Comprehensive Analysis of Combining Ability and Genetic Parameters for Green Fodder Yield and Quality Traits in Indian Cowpea (Vigna unguiculata L.)

doi:10.21203/rs.3.rs-4916238/v1

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Comprehensive Analysis of Combining Ability and Genetic Parameters for Green Fodder Yield and Quality Traits in Indian Cowpea (Vigna unguiculata L.)

https://doi.org/10.21203/rs.3.rs-4916238/v1

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Target traits in hybrid breeding programs are crucial as they are highly responsive to gene action and combining ability. The line × tester method aids in understanding the genetic interactions influencing these traits, enabling the development of superior hybrids by selecting parent combinations that optimize heterosis or hybrid vigor. The study involved 23 forage cowpea genotypes and 3 testers, resulting in 69 F1 hybrids produced at Tamil Nadu Agricultural University, Coimbatore. The experiment was conducted over two cropping seasons (2023–2024) at the New Area Farm Experimental Station. A Randomized Complete Block Design (RCBD) with three replications was employed. The line × tester interaction was highly significant for all traits, indicating the impact of additive and non-additive gene expression variations. Notably, specific genotypes displayed significant General Combining Ability (GCA) effects: GETC 21 for Crude Protein (CPR), GETC 49 for Number of Leaves (NOL) and CPR, and CL 348 for Dry Matter Yield (DMY) and Crude Fiber (CFR). Additionally, hybrids demonstrated substantial Specific Combining Ability (SCA) effects, particularly CS 98 × CO 9 and CL 321-1 × CO(FC) 8 for DMY, and GETC 49 × CO(FC) 8 and GETC 49 × CO 9 for days to fifty percent flowering (DFF). Mid-parent heterosis was evident, with IFC 9402 × CO(FC) 8 showing the highest heterosis for plant height and FD 1052 × TNFC0926 for CPR. These results underscore the importance of selecting lines and testers with high GCA and hybrids with high SCA to enhance Green Forage Yield (GFY), DMY, CPR, CFR, and NOL in forage cowpea. This approach promises the development of new, high-yielding, and nutritionally superior cowpea varieties.

Forage Cowpea

Genetic Diversity

Combining Ability

Mid-parent Heterosis

Hybrid

Cowpea (Vigna unguiculata (L.) Walp.; 2n = 2x = 22) Versatile short-duration dual-purpose (grain and fodder) leguminous crop with a genome size of ~ 620 million base pairs(1). It is widely grown in the semi-arid tropics of Africa, Latin America, and South Asia, as well as in other tropical regions between 40°N and 30°S at altitudes below 2000m (1). In India, cowpea is mainly cultivated in rice fallows in the states of Odisha, Madhya Pradesh, Chhattisgarh, Maharashtra, Andhra Pradesh, Karnataka, and Tamil Nadu. In 2022, the global total area harvested and yielded, of cowpea was 15.1 million hectares and 8.9 million tonnes(2). The fresh biomass of cowpea contains 20–24% crude protein, 43–49% neutral detergent fiber, 34–37% acid detergent fiber, 23–25% cellulose, and 5–6% hemicellulose on a dry matter basis. Additionally, cowpea fodder has a digestibility rate of over 70% (3). Green fodder productivity ranges from 25 to 45 tonnes per hectare, with a seed production potential of 3 quintals per hectare. Nationally, the crop yields approximately 0.9 million tonnes of seed and 5 million tonnes of fodder (3). However, at the current growth rate of forage resources, we are facing an 18.4% deficit in green fodder and a 13.2% deficit in dry fodder. To bridge this gap, the green forage supply must increase by 1.69% annually (4). The solution to the problem of this demand-supply gap lies in saving maximum fodders produced, both spatially and temporally, through the identification of new forage resources, including cowpea. Genetic variability, heritability, general combining ability, specific combining ability, and genetic advance are the important genetic components that provide useful information for fodder cowpea breeders to select the suitable breeding procedure for developing improved cross(5–8). To create a breeding program for the exploitation of heterosis in hybrid crop development or variety improvement, selecting appropriate parental genotypes is critical. The success of a breeding program depends on the ability to produce hybrids that exhibit desired traits. The concept of combining ability is a useful objective in the breeding processes because it helps to compare the performance of lines in hybrid combinations which can be used to evaluate how well the different cultivars combine, and which combinations inherit desired genes to their progeny effectively. GCA is the average performance- of a line in hybrid combinations. It is an indicator of additive gene action. SCA (specific combining ability) is the performance of particular hybrid combinations. It is the measure of non-additive gene action. The heterosis phenomenon was studied in many investigations by comparing hybrid progeny with both the mid-parent average and the better parent in different traits. They have also analyzed GCA and SCA as the mechanism to understand the genetic contributions of different parent lines. The findings show that heterosis is significant for most of the traits studied. These findings invariably show that hybrids usually perform better than both the average and the best-performing parent(9–12). A recent study establishes that the extent of SCA variance was more than GCA variance regarding most of the characters except days to maturity, dry matter content, and crude protein content. Another study established that good general combining ability effects, The parents FD 2288, IFC 95101, and CO 5 were recognized as good general combiners of fodder yield and yield contributing characters, It is possible to assess the genetic factors that are affecting fodder yield and fodder quality attributes in elite parents and their crossbreeds, Based on a line × tester mating design(12–15). The major objectives of the present investigation were − 1. Evaluate general and specific combining abilities of forage cowpea genotypes for fodder yield and quality traits.2. Determine heterosis for fodder yield and quality traits in cowpea hybrids.3. Identify genetic variation and heritability for earliness, fodder yield, and quality traits in cowpea. Analyze correlations among fodder yield and quality traits for improved selection in breeding.

