yield gap analysis: opportunities for crowdsourcing approaches to collect farm level data
DESCRIPTION
Presentation by Eskender Beza, João Vasco Silva, Pytrik Reidsma, Martin Herold, Lammert Kooistra, Laboratory of Geo-Information Science and Remote Sensing and Plant Production System (PPS) Session: ICTs/Mobile Apps for Management and Use of Agricultural Data on 7 Nov 2013 ICT4Ag, Kiali, RwandaTRANSCRIPT
Yield gap analysis: opportunities for crowdsourcing approaches to collect farm level data
Eskender Beza1,2, João Vasco Silva2, Pytrik Reidsma2, Martin Herold1, Lammert Kooistra 1
ICT4Ag international conference
4-8 November 2013
Rwanda, Kigali
1Laboratory of Geo-Information Science and Remote Sensing and
2Plant Production System (PPS)
Yield gap: Magnitude of the yield gap
Global yield gap atlas (GYGA) www.yieldgap.org • To provide the
best estimates of the exploitable yield gap
• It indicates
where the highest yield gaps exists.
Source: GYGA
What are the factors that cause the yield gap?
Selection of factors
Spatial analysis
Yield gap factors
database
Validation using authors feedback
Identify literatures
Data sources
Location of study areas
Methods used
Framework proposal
Considered and Explaining factors
Yield gap explaining factors in different regions
How to collect these many and diverse factors? Current data collection methods
Disadvantages
- Expensive
- Very labour demanding
- Longer time from collection to
analysis
Crowdsourcing for Agriculture: Case studies Climate change adaptation: Seeds4Needs – Biodiversity international
Tracking Pest and Disease Outbreaks
● CABI – Plantwise
● Grameen’s Community Knowledge Worker Program
Verifying Local Weather
● RANET project – Metrological Department in Zambia
M-Farm and iCow in Kenya
Ready-to-use platforms to crowdsource information:
o Jana
o Ushahidi
o Open Data Kit (ODK)....
Crowdsourcing: Yield gap analysis
• Case study
• Best practices
• Identify motivation
• Developing a framework
Thank you