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Article

Selection Strategy for Breeding Pepper Lines with Ornamental Potential

by
Fátima de Souza Gomes
1,
Samy Pimenta
1,*,
Gabriela Cristina Alves Custódio
1,
Wellington Silva Gomes
2,
Joyce Costa Ribeiro
1,
Nelson de Abreu Delvaux Júnior
1,
Marlon Cristian Toledo Pereira
1,
Monique Moreira Moulin
3,
Willer Fagundes de Oliveira
1,
Ana Karolyne Pereira Barbosa
1,
Hélida Christhine de Freitas Monteiro
1,
Ana Carolina Petri Gonçalves
4 and
Marcos Vinicius Bohrer Monteiro Siqueira
4
1
Department of Agricultural Sciences, State University of Montes Claros, St. Reinaldo Viana, 2630, Morada do Sol, Janaúba 39448-581, Brazil
2
Department of Agricultural and Natural Sciences, State University of Minas Gerais, St. Vereador Geraldo Moisés da Silva, Ituiutaba 38302-192, Brazil
3
Department of Biological Sciences, Federal Institute of Education, Science and Technology of Espírito Santo, Km 47 Rive, Alegre 29500-000, Brazil
4
Department of Agricultural and Biological Sciences, Minas Gerais State University, Frutal 38202-436, Brazil
*
Author to whom correspondence should be addressed.
Horticulturae 2025, 11(7), 789; https://doi.org/10.3390/horticulturae11070789
Submission received: 26 May 2025 / Revised: 13 June 2025 / Accepted: 20 June 2025 / Published: 3 July 2025
(This article belongs to the Section Genetics, Genomics, Breeding, and Biotechnology (G2B2))
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Versions Notes

Abstract

Considering that effective selection strategies are essential for the development of new ornamental pepper cultivars, the objective of this work was to select superior partially endogamic lines (PEL) of pepper in a F2:3 generation, using the combination of the genealogical method with mixed linear models. The experiment consisted of four cycles: parents and generations F1, F2 and F2:3. Qualitative (QLD) and quantitative (QTD) descriptors were evaluated. QLD were analyzed through descriptive statistics, and QTD were analyzed through estimates of genetic parameters and prediction of genetic values by REML/BLUP. Multivariate analysis was performed to group and select individuals based on QLD and QTD simultaneously. The descriptors number of flowers per axil, flower position, mature fruit color, fruit position, fruit brightness, and capsaicin in the placenta presented no variation within the F2:3 population. The selection accuracy varied from high to very high, denoting a high experimental precision. Higher additive genetic action was detected for descriptors, considering the individual heritability in the strict sense and the additive heritability within the progeny. Forty-eight PELs were selected quantitatively and, considering QLD and QTD descriptors simultaneously, the number of individuals was reduced from 48 to 30 PELs. The combined strategies used enabled to establish the best strategy for an efficient selection of superior PEL of ornamental pepper.

1. Introduction

Most breeding programs for peppers (Capsicum spp.) around the world are focused on the development of cultivars intended for consumption of their fruits, as fresh or industrialized peppers [1,2,3]. However, a new market niche has been consolidated: the use and exploration of the diversity of pepper species with ornamental potential [4,5]. This has been further driven by recent advances in genomics and molecular breeding strategies that support trait-specific selection in Capsicum spp. [6,7]. Several species have morphological characteristics that are explored with this purpose, such as variegated foliage, dwarf size, variety of colors of flowers and fruits, and fruits presenting different maturation stages on the same plant and at the same time [8,9].
Focused on meeting the increasing market demands for peppers, the State University of Montes Claros has a breeding program since 2017 for the development of new cultivars of Capsicum spp. for ornamental purposes. Thus, an active germplasm bank composed of 70 accessions was implemented and, after completing the evaluation and characterization phases, nine accessions with potential for ornamental exploration were pre-selected for the development of new cultivars [10].
Capsicum annuum L. is an autogamous species, its improvement can be prolonged with traditional methods applied to autogamous plants, including the genealogic method (pedigree) [4,11]. In this method, plants of F2 generation are selected based on predefined phenotypes. Seeds from these selected plants are harvested and sown separately in rows, forming the F2:3 progenies or families, which compose F3 progenies from F2 plants. The selection is carried out among and within F2:3 progenies. This process is repeated until successive generations result in progenies with the desired homozygosity level (F6 or F7). The records and licenses required are then obtained through several evaluation tests and the cultivar is introduced to the market [12,13].
The combination between the pedigree method and the mixed linear model to select individuals among and within families is more efficient and accurate, as the degree of kinship of the evaluated individual is considered [14]. However, researches involving grouping based on mixed data of individuals from the F2:3 generation using quantitative data adjusted based on additive genetic values for more accurate selection for Capsicum species. Similarly, the use of this quantitative statistical approach with qualitative variables in the selection process is unknown or not standardized [15,16].
This study proposes to simultaneously consider quantitative and qualitative variables for selection in early generations in the breeding program of C. annuum L. Therefore, the methodology adopted could be incorporated and subsidize selection processes in methods for improvement of other autogamous species. In this context, the objective of this work was to select superior partially endogamic lines (PEL) of pepper (C. annuum L.) in a F2:3 generation, proposing the combination between qualitative and quantitative data as a new selection strategy for breeding programs of peppers with ornamental purposes.