The experiment was conducted with 23 forage cowpea (Vigna unguiculata) genotypes and 3 testers collected from diverse sources. The place of collection and the characteristics of the genotypes are given in Table 1. Selfed seeds of parents and sixty-nine F₁ hybrids were obtained from the Department of Forage Crops, Tamilnadu Agricultural University, Coimbatore, India. The experiment was conducted for two cropping seasons 2023 to 2024, at the New Area Farm (TNAU, Coimbatore) Experimental Station located at a latitude of 11°00′58"N and longitude of 76°58′31"E. The genotypes were crossed using Kempthorne's line × tester. The selfed seeds of the 26 parents and their F₁ hybrids were planted following a Randomized Complete Block Design (RCBD) in three replications. Individual genotypes in each replication were raised in two rows, each 4 meters in length, with a spacing of 30 x 10 cm. The soil type is loam with a mixture of clay, sand, and silt. We followed the recommended agricultural practices of fertilization, irrigation, and weed management to ensure that the plants produced the highest yield.

2.1Phenotyping:

Guarded plants were randomly selected from each replication at 50% flowering for consistency and reliability (except the border plants). We recorded the phenotypic traits by measuring plant height (PH), from the base to the tip of the tallest stem, and counting the number of primary branches per plant (NPB), which are the branches emerging directly from the main stem. We also recorded the total number of leaves per plant. Green fodder yield per plant (GFY) is the fresh weight of the plant material. The leaf-stem ratio (LSR) is calculated by weighing and comparing the leaves and stems. Leaf length (LL) and leaf width (LW) were also measured.

2.2 Data analysis

The data were analyzed using ANOVA methods according to Steel and Torrie’s guidelines to find significant differences among the cowpea genotypes. The line × tester analysis with parent, general combining ability (GCA), and specific combining ability (SCA) effects were calculated based, on used R version 4.0.3 with the agricolae package(16). Using R version 4.0.3, plant breeding research can greatly benefit from Pearson's correlation, path analysis, and cluster analysis. Pearson's correlation measures the linear relationship between two variables, providing insights into potential associations among breeding traits using the metan package(17). Path analysis detects deeper by partitioning the direct and indirect effects of multiple predictors on an outcome, clarifying their causal pathways. Cluster analysis categorizes similar observations into groups, enabling researchers to identify and evaluate genetically similar breeding lines. Heatmaps were created using ggplot2 (18). These statistical tools collectively enhance the depth and precision of data analysis in cowpea breeding studies.

The nutritional content analysis was conducted in the laboratories of the Department of Forage Crops, TNAU, Coimbatore, India, following the standard Kjeldahl method, which involves digesting the sample in acid to convert nitrogen into ammonium sulfate to determine the crude protein content. Crude fiber content (CFB) and crude fat content (CFT) were determined through standard laboratory methods, such as the Van Soest method and Soxhlet extraction, respectively.

3.1 Cluster Analysis fodder cowpea genotype

Thirteen study traits were used to perform the cluster analysis of twenty-six parental genotypes in the Jaccard dissimilarity coefficient measures the dissimilarity between two genotypes by comparing the presence and absence of traits. This dissimilarity is used to form a dendrogram when applying UPGMA (Unweighted Pair Group Method with Arithmetic Mean) clustering. The resulting dendrogram (Fig. 1) visually represents the hierarchical relationships among the twenty-six genotypes. Three clusters were identified in the dendrogram among the twenty-six parental genotypes. Six genotypes made up Cluster I, which was separated into two subclusters. The first subcluster included the genotype IFC 9402, while the second subcluster comprised CL321-1, N311, IFC9304, FD719, and GETC6. Cluster II contained only one genotype, GETC40. Cluster III included nineteen genotypes, which were separated into two subclusters. The first subcluster consisted of TNFC0926, CO(FC)8, and CO9, while the second subcluster included FD1067, K − 13 -CP42, EC 240806, GETC 21, GETC 23, GETC 41, EC 467380, FD 1259, CS 98, GETC 49, GETC 18, GETC 15, FD 711, FD 1052, CL 348 and GETC10. CoFC 8, CO-9, and TNFC0926 are closely clustered but still exhibit some variation across traits like DMY, GFY, and PH.

3.2 Analysis of variance

The ANOVA results for fodder yield contributing characters across two growing seasons are presented in Table 2. Most traits were significantly affected by genotype, parents, and crosses, with notable exceptions such as the genotype effects on LW and LSR in Season 2, and parent effects on the number of leaves NOL and CFT in Season 1. Crosses' effects on ash content ASH and LSR were not significant in Season 1, as well as LW and LSR in Season 2. Lines showed significant effects for all characters except ASH in both seasons and LL in Season 2. Testers significantly influenced all traits except for DMY, NOL, LL, LW, CPR, CFB, and LSR in both seasons, and also GFY, PH, and ASH in the second season. Additionally, various interactions of parents x crosses and lines x testers significantly influenced most characters during the study.

