Characterization of the genetic diversity of breeding Cowpea Lines (Vigna unguiculata L.)

Caracterização da diversidade genética de linhagens de feijão-caupi (Vigna unguiculata L.) em melhoramento

Abstract

Cowpea (Vigna unguiculata L.) is a legume widely produced and consumed globally, with grains possessing significant nutritional value and diverse applications. Despite its production potential and broad variability and adaptability to adverse conditions, it remains a crop with limited research in the areas of genetics and plant breeding. Therefore, the objective of this study was to evaluate the genetic variability of 10 cowpea lines originating from the University of Córdoba using eight ISSR markers. The results indicated that polymorphism ranged from 20% (AC) to 58.3% (ACA). Cluster analysis grouped the lines into two clusters based on their genetic similarity rather than their origin. This was corroborated by genetic parameters such as expected heterozygosity (He​ = 0.16), the diversity index (I = 0.24), and the coefficient of genetic differentiation (Gst​ = 0.16), which demonstrate low genetic variability but with gene flow among the lines (Nm​ = 2.70) and greater variation within (91%) than between them. The results demonstrate the efficiency of SSR markers in determining genetic diversity within germplasm exhibiting a narrow genetic base. In contrast, Caupicor 50 exhibites greater genetic divergence and may represent a useful parental source for broadening the genetic variability of future breeding change for populations. Despite the reduced variation attributed to breeding processes and recurrent self-pollination, desirable agronomic traits are fixed. These traits can be selected in breeding programs aimed at developing promising genotypes that are adapted, resistant to biotic and abiotic factors, and possess good productivity and nutritional quality, thereby offering a food security alternative for many Andean regions.

Keywords:
genetic diversity; genetic resources; molecular markers; legume; plant breeding

Resumo

O feijão-caupi (Vigna unguiculata L.) é uma leguminosa amplamente produzida e consumida globalmente, cujos grãos possuem significativo valor nutricional e diversas aplicações. Apesar de seu potencial produtivo e ampla variabilidade e adaptabilidade a condições adversas, permanece uma cultura com pesquisa limitada nas áreas de genética e melhoramento de plantas. Portanto, o objetivo deste estudo foi avaliar a variabilidade genética de 10 linhagens de feijão-caupi originárias da Universidade de Córdoba utilizando oito marcadores ISSR. Os resultados indicaram que o polimorfismo variou de 20% (AC) a 58.3% (ACA). A análise de agrupamento classificou as linhagens em dois grupos com base em sua similaridade genética, e não em sua origem. Isso foi corroborado por parâmetros genéticos como heterozigosidade esperada (He = 0.16), o índice de diversidade (I = 0.24) e o coeficiente de diferenciação genética (Gst = 0.16), que demonstram baixa variabilidade genética, mas com fluxo gênico entre as linhagens (Nm = 2.70) e maior variação intralinhagem (91%) do que interlinhagem. Os resultados demonstram a eficiência dos marcadores SSR na determinação da diversidade genética dentro de germoplasma que exibe uma genética estreita. Em contraste, a cultivar Caupicor 50 exibe maior divergência genética e pode representar uma fonte parental útil para ampliar a variabilidade genética de futuras populações de melhoramento. Apesar da variação reduzida atribuída aos processos de melhoramento e à autopolinização recorrente, características agronômicas desejáveis ​​estão fixadas. Essas características podem ser selecionadas em programas de melhoramento genético com o objetivo de desenvolver genótipos promissores que sejam adaptados, resistentes a fatores bióticos e abióticos, e possuam boa produtividade e qualidade nutricional, oferecendo assim uma alternativa de segurança alimentar para muitas regiões andinas.

