
AbstractCassava mosaic disease and cassava brown streak disease are caused by viruses transmitted by Bemisia tabaci and affect approximately half of all cassava plants in Africa, resulting in annual production losses of more than $US 1 billion. A historical and current bias towards virus rather than vector control means that these diseases continue to spread, and high Bemisia populations threaten future virus spread even if the extant strains and species are controlled. Progress has been made in parts of Africa in replicating some of the successes of integrated Bemisia control programmes in the south‐western United States. However, these management efforts, which utilise chemical insecticides that conserve the Bemisia natural enemy fauna, are only suitable for commercial agriculture, which presently excludes most cassava cultivation in Africa. Initiatives to strengthen the control of B. tabaci on cassava in Africa need to be aware of this limitation, and to focus primarily on control methods that are cheap, effective, sustainable and readily disseminated, such as host‐plant resistance and biological control. A framework based on the application of force multipliers is proposed as a means of prioritising elements of future Bemisia control strategies for cassava in Africa. © 2014 Society of Chemical Industry
Insecticides, Manihot, aleurothrixus floccusus, Cassava; CBSD; CMD; Control; Superabundant, Potyviridae, cassava, Insect Vectors, Hemiptera, bemisia tabaci, whiteflies, Begomovirus, Africa, Animals, mosaic, Pest Control, control, Plant Diseases
Insecticides, Manihot, aleurothrixus floccusus, Cassava; CBSD; CMD; Control; Superabundant, Potyviridae, cassava, Insect Vectors, Hemiptera, bemisia tabaci, whiteflies, Begomovirus, Africa, Animals, mosaic, Pest Control, control, Plant Diseases
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 111 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
