Ecuadorian Littoral Musaceae Producers’ Typification Based on Their Production Systems, Agronomic Management, Biosecurity Measures, and Risk Level Against Foc TR4

Abstract

Musaceae represent one of the main crops of economic and food importance worldwide. In Ecuador, the production and export of bananas, plantains, and abaca are fundamental pillars of the national economy. However, the presence of Fusarium oxysporum f. sp. cubense tropical race 4 (Foc TR4) in neighbouring countries increases the risk to production systems. In this study, information was collected through simple random probability sampling, using a semi-structured survey that included sociodemographic information, crop characteristics, phytosanitary problems, agronomic management practices, and biosecurity measures. To differentiate the profile of producers, a Multiple Correspondence Analysis (MCA) was performed, followed by a hierarchical cluster analysis to establish their types. Additionally, a vulnerability index—Iv (low, medium, high, and critical—is proposed, considering variables such as geographic location, cultivar diversity, and producer management. Among the producers surveyed, 83.3% were men and 16.7% were women; 64% identified as Mestizo, 31% as Montubio, and 1.7% as Afro-Ecuadorian. At the time of the interview, only 38.5% used some biosecurity measures on their farms. Multivariate analyses identified six groups of producers with distinct characteristics, including ethnicity, location, crop type, phytosanitary issues, and adoption of biosecurity measures. Iv ranged from −0.60 to 3.20, with an average of 0.59. Producer groups 1 to 3 presented low to medium vulnerability, while groups 4 to 6 exhibited critical levels. These results demonstrate the diversity of production systems and profiles of Musaceae producers in Ecuador, as well as the need to strengthen biosecurity measures and phytosanitary management to reduce vulnerability to threats such as Foc TR4.

1. Introduction

The banana family, Musaceae, belongs to the order Zingiberales Griseb. [1,2,3]. It includes three currently recognized genera: Ensete Bruce ex Horan., Musa L., and Musella (Franchet) C.Y. Wu ex H.W. Li [4]. The genus with the greatest species richness is Musa, which contains species of agricultural interest due to their edible fruits (bananas and plantains) and industrial interest due to crops like abaca. Banana and plantain cultivars, regardless of their ploidy levels, exhibit mosaic ancestry patterns originating from Musa acuminata subspecies, with significant contributions from M. schizocarpa introgressions and homologous exchanges between the genomes of M. acuminata and M. balbisiana [5]. These cultivars display notable phenotypic and genotypic differences, leading to substantial natural variability [6], which results from both clonal and sexual reproduction [5]. This variability affects their resistance or tolerance to infections and diseases [7].

Globally, Musa genus cultivated species are among the most economically important and food-relevant products, after Oryza sativa L. (rice), Triticum vulgare L. (wheat), and Zea mays L. (maize) [8,9]. Their cultivation is widespread in tropical and subtropical regions of more than 50 countries and, in 2023, they covered an area of approximately 26 million hectares [10].

In Ecuador, the Musaceae production systems include banana, plantain, and Musa textilis Née (abaca) crops, which are export products and constitute a fundamental source of income with significant impact on the national economy [11,12,13]. The predominant banana export varieties belong to the Cavendish group (Williams and Valery) and Musa AA (Orito) [14], while for plantains, the Barraganete cultivar has prevailed in the export market [15,16]. Abaca has a lower weight in this export market [13,17].

Nationally in 2023, 184,000 ha of banana, 153,000 ha of plantain, 9000 ha of Orito, and 29020 ha of abaca were cultivated [10]. This activity (banana and plantain) contributed 25.4% to the agricultural Gross Added Value (GAV). Bananas accounted for 15.7% of non-oil exports [18]. The edible Musaceae value chain, including its processed products, has generated foreign revenue totalling USD 3855 million, and for abaca, around USD 21 million [19].

The production of Musaceae worldwide is mainly affected by diseases such as Ralstonia solanacearum Smith (moko), Mycosphaerella fijiensis Morelet (black sigatoka), or Fusarium oxysporum f. sp. cubense (Foc), known as Panama disease [20]. The last pathogen caused the first epidemic in the late 1950s and led to losses in the international banana market, which was dominated by the Gros Michel clone. This clone was later replaced by Cavendish clones, which are still in use [21] and account for 40% of global production. Currently, the presence of Fusarium tropical race 4 (Foc TR4) poses a risk to Cavendish clones’ production due to its rapid spread. To date, this disease has been reported in South America in Colombia, Peru, and Venezuela [22].

Farmers producing Musaceae in Ecuador cultivate their crops across a wide range of altitudes, from sea level in the Littoral region to the eastern foothills of the Andes in the Andean region. There are a total of 8851 registered producers. Among them, 61% operate small farms ranging from 0 to 30 hectares, 25% manage medium-sized farms between 31 and 100 hectares, and 14% oversee large farms exceeding 100 ha [23]. The main areas for Musaceae production are located in the provinces of Los Ríos, Guayas, El Oro, Manabí, and Santo Domingo de los Tsáchilas [24]. Notably, over the past decade, farmers in Santa Elena province have significantly expanded their cultivated area from 91 to 2296 ha [25], thanks to favourable climatic conditions and improved irrigation provided by the Chongón-San Vicente canalization [26].

Ecuador’s Musaceae production systems are notable for their geographic diversity, varying sizes, and management practices, along with the prevalence of genetically uniform cultivars. Two primary production systems have been identified: the first is a monoculture system focusing on either plantains or bananas, and the second involves a mix with perennial fruit or forest species [27,28]. Within the monoculture system, several variants exist that depend on factors such as farm size, crop management practices, crop type, market acceptance, and pricing strategies [27]. This system primarily employs conventional management techniques, which account for most of the cultivated areas, and typically involves the application of synthetic agrochemicals [28]. In contrast, organic management is grounded in natural principles, minimizing the use of chemicals [29]. This approach has not only aided in gaining access to international markets but also prevented negative impacts of pesticides on human and environmental health [30].

The vulnerability of a species, defined as the risk of collapse in extensive crops caused by diseases [31], is a consequence of its clonal cultivation. Thus, high vulnerability to Foc TR4 [32] and other pathogens, such as R. solanacearum [33], is attributable to the genetic uniformity of the crop and the demands of the export industry for a single variety (Williams). However, the characteristics of Musaceae production systems, such as surface area, use of tools, and production models that favour their diversification, can generate different levels of vulnerability to any pathogen in large cultivation areas and countries [34,35]. Therefore, the widespread adoption of biosecurity measures is essential to prevent the spread of diseases [36]. Still, predicting vulnerable areas is vital for controlling and containing their spread and establishment. The global and pantropical American predictive model [37], based on climatic variables available in WordClim, highlights Ecuador’s vulnerability to Foc TR4, with the highest risk levels located in the Littoral region. Furthermore, considering different climatic variables [38], vulnerability to Foc TR4 was assessed using the agroclimatic favourability index (AFIest), which projected the highest values for the provinces in the Littoral region and some in the Andean region.

The absence of comprehensive national-level data concerning the types of producers—categorized by crop types, production systems, biosecurity protocols, and farms cultivating Musaceae—stems from an insufficient understanding of this agricultural resource. This gap is exemplified by specific studies [28,39,40,41,42], which have predominantly concentrated on socioeconomic factors. Consequently, the primary objective of this research is to acquire data that will serve as a foundational reference for Musaceae cultivation in the Ecuadorian Littoral region. This encompasses an analysis of farmer profiles and the attributes of their production systems, including adopted biosecurity measures and cultivars, with the aim of identifying, defining, and characterizing the diversity of producers. Furthermore, a secondary aim involves the development of a vulnerability index to the threat of Foc TR4. This index, devised through a straightforward calculation, integrates levels of exposure (risk) and sensitivity (susceptibility) to evaluate overall risk, which has thus far been predicted through climatic data and spatial analysis [37,38].

2. Materials and Methods

2.1. Study Area

During the years 2022 and 2023, 96 plantations where abaca, banana or plantain cultivars are grown were visited (Figure 1), distributed between the Littoral region, Esmeraldas, Manabí, Guayas, Los Ríos, Santa Elena, El Oro and Santo Domingo de los Tsáchilas provinces, and in the western Andean foothills of the Andean region, Imbabura, Pichincha, Cotopaxi, Bolívar and Chimborazo provinces. These plantations are located between 1°28′ north latitude and 5°01′ south latitude, and from 75°11′ to 81°01′ west longitude, spanning from sea level to an altitude of 800 m.

The climatic conditions are influenced by the cold Humboldt and the warm El Niño currents [43], which mark two distinct seasons: the wet season, characterized by high temperatures and abundant rainfall from December to May, and the dry season, with low temperatures and little rainfall, from June to November [44]. The average annual temperature ranges between 24 and 25 °C, and the average annual rainfall varies from less than 60 mm (Santa Elena) to more than 2000 mm (Los Ríos), resulting in a mix of desert areas and humid or dry tropical forests [45].

Geologically, the soil is formed on the Cretaceous volcanic complex, which, to the north, reflects the presence of dissected sedimentary reliefs, and to the south, horizontal tabular reliefs [46]; 43% of this region is suitable for agricultural use, as the territory is horizontal with slight undulations, where tropical crops such as Theobrama cacao L. (cocoa), Coffea arabica L. (coffee), Musa paradisiaca L. (banana), Oryza sativa L. (rice), Zea mays L. (corn) and various grasslands predominate [47], in addition to other fruits such as Ananas comosus L. (pineapple), Mangifera indica L. (mango), and Cucumis melo L. (melon), among others [48].

