Analysis of distribution and pathogenesis of Mycosphaerella fijiensis, in subsistence farming systems of banana and plantain in Benin

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The distribution and severity of this disease in banana and plantain cropping systems result from both intrinsic and extrinsic factors that interplay dynamically. In this paper, we provide field incidence and severity of the disease in banana and plantain subsistence farming systems in 17 districts in Benin Republic. Pathogenicity test was conducted in greenhouse followed by the mapping of the study areas based on the virulence of M. fijiensis isolated from plant and soil samples collected from 114 plantain and banana fields. The results showed that the incidence of the disease in banana subsistence farming systems varied significantly according to the production area (p = 0.0465), the banana and plantain cultivars (p = 0.0184) and the types of cropping system (p < 0.0001). Dessert-banana-based monoculture systems were the most sensitive to pathogen attacks, with a Disease Severity Index (DSI) of 38.26 ± 0.53, followed by the intercropping systems (DSI = 33.64 ± 0.74) and home garden systems (DSI = 34.63 ± 0.61). Overall, plantain cultivars across different systems were more resistant M. fijiensis attacks (DSI = 35.57 ± 0.49), compared dessert banana subgroup (DSI = 37.46 ± 0.90) recorded to be the most susceptibleThe longest incubation times of 15.66 and 16.56 days recorded from isolates collected respectively in Houeyogbe in Zagnanado indicated the presence of the least virulent isolates. Contrariwise, the most virulent isolates with the shortest incubation times ranging from 11.75 to 12.58 days was recorded in Djidja and Toffo. These findings provide novel and valuable insights into epidemiology of banana and plantain farming systems in Benin. This outcome is essential to offering appropriate advice and support to farmers. In addition to this, existing production models are to be improved so that they can more effectively and sustainably control and prevent black Sigatoka disease. black leaf streak disease disease incubation time virulence Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Black Sigatoka, also known as black leaf streak disease, caused by pathogenic fungus Mycosphaerella fijiensis Morelet, [anamorph: Pseudocercospora fijiensis Deighton], is one of the most devastating diseases of banana and plantain (Kimunye et al., 2021 ; Pinzón‑Núñez, 2024) which have co-evolved with Musa for the last 13 million years (Arcila-Galvis et al., 2021 ). The causal agent is firstly reported on Sigatoka Valley, Fijian island at Viti Levu in 1963 (Rhodes, 1964 ). Since its discovery, the disease has continued to spread into new regions. This disease was accidentally introduced in Africa from Gabon in 1978 (Frossard, 1980 ), and has spread to all African countries (Blomme et al., 2013 ) including Benin where it was reported for the first time in 1993 (Jones & Mourichon, 1993 ). It attacks the leaves where more or less severe necrotic lesions are generally reported, thus causing premature senescence of the leaves (Castelan et al., 2012 ). This necrosis causes direct and indirect losses (Churchill, 2011 ), as they reduce the photosynthetic leaf area of the plant (Etebu & Wabiye, 2011 ). Direct losses are estimated to be between 20 and 50% of production, or even 100% from the second cycle onwards. These losses are attributed to poorly filled fruit, smaller bunches and low weights (Tuo et al., 2017 ). Indirect losses are associated with a reduction in fruit green life after harvest, premature fruit ripening, uneven fruit colouring, reduced pulp clarity and altered fruit taste (Castelana et al., 2012; Chillet et al., 2009 ), making them unsuitable for sale and consumption (Arango Isaza et al., 2016 ). Although M. fijiensis is considered a very prolific pathogen in all banana and plantain-producing countries, the disease continues to occupy new ecological niches (Robert et al., 2012 ) where it is prevalent, particularly in industrial banana production systems characterized by monoculture over large areas (Strobl and Mohan, 2020 ). This cropping system is not widespread in Benin; it accounts for about 11% of banana and plantain production. The rest of the plantations are mostly smallholdings where bananas and plantains are either grown in association with food crops or in the home garden system, which is used by 64.28% and 24.72% of banana and plantain producers in Benin, respectively (Togbé et al., 2024). These cropping systems are also subject to more or less severe attacks by black Sigatoka, causing damage with high economic impact due to the non-existence or inadequacy of control methods (Ahohouendo et al., 2020 ). Understanding the damage caused by pathogens to their hosts is a central focus of plant pathology. This is particularly important for cultivated plants such as banana and plantain (Cook et al., 2013 ) which are essential components of the diet for populations in West and Central Africa. These crops play a crucial role in addressing food security challenge in the region (Folefack et al., 2017 ). The relationships between the degree of symptom and yield loss on plants has been well established by several authors (Cook et al., 2013 ; Savary et al., 2019 ; Bock et al., 2022 ). This relationship is influenced by various aspects in both abiotic and biotic environment, which can act individually or in combination (Yonow et al., 2019 ). These factors significantly impact the spatial distribution and severity of plant diseases (Garcia-Guzman et al., 2016 ; Esguera et al., 2024 ). Studies of the pathogenic variability of this pathogen will provide a better understanding of strain distribution and their pathogenicity. This information can then be used to guide the selection of crops for particular locations, thereby minimising the damage associated with this disease (Villa et al., 2020). In this study, we (i) assessed the distribution of black Sigatoka in subsistence farming systems of banana and plantain and (ii) determined the pathogenic variation among M. fijiensis strains collected from various locations in Benin. This information will help in making informed decisions for effective management of black Sigatoka. Materials and methods Field disease incidence and severity evaluation Disease incidence and the Disease Severity Index (DSI) were estimated between May and November 2022 for black Sigatoka in 17 districts located in the Guineo-Congolean climatic zone of Benin. This climatic area is characterised by bimodal rainfall, with two rainy seasons (April to July and September to November) and two dry seasons (November to March and July to September). The mean annual rainfall ranges from 900 mm in the west to 1300 mm in the east, with mean annual temperature of 27°C, and mean relative humidity of approximately 80% (Aho et al., 2018 ). A total of 114 plantations were surveyed across 57 study villages, averaging two plantations per village. In each plantation, 10 banana plants were randomly selected at the pre-flowering stage from a plot of 150 m². The number of leaves with lesions symptomatic of black Sigatoka per banana plant was counted. Each leaf was visually inspected and the stage of symptom development was noted. The severity of the disease was assessed using a scale of 0 to 6 based on classes proposed by Gauhl ( 1989 ): 0 = no symptoms; 1 = < 1% streak and/or fewer than 10 spots; 2 = 1 to 5%; 3 = 6 to 15%; 4 = 16 to 33%, 5 = 34 to 50%, and 6 = 51 to 100% of the leaf area with symptoms of black Sigatoka. The Disease Severity Index (DSI) for each plant was calculated using Gauhl's formula (1994): $$\:DSI=\frac{{\Sigma\:}\:\text{n}\text{b}}{(\text{N}-1)\text{T}}\:\text{x}\:100$$ where n = number of leaves in each grade, b = grade (0–6), N = number of grades used in the scale (7), T = total number of leaves scored. Fungal material A series of twelve surveys was carried out in the study area to collect necrotic leaves showing the black Sigatoka symptoms. The pathogen was isolated in the laboratory from necrotic banana leaves collected from 114 banana and plantain plantations using the monosporic method. Lesions classified as stage 3 or 4 identified on the underside of leaf fragments. Conidia were extracted from the target lesions through mechanical rubbing. These conidia were then cultured on agar-agar medium that had been previously poured into Petri dishes. A sample of the agar-agar medium containing the trapped conidia was mounted on a slide and examined under a light microscope. The conidia of the pathogen were carefully isolated one by one using a microscalpel, then seeded on PDA medium, and incubated at room temperature for about twelve days. Once the spores had germinated, successive purifications resulted in pure monospore colonies, which were stored in the freezer (Traoré, 2008 ). Pathogenicity of M. fijiensis isolates Plant material and trial design The Orishele was used as a susceptible banana genotype to assess the pathogenicity of the isolates of M. fijiensis . Plants at the five to six leaf stage, obtained by macropropagation, were used for screening under a greenhouse. The trial design was a completely randomised block design with four replicates. Treatments were the isolates of M. fijiensis . Inoculum preparation and plants inoculation The inoculum was prepared by culturing M. fijiensis isolates on sterile V8 growth medium in Petri dishes, which were then sealed and stored at 25°C. After 14 days of incubation, the mycelium developed on the surface of the culture medium was scraped off and ground in sterile distilled water. The ground material was filtered through an 80 µm mesh sieve to remove large fragments. The inoculum concentration was adjusted using a Malassez cell to a final concentration of 2.10 5 conidia/ml. A few drops of 0.5% gelatin were added to the final suspension of each isolate to allow good adhesion of the conidia to the leaves. The