Agromorphological traits contributing to the selection of high yielding Cowpea genotypes in Côte d'Ivoire

 Corresponding author: Deless Edmond Fulgence THIEMELE. Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Agromorphological traits contributing to the selection of high yielding Cowpea genotypes in Côte d’Ivoire Deless Edmond Fulgence THIEMELE *, Jean Simon Konan ASSOUMAN, Saraka Didier Martial YAO and Nafan DIARRASSOUBA Department of Genetics and Biochemistry, Genetics Research Unit, Peleforo GON COULIBALY University of Korhogo, Po Box 1328 Korhogo, Côte d’Ivoire. World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 Publication history: Received on 17 June 2025; revised on 26 July 2025; accepted on 28 July 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.27.1.2781 Abstract Cowpea (Vigna unguiculata L. Walp.) is an important household staple in sub-Saharan Africa (SSA), particularly in West Africa. The objective of this study was to identify the agromorphological traits that contribute to high yield for exploitable in breeding programmes in Côte d’Ivoire. A study was conducted at the Peleforo GON COULIBALY University Botanical Garden, in Côte d’Ivoire involving 32 cowpea accessions from the in-situ collection of Peleforo GON COULIBALY University. The accessions were evaluated in a Fisher block design with three replications on the basis of 16 quantitative variables. The results of the Principal Component Analysis (PCA) confirmed this morphological variability at 73.78%. Hierarchical Ascending Classification classified accessions into three distinct diversity groups according to yield. Group 1 includes accessions with high yield (3728.75 kg/ha), followed by group 2 (2693.93 kg/ha) and group 3 (1620.28 kg/ha). Accessions NFE011, NTE015, NTE02 and NKO03 from group 1 were identified as highyielding accessions, with respective mean yields of 3855.07, 3737.30, 3668.89 and 3653.74 kg/ha. Regression model indicates that traits including plant width, number of nodes per plant, pod size and number per plant and 100-seed weight were the most significant contributors to grain yield. These results suggest that the selection of high-yielding accessions could be improved by focusing on these specific agromorphological traits. Keywords: Agromorphological Traits; High Yield Cowpea Accessions; Vigna Unguiculata; Côte d’Ivoire 1. Introduction Cowpea, Vigna unguiculata (L.) Walp, is a legume of the Fabaceae family, native to sub-Saharan Africa (SSA) [1, 2]. It is widely cultivated in tropical regions and beyond [3]. It plays an important role in human nutrition, food security, and income generation for farmers and food vendors in the region [4]. Cowpea seeds are very rich in protein, minerals, and vitamins (folic acid and vitamin B). It is also involved in combating malnutrition [5]. Cowpea is also important in cropping systems due to its drought resistance [6] and as a nitrogen-fixing plant, it contributes to soil fertility restoration and is beneficial in crop associations with cereals [7]. More than 87% of African production comes from West Africa [8], highlighting its importance for many populations. Globally, the annual production of dry seeds is 28.35 million tonnes ; more than 97% of which is produced in Africa [8]. In Côte d'Ivoire, cowpea is mainly grown in savannah areas for its seeds, which are eaten as a dry vegetable. Young