2.2. Sampling

The baseline information was generated by applying a simple, exhaustive random probability sampling method, in which once a subject is selected, they are removed from the population and therefore cannot be selected again [49]. To this end, the main production areas were explored, and once the plantation was identified and the producer’s collaboration was agreed upon, individual personal interviews were conducted. In addition, a semi-structured survey was designed, comprising closed-ended questions (fixed-response) and open-format multiple choice and open-ended questions, including descriptive items, depending on the content’s nature [49]. The types and formats of questions asked during the interviews are shown in

Table 1. The information gathered from interviews with Musaceae producers is organized into five sections, each featuring its respective variables (questions). The type of question, the initial response format, and their corresponding coding are specified.

Sections	Variable	Coding	Question Type	Response Type
Personal aspects of the producer	Producer age	AgeRang	Open-ended	Quantitative continuous
	Producer gender	ProdGend	Closed-ended	Qualitative nominal
	Property type	PropType	Open-ended	Qualitative nominal
	Ethnic Group	Ethnic	Open-ended	Qualitative nominal
	Education Level	EduLev	Open-ended	Qualitative ordinal
	Belongs to an association	Assoc	Open-ended	Qualitative nominal
	How many years have you been producing Musaceae?	ProdRang	Open-ended	Quantitative continuous
Geographical location of the farm	Province	Province	Open-ended	Qualitative nominal
Generalities of cultivation	Cultivation system?	PlanSys	Open-ended	Qualitative nominal
	Types of plantation?	Plant	Open-ended	Qualitative nominal
	Types of cultivars	CultType	Open-ended	Qualitative nominal
	What method of propagation do you perform?	Propag	Closed-ended	Qualitative nominal
	Cultivated area?	CropAreaRang	Open-ended	Qualitative ordinal
	What irrigation system do you use?	IrrigSys	Closed-ended	Qualitative nominal
Phytosanitary problems and plantation management	Do you have problems with weevil?	Picudo	Closed-ended	Qualitative ordinal
	Do you have problems with cochineal?	Cochinilla	Closed-ended	Qualitative ordinal
	Having problems with caterpillar?	Caterpillar	Closed-ended	Qualitative ordinal
	Do you have problems with trips?	Trips	Closed-ended	Qualitative ordinal
	Do you have problems with whiteflies?	Whitefly	Closed-ended	Qualitative ordinal
	Do you have problems with nematodes?	Nemat	Closed-ended	Qualitative ordinal
	Do you have problems with Fusarium?	Fusarium	Closed-ended	Qualitative ordinal
	Do you have problems with sigatoka?	Sigatoka	Closed-ended	Qualitative ordinal
	Do you have problems with moko?	Moko	Closed-ended	Qualitative ordinal
	Do you have problems with viral diseases?	Viruses	Closed-ended	Qualitative ordinal
	What kind of pest and disease control do you use?	PhytoCon	Closed-ended	Qualitative nominal
	What soil additives do you use?	Edaph	Open-ended	Qualitative nominal
Biosecurity measures	What biosecurity measures do you use?	BioSafe	Open-ended	Qualitative nominal

.

Of the set of questions, only three have numerical answers producer age (ProdAge), time as producer (ProdTime) and crop area (CropArea), because they are of the continuous metric type (

Table 2. Categorization of the numerical variables, producer age, years dedicated to Musaceae production, and plantation area, into five ranges (classes).

Classes	Producers’ Age	Years to Musaceae Production	Plantation Area (ha)
I	22–36	1–13	1–46
II	36–50	13–25	46–91
II	50–64	25–37	91–136
IV	64–78	37–49	136–181
V	78–92	49–61	181–226

), which will be categorized depending on subsequent analyses, while the remaining ones are of a qualitative nature and multi-state binary type (nominal categorical variables).

Considering that this is a descriptive study wherein the primary variable is qualitative and the population is finite and well-defined [50], the sample size was determined utilizing Cochran’s formula [51], expressed as n = (Nz²pq)/(d² (N − 1) + Z²pq), where N signifies the population size, which in this case comprises 8851 producers; Z indicates the confidence level = 1.96; d represents the sampling error = 0.1; p denotes the probability of success = 0.5; and q corresponds to the probability of failure = 0.5. The application of this formula indicates that the sample should consist of 95 respondents. Ultimately, a total of 96 responses were analyzed.

It is important to emphasize the limited representativeness of the sample for two main reasons. The first is the lack of census data [52] regarding the cultivation of Musaceae in agricultural activities. The second is the hesitance of Ecuadorian farmers to provide accurate information in surveys about their crop profits. This hesitance arises from a lack of trust in institutions, perceived risks related to potential tax obligations, security concerns, and a lower willingness to disclose private information, all of which are exacerbated by the sector’s informality and fragmentation [53].

2.3. Data Analysis

The survey data were organized in a matrix of 96 rows (producers) by 27 columns (questions), where the quantitative variables were transformed using the Sturges rule [54] (Table 1), resulting in a total of 121 categorical variables (Table S2). Initially, a descriptive analysis was performed on the response combinations between variables, especially those related to the sociological characteristics of the producers (gender, ethnicity, education level, cultivated area) and those associated with the location of the plantations, cultivars, and biosecurity measures, to profile the sample and establish comparisons using Chi-square tests. Subsequently, as in other typifying trials similar to the present one [28,55,56], the matrix was analyzed, first, through Multiple Correspondence Analysis (MCA) [57], an analysis specifically designed for the analysis of categorical variables [58]. In essence, MCA is an interdependence method for dimensionality reduction, akin to Principal Component Analysis (PCA), but based on the χ² distance, which captures the greatest variability of categorical variables in its initial dimensions, thereby emphasizing their significance. Next, a Hierarchical Classification Analysis (CA) based on the coordinates from these first dimensions constructs the groups by considering the Euclidean distance relating to the orthogonality of the retained dimensions [59]. To identify the producer groups, Ward’s hierarchical clustering method was utilized [57], which facilitates the formation of homogeneous and heterogeneous groups among producers based on their characteristics.

All the statistical analyses described above were developed using the R programme statistical packages [60] FactoExtra [61], FactoMineR [62], Factoshiny [63], FactoInvestigate [64], FactoClass [65], tidyverse [66], and readxl [67] from the data initially stored in a Microsoft Excel spreadsheet [68].

2.4. Production System Vulnerability

The vulnerability index (Iv) was created using variables extracted from geographical location, cultivar type information, and producer management (

Table 3. Variable values (indicators) for the vulnerability assessment to diseases, considering various factors and indicators.

Factors	Dimension	Indicator	Operational definition	Label
Exposure (risk level)	Proximity to the entry points of the country	B1. Distance to seaports	Distance in kilometres in a straight line from the farm to the nearest seaport	1. >400 km 2. 400–250 km 3. 250–104 km 4. 100–0 km
		B2. Distance to the Colombian land border (north)	Distance in kilometres in a straight line from the farm to the Rumichaca International Bridge	1. >400 km 2. 400–250 km 3. 250–104 km 4. 100–0 km
		B3. Distance to the Peru land border (south)	Distance in kilometres in a straight line from the farm to the Huaquillas International Bridge	1. >400 km 2. 400–250 km 3. 250–104 km 4. 100–0 km
	Biosecurity	B4. Biosecurity measures	The presence of biosecurity measures on the farm	1. Biosecurity measures are not applied 0. Apply biosecurity measures
Sensitivity (crop susceptibility)	Genetic vulnerability	A1. Cultivar resistance or susceptibility	The predominant variety grown on the farm is susceptible or not to Foc TR4	0. Resistant 1. Susceptible
		A2. Genetic diversity	The farm has a monoculture or is associated with other varieties or species	1. Monoculture 2. Associated
	Environmental vulnerability	A3. Production type	Chemical or organic synthesis products are used on the farm	1. Conventional 2. Organic
		A4. Sanitary product access	Use or non-use of external products for disease and pest control	1. Chemicals 2. Biological
		A5. Planting material origin	The crop is established with certified planting material	0. Corms or seedlings 1. Vitroplants
Socioeconomics	Management capacity	C1. Cultivated area	Number of hectares used for the main crop	1. Little 2. Medium 3. Big
		C2. Associativity	The farm owner belongs to an organization that can provide support or financing	1. Belongs to an organization 2. Does not belong to any organization
	Education	C3. Formal instruction	The farm owner completed higher education (university degree)	0. Does not have higher education 1. Has higher education

), with reference to the methodology for estimating the susceptibility of soils to Foc TR4 in Colombia [69]. First, the factors comprising vulnerability were established, taking into account the criteria of F. oxysporum experts; second, the indicators and dimensions that combine information collected in the field with expert criteria were identified [70].

In Formula (1), a quantification of the Musaceae vulnerability to the pathogen is proposed, considering that the established factors correspond to those indicated by the Intergovernmental Panel on Climate Change [71]. The inclusion of indicators, as well as the assignment of dimensions to the factors, was carried out according to the criteria of the expert panel, as shown in Table 3.

$$Iv=\left(\alpha Vg\times \beta Va\right)+\gamma \mathrm{S}-\delta \mathrm{E}$$

(1)

where

Vg = genetic vulnerability, which reflects the susceptibility of the cultivated variety and genetic diversity.

Va = environmental vulnerability, which includes the production type, chemical products access, and planting material origin.

S = Exposition, which represents the ports’ proximity and biosecurity infrastructure.

E = Socioeconomics, which includes cultivated area, associativity, and educational level.