last two newly developed leaves of each plant were inoculated on the underside with 50 ml of inoculum. The inoculated plants were maintained in a greenhouse at 100% relative humidity for one week using a humidifier. A photoperiod of 12 h, with and day and night temperatures of 28°C and 25°C, respectively, was maintained (Abadie, 2008). After one week, the humidity was reduced to 80%. Plants were watered regularly as needed throughout the experimental period. Data collection Data were collected on the leaves of inoculated plants between the 10th and 50th day after pathogen inoculation, with samples taken every 2 days. The following parameters were assessed for each plant (Traoré, 2008 ) : Disease incubation time (DIT): this metric assesses the virulence of the isolates by measuring the time it takes for the first leaf lesions to appear. Three categories of virulence have been established: very virulent isolate: DIT ≤ 15 days; virulent isolate: 16 days ≤ DIT ≤ 19 days, and less virulent isolate: DIT > 20 days; Disease development time (DDT): it evaluates the aggressiveness of the isolate by measuring the time taken for the lesions to reach stage 5. Statistical analysis An analysis of variance based on linear normal distribution models was used to determine the factors associated with DSI, as the variables explained were normal. The lm function was used for this purpose. Student-Newman-Keuls (SNK) tests were used to separate the means of the different modalities. Box plots were used to illustrate the incubation and development times of the different isolates. Analysis was performed using R4.1.3 software. (R Core Team, 2022). Result Variation in the incidence of black Sigatoka in banana cropping systems, banana subgroups and areas of study Significantly variation (p < 0.0001) in the incidence of black Sigatoka among the three cropping systems such as home garden, banana monoculture and banana-associated cropping was observed (Table 1 ). Additionally, a significant difference (p < 0.05) was observed in DSI between the two banana subgroups (plantain and dessert banana) within the plantations and among the 17 districts. Table 1 DSI’s analysis of variance according to banana subgroups, cropping systems and districts df Sum Square Mean Square Prob Cropping systems 2 263.80 131.90 < 0.0001*** Banana Sub-group 1 35.99 35.99 0.0184* Districts 16 99.98 6 249 0.0465* Cropping systems x Banana sub-group 2 25 509 12 754 0.1644977 ns Cropping systems x district 14 86 388 6 171 0.4926847 ns Banana Sub-group x district 9 34 245 3 805 0.7539311 ns Error 12 218.83 6 057 ns = No significant; * Significant p-value at the 5% level; *** significant p-value at the 0.01% level The standard deviations of the dispersion of the data around the means are relatively low for all variables (Table 2 ), demonstrating the consistency of the results. Home garden (34.63 ± 0.61) and banana in association with other crops (34.63 ± 0.61) were the least susceptible to the disease and showed no difference in susceptibility to M. fijiensis . Monoculture system was the most susceptible system (38.25 ± 0.53). Plantain cultivars were also more resistant to M. fijiensis (35.57 ± 0.49) compared to the dessert banana subgroup, which was more susceptible to black Sigatoka (37.46 ± 0.90). The disease was more prevalent in Tori-Bossito (38.80 ± 1.68), though was not statistically different from those of Houeyogbe (38.64 ± 1.95), Dogbo (37.77 ± 1.95), Athieme (37.91 ± 1.51), Allada (37.47 ± 1.95), Cove (37.19 ± 1.95) and Comè (36.59 ± 1.68). Lokossa was the least affected by the disease, with DSI of 33.39 ± 1.95. Intermediate district affected by black Sigatoka have a DSI ranging from 34.93 ± 1.95 for Djidja to 35.49 ± 1.95 for Dangbo. Table 2 Black Sigatoga severity index (means ± standard errors) by banana cropping system, banana subgroup and areas of study Mean ± SE Min Max p-value Cropping systems 0,0184* Food intercropping system 33.64±0.74 b 28.71 36.15 Home garden system 34.64±0.61 b 31.43 40.96 Mono cropping system 38.26±0.53 a 32.58 44.20 Banana Sub-group Dessert banana 37.46±0.90 a 31.69 44.20 <0,0001*** Plantain 35.57±0.49 b 28.71 41.21 Districts Adja-ouere 35.05±1.95 b 31.69 37.26 Adjohoun 34.56±1.95 c 33.91 35.65 Allada 37.47±1.95 a 34.80 39.02 Athieme 37.91±1.51 a 33.58 43.12 Come 36.59±1.68 a 33.30 40.01 Cove 37.19±1.95 a 35.65 39.61 Dangbo 35.49±1.95 b 35.01 36.15 Djidja 34.93±1.95 b 32.30 37.30 0,0465* Dogbo 37.77±1.95 a 35.58 41.21 Houeyogbe 38.64±1.95 a 32.85 43.56 Lokossa 33.39±1.95 d 32.58 34.30 Ouinhi 35.48±1.95 b 29.98 44.20 Sakete 34.38±1.95 c 31.43 37.53 Toffo 34.39±1.68 c 33.02 37.52 Tori-Bossito 38.80±1.68 a 35.51 40.96 Zagnanado 34.28±1.95 c 28.71 38.56 Ze 34.34±1.68 c 33.42 35.69 * Significant p-value at the 5% level; *** significant p-value at the 0.01% level; The means with the same alphabetic letters are not significantly different (p>0.05) according to the Newman-Keuls test; SE=Stantard Error Virulence The variation in the ability of M. fijiensis isolates to infect hosts and cause disease (virulence) was assessed based on their origin (Fig. 1 ). The results revealed significant variability in virulence among isolates from the different districts in the study, as determined by the Kruskal-Walli’s test (p < 0.0001). Specifically, isolates from the districts of Dogbo, Houeyogbe, Zagnanado and Ouinhi had the longest incubation period, varying between 15.66 days (Houeyogbe) and 16.56 days (Zagnanado), and were therefore the least virulent. The most virulent isolates were sourced from Djidja, Allada, Tori-Bossito, Athieme, Ze, Adja-Ouere, Sakete, Adjohoun and Dangbo, with the shortest average incubation times, ranging from 11.75 days (Djidja) to 12.58 days at Toffo (Fig. 2 ). Aggressiveness The variation in damage caused to banana plants by M. fijiensis isolates depending on their origin, which is reflected in the aggressiveness of the pathogen, measured as the pathogenicity factor. The analysis of the variation in this factor (Fig. 3 ) indicates significant variability in aggressiveness among isolates from the different townships, as determined by the Kruskal-Wallis’s test (p < 0.0001). (p < 0.0001). Additionally, M. fijiensis isolates from the commune of Houeyogbe had the longest average disease development time at 47.08 days and were therefore the least aggressive. Similarly, the isolates from Zagnanado and Lokossa were also among the least aggressive isolates, with the mean disease development times of 46.56 and 45.66 days, respectively. In contrast, the most aggressive isolates were found in the districts of Dangbo and Djidja, with an average disease development time of 40.8 days and 40.83 days, respectively. Correlation between aggressiveness and virulence of M. fijiensis isolates The correlation between aggressiveness and virulence of M. fijiensis isolates was illustrated by the Fig. 4 . The regression coefficient is highly significant (p-value < 0.0001), this indicates a strong linear relationship between the time taken to develop the disease and the incubation time of the disease. In fact, an average of 0.7561 units increase in disease development time was observed with one unit increase in incubation time. Discussion In this study, the variability of black Sigatoka incidence was assessed in relation to cropping systems, Musa subgroups and locations. This phytopathometry quantifies plant disease intensity for many different purposes including monitoring epidemics, understanding yield loss, comparing phenotypes for disease resistance, and evaluating effects of treatments (Bock et al. 2022 ). An examination of black Sigatoka incidence among smallholder banana and plantain-based farms across the Guineo-Gongolean zone of Benin Republic showed that the incidence of this disease varied between banana and plantain-based cropping systems. Three banana and plantain cropping systems were previously identified in the study area: (1) food intercropping system, which is by far the most common system adopted by farmers, (2) the monoculture system and (3) the home garden system (Togbe et al., 2024 ). The severe attack by M. fijiensis observed in the monoculture system is the results of an establishment of a medium with a prevailing environment favorable to the development of diseases (Kwa & Temple, 2019 ). This system involves a high planting density of between 1,667 and 2,500 plants per hectare (N'guetta et al., 2016), which provides a humid microclimate that is favourable to the biology of the pathogen (Yonow et al., 2019 ). Also, the susceptibility of monoculture systems to plant diseases results from reduced varieties number involved in the design of the systems, which are therefore genetically very uniform (Soarez et al., 2021). As a result, many crops have become much more susceptible to both established and emerging fungal strains (Leonel et al., 2024 ). This finding confirms the conclusions reported in several studies across countries with industrial-scale monoculture Cavendish plantations in Latin America, Africa and India, where this system is still predominant for economic reasons (Bellamy, 2013 ; Drenth and Kema, 2021; Ceresini et al., 2024 ). Research is increasingly focused on alternative banana-based systems for sustainable production due to the significant impacts of monoculture on biodiversity, which often involves removing natural vegetation and planting extensive areas with a single crop (Nwaogu and Cherubin, 2024 ). This cropping system can deplete soil nutrients, heighten susceptibility to pests and diseases, and increase a reliance on chemical inputs (Norhan et al., 2018 ), leading to negative environmental and agricultural consequences (Nwaogu and Cherubin, 2024 ). With this in mind, de Fouré and de Lapeyre de Bellaire (2020) advise against the establishment of Cavendish-based monoculture banana plantations, which are highly susceptible to black Sigatoka, and prevalent in the banana industry. The authors proposed promoting and introducing planting materials