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Article

Comprehensive Genetic Analysis of Edible-Podded Pea Genotypes: Variability, Heritability, and Multivariate Approach Across Two Agro-Climatic Zones in India

by
Saurabh Yadav
1,
Rajinder Kumar Dhall
1,*,
Hira Singh
1,*,
Parteek Kumar
2,
Priti Sharma
2,
Pradeep Kumar
3,
Priyanka Kumari
1 and
Neha Rana
1
1
Department of Vegetable Science, College of Horticulture & Forestry, Punjab Agricultural University, Ludhiana 141004, Punjab, India
2
School of Agricultural Biotechnology, College of Agriculture, Punjab Agricultural University, Ludhiana 141004, Punjab, India
3
ICAR—Central Institute for Arid Horticulture, Bikaner 334006, Rajasthan, India
*
Authors to whom correspondence should be addressed.
Horticulturae 2025, 11(1), 22; https://doi.org/10.3390/horticulturae11010022
Submission received: 12 November 2024 / Revised: 24 December 2024 / Accepted: 30 December 2024 / Published: 1 January 2025
(This article belongs to the Special Issue Genomics and Genetic Diversity in Vegetable Crops)
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Abstract

:
Evaluating genetically superior genotypes is essential for developing new hybrid varieties. This study aimed to assess the genetic diversity of 28 edible-podded pea genotypes by analyzing phenological traits, vigor, yield, and biochemical traits across two distinct agro-climatic zones in India. Significant variation was observed for most traits, with high genotypic and phenotypic coefficients of variation, heritability, and genetic advance, especially in vigor, yield, and biochemical traits. Phenological traits, except for the node at which the first flower appeared, exhibited minimal variability, indicating a high degree of uniformity. Yield per plant was negatively correlated with plant height but positively correlated with pod length, the number of seeds per pod, the number of pods per plant, and pod weight, indicating the potential for the simultaneous selection of these traits in breeding programs. Principal component analysis (PCA) identified six components explaining over 75% of the total variation, with yield and biochemical traits contributing the most to the observed diversity. These findings provide crucial insights for breeders aiming to improve quantitative traits, supporting the development of high-yielding and climate-resilient edible-podded pea varieties in India.

1. Introduction

Edible-podded peas, including Sugar Snap peas (Pisum sativum var. saccharatum) and Snow peas (P. sativum var. macrocarpon), are typically cultivated during the winter season, following similar practices to those used for garden peas. These peas are highly valued for their tender, fresh pods, which lack a parchment layer and offer a delightful combination of sweetness, crispness, and mild flavor [1]. Snow peas have thinner walls compared to Sugar Snap peas and resemble green beans with thick walls and small peas inside, while Snow pea pods are flat. These varieties are usually consumed whole, without the need for shelling, although tough strings along the edges are typically removed before eating. The suitability of the entire pod for consumption at the fresh stage is due to the expression of certain recessive genes [2]. For example, the recessive gene p eliminates the sclerenchymatous membrane of the inner pod wall, v reduces pod wall thickness, and n contributes to thick, fleshy pod walls. These genes have been extensively studied for their role in determining pod morphology and quality traits, as noted in earlier genetic analyses [3]. Such morphological traits are important for both consumer preference and breeding programs targeting edible-podded peas [2,3].
Pea cultivation is highly adaptable, thriving in diverse agro-climatic zones due to its extensive genetic diversity, which manifests both at the phenotypic and molecular levels. This adaptability can be attributed to a wide range of genotypic variations that influence key traits such as yield, phenology, and stress tolerance [4]. Such diversity not only enhances cultivation potential across different regions but also facilitates breeding programs aimed at improving trait stability under variable conditions [4,5]. In legumes, phenological traits, yield, and vigor are crucial for assessing genetic diversity and understanding crop performance and adaptation [6,7]. The performance of pea crops is heavily influenced by environmental conditions, such as temperature, soil type, and rainfall, which vary significantly between different agro-climatic regions. These environmental factors play a crucial role in shaping the phenological development, yield, and overall vigor of peas. In India, the diverse agro-climatic zones present unique challenges and opportunities for pea cultivation, necessitating breeding strategies that consider genotype-by-environment interactions (G × E). Breeding for adaptability in these conditions is essential for ensuring resilience and maximizing yield potential.
One of the primary goals of pea breeders is to enhance pea performance across varying environments as the effects of both the environment (E) and G × E interactions significantly influence the crop’s growth and productivity [8]. Traits like heritability and genetic variability are key tools in determining the potential for selection and improvement, as they distinguish traits driven by genetic factors from those heavily influenced by environmental conditions [4,6]. While many garden pea varieties have been developed in India, there is a growing demand for edible-podded pea varieties that address the nutritional losses—particularly in protein, fiber, and minerals—found in the pod walls of these peas [9].
The effectiveness of utilizing genetic variability through selection depends on factors such as heritability, genetic advance, and correlations among traits [10]. Furthermore, environmental variability introduces challenges in ensuring stable phenotypic expression, making it necessary to study traits across multiple locations. Understanding these factors in advanced breeding lines is critical for developing well-adapted edible-podded pea varieties [11]. Negative genetic correlations between traits can lead to trade-offs, limiting genetic progress and risking unintended declines in unselected traits (genetic slippage) [12]. Understanding the individual contributions of various traits enables breeders to perform more effective selection. Additionally, multivariate techniques, such as principal component analysis (PCA), are valuable for grouping genotypes and identifying suitable parents for crossbreeding [13].
This study aims to investigate the variability in edible-podded pea genotypes by examining phenological traits, vigor, yield, and biochemical traits across two distinct agro-climatic zones. This investigation also assesses the relationship between measured traits and genetic diversity to determine their role in selection and improvement. Specifically, we assess heritability, explore trait relationships, analyze germplasm structure through association analysis, and evaluate the effects of environmental factors and G × E interactions on these traits. The findings will contribute to enhancing breeding programs for edible-podded peas in India, with an emphasis on developing climate-resilient, high-yielding varieties.

