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Current IssueEditorial BoardOnline First ArticlesArchive

Research Article

volume 52 issue 4 (august 2018) : 386-391,   Doi: 10.18805/IJARe.A-4983

Evaluation of wheat genotypes (Triticum aestivum L.) for assessment of character association, path coefficient and cluster analysis

A
Anuj Kumar
S
Shailendra Singh Gaurav
T
Tejbir Singh
R
Ravi Singh Thapa
Cite article:- Kumar Anuj, Gaurav Singh Shailendra, Singh Tejbir, Thapa Singh Ravi (2018). Evaluation of wheat genotypes (Triticum aestivum L.) for assessment of character association, path coefficient and cluster analysis. Indian Journal of Agricultural Research. 52(4): 386-391. doi: 10.18805/IJARe.A-4983.

ABSTRACT

Thirty wheat genotypes (Triticum aestivum L.) were evaluated for 11 morphological and yield trait for analysis of character association (phenotypic and genotypic correlation coefficient), path analysis and cluster analysis. The experiment was conducted during rabi seasons of 2014-2015 in a randomized block design with three replication. Days to 50% heading showed positive and significant correlation with  flag leaf area and number of spiklet per ear; flag leaf area showed positive and significant correlation with 1000 grain weight; Plant height  showed positive and significant correlation with  spike length; spike length  showed positive and significant correlation with  1000 grain weight. Phenotypic path analysis showed  biological yield and number of grain per spike had highly positive and direct effect on grain yield. Direct and highly positive effect on grain yield was shown by number of productive tillers, plant height, spike length, number of spikelet per spike genotypic path coefficient. Biological yield and grains yield per plant show highly positive and direct effect on yield with number of productive tillers, plant height, number of spikelet per spike and spike length. In  cluster analysis the intra cluster distance ranged from 1.61 (cluster II) to 2.37 (cluster III and VI ). Thus the member of cluster II were  least divergent and similarly the  member of cluster III and IV were most divergent  The maximum inter cluster distance was between cluster II and III followed by cluster IV  and V , cluster VI and  III and cluster VI and  V that order therefore the accessions grouped in the five pair of cluster may be considered as most divergent.