The parameter weights of the α, β, γ, and δ were calculated from the explained variance by the first component of the Principal Component Analysis (PCA) by blocks, where each block corresponds to a factor. Thus, the Formula (1) parameters took the values α = 0.4 and β = γ = δ = 0.2, resulting in Formula (2),

$$Iv=\left(0.4Vg\times 0.2Va\right)+0.2\mathrm{S}-0.2\mathrm{E}$$

(2)

The indicator values that were included in each factor were multiplied together, under the additive probability rule [72], assuming that the occurrence probability of the event is 1 and the non-occurrence probability is 0. The individual weighting for each indicator was assigned in accordance with expert judgement, based on experience and observation in F. oxysporum epidemics. Formula (3) shows the development of the two preceding formulas, noting the parameters and elements for calculating the Iv for each productive unit.

The numerical values of the index were classified into four vulnerability levels (low, medium, high, and critical) according to the quartile distribution.

$$Iv=\left[0.4\right(A1\times A2)\times 0.2(A3\times A4\times A5\left)\right]+0.2(\mathrm{B}1\times \mathrm{B}2\times \mathrm{B}3\times \mathrm{B}4)-0.2(\mathrm{C}1\times \mathrm{C}2\times \mathrm{C}3)$$

(3)

3. Results

The subsequent subsections address various findings obtained through the cross-referencing of survey data. The initial section analyses the distribution of landowners by gender across provinces and cultivated areas. The second section evaluates producers’ social attributes by correlating information regarding their gender and ethnicity with their educational levels and membership in associations. The third section also presents the results pertaining to cultivated areas of each cultivar by province, as well as findings on social attributes through cross-referencing cultivars and biosecurity measures. The fourth section underscores the results emerging from the intersection of production systems and associations. The fifth section further investigates aspects related to MCA and AC, with particular emphasis on producer typification. Lastly, the vulnerability index (Iv) values are highlighted, taking into account the previously defined producer types and the sampled provinces.

3.1. Farms and Their Managers

Table 4. Musaceae producers interviewed by Ecuadorian provinces: total cultivation area by genus and province.

Province	Persons Interviewed						Area
	Men		Women		Total	Sampling %	Men		Women		Total	Sampling %
	Count	%	Count	%			(ha)	%	(ha)	%
Littoral	69	71.88	14	14.58	83	86.46	2020	91.49	128	5.80	2148	97.28
El Oro	4	4.17	3	3.13	7	7.3	49	2.22	62	2.81	111	5.03
Esmeraldas	9	9.38	1	1.04	10	10.42	53	2.40	1	0.05	54	2.45
Guayas	11	11.46	4	4.17	15	15.63	523	23.69	42	1.90	565	25.59
Los Ríos	16	16.67	1	1.04	17	17.71	745	33.74	4	0.18	749	33.92
Manabí	14	14.58	4	4.17	18	18.75	43	1.95	17	0.77	60	2.72
Santa Elena	3	3.13	0	0	3	3.13	341	15.44			341	15.44
Santo Domingo	12	12.5	1	1.04	13	13.54	266	12.05	2	0.09	268	12.14
Andean	11	11.46	2	2.08	13	13.54	49	2.22	11	0.50	60	2.72
Bolívar	4	4.17	2	2.08	6	6.25	31	1.40	11	0.50	42	1.90
Chimborazo	1	1.04	0	0	1	1.04	2	0.09	0	0	2	0.09
Cotopaxi	3	3.13	0	0	3	3.13	7	0.32	0	0	7	0.32
Imbabura	1	1.04	0	0	1	1.04	6	0.27	0	0	6	0.27
Pichincha	2	2.08	0	0	2	2.08	3	0.14	0	0	3	0.14
Total	80	83.33	16	16.67	96	100	2069	93.70	139	6.30	2208	100.00

presents the data on cultivated areas in the different provinces, categorized by the gender of their owners or managers (see Table 2). A total of 96 Musaceae producers (80 men and 16 women) were interviewed, managing an area of 2212 ha of Musaceae crops. The number of men is significantly higher than the number of women who have property responsibility (χ² = 42.667, df = 1, p = 6.49 × 10⁻¹¹). Of the total area of these farms, 2069 ha (93.7%) is managed by men, which is significantly higher than the 139 ha (6.3%) managed by women (χ² = 1687, df = 1, p < 2.2 × 10⁻¹⁶).

The largest number of sampled farms is concentrated in the Littoral region, with 83 producers (69 men and 14 women) responsible for an area of 2148 ha, representing 97.28% of the total plantation area (Table 4). The number of men responsible for the management of these farms is much higher than that of women (χ² = 36.446, df = 1, p = 1.57 × 10⁻⁰⁹), as well as the number of surfaces under their management (χ² = 1666.5, df = 1, p < 2.2 × 10⁻¹⁶). The provinces in this region with the largest farm areas under cultivation were Los Ríos, Guayas, and Santa Elena, with 749, 565, and 341 ha, respectively. The provinces with the largest number of producers interviewed were Manabí, Los Ríos, and Guayas, with 18, 17, and 15, respectively.

In the Andean region, 13 producers (11 men and 2 women) were interviewed, distributed across five provinces that represent a productive area of 60 ha, accounting for 2.72% of the total area (Table 4). As in the Littoral region case, the number of men dedicated to this crop is significantly higher than that of women (χ² = 6.2308, df = 1, p = 0.01255), as well as those who manage the most significant area (χ² = 24.067, df = 1, p = 9.306 × 10⁻⁰⁷) (men: 49 ha; women: 11 ha). The provinces with the highest number of interviewees were Bolívar (six) and Cotopaxi (three), which account for 1.90% and 0.32% of the total area considered, respectively.

3.2. Sociological Characteristics

Figure 2 represents the age frequencies of the interviewed producers, categorized by the established age classes (Table 2), taking into account their gender and the ethnic group with which they identify. The producers’ ages ranged from 22 to 88 years, with an average of 51.5 years. The men’s average age (52.8 years) was significantly higher than that of women (41.6 years) (t = 2.8854, df = 94, p = 0.005). Age classes II and III were the most common for men, encompassing individuals between 37 and 64 years of age, whereas for women, classes I and II were most common, with ages ranging from 22 to 50 years (Figure 2). For both genders, age classes II and III (37 to 64 years) account for 60.4% of the respondents.

Concerning the ethnicity of these producers, 2 identified themselves as Afro-Ecuadorian, 70 as Mestizo, and 24 as Montubio. In the Mestizo population, age class II was the most representative, while class III was the most representative in the Montubio population (Figure 2). The different proportionality between the ethnic groups of the respondents is evident (χ² = 75.25, df = 2, p < 2.2 × 10⁻¹⁶), with a predominance of the Mestizo ethnic group.

Regarding the total respondents’ education level (

Table 5. Education level and associativity percentages by gender and ethnicity of Musaceae producers in the Ecuadorian Littoral.

Education Level	Gender			Ethnicity
	Men	Women	Total	Afro-Ecuadorian	Mestizo	Montubio	Total
Incomplete primary	3.8	0	3.1	0	2.9	4.2	3.1
Complete primary	22.5	31.3	24	50	24.3	20.8	24
Incomplete secondary	11.3	12.5	11.5	0	7.1	25	11.5
Complete secondary	18.8	18.8	18.8	0	18.6	20.8	18.8
Incomplete university	3.8	18.8	6.3	0	8.6	0	6.3
Complete university	32.5	12.5	29.2	50	31.4	20.8	29.2
Fourth level	7.5	6.3	7.3	0	7.1	8.3	7.3
Total	83.3	16.7	100.0	2.1	72.9	25.0	100.0
Associated	18.8	0	15.6	0	12.9	25	15.6
Non-associated	81.2	100	84.4	100	87.1	75	84.4
Total	83.3	16.7	100.0	2.1	72.9	25.0	100.0

), 29.2% have completed their university studies, followed by a group of producers who have only completed primary and secondary studies (24.0% and 18.8%, respectively). The lowest percentage (3.13%) corresponded to the group of producers who have not completed primary education. Similarly, considering gender, the most significant proportion of male producers (32.5%) also completed university studies, followed by a group of producers (22.5%) who have completed primary education. In the case of women, the largest proportion (31.3%) have completed primary education, followed by those who completed their secondary studies (18.8%) and those who did not complete their university studies (18.8%). When comparing the educational levels between the two genders, no significant differences were found (χ² = 7.7014, df = 6, p = 0.2608), despite the disproportionate number of men (80) and women (16).

On the other hand, 15.6% of the producers interviewed belong to a producer association, while the rest (84.4%) are independent (Table 5). At the gender level, 18.8% of men are affiliated with an organization, and 81.2% are independent producers. On the contrary, all women interviewed do not belong to any agricultural organization. After applying Fisher’s exact test, no significant association was found (p = 0.0678, odds ratio = Inf; IC 95%: 0.77–Inf) between producers’ gender and their response to associativity. When comparing associativity by ethnicity (Table 5), the Montubio group producers showed greater organization, at 25%, followed by Mestizo producers (12.9%). In contrast, Afro-Ecuadorian producers, as a whole, are independent producers. Likewise, no significant association was found between ethnicity and associativity (p = 0.3636) after applying Fisher’s exact test.

3.3. Cultivated Varieties

The total number of Musaceae varieties in the considered farms is 11, comprising abaca (1), banana (5), and plantain (5), covering a total area of 2212 ha (

Table 6. Acreage of Musaceae plantations by province and crop.

