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