2. Materials and Methods

2.1. Experiment Location and Climate

The experiments were conducted in a greenhouse covered with a 50% shade screen at the experimental area of the State University of Montes Claros (UNIMONTES), in Janaúba, MG, Brazil (15°48′09′′ S, 43°18′32′′ W, and altitude of 533 m). The climate of the region is Aw, tropical savanna with a rainy summer and a dry winter, according to the Köppen classification [17]. The study consisted of four cycles, conducted in three consecutive years, with duration of six months for each cycle, in 2019 (I cycle), 2020 (II and III cycles), and 2021 (IV cycle) (Figure 1).
Seeds of the segregating population were obtained through biparental crossing between the accession UNI01 (P2, C. annuum var. glabriusculum), which was the masculine parent (donor of pollen grains), and the accession UNI05 (P1, C. annuum var. annuum), which was the female parent plant (pollen recipient) (1st cycle) (Figure 1). Both accessions belong to the active germplasm bank of the breeding program of pepper (Capsicum spp.) of the UNIMONTES.
The masculine parent (UNI01) presented flowers with white corolla without presence of spots, blue anthers, leaves with medium green intensity and medium width, and white-greenish fruits before maturation expressing red color during maturation, and pungent fruits [10]. The feminine parent (UNI05) presented flowers with violet corolla without presence of spots, violet anthers, narrow leaves with dark green intensity, dark purple fruits before maturation expressing red color during maturation, and pungent fruits [8].
The subsequent F2 generation was obtained by the growth and self-fertilization of F1 individuals (2nd cycle), with the growth of 20 F1 plants (Figure 1). After harvesting the fruits of F1 plants, F2 seeds were collected and sown in pots and grown in a greenhouse. A total of 200 F2 plants were grown until the fruit production. Thirty potential progenies were selected from this F2 population to compose the F2:3 generation (3rd cycle), considering individuals that presented the lowest phenotypic values for plant height and late flowering and fruiting cycles.
The 30 progenies selected formed the families of F2:3 generation (4th cycle). Each family was composed of eight individuals, totaling 240 PEL, which were grown in assays without experimental design, evaluated individually, without a defined experimental design.
In all cycles, seeds were sown in 128-cell plastic trays filled with a commercial substrate, using one seed per cell, which were daily irrigated. When the seedlings reached the transplanting stage (four to six definitive leaves), they were transplanted into 1-L pots filled with a mixture of clayey soil, coarse sand, and bovine manure at the proportion 1:1:1. Cultural practices were carried out according to recommendations for conventional crops [18] during the conduction of the experiments, with adaptations for protected and pot crops.

2.2. Descriptors Evaluated

2.2.1. Qualitative Descriptors

PEL were evaluated considering ten qualitative descriptors: number of flowers per axil (NFA), flower position (FLP), corolla color (CC), anther color (AC), fruit color before maturation (FCBF), mature fruit color (MFC), fruit surface texture (FST), fruit position (FRP), fruit brightness (FB), and capsaicin in the placenta (CP). The detection of capsaicin in the placenta of fruits was performed using a method consolidated in the literature [19].
These descriptors were evaluated by direct visual comparison under greenhouse conditions. The descriptors NFA, FLP, CC, AC, MFC, and FST were assessed visually, grading each genotype involved in the test according to the classes presented by the Bioversity International [20]. The descriptors FCBF, FRP, FB, and CP were evaluated according to the classes presented by the Brazilian National Service of Protection of Cultivars (SNPC) of the Brazilian Ministry of Agriculture, Livestock, and Food Supply (MAPA) [21].

2.2.2. Quantitative Descriptors

Five quantitative descriptors of ornamental importance for species of the genus Capsicum were considered, namely: flowering (FC) and fruit maturation (MC) cycles, and mean fruit length (MFL), diameter (MFD), and weight (MFW). The cycles were evaluated considering the number of days from sowing to the opening of the first flower (FC) and total ripening of the first fruit (MC). MFL and MFD were determined using five fruits per plant and a caliper (mm). MFW was determined by the ratio between fresh fruit weight and number of fruits per plant (g), measured in a digital balance with two decimals.