Province	Abacá	Barraganete	Dominico	Dominico Hartón	Hartón	Maqueño	Cavendish	Gros Michel	Orito	Valery	Williams	Overall Total	Number of Farms
Bolívar	0	7	0	0	0	0	0	31	4	0	0	42	6
Chimborazo	0	0	0	0	0	0	0	2	0	0	0	2	1
Cotopaxi	0	0	0	0	0	0	0	2	5	0	0	7	3
El Oro	0	0	0	0	0	0	27	0	0	0	84	111	7
Esmeraldas	39	6	2	0	6	0	0	1	0	0	0	54	10
Guayas	0	0	9	3	1	30	2	8	5	0	507	565	1
Imbabura	0	0	0	0	0	0	0	10	0	0	0	10	17
Los Ríos	15	22	0	0	5	0	0	149	4	45	509	749	18
Manabí	0	40	1	0	18	0	0	1	0	0	0	60	2
Pichincha	0	0	3	0	0	0	0	0	0	0	0	3	3
Santa Elena	0	0	0	0	0	0	0	0	0	0	341	341	13
Santo Domingo	50	30	17	0	8	0	0	2	16	75	70	268	6
Overall total	104	105	32	3	38	30	29	206	34	120	1511	2212
Number farms	7	17	7	1	13	1	4	15	8	2	21		96

). Four of the interviewers responded that the variety they grew was Cavendish without distinguishing between the Valery or Williams varieties, opting to keep these responses independent in all subsequent analyses. The abaca accounts for only 4.70% of this total area and has been identified in seven plantations. The five banana varieties (Cavendish, Gros Michel, Orito, Valery, and Williams) account for 85.89% of the total, distributed across 50 plantations. Among these, the Williams cultivar stands out, occupying 68.31% of the total surface area and being found in 21 plantations. Moreover, the five plantain varieties (Barraganete, Dominico, Dominico Hartón, Hartón, and Maqueño) represent 9.42% and have been distributed among 39 plantations, with Barraganete being the most prominent, accounting for 4.75% of the cultivated area across 17 of these farms. In addition to those already mentioned, two other cultivars are prominently represented: Gros Michel banana, spread across 15 plantations, and Hartón plantain, across 13.

Classes I (1–46 ha) and II (46–91 ha) of cultivated areas (

Table 7. Interviewed percentages of Musaceae cultivars and producers in the Littoral region of Ecuador, taking into account personal aspects, education level, and biosecurity measures applied.

Category/Cultivar	Cultivars
	Abacá	Banana					Plantain
		Cavendish	Gros Michel	Valery	Williams	Orito	Barraganete	Dominico	Dominico Hartón	Hartón	Maqueño
GENDER
Man	7.29	3.13	11.46	2.08	17.71	7.29	14.53	6.25	1.04	11.46	1.04
Woman	0	1.04	4.17	0	4.17	1.04	3.13	1.04	0	2.08	0
AGE CLASS (YEARS)
I (22–36)	0	2.08	2.08	0	4.17	2.08	5.21	1.04	0	1.04	0
II (37–50)	2.08	2.08	2.08	2.08	11.46	3.13	3.13	4.17	0	4.17	1.04
III (51–64)	2.08	0	5.21	0	3.13	2.08	5.21	2.08	1.04	4.17	0
IV (65–78)	3.13	0	4.17	0	3.13	1.04	4.17	0	0	4.17	0
V (79–92)	0	0	2.08	0	0	0	0	0	0	0	0
ETHNICITY
Afro-Ecuadorian	0	0	0	0	0	0	0	2.08	0	0	0
Mestizo	5.21	4.17	13.54	1.04	16.67	8.33	10.42	3.13	0	10.42	0
Montubio	2.08	0	2.08	1.04	5.21	0	7.29	2.08	1.04	3.17	1.04
EDUCATION LEVEL
Complete primary	4.17	0	6.25	0	0	2.08	3.13	3.13	1.04	3.13	1.04
Incomplete primary	1.04	0	1.04	0	0	0	1.04	0	0	0	0
Complete secondary	2.8	1.04	0	1.04	4.17	1.04	4.17	0	0	5.21	0
Incomplete secondary	0	0	3.13	1.04	2.08	1.04	2.08	2.08	0	0	0
Complete university	0	2.08	4.17	0	12.5	3.13	2.08	2.08	0	3.13	0
Incomplete university	0	1.04	1.04	0	0	1.04	2.08	0	0	1.04	0
Fourth level	0	0	0	0	3.13	0	3.13	0	0	1.04	0
BIOSECURITY MEASURES
Disinfection arch	0	0	0	1.04	0	0	0	0	0	1.04	0
Tool disinfection	0	0	1.04	0	0	0	4.17	0	0	1.04	0
Footbath	0	2.08	0	0	4.17	2.08	1.04	0	0	1.04	1.04
Wheelbath	0	0	0	0	1.04	0	0	0	0	0	0
All possible	0	1.04	2.08	1.04	10.42	2.08	0	0	0	1.04	0
None	7.29	1.04	12.5	0	6.25	4.17	12.5	7.29	1.04	9.38	0

) are the most frequent among respondents, with 678 ha and 633 ha, respectively. However, the largest number of plantations (82) is found in class I areas, which represent 85.42% of the total plantations. The provinces with the largest areas were Los Ríos (749 ha), Guayas (565 ha), Santa Elena (341 ha), and Santo Domingo (268 ha). However, the largest numbers of plantations where the surveys were conducted were in Manabí (18), Los Ríos (17), Guayas (15), and Esmeraldas (10).

Abaca cultivation is primarily in the hands of male producers aged between 37 and 78 years (age classes II, III, and IV), who are of Mestizo (5.21%) and Montubia (2.08%) ethnicity and have low educational levels, with 33.3% having incomplete primary education. None of the respondents apply biosecurity measures on their farms (Table 7).

Regarding banana cultivars (Table 7), the plantations are distributed among 40 male producers (41.67%), a number clearly higher than that of the 10 women (10.42%) (χ² = 18, df = 1, p = 2.209 × 10⁻⁰⁵), whose ages are between 22 and 92 years (all age classes), of fundamentally Mestizo ethnia (43.75%) and less representation of the Montubio ethnicity (8.33%), with different educational levels, among which 21.88% with completed university studies stand out. Although the majority apply different biosecurity measures (11.45%), a significant percentage apply all possible measures (16.67%), and some producers do not apply any of them (23.96%).

Finally, banana cultivar plantations (Table 7) are also managed by a greater number of male producers, 33 (34.38%), than women, with 6 producers (6.25%) (χ² = 18.692, df = 1, p = 1.536 × 10⁻⁰⁵).

The ages of these producers are between 22 and 78 years (age classes I, II, III and IV) and they basically belong to the Mestizo ethnic group (23.96%), surpassing the Montubio (14.58%) and Afro-Ecuadorian (2.08%) producers, whose education levels are distributed among all those considered in the survey, with high scores in primary (11.46%) and secondary (9.38%) completion. Those who do not apply biosecurity measures (30.21%) predominate compared to those who apply some (9.38%) and all possible measures (1.04%).

When comparing the education level by ethnicity (Table 5), Mestizo producers showed varied educational levels, with the highest proportion among those respondents (72.9%). The Montubio ethnic group occupied second place with 25.0% and the Afro-Ecuadorian ethnic group occupied third place with 2.1%. Among the Mestizo ethnic group, 31.4% have completed university studies, followed by producers with completed primary and secondary education, at 24.3% and 18.6%, respectively (Table 5). The Montubio ethnic group shows a fairly similar pattern, but those producers who did not complete their secondary studies stand out (25%). No differences were detected between the three ethnic groups in relation to the education levels achieved (χ² = 9.8726, df = 12, p = 0.6271) despite the disproportion in the number from these ethnic groups.

Abacá: textile industry. Plantain: feeding after cooking (Barraganete, Dominico, Dominico hartón, Hartón, and Maqueño). Banana: fresh feeding (Cavendish, Gros Michel, Orito, Valery, and Williams).

Biosecurity measures are applied in a few cases, as shown in

Table 8. Biosecurity measures in Musaceae plantations in the Littoral region of Ecuador, taking into account producers’ personal aspects.

Category	Biosecurity Measures
	None	Tool Disinfection	Footbath	Wheelbath	Disinfection Arch	All Possible	Overall Total
GENDER
Man	51.04	5.21	9.38	1.04	2.08	14.58	83.33
Woman	10.42	1.04	2.08	0	0	3.13	16.67
AGE CLASS (YEARS)
I (22–36)	10.42	1.04	1.04	0	1.04	4.17	17.71
II (37–50)	16.67	2.08	7.29	1.04	1.04	7.29	35.41
III (51–64)	18.75	2.08	2.08	0	0	2.08	24.99
IV (65–78)	13.54	1.04	1.04	0	0	4.17	19.79
V (79–92)	2.08	0	0	0	0	0	2.08
ETHNICITY
Afro-Ecuadorian	2.08	0	0	0	0	0	2.08
Mestizo	42.71	5.21	8.33	1.04	1.04	14.58	72.91
Montubio	16.67	1.04	3.13	0	1.04	3.13	25.01
EDUCATION LEVEL
Complete primary	19.79	2.08	2.08	0	0	0	23.95
Incomplete primary	3.13	0	0	0	0	0	3.13
Complete secondary	12.5	2.08	1.04	0	0	3.13	18.75
Incomplete secondary	8.33	0	1.04	1.04	1.04	0	11.45
Complete university	10.42	1.04	6.25	0	0	11.46	29.17
Incomplete university	3.13	0	1.04	0	1.04	1.04	6.25
Fourth level	4.17	1.04	0	0	0	2.08	7.29
CULTIVATED AREA CLASS
I (1–46)	58.33	6.25	10.42	0	1.04	9.38	85.42
II (46–91)	3.13	0	0	1.04	1.04	4.17	9.38
III (91–136)	0	0	0	0	0	1.04	1.04
IV (136–181)	0	0	0	0	0	2.08	2.08
V (181–226)	0	0	1.04	0	0	1.04	2.08

. Mostly, producers do not apply biosecurity measures in their plantations (61.46%) compared to 38.54% who do adopt some (χ² = 5.0417, df = 1, p = 0.02474).

