Optimal Yield Related Attributes for High Grain Yield using Ontogeny Based Sequential Path Analysis in Barnyard Millet (Echinochloa spp.)

Authors
S. Sood
R. K. Khulbe
L. Kant
Indian Council of Agricultural Research (ICAR), -Vivekananda Institute of Hill Agriculture, Almora, Uttarakhand, 263 601, India.
Abstract
Relationship between grain yield and its component traits can improve the efficiency of breeding programs by determining appropriate selection criteria. An investigation was carried out on barnyard millet (Echinochloa spp.) global germplasm collection to investigate the association among yield components and their direct and indirect effects on the grain yield of barnyard millet. The experiment was conducted in 2011 and 2012 in augmented and alpha lattice design, respectively. The results of correlation coefficients indicated that grain yield had high significant and positive association with flag leaf width and culm thickness during both years, whereas negative association of grain yield was observed with basal tillers and peduncle length. Simple path analysis indicated high direct effects of panicle exertion, flag leaf sheath length, flag leaf width and days to maturity in 2011; and flag leaf width and raceme number in 2012. However, these high direct estimates were biased due to multicolinearity. Therefore, ontogeny based sequential path analysis was used to establish the causal relationships determining grain yield in barnyard millet. Based on the results over the years, culm thickness and raceme number were found to be important traits for indirect selection. The other important traits suggested for inclusion in selection index were inflorescence length, plant height, flag leaf length, inflorescence width and number of basal tillers per plant.