3.3 Mean performance among all parental genotypes and F₁ crosses

Table 3 shows significant variability in fodder yield and quality traits among the 23 parental lines and three testers of cowpea. K-13-CP42 had the highest DMY in Season 1 with 47.94, while FD 1259 performed well in both seasons with 44.18 and 37.38. The average yield for lines was 36.17 in Season 1 and 33.17 in Season 2, with tester TNFC0926 having the highest yield in Season 1 at 44.30, but all testers saw a decrease in Season 2, averaging 30.05. For DFF, the line average was 56.56 days, with tester averages slightly varying between 56.57 and 56.4 days. Genotypes such as CL 348 and CL 321-1 had the shortest DFF, while GETC 41 and GETC 49 exhibited the longest. GETC 23 had the highest GFY with 277.54 and 224.07, while CL 321-1 had the lowest at 219.33 and 126.59. The average GFY for all lines was 241.74 in the first year and 194.39 in the second year, with testers averaging 252.56 and 236.22. For PH, GETC 40 had the highest average height with 95.3 and 60.26, and GETC 18 the lowest with 84.42 and 30.14. The average PH for all lines was 87.78 in the first year and 63.1 in the second year, while testers averaged 87.9 and 73.38. FD 1052 had the highest NOL at 75.25 and 62.29, while CL 321-1 had the lowest with 61.38 and 38.6. The average NOL for all lines was 69.48 and 51.66, with testers averaging 64.41 and 57.08. The results showed that for LL, EC 240806 had the highest average in season 1 (8.29) while FD 1067 had the highest in season 2 (8.5). In LW, CO(FC) 8 had the highest averages in both seasons (9.24 and 8.92). ASH content was highest in TNFC0926 for both Seasons (7.94 and 6.98). For CPR, FD 1052 had the highest in season 1 (23.36) and EC 240806 in season 2 (24.95). In terms of CFB, GETC 15 had the highest in season 2 (25.34), while FD 1052 led in season 1 (23.36). CFT was highest in CO 9 in season 2 (26.46) and GETC 15 in season 1 (7.98). NPB showed CO(FC) 8 leading in season 1 (2.4) and GETC 23 in season 2 (2.74). LSR was highest in GETC 49 in season 2 (0.82) and GETC 18 in season 1 (0.64). The overall line averages indicated significant variability among genotypes, with the average values reflecting substantial differences across traits and seasons.

The performance of the 69 hybrids across 13 fodder yield and quality traits was evaluated over two years, as shown in Table 4. The mean Dry Matter Yield (DMY) increased from 46.44 g/plant in the first year to 56.36 g/plant in the second year, with the hybrids GETC 10 x TNFC0926 and CS 98 x TNFC0926 showing the highest DMY at 69.0 g/plant and 67.49 g/plant, respectively. The Days to 50% Flowering (DFF) remained stable, as evidenced by the cross FD 1052 x CO 9, which exhibited flowering times of 54.2 days in Year 1 and 55.3 days in Year 2. Despite a decrease in the overall average Green Fodder Yield (GFY) from 294.49 g/plant in Year 1 to 279.82 g/plant in Year 2, the cross FD 711 x CO(FC) 8 achieved the highest GFY in Year 2. Plant Height (PH) varied significantly, with the highest PH recorded at 98.4 cm for IFC 9402 x TNFC0926, though the average PH dropped from 90.16 cm in Year 1 to 68.09 cm in Year 2. The number of leaves per plant (NOL) increased in Year 2, particularly in the cross FD 1259 x CO(FC) 8, which produced 74.9 leaves per plant. Leaf Length (LL) and Leaf Width (LW) remained stable across the study, with CL 348 x CO 9 maintaining the longest leaf length at 10.3 cm, and CL 348 x TNFC 0926 having the widest leaf width at 8.3 cm. Ash content remained consistent at around 8%, ensuring a stable nutritional quality. Crude Protein Content (CPR) increased in Year 2, with the cross GETC 21 x TNFC 0926 reaching 21.7%. Crude Fiber Content (CFB) levels were stable, with GETC 10 x CO 9 maintaining high levels at 19.7%, while Crude Fat Content (CFT) decreased from an average of 4.63% in Year 1 to 3.59% in Year 2. The number of Primary Branches (NPB) and Leaf-Stem Ratio (LSR) remained consistent, with GETC 10 x TNFC 0926 exhibiting an LSR of around 0.65.

NPB-Number of primary branches per plant, PH-Plant height (cm), NOL-Number of leaves per plant, CFB-Crude fiber content (%), CFT-Crude fat content (%), DMY-Dry matter yield per plant (g), DFF-Days to 50% flowering, CPR-Crude protein content (%), GFY-Green fodder yield per plant (g), LSR- Leaf stem ratio, LL- Leaf length(cm), and LW- Leaf width(cm).

