# Characterization and discrimination of Colombian *Capsicum* accessions using elliptic fourier analysis

R. A. Viáfara-Vega · M. Granada-Agudelo · H. Cárdenas-Henao

Received: 14 November 2024 / Accepted: 13 May 2025
© The Author(s) 2025

**Abstract** Chillies are one of the most cultivated plants in the world. The species of the genus *Capsicum* have a wide range of uses in agriculture, as vegetables and spices, in medicine and as ornamental plants. In Colombia, chilli represents an important exported crop, but the morphological characterization of this genetic resource is still poor. In this way, the Elliptic Fourier Analysis (EFA) is a value tool to evaluate the morphological variation of any group as allow the application of geometric morphometric to structures that do not have homologous points or are difficult to assign as chili fruits. For this purpose, fruits from the departments of Cauca, Nariño and Valle del Cauca were collected in marketplaces,

gardens and natural reserves. The accessions were identified based on morphological and molecular characteristics. Photos of each fruit were taken, digitized and used to obtain the coordinates of the fruit outline to perform an EFA. With the coefficients obtained from the EFA, a principal components analysis (PCA) and a clustering analysis were performed. Finally, a discriminant analysis was performed to differentiate the fruit outline of two *Capsicum* species. A total of 743 pepper fruits were collected, representing 160 accessions and 5 species (*C. annuum*, *C. frustescens*, *C. chinense*, *C. pubescens* and *C. baccatum*). Cluster analysis revealed five representative fruit shapes: long and curved, conical, asymmetrical conical, round and triangular. The wild accessions had round fruits, while the domesticated accessions had triangular, conical, asymmetrical conical and curved fruits. The discriminatory analysis made it possible to distinguish between *C. annuum* var. *glabriusculum* and *C. frustescens* wild, species that are difficult to identify on the basis of other morphological characters.

**Keywords** *Capsicum* genetic resources · Clustering analysis · Geometric morphometric · Morphological characterization

**Abbreviations**

EFA Elliptic Fourier analysis

Caa *Capsicum annuum* var. annuum

Cag *C. annuum* var. *glabriusculum*

**Supplementary Information** The online version contains supplementary material available at https://doi.org/10.1007/s10722-025-02482-0.

R. A. Viáfara-Vega (✉) · H. Cárdenas-Henao
Grupo de Estudios Ecogenéticos y de Biología Molecular. Facultad de Ciencias Naturales y Exactas, Universidad del Valle, Cali, Colombia
e-mail: ronald.viáfara@correounivalle.edu.co

M. Granada-Agudelo
Laboratoire des Interactions
Plantes-Microbes-Environnement (LIPME), Université de Toulouse, INRAE, CNRS, Castanet-Tolosan, France

M. Granada-Agudelo · H. Cárdenas-Henao
Centro de Investigación e Innovación en Bioinformática y Fotónica (CIBioFI), Facultad de Ciencias Naturales y Exactas, Universidad del Valle, Cali, Colombia
Cfr *C. frutescens*

Cch *C. chinense*

Cba *C. baccatum*

Cpu *C. pubescens*

## Introduction

Chilli peppers belong to the genus *Capsicum* (fam-
ily Solanaceae), which is one of the most cultivated
groups in the world. This is due to its multiple uses in
agriculture as a vegetable and spice, in medicine, and
for ornamental purposes (García-Gaytán et al. 2017;
Anaya-Esparza et al. 2021). The genus comprises 43
different species and is native to the tropical and sub-
tropical regions of the Americas (Barboza et al. 2020,
2022).

Several *Capsicum* species have been selected by
humans for different fruit sizes, shapes, and colors.
This has resulted in five domesticated species: *C. annuum* L. var. *annuum* (*Caa*), *C. chinense* Jacq. (*Cch*), *C. frutescens* L. (*Cfr*), *C. baccatum* L. (*Cba*), and *C. pubescens* (Wang & Bosland 2006; García-Gaytán et al. 2017; Barboza et al. 2022). The first three species are often confused and difficult to distinguish morphologically and molecularly (Barboza et al. 2022). By contrast, *Cba* and *Cpu* are easily identified by their floral colors (Russo 2012; García-Gaytán et al. 2017; Barboza et al. 2022).