REFERENCES

  1. Aharizad, S., Sabzi, M., Mohammadi, S.A., Khodadadi, E.(2012). Multivariate analysis of genetic diversity in wheat (Triticum aestivum L.) recombinant inbreed lines using agronomic traits. Annals of Biological Research. 3(5):2118-2126.
  2. Ahlawat, S., Chabra, A.K., Behl, R.K., Bist S.S. (2008). Genotypic divergence analysis for stay green characters in wheat (Triticum aestivum L.). The South Pacific Journal of Natural Science.26:73-81.
  3. Ali, Y., Atta, B.M., Akhter, J, Monneveux, P., Lateef, Z. (2008). Genetic variability, association anddiversity studies in wheat (Triticum aestivum L.)germplasm. Pak. J. Bot., 40: 2087-2097.
  4. Al-Jibouri, H.A., Miller, P.A., Robinson, H.P. (1958).Genotypic and phenotypic co variances in an upland cotton cross of interspecificorigin. Agronomy Journal.; 50:633-636.
  5. Dewey, D.R. and Lu , K.H. (1959). Correlation and path coefficient analysis of components of crested wheatgrass seedproduction. Agron. J. 51: 515-518.
  6. Hama, S.J., Ober, B., Rshead,K. (2016). The simple correlation coefficient and path analysisof grain yield and its related components for some genotypes of wheat (Triticum aestivum L.) for two seasons in Iraqi Kurdistan. Journal of Medicinal Plants Studies 4(1): 68-70
  7. Islam, S. And Begum, S.N. (2012).Molecular characterization of wheat (Triticum aestivuml.) genotypes through SSR markers. Bangl. J. Agril. Res. 37(3): 389-398
  8. Kalimullah,S., Khan, J. Irfaq, M., Rahman, H.U. (2012). Genetic variability, correlation and diversity studies in bread wheat (Triticum    aestivum L.) germplasm. J.Ani. P. Sci.,22(2): 330-333.
  9. Khan S.A. (2013)Genetic variability and heritability estimates in F2 wheat genotypes . Inter. J. Agri. Crop. Sci.5(9):983-986.
  10. Khodadadi, M.H., Fotokin, Miransari (2011). Genetic diversity of wheat (Triticum aestivum L.) genotypes ased on cluster and principal components analysis for breeding strategies. A. J. C. S. 5(1): 17-24.
  11. Kumar, S., Gaurav, S.S., Bhusan, B., Pal, R. (2013).Study of genetic parameter and genetic divergence for yield and yield components of bread wheat (Triticum aestivum L.) Biosci. Dis.5(1): 64-69.
  12. Mohamed, N.A. (1999). Some statistical procedures for evaluation of the relative contribution for yield components in wheat. Zagazig Journal Agriculture Research 26(2) 281–290.
  13. Mollasadeghi, V., Elyasi, S., Mirzamasoumzadeh, B. (2012). Genetic variation of 12 bread wheat genotypes based on number of physiological and morphological traits. Annals of Biological Research 3(10): 4734-4740.
  14. Rohani, S.K. and Marker, S. (2016). Correlation and path coefficient analysis of some quantitative traits in wheat (Triticuma estivum L.) Int. J. Multidis. Res. Dev.,3:(7), 15-20
  15. Singh, S.P. and Diwivedi, V.K. (2002). Character association and path analysis in wheat (Triticum aestivum L.). Agricultural Science Digest 22(4) 255 - 257.
  16. Tahmasebi, G., Heydarnezhadian, J., Aboughadareh, A.P. (2013). Evaluation of yield and yield components in some of promising wheat lines. Inter. J. Agri. Crop Sci. 5(20)L: 2379 -2384. 
  17. Talebi, R and Fayyaz, F. (2012). Quantitative evaluation of genetic diversity in Iranian modern cultivar of wheat (Triticum aestivum L.) using morphological and amplified fragment length polymorphism (AFLP) markers. Biharean biologist 6(1): 14-18.
  18. Valencia, J.A., Falaki, A.M., Miko, S., Mohammed, I.B., Abubakar, I.U. (2009). Evaluaton of some improved bread wheatvarieties at Chiyako, Jigawa state, Nigeria. ARPN J. Agri.bio. Sci., 4(4):4
  19. Zafarnaderi, N., Aharizad, S., Mohammadi, S.A. (2013) Relationship be­tween grain yield and related agronomic traits in bread wheat re­combinant inbred lines under water deficit condition. Ann Biol Res 4(4): 7-11. 
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Indian Journal of Agricultural Research
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    Research Article

    volume 52 issue 4 (august 2018) : 386-391,   Doi: 10.18805/IJARe.A-4983

    Evaluation of wheat genotypes (Triticum aestivum L.) for assessment of character association, path coefficient and cluster analysis

    A
    Anuj Kumar
    S
    Shailendra Singh Gaurav
    T
    Tejbir Singh
    R
    Ravi Singh Thapa
    Cite article:- Kumar Anuj, Gaurav Singh Shailendra, Singh Tejbir, Thapa Singh Ravi (2018). Evaluation of wheat genotypes (Triticum aestivum L.) for assessment of character association, path coefficient and cluster analysis. Indian Journal of Agricultural Research. 52(4): 386-391. doi: 10.18805/IJARe.A-4983.

    ABSTRACT

    Thirty wheat genotypes (Triticum aestivum L.) were evaluated for 11 morphological and yield trait for analysis of character association (phenotypic and genotypic correlation coefficient), path analysis and cluster analysis. The experiment was conducted during rabi seasons of 2014-2015 in a randomized block design with three replication. Days to 50% heading showed positive and significant correlation with  flag leaf area and number of spiklet per ear; flag leaf area showed positive and significant correlation with 1000 grain weight; Plant height  showed positive and significant correlation with  spike length; spike length  showed positive and significant correlation with  1000 grain weight. Phenotypic path analysis showed  biological yield and number of grain per spike had highly positive and direct effect on grain yield. Direct and highly positive effect on grain yield was shown by number of productive tillers, plant height, spike length, number of spikelet per spike genotypic path coefficient. Biological yield and grains yield per plant show highly positive and direct effect on yield with number of productive tillers, plant height, number of spikelet per spike and spike length. In  cluster analysis the intra cluster distance ranged from 1.61 (cluster II) to 2.37 (cluster III and VI ). Thus the member of cluster II were  least divergent and similarly the  member of cluster III and IV were most divergent  The maximum inter cluster distance was between cluster II and III followed by cluster IV  and V , cluster VI and  III and cluster VI and  V that order therefore the accessions grouped in the five pair of cluster may be considered as most divergent.