leaves are also eaten fresh. However, yields under traditional cultivation generally do not exceed 400 to 500 kg of seeds per hectare [9], with annual production around 38,127 tonnes, representing less than 1% of African production [8]. Despite its importance, cowpea remains a marginal crop [10]. World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2431 Several studies have been conducted on various aspects of cowpea, including growth characteristics and yield components of improved varieties [11, 12], intercropping with other legumes (groundnut-soybean) for improving soil fertility [13] and cultural techniques such as seeding density [14] have also been reviewed. Preliminary research work of [15, 16] on the morphological diversity of cowpea accessions, made it possible to have an in-situ collection of accessions conserved in the gene bank of Peleforo GON COULIBALY University. Their work also made it possible to identify the different modalities of the qualitative traits of the accessions in said collection. However, no predictive study on the yield of newly collected accessions from the UPGC gene bank has been carried out to date. Moreover, in a farming environment, cultivar differentiation is made through traits that are directly observable. Also, the identification of highyielding accessions through these observable traits could improve their selection conditions. The objective of this study was to identify the agromorphological traits that contribute to high yield for exploitable in breeding programmes in Côte d’Ivoire. 2. Material and methods 2.1. Experimental site The study was conducted at the Peleforo GON COULIBALY University Botanical Garden (9°27'28"N, 5°37'46"W) in Korhogo, northern of Côte d'Ivoire. The site is characterised by a tropical Sudano-Guinean climate, with two seasons, wet and dry. The seasons included a dry season from November to April and a rainy season from May to October, with mean annual rainfall ranging from 1100 to 1600 mm. The mean annual temperature is 27 °C, and the soils are Ferralitic [17]. 2.2. Treatments and design Thirty-two cowpea accessions, conserved at the Peleforo GON COULIBALY University genebank in Côte d’Ivoire, were used in this study (Table 1). The accessions were previously collected from the Poro, Bagoué, and Tchologo regions [15]. Table 1 Profiles and characteristics of cowpea accessions used in this study Accessions Origin Seed characteristics NBO04 Boundiali No coloration on the integument NOU06 Ouangolodougou White color with ovoid shape NTE02 Tengrela Dark red color NTE011 Tengrela Grey color with spots on the coat NTE013 Tengrela Dark red color NFE011 Ferkéssedougou Light red color NTE012 Tengrela Ochre color NTE015 Tengrela Couleur ocre, sans coloration sur le tégument NKO03 Korhogo White color NKO01 Korhogo No coloration on the integument NOU03 Ouangolodougou Dark red color with spots on the integument NKO02 Korhogo Light red color NFE012 Ferkéssedougou Light red color NBO011 Boundiali Light red color NTE03 Tengrela White color NSI01 Sinématiali No coloration on the integument NFE02 Ferkéssedouou Light red in color and ovoid in shape NKO08 Korhogo Black in color and globular in shape World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2432 NKN01 Kong Dark red color NOU012 Ouangolodougou Small, smooth seeds with ovoid or globular shape NOU05 Ouangolodougou Ochre color