Male producers are more likely to apply biosecurity measures (χ² = 16.892, df = 1, p = 3.957 × 10⁻⁰⁵) than women (Table 8). Considering the age classes, some biosecurity measures are applied in certain age groups, except in class V (79–92 years), where differences are detected (χ² = 23.135, df = 4, p = 1.19 × 10⁻⁰³). The least used measures are the “wheelbath” and the “disinfection arch,” while the most used are, in decreasing order, “all possible,” the “footbath,” and “tool disinfection”. Age class II (37–50 years) is the one that has the highest percentage of producers (Table 8) who apply biosecurity measures (18.74%). Afro-Ecuadorians do not apply any measures, while the other two ethnic groups do. Both Mestizos and Montubios apply the same biosecurity measures (p = 0.7413) after applying Fisher’s exact test. Producers with completed university education levels show that they apply “all possible measures” significantly more than the rest of the educational levels (χ² = 28.351, df = 5, p = 3.107 × 10⁻⁰⁵). In this sense, as the producer’s educational level increases, biosecurity in the plantations increases and diversifies, particularly when the primary level has been reached (Table 7), which represents 38.52% of the plantations, since those who have not completed these studies do not apply biosecurity measures. The cultivated area class with the highest application of biosecurity measures (Table 8) is class I (1–46 ha) with 27.09%, followed by class II (46–91 ha) with 6.25%. In the remaining surface classes, all possible measures are applied, representing 4.16% of the plantations. No increase in the application of security measures was detected in all the surveyed plantations as the cultivated area increased.

3.4. Musaceae Production Systems

Of the total producers interviewed, 71.87% present monoculture production and 28.13% associate Musaceae cultivars with other species (cocoa, orange, corn, among others). On the other hand, 47.92% of respondents practice organic agriculture, while 52.08% practice conventional agriculture (

Table 9. Musaceae producers by production system in the Ecuadorian Littoral.

	Organic (%)	Conventional (%)	Producers (%)
Associated crop	12 (12.5)	15 (15.63)	27 (28.13)
Monoculture	34 (35.42)	35 (36.45)	69 (71.87)
Producers	46 (47.92)	50 (52.08)	96 (100)

). In the monoculture system, 35.42% are organic farmers and 36.45% are conventional farmers, whereas in the associated crop system, 12.5% are organic farmers who limit their use of chemicals, and 15.63% use chemicals in production (Table 8). Within the group of these Musaceae producers, there are no significant differences between the two production systems (χ² = 0.039521, df = 1, p = 0.8424).

3.5. Producer Typification

3.5.1. Importance of the Considered Variables

The Multidimensional Correspondence Analysis (MCA) revealed four particular individuals (93, 94, 95, and 96) that showed divergence in different agronomic, phytosanitary, and management variables, which significantly influenced the results. These 4 outliers were not considered in the subsequent MCA with the remaining 92 producers (116 categorical variables and 3 supplementary quantitative variables).

The MCA determined that the first six dimensions (axes), which account for 26.41% of the information (

Table 10. Variance of the eigenvalues of the MCA for the significant dimensions for the data from 92 Musaceae producers in the Littoral region of Ecuador.

Dimension	Variance	Percentage
		Contribution	Accumulated
1	0.211	6.625	6.625
2	0.151	4.749	11.365
3	0.134	4.202	15.567
4	0.121	3.810	19.377
5	0.117	3.659	23.035
6	0.107	3.372	26.408

), have significantly greater inertia than that obtained from the 0.95 quartile in random distributions (26.41% versus 22.29%), indicating that they are sufficient to describe the survey data. The first two dimensions highlight the importance of 22 categorical variables of the 27 reflected in the data matrix relating to producer aspects (ethnicity, education level, years as producer), plantation geographic location (province), general information about the crop (cultivar, cultivation system, planting system, propagation method), phytosanitary problems and plantation management (presence of caterpillar, mealybug, fusarium, nematodes, weevil, sigatoka, thrips, viruses or whitefly, phytocontrol type, and soil treatments), and biosecurity measures.

The first dimension (6.62%) contrasts producers 65, 42, 83, 73, 39, 68, 38, and 40, with completed university studies, positioned in the positive portion, with producers 88, 16, 23, 92, 7, and 18, positioned in the negative portion, who only completed primary education. At the same time, the second dimension (4.75%) contrasts producers 16, 23, 92, 7, and 18, positioned in their positive coordinates (Figure 3), with producer 88 positioned in the negative part. In the positive portion of the first dimension, which shows a positive correlation (p = 1.02464 × 10⁻¹¹) with the cultivated area, the producers who grow William’s banana in monoculture—who apply subfoliar irrigation, carry out chemical phytosanitary control and soil chemical fertilization, and consider all possible biosecurity measures—stand out; also, there is a low incidence of R. similis and M. fijiensis (Figure 3). On the negative side, those who cultivate abaca in an organic system would stand out, as they do not apply phytocontrol, biosecurity measures, soil chemical fertilization, or irrigation systems. This results in a medium incidence of R. similis and a low incidence of M. fijiensis. Producer 88 represents a group of producers partially characterized by the characteristics mentioned in this negative portion of the first dimension, whose plantations are small in area (class I), mainly located in the Santo Domingo province, and are free from problems caused by D. grassi. For their part, the group consisting of producers 16, 23, 92, 7, and 18, who grow Barraganete and Dominico plantain in mixed cropping systems, mostly in Manabí province, apply cultural phytocontrol and report low and medium incidence of F. parvula, medium incidence of D. grassi, and high incidence of C. sordidus.

In the order obtained by the third and fourth dimensions, they represent 8.01% of the total inertia (Table 10, Figure 3). Of the 20 categorical variables that highlight these dimensions, 17 had previously been highlighted, 3 appeared as new, and 5 disappeared. The three new categorical variables refer to producer aspects (gender, age, and association). In contrast, the missing variables refer to producer aspects (education level and time as producer), crop general aspects (planting system), phytosanitary problems and management (thrips), and biosecurity measures.

The third dimension places producers 69, 16, 68, 33, 53, 36, 25, and 75 in the positive part, in contrast with producers 89, 70, and 40 who are in the negative part. This positive aspect highlights the Williams banana cultivation in organic plantations using biological phytocontrol, which presents high incidences of M. fijiensis and C. sordidus and an absence of Fusarium. The negative portion, which presents a significant correlation with the producer age (p = 3.8487 × 10⁻⁴), highlights the middle-aged producers (class III) who grow Hartón plantain, chemically fertilize the soil and are mainly from the Santo Domingo province, where D. grassi is absent. However, there is a low incidence of C. viridis and a medium incidence of R. similis.

The fourth and fifth dimensions represent 7.03% of the total inertia (Table 10, Figure 3). Between both dimensions, 20 categorical variables are highlighted, many of which were already highlighted in the previous dimensions. However, a new variable related to the producer’s aspects (property type) has been added, which had not yet appeared.

The fourth dimension contrast producers 3, 26, 2, 82, 7, and 90, which are positioned in positive coordinates, to producers 69, 16, 68, 33, 89, 53, 36, 25, 70, and 75, which are positioned at the negative extreme. The first ones, with incomplete university studies and mainly of Mestizo ethnia, grow Gros Michel banana on plantations in the Bolívar province with low virus or M. fijiensis infections and Fusarium presence. At the same time, the opposite producers are characterized by the characteristics mentioned above in the third dimension.

The fifth dimension contrasts producers 52, 51, 68, 69, 44, 89, 15, 36, 92 and 45, on the right of the graph, with producers 42, 23, 25, 55, 27 and 8 (on the left), in which the production area has shown a significant positive correlation (p = 0.044772). In comparison, the sixth dimension contrasts producers 52, 51, 44, 89, 15, and 92, at the top of the graph, with producers 68, 69, 36, 45, and 59, at the bottom, where time as producer (Figure 3) shows a significant positive correlation (p = 0.026139). As shown in Figure 3, three groups of producers are configured. Producers 51, 52, 15, 44, 92, and 89 are of middle age (class III); they grow Barraganete plantain in plantations in the El Oro province, and despite applying biological phytocontrol and disinfecting their tools, they show medium infestation by weevil (C. sordidus) and high infestation by nematodes (R. similis) and mealybug (D. grassi). Producers 36, 69, 68, 59, and 45 have been as such for a few years (class I) and are not part of agricultural associations, which cultivate Hartón plantain in plantations with surfaces between 46 and 91 ha (class II) in the Manabí or Santa Elena provinces, without pathogen incidences. Finally, producers 42, 55, 8, 23, 27 and 25 have not completed their secondary school studies and have been producers in the Santo Domingo province for between 13 and 25 years (class II) or between 37 and 49 years (class IV), and their plantations are affected by viruses, nematodes and weevils at a low incidence.

3.5.2. Typology of Producers

The MCA establishes six Musaceae producer groups (Figure 4) for the Ecuadorian Littoral region (Figure 5) whose typologies are summarized in

Table 11. Distribution, percentage, and typology of Musaceae producers in the Ecuador Littoral region.

Typology	Cluster	Producers	Percentage
Small Gros Michel banana producers for the local market in the Andean foothills.	1	4	4.4
Small plantain producers for the local market in the northern Littoral region.	2	6	6.5
Small Musaceae producers (including abaca) for the international market via exporters.	3	34	37.0
Plantain producers, mostly for export.	4	20	21.7
Organic banana producers for export.	5	8	8.7
Conventional banana producers for export.	6	20	21.7
		92	100.0

.

