Search

Banana weevil (Cosmopolites sordidus, Germar) is a major pest in East African Highland Banana. The influence of crop nutritional status on weevil damage is poorly understood. Nutrient availability affects the nutritional quality of plants for weevils and may affect weevil damage. Here, we evaluate the effect of insecticides alone and in combination with fertilisers (N, P, K and Si) on weevil damage using data from two experiments in central and southwest Uganda. In the first experiment, we varied chlorpyrifos and application rates of N, P and K. In the second experiment, we varied the application rates of K and Si. Treatment effects were analysed using generalised linear mixed models with a negative binomial distribution. In the first experiment, chlorpyrifos reduced and N increased weevil damage, while P and K had no significant effect. In the K or Si application rates reduced weevil damage compared with the control. We conclude that the combined application of chlorpyrifos with K and Si fertilisers can contribute to weevil damage control on sites with low nutrient availability and should form part of integrated weevil management in bananas. Future studies should assess how much reduction in insecticide use is possible in EAHB with judicious input rates.

East African highland banana (Musa acuminata genome group AAA-EA; hereafter referred to as banana) is critical for Uganda’s food supply, hence our aim to map current distribution and to understand changes in banana production areas over the past five decades. We collected banana presence/absence data through an online survey based on high-resolution satellite images and coupled this data with independent covariates as inputs for ensemble machine learning prediction of current banana distribution. We assessed geographic shifts of production areas using spatially explicit differences between the 1958 and 2016 banana distribution maps. The biophysical factors associated with banana spatial distribution and geographic shift were determined using a logistic regression model and classification and regression tree, respectively. Ensemble models were superior (AUC = 0.895; 0.907) compared to their constituent algorithms trained with 12 and 17 covariates, respectively: random forests (AUC = 0.883; 0.901), gradient boosting machines (AUC = 0.878; 0.903), and neural networks (AUC = 0.870; 0.890). The logistic regression model (AUC = 0.879) performance was similar to that for the ensemble model and its constituent algorithms. In 2016, banana cultivation was concentrated in the western (44%) and central (36%) regions, while only a small proportion was in the eastern (18%) and northern (2%) regions. About 60% of increased cultivation since 1958 was in the western region; 50% of decreased cultivation in the eastern region; and 44% of continued cultivation in the central region. Soil organic carbon, soil pH, annual precipitation, slope gradient, bulk density and blue reflectance were associated with increased banana cultivation while precipitation seasonality and mean annual temperature were associated with decreased banana cultivation over the past 50 years. The maps of spatial distribution and geographic shift of banana can support targeting of context-specific intensification op

In South-West Uganda, manure is highly valued for sustaining yields of East African Highland Banana, but it is in short supply. As a result, banana growers import manure from rangelands up to 50 km away. We aimed to explore the potential of this regional banana-livestock integration to meet crop nutrient requirements for sustainable intensification of banana cropping systems. We used a mixed-methods approach supported by detailed data collection. Multiple spatial levels were integrated: field-level modelling to determine long-term nutrient requirements, a household-level survey to characterize farmer practices, and a regional-level spatial analysis to map banana production and manure source areas. For median to 90th percentile banana yields (37-52 t FW/ha/year), minimum K requirements were 118–228 kg/ha/year. To supply this with manure, 10.5–20.5 t DM manure/ha/year would be needed, requiring 47–91 tropical livestock units and 27–52 ha of rangeland, far more than what is potentially available currently. However, using only manure to satisfy potassium requirements increases the risk of N losses due to nutrient imbalances likely to result from large manure applications. For sustainable intensification, manure supplemented with K-based fertilizers is a better option than manure alone, as it is more cost-effective and reduces potential N losses.

The following repository contains the underlying data and R scripts used for developing the manuscript submitted for publication: "Mapping the spatial distribution and geographic shift of East African highland banana (Musa sp.) cropping systems in Uganda" For reproducibility most of the analyses and outputs for the manuscript were performed in the R environment (R v4.0.5 and RStudio v1.4.1103). Users of the attached R scripts should note however that the code chunks are Mac or Linux specific, which should be accordingly adapted for use with Windows.