3.4 General combining ability

Several genotypes exhibited high General Combining Ability (GCA) for one trait and low GCA for other traits as presented in Table 5. For GETC 21, the maximum negative GCA effect in Y1 was − 15.0 for Dry Matter Yield and − 0.10 for Leaf Stem Ratio, while it had a very high positive GCA effect for Leaf Width at 0.84. In Y2, GETC 21 continued to exhibit very significant effects with the GCA least value for Number of Leaves (NOL) at -22.7 and recording the highest positive effect for Crude Protein (CPR) at 2.4. GETC 49 was outstanding for many traits in the two years. It had negative GCA effects of -17.2 for Number of Leaves (NOL), -0.99 for Leaf Length (LL), and − 0.85 for Leaf Width (LW) while having positive GCA effects of 1.5 for Crude Protein (CPR) and 1.49 for Number of Primary Branches (NPB). DMY had the most negative GCA effects, -21.0, followed by Green Fodder Yield (GFY), -89.8, LL, -1.74, LW, -0.21, Ash Content − 0.66, and NPB was the only one for which the GCA effect was positive, 1.63. The other promising line showing significant GCA effects was CL 348. In Y1, it had high positive GCA effects for Plant Height (PH) at 7.21 and Crude Fibre (CFB) at 5.0 while having a negative GCA effect for NPB at -1.48. In Y2, CL 348 showed the most negative GCA effects for PH -29.7, CPR − 3.1, and NPB at -1.63, while it had a positive GCA effect for LW at 0.75. FD 1067 expressed high positive GCA effects on PH and Ash Content, 21.6 and 0.44, respectively, but negatively on LSR with a value of -0.07. For Y1, FD 1067 had a positive effect for CFT, while EC 240806 had a high positive GCA effect for Ash Content of 0.36 in Y1, and for CFB of 2.5 in Y2. The analysis of the testers shows that for CO(FC) 8, the highest positive significant GCA value is for DMY Y2, with 0.43, and the highest negative significant GCA value is for DFF Y1, with − 1.127. For CO 9, the highest positive significant GCA value is for DMY Y2, with 1.46, and the highest negative significant GCA value is for GFY Y2, with − 6.3. For TNFC0926, the highest positive significant GCA value is for PH Y1, with 1.8, and the highest negative significant GCA value is for DMY Y2, with − 1.8.

3.5 Specific combining ability

The SCA effects for 69 fodder cowpea hybrids, analyzed for 13 characters over two years, are presented in Table 6 Significant and non-significant SCA effects were observed across the 13 traits analyzed. Traits such as DMY, DFF, GFY, PH, leaf length, leaf width, CPR, CFR, CFT, and LSR exhibited varying degrees of SCA effects among the hybrids. However, none of the hybrids showed significant SCA effects for the NPB and the NOL. For DMY, hybrids CS 98 x CO 9 and CL 321-1 x CO(FC) 8 showed the highest positive SCA effects with values of 10.65 and 8.66 respectively, while K – 13 -CP42 x CO 9 and IFC 9304 x TNFC0926 exhibited the maximum negative SCA effects with values of -10.25 and − 9.03. In terms of Days to fifty flowerings, hybrids GETC 49 x CO(FC) 8 and GETC demonstrated superior SCA with DFF1 values of 1.227,1.205, and DFF2 of 4.675 and 4.25 respectively, whereas GETC 49 x TNFC0926 showed the maximum negative SCA effects with DFF1 -2.432 and DFF2 -8.925. For green fodder yield, no genotypes were found with significant positive SCA effects across both years, while GETC 23 x CO(FC) 8 exhibited maximum negative, effects with GFY1 -25.351 and GFY2 -34.89. In terms of plant height, hybrids CL 348 x CO 9 and IFC 9304 x TNFC0926 showed positive SCA effects with PH1 4.647, PH2 15.955, and PH1 -4.857, PH2 12.555 respectively, while CL 348 x TNFC0926 and IFC 9304 x CO(FC) 8 had maximum negative SCA effects with PH1 -0.17, PH2 -12.753 and PH1 -1.358, PH2 -10.871. In terms of leaf length, IFC 9402 x TNFC0926 and FD 1259 x CO(FC) 8 showed the highest positive SCA effects with LL1 0.887, LL2 1.22 and LL1 0.581, LL2 1.081 respectively, while IFC 9304 x CO 9 and IFC 9402 x CO 9 exhibited maximum negative SCA effects with LL1 -0.645, LL2 -1.283 and LL1 -0.867, LL2 -0.929. For leaf width, EC 240806 x CO 9 and FD 1259 x CO 9 showed the highest positive SCA effects with LW1 1.035, LW2 0.308 and LW1 0.811, LW2 -0.13, while FD 711 x TNFC0926 and IFC 9304 x CO(FC) 8 had maximum negative SCA effects with LW1 -1.019, LW2 0.242 and LW1 -0.828, LW2 -0.154. For crude protein, hybrids N 311 x CO 9 and FD 1052 x CO 9 demonstrated superior SCA effects with CPR1 -0.127, CPR2 1.061 and CPR1 0.226, CPR2 0.977 respectively, while CS 98 x TNFC0926 and FD 1052 x CO(FC) 8 showed maximum negative SCA effects with CPR1 -0.077, CPR2 -1.152 and CPR1 -0.041, CPR2 -1.211. For crude fiber, hybrids GETC 10 x CO(FC) 8 and FD 1259 x CO(FC) 8 showed the highest positive SCA effects with CFR1 0.75, CFR2 0.52 and CFR1 0.621, CFR2 0.38, while CS 98 x TNFC0926 and IFC 9402 x CO 9 exhibited maximum negative SCA effects with CFR1 -1.27, CFR2 -1.31 and CFR1 -0.81, CFR2 -0.74. For crude fat, hybrids FD 711 x TNFC0926 and EC 240806 x CO 9 showed positive SCA effects with CFT1 0.713, CFT2 -0.536 and CFT1 0.99, CFT2 -0.02, while FD 1259 x CO 9 and FD 1067 x CO 9 had maximum negative SCA effects with CFT1 -0.793, CFT2 -0.002 and CFT1 -0.68, CFT2 -0.38. For leaf stem ratio, hybrids IFC 9304 x CO 9 and GETC 6 x TNFC0926 showed the highest positive SCA effects with LSR1 0.164, LSR2 0.007 and LSR1 0.153, LSR2 -0.015, while N 311 x CO(FC) 8 and FD 1067 x CO(FC) 8 exhibited maximum negative SCA effects with LSR1 -0.129, LSR2 0.007 and LSR1 -0.13, LSR2 -0.01. This two-year study of line x tester shows that both additive and non-additive variances were present for most characters. However, additive genes were more important than dominant genes because the variance due to GCA was higher than that due to SCA.

