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Communication

Native Cherimoya Trees with Commercial Potential from Southern Ecuador

by
Mirian Capa-Morocho
1,2,*,
Fernando Granja
1,2,
Marlene Molina-Müller
1,2,
Santiago C. Vásquez
1,2,
Santiago Erazo-Hurtado
1,
Alejandro Vaca
1,
Marlon Oswaldo Pineda-Escobar
1,
Guillermo Rogel
1,
Melissa A. Romero
3 and
Diego Chamba-Zaragocin
4
1
Agronomy Department, Faculty of Agricultural Sciences and Renewable Natural Resources, National University of Loja, Guillermo Falconí University Campus, Loja 110103, Ecuador
2
Research Group in Ecophysiology and Agricultural Production (AgroPHYS), National University of Loja, Guillermo Falconí University Campus, Loja 110103, Ecuador
3
Agricultura Engineering, Pontifical Catholic University of Ecuador, Amazonas Campus, Quito Way Km 12 ½ Right Margin-Second Line, Santa Cecilia, Nueva Loja 210205, Ecuador
4
Department of Agricultural Engineering, Faculty of Agricultural Sciences and Renewable Natural Resources, National University of Loja, Guillermo Falconí University Campus, Loja 110103, Ecuador
*
Author to whom correspondence should be addressed.
Crops 2026, 6(1), 7; https://doi.org/10.3390/crops6010007 (registering DOI)
Submission received: 8 November 2025 / Revised: 2 December 2025 / Accepted: 17 December 2025 / Published: 4 January 2026
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Abstract

The cherimoya is a plant resource of high genetic and economic value. However, in Ecuador, it remains poorly documented, particularly under the restrictive orographic and climatic conditions of the Andean region. The lack of information limits the use of native materials in breeding and conservation programs. Therefore, this study evaluated native cherimoya populations using standardized fruit quality descriptors to quantify existing variability and identify promising native morphotypes. Hierarchical clustering was used to identify groups with similar traits. PCA captured the characteristics of the fruits that contribute to variability, while the multi-character index determined the traits that contribute to fruit quality. Remarkable diversity in commercial attributes, including pulp yield, fruit weight, and sweetness–acidity balance, was identified. Clusters highlighted the morphotypes LMPB04, SUMB04, and PTA01, from Loja, Saraguro, and Paltas, respectively, as having the highest titratable acidity and fruit weight. In contrast, the multi-character index prioritized the pulp/seed and SS/TA ratio, identifying potential in EACAD01 and LYHA01 from Espíndola and Loja, respectively. These results demonstrated the existence of superior cherimoya individuals adapted to Andean conditions and provide a basis for developing high-quality, promising material that meets local and international market demands.

1. Introduction

The cherimoya (Annona cherimola Mill.) is a fruit species native to the inter-Andean valleys of Ecuador and Peru [1,2]. Several studies indicate that the province of Loja, in southern Ecuador, represents an important center of diversity for this species [1]. In this region, the cherimoya forms forest patches located between the humid Amazon basin and the coastal zone influenced by the cold Humboldt Current [3]. The topography of Loja varies between 150 and 3600 m above sea level, creating a marked heterogeneity of microclimates and ecological zones [4].
Interest in this fruit tree lies in its excellent organoleptic characteristics and potential for commercial production, which provides income for both small and large farmers [2]. The high diversity described for the Annonaceae [3] has also been identified in southern Ecuador, where environmental contrasts caused by abrupt variations in climate and topography have favored adaptability, differentiation, and intraspecific variability of local morphotypes [4,5,6,7]. The influence of the environment is reflected in the wide range of fruit morphologies and exocarp types, as well as in the presence of efficient natural pollinators, allowing the species’ yield to be maintained without the need for artificial pollination [8].
The Cumbe variety has become the most widely distributed cherimoya commercial variety in national and international markets due to its organoleptic attributes and uniformity; however, this preference for a single genotype is accelerating the erosion of genetic diversity and compromising long-term sustainability [1,9]. The reproduction and exchange of grafts among producers have led to the development of derived ecotypes, limiting opportunities for genetic improvement and reducing resilience to pests, diseases, and climate change [9]. Therefore, it is necessary to systematically characterize native ecotypes with commercial potential to diversify the supply and strengthen in situ and ex situ conservation strategies [1,10].
Given the notable positioning of cherimoya in specialized markets and its high cost per fruit compared to other fruit crops, it is necessary to develop materials with superior quality traits to enhance production and genetic selection programs [9,11]. Despite this potential, there are still knowledge gaps, particularly regarding attributes that exhibit significant variability among trees in native populations, morphotypes that stand out for their agronomic and commercial potential, and their adaptability to adverse conditions. Although there are extensive germplasm collections focused on the conservation of plant genetic resources, these have not been available for evaluation using systematic criteria aligned with domestic consumption and export requirements [8,12].
Due to the increasing commercial interest in cherimoya in international markets, it is essential to have current information on the quality and yield of fruit from native populations in the Andean region. In this regard, the objective of this study is to characterize the phenotypic variability of local morphotypes and identify promising, adaptive attributes to select material with high potential for incorporation into genetic improvement programs.