that are more resistant to black Sigatoka observed in Musa and have proven effective in several countries. Evidence suggests a potential adaptation of M. fijiensis to resistant cultivars, which can inform the design of more resilient agrosystems (Kimunye et al., 2021 ). Although banana monoculture is not widespread in Benin, with about 10.8% of plantations (Togbe et al., 2024 ), the current national agricultural policy promotes banana and plantain as diversification products, which have benefited from significant technical support in recent years through research projects and government funding. In the future, this national policy could lead to wider adoption of the monoculture system at the expense of the more dominant (65.5%) food intercropping system in the area of study (Togbe et al., 2024 ) among Beninese farmers. The present study showed that attacks by M . fijiensis were less significant on food intercropping system and home garden system, which support several authors' arguments for the sustainability of these systems. For this purpose, Bakshi et al. ( 2019 ) showed that, this multiple cropping system enhances biodiversity favourable for emergency of natural enemies of pests and diseases. Specifically, Crespo-Clas et al. ( 2024 ) have established the link between biological diversity within diversified cropping systems under banana and the richness of the rhizobacterial consortium. The authors have shown that their use can significantly reduce black Sigatoka incidence and enhance banana plants’ chlorophyll content and fruit production. As for Li et al. ( 2020 ), intercropping of banana with Allium tuberosum plants has shown a potential to reduce Panama disease caused by Fusarium oxysporum f. sp. cubense race 4. The susceptibility of various banana cultivars to black Sigatoka, compared to plantain cultivars, has been noted by several authors (Sánchez Timm et al., 2016 ; Aher, et al., 2024 ). This aligns with the findings of Kimunye et al. ( 2021 ), who reported that the B genome (BB, AB, AAB, ABB) was responsible for black Sigatoka resistance in some accessions, especially plantains with the AAB genomic formula. Most of banana and plantain cultivars are hybrids of the two wild diploid species Musa acuminata Colla (genome A) and M. balbisiana Colla (genome B). These crosses resulted in a series of diploids, triploids and tetraploids with genomic groups classified as AA, AB, AAA, AAB, ABB, AABB, AAAB and ABBB (Simmonds and Shepherd, 1955). This diversity in Musa is present in Benin (Chabi et al., 2018 ; Ahohouendo et al., 2022 ) and explains the variability in susceptibility to black Sigatoka observed in the present study. However, the susceptibility of a cultivar is not strictly linked to its genomic formula. Sources of resistance can also be found in diploids (AA). Previous reports of banana genotypes showing resistant and moderately resistant characteristics to black Sigatoka were mainly from diploid genome AA and triploid genome (AAB) (Soares et al., 2021 ). This is the case, for example, with the Namarai (AA) cultivar, which is resistant to black Sigatoka (Aher, et al., 2024 ). There may be other unique genes or enzymes involved in black Sigatoka resistance in these genotypes. These may include genes associated with jasmonic acid and ethylene signaling, transcription factors, phenylpropanoid pathways, antioxidants and pathogenesis-related proteins, and pathogenesis-related proteins (Soares et al. 2021 ). However, it should be noted that the efficiency of plant resistance to fungal pathogen is expected to decrease over time, due to their evolution with an increase in the frequency of virulent or highly aggressive strains (Suffers et al., 2017). In this study, three parameters were used to analyze the pathological traits of M. fijiensis . The first parameter, the number of disease units, indicates the disease severity as measured in the field. This parameter showed variability in severity indexes depending on the banana and plantain production zone. The second and third parameters measured were aggressiveness and virulence of the pathogen isolates, which were found to be highly correlated. These measurements provide insights into, the population structure of M. fijiensis in our study area. These results confirmed the variability in the distribution observed in the subsistence banana production systems of Benin. Virulence is the qualitative aspect that expresses the ability of a pathogen to infect a host and cause disease. Aggressiveness is the quantitative component that measures the extent of damage caused to the host by the pathogen's attack (Lannou 2012 ; Dutta et al., 2021). Notably, significant variability in the evaluated parameters was sometimes recorded between neighboring districts. For instance, Houeyogbe and Lokossa, although they were very close to each other, respective DSI values of 38.64 ± 1.95 and 33.39 ± 1.95 were recorded. Several authors have addressed the reasons for this pathogenic disparity in the geographical distribution of plant diseases. These include that the geographic distribution of fungal plant pathogens is influenced by several parameters: crop management, climatic, biotic and other environmental factors, as well as their host distribution and susceptibility levels (Borer et al., 2016 ). For example, local plant community structure and diversity may support different levels of plant pathogen diversity by favouring specialist or generalist pathogens or by reducing the density of susceptible hosts (Bever et al., 2015 ). Finally, this study focused on investigating factors governing the black Sigatoka incidence and severity attack variation in the subsistence farming systems of banana and plantain in Benin. Black Sigatoka incidence and severity attacks are higher in monoculture systems based on dessert banana than in more diversified systems of banana and plantain and/or other associated crops. This study has also revealed that virulence and aggressiveness varied according to the area in which M. fijienis isolates were collected. The information provided by this study in the main banana-producing areas of Benin will help to improve the banana production system by designing more resilient models of banana agroecological farming systems. In fact, banana and plantain have become priorities for development and agricultural diversification providing means of nutritional security in the Republic of Benin. By utilizing this information, farmers can enhance their current management methods and reduce the economic losses resulting from black Sigatoka disease outbreaks, thereby contributing to the long-term sustainability of banana and plantain production systems and ensuring food security. Declarations On behalf of all authors, the corresponding author states that there is no conflict of interest. Authors’ contribution Conceptualization: FAA; methodology: FAA, ECT; writing-original draft preparation: FAA; writing-review and editing: FAA, VIAE, RAA, ECT; visualization: FAA, VIAE, ECT; project administration: BCA; funding acquisition, FAA, ECT, BCA; Curation and Formal Analysis: RA. All authors have read and agreed to the published version of the manuscript. Data availability statement The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Funding This research was funding by " Agence Universitaire de la Francophonie (AUF)" and International Foundation for Science (IFS) under the grants N° DRAO-2017-U-S0531PRS20803 and N° 1I3_C_041413 respectively. References Abadie C, Apater MZ, Ignolet LP, Arlier JC, & Ourichon XM (2008) Artificial inoculation on plants and banana leaf pieces with Mycosphaerella spp ., responsible for Sigatoka leaf spot diseases. Fruits , 63(5), 319–323. https://doi.org/10.1051/fruits Aher A, Dethe A, Chavhan R, Hinge V, Dhutraj S (2024) Molecular elucidation of sigatoka disease resistance in diverse banana ( Musa spp.) genotypes using molecular markers and genetic diversity analysis. Sc. 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Sci., 1214, 012018. https://doi.org/10.1088/1755-1315/1214/1/012018 Nwaogu C, and Cherubin MR (2024) Integrated Agricultural Systems: The 21st Century Nature-Based Solution for Resolving the FEEEs Challenges. Adv. Agron. 185, 1–73. https://doi.org/10.1016/bs.agron.2024.02.003 Pinzón-Núñez AM, Feria-Gómez DF, Pérez-Ochoa GM, Arango-Palacio L, Rey-Valenzuela VE, Hoyos-Carvajal L, Zapata-Henao S (2024) New standard area diagram set for assessing black sigatoka in bananas. Eur J Plant Pathol., 170 :535–548. https://doi.org/10.1007/s10658-024-02917-x Rhodes P (1964) A new banana disease in Fiji. Commonwealth Phytopathol. News, 10, 38–41. Robert S, Ravigne V, Zapater MF, Abadie C, & Carlier J (2012) Contrasting introduction scenarios among continents in the worldwide invasion of the banana fungal pathogen Mycosphaerella fijiensis . Molecul. Ecol. , 21(5), 1098–1114. https://doi.org/10.1111/j.1365-294X.2011.05432.x Sánchez Timm E, Hidalgo Pardo L, Pacheco Coello R, Chávez Navarrete T, Navarrete Villegas O, Santos Ordóñez E (2016) Identification of Differentially-Expressed Genes in Response to Mycosphaerella fijiensis in the Resistant Musa Accession ‘Calcutta-4’ Using Suppression Subtractive Hybridization. PLoS ONE 11(8) : e0160083. doi: 10.1371/journal.pone.0160083 Savary S, Willocquet L, Pethybridge SJ. Esker P, McRoberts N, Nelson A (2019) The global burden of pathogens and pests on major food crops. Nat Ecol Evol 3, 430–439 (2019). https://doi.org/10.1038/s41559-018-0793-y Soares JMS, Rocha AJ, Nascimento FS, Santos AS, Miller RNG, Ferreira CF, Haddad F, Amorim V BO, & Amorim EP (2021) Genetic Improvement for Resistance to Black Sigatoka in Bananas : A Systematic Review. Front. Plant Sci . , 12(4), 1–15. https://doi.org/10.3389/fpls.2021.657916 Strobl E, and Mohan, P (2020) Climate and the Global Spread and Impact of Bananas’ Black Leaf Sigatoka Disease. Atmos., 11, 947 ; doi :10.3390/atmos11090947 Suffert F, Goyeau H, Sache I, Carpentier F, Gélisse S, Morais D, Delestre G (2017) Epidemiological trade-off between intra and interannual scales in the evolution of aggressiveness in a local plant pathogen population. Evol. Appl. 11 :768-780. DOI : 10.1111/eva.12588 Togbe CE, Ahohouendo FA, Badou AA, Kpenavoun-Chogou S, Ahohuendo BC (2024) Diversity in agricultural practices among smallholder plantain-based farms across the Guineo-Gongolean zone of Benin Republic, JARTS, Vol. 125 No.2, 175-184. https://doi.org/10.17170/kobra-2024093010892 Traoré, S. (2008). Contribution à l’étude de comportement d’hybrides de bananiers de dessert et de bananiers plantain ( Musa sp.) Vis-a-vis des parasites foliaires ( Mycosphaerella spp., Cladosporium musae) et racinaires ( Zythia Sp., Radopholus similis, Pratylenchus coffeae ). Thèse de doctorat. Université de Cocody Abidjan. Cote d’ivoire. 