and globular shape NOU04 Ouangolodougou Ochre color and globular shape NBO012 Boundiali Small, smooth seeds with ovoid or globular shape NOU02 Ouangolodougou White color NTE014 Tengréla Small, smooth seeds with ovoid or globular shape NOU011 Ouangolodougou Light red color NSI02 Sinématiali No coloration on the integument NBO014 Boundiali Ochre-red color NKN02 Kong Ochre-red color NBO013 Boundiali Ochre-red color NKO011 Korhogo Ochre-red color NBO02 Boundiali White color N = Cowpea; BO = Boundiali; TE = Tengréla; OU = Ouangolodougou; KO = Korhogo; SI = Sinématiali; FE = Ferkessédougou; and KN = Kong. The accessions were sown using a Fisher block design, with three replicates. Each of the three blocks consisted of 32 rows, each 5 m long, with each row representing an accession composed of 10 individuals. The accessions were randomly assigned to the rows. Fifteen days after sowing, thinning was done to one plant per hill. Weeding was carried out manually and regularly whenever found necessary. 2.3. Data collection and analysis Data collection was done according to the variables defined in the Cowpea Descriptor Table [18]. A total of 16 quantitative variables were considered for this study (Table 2). Data analysis was done using descriptive statistics (minimum, maximum, mean, and coefficient of variation) to obtain coefficients of variation to demonstrate the variability of the various quantitative traits measured. Analysis of variance (ANOVA) was done at the 5% probability threshold, to verify existence of differences between accessions with respect to the traits studied. Where the effects were significant, a Turkey test was performed to classify the different groups. Correlations between variables were also estimated using Pearson's correlation coefficient. Principal Component Analysis (PCA) was used to assess the similarity between individuals to highlight homogeneous groups using relationships between variables. Hierarchical Ascending Classification (HAC) was used to classify the accessions into different homogeneous groups. A multiple linear regression analysis was performed to predict bulb yield based on agromorphological traits using the model: Y = A + b1X1 + b2X2 +….bn Xn Where: Y = Grain yield, A = constant, X = vegetative variable, and b = Coefficient. The collected data were analysed using XLSTAT-Pro version 2019. Table 2 Quantitative traits used for agromorphological characterisation of cowpea accessions used in this study N° Traits Code Scoring 1 Plant height (cm) PH Measurement of plant height at 6 weeks after sowing 2 Plant width (cm) PW Measurement of plant width at 6 weeks after sowing 3 Leaflet length (cm) Ll Measurement of leaflet length at 6 weeks after sowing 4 Leaflet width (cm) Lw Measurement of leaflet width at 6 weeks after sowing 5 Number of nodes NbNd Recorded 6 weeks after sowing. Mean of 10 randomly selected plants 6 Mean of the 10 longest mature pods from 10 randomly selected plants World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2433 Pod length (cm) PodL 7 Pod width (cm) PodW Mean of the 10 widthest mature pods from 10 randomly selected plants 8 Pod weight (g) PodWe Average measurement (weighing) carried out on three pods per plant after harvesting 9 Number of lodges per pod NbLod Record the number of lodges per pod after harvest on three pods per plant. 