Chillies have a rich morphological variation: their
flowers, leaves and fruits have very different shapes at
the inter- and intraspecific level (Zhigila et al. 2014;
Barboza et al. 2022). In particular, fruit shape is
important because it is one of the factors considered
in the selection of plants from different *Capsicum* cul-
tivars. Moreover, it has a potential taxonomic value
to distinguish species. This variation in fruit shape
can be studied by means of different biometric tools,
such as morphometric methods. Morphometrics is the
study of the covariation of biological shape and the
causes of this covariation (Zelditch et al. 2012; Mit-
teroecker and Schaefe 2022). Typically, a Geomet-
ric Morphometric (GM) analysis is performed using
homologous points (landmarks) that allow the outline
of a given object to be drawn. A Procrustes analy-
sis (PA) is then used to analyze the distribution of a
set of shapes. Other types of shape analysis, such as
Elliptical Fourier Analysis (EFA), are used when the
shapes are very complex or when homologous points

(landmarks) are difficult to define (Toro-Ibacache
et al. 2010; Caple et al. 2017).

EFA uses mathematical Fourier functions to trans-
form “xy” coordinates into a matrix of harmonics
that represent the outline of a structure. This can be
used to reveal similarities or differences in shape out-
lines (Rufino et al. 2007; Dapar and Tabugo 2018). In
plants, including the genus *Capsicum*, both conven-
tional morphometry and GM analysis have been used
to compare the shape of fruits from different species
and sometimes to establish shape patterns (Goto et al.
2005; Visa et al. 2014; Tripodi and Greco 2018; Nan-
kar et al. 2020; Mangino et al. 2021).

Chili cultivation in Colombia is not as important
as in other countries, but represents an important
exported crop, valued at more than $10 million per
year (FAOSTAT 2023). However, characterization
research in germplasm collections around the world
usually evaluate few or no Colombian accessions
(maximum one or two) (Lee et al. 2016; Taranto et al.
2016; Tripodi and Greco 2018; Colonna et al. 2019).
Even at the national level, the number of investiga-
tions is low, considering the number of varieties
distributed in the country (Hernández et al. 2004;
Pardey-Rodríguez and García 2011; Villota-Cerón
et al. 2012).

For this reason, the objective of this study was the
characterization of the morphological diversity of the
fruits of Colombian *Capsicum* accessions by EFA.
In addition, EFA was also used to evaluate the dif-
ferences in fruit shape between two wild *Capsicum*
varieties (*C. frutescens* and *C. annuum* var. *glabrius-
culum*) with a high degree of similarity in other mor-
phological characters, such as color and size of the
fruit and number of flowers.

## Materials and methods

Fruit samples and species identification

Data were collected from different rural and urban
areas in the Valle del Cauca, Cauca and Nariño
departments. The objective was to collect fruits of
pepper varieties offered in marketplaces, market gal-
leries, nurseries, and others, including home gardens
and patches cultivated by the inhabitants of the area.
From each accession, 5 fruits were preserved for mor-
phometric analysis, and the remaining fruits were
used to obtain seeds from which plants were obtained
for morphological and molecular identification.

## Outline digitization

For the images of the fruits, the camera height was the same for all fruits. Once the photographs were taken, the fruit outlines were digitized using ImageJ software (Abramoff et al. 2004). For some fruits, it was necessary to fill the outline with a solid color before digitizing in ImageJ due to the presence of shadows that interfered with the digitization; this previous step was done in an image editor. It was ensured that all the contours had the same starting point of digitization, the right side of the calix of the fruit was chosen as the starting point because in Solanaceae fruits the calix is always present. In the same way, all contours had the same digitizing direction (clockwise), this was verified using the Momocs package in the R software (Bonhomme et al. 2014). Finally, the digitized contours were exported in XY coordinate format. The nomenclature of IPGRI et al. (1995) and Nankar et al. 2020 was used to describe the different shapes of chili pepper clusters.

