
Better inclusiveness in value chains
B2C Early 20th century
B2B Late 20th century
B2B
B2C
Future ? Better inclusiveness in value chains
Are today’s prices OK for selling? Information
Disintermediation B2C Direct product design 18 Be er inclusiveness in territories Sharing data through digital applications Data / agricultural & ecological facts
Massive data / agriculture & ecology -> Links to ecosystem services (models) -> Payment of ecosystemic services 19 Be er inclusiveness in territories Sharing resources through digital applications
Pays de Fougères (Irstea Rennes- L. Aissani)
Sharing biomass ! Local biomass cycling 20 Be er inclusiveness in territories Sharing resources through digital applications
Hub for ag machinery sharing
Precision agriculture… and more?
Sharing equipment: better use of resources / economical and social benefits Conclusion
Conclusion Digital agriculture is the 3rd revolution in agriculture
= Opportunity to improve agricultural production, to reduce costs and to better link farmers to others : farmers, consumers, land managers
With regard to bioeconomy
= Keywords are long-term production optimisation, traceability, transparency, better information to downstream (either consumers or food compagnies)
= The data chain, from farming operations to food products. Massive agricultural information will help food industry to better understand relationships between farm practices and food quality
= Opportunities: access to biomass, tailored/ qualified biomass better incomes (incl. ecosys services / global economy), agility, « visible » farmers, new solidarities
= Risks: sensors & 4G network coverage! Social turmoil Research highly needed linked to agriculture is expected and must be anticipated Contribu on to a posi on paper
Priority research needs for the next 10 years = Sensors for monitoring agricultural production = Interoperability for streamlining the data chain = Deep-learning for turning data into valuable knowledge = Understanding legal, social and economic issues and anticipating the social changes due to the spreading of digital technologies in agriculture Interdisciplinarity is a must!
Which tools for research and development are lacking today ? = a platform with agricultural and auxilliary data (food chain, territory) = living labs
Which types of partnerships? Which new stakeholders ? = Better linking upstream and downstream, building trust = Data sciences, computer sciences Merci pour votre attention
Thank you for your attention