Legume Research

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Legume Research, volume 44 issue 3 (march 2021) : 261-267

Assessment of genetic divergence in horsegram [Macrotyloma uniflorum (Lam) Verdc.] using quantitative traits

S. Priyanka1, R. Sudhagar1,*, C. Vanniarajan2, K. Ganesamurthy1
1Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India.
2Department of Plant Breeding and Genetics, Agricultural College and Research Institute, TNAU, Madurai-625 104, Tamil Nadu, India.
  • Submitted28-11-2018|

  • Accepted01-03-2019|

  • First Online 14-08-2019|

  • doi 10.18805/LR-4103

Cite article:- Priyanka S., Sudhagar R., Vanniarajan C., Ganesamurthy K. (2019). Assessment of genetic divergence in horsegram [Macrotyloma uniflorum (Lam) Verdc.] using quantitative traits . Legume Research. 44(3): 261-267. doi: 10.18805/LR-4103.
Genetic relatedness studies using 12 quantitative traits on 252 genotypes in horsegram revealed wide spectrum of variability for yield components. The genotypes were grouped into 25 clusters based on estimates of D2 statistic. Cluster I had the largest number with 83 genotypes followed by cluster II (77 genotypes), cluster IV (33 genotypes) and cluster III (30 genotypes). On the contrary, 20 solitary clusters from cluster V to XXV were formed except cluster XIV (9 genotypes) which could be given priority for specific trait improvement. Cluster XXI recorded the highest mean value for single plant yield (65.51 g). The intra and inter cluster distance was varying in magnitude indicating the presence of larger genetic diversity among accessions. The highest intra cluster distance was noticed in cluster XIV (23.63) followed by cluster IV (22.37). Maximum inter cluster distance was observed between solitary clusters viz., cluster XXI & XVII followed by cluster XXI & XV and cluster XXI & VII. These clusters would offer superior segregants when employed in hybridization programme.
Horsegram [Macrotyloma uniflorum (Lam.) Verdc.] is a member of leguminous family adapted to wide range of environmental regimes. It is a self-pollinated crop, having tolerance to drought (Bhardwaj and Yadav, 2012), salinity (Reddy et al., 1998) and heavy metal stress (Reddy et al., 2005). The seeds are enriched with a protein content of 18.5% - 28.5% (Savithramma and Shambulingappa, 1996), carbohydrates (50% to 70%), minerals, iron, molybdenum (Bravo et al., 1999) and vitamins (Sodani et al., 2004). Owing to its massive nutritional benefits, horsegram has been quoted as a potential therapeutic agent in Indian traditional medicine systems to treat kidney stones, urinary diseases, piles, common cold, throat infection and fever (Prasad and Singh, 2015). It is used as a fodder for milch animals because of its high protein content and also plays an important role as green manure by enriching soil fertility due to atmospheric nitrogen mineralization. Despite its role in agricultural, animal husbandry, human and soil health it is not being cultivated in ideal agronomic situations. This under-utilized legume crop will have its recognition in near future because of its potential nutritional and medicinal benefits.
Horsegram is typically a short day plant, with maturity duration of 120 to 180 days (Morris, 2008). It is a minor crop, being cultivated in low-input and marginal lands which limit the scientific efforts to enhance horsegram research and development. Knowledge on extent of genetic variability is a pre-requisite for any breeding programme. In comparison with other pulse crops, recently few studies on assessment of genetic diversity have been reported in horsegram (Gomashe et al., 2018; Viswanatha et al., 2016). Identification of diverse genotypes with significant yield and nutritional traits is a boon that could be utilized for hybridization programme to evolve superior high yielding varieties suited for diverse environments. With this view, this experimental study was conducted to understand the nature and magnitude of variability present among horsegram germplasm accessions using 12 quantitative traits.
Two hundred and fifty germplasm accessions retrieved from Dr. Ramiah Gene Bank, Tamil Nadu Agricultural University (TNAU) and two released varieties of horsegram viz., PAIYUR-2 (released by TNAU) and CRIDA 1-18 R (released by Central Research Institute for Dry land Agriculture) comprised the experimental material. Before laying out of experiment, the field was homogenized for fertility by sufficient manuring/crop residues through soil tests for ensuring uniform crop expression. Totally, 252 genotypes were raised in randomized block design with two replications in the experimental farms of Department of Pulses, TNAU, Coimbatore. The genotypes were sown in 4m lengthier rows with the spacing of 30 cm x 10 cm during rabi season of 2017. The crop was grown in pure rainfed condition. Observations were recorded on five randomly selected plants for 12 quantitative traits viz., days to 50% flowering, days to maturity, plant height (cm), number of primary branches per plant, pod length (cm), pod width (cm), number of clusters per plant, number of pods per cluster, number of pods per plant, number of seeds per pod, 100 seed weight (g) and seed yield per plant (g). Yield and its component traits were recorded at time of harvest except days to flowering and maturity. Assessment of genetic diversity was carried out by employing Mahalonobis D2 statistic (Mahalanobis, 1936) using Indostat-version 7.1 software. The clustering of genotypes was done on basis of D2 being treated as the square of generalized distance, as per method described by Tocher (Rao, 1952).
Horsegram is extensively cultivated in southern states i.e. Karnataka, Andhra Pradesh and Maharashtra and to some extent in parts of West Bengal, Bihar, Himachal Pradesh, Orissa, Chhattisgarh and foot hills of Uttar Pradesh (Purushottam et al., 2017). In India, horsegram covers an acreage of 0.5 million hectares with production and productivity of 0.26 million tones and 520 kg/ha respectively (Anonymous, 2015).