Cluster 1: This group is made up of four producers (4.4% of those surveyed), characterized by individuals such as 7 and 26 (Table 11, Figure 4), belonging to the Mestizo ethnic group, who traditionally grow Gros Michel bananas in associated cultivation (mostly with cocoa), located in the Bolívar and Imbabura provinces (Figure 5). They have little technical knowledge, apply lime to the soil, occasionally use chemicals, and have not implemented biosecurity measures. Problems with Foc R1 have been detected in these plantations.

Cluster 2: This cluster is composed of six producers (6.5%) and represented by individuals such as 16, 18 and 23 (Table 11, Figure 4), belonging to the Afro-Ecuadorian and Montubio ethnic groups with low education levels (incomplete secondary), who grow Dominico plantain in association with other crops such as cocoa and corn, in plantations located north of the Littoral region (Figure 5). Like the previous cluster, they are low-tech producers. Their production is marketed nationwide. They conduct cultural phytosanitary control but do not implement biosecurity measures on their farms. The plantations have significant problems with C. sordidus and M. fijiensis, medium infestation with D. grassi, and a low presence of F. parvula.

Cluster 3: This cluster is made up of 34 producers representing 37.0% of the total sample (Table 11, Figure 4). In this group, represented by producer 88, there are organic plantations of Orito, Gros Michel bananas, Barraganete, Dominico, and Hartón plantains, as well as Abacá, all grown in monoculture systems, distributed throughout all the producing areas (Figure 5). These are small producers who cultivate an area of between 1 and 33 hectares (class I), whose products are mainly destined for the international market through export services. They are poorly equipped with technology because they lack irrigation systems, do not apply soil additives, and fail to conduct any phytosanitary control or implement biosecurity measures. No problems with M. fijiensis, R. similis, or F. parvula have been detected.

Cluster 4: This cluster includes 20 small producers (21.7%) (Table 11), represented by producers 89 and 92 (Figure 4), who are characterized by practicing associated cultivation and monoculture of Barraganete and Hartón cooking plantains, mainly intended for export, and a small portion for domestic consumption. Located in eastern Manabí and northern Los Ríos (Figure 5). As biosecurity measures, they only carry out tool disinfection, presenting low infestation of F. parvula and C. viridis and medium incidence of R. similis, M. fijiensis, and C. sordidus.

Cluster 5: This cluster comprises eight producers (Figure 4) (8.7%), with producer 68 as its representative. These are professional, technically advanced producers dedicated to organic Williams banana production for export, located in the dry tropics of the Ecuadorian Littoral in the El Oro and Santa Elena provinces (Figure 5). These plantations have a cultivation area of between 47 and 91 hectares (Class II), originating from vitro plants and using subfoliar irrigation, where biological control is practiced. They also have high levels of R. similis, M. fijiensis, and D. grassi.

Cluster 6: This cluster is composed of 20 producers (21.7%) with completed university studies (Figure 4) and the highest level of technical development in conventional fruit production, featuring William’s banana monoculture for export, located in the humid tropics of the Littoral in the Los Ríos and Guayas provinces (Figure 5). This group is represented by individuals such as 38, 39, 40, 42, 65, 73, 83, and 90 (Figure 4), characterized by the application of chemical fertilizers to the soil, chemical phytosanitary controls, subfoliar irrigation, and the implementation of all possible biosecurity measures.

3.6. Production System Vulnerability

The vulnerability index (Iv) obtained for the 96 farms studied, after applying formula (3), ranges from −0.40 to 3.20, with an average value of 0.65 and a median of 0.00 (

Table 12. Vulnerability levels and summary of their statistics.

Vulnerability Level	Low	Medium	High	Critical
Case number	35	20	20	21
Farm percentage	36.46	20.83	20.83	21.88
Range of Iv	−0.40–−0.20	−0.20–0.00	0.00–1.60	1.60–3.20
Average Iv	−0.22	−0.02	1.14	2.27

, Table S3). The ranges of values of the Iv quartiles have assigned each of these farms to one of the four previously established vulnerability categories (Figure 5). The largest number has been classified as low Iv (35), while the categories with the smallest farm number (20) were classified as medium and high Iv (20). Although the distribution of farms between the proposed vulnerability levels is not identical, since the low and critical levels have presented more farms than the medium and high levels (Table 12), no significant differences were detected for the proportion of farms by vulnerability level (χ² = 0, df = 3, p = 1).

As can be seen (Table S3), the exposure values for the analyzed farms are correlated with their vulnerability indices (r = 0.659), indicating that the Foc TR4 infection risk level (exposure) increases as they approach the entry sites. This is more evident in the plantations located in the El Oro (r = 0.995), Guayas (r = 0.766), and Manabí (r = 0.761) provinces.

The Iv is not represented in the producer groups in a homogeneous way (Figure 6). It has been verified that in four of these clusters (3 to 6), there are farms with a critical IV level, while in three of the clusters (1 to 3), the frequent IV levels are low and medium. Considering the frequency of high and critical Iv levels, the farms of producers included in Clusters 5 and 6 are the most vulnerable to being affected by Foc TR4.

On the other hand, by superimposing the spatial distribution of the Iv with the leading road network (paved roads) (Figure 5), especially those that connect with the Guayaquil port, a greater concentration of farms with high and critical Iv is observed, in contrast to the farms located in the eastern Andean foothills corresponding to Cluster 1 and those located on the north Littoral corresponding to Cluster 2, where low and medium Iv levels predominate (Figure 5). This pattern suggests a relationship between road accessibility and the exposure of plantations, mainly related to the transportation of their production.

4. Discussion

As in the preceding section, the Discussion is segmented into subsections to highlight the points deemed most noteworthy. The initial subsection will address age, ethnicity, education level, and associations. The subsequent subsection will focus on cultivars and biosecurity measures. The third subsection will analyze the typification of producer profiles. Finally, the vulnerability to Foc TR4 will be examined.

4.1. Age, Ethnicity, Educational Level, and Associativity

This subsection discusses four attributes of the Musaceae producer sample. Age analysis offers insights into generational change, while educational level helps us understand the adoption or rejection of biosecurity measures or compliance with regulations set by the responsible agricultural authorities. Educational level can influence the adoption of new technologies and the willingness to try new farming practices, as it is linked to improvements in quality and higher productivity. It may even contribute to the development of resilient and sustainable production systems. Associativity influences crop improvement, quality, and productivity. However, participating in an association is not solely about gaining direct benefits but also involves understanding and improving teamwork [73].

In the sampled data, the number of male producers (80) stands out in comparison to female producers (16), with ages ranging from 22 to 88 years. Male producers tend to be older than their female counterparts. They predominantly represent the three surveyed ethnic groups. A broad spectrum of educational levels has been observed among the producers overall, from individuals with no basic education (the fewest) to those holding master’s and doctoral degrees. Nonetheless, most producers generally possess primary or secondary education. This pattern of educational attainment is similar when considering ethnicity, with the exception of the Afro-Ecuadorian group due to its low representation. Membership in associations remains very low, regardless of the producers’ gender, ethnicity, or educational level.

The age of the people surveyed presents values similar to those mentioned by the authors of [42], who reported average ages of 54 and 47 years for each gender, respectively. These data also agree, despite the different age classes considered, with those published for Ecuador, where it is evident that the greatest concentration of agricultural surface is run by adult producers, in the age group of 45 to 64 years, and that 31.5% of the agricultural area is worked by producers over 65 years old [24], which shows an ageing of the population in the agricultural sector. Likewise, agricultural producers in the Littoral region [24] identified themselves as Mestizos (66.2%), Montubia (11.2%), and Afro-Ecuadorians (1.2%), which are numbers that coincide with those obtained in this study.

The general educational level of producers in Ecuador [24] is primarily primary studies (53.9%), followed by secondary (19.7%), higher (11.2%), and postgraduate (1.1%) studies. However, in the case of the surveyed Musaceae producers, these proportions are not equivalent. The educational level of Musaceae producers is generally higher. There are fewer producers with primary education, but a greater number with secondary, university, and postgraduate degrees who have completed their studies. However, although the educational level of Musaceae producers is positive, at around 33%, a high percentage of producers have only completed primary education, reaching barely 24%. Furthermore, a significant number (20.9%) have not completed the studies they started.

Regarding the associativity of the Musaceae producers interviewed, only 15.6% belong to a guild (Table 5), which differs from the values reported in another study, where 47% of the producers were found to belong to an association [40]. This difference is because, in that publication, only producers dedicated to exporting from the northern area of Los Ríos were considered. At the same time, the present investigation provides information from the entire Littoral region and the foothills of the Andean region. Also, that reference is made only to plantain cultivation in a broad sense, although the Barraganete and Dominico cultivars are mentioned briefly [40], while other Musaceae cultivars have been included here in addition to the two mentioned.

4.2. Cultivars and Biosecurity Measures

Farmers’ preferences for a particular cultivar are primarily influenced by disease resistance, yield, market demands, and agroclimatic conditions [32,74,75,76]. In countries like Uganda, producer preferences depend on ancestral customs rooted in food security, better adaptability, and environmental tolerance, as well as the maturation cycle, texture, and flavour of the product, and the industry’s importance, especially in the brewing industry, as well as in local and export markets [74,76]. The domesticated species of the genus Musa exhibit considerable phenotypic plasticity [77], resulting in considerable phenotypic diversity [78,79] that extends beyond morphological [80] and genotypic [81,82,83] traits, as a consequence of the practical preferences of farmers and producers for different cultivars [84]. However, all this diversity and its implications are not yet well known [85].