10 Number of seeds per pod NbSP Record number of seeds per pod per plant after harvest on three pods per plant. 11 Seed length (cm) SL Mean of 10 mature seeds excluding those from the extremities of pods after harvest 12 Number of pods per plant NbP Mean number of mature pods from 10 randomly selected plants 13 Hundred weight seeds (g) HWS After harvesting, weigh 100 seeds per plant 14 Grain yield (kg/ha) Yield After harvesting, weigh the seeds per plant to estimate the yield per hectare. 15 Time to first flower (day) TFF Date of first flowering 16 Maturation time (day) MaT First pod ripening date 3. Results 3.1. Quantitative traits Descriptive analysis showed that some quantitative traits exhibited significant variations between the cowpea accessions (Table 3). Traits such as plant width (PW), number of nodes (NbNd), leaflet length (Ll), leaflet width (Lw), time to first flower (TFF), maturation time (Mat), pod length (PodL), pod width (PodW), number of lodges per pod (NbLod), number of seeds per pod (NbSP), and seed length (SL), exhibited low variability, with coefficients of variation less than 20%. Furthermore, plant height (PH), number of pods per plant (NbP), pod weight (PodWe), hundred weight seeds (HWS), and grain yield (Yield) varied considerably, with coefficients of variation of 41.5, 48.6, 23.4, 24.5 and 49.9%, respectively. Plant height (PH) ranged from 6 to 39.9 cm and was more uniform, with a mean of 13.37 ± 5.55 cm. The number of pods (NbP) was very variable, ranging from 8 to 134, with a mean of 44.91 ± 21.83. Pod weight (PodWe), had values ranging from 1.2 to 3.4 g, plus a mean of 2.31 ± 0.54 g. The weight of 100 seeds (HWS), ranged from 6.8 to 19.5 g, with a mean of 11.17 ± 2.74 g. Grain yield in kg per hectare (kg ha-1) was extremely variable, ranging from 244.05 to 6283.68 kg ha1 with a mean of 2179.69 ± 1087.73 kg ha-1. Table 3 Descriptive statistics of quantitative traits considered in this study Traits Minimum Maximum Means ± Standard Deviation CV (%) PH (cm) 6 39.9 13.37 ± 5.55 41.5 PW (g) 24 56 40.14 ± 5.62 14 NbNd 5 13 8.69 ± 1.2 13.8 Ll (cm) 5 16.3 9.91 ± 1.89 19.1 Lw (cm) 2.3 9 6.27 ± 1.15 18.4 TFF (days) 40 79 46.39 ± 7.48 16.1 MaT (days) 56 91 65.70 ± 6.56 10 NbP 8 134 44.91 ± 21.83 48.6 World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2434 PodL (cm) 13 21 17.34 ± 1.62 9.3 PodW (cm) 5.59 9.71 7.38 ± 0.89 12 PodWe (g) 1.2 3.4 2.31 ± 0.54 23.4 NbLod 10 21 17.10 ± 2.12 12.4 NbSP 10 20 16.61 ± 2.18 13.2 SL (cm) 5.69 11.3 7.2 ± 1.07 14.8 HWS (g) 6.8 19.5 11.17 ± 2.74 24.5 Yield (kg ha-1) 244.05 6283.68 2179.69 ± 1087.73 49.9 PH: Plant height, PW: Plant width, Ll: Leaflet length, Lw: Leaflet width, NbNd: Number of nodes, PodL: Pod length, PodW: Pod width, PodWe: Pod weight, NbLod: Number of lodges per pod, NbSP: Number of seeds per pod, SL: Seed length, NbP: Number of pods per plant, HWS: Hundred weight seeds, Yield: Grain yield, TFF: Time to first flower, MaT: Maturation time, CV: Coefficient of Variation. Table 4 presents the mean values of various vegetative traits measured in different cowpea accessions. The results showed significant differences (P < 0.001) between the accessions for all traits studied. Accession NBO04 was distinguished by high leaflet length (Ll) and leaflet width (Lw), with values of 12.9 and 7.12 cm, respectively. Accession NSI02 displayed exceptionally high values for time to first flowering (TFF) and time to physiological