The dynamics and environmental influence on interactions between cassava brown streak disease and the whitefly, Bemisia tabaci
Review statusPeer Review
MetadataShow full item record
Jeremiah, S.C., Ndyetabula, I.L., Mkamilo, G.S., Haji, S., Muhanna, M.M., Chuwa, C., & Legg, J.P. (2015). The dynamics and environmental influence on interactions between cassava brown streak disease and the whitefly, Bemisia tabaci. Phytopathology 105(5), 646-655.
Permanent link to cite or share this item: http://hdl.handle.net/10568/76371
Cassava brown streak disease (CBSD) is currently the most significant virus disease phenomenon affecting African agriculture. In this study, we report results from the most extensive set of field data so far presented for CBSD in Africa. From assessments of 515 farmers’ plantings of cassava, incidence in the Coastal Zone of Tanzania (46.5% of plants; 87% of fields affected) was higher than in the Lake Zone (22%; 34%), but incidences for both zones were greater than previous published records. The whitefly vector, Bemisia tabaci, was more abundant in the Lake Zone than the Coastal Zone, the reverse of the situation reported previously, and increased B. tabaci abundance is driving CBSD spread in the Lake Zone. The altitudinal “ceiling” previously thought to restrict the occurrence of CBSD to regions <1,000 masl has been broken as a consequence of the greatly increased abundance of B. tabaci in mid-altitude areas. Among environmental variables analyzed, minimum temperature was the strongest determinant of CBSD incidence. B. tabaci in the Coastal and Lake Zones responded differently to environmental variables examined, highlighting the biological differences between B. tabaci genotypes occurring in these regions and the superior adaptation of B. tabaci in the Great Lakes region both to cassava and low temperature conditions. Regression analyses using multi-country data sets could be used to determine the potential environmental limits of CBSD. Approaches such as this offer potential for use in the development of predictive models for CBSD, which could strengthen country- and continent-level CBSD pandemic mitigation strategies.