GIS-Based Multi-Criteria Analysis for Arabica Coffee Expansion in Rwanda

I. Nzeyimana, A.E. Hartemink, V. Geissen

Research output: Contribution to journalArticleAcademicpeer-review

17 Citations (Scopus)

Abstract

The Government of Rwanda is implementing policies to increase the area of Arabica coffee production. Information on the suitable areas for sustainably growing Arabica coffee is still scarce. This study aimed to analyze suitable areas for Arabica coffee production. We analyzed the spatial distribution of actual and potential production zones for Arabica coffee, their productivity levels and predicted potential yields. We used a geographic information system (GIS) for a weighted overlay analysis to assess the major production zones of Arabica coffee and their qualitative productivity indices. Actual coffee yields were measured in the field and were used to assess potential productivity zones and yields using ordinary kriging with ArcGIS software. The production of coffee covers about 32 000 ha, or 2.3% of all cultivated land in the country. The major zones of production are the Kivu Lake Borders, Central Plateau, Eastern Plateau, and Mayaga agro-ecological zones, where coffee is mainly cultivated on moderate slopes. In the highlands, coffee is grown on steep slopes that can exceed 55%. About 21% percent of the country has a moderate yield potential, ranging between 1.0 and 1.6 t coffee ha(-1), and 70% has a low yield potential (<1.0 t coffee ha(-1)). Only 9% of the country has a high yield potential of 1.6-2.4 t coffee ha(-1). Those areas are found near Lake Kivu where the dominant soil Orders are Inceptisols and Ultisols. Moderate yield potential is found in the Birunga (volcano), Congo-Nile watershed Divide, Impala and Imbo zones. Low-yield regions (<1 t ha(-1)) occur in the eastern semi-dry lowlands, Central Plateau, Eastern Plateau, Buberuka Highlands, and Mayaga zones. The weighted overlay analysis and ordinary kriging indicated a large spatial variability of potential productivity indices. Increasing the area and productivity of coffee in Rwanda thus has considerable potential.
Original languageEnglish
Article numbere107449
JournalPLoS ONE
Volume9
Issue number10
DOIs
Publication statusPublished - 2014

Keywords

  • suitability evaluation
  • soil properties
  • land evaluation
  • prediction
  • framework
  • quality
  • yield
  • model
  • corn

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