The preference for Cavendish group cultivars (Valery and Williams) is due to their high productivity, disease resistance (Foc), and high international demand [86], which has favoured their expansion and required the implementation of stricter biosecurity measures to prevent the spread of diseases such as Foc TR4 [87,88]. However, our analyses have shown that growers of Williams’ organic bananas are facing a high incidence of M. fijiensis, in addition to infestations with C. sordidus, due to the use of biological control practices. In the case of M. fijiensis, as in other pathogenic fungal species, the presence of reproductive structures (ascospores and conidia) facilitates its anemochory [89,90] or hydrochory [91,92], depending on environmental conditions, which allows it to infect more or less nearby plants [93,94,95,96]. This pathogen type is challenging to control, and the most effective strategies typically involve the use of chemicals [97]. For this reason, in organic production plantations, where chemical use is limited, pathogen incidence tends to be high [96,97]. Likewise, it is known that infections caused by M. fijiensis are limits to sustainable banana production worldwide [98,99,100]. In Ecuador [100], the control of this pathogen in the conventional system has led to an increase in the use of fungicides, which has negatively impacted human health, the environment, and the economy of small producers due to rising production costs.

Barraganete shows similarities with the Cavendish cultivars in terms of technical development or biosecurity measures. However, it is preferably grown in more traditional systems, as is the case with other cultivar groups in West African countries, which exhibit different responses to local pests or diseases [75,79]. In contrast, Gros Michel production is linked to cultural traditions. It is limited to the western Andean foothills, where the subtropical climate reduces the incidence of M. fijiensis, which is more prevalent in tropical environments [101]. Another factor contributing to the decrease in the aggressiveness of the disease is the association with Musaceae cultivars [101]. Cedeño et al., in their study with Barraganete plantain in monoculture [101], demonstrated a reduction in the incidence of the disease by around 50%. On the other hand, the Gros Michel cultivar increases the Brix degree concentration and titratable acidity [102,103], characteristics directly related to the flavour and colour of the fruit.

The Foc R1 presence in Gros Michel is strictly due to the susceptibility of this cultivar to this fungal infection, as reported towards the end of the 1950s [104] in almost all the Ecuadorian producing areas. However, there are areas, such as the western Andean foothills of Bolívar province, where this cultivar is still produced on a small scale, due to the favourable latitudinal zones that create special microclimates where the pathogen has not produced irreversible epidemics, in addition to generational customs and the deep-rooted consumption in some national markets. These results are compatible with other studies that evaluated, in addition to the Gros Michel cultivar, Orito, Maqueño morado and Dominico hartón in sites of Cumandá and La Maná, in Chimborazo and Cotopaxi provinces, respectively, located along the western Andean foothills [105,106], which have diverse agrarian dynamics, typified in microregions [107], due to their geographical position and agroecological characteristics [108].

The low adoption of biosecurity measures may be due to the increased production costs of implementing them, which were estimated at USD 2524.0 ha⁻¹ by 2024. However, the biosecurity measures applied in Musaceae production have been imposed by government resolution since 2019, to prevent the entry of Foc TR4 into Ecuador [109] and also to prevent the internal dissemination of R. solanacearum [36]. Essentially, the measures implemented (tool disinfection, footbaths, and wheelbaths) for moko disease control, caused by the R. solanacearum bacterium, a vascular pathogen with a high incidence in all Ecuadorian producing areas, do not incur a high cost [110]. Government resolution 0072 [111] seeks to encourage producers to adopt biosecurity measures to prevent the spread of this bacterium. The high percentage of producers who do not implement biosecurity measures is mainly due to their unawareness of government proposals and resolutions. The adoption of biosecurity measures reflects the producers’ capacity to respond to the phytosanitary conditions that occur in their plantations and their environment, which are related to their knowledge level [112] and union will [12].

Biosecurity is a shared responsibility among stakeholders (government agencies, industry, and producers), for which practices such as exclusion, eradication/confinement, and control [113] must be adopted, to reduce the risk of a disease [114]. Therefore, prevention becomes the most effective [115] and lowest-cost strategy for Musaceae plantations [116,117], where producers, in addition to becoming familiar with the diseases, dedicate their time to carrying out surveillance and management operations [118]. In Ecuador, recommendations for prevention have been provided, which include disinfecting footwear, vehicles, agricultural machinery, and tools, maintaining a visit record, establishing a phytosanitary security area, and providing clothing, signage, information panels, and personnel training [36].

4.3. Typification of Producers’ Profiles

Trials on Musaceae producer typification [108], as well as for other agricultural areas [55,119,120,121], have been based on variables of a different nature (qualitative and quantitative), not always coinciding, relative to the plantation size and cultivated area, production scale (harvest and productivity), cultivation practices (monoculture, intercropping, agroforestry), socioeconomic characteristics (gender, educational level, credit fund access, income, associativity), environmental and ecological characteristics (precipitation, water resources, altitude, soils), cultivation systems (organic or conventional), and regional diversity (cultivars) [122,123,124]. In short, it is about collecting information, often through surveys, on the agronomic, socioeconomic, and ecological characteristics of the plantations [125]. The objective is to understand the diversity among farmers for plant improvement, conservation, extension, and socioeconomic planning [121], for which different statistical methods (cluster analysis, Principal Component Analysis, Multiple Correspondence Analysis) have been applied depending on how the relationship between the variables studied is considered [126]. Logically, the variables selected will influence the results obtained [127].

The MCA has highlighted a series of categorical variables in the six significant dimensions that generally coincide with other typifications made in Musaceae production [122,123,124,128], such as cultural practices, cultivars, phytosanitary problems, and plantation management. However, differences may always be found depending on the variable’s nature and typification objectives [126], as in the work of López Mejía and collaborators [28] in which they considered a series of questions in their survey to assess issues related to the different market aspects of the products produced in the farms analyzed or the production systems before Musaceae implementation. However, they found that phytopathogens and the monoculture farming system were important in explaining the producer groups, as occurred in this study.

On the other hand, the contribution of the farms’ geographical location in different provinces, with varying socioeconomic, geographical, climatic, and environmental conditions [107], as well as the cultivar type, has become a significant variable in the configurations of the arrangements represented in Figure 3. In this regard, Musaceae cultivation in different agroecological zones of the country shows variability in disease incidence, such as M. fijiensis and moko, which directly influences the control strategies adopted [76]. However, moko disease is not a significant variable in the dimensions analyzed.

The interpretation provided by Guamán [129] of the results obtained in the mixed data factor analysis (MDFA) in his study on the factors influencing plantain production (Musa AAB) is consistent with the orders detected in the first two MCA dimensions applied in the present study. The first factor was called “surface” and was defined by the harvested surface, the productive age surface, the planted surface, and sales [129]. The second factor, which he called “use and care”, was defined by the use of phytosanitary products, chemical pesticide use, and chemical fertilizer use [129]. Unfortunately, it does not provide the analyzed data matrix to establish a more detailed comparison. In general terms, this approach [129] highlights that the characteristics related to the cultivation area, phytocontrol, and biosecurity measures are fundamental information in the typological analysis of Musaceae producers.

In the characterization of plantain-producing agrosystems in Santo Domingo and El Carmen towns, López Mejía and collaborators concluded that there were two productive systems: monoculture (“Group One”) and association (“Group Two”) [28]. Its “Group One” focuses on an intensive and exclusive plantain production, which would involve the use of agrochemicals, limiting biodiversity. In contrast, its “Group Two” focuses on a mixed and alternating production based on associated perennial fruit and forest species. These cultivation systems have also been considered in the data analyzed in the present study; however, their importance was only evident in the ordination obtained by the first two dimensions. The conclusion reached by López Mejía and collaborators is due to the items collected in their survey [28], which considers phytosanitary, productive, and local market aspects, presenting differences depending on the respective production system. In the present study, monoculture has been associated with the Williams cultivar, export, and conventionally managed plantations using phytochemicals. For its part, the associated cropping system has been related to the Barraganete and Dominico cultivars, as well as organically managed plantations, utilizing cultural phytocontrols.

To date, Ecuadorian agricultural farms’ characterizations have been of a socioeconomic nature in which different variables have been considered, as proposed by Cepeda et al. (2007) [130] who established four producer types from a producer socioeconomic analysis (multi-activity subsistence family farms, commercialized family farms, employer farms and capitalist farms) whose basic criterion was the labour allocation in the different productive processes in the farm. Tamayo & Cepeda [108], applying the same premises and after a banana sector historical analysis, defined four producer types (small employer farms, medium employer farms, commercial farms, and agro-exporting capitalist farms). For their part, Pocasangre and collaborators [131] proposed three production system types (conventional intensive production system, low-input agroforestry production system, and organic production system) based on different characteristics of agronomic practice. They applied to any plantations in Latin America. The typologies proposed in this study are based on socioeconomic, management and administration, cultivar type, or planting system characteristics that are easy to respond to and quantify, which is not the case with the previously discussed typologies. These six typologies are constructed within a methodological framework that combines expert knowledge, producer participation, and the application of multivariate analysis [127].

Clusters 1 and 2 comprise small producers of banana and abaca, both organic and conventional, serving the local market. These producers correspond to the types of pluriactive subsistence family farms and commercialized family farms [130] or employer farms [108]. Clusters 3 and 4 would correspond to employer farms [130] and medium-sized employer and commercial farms [108]. Taken together, these four clusters would correspond to low-input agroforestry production systems and organic production [108,131]. Finally, Clusters 5 and 6 would correspond to capitalist exploitations [108,130] or to the conventional intensive production system [131].

Production systems for Musaceae in Ecuador have only been studied in relation to bananas and plantains. However, other species and cultivars play a vital role in food security and the local economy. This study included economically significant Musaceae in a single analysis, demonstrating that plantations are not solely determined by the species cultivated but also by the management practices used by farmers. This information is helpful for decision-making from both research and public policy viewpoints. Characterizing production systems helps to identify the realities faced by farmers and the aspects that should be considered when planning activities.