## Elliptic fourier and multivariate analyses

The contour coordinates were examined with an EFA using the Momocs package in the R software (Bonhomme et al. 2014). This analysis uses Fourier series analysis to transform the xy coordinate data into a matrix of n x h dimensions (harmonic matrix), where n is the number of fruits and h is four times the number of harmonics (there are four coefficients for each harmonic). The number of harmonics depends on the structure studied and must be determined by the investigator using a cumulative variance curve (Claude 2008). The minimum number of harmonics explaining 99% of the variance of the data was determined using the data matrix of harmonic coefficients and a cumulative variance curve. This calculated number of harmonics was then used for multivariate principal component analysis (PCA) and discriminant analysis. The harmonic data matrix was used to perform a PCA using the FactoClass R package (Pardo and del Campo 2007), with three objectives: first, to reduce the dimensionality of the data matrix, second, to obtain the components that contribute most to the fruit shape, and third, to plot the distribution of the

variability of the fruit contours on two axes. In addition, a hierarchical clustering analysis was performed using Ward's distances to observe the classification of the samples in a dendrogram.

## Discriminant analysis: *C. annuum* var. *glabriusculum* vs. *C. frutescens* (wild accession)

To test whether variables associated with fruit outline could be useful in discriminating between two wild accessions, *Cag* and wild *Cfr* species, a discriminant analysis (K-means) was performed using the harmonics data matrix. Forty-seven fruits of *Cag* and fifty fruits of wild *Cfr* were used for this analysis. The ratio of within-group variance to total variance was observed to assess the accuracy of discrimination, as well as the proportion of correctly assigned fruits in each group.

All multivariate analyses were performed with the R packages FactoMine (Lê et al. 2008) and FactoClass (Pardo and del Campo 2007).

## Results

### Number of accessions and their distribution by species and department

A total of 743 chili fruits were collected, representing 160 accessions and 5 species (Table 1 and Fig. 1). Some accessions are represented by less than five fruits because they are not available in the markets. Valle del Cauca was the department with the highest number of accessions (75), while Nariño had the lowest number (27). More than 60% of the accessions belonged to the species *Caa*, while *Cch* was the least represented species (only 3 accessions). The number of fruits per accession and the collection sites can be observed in Supplementary Data 1.

### EFA and PCA

From the cumulative variance curve of the harmonics estimated by EFA, it was found that 10 harmonics were sufficient to explain 99% of the variation in the data, so the subsequent multivariate analyses were performed with a matrix of 40 coefficients per fruit (4 coefficients per harmonic). For the principal component analysis, most of the variance (> 90%) was
<table><caption>**Table 1** Number of *Capsicum* accessions and fruits collected and their distribution by department and species. *Caa*: *C. annuum* var. *annuum*, *Cag*: *C. annuum* var. *glabriusculum*, *Cfr*: *C. frutescens*, *Cch*: *C. chinense*, *Cba*: *C. baccatum* and *Cpu*: *C. pubescens*</caption><thead><tr><th>Departament</th><th>Number of accessions</th><th>Number of fruits</th><th>Caa</th><th>Cag</th><th>Cfr</th><th>Cch</th><th>Cba</th><th>Cpu</th></tr></thead><tbody><tr><td>Valle del Cauca</td><td>75</td><td>347</td><td>46</td><td>7</td><td>20</td><td>2</td><td>0</td><td>0</td></tr><tr><td>Nariño</td><td>27</td><td>108</td><td>10</td><td>2</td><td>1</td><td>0</td><td>6</td><td>8</td></tr><tr><td>Cauca</td><td>58</td><td>288</td><td>44</td><td>3</td><td>1</td><td>1</td><td>1</td><td>8</td></tr><tr><td>Total</td><td>160</td><td>743</td><td>100</td><td>12</td><td>22</td><td>3</td><td>7</td><td>16</td></tr></tbody></table>

