Character association studies for grain yield and its components in Greengram (Vigna radiata (L.) Wilczek) germplasm

Introduction

Mungbean, commonly referred to as greengram (Vigna radiata (L.) Wilczek), is an essential legume known for its nutritional value and adaptability. With a diploid chromosome number of 2n = 22, it belongs to the Fabaceae family and the Papilionoideae subfamily. The species native to India and Central Asia and is categorized into three subgroups: one cultivated (V.

radiata subsp. radiata) and two wild varieties (V. radiata subsp. sublobata and V. radiata subsp. glabara) (Asari et al. 2019) [2] . The belief that greengram originated in the Indian subcontinent is supported by historical sources (DeCandolle, 1884 ; Vavilov, 1926; Zukovskij, 1962) [4,6,7] reflecting its rich genetic diversity among both cultivated and wild types.

Greengram's significance as a pulse crop is attributed to its short growth cycle, high nutritional content, and ability to thrive in low-water conditions. It is widely cultivated and consumed across India, making it a vital food source. India stands as the leading global producer of mungbean, with cultivation extending to nearly all states. As of the 2021-22 season, mungbean was grown over 40.38 lakh hectares, yielding a total production of 31.5 lakh tonnes and a productivity rate of 783 kg/ha, which accounts for 11% of the nation's total pulse production.

In the 2022-23 kharif season, mungbean cultivation decreased to 33.37 lakh hectares, resulting in a production of 17.5 lakh tonnes (agricoop.nic). Within Maharashtra, it occupied 3.78 lakh hectares, yielding 1.47 lakh tonnes with a productivity of 390 kg/ha. Notably, approximately 82% of the total kharif production comes from six major states: Rajasthan, Karnataka, Maharashtra, Madhya Pradesh, Bihar, and Andhra Pradesh. Overall, mungbean contributes 16% of the area and 10% of the production within India's total pulse crop sector, highlighting its importance in the agricultural landscape (Annual report (2021-22): DES, Ministry of Agri. & FW (DA&FW), Govt. of India).

Materials and Methods

Results and Discussion

D² values were computed for all pairwise comparisons among the genotypes, which led to the classification of the 42 genotypes into eleven distinct clusters, highlighting significant diversity in most traits (Table 1). The squared Euclidean distance method was utilized to measure distances between genotype pairs, and clustering was achieved using Tocher's method (Figure 1). The mean values for nine yield-related traits in pigeonpea were estimated for each cluster, demonstrating a wide range of variation (Table 2). The cluster mean for days to 50 percent flowering ranged from 32.00 days in cluster VI to 38.72 days in cluster III. For days to maturity, the mean varied between 62.50 days in cluster VI and 68.67 days in cluster I. The highest plant height mean was observed in cluster III at 63.63 cm, while cluster II had the lowest at 44.91 cm. The number of primary branches per plant ranged from 3.91 in cluster II to 6.10 in cluster III. For secondary branches, the means varied from 4.80 in cluster II to 7.66 in cluster I.

Cluster I had the highest mean number of pods per plant at 22.92, while cluster VI had the lowest at 15.40. The maximum number of seeds per pod was found in cluster V (13.75), and the minimum was in cluster IV (11.96). The mean for 100-seed weight ranged from 2.50 in cluster VI to 6.00 in cluster V. Finally, seed yield per plant varied from 11.45 grams in cluster VI to 16.00 grams in cluster V. The clustering pattern of genotypes confirmed significant diversity. Cluster II contained the largest group with 15 genotypes, while Cluster I and Cluster III each had 9 genotypes, and Cluster IV had 7 genotypes. Clusters V and VI each had a single genotype. These findings align with those of Bhareti et al. (2019) [3] , who also reported six clusters. Similarly found 15 genotypes, identifying Cluster II as the largest polygenotypic cluster. The observed divergence within clusters indicates variability among genotypes in the same cluster, while inter-cluster divergence reflects genetic distances between different clusters. Both inter-and intra-cluster D² values were calculated during the divergence analysis. A detailed assessment of the clusters showed heterogeneity within and between them based on key traits. The composition of each cluster, along with interand intra-cluster distances, is presented in [3] . The intra-cluster values ranged from 0.00 to 54.60, with the highest intra-cluster distance of 54.60 observed in Cluster IV, followed by 52.64 in Cluster III and 49.38 in Cluster II.

The genotypes in these clusters can be considered suitable parents for hybridization programs, as the high degree of divergence among them is likely to yield more desirable breeding material for maximizing genetic advancement. This finding aligns with, who reported intra-cluster values ranging from 0.00 to 24.47, also noting that Cluster IV exhibited the maximum intra-cluster distance. Genotypes within these clusters, showing significant divergence, are ideal candidates for hybridization programs, as they are likely to produce desirable breeding material and enhance genetic advancement for specific traits. This implies that genotypes from these clusters can effectively serve as parents in hybridization efforts, given that crosses between genetically diverse parents can result in transgressive segregants. Greater emphasis should be placed on the traits contributing most to genetic divergence when selecting parents within their respective clusters for hybridization. The frequency of each yield component character ranked first and its corresponding contribution percentage toward genetic divergence is presented in Table 4. It was observed that 100-seed weight contributed the most to divergence at 25.67%, followed by the number of secondary branches per plant (24.39%), plant height (15.08%), number of primary branches per plant (13.01%), number of pods per plant (9.87%), number of seeds per pod (6.39%), days to 50 percent flowering (3.72%), seed yield per plant (0.81%), and days to maturity (0.35%). Similar findings were reported by Bhareti et al. (2019) [ 3 ] , who noted that 100-seed weight accounted for the highest percentage of divergence at 59.00%. Comparable results were also observed.

Mahalanobis Euclidean Distance (Not to the Scale)

Conclusion

The clustering analysis of 42 pigeonpea genotypes revealed significant genetic diversity, with eleven distinct clusters identified. Key yield-related traits exhibited notable variation, highlighting the potential for selective breeding. Clusters II and IV showed the highest intra-cluster distances, indicating suitable candidates for hybridization to enhance genetic advancement. The 100-seed weight emerged as the primary contributor to genetic divergence, followed by the number of secondary branches and plant height. These findings underscore the importance of genetic diversity in breeding programs, emphasizing the selection of diverse parent genotypes to maximize trait improvement and achieve desirable breeding outcomes.

References

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