2. Materials and Methods

2.1. Experimental Conditions

The investigation was conducted in the cantons of Calvas, Celica, Espíndola, Gonzanamá, Loja, Paltas, Quilanga, and Saraguro, in the province of Loja, located at elevations of approximately 1100–2300 m.a.s.l. (meters above sea level) (Figure 1). Local soil and climate conditions exhibit marked variability across the different altitudes and ecologies of the region. In the study area, minimum temperatures are around 15 °C, maximum temperatures can reach up to 30 °C, and average temperatures range from 22 to 27 °C. Relative humidity varies between 65 and 95%, and monthly rainfall varies from 12 to over 450 mm. Additionally, the Photosynthetically Active Radiation values range from 760 to 900 µmol m−2 s−1. The physical and chemical parameters of the soils in the studied areas were also collected and are presented in Table 1.

2.2. Experimental Material

A total of 948 fruits were collected from 270 native cherimoya trees, considering different exocarps (1 tree was considered a morphotype). An average of 3 to 4 healthy, well-developed fruits in the ripening stage were collected per plant from three different locations on the plant: upper, middle, and lower, according to the criteria of Andrés-Agustín et al. [23], Ozowara & Whitehead [24] and Vargas-Mendoza et al. [25], which are applied to diversity and reproduction studies. For the selection of trees to be sampled, trees separated by 1 km from each other were considered, in accordance with the germplasm conservation guide [26]. Each selected tree was georeferenced in the field using a Garmin GPSMAP® 66s GPS device (Garmin Ltd., Olathe, KS, USA), and the information generated is presented in Figure 1. Physiological maturity was determined based on changes in the color of the fruit skin, which changes from green to yellowish green or a dark, shiny green color, according to the criteria established by Gentile et al. [27]. The harvested fruits were transported to the Bromatology Laboratory at the National University of Loja. In the laboratory, the fruits were kept under ambient conditions, with an average daily air temperature of approximately 16.2 °C and an annual relative humidity of around 76% [28], until the quality evaluation.

2.3. Quantitative and Qualitative Parameters

The cherimoya characterization utilized quantitative and qualitative descriptors [29]. The quantitative descriptors measured (Table S1) included a comprehensive set of tree morphology (e.g., crown diameter, tree height, trunk cross-sectional area, main trunk height, branch length, number of leaves per shoot and number of nodes per meter of branch) leaf characteristics (e.g., lamina length, width, and thickness).
Crucially, the following fruit quality attributes were also measured: fruit length, diameter, and weight; exocarp thickness and weight; pulp weight; total seed weight and count per fruit; pulp/seed relation; firmness; soluble solids content; titratable acidity; the ratio of soluble solids to acidity; and fresh seed weight and dimensions.
The qualitative descriptors (Table S2) included plant architecture, growth model, trunk ramification and suckering tendence. For the leaves, the leaf blade shape was measured. Finally, fruit traits assessed the shape, exocarp type and color.
Five key variables were selected to identify superior trees with commercial potential for cherimoya. The principal variable chosen was the pulp/seed ratio, with an observed mean of 8.46, as this characteristic is the most sought after in the market [30]. To apply a more stringent selection criterion, only fruits with a pulp/seed ratio higher than 15 were chosen. Additionally, four other parameters were considered for selection: titratable acidity greater than 0.33% citric acid in 100 g of pulp [31], soluble solids content in pulp greater than 19 °Brix, an average fruit weight of 300 g [32], and a soluble solids/titratable acidity ratio between 5.27 and 21.6 [33]. The detailed methodologies for characterizing these five key quantitative variables are presented in Table 2. In order to organize and group the fruits, a standardized coding system was applied. For example, in the code PTA01, the letter “P” corresponds to the canton of Paltas, the letter “I” identifies the Tunaspamba sector, and the letter “A” indicates the order of the property (A, B, C, D, etc.), while “01” corresponds to the plant number associated with the morphotype. Likewise, to determine reliable averages for quality parameters, characterization guidelines for fruit crops were used [29], where each fruit was measured individually three times; once all measurements were collected, the average value per morphotype was calculated.