2. Materials and Methods

2.1. Plant Material and Cultural Practices

In this study, 28 edible-podded pea genotypes, including 10 genotypes of Sugar Snap peas and 18 genotypes of Snow peas, were evaluated (Table 1). The entire collection was maintained at Punjab Agricultural University (Ludhiana, India), and field trials were conducted at two locations to assess phenological traits, vigor, yield, and biochemical traits. The genotypes were sown using a randomized block design (RBD) with three replications at both locations. For each plot of each genotype, three representative plants were carefully selected to ensure uniformity and reduce bias, as these plants served as the basis for data collection on all traits. The spacing between rows was 30 cm, while the spacing between plants was 7.5 cm. Consistent cultural practices were followed at both locations. Prior to sowing, 45 kg of urea and 155 kg of superphosphate per acre were applied as a basal dose. For weed control, Stomp 30 EC (pendimethalin) @1.0 L per acre was applied within two days of sowing, dissolved in 150–200 L of water. Manual weeding was performed twice—one month and two months after sowing.

2.2. Location and Climatic Conditions

This experiment was conducted at two distinct locations in India, each falling under different agro-climatic zones. The first trial took place at the Vegetable Research Farm, the Department of Vegetable Science, Punjab Agricultural University, Ludhiana (30°54′26″ N latitude, 75°47′38″ E longitude, 247 m above sea level), which is located in the Trans-Gangetic Plains agro-climatic zone. The trial was conducted during December 2022–March 2023, with temperatures ranging from 9.51 °C to 22.12 °C and an average rainfall of 9.55 mm throughout the cropping period. The soil was sandy loam, with a pH of 8.5. The second trial was conducted at the Regional Research Station of Punjab Agricultural University in Keylong, Himachal Pradesh (32°56′70″ N latitude, 77°05′43″ E longitude, 3080 m above sea level), which falls under the Western Himalayan agro-climatic zone. This trial was conducted from May to August 2023. The soil in this region ranged from loamy sand to sandy loam with varying gravel content and was slightly acidic (pH 6.48). During the cropping period, temperatures ranged from 4 °C to 25 °C, with an average rainfall of 21.17 mm.

2.3. Data Collection

The data were individually collected from both locations. For each genotype, the data were taken from three randomly selected plants in each replication, and their means were computed for the following traits: phenological traits—the node on which first flower appears (NFA), days to first flowering (DTF), days to fifty percent flowering (DTFF), and days to pod formation (DTPF); plant vigor traits—plant height in cm (PH) and the number of primary branches (NB); yield components—the number of seeds per pod (NS), pod breadth in mm (PB), pod length in cm (PL), the number of pods per plant (NPPP), weight of ten pods in grams (TPW), and yield per plant in grams (Y); and biochemical parameters—dry matter percentage (DM), soluble protein content percentage on a fresh weight basis (SP), total sugar percentage (TS), reducing sugar percentage (RS), ascorbic acid in mg/100 g of fresh weight (AA), and fiber percentage on a fresh weight basis (F). Careful attention was given to ensure that the three selected plants were uniform and free from obvious defects or external stress, enhancing the reliability of the data collected. Data collection procedures were standardized across locations to minimize environmental bias and ensure comparability. To evaluate both yield and biochemical traits, pods were collected from the same three plants of each genotype in each replication that were previously selected for phenology and vigor assessments. Pods were harvested at the stage of edible maturity, before string development, and manually cleaned to eliminate any foreign particles and dust. All biochemical analyses were conducted on the whole pods of each replication, including the seeds. To measure the dry matter (DM) content of whole green peas, fresh pods from each genotype were dried in an oven at 65 ± 2 °C until a constant weight was achieved. The soluble protein (SP) content in green unshelled peas at the edible stage was estimated using Lowry’s method [14], while total sugar (TS) content in pods was assessed by the Dubois method [15]. The reducing sugar (RS) content in pods at the dry stage was measured using Nelson–Somogyi’s method [16]. Ascorbic acid (AA) content on a fresh weight basis was determined by the method proposed by Hussain [17], and fiber (F) content on a fresh weight basis was estimated using the method provided by James [18].

2.4. Statistical Analysis

The statistical analyses were conducted using the R program (version 3.6.3) [19]. A two-way analysis of variance (ANOVA) was carried out on the pooled mean data from both locations using the Metan package. Mean values were distinguished using the least significant difference (LSD) method at a significance level of 5%. Various genetic parameters, including genotypic variance (σ2g), phenotypic variance (σ2p), environmental variance (σ2e), the genotypic coefficient of variation (GCV), the phenotypic coefficient of variation (PCV), the environmental coefficient of variation (ECV), heritability (h2), and genetic advance as a percentage of the mean (GAPM), were calculated using the variability package. To evaluate genotype-by-location interactions, a detailed assessment of the data was performed, emphasizing how environmental factors influenced trait expression. Pearson correlation analysis was computed and visually presented for the phenotypic data using a two-tailed test of significance at a 5% level with the corrplot package in R (Version: 2024.09.0+375.pro3). Principal component analysis (PCA) involving the 18 traits was conducted using the vqv/ggbiplot package. These analyses provided insights into trait variability, relationships, and potential contributions to genetic improvement.

