Using GIS-Based Tools and Distribution Modeling to Determine Sweetpotato Germplasm Exploration and Documentation Priorities in Sub-Saharan Africa
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Date
2006-07-22
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Publisher
HortScience
Abstract
Detailed information on the geographic distribution of a crop is important in
planning efficient germplasm conservation strategies but is often not available, particularly
for minor crops. Using germplasm collection data from Kenya, Tanzania, and Uganda, we
used distribution modeling to predict the distribution of sweetpotato [Ipomoea batatas L.
(Lam.)] in sub-Saharan Africa. We used a consensus modeling approach using the
following algorithms: genetic algorithm for rule set prediction (GARP), maximum entropy,
BIOCLIM, and DOMAIN. The predicted distribution encompasses known sweetpotato
production areas as well as additional areas suited for this crop species. New geographic
areas where at least three models predicted presence were in Angola, Cameroon, Central
African Republic, The Congo, Democratic Republic of Congo, Gabon, Ghana, Angola,
Ethiopia, Mozambique, Rwanda, and the Central African Republic. This information can
be used to fill gaps in current sweetpotato germplasm collections as well as to further
enhance the current presence-only based distribution model. Our approach demonstrates
the usefulness of considering several models in developing distribution maps.
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Citation
Villordon, A., Njuguna, W., Gichuki, S., Ndolo, P., Kulembeka, H., Jeremiah, S. C., ... & Mwanga, R. O. (2006). Using GIS-based tools and distribution modeling to determine sweetpotato germplasm exploration and documentation priorities in sub-Saharan Africa. HortScience, 41(6), 1377-1381.