TRAIT ASSOCIATION ANALYSIS AND DIVERSITY ASSESSMENT IN BROWN TOP MILLET (Brachiaria ramose L.) GERMPLASM LINES
539 / 62
Authors
-
ANAND KUMAR
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
-
SK. SAMEENA
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
-
K. SRAVAN SIMHA REDDY
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
-
S. ANANDA RAJA KUMAR
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
-
P. CHANDRA OBUL REDDY
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
-
C. V. C. M. REDDY
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
-
A. CHANDRA SEKHAR
Molecular Genetics and Functional Genomics Laboratory, Department of Biotechnology School of Life Sciences, Yogi Vemana University Kadapa - 516 005
Keywords:
Browntop millet, GCV, Hierarchical Cluster Analysis, PCA, PCVAbstract
The experiment was conducted during the year Rabi 2022. Eight purelines developed by the SSD method have been assessed along with six lines collected from RARS, Nandyal for various phenotypic traits such as number of tillers, plant height, days to 50% flowering, flag leaf length, number of leaves per plant, primary rachis length, panicle exertion length, types of panicle, length of panicle, days to maturity, panicle weight, and 1000 grain weight were recorded. Significant variation has been observed for most of the traits such as maturity days (76-83 days), days to 50% flowering (52.6-67 days), plant height (15- 30 inch), leaves number (19-24), primary rachis length (2.7-7.1 inch), flag leaf length (4.6-7.3 inch), panicle exertion length (1.43-2.33 inch), panicle length (4.7-9.1 inch), panicle weight (0.7-2.6 gm), panicle types (open and close), number of tillers (2-4) and 1000 grain weight (0.67-2.05 gm). Path coefficient, genotypic coefficient variation, and phenotypic coefficient variation facilitate understanding the trait association influenced by genetic and environmental factors. There was a strong positive correlation between the panicle effect and the weight of 1000 grains. High heritability was observed for the trait panicle type (100%), followed by 1000 grain weight (88%), primary rachis length (80.83%), panicle weight (70.6%), panicle exertion length (63.52) and panicle length (53.48). PC score illustrated, BTM-6 with the highest PC score (3.43) followed by BTM-7 (1.95), BTM-2 (0.89, and BTM-5 (0.83). The present study signifies the genotypic and phenotypic variability in browntop millet with respect to the quantitative and qualitative traits with breeding importance.
References
1. Anuradha, N., Patro, T.S.S.K., Triveni, U., Rao,
2. P.J and Rajkumar, S. 2020. Trait
3. association and genetic variability in
4. browntop millet. Journal of
5. Pharmacognosy and Phytochemistry.
6. (1): 1950-1953.
7. APEDA, 2024 https://apeda.gov.in/milletportal/
8. Production.html
9. Ashoka, P and Sunitha, N.H. 2020. Review on
10. browntop millet-a forgotten crop. Journal
11. of Experimental Agriculture International.
12. (7): 54-60.
13. Babu, B.K., Sood, S., Agrawal, P.K.,
14. Chandrashekara, C., Kumar, A and
15. Kumar, A. 2017. Molecular and
16. phenotypic characterization of 149 finger
17. millet accessions using microsatellite and
18. agro-morphological markers.
19. Proceedings of the National Academy of
20. Sciences, India Section B: Biological
21. Sciences. 87: 1217-1228.
22. Chaudhary, S., Sagar, P., Hooda, B.K and Arya,
23. R.K. 2015. Multivariate analysis of pearl
24. millet data to delineate genetic
25. variation. Forage Research. 40(4): 201-
26. Clayton, W.D., Vorontsova, M.S., Harman, K.T
27. and Williamson, H. 2006. GrassBase-the
28. online world grass flora.
29. FAOSTAT, 2024. https://www.fao.org/faostat/
30. en/#data/QCL/visualize
31. Gana, A.S., Shaba, S.Z and Tsado, E.K. 2013.
32. Principal component analysis of
33. morphological traits in thirty-nine
34. accessions of rice (Oryza sativa L.)