2.4. Statistical Analysis

Descriptive statistics were calculated, including the maximum, minimum, mean, standard deviation (SD), and coefficient of variation (CV). Hierarchical clustering analysis was performed using the average linkage method and Euclidean distance Prior to performing the Pearson correlation analysis, the assumptions of normality, linearity, and homoscedasticity were verified to ensure the validity of the test. Subsequently, Pearson correlation coefficients were determined to assess the relationships among traits. Finally, Principal Component Analysis (PCA) was performed to illustrate the patterns of variation among the accessions. All analyses were performed using RStudio 2025.09.2 Build 418 [34].

2.5. Special Correlation Analysis Between Geographic and Phenotypic Distances (Mantel Test)

In order to assess whether phenotypic divergence between individuals is associated with geographical proximity, Mantel’s test based on Pearson correlations was applied. R software 4.5.2 was used [34] with the vegan [35], geosphere [36], readxl [37] and dplyr [38] libraries. For data preparation, the geographic coordinates of each tree were entered in decimal degrees to construct a geographic distance matrix using the Haversine distance. For the phenotypic data, the quantitative variables were standardized using z-scores prior to calculating Euclidean distances. These matrices were compared using a Mantel test with 9999 permutations, using Pearson’s correlation coefficient.

2.6. Multi-Character Selection Index Analysis

The multi-character index was calculated by integrating the five fruit quality parameters mentioned above. The data were processed with R using the readxl package for import and the dplyr package for handling. Z-scores were used for standardization and combined into a linear index represented in Equation (1):
I = ∑ a i z i
where a i are the weights assigned depending on the relative importance of the feature. In addition, the individual contributions were estimated. ( a i z i ) to identify the variables that contributed most to the final index. The values were then ordered from highest to lowest I to determine superior morphotypes.

3. Results

3.1. Descriptive Statistics and Promissory Material Selection

To focus on the most promising material for genetic improvement and commercial potential, a strict selection criterion was applied to the initial population based on five key quality traits. Only specimens that met or exceeded high thresholds for pulp/seed ratio (greater than 15), titratable acidity (greater than 0.33%), soluble solids (greater than 19° Brix), and fruit weight (at least 300 g), while maintaining an optimal soluble solids/titratable acidity ratio, were chosen. This process reduced the total study population to 17 promising accessions. For each accession, vegetative, reproductive, and fruit traits were summarized to assess whether the accessions converged on similar phenotypes or exhibited differentiated patterns. Complete details are provided in Supplementary Tables S1 and S2. Considering the observed differences in phenotype, future research should use molecular tools to confirm whether these fruit samples come from distinct genetic lineages or a single heterogeneous population. Among these selected accessions, productive traits showed the greatest variation, specifically the pulp/seed ratio (29.48%) and fruit weight (20.47%). Conversely, traits exhibiting the least variability were titratable acidity (12.82%), soluble solids (14.83%), and the soluble solids/titratable acidity ratio (15.51%) (Table 3).

3.2. Correlations

The Pearson correlation analysis identified significant relationships among the five key quality traits, which are crucial for genetic improvement programs (Figure 2). Two strong positive correlations (r = 0.60) were found that directly benefit selection: the first between fruit weight and soluble solids, suggesting that selecting for larger fruits will simultaneously yield greater sweetness. The second, also strong (r = 0.60), relationship occurred between soluble solids and the SS/TA ratio, confirming that increased sweetness is associated with an ideal flavor balance, thereby improving consumer acceptance.
The analysis also revealed important negative correlations to consider. Fruit weight was negatively correlated with the pulp/seed ratio (r = −0.40), indicating a slight trade-off between size and low seed content. Finally, titratable acidity showed the expected inverse relationship with the SS/TA ratio (r = −0.40). These findings are vital for guiding crossing strategies, prioritizing the combination of mutually beneficial traits.

