Cassava brown streak disease: a threat to food security in Africa

Published Online: 01/05/2015Cassava brown streak disease (CBSD) has emerged as the most important viral disease of cassava (Manihot esculenta) in Africa and is a major threat to food security. CBSD is caused by two distinct species of ipomoviruses, Cassava brown streak virus and Ugandan cassava brown streak virus, belonging to the family Potyviridae. Previously, CBSD was reported only from the coastal lowlands of East Africa, but recently it has begun to spread as an epidemic throughout the Great Lakes region of East and Central Africa. This new spread represents a major threat to the cassava-growing regions of West Africa. CBSD-resistant cassava cultivars are being developed through breeding, and transgenic RNA interference-derived field resistance to CBSD has also been demonstrated. This review aims to provide a summary of the most important studies on the aetiology, epidemiology and control of CBSD and to highlight key research areas that need prioritization

Community phytosanitation to manage cassava brown streak disease

Article purchased; Published online: 6 May 2017Cassava viruses are the major biotic constraint to cassava production in Africa. Community-wide action to manage them has not been attempted since a successful cassava mosaic disease control programme in the 1930s/40 s in Uganda. A pilot initiative to investigate the effectiveness of community phytosanitation for managing cassava brown streak disease (CBSD) was implemented from 2013 to 2016 in two communities in coastal (Mkuranga) and north-western (Chato) Tanzania. CBSD incidence in local varieties at the outset was >90%, which was typical of severely affected regions of Tanzania. Following sensitization and monitoring by locally-recruited taskforces, there was effective community-wide compliance with the initial requirement to replace local CBSD-infected material with newly-introduced disease-free planting material of improved varieties. The transition was also supported by the free provision of additional seed sources, including maize, sweet potato, beans and cowpeas. Progress of the initiative was followed in randomly-selected monitoring fields in each of the two locations. Community phytosanitation in both target areas produced an area-wide reduction in CBSD incidence, which was sustained over the duration of the programme. In Chato, maximum CBSD incidence was 39.1% in the third season, in comparison with an incidence of >60% after a single season in a control community where disease-free planting material was introduced in the absence of community phytosanitation. Kriging and geospatial analysis demonstrated that inoculum pressure, which was a function of vector abundance and the number of CBSD-infected plants surrounding monitored fields, was a strong determinant of the pattern of CBSD development in monitored fields. In the first year, farmers achieved yield increases with the new varieties relative to the local variety baseline of 94% in Chato (north-west) and 124% in Mkuranga (coast). Yield benefits of the new material were retained up to the final season in each location. The new variety (Mkombozi) introduced under community phytosanitation conditions in Chato yielded 86% more than the same variety from the same source planted in the no-phytosanitation control location. Although there was an 81% reduction in CBSD incidence in the new variety Kiroba introduced under community phytosanitation compared to control conditions in Mkuranga, there was no concomitant yield increase. Variety Kiroba is known to be tolerant to the effects of CBSD, and tuberous roots of infected plants are frequently asymptomatic. Community phytosanitation has the potential to deliver area-wide and sustained reductions in the incidence of CBSD, which also provide significant productivity gains for growers, particularly where introduced varieties do not have high levels of resistant/tolerance to CBSD. The approach should therefore be considered as a potential component for integrated cassava virus management programmes, particularly where new cassava plantations are being established in areas severely affected by CBSD

Cassava mosaic disease: incidence and yield performance of cassava cultivars in Zambia

Article purchasedCassava is the main food crop for an estimated 30% of the population in Zambia where yields of 5.8 t/ha are some of the lowest of any major cassava-producing country. A study was conducted to characterize yield responses of Zambian cassava genotypes to cassava mosaic disease (CMD), as well as the relative susceptibilities to the causal viruses. CMD-free planting material of four improved cultivars (Mweru, Chila, Tanganyika and Kampolombo), four officially-promoted landraces (Nalumino, Kapumba, Bangweulu and Katobamphunta) and a locally popular landrace (Manyopola) were evaluated at a field site in Rufunsa District, Lusaka Province (central-eastern Zambia). Manyopola and Bangweulu were found to be susceptible and had high foliar incidences of CMD (97.5% and 74.7%, respectively) based on visual CMD symptoms with high severity scores (3.5, 3.5), whilst cv. Kampolombo was resistant (incidence 0.7%, severity 2.0). Mweru had the highest root yield (17.6 t ha-1 ) while Kapumba, the second most susceptible cultivar, had the lowest root yield (3.2 t ha-1 ). Significant inverse regression 2 relationships were demonstrated between CMD incidence and CMD severity with root yield. Using these regressions together with published data on cassava production and countrywide CMD incidence in Zambia, it was possible to estimate annual losses due to CMD at ca. US$ 51.7 million. Evidence for resistance to CMD amongst several of the improved cassava cultivars tested suggests that there is great potential for the effective control and management of CMD in Zambia, if these materials could be widely disseminated

The role of women in production and management of RTB crops in Rwanda and Burundi: Do men decide, and women work?

This paper evaluates the determinants of decision-making in relation to the production of four crops (banana, cassava, potato, and sweet potato). Understanding the division of labor and decision-making in crop management may lead to designing better interventions targeted at improving efficiency in smallholder agriculture. In 2014, the research team conducted a quantitative household survey with heads of households involving 261 women and 144 men in Burundi and 184 women and 222 men in Rwanda. Most of the decisions and labor provision during the production of both cash crops (potato and banana) and food crops (sweet potato and cassava) were done jointly by men and women in male-headed households. Higher values for ‘credit access’, ‘land size’, and ‘farming as the main occupation of the household head’ increased the frequency of joint decision-making in male-headed households. A decline in the amount of farm income reduced the participation of men as decision-makers. A reduction in total household income and proximity to the market was correlated with joint decision-making. Gender norms also contributed to the lower participation of women in both decision-making and labor provision in banana and potato cultivation. Although a large proportion of decisions were made jointly, women perceived that men participate more in decision-making processes within the household during the production of cash crops. Increased participation by women in decision-making will require an active and practical strategy which can encourage adjustments to existing traditional gender norms that recognize men as the main decision-makers at both the household and community levels

Deep learning for image-based cassava disease detection

Open Access Journal; Published online: 27 Oct 2017Cassava is the third largest source of carbohydrates for human food in the world but is vulnerable to virus diseases, which threaten to destabilize food security in sub-Saharan Africa. Novel methods of cassava disease detection are needed to support improved control which will prevent this crisis. Image recognition offers both a cost effective and scalable technology for disease detection. New deep learning models offer an avenue for this technology to be easily deployed on mobile devices. Using a dataset of cassava disease images taken in the field in Tanzania, we applied transfer learning to train a deep convolutional neural network to identify three diseases and two types of pest damage (or lack thereof). The best trained model accuracies were 98% for brown leaf spot (BLS), 96% for red mite damage (RMD), 95% for green mite damage (GMD), 98% for cassava brown streak disease (CBSD), and 96% for cassava mosaic disease (CMD). The best model achieved an overall accuracy of 93% for data not used in the training process. Our results show that the transfer learning approach for image recognition of field images offers a fast, affordable, and easily deployable strategy for digital plant disease detection

First report of Ugandan cassava brown streak virus on cassava in Democratic Republic of Congo

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