326p Tuo S, Amari L-N, Cherif M, Ouedraogo SL, Kassi F, Kouame KG, Camara B, & Kone D (2017) Agronomic Performance of Plantain Cultivars ( Musa spp.) in Efficient Mixing Situation for the Control of Black Sigatoka in Southern Côte d’Ivoire. Asian J. Plant Pathol., 11(1), 1–9. https://doi.org/10.3923/ajppaj.2017.1.9 Villa JE, Horita M, Hyakumachi M, Tsuchiya K (2021) Pathogenic and genetic variability of Ralstonia solanacearum strains from the Philippines. Plant Pathol. ; 70 :544–554. https://doi.org/10.1111/ppa.13304k Yonow T, Ramirez-Villegas J, Abadie C, Darnell RE, Ota N, & Kriticos DJ (2019) Black Sigatoka in bananas : Ecoclimatic suitability and disease pressure assessments. 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2","display":"","copyAsset":false,"role":"figure","size":522146,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMycosphaerella fijiensis\u003c/em\u003e virulence distribution map in study area\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7584680/v1/4e1f72439e2d492c79d38f0b.png"},{"id":93623420,"identity":"26c20027-53e2-4d65-b8bf-e64d251dff67","added_by":"auto","created_at":"2025-10-15 18:29:38","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":37967,"visible":true,"origin":"","legend":"\u003cp\u003eBox plot showing the aggressiveness estimation of \u003cem\u003eM. fijiensis \u003c/em\u003eisolates based on their townships of origin\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7584680/v1/b573d4ade7e0bbc0227eaf2d.png"},{"id":93623422,"identity":"c6e0525e-394c-4838-bf15-28a4445d86da","added_by":"auto","created_at":"2025-10-15 18:29:38","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":221841,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between virulence and agressiveness of \u003cem\u003eM. fijiensis\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7584680/v1/03600a40de6377417a538962.png"},{"id":93623978,"identity":"2ed07f18-e562-4ca8-83b4-3a201bbef401","added_by":"auto","created_at":"2025-10-15 18:45:39","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1583317,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7584680/v1/a0a4e30e-ba23-443d-ae7f-228dc9d93def.pdf"}],"financialInterests":"","formattedTitle":"Analysis of distribution and pathogenesis of Mycosphaerella fijiensis, in subsistence farming systems of banana and plantain in Benin","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBlack Sigatoka, also known as black leaf streak disease, caused by pathogenic fungus \u003cem\u003eMycosphaerella fijiensis\u003c/em\u003e Morelet, [anamorph: \u003cem\u003ePseudocercospora fijiensis\u003c/em\u003e Deighton], is one of the most devastating diseases of banana and plantain (Kimunye et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Pinz\u0026oacute;n‑N\u0026uacute;\u0026ntilde;ez, 2024) which have co-evolved with \u003cem\u003eMusa\u003c/em\u003e for the last 13\u0026nbsp;million years (Arcila-Galvis et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The causal agent is firstly reported on Sigatoka Valley, Fijian island at Viti Levu in 1963 (Rhodes, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e1964\u003c/span\u003e). Since its discovery, the disease has continued to spread into new regions. This disease was accidentally introduced in Africa from Gabon in 1978 (Frossard, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1980\u003c/span\u003e), and has spread to all African countries (Blomme et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) including Benin where it was reported for the first time in 1993 (Jones \u0026amp; Mourichon, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). It attacks the leaves where more or less severe necrotic lesions are generally reported, thus causing premature senescence of the leaves (Castelan et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). This necrosis causes direct and indirect losses (Churchill, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), as they reduce the photosynthetic leaf area of the plant (Etebu \u0026amp; Wabiye, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Direct losses are estimated to be between 20 and 50% of production, or even 100% from the second cycle onwards. These losses are attributed to poorly filled fruit, smaller bunches and low weights (Tuo et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Indirect losses are associated with a reduction in fruit green life after harvest, premature fruit ripening, uneven fruit colouring, reduced pulp clarity and altered fruit taste (Castelana et al., 2012; Chillet et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), making them unsuitable for sale and consumption (Arango Isaza et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eAlthough \u003cem\u003eM. fijiensis\u003c/em\u003e is considered a very prolific pathogen in all banana and plantain-producing countries, the disease continues to occupy new ecological niches (Robert et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e) where it is prevalent, particularly in industrial banana production systems characterized by monoculture over large areas (Strobl and Mohan, \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This cropping system is not widespread in Benin; it accounts for about 11% of banana and plantain production. The rest of the plantations are mostly smallholdings where bananas and plantains are either grown in association with food crops or in the home garden system, which is used by 64.28% and 24.72% of banana and plantain producers in Benin, respectively (Togb\u0026eacute; et al., 2024). These cropping systems are also subject to more or less severe attacks by black Sigatoka, causing damage with high economic impact due to the non-existence or inadequacy of control methods (Ahohouendo et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eUnderstanding the damage caused by pathogens to their hosts is a central focus of plant pathology. This is particularly important for cultivated plants such as banana and plantain (Cook et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) which are essential components of the diet for populations in West and Central Africa. These crops play a crucial role in addressing food security challenge in the region (Folefack et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The relationships between the degree of symptom and yield loss on plants has been well established by several authors (Cook et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Savary et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bock et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This relationship is influenced by various aspects in both abiotic and biotic environment, which can act individually or in combination (Yonow et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These factors significantly impact the spatial distribution and severity of plant diseases (Garcia-Guzman et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Esguera et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Studies of the pathogenic variability of this pathogen will provide a better understanding of strain distribution and their pathogenicity. This information can then be used to guide the selection of crops for particular locations, thereby minimising the damage associated with this disease (Villa et al., 2020).\u003c/p\u003e\u003cp\u003eIn this study, we (i) assessed the distribution of black Sigatoka in subsistence farming systems of banana and plantain and (ii) determined the pathogenic variation among \u003cem\u003eM. fijiensis\u003c/em\u003e strains collected from various locations in Benin. This information will help in making informed decisions for effective management of black Sigatoka.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eField disease incidence and severity evaluation\u003c/h2\u003e\u003cp\u003eDisease incidence and the Disease Severity Index (DSI) were estimated between May and November 2022 for black Sigatoka in 17 districts located in the Guineo-Congolean climatic zone of Benin. This climatic area is characterised by bimodal rainfall, with two rainy seasons (April to July and September to November) and two dry seasons (November to March and July to September). The mean annual rainfall ranges from 900 mm in the west to 1300 mm in the east, with mean annual temperature of 27\u0026deg;C, and mean relative humidity of approximately 80% (Aho et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). A total of 114 plantations were surveyed across 57 study villages, averaging two plantations per village. In each plantation, 10 banana plants were randomly selected at the pre-flowering stage from a plot of 150 m\u0026sup2;. The number of leaves with lesions symptomatic of black Sigatoka per banana plant was counted. Each leaf was visually inspected and the stage of symptom development was noted. The severity of the disease was assessed using a scale of 0 to 6 based on classes proposed by Gauhl (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e1989\u003c/span\u003e): 0\u0026thinsp;=\u0026thinsp;no symptoms; 1\u0026thinsp;=\u0026thinsp;\u0026lt;\u0026thinsp;1% streak and/or fewer than 10 spots; 2\u0026thinsp;=\u0026thinsp;1 to 5%; 3\u0026thinsp;=\u0026thinsp;6 to 15%; 4\u0026thinsp;=\u0026thinsp;16 to 33%, 5\u0026thinsp;=\u0026thinsp;34 to 50%, and 6\u0026thinsp;=\u0026thinsp;51 to 100% of the leaf area with symptoms of black Sigatoka. The Disease Severity Index (DSI) for each plant was calculated using Gauhl's formula (1994):\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$\\:DSI=\\frac{{\\Sigma\\:}\\:\\text{n}\\text{b}}{(\\text{N}-1)\\text{T}}\\:\\text{x}\\:100$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ewhere n\u0026thinsp;=\u0026thinsp;number of leaves in each grade, b\u0026thinsp;=\u0026thinsp;grade (0\u0026ndash;6), N\u0026thinsp;=\u0026thinsp;number of grades used in the scale (7), T\u0026thinsp;=\u0026thinsp;total number of leaves scored.