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Plant Science Today (PST)

Research Articles

Vol. 11 No. 4 (2024)

Genetic variability, character association and path analyses effects on fiber yield and yield attributing morpho-agronomic traits of tossa jute (Corchorus olitorius L.)

DOI
https://doi.org/10.14719/pst.4183
Submitted
26 June 2024
Published
21-10-2024 — Updated on 23-10-2024
Versions

Abstract

Jute (Corchorus spp.) is a natural fiber crop having a lower extent of genetic variability due to its self-pollinating nature. The success of any breeding program for variety development primarily depends on the presence of genetic variation in the parental genotypes. A field experiment was conducted in a randomized complete block design at ManikganjStation of Bangladesh Jute Research Institute (BJRI) during 2019-2020. The genetic divergence of 58 tossa jute (C. olitorius) genotypes including two pre-released standard varieties (O-9897, BJRI Tossa pat 4) and 56 accessions were studied to select genotypes having the most divergence in natural rainy condition. The jute genotypes were categorized into five clusters based on Mahalanobis D2 analysis. Cluster I and IV showed maximum inter-cluster distance (181.44) while the maximum intra-cluster distance (16.15) was recorded in cluster I. Cluster V revealed the highest values for number of nodes, stem mid-diameter, core diameter, green weight with leaves, dry stick weight and dry fiber weight per plant while cluster IV showed higher means for plant height, green bark thickness and leaf area. The highest contribution (47.14%) was wielded by plant height of total deviations. The results recommended that hybridization between genotypes of cluster V, IV and III could provide a wide range of discrepancies in the segregating generation which could offer chance for isolation of good genotypes with high fibre yielding lines.