Keywords

1. Gupta, A., Mahajan, V., Kumar, M. and Gupta H. S. 2009. Biodiversity in Barnyard Millet (Echinochloa frumentacea Link) Germplasm in India. Genet. Resour. Crop Evol., 56: 883-889.
2. Dalkani, M., Darvishzadeh, R. and Hassani, A. 2011. Correlation and Sequential Path Analysis in Ajowan (Carum copticum L.). J. Medicinal Plant. Res., 5 (2): 211-216.
3. Dewey, D. R. and Lu, K. H. 1959. A Correlation and Path Coefficient Analysis of Components of Crested Wheat Grass Seed Production. Agron. J., 51: 515-518.
4. Feyzian, E. Dehghani, H., Rezai, A. M. and Jalali, M. 2009. Correlation and Sequential Path Model for Some Yield-related Traits in Melon (Cucumis melo L.). J. Agri. Sci. Tech., 11: 341-353.
5. Firouzabadi, M.B., Farrokhi, N. and Parsaeyan, M. 2011. Sequential Path Analysis of Some Yeld and Quality Components in Sugar Beet Grown in Normal and Drought Conditions. Italian J. Agron., 6: 45-51.
6. Upadhyaya, H. D., Gowda, C. L. L., Pundir, R. P. S., Reddy, V. G. and Singh, S. 2006. Development of Core Subset of Finger Millet Germplasm Using Geographical Origin and Data on 14 Quantitative Traits. Genet. Resour. Crop Evol., 53: 679-685.
7. Upadhyaya, H. D., Dwivedi, S. L., Singh, S. K., Singh, S., Vetriventhan, M. and Sharma, S. 2014. Forming Core Collections in Barnyard, Kodo, and Little Millets Using Morphoagronomic Descriptors. Crop Sci., 54: 2673-2682.
8. Hair, J. R., Anderson, R. E., Tatham, R. L. and Black, W. C. 1995. Multivariate Data Analysis with Readings. Prentice Hall, Englewood.
9. IPGRI, 1983. Echinochloa Millet Descriptors. Accessed 23rd August, 2015, http://www.bioversityinternational.org/uploads/tx_news/Echinochloa_millet_descriptors_394.pdf,
10. Kozak, M. and Azevado, R. A. 2011. Does Using Stepwise Variable Selection to Build Sequential Path Analysis Models Make Sense? Physiologia Plantarum, 141: 197-200.
11. Kozak, M. and Azevedo, R. A. 2014. Sequential Path Analysis: What Does “Sequential” Mean? Sci. Agric., 71: 525-527.
12. Kozak, M., Singh, P. K., Verma, M. R. and Hore, D. K. 2007. Causal Mechanism for Determination of Grain Yield and Milling Quality of Lowland Rice. Field Crop. Res., 102: 178-184.
13. Lal, M. and Maloo, S. R. 2006. Path Coefficient Analysis for Seed Yield in Barnyard Millet (Echinochloa frumentacea). Agric. Sci. Digest, 26 (2): 151-152.
14. Li, G., Zhang, J., Yang, C., Song, Y., Zheng, C., Wang, S., Liu, Z. and Ding, Y. 2014. Optimal Yield-related Attributes of Irrigated Rice for High Yield Potential Based on Path Analysis and Stability Analysis. Crop J., 2: 235-243.
15. Malek, H. H., Karimzadeh, G., Darvishzadeh, R. and Sarrafi, A. 2011. Correlation and Sequential Path Analysis of Some Agronomic Traits in Tobacco (Nicotiana tabaccum L.) to Improve Dry Leaf Yield. Aust. J. Crop Sci., 5(12): 1644-1648.
16. Mohammadi, M., Sharifi, P. and Karimizadeh, R. 2014. Sequential Path Analysis for Determination of Relationship between Yield and Yield Components in Bread Wheat (Triticum aestivum L.). Not. Sci. Biol., 6(1): 119-124.
17. Mohammadi, S. A., Prasanna, B.M. and Singh, N. N. 2003. Sequential Path Model for Determining Interrelationships among Grain Yield and Related Characters in Maize. Crop Sci., 43: 1690- 1697.
18. Prakash, R. and Vanniarajan, C. 2014. Correlation Analysis in Barnyard Millet [Echinochloa frumentacea (Roxb.) Link]. Trend. Biosci., 7(20): 3255-3257.
19. Prakash, R. and Vanniarajan, C. 2015. Path Analysis for Grain Yield in Barnyard Millet (Echinochloa frumentacea (roxb.) Link ). Bangladesh J. Bot., 44(1): 147-150.
20. R Core Team. 2014. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. URL: http://www.R-project.org/.
21. Padulosi, S., Bhagmal, Bala Ravi, S., Gowda, J., Gowda, K.T.K., Shanthakumar, G., Yenagi, N. and Dutta, M. 2009. Food Security and Climate Change: Role of Plant Genetic Resources of Minor Millets. Indian J. Plant Genet. Resour., 22: 1-16.
22. Samonte, S. O. P. B., Wison. L. T. and McClung, A. M. 1998. Path Analysis of Yield and Yield RelatedT of Fifteen Diverse Rice Genotypes. Crop Sci., 38:1130-1136.
23. Sood, S., Khulbe, R. K., Gupta, A., Agrawal, P. K., Upadhyaya, H. D. and Bhatt, J. C. 2015. Barnyard millet- A Potential Food and Feed Crop of Future. Plant Breed., 134: 135-147.
24. Sood, S., Khulbe, R. K., Saini, N., Gupta, A. and Agrawal, P. K. 2014. Interspecific Hybrid between Echinochloa esculenta (Japanese Barnyard Millet) and E. frumentacea (Indian Barnyard Millet): A New Avenue for Genetic Enhancement of Barnyard Millet. Electron. J. Plant Breed., 5: 248-253.
25. Sonnad, S. K., Santhakumar, G. and Salimath, P. M. 2008. Genetic Variability and Character Association Studies in White Ragi (Eleusine coracana Gaertn.). Karnataka J. Agric. Sci., 21: 572-575.
26. Yabuno, T. 1987. Japanese Barnyard Millet (Echinochloa utilis, Poaceae) in Japan. Econ. Bot., 41: 484-493.
Journal of Agricultural Science and Technology
Volume 18, Issue 7
November and December 2016
Pages 1933-1944