Genetic variability, correlation and path analysis in the BC2F2 population of groundnut
DOI:
https://doi.org/10.14719/pst.3282Keywords:
Groundnut, backcross, allele specific primers, variability and associationAbstract
The present study was carried out in the backcross population of groundnut involving TMV 7 and ICG 15419. Allele-specific primers were used to screen the population for high oleic acid and a total of 11 yield-contributing traits were included in this study. The number of primary and secondary branches had higher estimates of PCV and GCV whereas pod yield per plant had moderate PCV but low GCV. Along with the variability parameters, plant height, number of primary and secondary branches, pod width, 100 pod weight, oleic acid content and linoleic acid content had good estimates of heritability and genetic advance as a percent of the mean, whereas pod yield per plant had moderate and low, heritability and GAM respectively, with a negatively significant skewed distribution. Association analysis exhibited a positive correlation between the number of primary branches, number of secondary branches, pod length and 100 pod weight with pod yield per plant and it was evident that oleic acid was indirectly proportional to linoleic acid content. Hundred pod weights had the highest direct effect on pod yield per plant. Selection based on traits with a better relationship with pod yield per plant and moderate to high estimates of PCV, GCV, heritability and genetic advancement would help in accelerating the groundnut improvement program. High oleic, low linolenic lines of BC2F2 with better pod yield would be forwarded to the next generation.
Downloads
References
Wang ML, Khera P, Pandey MK, Wang H, Qiao L, Feng S et al. Genetic mapping of QTLs controlling fatty acids provided insights into the genetic control of fatty acid synthesis pathway in peanut (Arachis hypogaea L.). Plos One. 2015;10(4):e0119454. https://doi.org/10.1371/journal.pone.0119454
Norden A, Gorbet D, Knauft D, Young C. Variability in oil quality among peanut genotypes in the Florida breeding program. Peanut Science. 1987;14(1):7-11. https://doi.org/10.3146/i0095-3679-14-1-3
Saghai-Maroof MA, Soliman KM, Jorgensen RA, Allard RW. Ribosomal DNA spacer-length polymorphisms in barley: Mendelian inheritance, chromosomal location and population dynamics. Proceedings of the National Academy of Sciences. 1984;81(24):8014-18. https://doi.org/10.1073/pnas.81.24.8014
Johnson H, Robinson H, Comostock R. Estimates of genetics and environmental variability in soybeans. Agronomy Journal. 1955;47(7):314-18. https://doi.org/10.2134/agronj1955.00021962004700070009x
Burton G, De Vane E. Estimating heritability in tall fescue (Festuca arundinacea). Agron J. 1953;45:478-81. http://dx.doi.org/10.2134/agronj1953.00021962004500100005x
Lush JL. Intra-sire correlations or regressions of offspring on dam as a method of estimating heritability of characteristics. Journal of Animal Science. 1940;1940(1):293-301. https://doi.org/10.2527/jas1940.19401293x
Allard RW. Principles of plant breeding. Soil Science. 1961;91(6):414. https://doi.org/10.1097/00010694-196106000-00017
Snedecor GW, Cochran WG. Statistical methods, 8thEdn. Ames: Iowa State Univ Press Iowa. 1989;54:71-82.
Gopinath PP, Prasad R, Joseph B, Adarsh VS. GRAPES: General R shiny based analysis platform empowered by statistics; 2020. Available from: https://www.kaugrapes.com/home.
Miller P, Williams J, Robinson H, Comstock R. Estimates of genotypic and environmental variances and covariances in upland cotton and their implications in selection 1. Agronomy Journal. 1958;50(3):126-31. https://doi.org/10.2134/agronj1958.00021962005000030004x
Allan V. PB-Perfect: A comprehensive R-based tool for plant breeding data analysis; 2023. Available from: https://allanbiotools.shinyapps.io/pbperfect/.