Palavras-chave:
diversidade genética; recursos genéticos; marcadores moleculares; leguminosas; melhoramento de plantas

1. Introduction

Cowpea (Vigna unguiculata (L.) Walp.), known in the Colombian Caribbean region as black-eyed pea, is a drought-tolerant tropical grain legume cultivated primarily in tropical and subtropical regions. Globally, cowpea is grown on more than 15 million hectares, with an annual production exceeding 9 million metric tons. Approximately 97% of global production is concentrated in sub-Saharan Africa, where Nigeria, Niger, and Burkina Faso are the leading producers (FAOSTAT, 2025), underscoring the crop's strategic role in food security, nutrition, and the livelihoods of millions of smallholder farmers. The cowpea cultivated areas in the Caribbean region of Colombia increased from 14,361 ha in 2007 to 17,199 ha in 2020 and, only for the Department of Cordoba, areas changed from 710 ha to 1,572 ha in 2022, with increasing yields, from 0.9 to 1.4 t ha^-1(Colombia, 2024). The increase is based on the availability of varieties with greater potential for grain yield and nutritional quality. However, there are still technological limitations related to biotic and abiotic factors. Among them, weeds are a major problem in crops, because they can cause yield losses of up to 90%, in addition to increasing harvesting costs and decreasing grain quality (Vergara-Córdoba et al., 2024). In the Colombian context, its production is mainly concentrated in the departments of La Guajira, Magdalena, Cesar, Atlántico, Bolívar, Sucre, and Córdoba (Agronet, 2024). These regions are characterized by arid and dry environmental conditions, where the crop represents a fundamental source of income for small and medium-sized agricultural producers (Pastrana et al., 2019).

Cowpea is distinguished by its wide range of applications, including direct human consumption, animal nutrition, use as green manure, forage, vegetable production, and industrial innovations (Murga-Orrillo et al., 2024). Its grains have an outstanding nutritional profile, composed of 33% protein, 63% carbohydrates, and 4.6% lipids, in addition to a significant contribution of minerals, vitamins, and fiber (Sardar et al., 2024). This composition makes it an economical source of protein and energy, demonstrating key potential for mitigating malnutrition and improving nutritional health in vulnerable populations (Idris et al., 2025). Compared to other legumes, V. unguiculata thrives in a wide variety of soil types, pH ranges, and temperatures, showing remarkable adaptation to drought conditions, which positions it as a promising crop in the face of climate change (Senthamil et al., 2025). This has sparked interest from researchers and government agencies to promote its cultivation internationally. However, despite its socioeconomic relevance, in much of the world its cultivation is restricted to small plots where local and traditional genotypes are grown by farmers with empirical knowledge, who often lack access to advanced technologies and optimized genetic material (Pastrana et al., 2019; Martínez-Reina et al., 2020).

Internationally, the genetic resources of the genus Vigna comprise approximately 96,161 accessions conserved in around 21 genebanks (van Zonneveld et al., 2020). The most representative collections are held at IITA (19,020 accessions), WorldVeg in Taiwan (15,735 accessions), NBPGR in India (14,505 accessions), and the USDA-ARS in the United States (13,078 accessions). Among the species of the genus, Vigna unguiculata subsp. unguiculata comprises the largest proportion of conserved accessions (33,015), followed by Vigna radiata (29,399). Despite this representation in genebanks, studies evaluating and characterizing cowpea germplasm in detail remain limited compared to other crops. Information regarding genetic diversity is fundamental to plant breeding and agricultural research. Therefore, the effective conservation of variability and genetic improvement indispensably require well-characterized agricultural genetic resources (Sodo et al., 2023).