Bananas on smallholder farmers in the African Great Lakes region are often pruned to illuminate shorter understory intercrops, reducing overall farm profitability. The impact of this practice on environmental and nutritional indicators are not known. This study determined the effect of this practice on operating profit, protein yield, soil organic matter (SOM) balance, and nitrogen input; and the management options for optimal performance of the intercrops. Alternative scenarios for improving soil nutrient balances of the system were also explored. Data from an experiment intercropping bush beans with banana at three leaf pruning levels (i.e., retaining all, seven, and four leaves) was used as the input for the multi-objective optimization FarmDESIGN model. Retention of four functional leaves mimicked a worst-case scenario observed on farms. Banana and bush bean monocrops served as controls. The model maximized operating profit, protein yield, and SOM, and minimized nitrogen input. Nutrient input scenarios in which (i) farmyard manure was only applied at planting (business as usual (‘BaU’)); and ‘BaU’, was combined with (ii) hedges, (iii) inorganic fertilizers, (iv) hedges and goat manure, (v) hedges and inorganic fertilizers, (vi) inorganic fertilizers and goat manure, and (vii) hedges, inorganic fertilizers, and goat manure, were also explored. Severe banana leaf pruning reduced profitability, SOM, and protein yield, although it’s less nutrient demanding. In contrast, the “un-pruned banana-bush bean intercrop” and “sole banana crop” had a higher profitability, SOM balance, and protein yield, whereas they demand more soil nutrients. No profound improvements in operating profit, SOM balance, and protein yield occurred for ‘BaU’, while hedges resulted in mild improvements. Profound improvements in all objectives occurred with the addition of the inorganic fertilizers, while goat manure resulted in a high SOM balance and N input. For ‘BaU’ and hedges, “severely pruned

Changes in land-use have been observed in banana-based systems in the African Great Lakes region affected by Xanthomonas wilt disease (XW) of banana. Through focus group discussions (FGDs) and the 4-cell method (to map the area under production and the number of households involved), changes in land-use were assessed in 13 XW-affected landscapes/villages along a 230 km transect from Masisi (where XW arrived in 2001) to Bukavu (XW arrived around 2014) in the Eastern Democratic Republic of Congo. Farmers' perceptions on the sustainability of new land uses were also documented. Soil nutrient content and erosion levels were measured for five major land-use options/trajectories on 147 fields across 55 farms in three landscapes along the transect. From banana being ranked the most important crop (92% of landscapes) before XW outbreaks, its importance had declined, with it grown on smaller farms by most households in 36% of the landscapes, while in 64% of cases by few households on smaller plots. Farmers uprooted entire banana mats or fields, expanding land under other crops. Species richness did not change at landscape level, although 21 crops were introduced at farm level. Banana is, however, still perceived as more sustainable due to its multi-functional roles. Soils under banana had better chemical attributes, while high erosion levels (Mg ha−1 year−1) occurred under cassava (1.7–148.9) compared with banana (0.3–10.7) and trees (0.3–5.9). The shifts from banana could thus affect supply of key services and sustainability of the farming systems. This study offers a good basis for interventions in XW-affected landscapes.

Rural households in sub-Saharan Africa earn a substantial part of their living from rain-fed smallholder agriculture, which is highly sensitive to climate change. There is a growing number of multi-level assessments on impacts and adaptation options for African smallholder systems under climate change, yet few studies translate impacts at the individual crop level to vulnerability at the household level, at which other livelihood activities need to be considered. Further, these assessments often use representative household types rather than considering the diversity of households for the identification of larger-scale patterns at sub-national and national levels. We developed a framework that combines crop suitability maps with a household food availability analysis to quantify household vulnerability to climate-related impacts on crop production and effects of adaptation options. The framework was tested for Uganda, identifying four hotspots of household vulnerability across the country. Hotspots were visually identified as areas with a relatively high concentration of vulnerable households, experiencing a decline in household crop suitability. About 30% of the households in the hotspots in (central) southwest were vulnerable to a combination of 3 °C temperature increase and 10% rainfall decline through declining suitability for several key crops (including highland banana, cassava, maize and sorghum). In contrast only 10% of the households in West Nile and central northern Uganda were negatively affected, and these were mainly affected by declining suitability of common beans. Households that depended on common beans and lived at lower elevations in West Nile and central north were vulnerable to a 2 to 3 °C temperature increase, while households located at higher elevations (above 1100–2000 m.a.s.l. depending on the crop) benefited from such an increase. Options for adaptation to increasing temperatures were most beneficial in northern Uganda, while drought-relat