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A geography of taste: fair trade coffee and spatialized tag clouds
Frank LaFone, Bradley Wilson, Trevor Harris Department of Geology and Geography West Virginia University
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The Coffee Paradox A ‘coffee boom’ in consuming countries and a ‘coffee crisis’ in producing countries Paradox within the Paradox International Coffee Market has too much ‘low quality’ coffee Sales growth is in ‘high quality’ – fair trade, organic, etc “Because of the importance of cup characteristics in evaluating the quality of coffee, market operators never really succeeded in collectively defining objective quality criteria and way of measuring them, although steps have been taken in this direction.” (Daviron and Ponte, pg. 69)
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Taste and Place Taste is subjective, personal, complex – yet taste is used to determine coffee quality and thus price Important in rise of Fair Trade Coffee Cup of excellence competition New science of coffee quality Codified by Specialty Coffee Association of America (SCAA) Professional coffee quality evaluators Combine subjective and objective sensory techniques Identify unique flavor profiles of coffee from around the world
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Cup of Excellence Compétition
Competitions held in each coffee growing country Back link coffee flavor evaluation from cup to crop Relationships between flavor, varietals, soils, climate, and farm practices
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Cup of Excellence Competition
Spatial analysis of Alliance for Coffee Excellence quality competitions Central America Explore spatial analysis of coffee taste Link evaluations to regional geographic location (terroir) Challenge to link textual descriptions of flavor to the geography of coffee production and Fair Trade
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Wheel of Flavor
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Cup of Excellence Competition Data Description – General Variables
Range, Examples Year Country Honduras, Costa Rica, Nicaragua, Guatemala, El Salvador City Citalá, Jinotega, etc Region Corquin, San Juan Sacatepéquez, etc Coffee Variety Bourbón, Caturra and Catuai Processing Method washed and sun dried, conventional, etc Farm Name Santa Elena II, Shangrilá, etc Farmer Julia Rosa Mena de Lima, Ernesto Lima Mena, etc Farm Size Hectares Coffee Growing Area Altitude Meters Certifications Free Trade, etc
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Cup of Excellence Competition Data Description – Competition Variables
Range, Examples Rank 1 - n (n differs by country/year) Score 80-100 Lot Size Number of bags/boxes submitted Cupping Number Unique ID number Price USD in current year 2003 Dollars Derived from above Winning Bidder World Coffee Co.,Ltd., The Rosterie Inc, etc. Descriptors Citrus, creamy, mellow, complex, chocolate, sweet, floral, melon, butterscotch, rich, orange, carrot, jasmine, honey, spicy, syrupy, licorice
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Number of farms ranked above 80%
Honduras Costa Rica Nicaragua Guatemala El Salvador 2003 37 31 2004 21 28 35 2005 41 17 2006 33 25 18 23 2007 24 34 19 2008 26 30 36 2009 39
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Exploratory Spatial Data Analysis of Coffee Data
Environmental Variables Competition Variables
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Exploratory Spatial Data Analysis of Coffee Data
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All farms ranked above 80% score for all years plotted against price 2003 Dollars by Rank
Clear relationship Variability Outliers Question – what flavors drive the higher ranking and therefore price Flavor descriptors Text Qualitative spatial analysis Qualitative GIS
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Exploratory Spatial Data Analysis of Coffee Data
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Wordles Fill in information about wordles and what they are
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Wordle for All Countries, All Years
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Comparative Wordles Highest Dectile of Rank Compared to Lowest Dectile of Rank
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Comparative Wordles Lowest Dectile of Rank Compared to Highest Dectile of Rank
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Comparative Wordles Highest Dectile of Price Compared to Lowest Dectile of Price
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Comparative Wordles Lowest Dectile of Price Compared to Highest Dectile of Price
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Nicaragua Comparative Wordles Highest Dectile of Rank Compared to Lowest Dectile of Rank
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Nicaragua Comparative Wordles Lowest Dectile of Price Compared to Highest Dectile of Price
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El Salvador Comparative Wordles Highest Dectile of Price Compared to Lowest Dectile of Price
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El Salvador Comparative Wordles Lowest Dectile of Price Compared to Highest Dectile of Price
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El Salvador ESDA Numeric Analysis vs Nicaragua ESDA Numeric Analysis
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El Salvador Comparative Wordles Lowest Dectile of Price Compared to Highest Dectile of Price
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Future Directions
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Future Directions
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Future Directions
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Future Directions
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Conclusions
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Conclusion Qualitative GIS informs analysis
Text – descriptors, wordles, maps Exploratory Critique Future work – tea, terroir, wine, spatial humanities
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