3.6 Analysis of Mid-Parent Heterosis

Analysis of Mid-Parent Heterosis We calculated the heterosis for sixty-nine cross combinations of fodder cowpea for thirteen characters. Figure 2 presents a heatmap of mid-parent heterosis (MDH) percentages over two seasons. This analysis will be useful in the prediction of the potential benefits of hybrid vigor in improving fodder yield and quality. Analysis of mid-parent heterosis shows that there exists a wide range of Significant heterosis values across the different traits. For the number of primary branches per plant (NPB), heterosis varied from 1.40–16.13%, with an average of 5.08% in Season 1 of mid-parent. However, all the genotypes failed to exhibit positive heterosis in Season 2. The maximum significant positive heterosis in Season 1 was observed for the cross-combination GETC 40 x TNFC0926 (16.13%). For plant height (PH), the heterosis was significant. The range of mid-parent heterosis in Season 1 was from 0.45–19.69%, having a mean of 6.57%. A genotype, GETC 21 x TNFC 0926, expressed the highest heterosis. In Season 2, the mid-parent heterosis ranged from 1.48–143.15%, having a mean of 33.87%. The highest degree of heterosis was recorded for IFC 9402 x CO (FC) 8. The NOL showed heterosis from 1.90–59.73% in Season 2 with a mean of 25.99%. The most significant increase was observed in the cross CL 321-1 x CO 9 with a value of 59.73%. Crude fiber content (CFB) In Season 1, the mid-parent heterosis ranged from 2.68–13.36%, and in Season 2, it ranged from 0.53–10.80%. The highest was obtained in the cross CL 348 x CO 9 (13.36%). Crude protein content (CPR) In Season 2, the mid-parent heterosis varied from 0.13–39.78%, with a mean of 17.97%. The highest heterosis was observed in the genotype FD 1052 x TNFC0926 (39.78%). Heterosis in green fodder yield per plant (GFY) exhibited that the mid-parent heterosis range varied between 5.21 and 54.63%, with a mean of 25.20% during Season 1. Maximum percentage of heterosis was found in the genotype FD 1052 x CO (FC) 8. During Season 2, heterosis varied from 2.55–111.15%, with a mean of 47.33%. The highest values were found in IFC 9402 x CO 9. CFT showed heterosis to the extent of 16.32–112.87% in Season 1. Genotype FD 1052 x CO 9 recorded the highest heterosis percentage (112.87%). DMY reflected heterosis ranging from 0.62–119.35% in Season 1 with an average of 50.09%. The genotype K – 13 -CP42 x CO(FC) 8 showed maximum heterosis. In the second season, the maximum heterosis was found in K – 13 -CP42 x TNFC0926 (133.47%). In Season 1, leaf stem ratio (LSR) presented the highest heterosis in the genotype GETC 23 x CO (FC) 8 (26.98%).

3.7 Correlation Analysis of Important Traits in Fodder Cowpea

We analyzed the relationships among various traits (Fig. 3) and identified significant correlations to improve breeding and cultivation strategies. GFY was significantly positively correlated with DMY (r = 0.23), ASH(r = 0.22), LW(r = 0.16), LL(r = 0.18), CFT(r = 0.39) and NOL (r = 0.17) significantly negatively correlated with DFF (r=-0.54) and NBP (r=-0.70). DMY was significantly positively correlated with GFY (r = 0.23), CFT (r = 0.25), and NOL (r = 0.18). Highly positive correlations of CPR were found with NBP (r = 0.74) and DFF (r = 0.59). NBP had positive correlations with DFF (r = 0.73). CFT negatively correlated with DFF, CPR, and NBP. However, CFB was positively correlated with NPB (r = 0.27) and DFF (r = 0.15), whereas ASH was weakly positively correlated with DMY (r = 0.11), with LSR being positively correlated with LW (r = 0.20). The results depict interrelations among the selected traits which are important in fodder cowpea for further breeding.