Modern biotechnology and molecular genetics tools efficiently complement conventional approaches to germplasm selection and evaluation (Morillo et al., 2026). Currently, various DNA-based markers have been employed in cowpea to analyze genetic diversity, genetic linkage, and the mapping of quantitative trait loci (QTLs) (Nkhoma et al., 2020). Notable molecular techniques include chloroplast DNA polymorphisms (Udensi et al., 2022), RAPD (Random Amplified Polymorphic DNA) markers (Nair et al., 2024), RFLP (Restriction Fragment Length Polymorphism), TRAP (Target Region Amplification Polymorphism), SNP (Single Nucleotide Polymorphisms) (Vir et al., 2023), DAF (DNA Amplification Fingerprinting) (Spiaggia et al., 2009), DArT (Diversity Arrays Technology) (Osundare et al., 2023), SSR (Simple Sequence Repeats) (Deshahalli-Divakara et al., 2024), and ISSR (Inter-Simple Sequence Repeats) (Asadova et al., 2024). The latter are frequently used in diversity and population structure studies because they are based on the polymerase chain reaction (PCR), offer high levels of polymorphism, low cost, high reproducibility, heritability, and traceability, and do not require prior knowledge of the genome. Furthermore, they exhibit broad genomic distribution and allow for the discrimination of accessions at both intra- and interspecific levels (Rayanoothala et al., 2023).

In Colombia, cowpea cultivation is crucial for food security in the Caribbean region, where local varieties are grown that are characterized by low yields, poor nutritional value, and high susceptibility to phytosanitary problems (Araméndiz-Tatis et al., 2019, 2023). Consequently, the phenotypic and molecular evaluation and characterization of available germplasm are essential to identify promising materials adapted to the area. Therefore, the objective of this study was to evaluate the genetic diversity present in 10 improved cowpea lines using ISSR molecular markers, in order to identify patterns of variability and genetic similarity that can guide future selection and crossing strategies within genetic improvement programs.

2. Material and Methods

2.1. Plant material

A total of 10 cowpea (Vigna unguiculata (L.) Walp.) breeding lines were evaluated (Table 1). These lines were developed by the breeding program of the Universidad de Córdoba (Colombia) from a breeding population originally introduced from Missouri (USA), hereafter referred to as the “Missouri population.” The evaluated materials correspond to advanced breeding lines obtained through recurrent phenotypic selection within the introduced population rather than from controlled biparental crosses; therefore, they do not possess a defined pedigree derived from a formal hybridization program. The lines had been previously selected for agronomic performance under tropical environmental conditions. According to previous agronomic and nutritional evaluations, most Missouri-derived lines exhibit a predominantly determinate (bush-type) growth habit, cream to light-yellow seed color, and improved nutritional quality, including high iron and zinc contents.

Table 1
Cowpea (Vigna unguiculata L.) Walp. lines obtained in the breeding program of the University of Cordoba, by individual selection from a heterogeneous homozygous population of the Missouri cultivar (USA).

Genotype/Line	Code AET*	Main characteristics
Genotype 1	LM-50	Determinate growth
Genotype 2	LM-33	Determinate growth
Genotype 3	LM-17	Determinate growth
Genotype 4	Caupicor 50	Indeterminate growth
Genotype 5	LM-27	Determinate growth
Genotype 6	LM-55	Determinate growth
Genotype 7	LM-19	Determinate growth
Genotype 8	LM-41	Determinate growth
Genotype 9	LM-40	Determinate growth
Genotype 10	LM-45	Determinate growth

• ^*
  AET: Agronomic Evaluation Tests.

In addition, the commercial cultivar Caupicor 50, developed from local germplasm of the Córdoba region, was included as a reference genotype. Unlike the Missouri-derived lines, Caupicor 50 exhibits an indeterminate or climbing growth habit and represents a local commercial genotype that showed greater genetic divergence than the Missouri-derived lines in the molecular analyses.

2.2. DNA extraction

Molecular characterization was conducted at the Plant Molecular and Cellular Biology Laboratory of the Universidad Pedagógica y Tecnológica de Colombia (UPTC), Sede Tunja. Genomic DNA, was extracted from 200 mg of young leaf tissue from each of the lines using the Dellaporta et al. (1983) protocol, modified by Muñoz et al. (2008). DNA integrity was assessed by electrophoresis on 0.8% agarose gels run in 0.5%X TBE buffer (0.045M Tris-borate; 0.001M EDTA) at 80 volts, 400mA for 45 minutes and stained with GelRed (Biotum, USA), utilizing a Maxicell Primo EC-340 horizontal electrophoresis unit. DNA quality was verified by A260/A280 absorbance ratios, and quantification was performed using a spectrophotometer (EPOCH/2). Subsequently, the DNA was diluted to a concentration of 10 ng/µl in a total volume of 100 µl and stored at -20°C

