Identification of Diverse Genetic Architecture and Nutritional Protein Profiling for Yield and Attributing Traits in Pigeonpea [Cajanus cajan (L.) Millsp.]

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Introduction

Among various leguminous crops, pigeonpea [Cajanus cajan (L.) Millsp.] is the second most important one in India. It has got a high nutritional value and economic uses; its every part is useful for mankind. Despite the importance, a very little research has been made towards its improvement. A number of factors are responsible for the poor productivity includes lack of improved cultivars, poor crop husbandry, pest and disease attack such as the pod borer complex (Sahu et al., 2025a). Furthermore, sensitivity to abiotic stresses like water-logging and salinity also reduces pigeonpea production (Varshney et al., 2010). Extent of crop improvement programme in pigeonpea depends upon the expanse of its genetic variability, choices made for parents in hybridization and its selection procedure. The seed yield in pigeonpea is a complex trait which is highly influenced by the environmental variation. Success of yield improvement majorly depends upon its magnitude and nature of genetic variability present in the existing material, especially within diverse populations and germplasms (Sahu et al., 2025b).

Such assessments of genetic variability, character association, and diversity have proven essential for breeding programs not only in pigeonpea but across a wide variety of crop species, including linseed, oat, and grass pea (Sahu et al., 2016; Sahu and Tiwari, 2019; Sahu et al., 2022; Mishra et al., 2025b) [6].

Materials and Methods

The presented study included 20 germplasm of pigeonpea grown in different parts of the country planted in Completely Randomized Block Design (CRBD) with 3 replications during Kharif season for year 2021-22 at Research-cum-Instructional Farm, IGKV, Raipur, Chhattisgarh, India. A spacing of 60 cm between plants was maintained. All agronomic practiced were strictly followed. Observations were taken from randomly five plants from each replication for each genotype for characters viz., days to 50% flowering, duration of flowering, days to maturity, plant height (cm), no. of primary branches/plant, no. of pods/plant, no. of seeds/pod, 100 seed weight (g), shelling %, protein content (%) and seed yield/plant(g).The data was statistically analysed for descriptive statics, correlation and path analysis and genetic divergence analysis using OPSTAT and XLSTAT software.

Results and Discussion

Table 1 represented the ANOVA for seed and its component traits. Table 2 shows the genetic parameters where it is seen that maximum PCV (%) and GCV (%) was observed for traits no. of pods/plant followed by seed yield/plant. Low PCV (%) and GCV (%) was obtained for duration of flowering, days to maturity, plant height, no. of seeds/pod and 100 seed weight. High heritability was reported by days to 50% flowering, protein content, duration of flowering, low heritability was reported by plant height and shelling % and moderate heritability was reported by days to maturity and no. of seeds/pod. High GA (%) was reported by no. of pods/plant, seed yield/plant, primary branches/plant whereas, moderate GA (%) was reported by duration of flowering and 100 seed weight whereas low GA (%) was reported by days to maturity, plant height and no. of seeds/pod.

Table 3: Genotypic(G) and Phenotypic(P) correlation coefficient analysis for seed yield and its component traits in Pigeonpea. S.

No Characters Duration of Flowering Days to maturity Plant height (cm)

Primary branches/plant No. of pods/plant No. of seeds/pod 100 seed weight (g)

Table 4: Genotypic path coefficient (Direct & indirect) for seed yield and its component traits in Pigeonpea. Characters Days to 50 % flowering Duration of flowering Days to maturity Plant height (cm)

Primary branches/plant No. of pods/plant No. of seeds/ pod 100 seed weight (g)

Table 5: Cluster means for 11 quantitative characters in Pigeonpea. Cluster Days to 50% flowering Duration of flowering Days to maturity Plant height (cm)

Primary branches/ Plant No. of pods/ plant No. of seeds/ Pod 100 seed weight (g)

Shelling % Protein content (%)

Table 7 shows the intra and inter cluster distance between genotypes. The highest inter-cluster distance was found between cluster I and cluster III, followed by cluster V and cluster III. Table 6 represents cluster mean values for all the 11 characters. The highest cluster mean for days to 50% flowering was obtained for cluster III and the lowest in cluster I. Cluster V had the highest cluster mean for duration of flowering whereas, cluster III had the lowest. The cluster mean for days to maturity was highest for cluster II and lowest for cluster I. The highest cluster mean for plant height was obtained for cluster V and the lowest in cluster III.

Table 6: Genotypes of Pigeonpea can be grouped into 5 clusters containing following genotypes of Pigeonpea. Cluster No. Genotypes Name of genotypes Cluster I 1 RP-1 Cluster II 16 RP-2, RP-3, RP-5, RP-7, RP-14, RP-15, RP-17, ICP-6994, ICP-6996, ICP-7005, ICP-7373, ICP-7374, ICP-7379, C.G. Arhar-1, C.G.Arhar-2 Cluster III 1 RP-8 Cluster IV 1 Asha Cluster V 1 Rajeevlochan Table 7: Estimates of average intra-(bold) and inter- clusters distance in Pigeonpea Clusters 1 2 3 4 5 1 0.000 95.381 155.514 58.769 105.942 2 23.738 90.884 53.410 65.513 3 0.000 119.002 119.158 4 0.000 51.540 5 0.000 Primary branches/plant had highest cluster mean for cluster I and lowest for cluster IV. No. of pods/plant had highest cluster mean for cluster I and lowest for cluster III. The cluster mean for no. of seeds/pod was highest for cluster V and lowest for cluster III. 100 seed weight had highest cluster mean for cluster I and lowest for cluster III. The highest cluster mean for shelling % was for cluster III and lowest for cluster II. Protein content had highest cluster mean for cluster II and lowest for cluster I. Seed yield/plant had highest cluster mean for cluster I and lowest for cluster III.

Conclusion

The present study revealed substantial genetic variability among the 20 pigeonpea genotypes, indicating immense potential for crop improvement. Substantial genetic and nutritional variability exists among the germplasm. Selection based on the number of pods per plant and seed protein percentage offers a reliable route for simultaneous yield and quality improvement. The trait number of pods per plant emerged as the most reliable selection criterion for yield enhancement, as it exhibited the highest phenotypic and genotypic coefficients of variation (PCV and GCV), high heritability, and the highest genetic advance. Furthermore, correlation and path coefficient analyses confirmed that the number of pods per plant, alongside plant height, consistently showed a highly significant positive correlation and a strong direct positive effect on seed yield per plant. Genetic divergence analysis successfully grouped the genotypes into five distinct clusters. The maximum inter-cluster distance was observed between Cluster I and Cluster III, suggesting wide genetic diversity between the genotypes of these groups. Genotypes from Cluster I (RP-1), which recorded the highest cluster means for key traits like seed yield per plant, number of pods per plant, and 100 seed weight, hold great promise. Utilizing genotypes from highly divergent clusters (such as Cluster I (RP-1) and III (RP-8)) as parents in future hybridization programs is highly recommended to achieve superior transgressive segregants for high-protein and develop high-yielding pigeonpea varieties.

Fig 1: Dendrogram constructed using XLSTAT of 20 germplasms of Pigeonpea