STUDIES ON GENETIC VARIABILITYAND CHARACTERASSOCIATION FORYIELDAND ITS ATTRIBUTES IN BLACKGRAM [Vigna mungo (L.) Hepper].

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MAITRI PANIGRAHI*, L. PRASANTHI, K. HARIPRASAD REDDY AND A. R. NIRMAL KUMAR

Dept. of Genetics and Plant Breeding, S.V. Agricultural college, ANGRAU, Tirupati, Chittoor Dt.517502, Andhra Pradesh, India

ABSTRACT

An experiment was carried out to estimate the genetic parameters such as variability, heritability and genetic advance, character association and path analysis for eleven quantitative characters viz., days to 50 per cent flowering, days to maturity, plant height, number of primary branches per plant, number of clusters per plant, number of pods per plant, hundred seed weight, harvest index, SPAD chlorophyll meter reading, protein content and seed yield per plant in 42 genotypes of blackgram [Vigna mungo (L.) Hepper]. The genotypic coefficient of variation for all characters studies were less than the phenotypic coefficient of variation indicating the interaction of genotype with the environment. High heritability coupled with high genetic advance as per cent of mean was observed for days to maturity, number of plant height, number of clusters per plant, number of pods per plant and seed yield per plant. Association studies revealed that, days to 50 per cent flowering, days to maturity, plant height, number of primary branches per plant, number of clusters per plant, number of pods per plant and hundred seed weight showed positive and significant correlation with seed yield per plant both at the genotypic and phenotypic level. Path analysis studies revealed that clusters per plant, pods per plant and 100-seed weight had positive and high direct effects on seed yield per plant.

KEYWORDS:

Genetic variability, heritability, genetic advance, character association, path analysis.

INTRODUCTION

Blackgram [Vigna mungo (L.) Hepper], is one of the nutritious pulse crops, popularly known as urdbean. It is an important short duration pulse crop and self pollinated grain legume grown in many parts of India. It is mainly grown for its dry beans that are rich in proteins with high lysine content which is deficient in cereal grains. This crop is grown in cropping systems as a mixed crop, catch crop, sequential crop besides being grown as a sole crop under residual soil moisture conditions after the harvest of rice and also before and after the harvest of other summer crops under semi irrigated and dryland conditions. The productivity of pulse crops is very low as compared to cereals, the reason being growing of the crop in less fertile soil with less inputs and unavailability of cultivars with high yield potential adapted to local conditions. Hence, the selection for yield along with other contributing characters should be taken into account. For improving the seed yield, studies on genetic variability of important traits responsible for increasing the yield is highly necessary. Knowledge on heritability and genetic advance of the character indicate the scope for improvement of a trait through selection. Heritability estimates along with

genetic advance are also helpful in predicting the gain under selection. To accumulate optimum contribution of yield contributing characters, it is essential to know the correlation of various characters along with path coeffi-cients. The objective of the present study was to deter-mine the variability parameters along with correlation and path analysis to understand the mode of inheritance and degree and direction of association of different yield com-ponent traits with the seed yield.

MATERIALAND METHODS

The present investigation was carried out during rabi, 2017 at dry land farm of Regional Agricultural Re-search Station, Tirupati. The experimental material com-prised of 42 blackgram genotypes which were raised in

Randomised Block Design, each entry being sown in three Randomised Block Design, each entry being sown in three rows of 4 m length with a spacing of 30 × 10 cm. The package of practices recommended for the crop was fol-lowed. Eleven traits viz., days to 50 per cent flowering, days to maturity, plant height, number of primary branches per plant, number of clusters per plant, number of pods per plant, hundred seed weight, harvest index, SPAD chlo-rophyll meter reading, protein content and seed yield per plant were recorded from randomly selected plants ineach of the genotypes per replication, except days to 50 per cent flowering and days to maturity which were recorded on plot basis. The statistical analysis for variance was worked out according to Panse and Sukhatme (1961). Phenotypic and Genotypic coefficients of variation were calculated based on the method advocated by Burton (1952). Heritability, Genetic advance as per cent of mean and correlation coefficients were estimated as per the formula given by Johnson et al. (1955). The path coeffi-cient analysis was worked as suggested by Dewey and Lu (1959).advance. High heritability coupled with high genetic ad-vance as per cent of mean was recorded for days to

matumaturity, plant height, clusters per plant, pods per plant and seed yield per plant indicating the importance of ad-ditive gene action in governing the inheritance of these traits. This suggests that most likely the heritability is due to additive gene effects and hence selection may be ef-fective for these characters. It may be suggested that for additive effects pedigree or modified pedigree method of selection is followed. These results were in agreement with Sharma et al. (2006), Rahim et al. (2010) and Patidar
et al. (2018).

RESULTS AND DISCUSSION

The analysis of variance showed significant dif-ferences among the genotypes for all the characters stud-ied (Table 1) which gives the evidence of sufficient vari-ability among the genotypes. The estimates of phenotypic coefficient of variation were higher than the genotypic coefficient of variation (Table 2) indicating the influence of environment in governing the characters. Maximum estimate of phenotypic coefficient of variation was regis-tered for seed yield per plant (25.94 %) followed by clus-ters per plant (25.76 %) and primary branches per plant (25.41) suggesting the presence of sufficient phenotypic variability for these traits. Low estimates of phenotypic coefficient of variation was recorded for days to 50 per cent flowering (7.54) , harvest index (6.07 %) and pro-tein content (5.20 %). These results were in accordance with Kumar et al. (2015) for seed yield per plant and Patel et al. (2014) for clusters per plant. Quanitative char-acters are influenced more by the environment, obstruct-ing the transmission of the phenotype observed to the next generation. So, study on the heritable portion of the vari-ability is necessary. Heritability is a good index of charac-ters from parents to off springs and helps as a tool for selection of elite genotypes. In the present study, highest heritability was recorded for days to maturity (99.81 %) followed by days to 50 % flowering (98.72 %), plant height (97.91%), 100 seed weight (90.64 %), harvest index (83.90 %), SPAD chlorophyll meter reading (78.75 %), clusters per plant (67.67 %), pods per plant (67.46 %) and seed yield per plant (63.24 %). High heritability alone is not sufficient enough to exercise selection unless the infor-mation is accompanied with substantial amount of genetic