3.3. Principal Components Analysis (PCA)

The Principal Component Analysis (PCA) grouped the five key fruit quality traits into five components. The first two components, PC1 and PC2, were sufficient to capture the majority of the variance, cumulatively explaining 77.24% of the total variability (Table 4, Figure 3). This high cumulative percentage confirms that these two dimensions effectively summarize the complex relationships among the accessions.
PC1 (46.54% of variability) was primarily driven by the Pulp/Seed ratio (PS), which showed the highest loading coefficient (0.33), and Titratable Acidity (TA) (0.24) (Table 4). Visually, the TA and the Soluble Solids/Titratable Acidity ratio (SSTA) vectors demonstrated the greatest influence for PC1 in the 2D plot (Figure 3), as they project strongly along the horizontal axis. PC2 (30.70% of variability) was predominantly influenced by Titratable Acidity (TA), which registered the highest coefficient (0.45) on this axis (Table 4). The Pulp/Seed ratio (PS) vector also showed a strong orientation along PC2 in the scatter plot, indicating its relevance in separating accessions vertically.
The PCA plot (Figure 3) illustrates the distribution of the 17 accessions across the two main components. Clusters 2, 3, and 4 showed considerable overlap within the confidence ellipse, suggesting that their overall trait profiles are similar, despite the differences highlighted by the cluster mean values. Conversely, Cluster 1 accessions tended to be more separated, with some points lying outside the main ellipse, indicating a higher degree of heterogeneity or dissimilarity from the central mean of the other clusters. The projection of the vectors visually confirms the observed trait correlations, with Fruit Weight (FW) and Soluble Solids (SS) pointing in similar directions (positive correlation), and Pulp/Seed ratio (PS) pointing nearly opposite to the SSTA ratio.

3.4. Hierarchical Clustering Analysis

Four distinct groups were identified among the 17 superior cherimoya accessions, indicating significant variability in quality traits (Figure 4). Cluster 1 was the largest, grouping 11 accessions from 6 different cantons, suggesting a more common quality profile. The internal structure confirmed this cluster; although broad, it still contains subgroups. In contrast, the remaining clusters exhibited more specialized profiles. Cluster 2 consisted of a single accession (EGB03), emphasizing its unique trait combination. Clusters 3 (three accessions) and Cluster 4 (two accessions) are particularly distinct from the core of the population (Cluster 1). These groups joined the main branch at the basal node, highlighting that the superior accessions within them possess unique and highly valuable combinations of quality traits essential for targeted breeding programs aimed at developing superior commercial varieties.
Group 3 showed the highest pulp-to-seed ratio (23.49), mainly represented by the morphotype LMPA01 from Loja. Group 4, which included the codes LMPB04, SUMB04, and PTA01 from Loja, Saraguro, and Paltas, respectively, exhibited the highest titratable acidity (0.45%) and fruit weight (471 g). Group 2, represented by the morphotype EGB03 from Espíndola, displayed intermediate acidity levels. In contrast, Group 1, led by PTA08 from Paltas, presented the lowest values for soluble solids (27.65 °Brix) and fruit weight (274 g) (Table 5).

3.5. Mantel Test

The Mantel test showed no association between geographic and phenotypic distance matrices (r = –0.0665, p = 0.928). This negative correlation was statistically insignificant, suggesting that phenotypic variation does not exhibit a detectable spatial pattern of structuring.

3.6. Multi-Character Selection Index

The multi-character selection index (Table 6) showed that EACAD01 (1.77) and LYHA01 (1.60) have the highest commercial potential, mainly due to their high pulp/seed ratio and soluble solids/titratable acidity ratio. In contrast, the other morphotypes showed minor or negative contributions, indicating that the previously mentioned variables are the most decisive in selecting promising material.

3.7. Fruit Variability

Analysis of the fruit’s physical appearance confirmed high morphological variability within the native cherimoya populations, specifically concerning the exocarp type (Figure 5). Three distinct types were identified across the collected specimens. The impressa type was the most frequent, represented by 11 individuals, characterized by an indented or slightly depressed surface. The smooth lissa type was also common, accounting for 5 individuals. In contrast, the umbonata type, characterized by its small protuberances, was rare, and only one specimen was found. This diversity in fruit morphology, particularly the prevalence of the commercially desirable impressa type, confirms the broad genetic base available in the southern Ecuadorian germplasm for future selection and breeding efforts.