2.3. Genetic-Statistical Analyses

2.3.1. Qualitative Descriptors

The new selection strategy proposed was carried out as follows: the data obtained for qualitative descriptors were analyzed using descriptive statistics, through the final percentage (%) of each category per variable. These analyses and the graph plotting was carried out using the tidyverse and ggplot2 packages of the statistical program R [22], version 4.1.3.

2.3.2. Quantitative Descriptors

Genetic parameters of quantitative descriptors were estimated by the Restricted Maximum Likelihood (REML), and the prediction of genetic values through the approach Best Linear Unbiased Prediction (BLUP) [23], with the aid of a genetic-statistical program (SELEGEN-REML/BLUP). The mixed linear model adopted was:
y = Xr + Za + e
where: y is the vector of phenotypic values; r is the vector of replication effects, assumed as fixed, added to the overall mean; a is the vector of individual additive genetic effects, assumed as random; e is the vector of errors or residues, random; and X and Z are the matrices of incidence for the referred effects.
Analysis of Deviance (ANADEV) [24] was carried out to test the effect of the model and infer the significance of the genotypic effects. The results obtained through REML/BLUP were used to carried out the rank sum selection index [25], modified by establishing weights, equivalent to the respective coefficient of individual additive genetic variation (CVgi) of each descriptor. Selection was directed towards lower genetic values for the descriptors FC, MFL, MFD, and MFW, and in the positive sense (higher genetic values) for the maturation cycle.
After the rank sum, a selection intensity of 20% was applied among and within families, resulting in the genotypic selection of 48 PEL with the highest values for the rank sum to compose the next generation (F3:4). After the genotypic selection of 48 PEL based on quantitative descriptors, multivariate analysis was carried out to group and select individuals. Then, a second selection pressure was applied based on qualitative and quantitative descriptors, simultaneously, selecting 30 PEL.
The genetic dissimilarity was measured [26] and a dendrogram was developed using the unweighted pair-group method with arithmetic mean (UPGMA). The fit between the distance matrix and the clustering matrix was estimated by the cophenetic correlation coefficient, using the Mantel test (p < 0.001) and the optimal number of groups formed in the dendrogram was defined [27], adopting a k = 1.25 as a cut point to define the number of groups, with the aid of the Multivariate Analysis package of the statistical program R, version 4.1.3 [22], which was also used for plotting the dendrogram.

3. Results

3.1. Qualitative Descriptors

The descriptors number of flowers per axil, flower position, mature fruit color, fruit position, fruit brightness, and capsaicin in the placenta presented no variation within the F2:3 population of the families evaluated. These descriptors showed that the genotypes had one flower per axil, intermediate flower position, red mature fruits, strong fruit brightness, erect fruit position, and presence of capsaicin. Genetic variability among and within families was found for the descriptors: corolla color, anther color, fruit color before maturation, and fruit surface texture of the superior partially endogamic lines (PEL) evaluated (Figure 2).
A total of 50% of the PEL produced flowers with violet corolla, whereas 29.17% presented white corolla and 20.83% presented white corollas with violet margins (Figure 2). Regarding the anther color, 35.42% of the PEL evaluated presented pale blue anthers, 27.08% presented violet anthers, 29.17% presented blue anthers, and 8.33% presented yellow anthers (Figure 2).
Variability in fruit color before maturation was also found, with 64.58% violet fruits and 35.42% white-greenish fruits (Figure 2). There was a higher occurrence of fruits with a smooth surface texture (79.16%), followed by fruits with semi-wrinkled texture (16.67%) and a lower percentage of fruits with wrinkled texture (4.17%) (Figure 2).

3.2. Quantitative Descriptors

3.2.1. Analysis of Deviance, Estimates of Components of Variance, Genetic Parameters, and Prediction of Genetic Values

The mathematical model adopted to evaluate quantitative descriptors showed to be adequate by the analysis of deviance (ANADEV) through the likelihood ratio test (LRT). The random effects (genotypes) were statistically significant for all descriptors analyzed (Table 1). Consequently, the respective components of variance are significantly different from zero.
The estimates of genetic parameters and components of variances showed a genetic variability that can be explored for all quantitative descriptors evaluated (Table 1). The flowering cycle presented higher value of genotypic variance (85.85) than environmental variance (31.64).
Regarding the estimates of coefficient of individual additive genetic variation (CVgi), the maturation cycle had the lowest percentage (3.93%) and the mean fruit length had the highest percentage (15.42%). The quantification of genetic variability can still be carried out by the coefficient of residual variation (CVe%), which varied from 2.15% to 11.68% (Table 1).
Accuracy, or correlation between predicted and true genotypic values, is another important statistical parameter for genotypic evaluation. The progeny selection accuracy varied from 0.74 (high) for MFW to 0.91 (very high) for MFD (Table 1) and presented values of 0.85, 0.87, and 0.79 for FC, MC, and MFL, respectively.
The estimate of individual heritability in the strict sense (h2a), showed values varying from high (0.55 for MFW) to very high (0.84 for MFD). The additive heritability within the progeny (h2ad) showed similar estimates to those of h2a, with a high variation: from 0.62 (MFD) to 0.87 (MFL).