3. Results

3.1. Combined ANOVA

The pooled analysis of variance for 18 phenological traits, vigor, yield, and biochemical traits of 28 edible-podded pea genotypes, evaluated at Ludhiana and Keylong during 2022–2023, is presented in Table 2. The mean squares for genotypes and genotype-by-location interactions showed significant differences (p < 0.001) for all traits. Highly significant variation (p < 0.001) was also observed across both locations for all traits.

3.2. Phenotypic and Genotypic Coefficient of Variation

The PCV and GCV values are given in Table 3. PCV and GCV values below 10%, 10–20%, and above 20% were, respectively, regarded as low, intermediate, and high [20]. The values of PCV and GCV were low for DTPF (1.04, 5.76), DTF (1.62, 6.02), and DTFF (4.24, 5.84), were intermediate only for NFA (13.47, 19.30), and were high for NPPP (20.43, 22.47), NS (22.22, 23.17), PB (23.82, 25.89), PL (25.15, 27.64), DM (28.22, 33.46), SP (37.72, 41.59), NB (38.46, 39.34), AA (38.82, 40.94), TS (39.44, 41.49), TPW (41.89, 42.39), PH (45.50, 47.36), Y (46.15, 48.32), RS (52.07, 59.57), and F (61.33, 65.14).
For all traits, the PCV values consistently exceeded the corresponding GCV values. The difference between the PCV and GCV was 4.72, 1.60, 4.40, 5.83, 2.04, 0.95, 2.07, 2.94, 5.24, 0.88, 2.12, 2.05, 3.87, 0.50, 1.86, 2.17, 7.50, and 3.81 for DTPF, DTFF, DTF, NFA, NPPP, NS, PB, PL, DM, NB, AA, TS, SP, TPW, PH, Y, RS, and F, respectively (Table 3). The observed ECV values were high for F (21.97) and RS (28.95); were intermediate for PB (10.16), PL (11.46), TS (12.89), AA (13.02), PH (13.14), NFA (13.82), Y (14.30), SP (17.52), and DM (17.98); and were low for DTFF (4.01), DTPF (5.69), DTFB (5.80), TPW (6.51), NS (6.57), NB (8.31), and NPPP (9.35).

3.3. Broad-Sense Heritability (h2) and Genetic Advance as Percentage of Mean (GAPM)

The h2 values <40%, 40–80%, and >80% were categorized as low, medium, and high, respectively [20]. Estimates of heritability (h2) ranged from 3% to 98% for DTPF and TPW, respectively (Table 3). A high value of broad-sense heritability was observed for SP (82), PL (83), NPPP (83), PB (85), F (89), TS (90), AA (90), Y (91), PH (92), NS (92), NB (95), and TPW (98); an intermediate value of heritability was recorded for NFA (49), DTFB (52), DM (71), and RS (76); and a low value of heritability was recorded for DTPF (3) and DTFF (7).
The values of GAPM were categorized as high (>20%), intermediate (10–20%), and low (<10%) [20]. In this study, it was low for DTPF (0.39%), DTFF (0.90%), and DTFB (6.35%); intermediate for NFA (19.38%); and high for NPPP (38.28%), NS (43.90%), PB (45.13%), PL (47.14%), DM (49.03%), SP (70.46%), AA (75.81%), TS (77.23%), NB (77.43%), TPW (85.27%), PH (90.05%), Y (90.81%), RS (93.74%), and F (118.93%).

3.4. Correlation Analysis

A correlation coefficient analysis was conducted to examine the associations between phenological traits, plant vigor, yield, and biochemical traits. The results of the Pearson correlation coefficient are presented in Figure 1.
The phenological trait days to first flowering (DTF) showed a highly significant positive correlation with days to pod formation (DTPF) (0.88 ***), while DTPF was significantly associated with days to 50% flowering (DTFF) (0.44 **). Interestingly, DTFF was also significantly correlated with the yield-related trait number of pods per plant (NPPP) (0.45 *). Among yield-related traits, pod length (PL) exhibited a strong positive correlation with number of seeds per pod (NS) (0.81 ***). NS was also significantly associated with yield per plant (Y) (0.47 *) and ten pod weight (TPW) (0.48 *). Additionally, NPPP showed a positive association with Y (0.40 *), and Y was highly and significantly correlated with TPW (0.89 ***). Plant height (PH) displayed a positive and significant association with node of first flowering (NFA) (0.65 ***) but was negatively correlated with TPW (−0.54 ***) and Y (−0.44 *). Furthermore, a significant positive association was observed between biochemical and yield-related traits. Y and TPW were both significantly and positively correlated with ascorbic acid (AA) (0.38 * and 0.43 *, respectively). However, AA had a significant negative correlation with fiber (F) (−0.44 *) and NFA (−0.47 *). Total sugar (TS) exhibited a positive and significant correlation with reducing sugar (RS) (0.74 ***) and soluble proteins (P) (0.47 *). On the other hand, TS showed a significant negative association with DTFF (−0.47 **), DTPF (−0.38 *), DTF (−0.39 *), and NPPP (−0.55 **).