<figure><img src="image_1.png" /><figcaption>**Fig. 1** Flowers and fruits of *Capsicum* species found in this study. A: *C. annuum* var. *annuum*. B: *C. annuum* var. *glabriusculum*. C: *C. frutescens*. D: *C. baccatum*. E: *C. frutescens*. F: *C. chinense* fruit</figcaption></figure>

found in the first two components of the PCA. The plot of these two components highlights the great variability in the fruit shape of the collected accessions (Fig. 2), ranging from completely round fruits to elongated and curved fruits, although a large part of the samples have a conical pepper shape (straight and not so long).

Figure 3 shows the contribution of each component to fruit shape. The first component, with 84% of the variation, contributes to the sphericity of the fruit contour, which means that high values result in elliptical and round fruits, while low values result in thin and long fruits. The second component contributes to the variable “curvature”, low values are observed in

fruits with convex shape (strong curvature) and high values are observed in fruits with straighter contours. The remaining components contribute very little to the final contour of the fruit, but it is noteworthy that low values in component three give a triangular effect to the shape of the chili pepper fruit.

Hierarchical clustering analysis (ward distances)

The cluster analysis identified 5 types of contours within the 160 *Capsicum* accessions (Fig. 4). The average contour of each group and some fruits of some accessions are shown in Fig. 5. The five contour types are long and curved, conical, asymmetric conical, round and triangular. No relationship was found between the different contour types and the regions evaluated. However, there was a relationship with the different species, MANOVA analysis p-value <0,001. For example, all fruits of the wild variety *Cag* were included in the group of round peppers. Similarly, the fruits of *Cfr* were divided into two types, the wild accessions had round fruits, while the other fruits always belonged to the conical group. For *Cch*, all fruits were round and for *Cba*, the fruits were long and curved. Finally, *Caa* turned out to be a species with a wide variety of fruit shapes, since its accessions were found in all the groups created by the clustering analysis.

Discriminant analysis: *C. annuum* var. *glabriusculum* vs. *C. frutescens* (wild accession)

In this analysis, 11 harmonics were found to be sufficient to explain 99% of the variation in the sample (Supplementary Data 2). For PCA, the first two components accounted for 86% of the total variation, the first for 81% and the second for 5% (Supplementary Data 3). Figure 6 shows how the EFA coefficients
<figure><img src="image_2.png" /><figcaption>**Fig. 2** Principal component analysis (PCA) plot for 743 *Capsicum* fruits from southwestern Colombia. *Caa*: *C. annuum* var. *annuum*, *Cag*: *C. annuum* var. *glabriusculum*, *Cfr*: *C. frutescens*, *Cch*: *C. chinense*, *Cba*: *C. baccatum* and *Cpu*: *C. pubescens*</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>**Fig. 3** Contribution to *Capsicum* fruit contour of three first components</figcaption></figure>

estimated from the contours allow the discrimination
of the fruits of these two morphologically similar spe-
cies. The proportion of between-group variance to total
variance was 77%, indicating that much of the total
variation observed in this analysis is due to the com-
parison of the two species, supporting the separation of
the groups observed in Fig. 6. In addition, the percent-
age of correct assignments was quite high, with 88%
of fruits within each species correctly assigned to their

respective species (Supplementary Data 4). *Cag* tends
to have more elliptical fruits, while wild *Cfr* has fruits
with a more circular outline.
<figure><img src="image_4.png" /><figcaption>**Fig. 4** Cluster analysis using Ward's distances for 743 *Capsicum* fruits from southwestern Colombia with their mean contour. From left to right: conical, triangular, asymmetrical conical, long and curved, round</figcaption></figure>

<figure><img src="image_5.png" /><figcaption>**Fig. 5** Mean contour of the groups obtained by cluster analysis (top). Example of fruits of some accessions belonging to each group (bottom). A: round, B: triangular, C: conical, D: asymmetrical conical and E: long and curved</figcaption></figure>