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eFungal material\u003c/h3\u003e\n\u003cp\u003eA series of twelve surveys was carried out in the study area to collect necrotic leaves showing the black Sigatoka symptoms. The pathogen was isolated in the laboratory from necrotic banana leaves collected from 114 banana and plantain plantations using the monosporic method. Lesions classified as stage 3 or 4 identified on the underside of leaf fragments. Conidia were extracted from the target lesions through mechanical rubbing. These conidia were then cultured on agar-agar medium that had been previously poured into Petri dishes. A sample of the agar-agar medium containing the trapped conidia was mounted on a slide and examined under a light microscope. The conidia of the pathogen were carefully isolated one by one using a microscalpel, then seeded on PDA medium, and incubated at room temperature for about twelve days. Once the spores had germinated, successive purifications resulted in pure monospore colonies, which were stored in the freezer (Traor\u0026eacute;, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003ePathogenicity of\u003c/b\u003e \u003cb\u003eM. fijiensis\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e\n\u003ch3\u003ePlant material and trial design\u003c/h3\u003e\n\u003cp\u003eThe Orishele was used as a susceptible banana genotype to assess the pathogenicity of the isolates of \u003cem\u003eM. fijiensis\u003c/em\u003e. Plants at the five to six leaf stage, obtained by macropropagation, were used for screening under a greenhouse. The trial design was a completely randomised block design with four replicates. Treatments were the isolates of \u003cem\u003eM. fijiensis\u003c/em\u003e.\u003c/p\u003e\n\u003ch3\u003eInoculum preparation and plants inoculation\u003c/h3\u003e\n\u003cp\u003eThe inoculum was prepared by culturing \u003cem\u003eM. fijiensis\u003c/em\u003e isolates on sterile V8 growth medium in Petri dishes, which were then sealed and stored at 25\u0026deg;C. After 14 days of incubation, the mycelium developed on the surface of the culture medium was scraped off and ground in sterile distilled water. The ground material was filtered through an 80 \u0026micro;m mesh sieve to remove large fragments. The inoculum concentration was adjusted using a Malassez cell to a final concentration of 2.10\u003csup\u003e5\u003c/sup\u003e conidia/ml. A few drops of 0.5% gelatin were added to the final suspension of each isolate to allow good adhesion of the conidia to the leaves. The last two newly developed leaves of each plant were inoculated on the underside with 50 ml of inoculum. The inoculated plants were maintained in a greenhouse at 100% relative humidity for one week using a humidifier. A photoperiod of 12 h, with and day and night temperatures of 28\u0026deg;C and 25\u0026deg;C, respectively, was maintained (Abadie, 2008). After one week, the humidity was reduced to 80%. Plants were watered regularly as needed throughout the experimental period.\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eData were collected on the leaves of inoculated plants between the 10th and 50th day after pathogen inoculation, with samples taken every 2 days. The following parameters were assessed for each plant (Traor\u0026eacute;, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) :\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eDisease incubation time (DIT): this metric assesses the virulence of the isolates by measuring the time it takes for the first leaf lesions to appear. Three categories of virulence have been established: very virulent isolate: DIT\u0026thinsp;\u0026le;\u0026thinsp;15 days; virulent isolate: 16 days\u0026thinsp;\u0026le;\u0026thinsp;DIT\u0026thinsp;\u0026le;\u0026thinsp;19 days, and less virulent isolate: DIT\u0026thinsp;\u0026gt;\u0026thinsp;20 days;\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eDisease development time (DDT): it evaluates the aggressiveness of the isolate by measuring the time taken for the lesions to reach stage 5.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eAn analysis of variance based on linear normal distribution models was used to determine the factors associated with DSI, as the variables explained were normal. The lm function was used for this purpose. Student-Newman-Keuls (SNK) tests were used to separate the means of the different modalities. Box plots were used to illustrate the incubation and development times of the different isolates. Analysis was performed using R4.1.3 software. (R Core Team, 2022).\u003c/p\u003e\u003c/div\u003e"},{"header":"Result","content":"\u003cp\u003e\u003cb\u003eVariation in the incidence of black Sigatoka in banana cropping systems, banana subgroups and areas of study\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSignificantly variation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001) in the incidence of black Sigatoka among the three cropping systems such as home garden, banana monoculture and banana-associated cropping was observed (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, a significant difference (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) was observed in DSI between the two banana subgroups (plantain and dessert banana) within the plantations and among the 17 districts.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDSI\u0026rsquo;s analysis of variance according to banana subgroups, cropping systems and districts\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003edf\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSum Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMean Square\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eProb\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCropping systems\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e263.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e131.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.0001***\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBanana Sub-group\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0184*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDistricts\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e99.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 249\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.0465*\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCropping systems x Banana sub-group\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 509\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 754\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.1644977\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCropping systems x district\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 388\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.4926847\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBanana Sub-group x district\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e34 245\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3 805\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.7539311\u003csup\u003ens\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eError\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e218.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6 057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003ens\u0026thinsp;=\u0026thinsp;No significant; * Significant p-value at the 5% level; *** significant p-value at the 0.01% level\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe standard deviations of the dispersion of the data around the means are relatively low for all variables (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), demonstrating the consistency of the results. Home garden (34.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61) and banana in association with other crops (34.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61) were the least susceptible to the disease and showed no difference in susceptibility to \u003cem\u003eM. fijiensis\u003c/em\u003e. Monoculture system was the most susceptible system (38.25\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53). Plantain cultivars were also more resistant to \u003cem\u003eM. fijiensis\u003c/em\u003e (35.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49) compared to the dessert banana subgroup, which was more susceptible to black Sigatoka (37.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90). The disease was more prevalent in Tori-Bossito (38.80\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68), though was not statistically different from those of Houeyogbe (38.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95), Dogbo (37.77\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95), Athieme (37.91\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51), Allada (37.47\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95), Cove (37.19\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95) and Com\u0026egrave; (36.59\u0026thinsp;\u0026plusmn;\u0026thinsp;1.68). Lokossa was the least affected by the disease, with DSI of 33.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95. Intermediate district affected by black Sigatoka have a DSI ranging from 34.93\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95 for Djidja to 35.