3.5. Principal Component Analysis

PCA was employed to visually represent the dataset through a two-dimensional biplot (Figure 2). The analysis revealed 18 principal components (PCs), but only the first 6 PCs had eigenvalues greater than one, collectively explaining over 75% of the total variation (Figure 3). Information regarding the traits contributing the most variability and the genotypes with the greatest influence is presented in Figure 4 and Figure 5, respectively.
By analyzing the PCA results, it is clear that PC1 accounts for the largest portion of variation (23.89%). This variation is primarily attributed to traits such as TPW, Y, and PL, along with genotypes like Honey Snap, PED-18-1 (Sugar Snap pea), and Sugar Bon (Snow pea). PC2 explains 18.81% of the variation, with significant contributions from traits such as TS, RS, DTFF, and DTF, as well as genotypes like PED-18-8 (Sugar Snap) and Sugar Daddy (Snow pea). PC3 accounts for 12.17% of the variation, driven mainly by biochemical traits like F and DM, associated with Snow pea genotypes Airtel and Dwarf Grey Sugar. In contrast, PC4 (8.96%) shows variability in phenological traits (NFA) and yield-related traits (NS), with notable contributions from genotypes PED-18-5 and Namdhari-NA, from the Snow and Sugar Snap pea groups, respectively. PC5 and PC6 contribute approximately 6.5% of the variation each. Interestingly, the Snow pea genotype PED-21-6 is a significant contributor to both PC5 and PC6, associated with the yield-related trait PB and phenological trait NB, respectively.

4. Discussion

This study was conducted across two contrasting agro-climatic zones (Ludhiana and Keylong) to capture genotype-by-environment interactions and provide reliable insights into the genetic variability of edible-podded peas. While the study was conducted in a single cropping season, the multi-location approach partially mitigates this limitation by evaluating genotypes under diverse environmental conditions.
Significant (p < 0.001) variation among genotypes for all traits (Table 1) and across locations, coupled with significant genotype-by-location interactions, highlights the combined influence of genetic and environmental factors on phenotypic expression. This observed diversity underscores the importance of evaluating genotypes across diverse environments to identify stable and high-yielding lines [20]. Previous studies have also reported considerable variability in phenological, vigor-related, yield-related, and biochemical traits within pea germplasm [21,22,23,24,25,26]. Furthermore, environmental factors, such as weather, soil conditions, and agricultural practices, influence gene expression, contributing to the observed phenotypic variation [27,28]. This emphasizes the need for genotype-specific management practices and multi-environment trials over multiple years to validate the stability of high-performing genotypes and further investigate environmental interactions.
Variability analysis revealed high PCV and GCV values for traits such as vigor, yield, and biochemical attributes, indicating substantial diversity and strong genetic control, thereby highlighting the potential for significant genetic improvement through selection [18]. In contrast, phenological traits exhibited low PCV and GCV, suggesting limited phenotypic and genotypic variability and a potentially lower scope for genetic gain [18].
A higher PCV compared to the GCV was recorded for vigor, yield, and biochemical traits, reflecting greater environmental influence on their phenotypic expression [29]. Conversely, a lower GCV compared to the PCV for phenological traits suggests a stronger genetic influence [29]. These findings emphasize the need to consider both genetic and environmental factors when selecting for traits influenced by environmental factors, such as vigor, yield, and biochemical characteristics. Similar observations have been made in previous studies [30], which have emphasized that while GCV provides insights into genetic variability in quantitative traits, it does not solely define heritable variation.
Heritability estimates varied across traits, with high values (>60%) observed for most traits except for phenological traits (Table 3), suggesting they are less influenced by environmental factors [31]. This aligns with previous studies that suggest that traits with high heritability typically exhibit a smaller genotype-by-environment interaction [28]. However, the low heritability for phenological traits indicates substantial environmental influence and underlines the need for integrating genomic tools, such as QTL mapping and marker-assisted selection, to complement phenotypic selection [32]
The effectiveness of genetic improvement is linked to the magnitude of the GCV, heritability, and genetic advance [33]. In this study, high heritability combined with high genetic advance was observed for most traits, except phenological traits, indicating the potential for significant genetic improvement through selection [34]. Additionally, these findings also highlight that at least 0.90% genetic improvement could be achieved for these 18 traits through selective breeding.
Polygenic traits are sensitive to environmental factors, meaning that selection based solely on yield may not be effective [21]. For effective improvements, selection must account for associated traits [35]. Significant correlations between traits not only induce variations in one trait through additive gene effects but also have indirect effects on correlated traits [33]. Genetic linkage or epistatic interactions between different genes may explain these associations [36]. The results of the correlation analysis are demonstrated in Figure 1. All the phenological traits found correlated to each other in this study. Similar results were also found by Panwar et al. [37], where they obtained a positive and significant correlation between NFA, DTFF, and DTPF. These traits are directly or indirectly classified peas into different maturity groups. Additionally, the vegetative growth of a plant affects its reproductive growth, and in this study, the height of pea plants is positively and significantly associated with NFA, but TPW and Y are negatively correlated with PH, which are the prerequisites of a high-yielding variety [37,38].
Moreover, the identification of key traits that contribute effectively to high yield is important. Generally, the yield of peas depends upon many factors like pod length, pod weight, the number of seeds per pod, the number of pods per plant, and pod weight. All these traits are also found to be associated with each other in this study. The results related to the association of all the phenological, vigor- and yield-related traits are similar to the previous findings of Chauhan et al. [38] for Sugar Snap peas and Al-Aysh et al. [21], Mamatha et al. [39], Kumar et al. [40] and Uhlarik et al. [41] for peas.
Furthermore, a significant positive correlation was observed between ascorbic acid (AA) content and yield-related traits such as Y and TPW. This positive association between AA and yield highlights the potential for integrating biochemical traits as selection criteria for improving yield stability. The observed positive association suggests that higher AA levels may contribute to improved plant health as it is a critical antioxidant in plants, playing a key role in protecting cells from oxidative stress, enhancing photosynthetic efficiency, and supporting various metabolic processes (Gallie et al. [42]), which in turn leads to increased yield and pod weight. These findings are consistent with a previous study by Al-Aysh et al. [21] on garden pea, where similar positive correlations between antioxidant content and yield have been reported. Breeding strategies should emphasize these correlated traits to ensure improvement in overall productivity [38,39,40,41].
In line with earlier findings by Shu et al. [43], our study found a significant positive association between TS and RS. Although TS showed a positive and substantial association with SP as previously reported by Chauhan et al. [38], it expresses a significant negative correlation with NPPP and several key reproductive traits, including the DTFF, DTPF, and DTF. This inverse relationship suggests a potential resource allocation trade-off, where limited resources necessitate a balance between vegetative growth, reproductive development, and carbohydrate storage [44]. Plants that invest more in sugar accumulation may do so at the expense of earlier flowering and pod formation [44]. These findings align with previous studies by Mamatha et al. [39] and Kumar et al. [40] on garden pea itself, where similar negative correlations have been reported between carbohydrate reserves and reproductive timing. Understanding these relationships is crucial for breeding programs aimed at improving both sugar content and reproductive efficiency in garden pea, as a simultaneous selection for these traits may be challenging due to their inherent trade-offs.
Traits such as yield and vigor exhibited high autocorrelation, which, while reflecting underlying biological relationships and aiding in the identification of indirect selection pathways, may introduce overlapping information. To address this, principal component analysis (PCA) was employed to pinpoint the key traits contributing to the overall variability. The PCA revealed 18 principal components, with the first 6 explaining over 75% of the variation (Figure 3). The grouping of genotypes was found to be independent of their classification as Snow peas or Sugar Snap peas. These genotypes can be exploited for hybridization in varietal improvement programs. Thirteen traits, particularly yield and biochemical traits, contributed significantly to the overall variability within the assessed edible-podded pea genotypes (Figure 4). Similar results have been reported for yield-related traits by Ouafi et al. [45], Singh et al. [46], and Ali et al. [47], while the findings related to biochemical traits are consistent with the work of Kuneva et al. [48] and Ton et al. [49].