4. Discussion

Understanding the diversity of characteristics in regional plant material is crucial for conservation and crop development. Characterization is generally used to establish genetic improvement programs, specifically to develop new varieties that are more commercially attractive to the average consumer and extend production to suitable areas [39]. For this reason, considering these key quality traits was essential for the detailed characterization performed in this study.
Native cherimoya populations were distributed across different altitudinal and ecological ranges in the province of Loja, enabling the selection of highly diverse morphotypes adapted to contrasting conditions. This aligns with the assertion by Dawson et al. [40], who state that diversity is a key factor in adaptation to environmental change. Furthermore, factors such as soil temperature, humidity, and chemical properties influence the growth and yield of some Annonaceae species [41], which is relevant for identifying environments where promising material can develop. Additionally, some authors, such as Donhouedé et al. [42] quantified the contribution of soil, climate, and genotype to the variation in fruit composition (sugars, lipids, proteins, etc.), concluding that both soil and genotype explain a large part of the variability, with a smaller effect attributable to climate. Results that partially agree with the soil and climate conditions under which the study was conducted.
Among the five fruit quality descriptors evaluated, the pulp-to-seed ratio and fruit weight showed the greatest variability, which coincides with previous findings [43]. The high variability observed in the pulp-to-seed ratio is a positive aspect for genetic improvement. Fos et al. [44] reported that fewer seeds favor higher pulp content, a characteristic highly desirable for breeding programs and consumers. Conversely, a high number of seeds can favor the formation of large fruits, as phytohormones such as auxins and gibberellins present in the seeds can influence fruit size. Another highly variable characteristic is fruit weight. González [3] points out that this parameter is relevant for consumption, with wide ranges that allow selecting potential accessions for cultivation and genetic improvement. The traits that showed minimal variation were: titratable acidity, soluble solids, and the soluble solids/titratable acidity ratio, which can be attributed to the fact that the cherimoya is, by nature, a fruit tree with high sugar content and low acidity.
Hierarchical clustering analysis identified four groups with shared quality profiles, reflecting a certain degree of underlying genetic relatedness, as reported in other studies [45,46,47]. Furthermore, PCA captured 77.24% of the variability with the first components, a result higher than the 40.61% reported by Castañeda [48]. Thus, clustering and PCA reveal functional similarities among accessions, as determined by quality traits proposed by different authors, which are highly variable and important for breeding programs [49,50].
According to the grouping, the values obtained fall within commercially acceptable ranges and are consistent with previous descriptions of native plant material in the province of Loja [51]. At the same time, the resulting high variability supports the hypothesis that the southern region of Ecuador could be the center of origin of the crop, a hypothesis suggested by other studies that highlight the genetic strength of the material and its competitive potential against commercial varieties [9,12,32,39,52,53]. However, it is important to continue research to trace the origin of the plant material, determine the population structure, and support the selection of superior plants for breeding programs [54].
Cluster analysis identified group 4 (LMPB04, SUMB04, and PTA01) from Loja, Saraguro, and Paltas, respectively, as exhibiting the highest titratable acidity and fruit weight. These traits are closely linked to the perception of acidity and the fruit’s sensory quality, particularly taste, where the intensity of acidity directly influences fruit acceptability [50]. Conversely, multi-trait analysis identified morphotypes (EACAD01 and LYHA01) from Loja and Espíndola, respectively, as having commercial potential, weighting the relative contributions of each trait by agronomic importance and prioritizing variables such as pulp-to-seed ratio and SS-to-TA ratio. These characteristics have been identified as important for commercial selection and genetic improvement [50,51].
Although cluster analysis and multi-trait analysis may differ, this variation is due to distinct methodological approaches. Taken together, they show that selecting promising material can be approached through complementary strategies, consistent with the variability reported in Annonaceae [39,49,51] and with the need to apply multiple criteria for their identification.
The correlations observed between the variables indicate that soluble solids are positively associated with fruit weight. This relationship is well-documented and is attributed to the increase in fruit diameter and sugar accumulation during the ripening process, aligning with previous studies [55,56]. Additionally, the positive correlation between the ratio of soluble solids to titratable acidity (SS/TA) and soluble solids can be explained by the enhancement of organoleptic attributes as fruits ripen. This phenomenon has been documented in both climacteric and non-climacteric fruits [57,58].
Finally, the Mantel test revealed no significant association between the geographic and phenotypic distance matrices, showing a low negative correlation value. These findings suggest that factors such as human movement of plant material, local selection processes, microenvironmental conditions, or phenotypic plasticity could have influenced the observed spatial pattern. This weak correlation has been previously reported by Castañeda [48].
Regarding the type of fruit exocarp, this study identified predominantly fruits with an impressed exocarp, a characteristic associated with potential commercial suitability. These findings align with those reported by Pariona and Maldonado [30], who reference earlier research by Schroeder [59]. That research describes smooth fruits with gentle depressions and small protuberances, traits typical of the ‘Cumbe’ prototype. This is the most widely produced and marketed variety internationally, thus supporting its use as a quality benchmark.
The strong presence of the ‘Cumbe’ cultivar in international markets illustrates how a single high-value genotype can set commercial standards while also narrowing the genetic diversity of the crop. This issue is particularly important as genetic diversity is crucial for adapting to environmental changes [40]. Unfortunately, tree species are increasingly susceptible to genetic erosion due to population reductions driven by land-use changes, environmental degradation, and local climate variation, which may favor certain genotypes over others [60]. This situation underscores the strategic importance of identifying locally adapted, high-quality morphotypes that can enhance commercial opportunities while also conserving Andean germplasm [61].