Genotypic correlations were higher than the phe-notypic correlations (Table 3) for most of the characters which can be explained due to the masking or modifying effects of environment on genetic association between characters. In the present investigation, seed yield per plant recorded high significant and positive association with clusters per plant (rp = 0.709** and r g = 0.757**), fol-lowed by plant height (rp = 0.466** and r g = 0.605**), num-ber of pods per plant (rp = 0.613** and r g = 0.572**) and days to maturity (rp = 0.409** and rg = 0.515**). These results were in accordance with the findings of Umadevi and Ganesan (2005), Shivade et al. (2011) and Mathivathana et al. (2015). Hence, these characters can be utilized in indirect selection so as to improve the seed yield per plant. Path coefficient analysis revealed that number of clusters per plant (P = 0.4652 and G = 0.6288), pods per plant (P = 0.3851 and G = 0.2916) and 100 seed weight (P = 0.3734 and G = 0.4221) (Table 4, Fig 1 and Fig 2) showed true relationship with seed yield per plant by plant establishing significant and positive direct effects both at the genotypic and phenotypic level. These results were similar with that of Bharti et al. (2014) and Bandi et al. (2018). The residual effect was 0.578, indicating that along with the present characters some more characters like pod length, seeds per pod, main stem bearing should be taken into consideration while formulating selection strategies for yield improvement.

CONCLUSION

The present investigation registered high heritability along with high genetic advance as per cent of mean for days to maturity, plant height, clusters per plant, pods per plant and seed yield per plant suggesting that these characters should be given top priority for effective selection. Considering the nature and magnitude of character association and their direct and indirect effects it can be concluded that the improvement in seed yield is possible through simultaneous manifestation of clusters per plant, pods per plant and 100-seed weight.

REFERENCES

  1. Bandi, H. R. K., Nagendra Rao, K., Vamsi Krishna, K and Srinivasulu, K. 2018. Correlation and path-coefficient estimates of yield and yield components traits in rice fallow blackgram [Vigna mungo (L.) Hepper]. International Journal of Current Microbiology and Applied Sciences.
    7(3): 3304-3309.
  2. Bharti, B., Kumar, R., Bind, H. N., Kumar, A and Sharma, V., 2014. Correlation and path analysis for yield and yield components in black gram [Vigna mungo
  3. (L.) Hepper]. Progressive Research. 8: 473-476
  4. Burton, G.W. 1952. Quantitative inheritance in grass. Proceedings of 6th International Grassland Congress, Pennsylvania State College, U.S.I:
    277-283.
  5. Dewey, D.R and Lu, K.H. 1959. A correlation path coefficient analysis of components of crested wheat grass. Agronomy Journal. 51: 515-518.
  6. Johnson, H.W., Robinson, H.O and Comstock, R.E. 1955. Estimates of genetic and environmental variability
  7. in soybean. Agronomy Journal. 47: 314-318.
  8. Kumar, G.V., Vanaja. M., Sathish, P., Vagheera, P and Lakshmi, N.J. 2015. Correlation analysis for quantitative traits in blackgram [Vigna mungo (L.) Hepper] in different seasons. International Journal of Scientific and Research Publica tions. 5(4):1-10.
  9. Mathivathana, M. K., Shunmugavalli, N., Muthuswamy, A and Harris, C.V., 2015. Correlation and path analysis in black gram. Agricultural Scie-
    -nce Digest. 35(2): 158-160.
  10. Panse, V.G and Sukhatme, P.V. 1961. Statistical Meth od for Research Workers. 2nd edition. ICAR,New Delhi, pp. 351.
  11. Patel, R.V., Patil, S.S., Patel, S.R and Jadhav, B.D. 2014. Genetic Variability and Character Assoc–iation in blackgram [Vigna Mungo (L.) Hepper] during Summer. Trends in Biosciences. 7(23):
  12. 3795-3798
  13. Patidar, M., Hemlata, Sharma and Haritwal Santra. 2018. Genetic variability studies in blackgram [Vigna mungo (L.) Hepper]. International Journal of
    Chemical Studies. 6(2): 1501-1503.
  14. Rahim, M.A., Mia, A.A., Mahmud, F., Zeba N and Afrin, K. S. 2010. Genetic variability, character association and genetic divergence in mungbean
    ( Vigna radiate L. Wilczek). Plant Omics Journal. 3(1): 1-6.
  15. Sharma, D.K., Billore, M and Shrivastava, M. 2006. Estimation of variability parameters in black-gram (Vigna mungo L.) in Western Madhya Pradesh. Biosciences, Biotechnology Research Asia. 3
    (1a): 283-284.
  16. Shivade, H.A., Rewale, A.P and Patil, S.B. 2011. Correlation and Path analysis for yield and yield components in blackgram [Vigna mungo (L.) Hepper]. Legume Research. 34: 178-183.
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