## Discussion

Number of accessions and their distribution by species and department

Most of the collected accessions belonged to the *Caa* species (100 accessions); this species is the most economically important and has the widest global distribution; the vast majority of commercial chili cultivars belong to this species (Barboza et al. 2022). Therefore, it is not surprising that it was the most collected

species in this study. Furthermore, *Cba* and *Cpu* species were only collected in the departments of Cauca and Nariño, with no representation in Valle del Cauca. *Cpu* accessions are usually distributed in the highlands (> 1200 masl) and are found between 14–20 °C (Yamamoto et al. 2013; Barboza et al. 2022). Most of the *chile* cultivation in Valle del Cauca is located above the inter-Andean valley, since the arable land of the Andean Mountain ranges is mainly dedicated to the production of coffee and other crops (potatoes and timber trees); this inter-Andean valley has an average

<figure><img src="image_6.png" /></figure>
<figure><img src="image_7.png" /><figcaption>**Fig. 6** Discriminant k-means analysis for two pepper species, *C. annuum* var. *glabriusculum* vs. *C. frutescens* (wild accession)</figcaption></figure>

altitude of 1000 masl and an annual temperature of 25 °C (Alvarado-Solano and Otero 2015). Under these environmental conditions, it is more common to cultivate species of the *annuum* group (*C. annuum*, *C. frutescens* and *C. chinense*) than *Cba* and *Cpu* species. On the other hand, in Cauca and Nariño, the areas where chili peppers are grown have higher altitudes and lower temperatures than in Valle del Cauca, which makes them more suitable for the cultivation of the latter two species.

### EFA, PCA and hierarchical cluster analysis (ward's distances)

Most species were included in more than one cluster, especially *Caa* accessions, with fruits recorded in all clusters. This is consistent with what has been recorded in other research (Tripodi and Greco 2018; González-López et al. 2021; Khokhar et al. 2022; Li et al. 2022). *Caa* is of great economic importance as it is the most cultivated species of *Capsicum*. It has led to the development of many cultivars and has been extensively studied and used in plant breeding programs. Even before it became globalized, Native American cultures domesticated and selected this species, giving it the great diversity of fruit shapes

that exist today (Pickersgill 1969; Perry et al. 2007; Quin et al. 2014; Barboza et al. 2022).

As opposed to other species, *Cch* was only included in one cluster. Nimmakayala et al. (2021) recorded up to three different fruit shapes for this species, although they worked with accessions distributed in the Amazon region, where this species is native. While the accessions collected in this study were from the Andean region, which can explain the lower fruit shape found.

*Cfr* was recorded in two clusters (round and conical) as mentioned in the results. The round fruits were assigned to the wild *Cfr* accessions, while the conical fruits were assigned to a commercial accession called “Tabasco”. Dutta et al. 2018, in their study of *Cfr* accessions from India by means of morphological characters, found five distinct clusters for this species. However, although a smaller number of clusters was obtained in the present study, Dutta et al. 2018 did not record any accessions with round fruits. This can be explained by the fact that *Cfr* with round fruits is an accession that is naturally distributed in the Americas, and since it is not commercially available, it is difficult to find in other continents.

The PCA identified three main factors that influence the contour of chili fruits in longitudinal view: sphericity, asymmetry (curvature) and the triangular
component. Sphericity, the most important of the three, refers to the circular or elliptical shape of chili fruits, and all the wild chili accessions evaluated (*Cag* and wild *Cfr*) were included in the same cluster. This is consistent with what has been reported for the wild species of the genus, which mostly have round or semi-round fruits (Barboza et al. 2022), as opposed to the domesticated species, which mostly have fruits with a non-circular shape (conical or triangular). However, *Cpu* accessions (a domesticated species) also had round fruits and were included in the round fruit group, although their fruits are quite large compared to those of the wild species (more than 10 cm in diameter).

