Trial data management application 10 july 2011 v esri


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Presentation by Glenn Hyman and Ernesto Giron on agricultural trial database for climate change adaptation planning, at the 2011 ESRI International User Conference in San Diego, CA, July 14th, 2011

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  • Theme 1: the big picture
  • For Lobell map: Values show the linear trend in temperature for the main crop grown in that grid cell, and for the months in which that crop is grown. Values indicate the trend in terms of multiples of the standard deviation of historical year-to-year variation. ** A 1˚C rise tended to lower yields by up to 10% except in high latitude countries, where in particular rice gains from warming.** In India, warming may explain the recently slowing of yield gains. For yield graph: Estimated net impact of climate trends for 1980-2008 on crop yields for major producers and for global production. Values are expressed as percent of average yield. Gray bars show median estimate and error bars show 5-95% confidence interval from bootstrap resampling with 500 replicates. Red and blue dots show median estimate of impact for T trend and P trend, respectively. **At the global scale, maize and wheat exhibited negative impacts for several major producers and global net loss of 3.8% and 5.5% relative to what would have been achieved without the climate trends in 1980-2008. In absolute terms, these equal the annual production of maize in Mexico (23 MT) and wheat in France (33 MT), respectively.Source:Climate Trends and Global Crop Production Since 1980David B. Lobell1,*, Wolfram Schlenker2,3, and Justin Costa-Roberts1Science magazine
  • The climate analogue tool identifies the range of places whose current climates correspond to the future of a chosen locality. Potential for :- testing/validation ‘climate proofed’ technology Knowledge exchange (Farms of the future project: cross-site farmer visits) and participatory crop and livestock trials
  • Example of analogue sites
  • CCAFS is investing in a large multi-purpose repository of multi-site agricultural trial information, and now looks to develop methods for analyzing this data to understand varietal response through genotype by environment (GxE) analyses. The methods developed under this consultancy will then be used for training developing country scientists and to develop a community of data analysts looking at varietal response for a whole range of crops.
  • AMKN is a portal for accessing and sharing agricultural A&M knowledge.
  • Trial data management application 10 july 2011 v esri

    1. 1. Agricultural technology evaluation: Trial metadatabaseand file repository<br /><br />
    2. 2.<br />
    3. 3. (c) Neil Palmer (CIAT)<br />Importance & Potential <br />Collating input climate and agricultural data<br />Design of experiments<br />Calibration, validation and crop model runs<br /><ul><li>Exploration of adaptation options
    4. 4. Genetic improvement
    5. 5. On-farm management practices
    6. 6. Test them via modelling
    7. 7. Build “adaptation packages”
    8. 8. Assess technology transfer options</li></li></ul><li>Historical impacts on food security<br />Observed changes in growing season temperature for crop growing regions,1980-2008. <br />Lobell et al (2011) <br />% Yield impact <br />for wheat<br />
    9. 9. >> Multi-site agricultural trial database (<br />Effect of +1ºC warming on yield<br />Sites with >23ºC would suffer even if optimally managed<br />20,000+ maize trials in 123 research sites<br />More than 20% loss in sites with >20ºC, under drought<br />Lobell et al. 2011<br />
    10. 10. >> Multi-site agricultural trial database (<br />New data in 2011<br /><ul><li> Over 3,000 trials
    11. 11. 16 crops
    12. 12. 20 countries
    13. 13. > 15 international and national institutions</li></li></ul><li>Trial sites and trials<br />
    14. 14. Bean trial data<br />
    15. 15. Rice trial data<br />
    16. 16. Web Application Framework<br />Clients<br />Server<br />Data Base<br />PostgreSQL 8.3<br />Internet<br />Web Server<br />PHP 5.2.4<br />Symfony 2.4<br />Repository files<br />Trial File<br />Results File<br />Environmental File<br />
    17. 17. Database design<br />
    18. 18. Authentication : <br /><ul><li>All users must register
    19. 19. User profiles and permissions restrict functionality and capacity to edit or download information
    20. 20. Facility to change password</li></li></ul><li>4 main entry points.<br />Trial group: the group of trials across growing seasons or across sites (for example, international maize drought trial)<br />Trial: individual trial during one growing season at one site<br />Bibliography: any publication or report related to trials, including peer-reviewed articles, annual reports, gray literature, field books, etc. etc. <br />Other: All related tables<br />Database page<br />
    21. 21. Utilizes auto complete where possible<br />Users choose options already found in tables as opposed to putting in new data – to avoid duplication and error<br />
    22. 22. Fields that are required are indicated as such.<br />
    23. 23. The positive sign icon is clicked to add a new entry to a table<br />After clicking icon, a new form appears to enter tabular information<br />
    24. 24. Data sharing and intellectual property rights protocol<br />This form accepts code from Creative Commons to establish IPR: click on the hyperlink.<br />Step 1: A window appears that explains how to establish IPR. Click on Creative Commons logo<br />Step 3: Generate code<br />Step 2: <br />Answer questions<br />
    25. 25. Accepts coordinate input in both degrees, minutes and seconds and decimal degrees; converts automatically from one to the other<br />
    26. 26. Users can add varieties here. Our current list includes over 700 varieties that we took from DSSAT <br />
    27. 27. Users can enter the traits or variables measured in the trial here. We have acquired these variable names from GCP’s<br />
    28. 28. Uploading trial data<br />Trial results upload: in whatever format researcher manages their data in<br />Supplemental information upload: methods used in the trial, management, etc. etc.<br />Researchers designate whether environmental data can be downloaded or not.<br />Weather conditions during trial, upload: in whatever format researcher manages their data in<br />Soil conditions file: in whatever format researcher uses<br />
    29. 29. If users have given permission for others to download their files, they will have that capacity…….otherwise, any data or information about trials entered into the site will only be available as metadata (data about the trials, but not the raw data).<br />
    30. 30. Batch Upload<br />
    31. 31. Bibliography: any document related to agricultural technology evaluation at a site - such as field notes, gray literature and peer-reviewed publications<br />
    32. 32. CCAFS 'value addition<br />Matching with the CCAFS Analogue tool & Farms of the future project<br />
    33. 33. Karnal (India)<br />Rainy season from June to September<br />
    34. 34. Exploring bean trials in Central America and East Africa<br />Search for similar sites<br />Search bean trials for high yields for particular varieties<br />Map and graph the results<br />
    35. 35. In map below – green areas are most climatologically similar to Kampala, Uganda. In graphic to the right, the Analogue dissimilarity index is plotted against average yields for the Jamapa variety of common bean. Trial results from sites with low dissimilarity and high yields may be of interest to Kampala bean researchers. <br />
    36. 36. In map below – green areas are most climatologically similar to Masaya, Nicaragua. In graphic to the right, the Analogue dissimilarity index is plotted against average yields for the PorrilloSinteticovariety of common bean at 128 sites. Trials results from sites with low dissimilarity and high yields may be of interest to Masaya bean researchers. <br />
    37. 37. Related ongoing activities <br />Development of a generic methodology for G x E analysis to understand varietal response through genotype by environment. Method fully coded, documented and integrated into R-package<br />Application of the method to one case study, using the data at<br />Collaboration with crop modeling initiatives AgMIPS and Global Futures, including modeled trials. <br />Development of a community of data analysts looking at varietal response for a whole range of crops (blog in<br />Exploring collaboration with selected group of on-going programs and initiatives<br />
    38. 38. Thank you for your attention<br />Q&A<br />>> The Adaptation & Mitigation Knowledge Network<br />It links farmers’ realities on the ground with promising scientific research outputs, to inspire new ideas and highlight current challenge.<br />