[Day 3] Agcommons Quickwin: Crop Disease Surveillance


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CGIAR-CSI Annual Meeting 2009: Mapping Our Future. March 31 - April 4, 2009, ILRI Campus, Nairobi, Kenya

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[Day 3] Agcommons Quickwin: Crop Disease Surveillance

  1. 1. Empowering the World’s Poorest to Escape Poverty Grameen Foundation Quick Win Project Community Level Crop Building Sustainable Businesses in a Developing World Disease Surveillance April 2nd, 2009 Improving the lives of small-holder farmers through community level crop disease surveillance
  2. 2. Quick Win Overview Objective Build and test the viability of a system that uses mobile devices equipped with cameras and GPS to locate, diagnose, and prevent the spread of crop-disease outbreaks and relies upon a network of rural intermediaries for data collection and information dissemination. Partnerships •International Institute for Tropical Agriculture (IITA) • National Agricultural Research Organization (NARO) •Grameen Technology Center 2
  3. 3. Community Knowledge Worker Project CKW Objectives • Build a network of rural intermediaries to reach small-holder farmers • Develop mobile information services that meet the demands of poor farmers • Create a cost-effective means for collecting granular data from rural communities
  4. 4. Community Knowledge Worker Project •7 month pilot in two sites •Identify, recruit, train, and support CKWs •Rapid prototype 4-5 mobile information services •Conduct 4 mobile surveys using a range of technologies •Track CKW performance and document findings to design model for scaling over time
  5. 5. Quick Win Approach •Train and support Community Knowledge Workers (CKWs) •Develop mobile tools and back-end system •Conduct site visits and take samples • Analyze data to create information products and maps • Document findings and fine-tune geospatial application and surveillance system
  6. 6. Why Banana? • Importance as food crop and cash crop • Annual losses of $70-$200 million • High yielding staple food • Opportunity to monitor resurgence of an existing disease and threat of a new disease outbreak simultaneously • Resurgence of BXW • Recent alert for BBTV in Uganda
  7. 7. Distribution of banana in Uganda Source: Jerome Kubiriba, NARO
  8. 8. Overall control of BBW as per 2008 Source: Jerome Kubiriba, NARO
  9. 9. Geospatial Crop Disease Surveillance Application • Form-based mobile surveys • Sent via GPRS to back-end system • Reports analyzed by agricultural experts • Affirmative reports are mapped • Team travels to field to confirm certain percentage (TBD) of affirmative reports • Target of 1200 surveys over pilot period
  10. 10. Banana production constraints 1. Bacterial wilt 2. Banana weevil (SMALL ELEPHANT) weevil corm damage Dry necrotic leaves 3. Black Sigatoka 4. Nematodes wilted banana plant root damage 5. Fusarium wilt Yellow leaves 6. Banana streak virus discoloured streaked leaf pseudostem discoloured corm Source: Jerome Kubiriba, NARO
  11. 11. Disease Control Mobile Information Services • On-demand mobile information service • Timely information on disease spread • Actionable tips • Information on – Location of clean planting materials – Control techniques – Consequences of inaction – Disease spread information • Potential to use photos/diagrams/maps
  12. 12. Banana Bunchy Top Disease What to Do? DESTROY all infected plants and their suckers CHECK all your plants ONLY use healthy planting material Source: IITA
  13. 13. Banana Bacterial Wilt BREAK OFF the male bud DESTROY sick plants and their suckers Use CLEAN S SUCKERS and CLEAN TOOLS Source: IITA
  14. 14. Quick Win Analysis and Outputs • Analyze CKW ability to accurately identify and document disease outbreaks • Evaluate usefulness of information disseminated • Assess usability of tool • Analyze data accuracy and ability to map incidence by pilot area, CKW characteristics, and different classes of mobile technology • Estimate required frequency/response time by experts • Map CKW reports to existing incidence reports • Map location of clean planting materials to outbreaks • Map affirmative reports over time
  15. 15. GIS output: increase risk awareness e.g. BXW Impact of BXW? Uganda: Uganda: losses of 70 - 200 million annual US $ annual losses of 70 - 200 million US2-3 % of GDP $ 2-3 % of GDP Burundi and Rwanda: Burundi and 100 million US $ predicted Rwanda: predicted 100 million US $ Source: IITA
  16. 16. Expected Long-Term Impact • Decrease spread of crop disease , especially in high risk areas affected by endemic and emerging diseases • Empower small-holder farmers to halt disease spread through access to timely information • Enable agricultural experts to plan preventative measures in a cost and time-effective manner • Enhance scientists’ ability to monitor disease outbreaks and disseminate information to farmers in remote areas and rural communities where regular visits by extension agents and agricultural scientists may not be possible
  17. 17. Acknowledgements • IITA • Bill and Melinda Gates Foundation • CH2M Hill AGCommons • CGIAR • FAO • NARO
  18. 18. Project Details • Approx. 40 CKWs in two districts • Three mobile devices • Two six-week pilots • Two mobile applications • Monitoring for at least two diseases in banana • Three experts • Back-end data analysis on schedule TBD • Field visits to take samples every two weeks • Mapping of results on schedule TBD • Publically available map products