2.3. ISSR amplification

Eight ISSR primers synthesized by Bioneer Corporation (Alameda, CA, USA) were used for genetic diversity analysis (Table 2). These markers were chosen based on previous studies demonstrating their reproducibility and polymorphism in Vigna species (Saxena and Rukam, 2020). PCR amplification were performed in a final reaction volume of 25 µl containing 20 ng genomic DNA, 2 µM primer, 0.2 mM dNTPs, 1.5 mM MgCl₂, 1× reaction buffer, and 1 U Taq DNA polymerase.

Table 2
ISSR markers used for genetic diversity analysis of 10 cowpea breeding lines.

Primer	Sequence (5´- 3´)	Annealing (°C)
AG	HBH(AG)7	50
CA	DBDA(CA)7	50
ACA	BDB(ACA)5	50
CCA	DDB(CCA)5	55
CGA	DHB(CGA)5	58
CT	DYD(CT)7C	55
GT	VHV(GT)5G	58
TG	HVH(TG)7T	55

• The following designations are used for generative sites: H (A or T or C); B (G or T or C); V (G or A or C) and D (G or A or T).

Amplification were carried out in a PTC-100 Programmable Thermal Controller (MJ Research, Inc., USA) using the following cycling program: an initial denaturation at 95°C for 5 min. followed by 37 cycles of denaturation at 95°C for 30 s, primer annealing at the corresponding temperature for each primer (50°C for 50°C for AG, CA and ACA; 55°C for CT, TG and CCA for GT; and 61°C for CGA), extension at 72°C for 2 min; and a final extension at 72°C for 7 min. A negative control lacking template DNA was included in each PCR assay to verify the absence of contamination.

Amplification products were separated by electrophoresis on 2% agarose gels prepared in 0.5X TBX, run at 40 V for approximately 45 minutes in a Maxicell Primo EC 340 electrophoresis gel system chamber, stained with GelRed^TM, and then visualized under ultraviolet light for scoring.

2.4. Statistical analysis

ISSR bands were scored as present (1) or absent (0) to generate a binary data matrix. Genetic similarity among lines was estimated using the Nei and Li similarity coefficient (Nei and Li, 1979), implemented in the SIMQUAL module of NTSYS-pc version 2.1 (Rohlf, 2000). Based on the similarity matrix, a dendrogram was constructed using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA). The optimal cut-off points for defining genetic groups were determined according to the method proposed by Jamshidi and Jamshidi, (2011).

Genetic diversity parameters, including the number of polymorphic loci, percentage of polymorphic loci, and expected heterozygosity (He), were estimated using TFPGA software (Miller, 1997). Genetic differentiation among lines was assessed using the coefficient of genetic differentiation (Gst) (Nei, 1987), whereas gene flow (Nm) was estimated according to the method proposed by (McDemott and McDonald, 1993).

Genetic similarity between pairs of genotypes was calculated according to Nei and Li (1979) (Equation 1):

$G{s}_{ij}=\frac{2N_{ij}}{Ni+N{j}_{}}$ (1)

where $G{s}_{ij}$ is the genetic similarity between genotypes i and j, N_ij is the number of shared bands, and N_i and N_j represent the total number of bands observed in genotypes i and j, respectively.

The goodness of fit between the similarity matrix and the dendrogram was evaluated using the cophenetic correlation coefficient (CCC) calculated with the COPH and MXCOMP modules of NTSYS-pc.

Population structure was inferred using the Bayesian clustering algorithm implemented in STRUCTURE version 2.3.4 (Hubisz et al., 2009; Earl and von Holdt, 2012). The optimal number of genetic clusters (K) was determined using the ΔK method proposed by Evanno et al. (2005). Values of K = 1–10 were evaluated using an admixture model with a burn-in period of 100,000 iterations followed by 1,000,000 Markov Chain Monte Carlo (MCMC) iterations.