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95 for Dangbo.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Black Sigatoga severity index (means \u0026plusmn; standard errors) by banana cropping system, banana subgroup and areas of study\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMin\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMax\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCropping systems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;0,0184*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eFood intercropping system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e33.64\u0026plusmn;0.74\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e28.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e36.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eHome garden system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.64\u0026plusmn;0.61\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e31.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e40.96\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eMono cropping system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e38.26\u0026plusmn;0.53\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e32.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e44.20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBanana Sub-group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eDessert banana\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e37.46\u0026plusmn;0.90\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e31.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;44.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026lt;0,0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003ePlantain\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e35.57\u0026plusmn;0.49\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e28.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e41.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"bottom\" style=\"width: 526px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistricts\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eAdja-ouere\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e35.05\u0026plusmn;1.95\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e31.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e37.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eAdjohoun\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.56\u0026plusmn;1.95\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e33.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e35.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eAllada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e37.47\u0026plusmn;1.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e34.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e39.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eAthieme\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e37.91\u0026plusmn;1.51\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e33.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e43.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eCome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e36.59\u0026plusmn;1.68\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e33.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e40.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eCove\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e37.19\u0026plusmn;1.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e35.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e39.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eDangbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e35.49\u0026plusmn;1.95\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e35.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e36.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eDjidja\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.93\u0026plusmn;1.95\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e32.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e37.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;0,0465*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eDogbo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e37.77\u0026plusmn;1.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e35.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e41.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eHoueyogbe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e38.64\u0026plusmn;1.95\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e32.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e43.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eLokossa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e33.39\u0026plusmn;1.95\u003csup\u003ed\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e32.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e34.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eOuinhi\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e35.48\u0026plusmn;1.95\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e29.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e44.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eSakete\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.38\u0026plusmn;1.95\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e31.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e37.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eToffo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.39\u0026plusmn;1.68\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e33.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e37.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eTori-Bossito\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e38.80\u0026plusmn;1.68\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e35.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e40.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eZagnanado\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.28\u0026plusmn;1.95\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e28.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e38.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 198px;\"\u003e\n \u003cp\u003eZe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 111px;\"\u003e\n \u003cp\u003e34.34\u0026plusmn;1.68\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 50px;\"\u003e\n \u003cp\u003e33.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 74px;\"\u003e\n \u003cp\u003e35.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e* Significant p-value at the 5% level; *** significant p-value at the 0.01% level; The means with the same alphabetic letters are not significantly different (p\u0026gt;0.05) according to the Newman-Keuls test; SE=Stantard Error\u003c/p\u003e\n\u003ch3\u003eVirulence\u003c/h3\u003e\n\u003cp\u003eThe variation in the ability of \u003cem\u003eM. fijiensis\u003c/em\u003e isolates to infect hosts and cause disease (virulence) was assessed based on their origin (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The results revealed significant variability in virulence among isolates from the different districts in the study, as determined by the Kruskal-Walli\u0026rsquo;s test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Specifically, isolates from the districts of Dogbo, Houeyogbe, Zagnanado and Ouinhi had the longest incubation period, varying between 15.66 days (Houeyogbe) and 16.56 days (Zagnanado), and were therefore the least virulent. The most virulent isolates were sourced from Djidja, Allada, Tori-Bossito, Athieme, Ze, Adja-Ouere, Sakete, Adjohoun and Dangbo, with the shortest average incubation times, ranging from 11.75 days (Djidja) to 12.58 days at Toffo (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eAggressiveness\u003c/h2\u003e\u003cp\u003eThe variation in damage caused to banana plants by \u003cem\u003eM. fijiensis\u003c/em\u003e isolates depending on their origin, which is reflected in the aggressiveness of the pathogen, measured as the pathogenicity factor. The analysis of the variation in this factor (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) indicates significant variability in aggressiveness among isolates from the different townships, as determined by the Kruskal-Wallis\u0026rsquo;s test (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Additionally, \u003cem\u003eM. fijiensis\u003c/em\u003e isolates from the commune of Houeyogbe had the longest average disease development time at 47.08 days and were therefore the least aggressive. Similarly, the isolates from Zagnanado and Lokossa were also among the least aggressive isolates, with the mean disease development times of 46.56 and 45.66 days, respectively. In contrast, the most aggressive isolates were found in the districts of Dangbo and Djidja, with an average disease development time of 40.8 days and 40.83 days, respectively.\u003c/p\u003e\u003cp\u003e\u003cb\u003eCorrelation between aggressiveness and virulence of\u003c/b\u003e \u003cb\u003eM. fijiensis\u003c/b\u003e \u003cb\u003eisolates\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe correlation between aggressiveness and virulence of \u003cem\u003eM. fijiensis\u003c/em\u003e isolates was illustrated by the Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. The regression coefficient is highly significant (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.0001), this indicates a strong linear relationship between the time taken to develop the disease and the incubation time of the disease. In fact, an average of 0.7561 units increase in disease development time was observed with one unit increase in incubation time.