maturity (MaT), with values of 78.250 and 89.250 days, respectively. Table 5 presents a detailed comparative analysis of the accessions, measuring key production variables. The results showed significant differences (P < 0.001) between the accessions for all production variable. Accession NFE011 had the highest grain yield of 3855.073 kg ha-1, and again the highest number of pods (76.750); and high seed weight. Accession NSI02, on the other hand, had the lowest values for number of pods (8) and yield (317.88 kg ha-1). Accession NKO04 had outstanding pod width (8.99 cm), the highest overall. In terms of 100 seed weight, NFE011 and NTE015 were among the highest, with 10.55 and 13.27 g, respectively. Table 4 Data for the cowpea vegetative traits evaluated in this study Accessions PH PW NbNd Ll Lw TFF MaT NBO011 16.7 abc 43.37 abc 9 abcdef 10.45 abc 7 abcd 44 abcd 63.75 ab NBO012 11.45 abc 41.05 abcd 9.25 abcdef 8.75 abc 5.62 def 45.25 abcd 64.5 ab NBO013 11 abc 38.35 abcd 8.25 bcdef 8.9 abc 5.37 def 46.5 abcd 65.25 ab NBO014 11.67 abc 39.5 abcd 8.25 bcdef 9.9 abc 5.62 def 44.25 abcd 64.5 ab NBO02 9.77 bc 36.12 abcd 7.25 f 8.82 abc 5.750 def 47.25 abcd 64.75 ab NBO04 13.87 abc 36.7 abcd 10.5 ab 12.9 ab 7.12 abcd 61.25 ab 82.25 a NFE011 12.95 abc 39.82 abcd 8.75 abcdef 10.2 abc 6.32 bcdef 41 d 57.5 b NFE012 13.35 abc 40.52 abcd 7.750 def 9.07 abc 6.6 abcdef 42.75 abcd 63.25 ab NFE02 12.12 abc 39.72 abcd 8.75 abcdef 8.35 bc 5.8 def 45.5 abcd 65.25 ab NKN01 13.77 abc 41.07 abcd 7 f 9.92 abc 6.6 abcdef 46 abcd 65 ab NKN02 8.125 c 34.87 bcd 7.75 def 8.75 abc 5.37 def 47.25 abcd 66.75 ab NKO01 28 ab 41.72 abcd 10.75 a 8.67 abc 5.1 ef 58.25 abc 79.25 a NKO011 13.05 abc 40.37 abcd 9.75 abcde 9.05 abc 6.12 bcdef 44 abcd 63.5 ab NKO02 13.72 abc 44.75 abc 9.25 abcdef 8.35 abc 5.95 cdef 43.75 abcd 64 ab NKO03 10.6 abc 32.52 cd 9.75 abcde 11.62 abc 7.15 abcd 41.75 abcd 57.5 b NKO08 11.37 abc 36.72 abcd 9 abcdef 11.12 abc 7.85 ab 41.75 bcd 63.75 ab NOU011 9.25 c 36.92 abcd 8.5 abcdef 8.17 bc 5.8 def 45.5 abcd 64.75 ab World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2435 NOU012 11.37 abc 40.87 abcd 10 abcd 9.5 abc 6.1 bcdef 46.75 abcd 65 ab NOU02 10.32 abc 41.62 abcd 8.5 abcdef 9.62 abc 6.1 bcdef 44.5 abcd 63 ab NOU03 17.82 abc 47.02 ab 9 abcdef 9.42 abc 6.27 bcdef 41.5 bcd 63.25 ab NOU04 11.37 abc 35.1 abcd 8.25 bcdef 10.15 abc 6.72 abcdef 42.25 abcd 64.25 ab NOU05 13.55 abc 39.05 abcd 8 cdef 10 abc 6.85 abcde 41.25 cd 63 ab NOU06 8.87 c 44.6 abc 8.5 abcdef 13.07 ab 7.85 ab 50 abcd 64 ab NSI01 33.475 a 42.45 abcd 10.25 abc 8.77 abc 5.02 f 50 abcd 70 a NSI02 16.97 abc 30.47 d 7.5 ef 6.27 c 2.9 g 78.25 a 89.25 a NTE011 10.07 abc 42.95 abcd 7.75 def 12.47 ab 7.67 abc 41.75 abcd 63 ab NTE012 13.57 abc 44.2 abc 8.75 abcdef 9.97 abc 6.25 bcdef 45.25 abcd 64.75 ab NTE013 14.15 abc 47.8 a 8.5 abcdef 10.12 abc 6.55 abcdef 42.5 abcd 63.5 ab NTE014 10.62 abc 41.4 abcd 8.5 abcdef 9.45 abc 5.8 def 45.5 abcd 65 ab NTE015 11.17 abc 38.55 abcd 8.75 abcdef 15.25 a 6.77 abcdef 41.25 cd 58.25 b NTE02 11.3 abc 45.02 abc 7.75 def 11 abc 8.27 a 41 d 63 ab NTE03 12.42 abc 39.3 abcd 8.5 abcdef 9.07 abc 6.35 bcdef 46.75 abcd 67.25 ab Pr > F < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 PH: Plant height, PW: Plant width, Ll: Leaflet length, Lw: Leaflet width, TFF: Time to first flower, MaT: Time to first pod maturation, NbNd: Number of nodes per