3.2.2. Simultaneous Selection of Superior Partially Endogamic Lines (PEL)

Considering the descriptors of higher importance (FC and MC), the mean individual phenotypic value found for the selected population was lower than that of the F2:3 population (Table 1) for the descriptor FC. The selected PEL presented mean cycle of 81 days for flowering and 120 days for fruit maturation (Figure 3a). The negative estimates regarding predicted additive genetic effects found for descriptors FC and MC of the PEL selected by the index were 81.25% and 79.17%, respectively (Figure 3b).
The selected PEL presented positive predicted additive genetic values, varying from 67 to 99 days for FC and from 107 to 129 days for MC (Figure 3c). In addition, the predicted additive genetic values were lower than the overall mean of the population. The mean genotypic selection gain showed positive predictions in all 48 superior PEL selected for the descriptors FC and MC (Figure 3b). The gains showed amplitudes from 0.44 to 16.18 for FC and from 0.01 to 11.04 for MC. The amplitude for the new predicted mean of the improved population for FC and MC among the superior PEL varied considerably: from 88 to 104 days for FC and from 126 to 132 days for MC (Figure 3c).
Regarding the descriptors of fruits (MFL, MFD, and MFW), the mean individual phenotypic values found for the selected population were similar to those of the plant cycle descriptors, with lower means in relation to those of the F2:3 population (Table 1). The selected genotypes presented means of 25.16 mm for MFL, 10.73 mm for MFD, and 1.5 g for MFW (Figure 3a).
MFL, MFD, and MFW of the selected superior PEL were 63.89%, 58.34%, and 55.56%, respectively, presenting negative predictions for the additive genetic effects (Figure 3b). Regarding the predicted additive genetic values (Figure 3c), all PEL selected for the descriptors MFL, MFD, and MFW had positive predictions, presenting predicted additive genetic values from 16.55 to 28.64 mm for MFL; 6.39 mm to 15.88 mm for MFD; and 0.87 g to 1.78 g for MFW.
The mean genotypic selection gains were positive (Figure 3b), with amplitude of 0.20 to 9.36 mm for MFL; 0.12 to 6.26 mm for MFD; and 0.01 g to 0.32 g for MFW. The new predicted means (Figure 3c) of the superior PEL were from 25.06 to 34.22 mm for MFL; 10.42 to 16.70 mm for MFD; and 1.52 g to 1.83 g for MFW.

3.3. Multivariate Analysis

Dissimilarity Measures (GOWER), Clustering by the Unweighted Pair-Group Method with Arithmetic Mean (UPGMA) and Cophenetic Correlation Coefficient (CCC)

CCC presented a estimate of 0.82 and was significant by the Mantel test (p < 0.01). The cut point by the Mojena Method enabled the formation of seven genetically different groups (Figure 4).
The dendrogram (Figure 4) showed the grouping of 48 PEL selected quantitatively and, highlighted in red, the 18 PEL that were not selected after the second selection of PEL considering qualitative and quantitative descriptors simultaneously, thus decreasing the number of individuals from 48 to 30 PEL.
Group I was formed by only one PEL (F156 P7); Group II was formed by three PEL; and Group III presents characteristics expressed by the parent UNI01 (masculine parent) and was formed by seven PEL.
Group IV presents characteristic phenotypes of the feminine parent (UNI05) and was formed by twelve PEL, of which three PEL stood out (F33 P7, F125 P8, and F33 P1) and were between the eight PEL that presented the lowest predicted additive genetic values in the ranking of the F2:3 population for FC. Group V present five PEL. Groups VI and VII consisted exclusively of one PEL each: F49 P2 and F163 P2, respectively.