35. grown in a rainfed lowland ecology of
36. Nigeria. Journal of Plant Breeding and
37. Crop Science. 5(10): 120-126.
38. Kandel, M., Dhami, N.B and Shrestha, J. 2019.
39. Phenotypic diversity of finger millet
40. (Eleusine coracana (L.) Gaertn.)
41. genotypes. Malaysian Journal of
42. Sustainable Agriculture. 3(2): 20-26.
43. Mahajan, P., Bera, M.B., Panesar, P.S and
44. Chauhan, A. 2021. Millet starch: A
45. review. International Journal of Biological
46. Macromolecules. 180: 61-79.
47. Maji, A.T and Shaibu, A.A. 2012. Application
48. of principal component analysis for rice
49. germplasm characterization and
50. evaluation. Journal of Plant Breeding
51. and Crop Science. 4(6): 87-93.
52. Mokkaraj, J and Geethanjali, S. 2016. Genetic
53. Diversity and Variability in Foxtail millet
54. (Setaria italica L.) Germplasm based on
55. morphological traits. Electronic Journal
56. of Plant Breeding, 7(2): 303-316.
57. Nirubana, V., Ravikesavan, R and
58. Ganesamurthy, K. 2019.
59. Characterization and clustering of kodo
60. millet (Paspalum scrobiculatum L.)
61. genotypes based on qualitative
62. characters. Electronic Journal of Plant
63. Breeding. 10 (1): 101-110.
64. Ramesh, P., Juturu, V.N., Yugandhar, P.,
65. Pedersen, S., Hemasundar, A., Yolcu, S.,
66. Chandra O. Reddy, P., Chandra Mohan
67. Reddy, C.V., Veerabramha Chari, P.,
68. Mohan, R. and Chandra Sekhar, A. 2023.
69. Molecular genetics and phenotypic
70. assessment of foxtail millet (Setaria
71. italica (L.) P. Beauv.) landraces revealed
72. remarkable variability of morphophysiological,
73. yield, and yield related
74. traits. Frontiers in Genetics. 14:
75. Sameena, S., Kumar, A., Reddy, K. S. S.,
76. Kumar, S. A. R., Kola, G., Gunti, M., Puli,
77. Reddy, P.C.O., Reddy, C. V. C. M and
78. Sekhar, A. C. 2024. ICPOES Based seed
79. micronutrient content analysis as Tool to
80. identify Allelic Sergeants’ in a Stable RIL
81. mapping population of Foxtail millet
82. (Setaria italica L.). Indian Journal of
83. Applied and Pure Biology. 39(2): 1117-
84. Shashibhushan, D., Kumar, C.S and Kondi,
85. R.K.R. 2022. Genetic diversity analysis
86. of Pearl Millet germplasm by cluster
87. analysis. Emergent Life Sciences
88. Research. 8: 70-74.
89. Sheahan, C.M. 2014. Plant guide for browntop
90. millet (Urochloa ramosa). USDA-Natural
91. Resources Conservation Service, Cape
92. May Plant Materials Center, Cape May,
93. NJ.
94. Singh, P., Jain, P.K and Tiwari, A. 2020.
95. Principal component analysis approach
96. for yield attributing traits in chilli
97. (Capsicum annum L.)
98. genotypes. Chemical Science Review
99. and Letters. 9(33): 87-91.
100. Uddin, M.S., Azam, M.G., Bagum, S.A and
101. Hakim, M.A. 2020. Genetic diversity
102. analysis of proso millet (Panicum
103. miliaceum L.) in relation to phenotypic
104. characters. Journal of Agricultural
105. Science and Engineering Innovation
106. (JASEI). 1(2): 18-22.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The author owns the article's copyright until the article is accepted for publication. After acceptance, the author(s) assigns the article's copyright jointly to both the authors and the Publishers of the Journal of Research ANGRAU (ANGRAU) and licensed under a Creative Commons Attribution-Non Commercial-Share Alike 4.0 International License.