3.8 Path Coefficient Analysis of Indirect and Direct Effects on Green Fodder Yield

The path analysis, plotted in Fig. 4, shows several significant direct and indirect effects on Green GFY. CFB directly negatively affects GFY (β = -0.41). CPR also direct negative GFY (β = -0.34). NPB, on the other hand, has a β = -0.12, NOL has a coefficient of β = 0.04, LL demonstrates a β = -0.07, ASH has a coefficient of -0.10, Crude Fat Content CFT has a coefficient of β = -0.48, LW result a coefficient of β = -0.04, and DFF shown a coefficient of β = -0.08. The most important indirect effects on GFY are (1) LW contributing to GFY through a positive effect on CFB, with a β = 0.0552, and (2) NPB negatively affecting GFY through a negative effect on CPR, with a β = −0.0881, as is shown in Fig. 4. The results indicate the complexity of the interaction that takes place between factors affecting GFY, where both direct and mediated relationships contribute to the overall yield.

Selection is an important practice for the identification of desirable traits in genetically diverse materials, such as yield, nutritional quality, and drought resistance, so that the developed varieties can be improved(19). Cluster analysis plays a vital role in assessing genetic diversity and relationships among the lines and testers based on their traits(20). The findings of the cluster analysis dendrogram-based heatmap show (Fig. 1) significant variation among important forage traits. This supports the crossing of 23 female parents and 3 male parents to generate super heterotic hybrids. Similar results were reported in a previous study(21, 22). The unique clustering of certain genotypes, such as those in Cluster III, indicates their potential as general combiners with a broad genetic base, which is advantageous for breeding programs focused on enhancing adaptability and performance across diverse environments (23–25). The use of UPGMA clustering with the Jaccard dissimilarity coefficient proved effective in identifying genetic relationships and provided an important method for analyzing genetic diversity in fodder cowpea breeding.

The ANOVA results in the study indicate highly significant differences between the fodder cowpea genotypes, demonstrating genetic diversity among the 95 genotypes, which suggests the effectiveness of the line x tester method for such crosses. Most traits examined showed statistically significant variance attributed to the parent vs. cross method, indicating the presence of hybrid vigor(5, 15, 26, 27). The line-x tester method was highly significant for most traits except for NOL and CFT, emphasizing the importance between parents (lines x testers) and crosses. Although most parents were highly significant, their testers for many traits were non-significant; however, the significant line-x-tester interaction suggests that specific combining ability between lines and testers was more crucial for determining trait performance than the testers' variability alone. Similar results were reported in previous investigations(5, 6, 12–14, 26, 28–30).

High mean DMY (g/per plant) in genotypes such as K-13-CP42 and FD 1259 indicates the potential for high and stable yields. Variability in DFF between early maturing genotypes like CL 348 and late maturing ones like GETC 41 suggests suitability for different conditions. The high mean GFY (g/per plant) in GETC 23, tester, and most of the line indicates substantial biomass production potential. Structural diversity may help with yield because of differences in PH with the tallest GETC 40, tester, and leaf traits like the longest mean LL in EC 240806. Nutritional traits such as CPR and CFB varied significantly, with genotypes like TNFC0926 excelling in different categories and improving fodder quality. These findings suggest breeding strategies can combine high-yielding and nutritionally superior traits, improving cowpea's productivity and quality as a fodder crop. Seasonal impacts highlight the need for multi-environment testing to identify stable, high-yielding genotypes. Similar results were informed in previous analyses(31–34).

The results of 69 hybrids indicate significant potential for improving fodder yield and quality through Line × Tester combinations in cowpea hybrids. The increase in DMY in the second year suggests that specific hybrids, such as GETC 10 x TNFC0926 and CS 98 x TNFC0926, may possess genetic advantages or better adaptability, leading to higher biomass production. The stability in DFF across the years, particularly in the cross FD 1052 x CO 9, suggests that flowering time is a relatively stable trait, which is essential for uniform harvesting. The observed decrease in average GFY, despite some hybrids performing well, indicates the influence of environmental factors on yield, which requires further investigation to determine the underlying causes. The variation in PH, with some hybrids like IFC 9402 x TNFC0926 achieving high plant heights while others showed reduced heights, highlights the need for further selection to achieve consistent plant height across different environments. The increase in NOL in Year 2, especially in the cross FD 1259 x CO(FC) 8, points to the potential for higher biomass production through targeted selection for leafiness. The stability of LL and LW suggests that these traits are less affected by environmental factors, making them reliable for selection in breeding programs. The consistent ash content across the hybrids indicates stable nutritional quality, while the increase in CPR in certain crosses suggests potential for enhancing the protein content of cowpea fodder. The stability of CFB levels and the observed decrease in CFT suggest areas for further research to improve fat content stability while maintaining high fiber levels. The consistent NPB and LSR indicate that these traits are relatively stable, which is beneficial for maintaining a favorable leaf-to-stem ratio, crucial for fodder quality. These findings align with previous research(33–40).Studies have demonstrated the potential of these hybrids in breeding programs to enhance the yield and quality of cowpea fodder(31, 33, 34, 36–40). Future research should focus on confirming these findings across different environments to ensure stability and adaptability.