The second factor was asymmetry, which had a great influence in conical and long fruits. Round fruits, such as pumpkin, did not show as strong asymmetry as the former. The species more propense to have asymmetrical fruits were *Caa* and *Cfr*, Li et al. 2022 also find this pattern with all the curved and long fruits belong to the *Caa* species. Even some fruits of the same accession could show asymmetry and others could not show asymmetry. This is related to both genetic and nongenetic factors and can exist at individual level (Mann 1943; Nakagawa et al. 1968; Currie et al. 2000; Berger et al. 2017). For example, Khokhar et al. 2022 have shown that the asymmetric character of the fruit is highly heritable (0.89) and has a low influence of the environment.

The contours evaluated in this study were obtained from photographs with a longitudinal view of the fruit. From this view, it was possible to characterize a large part of the variation (91.3%) of the contours present in the evaluated material. Other research, such as Beyer et al. (2002) and Nankar et al. (2020), evaluated other views of the fruit (transverse view) by means of other morphometric analyses, identifying coefficients that allow the study of another type of variation in fruit shape that cannot be obtained from the longitudinal view. In this study, the “pumpkin” shaped pepper fruits have been included in the group of elliptical peppers, since from the longitudinal view these types have an elliptical shape. However, from the transversal view, it is possible to distinguish them in a different group because their circumference is not round but shows waves. Therefore, a combination of longitudinal and transversal views can be used to characterize Capsicum accessions for subsequent research.

An important aspect of EFA is the digitizing direction, which is the direction which the coordinates of a contour follow (clockwise or counterclockwise). During the first analysis performed on our database, we noticed a mirror effect in the PCA performed on the Fourier coefficients. Under this effect, fruits with the same shape appeared on both sides of the horizontal axis (component 1), forming a point cloud with bilateral symmetry (Supplementary Data 5). We noticed that the only difference in the data matrix was the direction of digitization; although both had the same point of origin (fruit calyx), their direction was opposite to each other. By ensuring that all fruits had the same direction, the PCA plot showed the results presented in this paper. Therefore, it is important to check the digitizing direction of all samples when performing EFA to avoid spurious results.

Finally, five representative fruit shapes (triangular, conical, asymmetric conical, long and curved, and round) emerged from the hierarchical clustering analysis for all the accessions evaluated. Many of these clusters are very much in agreement with the clusters found in other research. For example, Nankar et al. 2020 suggest that, despite their great morphological diversity, Capsicum fruits can be grouped into five typical shapes: elongated, conical, round, pumpkin and bell. The first three groups were found in this study, while the bell-shaped or “blocky” pepper was deliberately excluded here, as it represents a fruit shape associated with very commercial varieties (paprika) widely distributed worldwide. Similarly, Khokhar et al. 2022 found three common fruit shapes in *Caa* and *Cfr* accessions, elongate, conical and round. Therefore, the variation of fruit shape in the Colombian accessions of *Capsicum* it is similar to those found in other countries. This highlights the genetic diversity distributive in southwest Colombia that can be used in breeding programs.

Discriminant analysis: *C. annuum* var. *glabriusculum* vs. *C. frutescens* (wild accession)

*Cag* and *wild Cfr* are two species with quite similar morphology (Supplementary Data 6), both have small fruits (less than 3 cm in diameter), the flowers have white corollas and are also small (less than 3 cm in diameter), the stamens can be purple to dark green or blue, and they can have quite pubescent leaves. One of the characteristics used to distinguish them is the

<figure><img src="image_8.png" /></figure>
presence of only one flower per node in most *Cag* accessions, while *wild Cfr* has two per node, but this characteristic is not always easy to observe because one of the two flowers of *wild Cfr* is smaller than the other and sometimes tends to wither or fall off (especially the flowers of the first sympodial units).

In this analysis, there was an 88% correct assignment rate for wild *Cfr* fruits, with only 6 fruits incorrectly assigned to their species. All of these fruits belonged to the same accession and were identified as *Cfr* based on their morphological characteristics, but identification with the DNA barcoding markers of Jeong et al. (2020), *Waxy* gene (data not shown), indicated that this accession belonged to the *Caa* species. Therefore, it is doubtful whether this accession is a hybrid between the two evaluated species.

