Biotic constraints cause major crop losses and, hence, food insecurity in sub-Saharan Africa. This study documented the popularity, production constraints, pests and diseases, farmers’ perceptions on the severity of biotic constraints and the impact of related crop losses on household food security for the key root, tuber and banana (RTB) crops (cassava, potato, sweetpotato and banana). Farmer interviews were conducted in 2014 covering 811 households in Rwanda and Burundi. Farmers were asked to list their RTB crop production constraints, name insect pests and diseases of RTB crops, estimate crop loss due to pests and diseases, and mention if their household experienced any form of food insecurity due to pests and diseases. Cutworms and late blight in potato, banana weevils and banana Xanthomonas wilt in banana, cassava whitefly and cassava mosaic disease in cassava, sweetpotato weevils, and sweetpotato virus disease in sweetpotato were the most predominant pests and diseases reported. Crop losses due to pests and diseases for sweetpotato, banana, potato and cassava were estimated at 26%, 29%, 33%, and 36%, respectively, in Rwanda and 37%, 48%, 38%, and 37% in Burundi. Pests and diseases reduce the profitability of RTB crops, threaten food security, and constitute a disincentive for investment. Sustainable and affordable integrated pest management packages need to be developed.

Banana xanthomonas wilt ( XW ) caused by X anthomonas campestris pv. musacearum ( X cm) attacks all banana cultivars. Xcm in inflorescence‐infected P isang A wak plants with wilting male bud bracts is restricted to the upper parts of the true stem; therefore, cutting these plants at the pseudostem base has been recommended to prevent further X cm spread. In order to fine‐tune existing control strategies, this study examined the movement of X cm into plants and mats, in relation to disease incubation period. M ature P isang A wak and E ast A frican highland ( AAA ‐ EA ) plants were inoculated with X cm through abscission wounds of female bracts, male bud bracts, male flowers, a combination of male bud bracts and flowers, and by cutting male buds with a contaminated machete. Thirty plants per genotype and treatment were monitored for 24 months for disease symptoms. An additional 68 AAA ‐ EA and 33 P isang A wak plants were sampled weekly to assess the rate of X cm spread within the plants. All floral entry points resulted in disease, with the highest incidence in combined male bract and male flower abscission wound inoculations. The study confirmed the systemicity of X cm, with the pathogen able to live within the mat for long periods (5–16 months) without causing disease. Reliance on disease symptom expression to manage XW is therefore not sufficient. The long incubation period in lateral shoots may explain the current resurgence of the disease in locations where the disease was thought to have been successfully eradicated.

Banana production landscapes in the African Great Lakes Region (AGLR) have been under immense pressure from Xanthomonas wilt (XW) disease over the past two decades. XW, first reported on banana in central Uganda and eastern DR Congo in 2001, has since spread to the entire AGLR. XW is currently spreading westwards from hot spots in eastern DR Congo highlands, putting the plantain (Musa AAB genome) belt of central and west Africa at risk. In-depth understanding of the key variables responsible for disease spread, current hotspots, and vulnerable landscapes is crucial for disease early warning and management. We mapped aggregated disease distribution and hotspots in the AGLR and identified vulnerable landscapes across African banana production zones. Available data on disease prevalence collected over 11 years was regressed against environmental and expert developed covariates to develop the AGLR XW hotspots map. For the Africa-wide risk map, precipitation, distance to hotspots, degree of trade in fresh banana products, production zone interconnectedness and banana genotype composition were used as covariates. In the AGLR, XW was mainly correlated to precipitation and disease/banana management. Altitude and temperature had unexpectedly low effects, possibly due to an overriding impact of tool-mediated spread which is part of the management covariate. In the AGLR, the eastern part of DR Congo was a large hotspot with highest vulnerability. Apart from endemic zones in the AGLR and Ethiopia, northern Mozambique was perceived as a moderate risk zone mainly due to the predominance of ‘Bluggoe’ (Musa ABB type) which is highly susceptible to insect-vectored transmission. Presence of XW hotspots (e.g. eastern DR Congo) and vulnerable areas with low (e.g. north-western Tanzania) or no disease (e.g. Congo basin, western DR Congo and northern Mozambique) pressure suggest key areas where proactive measures e.g. quarantines and information sharing on XW diagnosis, epidemiology, and control could be beneficial.

Pests and diseases are key biotic constraints limiting banana production among smallholder farmers in Eastern and Central Africa. Climate changemay favour pest and disease development and further exacerbate the vulnerability of smallholder farming systems to biotic constraints. Information on effects of climate change on pests and pathogens of banana is required byby policy makers and researchers in designing control strategies and adaptation plans. Since altitude is inversely related to temperature, this study used the occurrence of key banana pests and diseases along an altitude gradient as a proxy for the potential impact of changes in temperature associated with global warming on pests and diseases. We assessed the occurrence of banana pests and diseases in 93 banana fields across three altitude ranges in Burundi and 99 fields distributed in two altitude ranges in Rwanda watersheds. Incidence and prevalence of Banana Bunchy Top Disease (BBTD) and Fusarium wilt (FW) was significantly associated with temperature and altitude in Burundi, revealing that increasing temperatures may lead to upward movement of banana diseases. No significant associations with temperature and altitude were observed for weevils, nematodes and Xanthomonas wilt of banana (BXW). Data collected in this study provides a baseline to verify and guide modelling work to predict future pest and disease distribution according to climate change scenarios. Such information is useful in informing policy makers and designing appropriate management strategies.

Across Africa, banana bunchy top disease (BBTD) severely impacts banana production and livelihoods of millions of smallholder farmers. Mapping vulnerability of landscapes to monitor BBTD establishment and spread is crucial for proactive measures of disease exclusion. To highlight current and future risks of BBTD in Africa, the relationship between 1160 field observations from 14 BBTD surveys and environmental covariate maps was determined using logistic regression. From these relationships, we inferred the environmental suitability of the African landscape for the possible wider spread of BBTD. Using this information and expert knowledge, we generated a map highlighting the main banana production areas at risk of BBTD entry and establishment. We combined these maps to create a priority map that highlights the areas that need most attention in combating BBTD through surveillance and measures to prevent its spread. Our analysis shows that BBTD is widespread across tropical Africa, with dispersal over several hotspots. Central and Western Africa are most favourable for the development of BBTD. Central, West and South‐East Africa are most at risk of BBTD entry and initial establishment. Areas in West and Central Africa, in the Great Lakes Region in Eastern Africa and in South‐East Africa, particularly in Malawi and Mozambique, score high on the prioritization index for surveillance and mitigation efforts. Recent reports of BBTD presence in north‐western Uganda and western Tanzania support these risk predictions. For these and other not‐yet‐infected areas, measures for close surveillance and proactive management of the disease are needed.