5. Conclusions

Analysis of phenotypic variability of 270 native cherimoya morphotypes from southern Ecuador revealed a wide range of key fruit quality traits. Several materials with characteristics of interest for selection and breeding were identified. Notably, the morphotypes LMPB04, SUMB04, and PTA01, from Loja, Saraguro, and Paltas, respectively, stood out for their superior combination of fruit weight, pulp/seed ratio, and SS/TA balance. On the other hand, the morphotypes EACAD01 and LYHA01, from Espíndola and Loja, respectively, demonstrated high commercial potential due to their significant contributions to the pulp-to-seed ratio and the SS/TA index. These findings highlight the importance of native germplasm from southern Ecuador as a source of functional variation and as a basis for developing varieties adapted to Andean conditions. It is recommended that the outstanding morphotypes be further validated through multivariate trials and genetic analyses to confirm their stability and usefulness in long-term breeding and conservation programs.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/crops6010007/s1, Table S1: Minimums (Min), maximums (Max), mean, standard deviation (SD) and coefficient of variation (CV) for quantitative descriptors of 17 cherimoya morphotypes. Table S2: Qualitative descriptors of 17 cherimoya morphotypes in southern Ecuador

Author Contributions

Conceptualization, M.C.-M., F.G., M.M.-M. and S.C.V.; methodology, M.C.-M., F.G., M.M.-M. and S.C.V.; formal analysis, M.C.-M., F.G., S.E.-H. and M.A.R.; investigation, M.C.-M., F.G., M.M.-M., S.C.V., S.E.-H., A.V., M.O.P.-E., G.R., M.A.R. and D.C.-Z.; writing—original draft preparation: M.C.-M., S.E.-H. and M.A.R.; writing—review and editing: M.C.-M., S.E.-H., S.C.V., M.O.P.-E., G.R., M.A.R. and D.C.-Z. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by grants from the FIASA Program (Fondo de Investigación para la Agrobiodiversidad, Semillas y Agricultura Sustentable, Ecuador), under Grant No. FIASA-CA-2023-011, and by the Research Directorate (Dirección de Investigación) of the Universidad Nacional de Loja, Ecuador, under Project 02-DI-FARNR-2023-E.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors would like to thank the small farmers in the province of Loja for allowing them access to the native cherimoya trees and for sharing their valuable knowledge during field visits. We are grateful to the agronomy students at the National University of Loja (UNL) who participated in collecting the plant material. Special thanks to Beatriz Guerrero-León, from UNL, for her help in analyzing fruit quality. We extend our gratitude to the technical staff of the Ministry of Agriculture and Livestock (MAG) and the Decentralized Autonomous Government of Espíndola, Loja, Ecuador, for their logistical support during the fieldwork.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location map of cherimoya trees in the Loja Province, southern Ecuador. White symbols show the specific locations where native cherimoya accessions were sampled.
Figure 1. Location map of cherimoya trees in the Loja Province, southern Ecuador. White symbols show the specific locations where native cherimoya accessions were sampled.
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Figure 2. Pearson correlation coefficients among five quality traits on cherimoya fruits. Significant coefficients are set in boldface. P/S = Pulp/Seed relation. TA = Titratable acidity. FW = Fruit weight. SS = Soluble solids. SS/TA = Soluble solids/Titratable acidity relation. The area in blue represents a positive correlation, whereas the area in red represents a negative correlation.
Figure 2. Pearson correlation coefficients among five quality traits on cherimoya fruits. Significant coefficients are set in boldface. P/S = Pulp/Seed relation. TA = Titratable acidity. FW = Fruit weight. SS = Soluble solids. SS/TA = Soluble solids/Titratable acidity relation. The area in blue represents a positive correlation, whereas the area in red represents a negative correlation.
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Figure 3. Two-dimensional scatter plot for the first two principal components (PC1 and PC2, 77.24% of the total variability) for the 4 clusters generated. P.S = Pulp/Seed relation. TA = Titratable acidity. FW = Fruit weight. SS = Soluble solids. SS.TA = Soluble solids/Titratable acidity relation.
Figure 3. Two-dimensional scatter plot for the first two principal components (PC1 and PC2, 77.24% of the total variability) for the 4 clusters generated. P.S = Pulp/Seed relation. TA = Titratable acidity. FW = Fruit weight. SS = Soluble solids. SS.TA = Soluble solids/Titratable acidity relation.
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Figure 4. Dendrogram based on fruit quality characteristics: pulp/seed relation, titratable acidity, soluble solids, fruit weight and solids/acidity relation. The numbers in the dendrogram indicate the cluster (group).
