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Research Articles

Vol. 12 No. sp3 (2025): Advances in Plant Health Improvement for Sustainable Agriculture

Genetic variability studies on yield attributing traits in Palmyrah (Borassus flabellifer L.): Implications for crop improvement

DOI
https://doi.org/10.14719/pst.8253
Submitted
14 March 2025
Published
10-07-2025

Abstract

Palmyrah is a dioecious palm, which is known for its resilience in arid and semi-arid environments. It is used to produce numerous edible and non-edible products. The association among yield-related traits and their pattern of influence are useful in evaluating and planning the selection criteria for desirable traits. The aim of this study was to examine the genetic variability and character association among the Palmyrah genotypes. A total of thirty accessions of Palmyrah were used for this study. Eleven traits contributing to growth and yield were recorded and analysed for genetic variability, correlation and path analysis. The number of bunches, single fruit weight and fruit yield per palm recorded the higher estimates of GCV and PCV. Among the eleven traits, 10 traits showed high heritability and GAM, whereas the trunk girth showed high heritability and moderate GAM. Fruit yield per palm exhibited positive correlation with trunk girth, number of bunches, number of fruits per bunch and single fruit yield. Path coefficient analysis revealed that the traits like number of bunches and single fruit weight had a positive and high direct effect on fruit yield per palm. Based on these results, Palmyrah improvement programme could be accelerated by selecting the variables that have a stronger correlation to fruit yield per palm and moderate to high estimates of PCV, GCV, heritability and high genetic advancement.

References

  1. 1. Vengaiah PC, Prasad KR, Murthy GN, Sumitha S, Jerard BA. Palmyrah (Borassus flabellifer L) tuber in India: present status and scope. Asian J Curr Res. 2024;9(2):73–80. https://doi.org/10.56557/ajocr/2024/v9i28596
  2. 2. Rao MC, Swami DV, Ashok P, Nanda SP, Rao BB. Scope, nutritional importance and value addition in palmyrah (Borassus flabellifer L.): an under exploited crop. Bioactive Compounds: Biosynthesis, Characterisation and Applications. 2021:207. https://doi.org/10.5772/intechopen.97501
  3. 3. Vengaiah PC, Kaleemullah S, Madhava M, Mani A, Sreekanth B. Some physical properties of palmyrah palm (Borassus flabellifer L.) fruits. Curr J Appl Sci Technol. 2021;40(24):18–25. https://doi.org/10.9734/cjast/2021/v40i2431498
  4. 4. Marimuthu M, Easwaran S, Guhan V, Vinoth R. Production of Nungu candy: an experimental study. Int J Plant Soil Sci. 2023;35(10):192–4. https://doi.org/10.9734/ijpss/2023/v35i103054
  5. 5. Pavithra S, Vethamoni I, Pazhanivelan S, Venkatesan K, Anand M. Phytochemical profiling of dried palmyrah haustorium powder through GC-MS analysis: unveiling novel bioactive compounds. Int J Plant Soil Sci. 2023;35(19):1235–43. https://doi.org/10.9734/ijpss/2023/v35i193662
  6. 6. Rasheed A, Hao Y, Xia X, Khan A, Xu Y, Varshney RK, et al. Crop breeding chips and genotyping platforms: progress, challenges, and perspectives. Mol Plant. 2017;10(8):1047–64. https://doi.org/10.1016/j.molp.2017.06.008
  7. 7. Agong SG, Schittenhelm S, Friedt W. Genotypic variation of Kenyan tomato (Lycopersicon esculentum L.) germplasm. J Food Technol Afr. 2001;6(1):13–7. https://doi.org/10.4314/jfta.v6i1.19277
  8. 8. Kumar N, Paul S. Selection criteria of linseed genotypes for seed yield traits through correlation, path coefficient and principal component analysis. J Anim Plant Sci. 2016;26(6).
  9. 9. Manisha RP, Vijay SK, Madhavi BB, Jadhav RD. Correlation and path analysis study in F5 generation of cowpea. Int J Curr Microbiol Appl Sci. 2018;6:1529–37.
  10. 10. Paghadar PJ, Vachhani JH, Gajera KP, Chovatiya SJ. Evaluation of correlation and path analysis in vegetable cowpea (Vigna unguiculata (L.) Walp). Int J Chem Stud. 2019;7(4):628–30.
  11. 11. Workalemahu G, Mohammed W. Correlation coefficients, path analysis and disease reaction between yield and yield components in potato (Solanum tuberosum L.) genotypes in Bale, Southeastern Ethiopia. Plant Sci Today. 2016;3(3):293–7. https://doi.org/10.14719/pst.2016.3.3.201
  12. 12. Searle SR. Phenotypic, genetic and environmental correlations. Biometrics. 1961;17(3):474–80. https://doi.org/10.2307/2527838
  13. 13. Burton GW, De Vane DE. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. https://doi.org/10.2134/agronj1953.00021962004500100005x
  14. 14. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. 1995. https://doi.org/10.2134/agronj1955.00021962004700070009x
  15. 15. Al‐Jibouri H, Miller PA, Robinson HF. Genotypic and environmental variances and covariances in an upland cotton cross of interspecific origin. Agron J. 1958;50(10):633–6. https://doi.org/10.2134/agronj1958.00021962005000100020x
  16. 16. Dewey DR, Lu K. A correlation and path‐coefficient analysis of components of crested wheatgrass seed production. Agron J. 1959;51(9):515–8. https://doi.org/10.2134/agronj1959.00021962005100090002x
  17. 17. Sivasubramaniam S, Madhava Menon P. Genotypic and phenotypic variability in rice. Madras Agric J. 1973;60(9–12):1093–6.
  18. 18. Natarajan C, Ganesamurthy K, Kavitha M. Genetic variability in coconut (Cocos nucifera). Electron J Plant Breed. 2010;1(5):1367–70.
  19. 19. Kumar DK, Lakshmana D, Nagaraja NR, Nadukeri S, Ganapathi M. Genetic variability and correlation for nut and yield characters in arecanut (Areca catechu L.) germplasm. Electron J Plant Breed. 2021;12(4):1170–7. https://doi.org/10.37992.2021.1204.161
  20. 20. Sankaran M, Damodaran V, Singh DR, Sankar IJ, Jerard BA. Genetic analysis in Pacific and Nicobar Islands coconut collections conserved at Andaman Islands, India. Indian J Hortic. 2015;72(1):117–20. https://doi.org/10.5897/AJB12.2742
  21. 21. Myint KA, Amiruddin MD, Rafii MY, Abd MY, Izan SH. Character interrelationships and path analysis for yield components in MPOB-Senegal oil palm germplasm. Sains Malays. 2021;50:699–709. https://doi.org/10.17576/jsm-2021-5003-12
  22. 22. Sathishkumar S, Thomas B, Gopi R. Intra-varietal variability in komadan coconut (Cocos nucifera L.) palms. Adv Life Sci. 2016;5(12):5074–8. https://www.indianjournals.com/ijor.aspx?target=ijor:als&volume=5&issue=12&article=058&type=pdf
  23. 23. Krualee S, Sdoodee S, Eksomtramage T, Sereeprasert V. Correlation and path analysis of palm oil yield components in oil palm (Elaeis guineensis Jacq.). Agric Nat Resour. 2013;47(4):528–33.
  24. 24. Balakrishna P, Pinnamaneni R, Pavani KV, Mathur RK. Correlation and path coefficient analysis in Indian oil palm genotypes. J Pure Appl Microbiol. 2018;12(1):195–206. https://doi.org/10.22207/JPAM.12.1.25

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