Finally, an Analysis of Molecular Variance (AMOVA) was performed using GenAlEx version 6.5 (Peakall and Smouse, 2012) with 1,000 permutations to estimate the partitioning of molecular variation within and among genetic groups.

3. Results

3.1. ISSR marker polymorphism and amplification profile

The evaluation of eight ISSR primers across the 10 cowpea (Vigna unguiculata L.) lines generated a total of 174 reproducible bands, of which 76 were polymorphic, corresponding to an overall average polymorphism of 43.68%. The number of loci produced per marker varied, with the highest proportion of polymorphic loci observed for primers ACA (58.33%, 14 polymorphic bands) and CA (57.89%, 11 polymorphic bands). In contrast, primer AG yielded the lowest level of polymorphism (20.00%, 4 polymorphic bands). The remaining primers—CCA, CGA, CT, GT, and TG—exhibited polymorphic percentages ranging between 25.00% and 50.00% (Table 3). Conserved loci across all evaluated genotypes accounted for 56.32% (98 bands) of the total amplified fragments.

Table 3
Genetic parameters evaluated in 10 advanced lines of Vigna unguiculata L. for the Colombian Caribbean.

Total Population								POP 1		POP II
Primer	N°bands	N°loci polimorfic	%loci polimorfic	He	I	Gst	Nm	He	I	He	I
AG	20	4	20	0.05	0.08	0.15	2.72	0.05	0.08	0.03	0.05
CA	19	11	57.89	0.24	0.34	0.23	1.70	0.16	0.23	0.21	0.31
ACA	24	14	58.33	0.21	0.32	0.22	1.80	0.18	0.25	0.16	0.24
CCA	20	7	35	0.14	0.20	0.04	12.69	0.13	0.19	0.13	0.20
CGA	26	13	50	0.19	0.29	0.09	4.64	0.20	0.28	0.15	0.22
CT	20	5	25	0.094	0.14	0.03	15.46	0.07	0.11	0.11	0.16
GT	22	10	43.48	0.15	0.23	0.14	3.18	0.14	0.20	0.18	0.27
TG	23	10	43.488	0.15	0.23	0.14	3.18	0.13	0.19	0.14	0.21
Total Promedio	174	76	43.68	0.16	0.24	0.16	2.70	0.14	0.20	0.14	0.21

• He: Expected heterozygosity; I: Shannon Index; Gst: Coefficient of genetic differentiation; PIC: Polymorphic Information Content; Nm: Gene flow.

3.2. Genetic diversity parameters

At the population level, the mean expected heterozygosity ($H_e$) across all eight ISSR markers for the 10 lines was $0.16\pm 0.02$. Marker-specific $H_e$ values ranged from 0.05 for AG to 0.24 for CA (Table 3). Shannon’s Information Index ($I$) averaged $0.24\pm 0.03$ for the total population, with individual values per locus spanning from 0.08 (AG) to 0.34 (CA).

When evaluating the population partitioned into the two primary clusters identified by genetic structure analysis, Population I (POP I) presented a mean $H_e$ of 0.14 and a mean $I$ of 0.20. Similarly, Population II (POP II) exhibited a mean $H_e$ of 0.14 and a mean $I$ of 0.21 (Table 3).

3.3. Cluster analysis (UPGMA)

Hierarchical cluster analysis based on the Nei–Li similarity coefficient and the UPGMA algorithm resolved the 10 cowpea lines into three distinct clusters at a genetic similarity threshold of approximately 15.6% (0.156 similarity coefficient) (Figure 1):

Figure 1
Dendrogram of breeding lines of cowpea based on the Nei-Li similarity coefficient and estimated with seven ISSR markers with UPGMA, SAHN and TREE classification methods of NTSYS-pc, version 1.8 (Exeter Software, NY, USA).