5. Conclusions

The present investigation underscores the substantial genetic variability among 28 edible-podded pea genotypes for vigor, yield, and biochemical traits, with certain phenological traits being more influenced by environmental factors. The correlation analysis revealed significant interdependence among phenological and yield traits, particularly highlighting the role of pod weight, pod length, and ascorbic acid content in enhancing yield potential. The PCA identified yield and biochemical traits as the major contributors to variability, emphasizing their prioritization in varietal improvement programs. Based on the PCA, the genotypes Airtel, Sugar Bon, PED-2021-6, Dwarf Grey Sugar, Sugar Daddy, and Namdhari-NA from the Snow pea group, and Honey Snap, PED-2018-1, PED-2018-6, and PED-2018-6 from the Sugar Snap pea group, emerged as the most diverse genotypes. These genotypes offer significant potential for breeding programs due to their diverse traits and adaptability to varying environmental conditions. The observed diversity also underscores the importance of multi-environment testing to identify stable genotypes capable of maintaining performance across agro-climatic zones. Moreover, although this study provides valuable insights into the genetic variability of edible-podded peas, the conclusions are limited by the single-year observation and the sample size used. Future studies involving multi-year trials and larger populations are recommended to validate these findings.

Author Contributions

Conceptualization, R.K.D.; methodology, R.K.D. and S.Y.; software, S.Y. and P.K. (Parteek Kumar); validation, R.K.D., S.Y. and H.S.; formal analysis, S.Y. and P.K. (Pradeep Kumar); investigation, R.K.D.; resources, R.K.D.; data curation, S.Y., P.K. (Priyanka Kumari) and N.R.; writing—original draft preparation, S.Y. and P.K. (Parteek Kumar); writing—review and editing, H.S., P.S. and P.K. (Pradeep Kumar); supervision, R.K.D. and P.S.; project administration, R.K.D.; funding acquisition, R.K.D. All authors have read and agreed to the published version of the manuscript.

Funding

The work is funded by the Ministry of Science and Technology, the Department of Biotechnology, the Government of India, under the Scheme “Centre of Excellence—Development and Integration of Advanced Genomic Technologies for Targeted Breeding” (No: BT/Ag/CoE/PAU-GSKIG/2020-21) and CSS 52 (PC-6372).

Data Availability Statement

The data associated with this study have already been given in the manuscript.