On the other hand, for *Caa* fruits, the correct assignment was 94%, with only 3 fruits being incorrectly assigned. Contrary to the previous case, these three fruits were from different accessions and presented a certain asymmetry, which caused the elliptical shape of *Caa* to be deformed towards a shape more similar to the fruits of *Cfr*, and therefore assigned to the latter species.

## Usefulness of EFA in the characterization of *Capsicum* fruit outlines

Investigations verify that EFA is as effective as the traditional morphometric analysis (TM) and the landmark morphometric analysis (LMA) for the evaluation of structure variation (Özkan et al. 2018; Neto et al. 2019). However, TM does not study the variability of the shape as a geometric property free of size effects (Viscosi and Fortini 2011) and when the structure is too complex, might not adequately document shape (van Bocxlaer and Schultheiß 2010). Instead, EFA is a powerful tool for the analysis of complex structures without size effects (Premoli 1996; Nawrocki et al. 2018, Caiza et al. 2021). IPGRI et al. (1995) reported that some *Capsicum* accessions could have complex fruit shapes, especially at pedicel attachment and fruit end, together with the presence of appendage at blossom end and cross-sectional corrugation. These characteristics may be difficult to analyze with TM, but since the outline is the synthesis of many measures (height, length, width, inclination, convexity, etc.), EFA can adequately depict these

complex shapes (Brusoni and Basso 2007; Nawrocki et al. 2018).

Finally, Fourier elliptic analysis is a low-cost tool, since it only requires photos of the target structure. Even a smartphone with a decent quality camera can be used to take photos of the structure. In the same way, computational and statistical analysis in R software does not consume much time or computer resources. An analysis with a sample of 743 fruits and 10 harmonics, as made in this study, does not take more than 1 h and could be performed in a personal computer. Momocs R library provides a tutorial script and many examples on the web. This makes it easy to understand how to use the program.

## Conclusions

This study is the first in the country to characterize the fruit shapes of *Capsicum* with the use of morphometric tools (EFA). A great diversity in fruit shape was found, categorizing chili accessions into five fruit shapes: Wild accessions had round fruits, while domesticated accessions had triangular, conical, asymmetrical and curved fruits. These variations in fruit shaped is similar to the recorded in other countries and represent a great genetic resource in Colombia that can be used in future plans of breeding. Finally, *C. annuum* var. *glabriusculum* and *C. frutescens* wild are very similar in the characteristics of the flowers and leaves and are difficult to identify taxonomically. However, EFA could adequately discriminate between these two Capsicum species on the basis of fruit shape, while *C. annuum* var. *glabriusculum* has elliptical fruits, *C. frutescens* wild has round fruits.

**Acknowledgements** We are very grateful to Jhon Jairo Calderón for his support in collecting samples in the department of Nariño. To Leidy Laura Arias, Jorge Mario Ruiz, Mary Belcy Bonilla, Héctor Cifuentes, Mauricio Peñuela and José Cándelo for their guidance and support in collecting samples in the departments of Cauca and Valle del Cauca.

**Author contributions** Ronald A. Viáfara-Vega conceptualized and designed the experiment, analyzed the data, prepared the figures and/or tables, wrote the original manuscript, revised and approved the final document. Margarita Granada-Agudelo designed the experiment, analyzed the data, wrote the original manuscript, revised and approved the final document. Heiber Cárdenas conceptualized and designed the experiment, revised
and approved the final document, managed and supervised the project.

**Funding** Open Access funding provided by Colombia Consortium. This project was funded by the internal call 2020 for the creation of a bank of eligible projects for research and artistic creation in the sciences, arts, humanities, technologies and innovation of the Universidad del Valle, Colombia (CI 71266 and CI 71310). The author was supported for the publication of the article by the Universidad del Valle through the transformative agreements (501100007329).

**Data availability** No datasets were generated or analysed during the current study.

**Declarations**

**Conflict of interest** The authors declare no competing interests.

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