4. Discussion

4.1. Insights from the Qualitative Descriptors

Although genetic variability is one of the most important elements for breeding programs, its absence for some characteristics can be positive, such as in the specific case of capsaicinoids, which are molecules responsible for the pepper fruit pungency. Some characteristics, such as pungency, are undesirable in the ornamental plant market, since it can reduce the preference of consumers and growers for the genotype. In genetic terms, the results obtained indicate that the genic locus responsible for the expression of the character (absence of capsaicin) is fixed. Two studies reported that this characteristic is controlled by only one dominant gene [28,29].
In the case of number of flowers per axil, the absence of variability found in the present study can be connected to the species C. annuum [30]. This species has very short internodes, and ornamental varieties present low size, thus, it may lead to an error of evaluation in the selection process by believing that there will be more than two flowers per node [10].
The segregation found for corolla color in the PEL evaluated was probably due to the contrasting parental genetic, the type of heritage (characterized as monogenic), and the codominant allelic interaction [29,31]. Flowers of different colors, such as those of this species, can be explored for ornamental purposes. Therefore, specific combinations can be obtained when combining this descriptor with other descriptors, generating varied products, thus reaching a greater number of consumers. This descriptor is important for identification of species and for phenotypic selection of individuals, in which taxonomists examine mainly the flowers.
The variability in anther color is a result of phenotypic segregation, as the parents presented contrasting anther colors. The observed colors denoted a potential for ornamental exploration, as it will provide contrast between the colors of flowers, fruits, and foliage, making the genotypes more attractive.
The emergence of semi-wrinkled fruit texture for plants of the F3 generation of PEL indicate that the parents were not homozygous for this characteristic, as both parents present a smooth fruit surface texture. However, the population presented phenotypic segregation for the referred descriptor. The texture can be useful for the characterization of genotypes through qualitative descriptors of fruits [32].
The phenotypic variability of fruits regarding color before maturation was due to the contrasting parental characteristics: white-greenish fruits (UNI01) and (UNI05) violet fruits [8]. Anthocyanins are the pigments responsible for the violet and red color of pepper fruits, denoting the ornamental potential of genotypes, since these colors are attractive to consumers, increasing the probability of sale [33]. Fruit color is one of the most important appearance characteristics for peppers (C. annuum L.), as it is the main reference adopted by consumers for selecting and purchase peppers [34].
The results showed that most genotypes present a desirable standard to the ornamental market. This perspective is favorable for breeding programs, since the selection is based on several characteristics. In this case, there is a higher possibility of combination of descriptors of ornamental interest that can be selected in PEL to compose a F3:4 generation.

4.2. Insights from the Qualitative Descriptors

4.2.1. Estimates of Components of Variance, Genetic Parameters, and Prediction of Genetic Values

Information on genetic variability and genetic parameters of characteristics of interest enables the genotypic selection among and within families, thus improving the breeding focused on obtaining pepper lines with ornamental potential [35].
Genetic materials desirable for selection should present higher CVgi% values than the CVe%, which are connected to environmental variations [36]. CVgi% and CVe% values vary depending on the characteristic, genotype, and plant species [37]. In the present study, all quantitative descriptors presented higher individual additive genetic coefficients of variation (CVgi) than residual coefficients of variation, denoting the existence of genetic variability to be explored.
The existence of this variability is essential for selection of superior PEL and for a continuous improvement of generations for obtaining lines with desirable ornamental characters. In addition to CVgi, [38] recommend the use of selective accuracy in the evaluation of experimental precision, focused on covering the maximum genetic information of the evaluated population.
The high selection accuracy values found ratify the experimental precision and the expressive genetic control, resulting in a strong reliability in the selection based on the descriptors studied. This is the most important statistical parameter in the selection of genotypes, as it correlates the true with the predicted genotypic value through the information obtained in the experiments [39]. The selection process in breeding programs is carried out searching for accuracy values above 70% [40]. Therefore, the values found in the present work are promising, ensuring the selection of PEL with precision and reliability, allowing the identification of genotypes with potential for the development of new ornamental pepper cultivars of pure lines.
The higher genetic variance and low environmental variance found among and within the PEL denote that the population is promising, enabling the obtaining of selection gains and the finding of the heritable part of the phenotypic data measured. The residual variance represents all sources of variation that are from non-genetic causes [41]. Non-genetic factors can make the individual to present similar results [42].
Despite the environmental effects, fruit characteristics are largely determined by heredity [43]. In the present study, the evaluated fruit high heritability; therefore, most of the observed variation in the population is due to genetic effects. There are reports of identification of many quantitative trait loci (QTL) with a strong effect on the phenotypic expression of fruit weight, length and diameter [44]. In addition, were also identified two QTL for fruit length (Ftl) (fl2.1 and fl3.1) and four QTL for fruit diameter (Ftd) (fd1.1, fd2.1, fd4.1 and fd11.2) in pepper (Capsicum spp.) [45]. In addition to the identification of two QTL for fruit length (paufl2.1 and paufl2.2), which explained 21.78% of the phenotypic variation [46].
The population also presented high heritability in the strict sense for other quantitative characters, expressing the reliability of phenotypic values for selection of superior PEL. This is due to the relatively small contribution of the environment for the expression of the phenotype [47], allowing the obtaining of genetic gains with phenotypic selection in initial generations of endogamic populations, as in the case of the F2:3 generation [48].
The high estimates of additive heritability within the PEL were another component of variance that stood out. In practice, the selective process will be effective and will make the selection of PEL through REML/BLUP for generation improvement to result in greater weight to the family effect. This is expected in F4 generations of autogamous species, since 3/4 of the additive genetic variation were found among families and only 1/4 within family [12]. The results obtained in the present work denote that the descriptors studied can and should be used for selection of PEL to form a F4 population, thus promoting an actual gain with high accuracy.