Acknowledgments

The research work was carried out with the support of Punjab Agricultural University, Ludhiana.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Correlation coefficient matrix. Note: The correlation coefficient, along with its level of significance: * for p ≤ 0.05, ** for p ≤ 0.01, and *** for p > 0.001, denoting the respective significance levels; NFA, node on which first flower appears; DTF, days to first flowering; DTFF, days to fifty percent flowering; DTPF, days to pod formation; PH, plant height (cm); NB, number of primary branches; NS, number of seeds per pod; PB, pod breadth (mm); PL, pod length (cm); NPPP, number of pods per plant; TPW, weight of ten pods (g); Y, yield per plant (g); DM, dry matter (%); SP, soluble protein content percentage on a fresh weight basis; TS, total sugar (%); RS, reducing sugar (%); AA, ascorbic acid mg/100 g of fresh weight; and F, fiber percentage on fresh weight basis. ns—non-significant.
Figure 1. Correlation coefficient matrix. Note: The correlation coefficient, along with its level of significance: * for p ≤ 0.05, ** for p ≤ 0.01, and *** for p > 0.001, denoting the respective significance levels; NFA, node on which first flower appears; DTF, days to first flowering; DTFF, days to fifty percent flowering; DTPF, days to pod formation; PH, plant height (cm); NB, number of primary branches; NS, number of seeds per pod; PB, pod breadth (mm); PL, pod length (cm); NPPP, number of pods per plant; TPW, weight of ten pods (g); Y, yield per plant (g); DM, dry matter (%); SP, soluble protein content percentage on a fresh weight basis; TS, total sugar (%); RS, reducing sugar (%); AA, ascorbic acid mg/100 g of fresh weight; and F, fiber percentage on fresh weight basis. ns—non-significant.
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Figure 2. Biplot for the 28 edible-podded genotypes and all the 18 traits along the first 2 principal components. NFA, node on which first flower appears; DTF, days to first flowering; DTFF, days to fifty percent flowering; DTPF, days to pod formation; PH, plant height (cm); NB, number of primary branches; NS, number of seeds per pod; PB, pod breadth (mm); PL, pod length (cm); NPPP, number of pods per plant; TPW, weight of ten pods (g); Y, yield per plant (g); DM, dry matter (%); SP, soluble protein content percentage on a fresh weight basis; TS, total sugar (%); RS, reducing sugar (%); AA, ascorbic acid mg/100 g of fresh weight; and F, fiber percentage on fresh weight basis.
Figure 2. Biplot for the 28 edible-podded genotypes and all the 18 traits along the first 2 principal components. NFA, node on which first flower appears; DTF, days to first flowering; DTFF, days to fifty percent flowering; DTPF, days to pod formation; PH, plant height (cm); NB, number of primary branches; NS, number of seeds per pod; PB, pod breadth (mm); PL, pod length (cm); NPPP, number of pods per plant; TPW, weight of ten pods (g); Y, yield per plant (g); DM, dry matter (%); SP, soluble protein content percentage on a fresh weight basis; TS, total sugar (%); RS, reducing sugar (%); AA, ascorbic acid mg/100 g of fresh weight; and F, fiber percentage on fresh weight basis.
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Figure 3. Eigenvectors and total percentage variation among the traits within 28 edible-podded pea genotypes. Note: Dim. 1, Principal Component 1; Dim. 2, Principal Component 2; Dim. 3, Principal Component 3; Dim. 4, Principal Component 4; Dim. 5, Principal Component 5; Dim. 6, Principal Component 6, Dim. 7, Principal Component 7; Dim. 8, Principal Component 8; Dim. 9, Principal Component 9; Dim. 10, Principal Component 10; Dim. 11, Principal Component 11; Dim. 12, Principal Component 12; Dim. 13, Principal Component 13; Dim. 14, Principal Component 14; Dim. 15, Principal Component 15; Dim. 16, Principal Component 16; Dim. 17, Principal Component 17; Dim. 18, Principal Component 18.
Figure 3. Eigenvectors and total percentage variation among the traits within 28 edible-podded pea genotypes. Note: Dim. 1, Principal Component 1; Dim. 2, Principal Component 2; Dim. 3, Principal Component 3; Dim. 4, Principal Component 4; Dim. 5, Principal Component 5; Dim. 6, Principal Component 6, Dim. 7, Principal Component 7; Dim. 8, Principal Component 8; Dim. 9, Principal Component 9; Dim. 10, Principal Component 10; Dim. 11, Principal Component 11; Dim. 12, Principal Component 12; Dim. 13, Principal Component 13; Dim. 14, Principal Component 14; Dim. 15, Principal Component 15; Dim. 16, Principal Component 16; Dim. 17, Principal Component 17; Dim. 18, Principal Component 18.
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Figure 4. Most contributing traits for each dimension or principal component. Note: Dim. 1, Principal Component 1; Dim. 2, Principal Component 2; Dim. 3, Principal Component 3; Dim. 4, Principal Component 4; Dim. 5, Principal Component 5; Dim. 6, Principal Component 6; Dim. 7, Principal Component 7; Dim. 8, Principal Component 8; Dim. 9, Principal Component 9; Dim. 10, Principal Component 10; Dim. 11, Principal Component 11; Dim. 12, Principal Component 12; Dim. 13, Principal Component 13; Dim. 14, Principal Component 14; Dim. 15, Principal Component 15; Dim. 16, Principal Component 16; Dim. 17, Principal Component 17; Dim. 18, Principal Component 18.
Figure 4. Most contributing traits for each dimension or principal component. Note: Dim. 1, Principal Component 1; Dim. 2, Principal Component 2; Dim. 3, Principal Component 3; Dim. 4, Principal Component 4; Dim. 5, Principal Component 5; Dim. 6, Principal Component 6; Dim. 7, Principal Component 7; Dim. 8, Principal Component 8; Dim. 9, Principal Component 9; Dim. 10, Principal Component 10; Dim. 11, Principal Component 11; Dim. 12, Principal Component 12; Dim. 13, Principal Component 13; Dim. 14, Principal Component 14; Dim. 15, Principal Component 15; Dim. 16, Principal Component 16; Dim. 17, Principal Component 17; Dim. 18, Principal Component 18.