References

  1. Aly-Hassan MS. A new perspective in multifunctional composite materials. Multifunctionality of Polymer Composites. 2015;42-67. https://doi.org/10.1016/b978-0-323-26434-1.00002-7
  2. Khan JA. Biofiber reinforcements in composite materials. The Use of Jute Fibers as Reinforcements in Composites. 2015;3-34. https://doi.org/10.1533/9781782421276.1.3
  3. Loumerem M, Alercia A. Descriptors for jute (Corchorus olitorius L.). Genet Resour Crop Evol. 2016;63:1103-11. https://doi.org/10.1007/s10722-016-0415-y
  4. Kundu BC. Origin of jute. Indian J Plant Breed. 1951;11(1):95-99. http://www.isg pb.org/documents/archive/vol-11-no-1-1951.pdf.
  5. Edmonds JM. Herbarium survey of African Corchorus L. species. Systematic and Ecogeographic Studies on Crop Gene pools, Intonational Board for Plant Genetic Resources, Rome, Italy. 1990;4:284. https://cgspace.cgiar.org/handle/10568/104425
  6. FAO- Food and Agricultural Organization. Statistics on Jute, Kenaf and Allied Fibers. 2023.
  7. Kundu A, Topdar N, Sarkar D, Sinha MK, Ghosh A, Banerjee S, et al. Origins of white (Corchorus capsularis L.) and dark (C. olitorius L.) jute: a reevaluation based on nuclear and chloroplast microsatellites. Journal of Plant Biochemistry and Biotechnology. 2012;22(4):372-81. https://doi.org/10.1007/s13562-012-0165-7
  8. Andriesse W, Giller K, Jiggins J, Löffler H, Oosterveer P, Woodhill J. The role of agriculture in achieving MDG1. A Review of the Leading Reports, Wageningen International, Wageningen, The Netherlands. 2007; p 88.
  9. BBS-Bangladesh Bureau of Statistics, Estimates of Jute, Agriculture Wing. 2017-2018.
  10. BJRI-Genetic resources of jute, kenaf and mesta crops. Bangladesh Jute Research Institute, Manik Mia Avenue, Ministry of Agriculture, Dhaka-1207, Bangladesh. 2022. www.bjri.gov.bd
  11. Panse VG, Sukhatme PV. Statistical methods for agricultural workers (2nd Edition). Indian Council of Agricultural Research (ICAR), New Delhi. 1967;XVI+381. https://opac.narc.gov.np/opac_css/index.php?lvl=notice_display&id=1114
  12. Gomez KA, Gomez AA. Statistical procedures for agricultural research, Wiley India (P) Ltd., New Delhi, India. 1984.
  13. R Core Team, R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria. 2021. URL: https://www.R-project.org/
  14. Minitab, Minitab Statistical Software, U/o Cubic Computing (P) Ltd., Karnataka, India. 2019. http://www.minitab.com
  15. Burton GW. Quantitative inheritance in grasses, Proceedings of the Sixth International Grassland Congress, State College, Pa., 1952, Washington. DC. 1953;1: 277-83.
  16. Burton GW, DeVane EH. Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agronomy Journal. 1953;45(10):478. https://doi.org/10.2134/agronj1953.00021962004500100005x
  17. Johnson HW, Robinson HF, Comstock RE. Estimates of genetic and environmental variability in soybeans. Agronomy Journal. 1955;47(7): 314. https://doi.org/10.2134/agronj1955.00021962004700070009x
  18. Khan MMH, Rafii MY, Ramlee SI, Jusoh M, Mamun A. Genetic variability, heritability and clustering pattern exploration of Bambara groundnut (Vigna subterranea L. Verdc) accessions for the perfection of yield and yield-related traits. BioMed Res Intl. 2020;1-31. https://doi.org/10.1155/2020/2195797
  19. Singh D, Lawrence K, Marker S, Bhattacharjee I, Lawrence R, Choudhary R, et al. Rainfed assessment of foxtail millet (Setaria italica L. Beauv) germplasms through genotyping and principal component analysis. Front Plant Sci. 2023;14:1-18. https://doi.org/10.3389/fpls.2023.1017652
  20. Singh PK, Choudhary RD. Biometrical methods in quantitative genetic analysis. Kalayani Publishers, New Delhi. 1997;178-85.
  21. Bhandari HR, Bhanu AN, Srivastava K, Singh MN, Shreya HA. Assessment of genetic diversity in crop plants - An overview. Advances Plants Agric Res. 2017;7:279-86. https://doi.org/10.15406/ apar.2017.07.00255
  22. Olanrewaju OS, Oyatomi O, Babalola OO, Abberton M. Genetic diversity and environmental influence on growth and yield parameters of bambara groundnut. Front Plant Sci. 2021;12:1-15. https://doi.org/10.3389/fpls.2021.796352
  23. Brunda SM, Kamatar MY, Naveen KL, Hundekar R. Study of genetic variability, heritability and genetic advance in foxtail millet in both rainy and post rainy season. J Agri Vet Sci. 2014;7:34-37. https://doi.org/10.9790/2380-071133437
  24. Ghosh T. Handbook on jute, FAO Plant Production and Protection Paper. 1983;51:1-219. https://books.google.com.bd/books?id=cOmqa2fIQJcC&printsec=frontcover
  25. Khatun R, Hossain MA, Rashid MH, Bhuiyan MSH, Al-Mamun M. Correlation and regression between fibre yield and other plant characters in tossa jute. Int J Biol Biotech. 2007;4(4): 399-401.
  26. Sawarkar A, Yumnam S, Patil SG, Mikherjee S. Correlation and path coefficient analysis of yield and its attributing traits in tossa jute (Corchorus olitorius L.). The Bioscan J. 2014;9(2):883-87.
  27. Singh RK, Chaudhary BD. Biometrical methods in quantitative genetic analysis. Kalyani Publishers, New Delhi-Ludhiana, India. 1985;318.
  28. Patel RP, Kumar RR, Singh R, Singh RR, Rao BRR, Singh VR, Lal RK. Study of genetic variability pattern and their possibility of exploitation in Ocimum germplasm. Industrial Crops and Products. 2015;66:119-22. https://doi.org/10.1016/j.indcrop.2014.12.043
  29. Ivy NA, Uddin MS, Sultana R, Masud MM. Genetic divergence in maize (Zea mays L.). Bangladesh Journal of Plant Breeding and Genetics. 2007;20(1):53-56. https://doi.org/10.3329/bjpbg.v20i1.17027