4.4. Vulnerability Facing Foc TR4

The Iv calculated for the farms is consistent with the reality of Ecuadorian Musaceae production systems in terms of exposure factors (distances to entry points and biosecurity) and sensitivity (genetic and environmental vulnerability). Therefore, the farms that are closest to the possible entry points of the pathogen (El Oro, Guayas, Manabí, or Santa Elena) have higher exposure values, which translates into an increase in their vulnerability [132]. However, Iv on farms in the same production area may present lower values as a result of adequate agronomic management and administration. Based on the information collected from the survey, it was found that farms located near the country’s ports of entry correspond to production systems that can be conventional in large areas or organic in smaller areas. In both cases, production is carried out intensively (technologically) and the harvest is destined for export. The fruit marketing in external markets enables these farms to invest in biosecurity systems, which are efficient measures to counteract the risk of Foc TR4 entry, but not its possible establishment [35]. Although these farms implement biosecurity measures, they remain at high risk of incursion from this pathogen.

Although the farms’ distance to the road network was not considered as a vulnerability study variable, the incidence level observed in Figure 5 suggests a possible relationship. Previous studies in a wild species (Plantago lanceolata L.) have shown that road proximity can favour the dissemination of pathogens (Podosphaera plantaginis (Castagne) Braun & Takamatsu), by facilitating the movement of spores and contaminated materials through vehicular and human traffic [133]. Therefore, the road network could be an important factor in dispersion dynamics that should be considered in future research.

On the other hand, farms located further away from the sea and land ports of entry to the country (in the lower part of the foothills of the mountain range in Los Ríos, Bolívar, and Cotopaxi) frequently present low Iv values, given that their exposure factors are also low. However, they share the Foc TR4 genetic susceptibility [32]. These production systems are traditional and mainly produce Gros Michel bananas for domestic consumption, and are also characterized by specific commercial relationships. Unlike the coastal plains’ farms, the producers of these farms do not acquire phytosanitary products or fertilizers at the same commercial sites, and the few who apply them do not use the same communication means with the Littoral transport vehicles and supply [134]. Furthermore, the harvest marketing is mainly focused on Andean region markets, utilizing vehicles that transport other vegetables, such as potatoes (Solanum tuberosum L.), or other fruits from the Andes foothills and high altitudes (Figure 7); therefore, the risk of moving soil with Foc TR4 propagules or infected material is minimal.

Genetic vulnerability is primarily determined by the diversity of resistance genes in a crop variety, as well as by environmental interactions with pathogen populations or abiotic stress levels [135]. In the Ecuadorian scenery, where production systems are based on cultivars without genetic resistance, the genotype–environment interaction is highly influential in determining genetic vulnerability to Foc TR4. The cultivars’ interaction with soil microorganism populations, which are present in both organic and traditional crops, can be associated with the biotic suppressiveness levels of soil [136,137], which would explain why, in several farms, mostly of Gros Michel bananas, there is Foc R1 presence, but with low intensity levels and economic impact [138]. In traditional cultivation systems, the high genetic vulnerability of cultivated varieties is compensated for by low environmental vulnerability levels, possibly as a consequence of crop management practices that contribute to the maintenance of diversity [139]. Although biotic or abiotic suppressiveness has not been studied in these soils, the presence of these two phenomena would explain why epidemics caused by Foc are more severe in traditional agriculture than in conventional agriculture.

Vulnerability of the systems of Ecuadorian production has not been assessed. However, this study estimates the Foc TR4 risk outbreaks in banana crops in Ecuador based on climatic data, concluding that all banana-growing areas have favourable climatic conditions for an Foc TR4 outbreak, increasing in those areas with higher cultivation intensity [38], which in this case would be Los Ríos with 69,309 ha, Guayas with 53,857 ha and El Oro with 33,968 ha [25]. However, other studies conclude that highland crops in the Bolívar and Pichincha provinces have unfavourable conditions for a pest outbreak [38]. Added to this circumstance is the ecological diversity and low exposure, confirming that traditional production systems in foothills are less vulnerable to Foc TR4 entry and establishment compared to intensive conventional production systems located in the coastal plains, which have greater exposure and crop homogeneity [22,32,95].

The estimated Iv indicates levels of low and critical vulnerability, as well as intermediate responses. Iv can be valuable both for designing phytosanitary surveillance activities, where plantations are monitored for early detection, and for public policies to ensure biosecurity measures are prioritized to reduce the risk of the pathogen entering the most exposed areas. In this way, resource allocation and surveillance efforts would be guided by Iv values, enabling the implementation of the most suitable biosecurity measures based on the crop’s characteristics.

The current disease absence in the country suggests that the contingency plan implemented for Foc TR4 prevention, detection, and control, decreed by the MAG [140], together with the contingency plan of neighbouring countries, has been effective [141]. However, in the face of the threat, INIAP is evaluating the agronomic behaviour of the Cavendish clone, GCTCV 218 (Formosana), and six Gal clones with Foc TR4 resistance [142]. The introduction of pathogen-resistant cultivars will significantly influence the vulnerability of production systems. Currently, there are no resistant varieties grown commercially in Ecuador; they are being evaluated. Iv results could also be useful in identifying which farms should prioritize switching to a resistant variety as a mitigation measure against the introduction of Foc TR4. Furthermore, the characteristics of production systems can also be instrumental in designing impact mitigation strategies, such as identifying areas where the pathogen can easily establish itself and promoting the transition from susceptible to resistant varieties.

Additionally, a risk analysis was conducted to assess the potential introduction of Foc TR4 in Ecuador, evaluating the probability of entry and establishment of the pathogen. In the income component, it was concluded that the probability was high for all Musaceae crops in the country [143]. However, epidemiological studies indicated that the pathogen’s mobility towards free zones was highly determined by anthropogenic factors [20]. This is the reason why there are still areas free of this pathogen in countries where Foc TR4 presence has been reported [35]. On the other hand, in the establishment component, it indicates that Ecuadorian crops have a high probability for Foc TR4 to establish itself and have high economic consequences [143]; however, it does not explain why several Gros Michel, Maqueño or Hawaiian banana farms have Foc R1 with a low disease intensity (incidence and severity) and their harvest remains economically profitable.

5. Conclusions

Through the analysis of farmers’ profiles and the characteristics of their production systems, including the biosecurity measures adopted and cultivars, the diversity of Ecuadorian Musaceae producers has been identified, defined, and characterized, although the sample analyzed is not representative. The final overview of the producers is summarized in the following four points:

(1) Among Ecuadorian Musaceae producers, male producers stand out compared to female producers, with ages ranging from 22 to 88 years. Male producers tend to be older than their female counterparts. They predominantly belong to the three ethnic groups surveyed. A wide range of educational levels is observed among the producers, from those with no formal education to those holding master’s and doctoral degrees. However, most producers generally have primary or secondary education. This pattern of educational attainment is similar across ethnicities, except for the Afro-Ecuadorian group, which is significantly underrepresented. Membership in associations remains very low, regardless of gender, ethnicity, or educational level.

(2) The preferred cultivars for cultivation include those of the Cavendish group (bananas) and Barraganete (plantain), which are primarily produced for export, as well as Gros Michell (banana) and Hartón (plantain) for local consumption. However, abaca, despite having a significant export market [144], was not emphasized in the sample.

(3) The insufficiency in the implementation of biosecurity measures is prevalent among producers across all age groups, which contrasts with the higher proportions of producers possessing secondary or higher education. Smaller plantations are more inclined to lack biosecurity measures, whereas an increase in the cultivated area does not exhibit a definitive pattern regarding the application of biosecurity protocols. It is crucial to enhance awareness and provide training to producers for the implementation of biosecurity protocols.

(4) The typification was developed using producer attributes commonly considered in this area of research; however, in this case, other characteristics were also included, such as observed diseases in the field, implemented biosecurity measures, and production systems, which play a key role in explaining these groups of producers. The six typologies illustrate the diversity of Musaceae crops in Ecuador by covering various morphologically distinct varieties, thus creating a foundation for future research. What is remarkable about these typologies is that they were constructed within a methodological framework that combines expert knowledge, who designed the survey questions, with input from producers, which, unfortunately, was not as extensive as desired, alongside the application of multivariate analysis, including MCA and CA. It is essential to incorporate additional economic variables in future analyses to improve the clarity of the typologies presented.

Meanwhile, a vulnerability index (Iv) was created to evaluate the threat of Foc TR4 in the sample plantations, based on criteria set by experts. Iv was calculated using exposure, which measures a risk level, cultivar sensitivity (including genetic and environmental vulnerability), and socioeconomic factors (such as management capacity and education level), all of which affect the entry and establishment of the pest. The risk level (exposure) is positively linked to the Iv, meaning the closer a farm is to potential Foc TR4 entry points, the higher the Iv. The benefit of Iv lies in its straightforward calculation and its capacity to be adjusted as new information emerges. The proposed vulnerability levels will support decision-making in areas where the Iv is highest, indicating where more focused controls should be implemented to prevent Foc TR4 entry.

The vulnerability levels of Iv show that producers classified as “small producers” (Clusters 1, 2, and 3) are less vulnerable compared to others. The previously established typologies exhibit higher vulnerability levels the closer they are to main communication routes, border crossings, or seaports, emphasizing those in the provinces of El Oro, Guayas, Manabí, and Esmeraldas. Unfortunately, during the final review of this work, the detection of Foc TR4 in the province of El Oro [145] was announced, confirming the validity of Iv. It is hoped that the measures implemented by government officials and the experience gained in recent years in neighbouring Colombia will assist in containing and reducing this outbreak of Foc TR4 in Ecuador, which has, until now, not been affected by this disease.