• Group I: Composed of three lines derived from the Missouri population: LM-50 (GENT-1), LM-33 (GENT-2), and LM-17 (GENT-3).

• Group II: Formed by five Missouri-derived lines: LM-27 (GENT-5), LM-55 (GENT-6), LM-19 (GENT-7), LM-41 (GENT-8), and LM-45 (GENT-10).

• Group III: Encompassed two genotypes: the commercial variety control Caupicor 50 (GENT-4) and line LM-40 (GENT-9).

The cophenetic correlation coefficient ($r$) calculated between the Nei-Li similarity matrix and the cophenetic matrix was greater than 0.70 ($r>0.70$), confirming goodness-of-fit and statistical reliability of the UPGMA dendrogram topology relative to the pairwise genetic distances.

3.4. Population genetic structure analysis

Bayesian population structure analysis executed in STRUCTURE, evaluated via the Evanno $\Delta K$ method, identified $K=2$ as the peak delta value, defining two optimal genetic clusters ($K=2$) among the 10 evaluated lines (Figure 2).

Figure 2
Delta K values ​​obtained from Harvester Structure, calculated as the mean of the probability of K divided by the standard deviation of the probability of K. Evannoé method with optimal model K= 2.

Under the assignment model for $K=2$ (Figure 3):

Figure 3
Population genetic structure of 10 breeding cowpea lines analyzed, calculate using the Structure software. Each vertical bar represents an individual sample, and the color of the bar indicates the probability that an individual will be assigned to one of the identified groups.

• Cluster 1 (Red assignment): Included seven of the Missouri-derived lines: LM-50 (1), LM-33 (2), LM-17 (3), LM-27 (5), LM-55 (6), LM-19 (7), and LM-41 (8), which showed standard membership coefficients ($q_k\ge 0.95$) to this cluster.

• Cluster 2 (Green assignment): Composed of Caupicor 50 (4), LM-40 (9), and LM-45 (10), displaying predominant membership to the second genetic ancestral group.

3.5. Genetic differentiation and Analysis of Molecular Variance (AMOVA)

Nei’s coefficient of genetic differentiation ($G_{st}$) across all loci was 0.16, indicating that 16% of the total genetic variation is partitioned between genetic groups, while 84% resides within them (Table 3). Locus-specific $G_{st}$ values ranged from 0.03 (CT) to 0.23 (CA). Estimated historical gene flow ($N_m$) averaged 2.70 individuals per generation across all loci, with values per marker varying from 1.70 (CA) to 15.46 (CT) (Table 3).

The Analysis of Molecular Variance (AMOVA) confirmed the population partitioning (Table 4). Of the overall variance components (${\sigma }^2=16.67$), 9% (${\sigma }^2=1.52$, $p=0.001$) was attributed to variation between lines/groups, whereas 91% (${\sigma }^2=15.14$, $p=0.010$) accounted for internal genetic variance within the evaluated lines (Table 4).

Table 4
Analysis of molecular variance (AMOVA) in 10 breeding lines of Vigna unguiculata L. for the Colombian Caribbean.

Source	df	Sum of squares	Mean squares	Variance components	Total variation %	p-value
Between the lines	1	22.43	22.43	1.52	9	0.001
Within the lines	8	121.17	15.14	15.14	91	0.01**
Total	9	143.60		16.67	100

• ^*
  Significance test after 1000 permutations. df: Degree of freedom.

4. Discussion

The eight ISSR markers evaluated in this study produced a total of 174 reproducible bands across the 10 cowpea lines, a marker profile sufficient to estimate basic genetic parameters and comparable to marker totals reported in preliminary characterization studies in Vigna species (Asadova et al., 2024; Diallo et al., 2024). Given the small number of genotypes evaluated (10 lines), ISSR markers serve as a useful tool for preliminary genetic characterization rather than a definitive measure of overall genomic efficiency.