\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the variability of black Sigatoka incidence was assessed in relation to cropping systems, \u003cem\u003eMusa\u003c/em\u003e subgroups and locations. This phytopathometry quantifies plant disease intensity for many different purposes including monitoring epidemics, understanding yield loss, comparing phenotypes for disease resistance, and evaluating effects of treatments (Bock et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). An examination of black Sigatoka incidence among smallholder banana and plantain-based farms across the Guineo-Gongolean zone of Benin Republic showed that the incidence of this disease varied between banana and plantain-based cropping systems. Three banana and plantain cropping systems were previously identified in the study area: (1) food intercropping system, which is by far the most common system adopted by farmers, (2) the monoculture system and (3) the home garden system (Togbe et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). The severe attack by \u003cem\u003eM. fijiensis\u003c/em\u003e observed in the monoculture system is the results of an establishment of a medium with a prevailing environment favorable to the development of diseases (Kwa \u0026amp; Temple, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This system involves a high planting density of between 1,667 and 2,500 plants per hectare (N'guetta et al., 2016), which provides a humid microclimate that is favourable to the biology of the pathogen (Yonow et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Also, the susceptibility of monoculture systems to plant diseases results from reduced varieties number involved in the design of the systems, which are therefore genetically very uniform (Soarez et al., 2021). As a result, many crops have become much more susceptible to both established and emerging fungal strains (Leonel et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This finding confirms the conclusions reported in several studies across countries with industrial-scale monoculture Cavendish plantations in Latin America, Africa and India, where this system is still predominant for economic reasons (Bellamy, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Drenth and Kema, 2021; Ceresini et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Research is increasingly focused on alternative banana-based systems for sustainable production due to the significant impacts of monoculture on biodiversity, which often involves removing natural vegetation and planting extensive areas with a single crop (Nwaogu and Cherubin, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This cropping system can deplete soil nutrients, heighten susceptibility to pests and diseases, and increase a reliance on chemical inputs (Norhan et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), leading to negative environmental and agricultural consequences (Nwaogu and Cherubin, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). With this in mind, de Four\u0026eacute; and de Lapeyre de Bellaire (2020) advise against the establishment of Cavendish-based monoculture banana plantations, which are highly susceptible to black Sigatoka, and prevalent in the banana industry. The authors proposed promoting and introducing planting materials that are more resistant to black Sigatoka observed in \u003cem\u003eMusa\u003c/em\u003e and have proven effective in several countries. Evidence suggests a potential adaptation of \u003cem\u003eM. fijiensis\u003c/em\u003e to resistant cultivars, which can inform the design of more resilient agrosystems (Kimunye et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Although banana monoculture is not widespread in Benin, with about 10.8% of plantations (Togbe et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e), the current national agricultural policy promotes banana and plantain as diversification products, which have benefited from significant technical support in recent years through research projects and government funding. In the future, this national policy could lead to wider adoption of the monoculture system at the expense of the more dominant (65.5%) food intercropping system in the area of study (Togbe et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) among Beninese farmers.\u003c/p\u003e\u003cp\u003eThe present study showed that attacks by \u003cem\u003eM\u003c/em\u003e. \u003cem\u003efijiensis\u003c/em\u003e were less significant on food intercropping system and home garden system, which support several authors' arguments for the sustainability of these systems. For this purpose, Bakshi et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) showed that, this multiple cropping system enhances biodiversity favourable for emergency of natural enemies of pests and diseases. Specifically, Crespo-Clas et al. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) have established the link between biological diversity within diversified cropping systems under banana and the richness of the rhizobacterial consortium. The authors have shown that their use can significantly reduce black Sigatoka incidence and enhance banana plants\u0026rsquo; chlorophyll content and fruit production. As for Li et al. (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), intercropping of banana with \u003cem\u003eAllium tuberosum\u003c/em\u003e plants has shown a potential to reduce Panama disease caused by \u003cem\u003eFusarium oxysporum\u003c/em\u003e f. sp. \u003cem\u003ecubense\u003c/em\u003e race 4.\u003c/p\u003e\u003cp\u003eThe susceptibility of various banana cultivars to black Sigatoka, compared to plantain cultivars, has been noted by several authors (S\u0026aacute;nchez Timm et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Aher, et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). This aligns with the findings of Kimunye et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), who reported that the B genome (BB, AB, AAB, ABB) was responsible for black Sigatoka resistance in some accessions, especially plantains with the AAB genomic formula. Most of banana and plantain cultivars are hybrids of the two wild diploid species \u003cem\u003eMusa acuminata\u003c/em\u003e Colla (genome A) and \u003cem\u003eM. balbisiana\u003c/em\u003e Colla (genome B). These crosses resulted in a series of diploids, triploids and tetraploids with genomic groups classified as AA, AB, AAA, AAB, ABB, AABB, AAAB and ABBB (Simmonds and Shepherd, 1955). This diversity in \u003cem\u003eMusa\u003c/em\u003e is present in Benin (Chabi et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Ahohouendo et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and explains the variability in susceptibility to black Sigatoka observed in the present study. However, the susceptibility of a cultivar is not strictly linked to its genomic formula. Sources of resistance can also be found in diploids (AA). Previous reports of banana genotypes showing resistant and moderately resistant characteristics to black Sigatoka were mainly from diploid genome AA and triploid genome (AAB) (Soares et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This is the case, for example, with the Namarai (AA) cultivar, which is resistant to black Sigatoka (Aher, et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). There may be other unique genes or enzymes involved in black Sigatoka resistance in these genotypes. These may include genes associated with jasmonic acid and ethylene signaling, transcription factors, phenylpropanoid pathways, antioxidants and pathogenesis-related proteins, and pathogenesis-related proteins (Soares et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, it should be noted that the efficiency of plant resistance to fungal pathogen is expected to decrease over time, due to their evolution with an increase in the frequency of virulent or highly aggressive strains (Suffers et al., 2017).\u003c/p\u003e\u003cp\u003eIn this study, three parameters were used to analyze the pathological traits of \u003cem\u003eM. fijiensis\u003c/em\u003e. The first parameter, the number of disease units, indicates the disease severity as measured in the field. This parameter showed variability in severity indexes depending on the banana and plantain production zone. The second and third parameters measured were aggressiveness and virulence of the pathogen isolates, which were found to be highly correlated. These measurements provide insights into, the population structure of \u003cem\u003eM. fijiensis\u003c/em\u003e in our study area. These results confirmed the variability in the distribution observed in the subsistence banana production systems of Benin. Virulence is the qualitative aspect that expresses the ability of a pathogen to infect a host and cause disease. Aggressiveness is the quantitative component that measures the extent of damage caused to the host by the pathogen's attack (Lannou \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Dutta et al., 2021). Notably, significant variability in the evaluated parameters was sometimes recorded between neighboring districts. For instance, Houeyogbe and Lokossa, although they were very close to each other, respective DSI values of 38.64\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95 and 33.39\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95 were recorded. Several authors have addressed the reasons for this pathogenic disparity in the geographical distribution of plant diseases. These include that the geographic distribution of fungal plant pathogens is influenced by several parameters: crop management, climatic, biotic and other environmental factors, as well as their host distribution and susceptibility levels (Borer et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). For example, local plant community structure and diversity may support different levels of plant pathogen diversity by favouring specialist or generalist pathogens or by reducing the density of susceptible hosts (Bever et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eFinally, this study focused on investigating factors governing the black Sigatoka incidence and severity attack variation in the subsistence farming systems of banana and plantain in Benin. Black Sigatoka incidence and severity attacks are higher in monoculture systems based on dessert banana than in more diversified systems of banana and plantain and/or other associated crops. This study has also revealed that virulence and aggressiveness varied according to the area in which \u003cem\u003eM. fijienis\u003c/em\u003e isolates were collected. The information provided by this study in the main banana-producing areas of Benin will help to improve the banana production system by designing more resilient models of banana agroecological farming systems. In fact, banana and plantain have become priorities for development and agricultural diversification providing means of nutritional security in the Republic of Benin. By utilizing this information, farmers can enhance their current management methods and reduce the economic losses resulting from black Sigatoka disease outbreaks, thereby contributing to the long-term sustainability of banana and plantain production systems and ensuring food security.