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Figure 5. Contribution of the genotypes to the first six principal components. Note: 1, Airtel; 2, Oregon Sugar pod; 3, Arka Sampoorna; 4, PED-21-4; 5, Tardio; 6, Sugar Bon; 7, PED-2018-5; 8, PED-2021-6; 9, PED-2021-2; 10, PED-2018-7; 11, Namdhari Afila 12, Mithi Phali; 13, Tarvedo Sugar; 14, PED-2021-7; 15, Dwarf Grey Sugar; 16, PED-2018-1; 17, Sugar Daddy; 18, PED-21-1; 19, Sugar Snappy; 20, PED-21-5; 21, PED-21-3; 22, PED-18-6; 23, Namdhari-NA; 24, PED-2018-8; 25, HPM-1; 26, HPM-2; 27, Honey Snap; 28, Royal Snow; Dim. 1, Principal Component 1; Dim. 2, Principal Component 2; Dim. 3, Principal Component 3; Dim. 4, Principal Component 4; Dim. 5, Principal Component 5; Dim. 6, Principal Component 6.
Figure 5. Contribution of the genotypes to the first six principal components. Note: 1, Airtel; 2, Oregon Sugar pod; 3, Arka Sampoorna; 4, PED-21-4; 5, Tardio; 6, Sugar Bon; 7, PED-2018-5; 8, PED-2021-6; 9, PED-2021-2; 10, PED-2018-7; 11, Namdhari Afila 12, Mithi Phali; 13, Tarvedo Sugar; 14, PED-2021-7; 15, Dwarf Grey Sugar; 16, PED-2018-1; 17, Sugar Daddy; 18, PED-21-1; 19, Sugar Snappy; 20, PED-21-5; 21, PED-21-3; 22, PED-18-6; 23, Namdhari-NA; 24, PED-2018-8; 25, HPM-1; 26, HPM-2; 27, Honey Snap; 28, Royal Snow; Dim. 1, Principal Component 1; Dim. 2, Principal Component 2; Dim. 3, Principal Component 3; Dim. 4, Principal Component 4; Dim. 5, Principal Component 5; Dim. 6, Principal Component 6.
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Table 1. List of edible-podded pea genotypes used in present study.
Table 1. List of edible-podded pea genotypes used in present study.
S. No.GenotypesEdible-Podded TypeSource
1.AirtelSnow peaUSA
2.Oregon Sugar PodSnow peaUSA
3.Arka SampoornaSnow peaIIHR, Bangalore
4.PED-2021-4Sugar Snap peaPAU, Ludhiana
5.TardioSnow peaPAU, Ludhiana
6.Sugar BonSnow peaUSA
7.PED-2018-5Sugar Snap peaPAU, Ludhiana
8.PED-2021-6Snow peaPAU, Ludhiana
9.PED-2021-2Snow peaPAU, Ludhiana
10.PED-2018-7Sugar Snap peaPAU, Ludhiana
11.Namdhari AfilaSnow peaNamdhari Seeds
12.Mithi PhaliSnow peaPAU, Ludhiana
13.Tarbedo SugarSnow peaPAU, Ludhiana
14.PED-2021-7Snow peaPAU, Ludhiana
15.Dwarf Grey SugarSnow peaPAU, Ludhiana
16.PED-2018-1Sugar Snap peaPAU, Ludhiana
17.Sugar DaddySnow peaUSA
18.PED-2021-1Snow peaPAU, Ludhiana
19.Sugar SnappySugar Snap peaUSA
20.PED-2021-5Sugar Snap peaPAU, Ludhiana
21.PED-2021-3Snow peaPAU, Ludhiana
22.PED-2018-6Sugar Snap peaPAU, Ludhiana
23.Namdhari-NASnow peaNamdhari Seeds
24.PED-2018-8Sugar Snap peaPAU, Ludhiana
25.Him Palam Mithiphali 1 (HPM-1)Snow peaCSKHPKV, Palampur
26.Him Palam Mithiphali 2 (HPM-2)Snow peaCSKHPKV, Palampur
27.Honey SnapSugar Snap peaUSA
28.Royal SnowSugar Snap peaUSA
Table 2. Mean squares of combined ANOVA of plant vigor, yield, and biochemical traits of 28 edible-podded pea genotypes evaluated in two different locations.
Table 2. Mean squares of combined ANOVA of plant vigor, yield, and biochemical traits of 28 edible-podded pea genotypes evaluated in two different locations.
TraitSource of Variation
MSg
(Df = 27)		MSe
(Df = 1)		MSgxe
(Df = 27)		MS
Error
NFA9.03 ***207.86 ***3.75 ***0.13
DTF23.70 ***1592.24 ***21.05 ***4.47
DTFF47.38 ***744.88 ***9.98 **4.48
DTPF22.22 ***1755.83 ***23.56 ***3.57
PH5968.72 ***15,246.63 ***232.27 ***7.00
NB4.957 ***9.00 ***0.02 ***0.007
NS5.80 ***3.06 ***0.60 ***0.03
PB44.34 ***117.17 ***7.80 ***0.20
PL12.77 ***56.47 ***1.99 ***0.03
NPPP48.71 ***151.24 ***9.52 ***0.26
TPW1537.31 ***1348.11 ***4.25 **2.13
Y6960.83 ***18,818.00 ***367.98 ***9.65
DM66.63 ***519.76 ***20.54 ***0.20
TS9.57 ***2.13 ***1.56 ***0.011
RS1.59 ***6.90 ***0.50 ***0.001
SP2.65 ***3.38 ***0.76 ***0.005
AA1068.10 ***393.11 ***176.65 ***1.45
F2.06 ***5.77 ***0.21 ***0.001
Note: ** = Significant at 0.01 probability level; *** = Significant at 0.001 probability level; NFA, node on which first flower appears; DTF, days to first flowering; DTFF, days to fifty percent flowering; DTPF, days to pod formation; PH, plant height (cm); NB, number of primary branches; NS, number of seeds per pod; PB, pod breadth (mm); PL, pod length (cm); NPPP, number of pods per plant; TPW, weight of ten pods (g); Y, yield per plant (g); DM, dry matter (%); SP, soluble protein content percentage on a fresh weight basis; TS, total sugar (%); RS, reducing sugar (%); AA, ascorbic acid mg/100 g of fresh weight; and F, fiber percentage on fresh weight basis.
Table 3. Variance components, h2b and GAPM for different traits.
Table 3. Variance components, h2b and GAPM for different traits.
Traitσ2gσ2pσ2eGCVPCVECVh2 (%)GAGAPM (%)
NFA2.224.572.3413.4719.3013.82492.1519.38
DTF1.5020.7010.881.626.024.0170.680.90
DTFF12.1723.0419.204.245.845.80525.226.35
DTPF0.6820.8520.171.045.765.6930.310.39
PH1935.722097.27161.5445.5047.3613.149287.0790.05
NB1.621.700.0738.4639.348.31952.5777.43
NS1.882.040.1622.2223.176.57922.7043.90
PB13.9316.472.5323.8225.8910.16857.0745.13
PL3.984.800.8325.1527.6411.46833.7447.14
NPPP15.1818.353.1820.4322.479.35837.2938.28
TPW508.34520.6312.8241.8942.396.519845.8985.27
Y2248.302464.24215.9446.1548.3214.309193.3090.81
DM19.5627.57.9428.2233.4617.98717.6849.03
TS3.083.410.3339.4441.4912.89903.4477.23
RS0.470.630.1452.0759.5728.95761.2493.74
SP0.821.000.1837.7241.5917.52821.770.46
AA343.16381.7738.638.8240.9413.029036.1875.81
F0.660.740.0861.3365.1421.97891.57118.93
Note: NFA, node on which first flower appears; DTF, days to first flowering; DTFF, days to fifty percent flowering; DTPF, days to pod formation; PH, plant height (cm); NB, number of primary branches; NS, number of seeds per pod; PB, pod breadth (mm); PL, pod length (cm); NPPP, number of pods per plant; TPW, weight of ten pods (g); Y, yield per plant (g); DM, dry matter (%); SP, soluble protein content percentage on a fresh weight basis; TS, total sugar (%); RS, reducing sugar (%); AA, ascorbic acid mg/100 g of fresh weight; and F, fiber percentage on fresh weight basis.
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Yadav, S.; Dhall, R.K.; Singh, H.; Kumar, P.; Sharma, P.; Kumar, P.; Kumari, P.; Rana, N. Comprehensive Genetic Analysis of Edible-Podded Pea Genotypes: Variability, Heritability, and Multivariate Approach Across Two Agro-Climatic Zones in India. Horticulturae 2025, 11, 22. https://doi.org/10.3390/horticulturae11010022