4.2.2. Simultaneous Selection of Superior PEL

The effect of genotypes in mixed models is considered random [39]. Thus, tests for comparison of means are not carried out. In addition, these comparisons result in inferences on phenotypic means and not on genotypic means. The ideal and safer method for selection purposes is basing on the PEL genotypic value acquired through descending ordering as a function of their genetic values obtained through mixed modeling. These are the true values to be predicted and, thus, can indicate the PEL free from environmental effect. This information is confirmed when observing the original means in relation to the individual phenotypic values of PEL, which presented higher values than the predicted additive genetic values.
The positive predicted genetic values denoted new higher means in relation to the overall mean estimates, despite presenting negative estimates of predicted additive genetic effects. In general, negative gains indicate an easy selection of individuals, which is carried out to reduce phenotypic values of, for example, the descriptors FC, MFL, MFD, and MFW. These descriptors are estimated through REML/BLUP and refer to the values found without environmental effects. They are equivalent to the predicted genetic mean values for the selected genotypes. The new mean refers to the overall mean of the characteristic added to the gain. Thus, a new population mean is obtained for a determined characteristic [49].
The values obtained for the new means are the predictions carried out by BLUP for commercial crops, i.e., commercial crops should present, on average, such values [50]. Identifying materials with results superior to the overall mean of the experiment is important for breeding programs, as it allows to discard lesser promising individuals and, thus, saves time and resources. The low amplitude presented by some characters is probably due to the narrowing of the means predicted by the REML/BLUP, which reduces phenotypic variance, decreasing the differences observed between genotypes, resulting in more genetic than environmental effects [40].
The selection of superior PEL was carried out among and within families, since the F2:3 generation under study had a high heterozygosity, a strategy that has proven effective in similar studies using multivariate analysis to identify ornamental ideotypes in pepper populations [51]. The lines were selected based on an early flowering cycle and on a late maturation cycle, which are between the descriptors of higher importance, allowing for a greater range of days with contrast in fruit color at different plant stages. The search for early pepper (Capsicum spp.) materials favors growers by decreasing the maintenance and optimizing the production process [52].
Regarding the fruit descriptors, the lightest and shortest fruits were selected, which tend to be ideal for ornamental purposes [53], mainly when combined with a small plant size. In addition, these characteristics increases the probability of selecting genotypes with erect fruits and, therefore, more pronounced on the foliage [54]. Large, long fruits are usually more attractive to the fresh pepper market [55]. Ornamental plant markets demand small-sized pepper plants [52], therefor, selection focused on reducing these characters is more adequate.

4.3. Insights from the Multivariate Analysis

The groups formed confirm the detection of genetic variability between PEL in the F2:3 population and reinforces the need for conducting more self-fertilization cycles in the selection practice for the advancement of segregate generations [5]. This genetic diversity depends mainly on the process of formation of the genetic resources studied, on the biology of fertilization of species, and on the diversity and size of the collection areas [56].
Capsicum populations can be explored through multivariate analysis, which is a viable option for studies of diversity and assists the breeder in the decision making for selection, mainly, when combined with the joint analysis of qualitative and quantitative data [5,57,58]. Qualitative characteristics, such as flower, fruit, and leaf colors are important for ornamental peppers, as they can be attractive to consumers.

