Cassava is an important crop in Africa that is widely cultivated for its starchy tuberous root, which constitutes a major source of dietary carbohydrates. Cassava mosaic disease (CMD) is the most devastating disease affecting cassava in Africa and causes enormous losses in yield. In Benin, specifically, cultivars resistant to CMD are not commonly planted, and even when CMD is observed in fields, farmers do not implement control measures, presumably because they lack proper knowledge and training. Our study aimed to evaluate farmers’ knowledge of CMD to determine whether there is consistency between farmers’ criteria for selecting cassava cultivars and the currently CMD-recommended cassava varieties. We conducted structured interviews with 369 farmers in 20% of townships in each of three agro-ecological zones in Benin between November 2015 and February 2016. Farmers were selected randomly in each household, and their fields were assessed for CMD incidence and severity. All farmers surveyed, representing a broad demographic pool with regard to education level, age group, and years of experience in cassava production, successfully recognized CMD symptoms in photos, but most (98.60%) said they did not know the causes and vectors of the disease. Most farmers (93.51%) reported that they obtain planting material from neighboring fields or their own fields. In total, 52 unique cultivars were identified, of which 3 (5.76%) were preferred based on their yield and precocity and 3 (5.76%) were preferred based on taste or ability for transformation. The assessment of disease incidence and severity showed that the areas most affected by CMD were Comè Township (37.77% of fields affected) and agro-ecological zone VIII (26.33%). Farmers already know how to recognize the symptoms of CMD and could implement control measures against it if they are trained by researchers. Across all surveyed areas, we identified six preferred cultivars based on the four most commonly stated preference criteria (precocity, yield, gari, and taste. Our results suggest that farmers will be more likely to use CMD-resistant cultivars and clean plant material if the plants meet their existing preference criteria. We suggest that CMD-resistant cultivars will be embraced only if the recommended cultivars are strategically aligned with the characteristics desirable to the cassava farmers in each region.

Cassava production in Africa is constrained by number of biotic factors, including cassava mosaic disease (CMD). In response to this challenge, the PlantVillage Nuru application, which employs artificial intelligence for CMD diagnosis, provides farmers with the ability to independently detect the disease. This study examines the factors influencing the adoption of the innovative Nuru application by farmers in Benin. Data were randomly collected from 305 farmers in three Agricultural Development Poles (PDAs 5, 6 and 7). A binary logit model was used to analyze the determinants of adoption. The results show that, despite the potential of the Nuru application, the adoption rate remained relatively low at 14.1%. The key drivers of adoption were found to be participation in CMD training, disease knowledge, ownership of an Android smartphone, education level and practice of crop association. These findings emphasize the necessity of intensifying farmers’ training and raising awareness about CMD. Effective strategies to reach and train a significant number of farmers are crucial. Enhancing Nuru adoption can lead to more effective CMD management and improved cassava production, which will have a positive impact on food security in Africa and strengthen the resilience of farming communities against biotic challenges.

Societal Impact Statement: Banana and plantain are vital for food security and income in West Africa, yet banana bunchy top virus (BBTV) threatens production. This study combined remote sensing, field surveys, modelling and socio‐economic analysis to assess BBTV spread and control strategies in Benin. We found that risk is highest in southern regions with low disease awareness, limited adoption of control measures and widespread informal planting material exchange. By identifying priority areas and context‐specific interventions, our findings provide actionable guidance for targeted BBTV management, supporting smallholder resilience, reducing disease impact and safeguarding livelihoods across sub‐Saharan Africa. Summary: This study investigates banana bunchy top virus (BBTV), a major threat to banana and plantain production in Benin, which are critical for food security and income for smallholder farmers. We combined remote sensing, field surveillance, household surveys and mathematical modelling to map banana cultivation; detect BBTV prevalence; and evaluate control strategies. BBTV was detected in 140 of 747 fields, with the highest prevalence in southern humid regions; modelling showed that injection was the most effective nationally, while uprooting was the most effective in high‐risk, socio‐economically vulnerable areas. Our findings highlight the need for context‐specific, spatially targeted interventions integrating clean planting materials, farmer education and epidemiologically informed management to enhance smallholder resilience and safeguard livelihoods.

Transboundary diseases, such as cassava mosaic disease (CMD), represent a significant risk to food security and the livelihoods of millions of households in sub-Saharan Africa. To address this issue, awareness campaigns have been conducted targeting farmers and stakeholders within the cassava secor. The objective of this study is to quantify the impact of these awareness campaigns on the knowledge of CMD, the adoption of management practices, and the incidence of the disease in cassava fields. A random sample of 305 farmers and 77 cassava fields in Benin was selected for data collection. To account for potential selection bias associated with observable characteristics, we applied Propensity Score Matching (PSM). The results indicate that farmers who participated in the training demonstrated significantly higher levels of CMD knowledge and were more likely to adopt a greater number of management practices, which ultimately led to a reduction in the prevalence of the disease in their fields. However, CMD symptoms were still prevalent in the majority (61,04) of cassava farms, regardless of participation in the campaigns, due to the lack of healthy planting material and the abundance of whiteflies. These findings suggest that awareness campaigns can significantly improve farmers' knowledge and encourage behavioural changes in the identification and adoption of sustainable CMD management practices. It also shows the need to provide famers with healthy cuttings for more effective disease management.

Black sigatoka disease (BSD) is the most important foliar threat in banana production, and breeding efforts against it should take advantage of genomic selection (GS), which has become one of the most explored tools to increase genetic gain, save time, and reduce selection costs. To evaluate the potential of GS in banana for BSD, 210 triploid accessions were obtained from the African Banana and Plantain Research Center to constitute a training population. The variability in the population was assessed at the phenotypic level using BSD- and agronomic-related traits and at the molecular level using single-nucleotide polymorphisms (SNPs). The analysis of variance showed a significant difference between accessions for almost all traits measured, although at the genomic group level, there was no significant difference for BSD-related traits. The index of non-spotted leaves among accessions ranged from 0.11 to 0.8. The accessions screening in controlled conditions confirmed the susceptibility of all genomic groups to BSD. The principal components analysis with phenotypic data revealed no clear diversity partition of the population. However, the structure analysis and the hierarchical clustering analysis with SNPs grouped the population into four clusters and two subpopulations, respectively. The field and laboratory screening of the banana GS training population confirmed that all genomic groups are susceptible to BSD but did not reveal any genetic structure, whereas SNP markers exhibited clear genetic structure and provided useful information in the perspective of applying GS.