Dewey DR, Lu KH. A correlation and path?coefficient analysis of components of crested wheatgrass seed production 1. Agronomy Journal. 1959;51(9):515-18. https://dx.doi.org/10.2134/agronj1959.00021962005100090002x
Shasidhar Y, Variath MT, Vishwakarma MK, Manohar SS, Gangurde SS, Sriswathi M et al. Improvement of three popular Indian groundnut varieties for foliar disease resistance and high oleic acid using SSR markers and SNP array in marker-assisted backcrossing. The Crop Journal. 2020;8(1):1-15. https://doi.org/10.1016/j.cj.2019.07.001
Jadhav MP, Patil MD, Hampannavar M, Venkatesh, Dattatreya P, Shirasawa K et al. Enhancing oleic acid content in two commercially released peanut varieties through marker?assisted backcross breeding. Crop Science. 2021;61(4):2435-43. https://doi.org/10.1002/csc2.20512
Chavadhari R, Kachhadia V, Vachhani J, Virani M. Genetic variability studies in groundnut (Arachis hypogaea L.). Electronic Journal of Plant Breeding. 2017;8(4):1288-92. https://doi.org/ 10.5958/0975-928X.2017.00184.3
Motagi BN, Bhat RS, Pujer S, Nayak SN, Pasupaleti J, Pandey MK et al. Genetic enhancement of groundnut: Current status and future prospects. Accelerated Plant Breeding, Volume 4: Oil Crops. 2022;63-110. https://doi.org/10.1007/978-3-030-81107-5_3
Krishnamurthy D, Goudar P, Keerthi C. Groundnut under organic farming: Genetic variability and association studies for yield, quality and disease resistance in recombinant inbred lines. Legume Research-An International Journal. 2015;38(5):626-30. https://dx.doi.org/10.18805/lr.v38i5.5940
Yusuf Z, Zeleke H, Mohammed W, Hussein S, Hugo A. Genetic variability for oil quality traits in groundnut (Arachis hypogaea L.) cultivars. Research Journal of Agronomy. 2019;15:12-16. https://dx.doi.org/10.13140/RG.2.2.12544.43526
Sukrutha B, Akkareddy S, Vemireddy L, Kumar ARN, Latha P, Nagamadhuri K. Identification of multi-trait donor sources in groundnut (Arachis hypogaea L.) for yield and seed quality improvement. Electronic Journal of Plant Breeding. 2022;13(3):1024-35. https://dx.doi.org/ 10.5958/0976-0571.2015.00002.8
Killi F, Beycioglu T. Genetic and environmental variability, heritability and genetic advance in pod yield, yield components, oil and protein content of peanut varieties. Turkish Journal of Field Crops. 2022;27(1):71-77. https://dx.doi.org/10.17557/tjfc.1050448
Gangadhara K, Nadaf HL. Genetic analysis of oleic acid and linoleic acid content in relation to oil quality in groundnut. Electronic Journal of Plant Breeding. 2018;9(1):283-94. https://dx.doi.org/10.5958/0975-928X.2018.00033.9
Kamdar JH, Jasani MD, Bera SK, Georrge JJ. Effect of selection response for yield related traits in early and later generations of groundnut (Arachis hypogaea L.). Crop Breeding and Applied Biotechnology. 2020;20. https://doi.org/10.1590/1984-70332020v20n2a31
Mohapatra N, Khan H. Nature and degree of distribution for yield and yield attributes in F3 generations of groundnut (Arachis hypogaea L.). Journal of Pharmacognosy and Phytochemistry. 2020;9(4):453-56. https://doi.org/10.20546/ijcmas.2020.907.266
Mitra M, Gantait S, Kundu R. Genetic variability, character association and genetic divergence in groundnut (Arachis hypogaea L.) accessions. Legume Research-An International Journal. 2021;44(2):164-69. https://doi.org/10.18805/LR-4123
Gali S, Reddy D, Prasanna RA, John K, Sudhakar P, Rao VS. Correlation and path coefcient analyses in large seeded peanut (Arachis hypogaea L.) for kernel yield. Electronic Journal of Plant Breeding. 2023;14(1):272-78. https://dx.doi.org/10.37992/2023.1401.002
Kamdar J, Jasani M, Ajay B, Rani K, Manivannan N, Vasanthi R et al. Fatty acid desaturase-2 (ahFAD2) mutant alleles in peanut (Arachis hypogaea L.) pre-breeding lines: An insight into the source, features, discourse and selection of novel pre-breeding lines. Genetic Resources and Crop Evolution. 2021;68:529-49. https://doi.org/10.1007/s10722-020-00999-0
Downloads
Published
Versions
- 21-05-2024 (2)
- 12-05-2024 (1)
How to Cite
Issue
Section
License
Copyright (c) 2024 Rachel Lissy Vargheese, S. Saravanan, S. Juliet Hepziba, S.Merina Prem Kumari, A. Kavitha Pushpam, M. Arumugam Pillai
This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright and Licence details of published articles
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Open Access Policy
Plant Science Today is an open access journal. There is no registration required to read any article. All published articles are distributed under the terms of the Creative Commons Attribution License (CC Attribution 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited (https://creativecommons.org/licenses/by/4.0/). Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).