The average polymorphism observed across the evaluated germplasm was 43.68%, ranging from 20.00% (AG) to 58.33% (ACA) (Table 3). This level of polymorphism reflects moderate marker variation within the evaluated set. Differences in polymorphism levels reported across literature—such as higher values observed in broader germplasm collections or mutant populations (Asadova et al., 2024; Diallo et al., 2024; Mwangi et al., 2021)—are primarily attributable to differences in sample size, marker types (ISSR vs. SSR or SNP), and the broader genetic background of the evaluated germplasm, rather than direct differences in marker performance.

The low levels of genetic diversity observed across the total population (mean $H_e=0.16\pm 0.02$; $I=0.24\pm 0.03$) directly relate to the reproductive biology and selection history of the material. Vigna unguiculata is a predominantly autogamous species, and the evaluated lines originate from a shared pedigree background derived from the Missouri population and subjected to advanced line selection. This recurring self-pollination and shared breeding lineage naturally limit genetic diversity, a pattern consistent with expected dynamics in advanced breeding lines (Boukar et al., 2020; Sarr et al., 2021). These results should be interpreted as an inference tied specifically to the shared breeding origin of the Missouri-derived lines rather than generalized assumptions regarding geographic origin. Contextual references in other Vigna germplasm, such as Mediterranean landraces or wild accessions (Diouf et al., 2021; Gbedevi et al., 2021), illustrate higher diversity driven by distinct evolutionary histories, wild introgression, and broader geographic sampling.

Regarding population structure, hierarchical UPGMA clustering based on Nei–Li genetic similarity resolved the 10 lines into three distinct clusters at a similarity coefficient of 0.156 (Figure 1). In contrast, Bayesian population structure analysis via STRUCTURE identified $K=2$ as the optimal number of genetic subpopulations (Figure 2, Figure 3). This structural nuance highlights the difference between distance-based hierarchical clustering (UPGMA), which sub-divides Missouri-derived lines into two subgroups alongside a separate cluster comprising 'Caupicor 50' and line LM-40, and model-based Bayesian clustering (STRUCTURE), which assigns individuals to two primary ancestral gene pools. References to phenotypic similarity were excluded from this interpretation, as evaluations were restricted to molecular marker profiles.

The coefficient of genetic differentiation ($G_{st}=0.16$) and estimated historical gene flow ($N_m=2.70$) indicate moderate differentiation and shared ancestry among the lines. This structural pattern is further clarified by the Analysis of Molecular Variance (AMOVA), which indicated that 91% of the total molecular variance resided within the STRUCTURE-defined groups, while 9% accounted for variance between groups ($p=0.001$) (Table 4). This 91% within-group variation reflects molecular variance among individuals within the assigned clusters rather than internal variability within individual homozygous lines. Direct comparisons with studies evaluating landraces across broad agroecological scales or using different marker systems (e.g., Ghalmi et al., 2010) are inappropriate due to fundamental differences in geographic scale, sampling strategy, and marker resolution.

From a breeding perspective, the genetic uniformity and shared background detected among the Missouri-derived lines confirm their high level of genetic purity and stability. Maintaining high genetic purity is essential for varietal registration, seed certification, and maintaining line identity during seed multiplication. If the goal of future breeding efforts is to increase genetic variance, strategic crosses using more divergent lines—such as 'Caupicor 50' or external germplasm sources—may be considered to introduce novel genetic combinations.

Acknowledgements

The authors are grateful to the Vice-Rectorate for Research of Universidad del Magdalena for the financial support provided for this study. The authors also acknowledge Universidad Pedagógica y Tecnológica de Colombia (UPTC) and Universidad de Córdoba for their technical and scientific support during the development of the research.

Data Availability Statement

The datasets generated and analyzed during the current study are available from the corresponding author upon reasonable request.

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*

e-mail: [e-mail]

Editor:

José Galizia Tundisi

Publication Dates

• Publication in this collection
  19 Oct 2026
• Date of issue
  2026

History

• Received
  27 May 2026
• Accepted
  16 Sept 2026