Horsegram cultivating lands are resource challenging/demanding which requires development of climatic resilience genotypes. The climatic challenges include extremities of drought and cold, salinity and diseases. Because of these constraints, the yield potential of horsegram is not fully realized. Additionally, it is being grown extensively in rabi season due to photosensitivity nature. Development of multiple tolerant and photo-insensitive varieties with improved yield would extend its cultivation in non-traditional areas thereby yield gap can be compensated.
Presence of wide spectrum of genetic variability is essential for any crop improvement strategy. Genetic diversity can be exploited through collection and evaluation of germplasm lines and genotypes of a crop, which is pre-requisite for any breeding programme (Ramakrishnan et al., 2014). The analysis of variance revealed highly significant differences for all the traits included in the study (Table 1). However, it is not a reliable measure for prediction of divergence among genotypes (Geetha et al., 2011). Knowledge on quantitative divergence of the traits contributing to yield is of primary concern for a plant breeder, which was widely fulfilled by multivariate (D2) analysis.

Table 1: Analysis of variance for quantitative traits.

D2 statistic is a powerful tool to measure the genetic divergence within set of genotypes (Murty et al., 1966; Dasgupta et al., 2005). Based on estimates of D2 statistic, 252 accessions were grouped into 25 clusters (Table 2) with generalized distance ranging from 0.00 to 52.79. Traits viz., number of pods per plant (34.14%), hundred seed weight (18.82%), days to fifty per cent flowering (16.97%),  number of clusters per plant (10.21%) contributed maximum towards genetic divergence whereas, least contribution was made by days to maturity (0.10%) and number of primary branches per plant (0.35%). It was noted that most of the yield related traits had exhibited considerable contribution towards cluster divergence hence, probability of improving these traits turns to be feasible by hybridization and selection (Fig 1). The results were in conformity with the findings of Geetha et al., (2011).

Fig 1: Contribution of quantitative traits towards cluster divergence.


Table 2: Clustering pattern of 252 genotypes in horsegram.

Among the 25 clusters, maximum accessions were grouped under cluster I (83 genotypes) followed by cluster II (77 genotypes), cluster IV (33 genotypes) and cluster III (30 genotypes). On the contrary, 20 solitary clusters viz., cluster V to XXV except cluster XIV were formed, which could be given priority for improvement of specific traits. Clusters with single genotype were high owing to reason that experimental accessions were collected through various explorations across Indian States over years. These geographical variations might have yielded more number of solitary clusters. The intra and inter cluster distance among 25 clusters were presented in Table 3. The highest intra cluster distance was noticed in cluster XIV (23.63) followed by cluster IV (22.37), cluster III (17.26), cluster II (15.73) and cluster I (15.52) while the remaining 20 clusters were found to be unique cluster possessing no intra cluster value. The genotypes present within cluster tend to be genetically less diverse compared to other clusters. Maximum inter cluster distance was observed between solitary clusters viz., cluster XXI and XVII (52.79) followed by cluster XXI and XV (50.97) and cluster XXI and VII (50.97). Promoting hybridization between diverse genotypes would be highly heterotic thereby evolve superior varieties (Singhal et al., 2010). The least inter cluster distance was recorded between cluster XIX and VII, cluster XVIII and X and cluster XVIII and XII with a distance of 13.02, 12.33 and 12.53 respectively.

Table 3: Mean intra (bold) and inter cluster distance in horsegram.

The average cluster mean values for 12 traits would help to identify genotypes for improving specific yield components (Table 4). Cluster XIII with single genotype and Cluster XIV with 9 genotypes recorded lower mean value for days to fifty percent flowering whereas, cluster IX and XIII for days to maturity. These genotypes could be utilized as a donor for evolving short duration types. Among the germplasm accessions, cluster XXI (PLS 6105) was found to be high yielding line with mean yield of 65.51 g. Cluster XXII (PLS 6004) recorded the highest group mean for yield components viz., number of clusters per plant, number of pods per plant and pod width. Being a unique cluster, the genotype can be used in crossing programme to evolve high yielding varieties as it exhibits superior per se performance for several yield components. A solitary cluster XI (PLS 6224) recorded the highest mean for number of pods per cluster (4.35). Neelam et al., (2014) reported significant correlation between number of pods per plant and single plant yield. Hence, accession PLS 6224 can be utilized for yield improvement by breeding for increased number of pods per plant. Several other unique clusters were also contributed for yield components viz., cluster XIX (8513/4-3) recorded the highest mean yield with 5.32 g for hundred seed weight, cluster XVIII (PLS 6221) possessed highest mean value for number of seeds per pod (7.12 g) and cluster X (PLS 6030) for number of primary branches per plant (10). These genotypes can be used as a donor to derive agronomically superior varieties. On a nutshell, it was concluded that horsegram accessions taken for study revealed wide range of genetic diversity and many unique clusters with promising accessions were formed contributing to the improvement of specific yield components (Table 5). These unique clusters can be given due importance in the future breeding programme to evolve superior types. These diverse genotypes shall be utilized in different research institutes.

Table 4: Cluster mean values obtained by Tocher’s method for 12 quantitative traits in horsegram.


Table 5: Promising accessions identified.

We acknowledge sincerely the Board of Research in Nuclear Sciences for providing the financial support and Dr. S. Dutta, Program Officer (RTAC), BARC and Dr. J. Souframanien, Principal Collaborator, NA&BTD, BARC, Mumbai for their support. The authors are highly thankful to the Professor and Head, and Plant Breeders of Regional Research Station, PAIYUR, TNAU, Tamil Nadu for sharing their valuable germplasm resources with related information. We gracefully endow our great gratitude to Dr. P. Jayamani, Professor and Head, Department of Pulses, TNAU, Coimbatore her relentless scientific support.

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