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eOn behalf of all authors, the corresponding author states that there is no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: FAA; methodology: FAA, ECT; writing-original draft preparation: FAA; writing-review and editing: FAA, VIAE, RAA, ECT; visualization: FAA, VIAE, ECT; project administration: BCA; funding acquisition, FAA, ECT, BCA; Curation and Formal Analysis: RA. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funding by \u0026quot;\u003cem\u003eAgence Universitaire de la Francophonie\u003c/em\u003e (AUF)\u0026quot; and International Foundation for Science (IFS) under the grants N\u0026deg; DRAO-2017-U-S0531PRS20803 and N\u0026deg; 1I3_C_041413 respectively.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\n\u003col\u003e\n\u003cli\u003eAbadie C, Apater MZ, Ignolet LP, Arlier JC, \u0026amp; Ourichon XM (2008) Artificial inoculation on plants and banana leaf pieces with \u003cem\u003eMycosphaerella \u003c/em\u003espp ., responsible for Sigatoka leaf spot diseases. \u003cem\u003eFruits\u003c/em\u003e, 63(5), 319\u0026ndash;323. https://doi.org/10.1051/fruits\u003c/li\u003e\n\u003cli\u003eAher A, Dethe A, Chavhan R, Hinge V, Dhutraj S (2024) Molecular elucidation of sigatoka disease resistance in diverse banana (\u003cem\u003eMusa \u003c/em\u003espp.) genotypes using molecular markers and genetic diversity analysis. Sc. Hortic. 336, 113446. https://doi.org/10.1016/j.scienta.2024.113446\u003c/li\u003e\n\u003cli\u003eAho N, Aho S, Agbokou I, Kaffo BA, Seni S, et Loconon DZ (2018) Introduction \u0026agrave; la r\u0026eacute;silience aux changements climatiques en Afrique de l\u0026rsquo;Ouest : R\u0026eacute;pertoire des dates pr\u0026eacute;d\u0026eacute;termin\u0026eacute;es des saisons pluvieuses dans les villages et quartiers de ville du B\u0026eacute;nin. Minist\u0026egrave;re de l\u0026rsquo;Energie, de l\u0026rsquo;Eau et des Mines-PNUD B\u0026eacute;nin, Cotonou.\u003c/li\u003e\n\u003cli\u003eAhohouendo FA, Togbe CE, Agbovoedo FR, Ahohuendo BC (2020) Farmers\u0026apos; Knowledge, Perceptions and Management of Black Sigatoka in Small Plantain-Based Farms in Southern Benin. AJLS, Vol. 8, No. 5, 2020, pp. 172-182. doi: 10.11648/j.ajls.20200805.23\u003c/li\u003e\n\u003cli\u003eAhohouendo FA, Togbe CE, Honfo FG, Agbovoedo FR, Tossou CC, and Ahohuendo BC (2022) Analysis of agro-morphological diversity among plantains (\u003cem\u003eMusa \u003c/em\u003especies AAB) in Benin Republic West Africa. Afri. J. Agric. Vol. 18(7), pp. 470-480. DOI : 10.5897/AJAR2022.16037\u003c/li\u003e\n\u003cli\u003eArango Isaza RE, Diaz-Trujillo C, Dhillon B, Aerts A, Carlier J, Crane CF, de Jong T, de Vries I, Dietrich R, Farmer AD, Fortes-Fereira C, Garcia S, Guzman M, Hamelin RC, Lindquist EA, Mehrabi R, Quiros O, Schmutz J, Shapiro H, Kema GHJ (2016) Combating a Global Threat to a Clonal Crop: Banana Black Sigatoka Pathogen \u003cem\u003ePseudocercospora\u003c/em\u003e \u003cem\u003efijiensis \u003c/em\u003e(Synonym \u003cem\u003eMycosphaerella fijiensis) \u003c/em\u003eGenomes Reveal Clues for Disease Control. PLoS Genet., 12(8), 1\u0026ndash;36. https://doi.org/10.1371/journal.pgen.1005876\u003c/li\u003e\n\u003cli\u003eArcila-Galvis JE, Arango RE, Torres-Bonilla JM, Arias T (2021) The Mitochondrial Genome of a Plant Fungal Pathogen \u003cem\u003ePseudocercospora fijiensis\u003c/em\u003e (\u003cem\u003eMycosphaerellaceae\u003c/em\u003e), Comparative Analysis and Diversification Times of the Sigatoka Disease Complex Using Fossil Calibrated Phylogenies. Life, 11, 215. https://doi.org/10.3390/life11030215\u003c/li\u003e\n\u003cli\u003eBakshi P, Bhushan A, Bali K, Kour K (2019) Intercropping in Fruit Orchards: A Way Forward for Doubling the Farmer\u0026rsquo;s Income. Int. J. Agric. 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Plant Pathol. ; 70 :544\u0026ndash;554. https://doi.org/10.1111/ppa.13304k \u003c/li\u003e\n\u003cli\u003eYonow T, Ramirez-Villegas J, Abadie C, Darnell RE, Ota N, \u0026amp; Kriticos DJ (2019) Black Sigatoka in bananas : Ecoclimatic suitability and disease pressure assessments. \u003cem\u003ePLoS ONE\u003c/em\u003e, 14(8), 1\u0026ndash;25. https://doi.org/10.1371/journal.pone.0220601 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"tropical-plant-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tppa","sideBox":"Learn more about [Tropical Plant Pathology](https://www.springer.com/journal/40858)","snPcode":"40858","submissionUrl":"https://www.editorialmanager.com/tppa","title":"Tropical Plant Pathology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"black leaf streak disease, disease incubation time, virulence","lastPublishedDoi":"10.21203/rs.3.rs-7584680/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7584680/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBlack Sigatoka, caused by \u003cem\u003eMycosphaerella fijiensis\u003c/em\u003e is responsible of phytosanitary constraints that affect considerably the global banana and plantain production. The distribution and severity of this disease in banana and plantain cropping systems result from both intrinsic and extrinsic factors that interplay dynamically. In this paper, we provide field incidence and severity of the disease in banana and plantain subsistence farming systems in 17 districts in Benin Republic. Pathogenicity test was conducted in greenhouse followed by the mapping of the study areas based on the virulence of \u003cem\u003eM. fijiensis\u003c/em\u003e isolated from plant and soil samples collected from 114 plantain and banana fields. The results showed that the incidence of the disease in banana subsistence farming systems varied significantly according to the production area (p\u0026thinsp;=\u0026thinsp;0.0465), the banana and plantain cultivars (p\u0026thinsp;=\u0026thinsp;0.0184) and the types of cropping system (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Dessert-banana-based monoculture systems were the most sensitive to pathogen attacks, with a Disease Severity Index (DSI) of 38.26\u0026thinsp;\u0026plusmn;\u0026thinsp;0.53, followed by the intercropping systems (DSI\u0026thinsp;=\u0026thinsp;33.64\u0026thinsp;\u0026plusmn;\u0026thinsp;0.74) and home garden systems (DSI\u0026thinsp;=\u0026thinsp;34.63\u0026thinsp;\u0026plusmn;\u0026thinsp;0.61). Overall, plantain cultivars across different systems were more resistant \u003cem\u003eM. fijiensis\u003c/em\u003e attacks (DSI\u0026thinsp;=\u0026thinsp;35.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49), compared dessert banana subgroup (DSI\u0026thinsp;=\u0026thinsp;37.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90) recorded to be the most susceptibleThe longest incubation times of 15.66 and 16.56 days recorded from isolates collected respectively in Houeyogbe in Zagnanado indicated the presence of the least virulent isolates. Contrariwise, the most virulent isolates with the shortest incubation times ranging from 11.75 to 12.58 days was recorded in Djidja and Toffo. These findings provide novel and valuable insights into epidemiology of banana and plantain farming systems in Benin. This outcome is essential to offering appropriate advice and support to farmers. In addition to this, existing production models are to be improved so that they can more effectively and sustainably control and prevent black Sigatoka disease.\u003c/p\u003e","manuscriptTitle":"Analysis of distribution and pathogenesis of Mycosphaerella fijiensis, in subsistence farming systems of banana and plantain in Benin","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-15 18:29:33","doi":"10.21203/rs.3.rs-7584680/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revisions","date":"2025-12-22T08:57:29+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-10-14T15:00:28+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-02T13:20:50+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Tropical Plant Pathology","date":"2025-09-29T14:48:55+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-09-26T06:10:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Tropical Plant Pathology","date":"2025-09-23T17:06:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"tropical-plant-pathology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tppa","sideBox":"Learn more about [Tropical Plant Pathology](https://www.springer.com/journal/40858)","snPcode":"40858","submissionUrl":"https://www.editorialmanager.com/tppa","title":"Tropical Plant Pathology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"2d6f3be1-8dbf-47cb-aa6e-aba25fa24595","owner":[],"postedDate":"October 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-05T14:45:59+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-15 18:29:33","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7584680","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7584680","identity":"rs-7584680","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}