Figure 4. Dendrogram based on fruit quality characteristics: pulp/seed relation, titratable acidity, soluble solids, fruit weight and solids/acidity relation. The numbers in the dendrogram indicate the cluster (group).
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Figure 5. Variability in exocarp types of cherimoyas. (a) Lissa; (b) Impressa; (c) Umbonata.
Figure 5. Variability in exocarp types of cherimoyas. (a) Lissa; (b) Impressa; (c) Umbonata.
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Table 1. Physical and chemical soil parameters of native cherimoya populations in Loja province.
Table 1. Physical and chemical soil parameters of native cherimoya populations in Loja province.
VariableRange (Study Area)Method
Bulk density (g/cm3)1.0–1.4Cylinder method [13]
Soil textureLoam to clay loam (predominant)Bouyoucos hydrometer method [14]
pH5.5–6.5Electrometry in soil-water suspension (1:2.5 or 1:1) [15].
Organic matter (%)3.0–4.5Walkley–Black wet oxidation [16]
Cation exchange capacity (meq/100 g)19–23Ammonium acetate pH 7 [17]
Nitrogen (%)0.22–0.33Kjeldahl digestion [18]
Phosphorus (mg/kg)6.4–94.6Olsen method (NaHCO3 0.5 M, pH 8.5) [19]
Potassium (mg/kg)234–491Extraction with ammonium acetate (1N, pH 7) and AAS reading [20]
Magnesium (mg/kg)216–6321N ammonium acetate + AAS spectrophotometry [21]
Calcium (mg/kg)1367–4011Ammonium acetate 1N + AAS [21]
Iron (mg/kg)59–271Extraction with DTPA/EDTA (Lindsay & Norvell) + AAS [22]
Copper (mg/kg)0.5–8.5DTPA-EDTA (Lindsay y Norvell) + AAS [22]
Manganese (mg/kg)14–73DTPA-EDTA + AAS [22]
Table 2. Quantitative descriptors used for the physicochemical and morphological evaluation of cherimoya fruits harvested in the province of Loja, Ecuador.
Table 2. Quantitative descriptors used for the physicochemical and morphological evaluation of cherimoya fruits harvested in the province of Loja, Ecuador.
DescriptorDetermination Method
Pulp/Seed ratio (PS)Division of the weight of pulp over total weight of all fresh seeds per fruit.
Titratable acidity (% of citric acid per 100 g of pulp) (TA)Citric acid content per 100 g of pulp determined by the AOAC method (942.15).
Soluble solids (°Brix) (SS)Average sugar value for 5 representative fruits determined using a HI-96800 digital refractometer (Hanna Instruments, Woonsocket, RI, USA).
Fruit weight (g) (FW)Weight of the mature fruit without its peduncle.
Acidity ratio (SSTA)Relationship between total soluble solids (TSS, expressed in °Brix) and titratable acidity (TA, expressed as % citric acid).
Table 3. Summary statistics of fruit quality traits in samples collected from Loja province, Ecuador.
Table 3. Summary statistics of fruit quality traits in samples collected from Loja province, Ecuador.
VariablesMaxMinMeanSDCV (%)
Pulp/Seed ratio23.4910.2214.644.3229.48
Titratable acidity (meq/100 g)0.480.330.390.0512.82
Soluble solids (°Brix)27.6516.1022.543.3414.83
Fruit weight (g)492.80236.00392.0080.2620.47
Soluble solids/Titratable acidity ratio74.7144.8658.239.0315.51
Note: SD = standard deviation; CV (%) = coefficient of variation (expressed as a percentage).
Table 4. First 2 components from the PCA of 5 quality traits in 17 native cherimoya morphotypes of southern Ecuador.
Table 4. First 2 components from the PCA of 5 quality traits in 17 native cherimoya morphotypes of southern Ecuador.
TraitsPC1PC2
Pulp/Seed relation0.330.21
Titratable acidity (meq/100 g)0.240.45
Soluble solids (°Brix)0.240.05
Fruit weight (g)0.130.00
Soluble solids/Titratable acidity relation0.000.00
Variability (%)46.5430.70
Table 5. Mean values of clusters based on 5 quality traits of cherimoya fruit from southern Ecuador.
Table 5. Mean values of clusters based on 5 quality traits of cherimoya fruit from southern Ecuador.
ClusterPulp/Seed RelationTitratable Acidity (%)Soluble Solids (°Brix)Fruit Weight (g)Soluble Solids/Titratable Acidity Relation
115.700.3517.10274.0047.70
212.500.3924.00432.0060.90
322.700.3623.70312.0065.90
418.900.4520.30471.0044.90
Table 6. Multicharacter selection index and relative contributions for each trait of cherimoya fruits native to the Andean region of southern Ecuador.
Table 6. Multicharacter selection index and relative contributions for each trait of cherimoya fruits native to the Andean region of southern Ecuador.
IDIndexFWP/SSSTASS/TA
EACAD011.77−0.162.35−0.30−0.08−0.05
LYHA011.60−0.03−0.020.19−0.281.73
CECBA 021.56−0.202.09−0.240.02−0.10
LYHB041.08−0.131.30−0.110.16−0.14
GNA071.03−0.191.21−0.160.35−0.20
CaMUA040.89−0.170.720.290.030.02
P/S = Pulp/Seed relation. TA = Titratable acidity. FW = Fruit weight. SS = Soluble solids. SS/TA = Soluble solids/Titratable acidity relation.
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Capa-Morocho, M.; Granja, F.; Molina-Müller, M.; Vásquez, S.C.; Erazo-Hurtado, S.; Vaca, A.; Pineda-Escobar, M.O.; Rogel, G.; Romero, M.A.; Chamba-Zaragocin, D. Native Cherimoya Trees with Commercial Potential from Southern Ecuador. Crops 2026, 6, 7. https://doi.org/10.3390/crops6010007