The results showed a higher GCA value for female parents than male parents for most of the studied traits. Different research results have also shown that GCA effects for most traits are significantly positive, with female parents contributing more advantageous to yield and quality than male parents. For example,Anitha et al. (2017) showed that GCA effects were higher in female parents, and they play important roles in traits of economic importance such as yield, so it is very useful for hybrid developers to incorporate these lines into their breeding programs.Romanus, Hussein, and Mashela (2008) also observed significant GCA effects on several traits, suggesting a part of additive gene action. Similarly,(Owusu et al. 2020) underlined the role of GCA as a major contributor to trait variation, particularly regarding maturity and seed weight. They described the clear importance of female parents in general combining abilities.Patel (2013) andAyo-Vaughan et al. (2013) further confirmed these findings by suggesting that the high GCA effects of parents have a positive impact on trait improvement. These studies confirm that prioritizing female parents with positive GCA values can enhance the effectiveness and consistency of fodder cowpea breeding programs. On the other hand, current study results revealed the important role of GCA in fodder cowpea breeding. This indicates that additive gene effects play a major part in gene action. These genetic elements are especially important for predicting progeny performance, selection, and hybridization methods.Anitha et al. (2017) documented that both additive and non-additive genetic effects play a critical role in fodder cowpea but more importantly additive effects for several yield-related traits. Similarly, result,Owusu et al. (2018) also reported.Kumar, Phogat, and Bhusal (2015); Kumari and Chauhan (2018); Lovely and Kumar (2024) suggested that the utilization of parents with high GCA effects can greatly improve the advancement of new synthetic varieties with desired characteristics such as higher production and better-quality nutritional constituents. Additionally,Jou-Nteufa and Ceyhan (2022) mentioned that segregating traits controlled by additive genetic variance usually have high narrow-sense heritability, which means they correlate well with the true breeding values of individuals improved in early-generation selection. This genetic knowledge enhances breeding efficiency and leads to the development of high-quality forage cowpea cultivars.

The results of the current studies showed varying degrees of SCA among the hybrids, suggesting the importance of non-additive genetic effects (such as dominance or epistatic effects). For instance, hybrids such as CS 98 x CO 9 and CL 321-1 x CO (FC) 8 showed the highest positive SCA effects for DMY, while GETC 49 x CO (FC) 8 and GETC 49 x CO 9 demonstrated superior SCA for days to DFF. Similarly, hybrids CL 348 x CO 9 and IFC 9304 x TNFC0926 exhibited positive SCA effects for plant height, whereas IFC 9402 x TNFC0926 and FD 1259 x CO (FC) 8 showed high SCA for LL. For CPR, hybrids N 311 x CO 9 and FD 1052 x CO 9 demonstrated superior SCA effects. These findings highlight that hybrids with high SCA for multiple traits often result from crosses involving parents with favorable additive genetic effects. Similar results were recorded in previous studies(13, 26, 27, 30). This emphasizes the critical role of selecting parents with GCA to achieve desirable hybrid performance in breeding programs. Selecting parents with strong GCA can lead to hybrids with enhanced traits, which is crucial for improving crop performance and yield (41, 44). In summary, these findings the importance of strategic parent selection in breeding programs aiming to optimize multiple traits simultaneously. Selecting parents with strong SCA is essential for developing high-performing hybrids with desirable traits, ensuring better crop yields and improved agricultural outcomes.

Studies have shown that GCA effects were higher in female parents, playing important roles in traits of economic importance such as yield, making it very useful for hybrid developers to incorporate these lines into their breeding programs(5). Significant GCA effects on several traits have also been observed, suggesting a part of additive gene action (41). Similarly, the role of GCA as a major contributor to trait variation, particularly regarding maturity and seed weight, has been underlined, describing the clear importance of female parents in general combining abilities (12). These findings were further confirmed by studies suggesting that the high GCA effects of parents have a positive impact on trait improvement(6, 43). These studies confirm that prioritizing female parents with positive GCA values can enhance the effectiveness and consistency of fodder cowpea breeding programs. On the other hand, current study results revealed the important role of GCA in fodder cowpea breeding, indicating that additive gene effects play a major part in gene action. These genetic elements are especially important for predicting progeny performance, selection, and hybridization methods. It has been documented that both additive and non-additive genetic effects play a critical role in fodder cowpea, with additive effects being more important for several yield-related traits(5). Similar results have been reported(12). The use of parents with high GCA effects can greatly improve the advancement of new synthetic varieties with desired characteristics such as higher production and better-quality nutritional constituents(11, 24). Additionally, it has been mentioned that segregating traits controlled by additive genetic variance usually have high narrow-sense heritability, correlating well with the true breeding values of individuals improved in early-generation selection, enhancing breeding efficiency and leading to the development of high-quality forage cowpea cultivars (9).

The analysis of mid-parent heterosis across the sixty-nine cross combinations of fodder cowpea demonstrates significant potential for improving fodder yield and quality traits through selective breeding. The observed heterosis values for traits such as primary branches, plant height, number of leaves, crude fiber content, crude protein content, and green fodder yield suggest that hybrid vigor can be effectively harnessed to enhance crop performance. These findings are consistent with previous research, which highlights the influence of environmental factors on heterosis expression(34), as well as the potential for substantial growth improvements in traits like plant height and leaf production under optimal conditions(5, 11, 45). The high heterosis observed for crude fiber, dry matter yield, and the leaf-stem ratio indicate the presence of considerable genetic diversity and advantageous alleles within the parental lines, which are essential for developing high-performing hybrids. The genetic analysis underscores the complex interplay of both additive and non-additive gene actions, suggesting that a comprehensive breeding strategy should account for both types of gene effects to maximize trait improvement. These results affirm the value of mid-parent heterosis as a tool in breeding programs, providing a pathway for achieving significant advancements in fodder cowpea production and nutritional quality(46–48).