    REFERENCES

    1. Aharizad, S., Sabzi, M., Mohammadi, S.A., Khodadadi, E.(2012). Multivariate analysis of genetic diversity in wheat (Triticum aestivum L.) recombinant inbreed lines using agronomic traits. Annals of Biological Research. 3(5):2118-2126.
    2. Ahlawat, S., Chabra, A.K., Behl, R.K., Bist S.S. (2008). Genotypic divergence analysis for stay green characters in wheat (Triticum aestivum L.). The South Pacific Journal of Natural Science.26:73-81.
    3. Ali, Y., Atta, B.M., Akhter, J, Monneveux, P., Lateef, Z. (2008). Genetic variability, association anddiversity studies in wheat (Triticum aestivum L.)germplasm. Pak. J. Bot., 40: 2087-2097.
    4. Al-Jibouri, H.A., Miller, P.A., Robinson, H.P. (1958).Genotypic and phenotypic co variances in an upland cotton cross of interspecificorigin. Agronomy Journal.; 50:633-636.
    5. Dewey, D.R. and Lu , K.H. (1959). Correlation and path coefficient analysis of components of crested wheatgrass seedproduction. Agron. J. 51: 515-518.
    6. Hama, S.J., Ober, B., Rshead,K. (2016). The simple correlation coefficient and path analysisof grain yield and its related components for some genotypes of wheat (Triticum aestivum L.) for two seasons in Iraqi Kurdistan. Journal of Medicinal Plants Studies 4(1): 68-70
    7. Islam, S. And Begum, S.N. (2012).Molecular characterization of wheat (Triticum aestivuml.) genotypes through SSR markers. Bangl. J. Agril. Res. 37(3): 389-398
    8. Kalimullah,S., Khan, J. Irfaq, M., Rahman, H.U. (2012). Genetic variability, correlation and diversity studies in bread wheat (Triticum    aestivum L.) germplasm. J.Ani. P. Sci.,22(2): 330-333.
    9. Khan S.A. (2013)Genetic variability and heritability estimates in F2 wheat genotypes . Inter. J. Agri. Crop. Sci.5(9):983-986.
    10. Khodadadi, M.H., Fotokin, Miransari (2011). Genetic diversity of wheat (Triticum aestivum L.) genotypes ased on cluster and principal components analysis for breeding strategies. A. J. C. S. 5(1): 17-24.
    11. Kumar, S., Gaurav, S.S., Bhusan, B., Pal, R. (2013).Study of genetic parameter and genetic divergence for yield and yield components of bread wheat (Triticum aestivum L.) Biosci. Dis.5(1): 64-69.
    12. Mohamed, N.A. (1999). Some statistical procedures for evaluation of the relative contribution for yield components in wheat. Zagazig Journal Agriculture Research 26(2) 281–290.
    13. Mollasadeghi, V., Elyasi, S., Mirzamasoumzadeh, B. (2012). Genetic variation of 12 bread wheat genotypes based on number of physiological and morphological traits. Annals of Biological Research 3(10): 4734-4740.
    14. Rohani, S.K. and Marker, S. (2016). Correlation and path coefficient analysis of some quantitative traits in wheat (Triticuma estivum L.) Int. J. Multidis. Res. Dev.,3:(7), 15-20
    15. Singh, S.P. and Diwivedi, V.K. (2002). Character association and path analysis in wheat (Triticum aestivum L.). Agricultural Science Digest 22(4) 255 - 257.
    16. Tahmasebi, G., Heydarnezhadian, J., Aboughadareh, A.P. (2013). Evaluation of yield and yield components in some of promising wheat lines. Inter. J. Agri. Crop Sci. 5(20)L: 2379 -2384. 
    17. Talebi, R and Fayyaz, F. (2012). Quantitative evaluation of genetic diversity in Iranian modern cultivar of wheat (Triticum aestivum L.) using morphological and amplified fragment length polymorphism (AFLP) markers. Biharean biologist 6(1): 14-18.
    18. Valencia, J.A., Falaki, A.M., Miko, S., Mohammed, I.B., Abubakar, I.U. (2009). Evaluaton of some improved bread wheatvarieties at Chiyako, Jigawa state, Nigeria. ARPN J. Agri.bio. Sci., 4(4):4
    19. Zafarnaderi, N., Aharizad, S., Mohammadi, S.A. (2013) Relationship be­tween grain yield and related agronomic traits in bread wheat re­combinant inbred lines under water deficit condition. Ann Biol Res 4(4): 7-11. 
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