4.4. Description of Ideotypes from Selection of PEL

The formation of groups based on simultaneous selection of qualitative and quantitative descriptors was used to proposes seven options of ideal genotypes:
I.
White flowers, violet anther, white-greenish fruits before maturation, wrinkled fruit surface texture, FC of 80 days; MC of 120 days, MFL of 33.98 mm, MFD of 12.38 mm, and MFW of 1.5 g. These features suggest a unique genetic background and potential for late-season ornamental displays.
II.
White flowers, blue anther, white-greenish fruits before maturation, semi-wrinkled fruit surface texture, FC of 96; MC of 119 days; MFL of 27.15 mm, MFD of 7.68 mm, and MFW of 1.38 g. The combination of medium flowering time and reduced fruit size makes them suitable for pot cultivation with moderate aesthetic appeal.
III.
White flowers, light blue anther, white-greenish fruits before maturation, smooth fruit surface texture, FC of 74 days, MC of 119 days, MFL of 25.44 mm, MFD of 9.83 mm, and MFW of 1.37 g. These lines exhibit early flowering and maturation, with small fruits, fitting well into commercial ornamental production systems aiming for uniformity and early market entry.
IV.
Violet flowers, violet anther, violet fruits before maturation, smooth fruit surface texture, FC of 76 days, MC of 119 days, MFL of 23.35 mm, MFD of 11.6 mm, and MFW of 1.57 g. With early flowering cycles and compact fruit size, these genotypes are highly desirable in ornamental markets due to their vivid coloration and compactness.
V.
White flowers with violet margins, light blue anther, violet fruits before maturation, semi-wrinkled fruit surface texture, FC of 82 days, MC of 120 days, MFL of 25.06 mm, MFD of 9.32 mm, and MFW of 1.43 g. These unique combinations enhance ornamental contrast, appealing to consumers looking for novelty in fruit appearance and floral traits.
VI.
White flowers with violet margins, light blue anther, white-greenish fruits before maturation, semi-wrinkled fruit surface texture, FC of 72 days, MC of 111 days, MFL of 33.04 mm, MFD of 14.52 mm, and MFW of 1.54 g. It is distinguished by its large fruits with a pronounced texture, which can be exploited commercially.
VII.
White flowers with violet margins, blue anther, white-greenish fruits before maturation, smooth fruit surface texture, FC of 67 days, MC of 119 days, MFL of 23.42 mm, MFD of 13.55 mm, and MFW of 1.22 g. Distinguished by very early flowering, white-margined flowers, and small smooth fruits, this genotype represents an ideal ideotype for ornamental use and short production cycles.
The present approach enables the decision making for selection of groups by PEL depending on the interests of the breeder, objective of the breeding program, consumer market, and ideotype selected from the seven options proposed as ideal genotypes.

5. Conclusions

There is genetic variability between and within partially inbred lines (PEL), which can be explored considering qualitative and quantitative variables. The high accuracy and heritability of the estimated quantitative descriptors allowed us to accurately select potential PEL, with emphasis on additive genetic effects and the lowest additive genotypic values for ornamental components. Seven distinct groups were obtained and allowed the identification of a total of 30 PEL (F2:3), which were selected to compose the next generation (F3:4).

Author Contributions

F.d.S.G.: Formal analysis, investigation, writing—original draft, writing—review. S.P.: conceptualization, supervision, writing—review and editing. G.C.A.C.: writing—review and editing, investigation. W.S.G.: writing—review and editing, formal analysis and conceptualization. J.C.R.: writing—review and editing, visualization, validation, investigation. N.d.A.D.J.: conceptualization, supervision, writing—review and editing. M.C.T.P.: writing—review and editing. M.M.M.: formal analysis, conceptualization, writing—review and editing. W.F.d.O.: supervision, writing—review and editing. A.K.P.B.: writing—review and editing, investigation. H.C.d.F.M.: supervision, writing—review and editing, A.C.P.G.: review and editing, M.V.B.M.S.: review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

Support for the project was provided by the Minas Gerais State Research Support Foundation (FAPEMIG - APQ-03144-22). The financial support for publication was provided by the Minas Gerais State University (Edital PROPPG N° 02/2025–PROPUBLIC/UEMG).

Data Availability Statement

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

Conflicts of Interest

The authors did not receive support from any organization for the submitted work. All authors certify that they have no affiliations with or involvement in any organization or entity with any financial interest or non-financial interest in the subject matter or materials discussed in this manuscript. The authors have no competing interests to declare that are relevant to the content of this article.