The correlation and path coefficient analyses in this study highlight the complex interactions among various traits influencing green fodder yield (GFY) in cowpea. The positive correlations between GFY and traits like DMY, ASH, LW, LL, CFT, and NOL suggest that selecting these traits could enhance overall fodder yield, consistent with previous findings(22). Conversely, the negative correlation between GFY and DFF indicates that earlier flowering is crucial for improving yield, as also reported (42). The path coefficient analysis further elucidates that while traits such as CFB and CPR negatively impact GFY, likely due to their effects on nutrient absorption and biomass production, traits like NOL, LL, CFT, and ASH have positive direct effects on GFY. This implies that improving photosynthetic efficiency and mineral nutrition are key strategies for enhancing yield, corroborating previous work(38, 49). However, excessive branching, indicated by higher NBP, may reduce GFY due to intra-plant competition, aligning with findings (22). The study underscores the importance of balancing traits such as crude fiber and protein content, as high fiber can be difficult to digest, while appropriate protein levels are essential for growth (50). These insights provide a valuable framework for breeding programs to improve cowpea as a fodder crop.

Overall, the examined traits exhibit a greater influence of GCA effects compared to SCA effects. A higher value of GCA is advantageous for breeding programs that focus on selection and hybridization, as it indicates that the traits are largely governed by additive gene effects. However, some traits showing considerable SCA suggest the presence of non-additive gene actions, such as dominance and epistasis. This non-additive gene activity is beneficial for heterosis breeding programs, where hybrid vigor is sought. By leveraging both GCA and SCA, plant breeders can effectively utilize additive genetic effects for improving traits through selection and non-additive effects for exploiting hybrid vigor.

An efficient assessment of genetic diversity and relationships among lines, testers based on selected important forage traits, supporting the crossing of 23 female parents and 3 male parents. ANOVA results emphasize the effectiveness of the line x-tester method for these crosses. Combining high-yielding and nutritionally superior traits enhances cowpea's productivity and quality as a fodder crop. Higher GCA values for female parents than male parents for most traits indicate the significant role of additive gene effects in trait improvement. Through selective breeding, there are substantial improvements in cowpea traits, with positive correlations between traits like GFY, DMY, ASH, LW, LL, and NOL. Essential for developing high-performing hybrids with desirable characteristics, ensuring better crop yields and improved agricultural outcomes.

Ethics approval and consent to participate.

Not applicable.

Consent for Publication.

All authors have consented to the publication of this manuscript.

Availability of data and materials

The data supporting the findings of this study are included in this published article. Additional data can be provided upon reasonable request from the corresponding author.

Competing interests

All authors declared that there is no conflict of interest.

Funding

This research was financially supported by HATSUN Agro Product Ltd, Chennai (India), and the ICAR-NTSC Fellowship.

Authors' contributions

E.T. was responsible for conceptualization and methodology, project management, and securing funding. M.K.T. conducted the formal analysis and wrote the original manuscript draft. P.R. handled data curation and validation of the results. S.K. reviewed the manuscript, and S.R.S.R. provided supervision and resources for the research.

ACKNOWLEDGMENTS

We sincerely thank all the technical and non-technical staff at the Department of Forage Crops, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore, India, for their valuable support and help during this research.

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Tables 1 to 6 are available in the Supplementary Files section.

No competing interests reported.

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Comprehensive Analysis of Combining Ability and Genetic Parameters for Green Fodder Yield and Quality Traits in Indian Cowpea (Vigna unguiculata L.)

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Version 1

Abstract

Figures

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1Phenotyping:

2.2 Data analysis

3. RESULTS

3.1 Cluster Analysis fodder cowpea genotype

3.2 Analysis of variance

3.3 Mean performance among all parental genotypes and F₁ crosses

3.4 General combining ability

3.5 Specific combining ability

3.6 Analysis of Mid-Parent Heterosis

3.7 Correlation Analysis of Important Traits in Fodder Cowpea

3.8 Path Coefficient Analysis of Indirect and Direct Effects on Green Fodder Yield

4. DISCUSSION

5. CONCLUSION

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

Comprehensive Analysis of Combining Ability and Genetic Parameters for Green Fodder Yield and Quality Traits in Indian Cowpea (Vigna unguiculata L.)

Status:

Version 1

Abstract

Figures

1. INTRODUCTION

2. MATERIALS AND METHODS

2.1Phenotyping:

2.2 Data analysis

3. RESULTS

3.1 Cluster Analysis fodder cowpea genotype

3.2 Analysis of variance

3.3 Mean performance among all parental genotypes and F1 crosses

3.4 General combining ability

3.5 Specific combining ability

3.6 Analysis of Mid-Parent Heterosis

3.7 Correlation Analysis of Important Traits in Fodder Cowpea

3.8 Path Coefficient Analysis of Indirect and Direct Effects on Green Fodder Yield

4. DISCUSSION

5. CONCLUSION

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

3.3 Mean performance among all parental genotypes and F₁ crosses