AMA Style

Yadav S, Dhall RK, Singh H, Kumar P, Sharma P, Kumar P, Kumari P, Rana N. Comprehensive Genetic Analysis of Edible-Podded Pea Genotypes: Variability, Heritability, and Multivariate Approach Across Two Agro-Climatic Zones in India. Horticulturae. 2025; 11(1):22. https://doi.org/10.3390/horticulturae11010022

Chicago/Turabian Style

Yadav, Saurabh, Rajinder Kumar Dhall, Hira Singh, Parteek Kumar, Priti Sharma, Pradeep Kumar, Priyanka Kumari, and Neha Rana. 2025. "Comprehensive Genetic Analysis of Edible-Podded Pea Genotypes: Variability, Heritability, and Multivariate Approach Across Two Agro-Climatic Zones in India" Horticulturae 11, no. 1: 22. https://doi.org/10.3390/horticulturae11010022

APA Style

Yadav, S., Dhall, R. K., Singh, H., Kumar, P., Sharma, P., Kumar, P., Kumari, P., & Rana, N. (2025). Comprehensive Genetic Analysis of Edible-Podded Pea Genotypes: Variability, Heritability, and Multivariate Approach Across Two Agro-Climatic Zones in India. Horticulturae, 11(1), 22. https://doi.org/10.3390/horticulturae11010022

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