Cassava brown streak disease (CBSD) is a major threat to smallholder farmers in sub-Saharan Africa (SSA), where cassava is a staple crop. Caused by cassava brown streak ipomoviruses (CBSIs), CBSD has spread extensively since its detection in Uganda in 2004, raising concerns about ongoing spread through Southern and Central Africa and potential expansion to West Africa, home to the world’s largest cassava producer, Nigeria. Building on a stochastic epidemiological model that predicts CBSD spread at the scale of Uganda, we incorporate extensive field surveillance records to extend the model to all thirty-two major cassava-producing countries in SSA. We then deploy the model to address key strategic questions such as estimating the present day CBSD distribution and predicting rates of ongoing spread towards West Africa. We also evaluate the risk of direct introductions resulting from extreme cases of long-range movement of infected planting material by air, sea or land, which could trigger outbreaks far beyond normal dispersal limits. Our model predicts the likely arrival of CBSD in Nigeria via cross-continental spread within 25 years, and if directly introduced anywhere in West Africa, spreading to most West African nations within 10 years of introduction. The risks of ongoing and future CBSD spread highlighted in this study underscore the need for proactive phytosanitation measures, including clean seed programs, vector control, and quarantine policies to curb CBSD spread. Moreover, the model described in this study not only provides estimates for arrival times across SSA, but also lays the foundations for a continental-scale quantitative framework wherein both surveillance and management options can be explored and optimised.
Understanding patterns of crop response to environmental factors is critical to simulating target environments in selection environments. In early stages of varietal development, breeding lines are usually developed in centralized facilities. Subsequently, testing continues on a broader array of research stations before dissemination to farmers, fields. Such a system is practiced in common bean (Phaseolus vulgaris L.) breeding in East Africa. A regional yield trial called the East Central Africa bean yield trial was distributed in three separate groups that aligned with three breeding pipelines: Andean bush beans (Group 1 or G1), Mesoamerican bush beans (G2), and climbing beans (G3). Forty-three trials met minimal standards of data quality. Trial environments composed of a site, planting date, and its climatic parameters were clustered based on 13 variables of temperature, rainfall, relative humidity, vapor pressure deficit, and altitude. Climatic data were derived from the NASA Prediction of Worldwide Energy Resources (POWER) database, which estimates day-by-day weather for each site. Four climate clusters emerged from this analysis. Climbing bean yield corresponded to climate clusters and heavily responded to high altitude and temperature. Most Andean bush bean environments occupied a centric cluster with few extreme variables. No patterns were observed in the Mesoamerican bush beans. This method should be extended to a larger set of trials and should be used to compare research station environments with farmer production environments.
Common bean (Phaseolus vulgaris L.) is one of the most abundantly consumed legume crops as foods worldwide. In many African countries, this crop is an important staple food because of its rich nutrients. The Great Lakes region of Central Africa, which includes Rwanda, the nation with the highest per capita consumption of common beans worldwide, is known to be a center of common bean diversity in Africa. Increasing the amount of iron and zinc in common bean for biofortification has been a key breeding goal in Rwanda and other countries. In this study, using 192 accessions, including local landraces from Rwanda, breeding materials, released varieties, and others, we performed genome wide association studies (GWAS) to determine the loci governing those traits in addition to other agronomic traits. We identified a locus that was strongly associated with seed zinc concentration and candidate genes. The information might be a great help for marker-assisted breeding of this trait in common bean.
Fall army worm Spodoptera frugiperda (J E Smith) is a significant invasive pest in maize, feeding from young seedlings till maturity. Field experiments were conducted to assess the effectiveness of new insecticides in maize during 2024 and 2025. The lowest incidence was observed in Spinosad 2.5%SC (9.87 and 13.18%); it was followed by plots treated with Bacillus thuringiensis and Metarhizium anisopliae. Application of cartap hydrochloride 50SP @ 2 ml/ l and Novaluron 10EC@ 2 ml/ l also recorded less larval incidence as compared to control. Among the treated plots, diflubenzuron 2%G @2 ml/ l recorded the highest incidence.
