The cultivated banana and plantain (Musa spp.) are valuable for nutritional and socio-economic security for millions of people worldwide. In Benin, banana and plantain are among the most produced, consumed, and traded commodities. Its production is mainly for local consumption and remains insufficient to the demand. However, the varietal diversity of banana and plantain cultivated in Benin is not documented. This study aims at characterizing the banana and plantain cropping systems, genetic diversity, and production constraints as a baseline to the full utilization of this resource in crop improvement and to identify the potential production and agronomic qualities. A baseline investigation of ethnobotanical attributes of banana cultivars was done in 51 randomly chosen villages in southern Benin. Interviews with randomly selected representative farmers were carried out. Key informant interviews and focus group discussions were used for global confirmatory investigation of survey data. Socio-demographic data and indigenous knowledge on the farmer uses of banana and plantain diversity, such as cultural practices, origin, and availability of banana and plantain planting materials, and the constraints and criteria of varietal preference cited by farmers were ranked. Eighty-seven locally recognized cultivars were found: 73 of banana and 14 of plantain groups. The most popular cultivars were Sotoumon (banana) (52.94%), Aloga (plantain) (41.17%), Planta (banana) (33.33%), and Adjangan (plantain) (27.45%). Of the eleven production constraints identified, the main biotic challenges were banana weevil Cosmopolites sordidus Germar and banana bunchy top virus (BBTV), while abiotic problems were drought and the wind. Some local varieties like Amandan, Assonwonnou, Coleti, and Ninkouin are extremely rare owing to agronomic and economic preference perceptions. This study provides a baseline for banana diversity in Benin and the West African region and entry points for biological characterization and production improvement. This would enable the exploitation of this resource for plant breeding towards biotic and abiotic challenges facing banana production.

Disaster plant pathology addresses how natural and human-driven disasters impact plant diseases and the requirements for smart management solutions. Local to global drivers of plant disease change in response to disasters, often creating environments more conducive to plant disease. Most disasters have indirect effects on plant health through factors such as disrupted supply chains and damaged infrastructure. There is also the potential for direct effects from disasters, such as pathogen or vector dispersal due to floods, hurricanes, and human migration driven by war. Pulse stressors such as hurricanes and war require rapid responses, whereas press stressors such as climate change leave more time for management adaptation but may ultimately cause broader challenges. Smart solutions for the effects of disasters can be deployed through digital agriculture and decision support systems supporting disaster preparedness and optimized humanitarian aid across scales. Here, we use the disaster plant pathology framework to synthesize the effects of disasters in plant pathology and outline solutions to maintain food security and plant health in catastrophic scenarios. We recommend actions for improving food security before and following disasters, including (i) strengthening regional and global cooperation, (ii) capacity building for rapid implementation of new technologies, (iii) effective clean seed systems that can act quickly to replace seed lost in disasters, (iv) resilient biosecurity infrastructure and risk assessment ready for rapid implementation, and (v) decision support systems that can adapt rapidly to unexpected scenarios. [ ] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .

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.

Banana bunchy top disease (BBTD) has been reported in southwestern Rwanda since the 1980s. Recent sporadic observations of BBTD in western and central regions, made by extension services and the Rwanda Agriculture and Animal Resources Development Board, merited a comprehensive field survey across the country. This survey was performed in 2022 and 2023 to confirm and map the presence of BBTD in suspected areas in Rwanda. Combining the Rwandan survey with BBTD surveys in neighboring countries (eastern DR Congo, Burundi, and Uganda), a BBTD probability model was developed for Rwanda, taking into account environmental, land-use/land-cover, and socioeconomic variables, from which a country-wide vulnerability map was compiled. Field surveys confirmed that BBTD has spread to the Nyamasheke and Rubavu districts along Lake Kivu, all districts of Kigali, and the bordering districts of Rulindo and Kamonyi. Predictive risk mapping confirmed that these regions are the highest-risk areas of the country. Southeastern regions of Rwanda are identified as additional areas at risk for BBTD, mainly areas extending from Kigali to Gisagara in the south and to Kirehe in the east. Although BBTD is currently not widespread across Rwandan banana production zones, key recommendations are made to prevent further incursions. Specifically, Kigali was identified as a new hotspot for the spread of BBTD in Rwanda, and here, coordinated and rigorous eradication is key. Farmers’ interviews revealed a critical need for awareness campaigns and training on BBTD. Most farmers were unaware of how the disease spreads, effective disease recognition, how to prevent its introduction and establishment, and how to manage the disease at both initial and advanced stages, making a comprehensive management approach imperative. [ ] Copyright © 2025 The Author(s). This is an open access article distributed under the CC BY 4.0 International license .