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Horticulturae 11 00789 g001
Figure 1. Illustrative Flowchart of the breeding program of pepper (C. annuum L.) focused on obtaining lines with advanced ornamental potential by the Pedigree Method. Highlighted plants are the selected ones. UNIMONTES, Janaúba, MG, Brazil, 2024.
Figure 1. Illustrative Flowchart of the breeding program of pepper (C. annuum L.) focused on obtaining lines with advanced ornamental potential by the Pedigree Method. Highlighted plants are the selected ones. UNIMONTES, Janaúba, MG, Brazil, 2024.
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Figure 2. Percentages observed in 240 partially endogamic lines of pepper (C. annuum L.) for the qualitative descriptors: (a) corolla color; (b) anther color; (c) fruit color before maturation; (d) fruit surface texture. UNIMONTES, Janaúba-MG, Brazil, 2025.
Figure 2. Percentages observed in 240 partially endogamic lines of pepper (C. annuum L.) for the qualitative descriptors: (a) corolla color; (b) anther color; (c) fruit color before maturation; (d) fruit surface texture. UNIMONTES, Janaúba-MG, Brazil, 2025.
Horticulturae 11 00789 g002
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Figure 3. Scatter diagrams with: (a) distribution of phenotypic values and rank; (b) additive genetic effects and genetic gain; (c) additive genetic values (u + a), and new predicted means, of 48 F2:3 partially endogamic lines selected through the Mulamba and Mock index based on quantitative descriptors of pepper (C. annuum L.). UNIMONTES, Janaúba-MG, Brazil, 2025.
Figure 3. Scatter diagrams with: (a) distribution of phenotypic values and rank; (b) additive genetic effects and genetic gain; (c) additive genetic values (u + a), and new predicted means, of 48 F2:3 partially endogamic lines selected through the Mulamba and Mock index based on quantitative descriptors of pepper (C. annuum L.). UNIMONTES, Janaúba-MG, Brazil, 2025.
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Figure 4. Clustering by the unweighted pair-group method with arithmetic mean (UPGMA) of 48 partially endogamic lines, based on qualitative and quantitative descriptors in a F2:3 population of peppers (C. annuum L.). UNIMONTES, Janaúba-MG, Brazil, 2025.
Figure 4. Clustering by the unweighted pair-group method with arithmetic mean (UPGMA) of 48 partially endogamic lines, based on qualitative and quantitative descriptors in a F2:3 population of peppers (C. annuum L.). UNIMONTES, Janaúba-MG, Brazil, 2025.
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Table 1. Components of variance, genetic parameters, and analysis of deviance estimated for quantitative descriptors in a F2:3 population of peppers (C. annuum L.) from partially endogamic lines (PEL). UNIMONTES, Janaúba-MG, Brazil, 2025.
Table 1. Components of variance, genetic parameters, and analysis of deviance estimated for quantitative descriptors in a F2:3 population of peppers (C. annuum L.) from partially endogamic lines (PEL). UNIMONTES, Janaúba-MG, Brazil, 2025.
PEL (F2:3)
ParametersFCMCMFLMFDMFW
σ2a85.8525.5014.692.520.03
σ2e31.646.748.440.480.02
σ2p117.5029.2523.143.000.06
h2a0.730.760.630.840.55
PSA0.850.870.790.910.74
h2ad0.650.660.870.620.63
CVgi%10.513.9315.4215.2012.83
CVe%6.382.1511.686.6311.37
GM88.08120.6824.8610.441.51
LRT133.65 **98.48 **100.77 **171.2 **43.81 **
FC = flowering cycle (days); MC = maturation cycle (days); MFL = mean fruit length (mm); MFD = mean fruit diameter (mm); and MFW = mean fruit weight (g); σ2a = genetic variance between progenies; σ2e = residual variance; σ2p = phenotypic variance; h2a = individual heritability in the strict sense; PSA = progeny selection accuracy, assuming complete survival; h2ad = additive heritability within the progeny; CVgi = individual additive genetic coefficient of variation; CVe = coefficient of residual variation; GM = overall mean; LRT = Likelihood Ratio Test. Chi-Square Tabulated Values: 6.63 for 1% (**) significance levels.
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MDPI and ACS Style

Gomes, F.d.S.; Pimenta, S.; Custódio, G.C.A.; Gomes, W.S.; Ribeiro, J.C.; Delvaux Júnior, N.d.A.; Pereira, M.C.T.; Moulin, M.M.; Oliveira, W.F.d.; Barbosa, A.K.P.; et al. Selection Strategy for Breeding Pepper Lines with Ornamental Potential. Horticulturae 2025, 11, 789. https://doi.org/10.3390/horticulturae11070789

AMA Style

Gomes FdS, Pimenta S, Custódio GCA, Gomes WS, Ribeiro JC, Delvaux Júnior NdA, Pereira MCT, Moulin MM, Oliveira WFd, Barbosa AKP, et al. Selection Strategy for Breeding Pepper Lines with Ornamental Potential. Horticulturae. 2025; 11(7):789. https://doi.org/10.3390/horticulturae11070789

Chicago/Turabian Style

Gomes, Fátima de Souza, Samy Pimenta, Gabriela Cristina Alves Custódio, Wellington Silva Gomes, Joyce Costa Ribeiro, Nelson de Abreu Delvaux Júnior, Marlon Cristian Toledo Pereira, Monique Moreira Moulin, Willer Fagundes de Oliveira, Ana Karolyne Pereira Barbosa, and et al. 2025. "Selection Strategy for Breeding Pepper Lines with Ornamental Potential" Horticulturae 11, no. 7: 789. https://doi.org/10.3390/horticulturae11070789

APA Style

Gomes, F. d. S., Pimenta, S., Custódio, G. C. A., Gomes, W. S., Ribeiro, J. C., Delvaux Júnior, N. d. A., Pereira, M. C. T., Moulin, M. M., Oliveira, W. F. d., Barbosa, A. K. P., Monteiro, H. C. d. F., Gonçalves, A. C. P., & Siqueira, M. V. B. M. (2025). Selection Strategy for Breeding Pepper Lines with Ornamental Potential. Horticulturae, 11(7), 789. https://doi.org/10.3390/horticulturae11070789

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