plant. Means followed by the same letter within a column are not significantly different at P < 0.05. World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2436 Table 5 Mean values of agronomic traits evaluated in cowpea accessions used in this study Accessions NbP PodL PodW PodWe NbLod NbSP SL HWS Yield NBO011 55.5 abcd 17.87 cdef 7.05 defgh 1.95 fghijkl 17.25 abcd 17 abcd 6.63 abc 9 abc 2319.08 abcdef NBO012 45.25 abcde 18 bcdef 6.38 gh 2.15 efghijk 18.5 a 17.5 abc 6.47 abcd 9.3 abc 2006.46 abcdef NBO013 44.5 abcde 17 defgh 6.50 fgh 1.82 ghijkl 17.5 abc 16.75 abcd 6.33 bcd 8.75 bc 1696.49 bcdef NBO014 55.5 abcd 16.5 defghi 6.55 efgh 1.72 ijkl 17.250 abcd 16.75 abcd 6.42 bcd 7.575 c 1962.34 abcdef NBO02 30 bcde 18 bcdef 6.80 efgh 1.9 fghijkl 17.500 abc 16.75 abcd 6.39 bcd 8.55 bc 1102.83 def NBO04 49 abcde 16.8 defgh 8.99 a 2.97 abc 14.500 cde 13.5 de 10.78 a 17.67 a 3068.14 abcd NFE011 76.75 a 18.42 bcde 7.07 defgh 2.47 abcdefgh 19 a 18 ab 6.92 abcd 10.55 abc 3855.073 a NFE012 40 abcde 18.57 abcd 7.24 bcdefgh 2.55 abcdefg 19.25 a 18.25 ab 6.82 abcd 10.4 abc 2014.04 abcdef NFE02 33.25 abcde 17.2 cdefg 7.08 defgh 2.55 abcdefg 18 a 17.5 abc 6.91 abcd 10.17 abc 1593.1 cdef NKN01 57.5 abcd 15.5 ghi 7.71 abcdefg 1.625 kl 16.5 abcd 16.25 abcd 6.44 abcd 10.5 abc 2554.25 abcde NKN02 20.25 de 17.45 cdefg 7.06 defgh 2.22 defghijk 17.5 abc 17.25 abc 6.65 abcd 10.17 abc 931.29 ef NKO01 34.75 abcde 15.95 fghi 7.69 abcdefg 3.05 abc 12.25 e 11.75 e 10 a 19.37 a 2076.26 abcdef NKO011 36 abcde 16.5 defghi 6.748 efgh 1.67 jkl 16.5 abcd 16.5 abcd 6.345 cd 8.76 bc 1414.55 def NKO02 44.5 abcde 17.22 cdefg 7.32 bcdefgh 2.45 bcdefghi 18.5 a 18.25 ab 6.728 abcd 9.95 abc 2133.98 abcdef NKO03 71 ab 18.4 bcde 7 efgh 2.32 cdefghijk 19.25 a 18.75 a 6.793 abcd 10.3 abc 3653.74 abc NKO08 32.75 abcde 17.02 defgh 7 efgh 2.8 abcde 17.25 abcd 16.5 abcd 7.16 abcd 10.9 abc 1576.22 cdef NOU011 24.75 cde 18.2 bcde 6.99 efgh 2.47 abcdefgh 17.75 ab 17.5 abc 6.77 bcd 10.35 abc 1200.6 def NOU012 75.25 a 16.37 efghi 6.36 gh 1.87 ghijkl 17.25 abcd 17.25 abc 6.35 bcd 8.52 bc 3021.71 abcde NOU02 43.25 abcde 17.1 defg 6.98 efgh 2.1 efghijkl 18.25 a 17.75 ab 6.70 abcd 9.32 abc 1863.59 abcdef NOU03 44 abcde 17.37 cdefg 7.84 abcdef 2.11 efghijkl 14.75 bcde 14.75 bcde 8.05 abcd 14.79 ab 2492.74 abcde NOU04 26.5 bcde 19.25 abc 6.77 efgh 2.4 bcdefghij 18.5 a 18 ab 6.48 abcd 11.05 abc 1396.48 def NOU05 34.75 abcde 18.5 bcd 7.20 cdefgh 2.47 abcdefgh 18 a 17.5 abc 6.64 abcd 10.05 abc 1631.96 cdef NOU06 48 abcde 20.62 a 8.60 ab 2.95 abcd 17.75 ab 17.5 abc 7.76 abcd 13.12 abc 2967.69 abcde NSI01 26.5 bcde 14.62 ij 7.26 bcdefgh 2.07 efghijkl 14.25 de 14 cde 8.35 abc 12.22 abc 1251.29 def World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2437 NSI02 8 e 13.21 j 7.87 abcde 1.67 jkl 12.75 e 12.25 e 7.85 abcd 12.07 abc 317.88 f NTE011 41 abcde 18.37 bcde 8.86 a 3.12 ab 18 a 18 ab 7.56 abcd 13.22 abc 2582.64 abcde NTE012 34.5 abcde 17.3 cdefg 7.47 bcdefg 2.42 bcdefghi 18.75 a 18.25 ab 6.89 abcd 11.15 abc 1862.51 abcdef NTE013 42.25 abcde 20.07 ab 8.41 abcd 2.62 abcdef 17.25 abcd 16.250 abcd 7.858 abcd 13.15 abc 2424.078 abcde NTE014 69 abc 16.62 defghi 6.05 h 1.37 l 17.75 ab 17.5 abc 6.21 d 7.6 c 2427.46 abcde NTE015 66 abc 17.77 cdef 8.55 abc 3.200 a 17 abcd 16.25 abcd 7.31 abcd 13.27 abc 3737.3 ab NTE02 62.5 abcd 18.07 bcde 8.85 a 2.97 abc 19.5 a 19 a 7.09 abcd 11.5 abc 3668.89 abc NTE03 64.5 