Local and regional spread of banana xanthomonas wilt (BXW) in space and time in Kagera, Tanzania

Abstract

Banana is an important crop in the Kagera region of Tanzania. Banana xanthomonas wilt (BXW) was first reported in Kagera in 2006, and is now an important limiting factor in banana production, because all cultivars are susceptible and infected plants can fail to produce fruit. BXW is caused by Xanthomonas campestris pv. musacearum (Xcm), which is spread by farm tools, infected planting materials, and pollinating insects. Practices that address Xcm dissemination, such as mat removal, debudding and tool sterilization, have not prevented the spread of BXW in the region. Disease surveys were conducted in Kagera from 2007 to 2011 to assess BXW presence, monitor its intensity and evaluate its socioeconomic impacts. Spatiotemporal clusters of BXW were analysed with ARCGIS and SAS. The relationship between BXW clusters and environmental variables was examined using bivariate correlations in SPSS; two modelling approaches, MaxEnt (maximum entropy) and logistic regression, were used to predict the potential distribution of BXW in Tanzania. Disease progress over time was best described with the Gompertz model. Significant clustering of BXW was observed in all years and hotspots were located in the Muleba, Karagwe, Misenyi and Bukoba rural districts. These findings suggest that BXW spreads rapidly over short distances. BXW clusters were positively correlated with rainfall and negatively with temperature and altitude. According to MaxEnt, precipitation was the main factor associated with BXW development. MaxEnt and logistic regression predicted a wide potential distribution of BXW in Tanzania because the climate in all banana-growing regions is conducive for its establishment.

Genetically engineered bananas resistant to Xanthomonas wilt disease and nematodes

“…BXW disease is transmitted mainly by insects, contaminated farming tools, infected planting materials, and probably rain splash (Shimwela et al. ,b). It can be contained by the use of cultural practices such as removal of the male bud to prevent insect transmitted infection, using sterilized farming tools, destroying infected plants, and using clean pathogen‐free planting materials.…”

“…However, the adoption of these practices is inconsistent as these techniques are labor intensive and may enhance disease spread if cutting of plants occurs during rainy season (Shimwela et al. ,b). The disease affects all banana varieties and no resistant source has been identified in Musa germplasm yet.…”

Sustainability of banana-based agroecosystems affected by Xanthomonas wilt disease of banana

“…XW control efforts over the past 15 years have been reactive or focused on mitigation and the drivers of XW spread at various spatial scales are yet to be unravelled. Existing mapping efforts (Tushemereirwe et al, 2006;Bouwmeester et al, 2016;Shimwela et al, 2017) focused specifically on individual countries or regions within countries and often only highlighted disease presence or absence in a zone. Knowledge and spatial mapping of the relationship between these covariates and XW disease severity and/or incidence can help to pin-point disease hot spots, fronts and vulnerable landscapes.…”

“…Environmental variables (e.g. altitude, rainfall, temperature) and banana cultivar composition have a relationship with XW disease (Blomme et al, 2005;Biruma et al, 2007;Bouwmeester et al, 2016;Shimwela et al, 2017). Precipitation, temperature and altitude influence insect vector activity and thus the incidence and severity of XW disease (Blomme et al, 2005;Shimelash et al, 2008;Rutikanga et al, 2015).…”

“…Deliberating on these XW spatial risk maps with stakeholders is anticipated to proactively guide decisions and strategies for XW prevention and management at landscape and regional level. This study will build on existing XW mapping exercises in the region Tushemereirwe et al, 2006;Ndungo et al, 2008;Bouwmeester et al, 2016;Shimwela et al, 2017) that have often been region-or country-specific.…”