Legume Research

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Legume Research, volume 34 issue 1 (march 2011) : 41- 44

CORRELATION AND PATH ANALYSIS STUDIES IN F3 POPULATION OF COWPEA (Vigna unguiculata (L.) Walp.)

D. Bhardu*, P.A. Navale
1Department of Agricultural Botany, College of Agriculture, MPKV, Pune - 411004, India
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Cite article:- Bhardu* D., Navale P.A. (2024). CORRELATION AND PATH ANALYSIS STUDIES IN F3 POPULATION OF COWPEA (Vigna unguiculata (L.) Walp.). Legume Research. 34(1): 41- 44. doi: .
An investigation was carried out in F3 population of cross Dapoli safed x GC-10 and their parents to understand the association among the yield components and their direct and indirect effects on the seed yield. Grain yield per plant recorded significant and positive correlation with number of pods per plant, biomass at harvest, number of branches per plant, test weight, pod length, and vine length. Number of pods per plant recorded highest magnitude of direct effects on seed yield per plant followed by test weight, biomass at harvest and number of branches per plant. Hence, selection on the basis of high biomass at harvest, number of pods per plant, test weight, pod length, number of branches per plant and seed yield per plant in segregating populations of cowpea will be more effective in the development of promising genotypes.
  1. Anbumalarmathi J, Sheeba,.A and Deepasankar P. (2005) Res. On Crops 6(3):517-519.
  2. Cristiane Lopes Carneiro de Souza, Angela Celis de Almedia Lopes, Regina Lucia Ferreira Gomes, Maurisrael De Moura Rocha and Erismar Mesuita Silva (2007) Crop Breeding and Applied Biotechnology 7:262-269.
  3. Dewey,D.R., Lu, H. K. (1959). Agron. J. 51 (6): 515-518.
  4. Lal H, Rai M, Karan S, Verma A and Ram D (2006) ISHS Acta Horticulturae 752: I International Conference on Indigenous Vegetables and Legumes. Prospectus for Fighting Poverty, Hunger and Malnutrition
  5. Nath, Vishwa, Lal H, Rai .M, Rai. N and Ram. D (2009) Indian J. Plant Genet. Resou., 22 (1)
  6. Nigude, A. D, Dumbre, A. D, Lad, D. B. and Banger, N. D. (2004) J. Maharashtra agric. Univ. 29 (1): 13-18.
  7. Sheela Mary,.S. and Gopaln A. (2006) J. Appl Sci.Res, 2 (10):687-690.
  8. Singh, R.K, and Chaudary, B. D. (1977) Biometrical methods in quantitatnic genetic analysis, Kalyani pub., New Delhi.Pp.39-68.
  9. Suma Biradar, Salimath. P.M and Sridevi.O (2007) Karnataka J. Agric. Sci., 20 (2): 525-524.

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