abcd 15 hij 7.78 abcdef 1.8 hijkl 13.25 e 12.5 e 8.55 abc 14.05 ab 2945.44 abcde Pr > F < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 < 0.0001 PodL: Pod length, PodW: Pod width, PodWe: Pod weight, NbLod: Number of lodges per pod, NbSP: Number of seeds per pod, SL: Seed length, NbP: Number of pods per plant, HWS: Hundred weight seeds, Yield: Grain yield. Means followed by the same letter within a column are not significantly different at P < 0.05 World Journal of Advanced Research and Reviews, 2025, 27(01), 2430-2443 2438 3.2. Correlation between the traits Positive and highly significant correlations (P<0.0001) were observed between the measured variables. Plant width (PW) had a strong correlation with Lw (r = 0.708) and MaT (r = 0.950). On the other hand, the number of nodes (NbNd) showed a moderate correlation with Lw (r = 0.566) and TFF (r = 0.564); but a more significant one with MaT (r = 0.675). The number of pods per plant (NbP) showed positive correlations with PodL (r = 0.528), and PodW (r = 0.535) correlated with PodWe (r = 0.712). The number of lodges per pod (NbLod) also showed significant positive correlations with PodL (r = 0.684), with seed length (r = 0.758) and with hundred weight seeds (HWS) (r = 0.690). Grain yield had a high correlation with PodWe (r = 0.712), with SL (r = 0.684), HWS (r = 0.758) and number of seeds per pod (r = 0.615). 3.3. Morphological diversity The results of the principal component analysis (PCA) revealed that the first three principal axes explained a large portion of the total variance in the data, accumulating up to 73.784% (Table 6). Axis 1, which alone explained 37.459% of the variance, was primarily positively correlated with variables including time to first flower (TFF), time to physiological maturity (MaT), seed length and 100 seed weight (HWS). It also showed significantly negative correlations with the number of lodges per pod (NbLod) and the number of seeds per pod (NbSP). Table 6 Eigenvalue matrix and correlations between variables and axes of PCA in plane 1-2 Axis 1 Axis 2 Axis 3 Eigen value 5.993 3.969 1.843 Total variance (%) 37.459 24.803 11.522 Cumulative variance (%) 37.459 62.262 73.784 Traits Correlations between traits and axes PH 0.445 0.078 0.494* PW -0.108 0.362 0.363 NbNd 0.460 0.198 0.455 Ll -0.109 0.815** -0.067 Lw -0.396 0.763** -0.076 TFF 0.869** -0.111 -0.126 MaT 0.903** -0.144 -0.158 NbP -0.209 0.511 0.710** PodL -0.485 0.517 -0.367* PodW 0.480 0.710** -0.320* PodWe 0.297 0.713** -0.454* NbLod -0.890** 0.179 -0.173 NbSP -0.902** 0.158 -0.162 SL 0.936** 0.285 -0.111 HWS 0.869** 0.404 -0.144 Yield 0.025 0.819** 0.415 PH: Plant height, PW: Plant width, Ll: Leaflet length, Lw: Leaflet width, NbNd: Number of nodes, PodL: Pod length, PodW: Pod width, PodWe: Pod weight, NbLod: Number of lodges per pod, NbSP: Number of seeds per pod, SL: Seed length, NbP: Number of pods per plant, HWS: Hundred weight seeds, Yield: Grain yield, TFF: Time to first flower, MaT: Maturation time Values in bold are correlations significant at the 1 and 5% threshold: **: Significant at 1 % level of probability and, *: Significant at 5 % level of probability. Axis 2 which explained 24.803% of the variance, was strongly positively correlated with leaflet length (Ll), width (Lw), grain yield, pod weight (PodWe) and pod width (PodW). Axis 3 explained 11.522% of the variance, which showed