AMA Style

Capa-Morocho M, Granja F, Molina-Müller M, Vásquez SC, Erazo-Hurtado S, Vaca A, Pineda-Escobar MO, Rogel G, Romero MA, Chamba-Zaragocin D. Native Cherimoya Trees with Commercial Potential from Southern Ecuador. Crops. 2026; 6(1):7. https://doi.org/10.3390/crops6010007

Chicago/Turabian Style

Capa-Morocho, Mirian, Fernando Granja, Marlene Molina-Müller, Santiago C. Vásquez, Santiago Erazo-Hurtado, Alejandro Vaca, Marlon Oswaldo Pineda-Escobar, Guillermo Rogel, Melissa A. Romero, and Diego Chamba-Zaragocin. 2026. "Native Cherimoya Trees with Commercial Potential from Southern Ecuador" Crops 6, no. 1: 7. https://doi.org/10.3390/crops6010007

APA Style

Capa-Morocho, M., Granja, F., Molina-Müller, M., Vásquez, S. C., Erazo-Hurtado, S., Vaca, A., Pineda-Escobar, M. O., Rogel, G., Romero, M. A., & Chamba-Zaragocin, D. (2026). Native Cherimoya Trees with Commercial Potential from Southern Ecuador. Crops, 6(1), 7. https://doi.org/10.3390/crops6010007

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