  30. Azam MGA, Sarker UKS, Mian MAKM, Banik BRB, Talukder MZA. Genetic divergence on quantitative characters of exotic maize inbreds (Zea mays L.), Bangladesh Journal of Plant Breeding and Genetics. 2013;26(2):9-14. https://doi.org/10.3329/bjpbg.v26i2.23844
  31. Alam MA, Khan AA, Islam MR, Ahmed KU, Khaldun ABM. Studies on genetic divergence in maize (Zea mays L.) inbreeds. Bangladesh J Agril Res. 2013;38(1):71-76. https://doi.org/10.3329/bjar.v38i1.15191
  32. Lakshmi NJ, Vanaja M, Yadav SK, Patil A, Prasad CR, Sathish P, et al. Assessing genetic diversity of maize genotypes for transpiration efficiency. Electronic Journal of Plant Breeding. 2020;11(3):822-30. https://doi.org/10.37992/2020.1103.135
  33. Mukul MM, N Akter. Morpho-anatomical variability, principal component analysis and Euclidean clustering of tossa jute (Corchorus olitorius L.), Heliyon, Elsevier. 2021a;7(5):e07042. https://doi.org/10.1016/j.heliyon.2021.e07042
  34. Sawarkar A, Pradhan A, Yumnam S, Raman RB, Ghosh SC, Mukherjee S. Principal component analysis, Euclidean clustering of tossa jute (Corchorus olitorius L.) genotypes for the drought stress tolerance. International Journal of Agriculture Sciences. 2022;14(12):12126-33.
  35. Mukul MM. Elucidation of genotypic variability, character association and genetic diversity for stem anatomy of twelve tossa jute (Corchorus olitorius L.) genotypes. Hindawi-BioMed Research International. 2020;1-16. https://doi.org/10.1155/2020/9424725
  36. Asadi, Dewi N, Nugroho K, Terryana RT, Mastur, Lestari P. Evaluation of SSR and important agronomical characters of promising mutant lines of soybean. Biodiversitas Journal of Biological Diversity. 2020;21(1):299-310. https://doi.org/10.13057/biodiv/d210137
  37. Ngomuo M, Stoilova T, Feyissa T, Ndakidemi PA. Characterization of morphological diversity of jute mallow (Corchorus spp.). Hindawi, International Journal of Agronomy. 2017;1-12. https://doi.org/10.1155/2017/6460498
  38. Mukul MM, Akter N, Ahmed SSU, et al. Analyses of genetic variability, character association, heritability and genetic advance of tossa jute (Corchorus olitorius) genotypes for morphology and stem anatomy. American Journal of BioScience. 2020b;8(4):99-112. https://doi.org/10.11648/j.ajbio.20200804.12
  39. Al-Mamun M, Hossain MS, Khatun R, Yahiya ASM, Islam MM. Genetic variability, character association and path analysis of white jute (Corchorus capsularis L.). J Sher-e-Bangla Agric Univ. 2010;4(1):39-42. http://www.saulibrary.edu.bd/sauj/jsau/v.4.n.1/v.4.n.1.a.7.pdf
  40. Nyadanu D, Adu Amoah R, Kwarteng AO, Akromah R, Aboagye LM, Adu-Dapaah H, et al. Domestication of jute mallow (Corchorus olitorius L.): Ethnobotany, production constraints and phenomics of local cultivars in Ghana. Genet Resour Crop Evol. 2017;64(6):1313-29. https://doi.org/10.1007/s10722-016-0438-4
  41. Mukul MM, Akter N, Islam MM, et al. Morpho-phenetical study of high yielding tossa jute variety BJRI Tossa Pat 7 (MG-1) for bast fibre yield and qualities. Heliyon, Elsevier. 2021b;7(10):1-17. https://doi.org/10.1016/j.heliyon.2021.e08129
  42. Mukul MM. Genetic analyses of morphological traits and phenotypic screening of tossa jute germplasm grown under salinity stress. Heliyon, Elsevier. 2023;9(1):1-14. https://doi.org/10.1016/j.heliyon.2022.e12448
  43. Islam MM, Ali MA, Bhuiyau MSR, Rahman MM, Yahiya ASM. Genetic variability, correlation and path analysis in tossa jute (Corchorus olitorius L.) germplasm. Sher-e-Bangla Agric Univ. 2009;2(2):94-98.
  44. Das A, Kumar D. Genetic divergence and character association for yield and quality attributing characters in tossa jute (Corchorus olitorius L.). Electronic Journal of Plant Breeding. 2016;7(3):529-37. https://doi.org/10.5958/0975-928X.2016.00068.5
  45. Mukul MM, Ahmed SSU, Akter N, et al. Responses of seed germination, seedling growth under salinity stresses and variability for phenotypic traits in tossa jute (Corchorus olitorius L.). Plant Science Today. 2021c;8(2):416-24. https://doi.org/10.14719/pst.2021.8.1.999
  46. Nachimuthu VV, Robin S, Sudhakar D, Raveendran M, Rajeswari S, Manonmani S. Evaluation of rice genetic diversity and variability in a population panel by principal component analysis. Indian J Sci Technol. 2014;7(10):1555-62. https://doi.org/10.17485/ijst/2014/ v7i10.14
  47. Kar CS, Kundu A, Sarkar D, Sinha MK, Mahapatra BS. Genetic diversity in jute (Corchorus spp.) and its utilization: A review. Indian J Agric Sci. 2009;79(8):575-86. https://epubs.icar.org.in/index.php/IJAgS/article/view/2454
  48. Choudhary SB, Sharma HK, Karmakar PG, Kumar AA, Saha AR, Hazra P, Mahapatra BS. Nutritional profile of cultivated and wild jute (Corchorus) species. Aust J Crop Sci. 2013;7:1973-82. http://www.cropj.com/choudhary_7_13_2013_1973_1982.pdf
  49. Ghosh RK, Sreewongchai T, Nakasathien S, Phumichai C. Phenotypic variation and the relationships among jute (Corchorus species) genotypes using morpho-agronomic traits and multivariate analysis. Australian Journal of Crop Science. 2013;7(6):830-42. https://www.cropj.com/phumichai_7_6_2013_830_842.pdf
  50. Mukul MM, Akter N, Mostofa MG, Rahman MS, et al. Analyses of variability, Euclidean clustering and principal components for genetic diversity of eight tossa jute (Corchorus olitorius L.) genotypes. Plant Science Today. 2020c;7(4):564-76. https://doi.org/10.14719/pst.2020.7.4.854
  51. Mukul MM. Nutraceutical diversity of eco-friendly jute and allied fiber (JAF) crops in Bangladesh (Chapter). Intech Open, UK. 14 June, 2022. https://doi.org/10.5772/intechopen.102664

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