For the visit of Tim Shilling, the Executive Director of the Global Coffee Quality Research Initiative we put together a presentation about our capacity and experience in coffee research
Transcript: New from BookNet Canada for 2024: BNC CataList - Tech Forum 2024
DAPA Capacity GCQRI
1. Dapa presentation to GCQRI June 2011 P Läderach T Oberthür M Lundy A Eitzinger Christian Bunn Expertise and Contributions With Presentations by Laure Collet, Robert Andrade, Henk van Rikxoort, Martin Wiesinger
7. Impact analysis Risk Evaluation Predict future suitability and distribution of coffee sourcing areas Evaluate potential impacts of CC on coffee quality and quantity Identify alternative crops suitable under predicted climate change Evaluate the implications of changes in coffee quality and quantity studies on social parameters Accompany farmer organizations and engage supply chain actors
8. Vulnerability Risk Reduction Vulnerability (IPCC 2001) Exposure Participatory workshops Socio Economic Indicators on 5 Assets (DFID 1999) Vulnerability profiles more suitable no change less suitable Sensitivity Adaptive capacity
12. New Project on Pest ManagementCrop Alternatives
13. Towards Integrated Policy Support Development of a Price Module 80% of Coffee Production will be negatively impacted by CC How does this affect markets? How can we integrate this into Crop Models? Use of a Coffee Growth Model CAF2007 Cooperation with CATIE Enables us to model adaptation options Market Importer Producer p p p q q q Oijen, M. V., Dauzat, J., Lawson, J.-michel H. G., Vaast, P., & Rica, C. (2010). Coffee agroforestry systems in Central America : II . Development of a simple process-based model and preliminary results.
36. Homologue Competitive to comparative advantage Identifies places climatically and pedologically similar to a known individual location. Concept: Dependingonthedegreewithwhichclimate and soilsinfluenceproductquality, places with similar climates and soils can have similar qualities. Providesmeanstoidentify places withpotentialfortheintroduction of a promesingvariety / technology.
38. Low Shade % High Shade % Predicted probability map of disease risk for two shade conditions Observed geo-referenced disease attack intensities under low shade and high shade conditions Disease driving environmental factors generated for the study region: rainfall; slope % and aspect, elevation Comparing score predictions with high certainty Pest and desease management
39. Sun points Pest and desease management Mycena citricolor attack intensity index high shade (15 - 65%) and low shade (0 -15 %) cover
40. 0,8 0,7 0,6 3 0,5 2 Predicción hecha con sol 0,4 4 0,3 0,2 1 0,1 0 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 Predicción hecha con sombra Comparison of score predictions for Mycenacitricolor attack intensity index with high and low shade cover 4 behaviours : 1. Low scores with high and low shade cover: environment unfavourable for disease development 2. Similar scores with high and low shade cover: no effect of shade 3. Higher scores with low shade cover : sun exposure is favourable to disease development 4. Higher scores with high shade cover : shade is favourable to disease development
41. 0,8 0,7 3 0,6 0,5 Prediction made with sun model 4 0,4 0,3 0,2 0,1 0 0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 Prediction made with shade model Comparison of driving environmental factors for groups 3 and 4 3. Higher scores with low shade cover : sun exposure is favourable to disease development Interactions shade-environment for Mycena citricolor development 4. Higher scores with high shade cover : shade is favourable to disease development In the study area, shade is especially favourable for Mycena development on West and North oriented slopes, and unfavourable on East and South oriented slopes
64. Understand the spatial relationships between coffee quality on one side, and environmental and production system characteristics on the other side for each identified domain.
65. Identify the most important environmental factors that impact on key coffee quality characteristics.
78. Random sample Random Sample Descriptive Statistics
79. Random sample and Counterfactual Sample randomly selected from the interest area Counterfactual Select treatment and control Econometric Define changes in wellbeing due to adoption
80. Ongoing work Evaluation on CAFÉ practices Assessing the benefits for smallholders due to fare price and associations Economic analysis on Boarder Coffee Establishing base line, monitoring and indicators and assessing impact
92. CONTACTS Henk van Rikxoort Student Tropical Agriculture Consultant – Agriculture and Climate Change Wageningen The Netherlands Mobile Colombia +573105325712 Mobile Europe +31618187108 E-mail henk.vanrikxoort@wur.nl Fotos – Neil Palmer (CIAT)
Showing basic statistics of a cupper profile. How the cupper cupped over the last month. Comparing him to the average cupping scores and also providing an overview of the scores he gave within this time span.
Agreement with national coffee organisationsWe have all data forcentralamericaGIZ agronomy projects in parts of africa, asiaMake a map of all project areas and network partners
Agreement with national coffee organisationsWe have all data forcentralamericaGIZ agronomy projects in parts of africa, asiaMake a map of all project areas and network partners
Agreement with national coffee organisationsWe have all data forcentralamericaGIZ agronomy projects in parts of africa, asiaMake a map of all project areas and network partners