Investigating How Seed Yield is Influenced by Different Agronomic Traits in Local Sesame (Sesamum indicum L.) Lines Through the Utilization of Path Analysis and Principal Components Analysis

Document Type : Research Article

Authors

1 Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

2 Seed and Plant Improvement Research Department, South Kerman Agricultural and Natural Resources Research and Education Center, AREEO, Jiroft, Iran

3 Seed and Plant Improvement Department, Ardabil Agricultural and Natural Resources Research Center, AREEO, Ardabil, Iran

Abstract

Introduction
The importance of sesame (Sesamum indicum L.) as a key crop in numerous regions can be attributed to its adaptability to dry climates, the nutritional value of its oil, and its health advantages. The necessity of improving the sesame plant is important by its comparatively low yield. The use of improved cultivars by plant breeding and breeding methods has resulted in a higher yield and higher quality of crops, which in the case of sesame plants include a greater increase in the seed yield and improvement in its quality. In a breeding program, increasing genetic diversity enhances the ability to select superior genotypes, and a more efficient selection process contributes to greater breeding success. The use of local sesame cultivars is particularly valuable because of their potential to generate improved genotypes. Understanding the relationships between yield and other related traits allows these traits to be used more effectively as selection indicators for genetic improvement. The nature of the relationship between yield and its components determines what appropriate traits should be used in plant breeding.
Materials and Methods
To discover the correlations among seed yield and some important agricultural traits in order to determine the direct and indirect effects of each trait on seed yield and finally to choose the ideal genotypes in terms of various characteristics, a total of 36 local sesame cultivars were evaluated in 3 regions (Karaj, Moghan and Jiroft) by using a randomized complete block design for two years (2017-2018). A total of 14 quantitative traits were studied in this study, including measurements like the number of days from germination to the beginning of flowering, the number of days from germination to the beginning of maturity, the height of the first capsule from the plant crown, the height of the plant, the number of branches, the number of capsules in one plant, the number of seeds in one Capsule, seed weight of one capsule, the weight of 1000 seeds, capsule length, capsule width, capsule diameter, biological performance and seed yield.
Results and Discussion
The calculation of simple correlation coefficients showed that the height of the first pod from the plant crown, seed weight of a capsule, biological yield, number of seeds in a capsule and plant height have the highest correlation coefficients with seed yield. The height of the first capsule from the plant crown, the number of seeds in the capsule and the height of the plant were demonstrated by path analysis had the most positive direct effect and the number of days until the start of maturity had the most negative direct effect on seed yield and it is suggested that they be used as selection indicators for the improvement of seed yield. Five components were identified through the results of the principal components analysis which explained 77.92% of the variations in the data. Out of all the genotypes analyzed in terms of yield, genotypes 78-730, 78-229, and 78-570, displayed the greatest seed yield on the biplot generated by the first and second components. All evaluated traits led to the identification of four separate groups through cluster analysis. Overall, the results indicated that the cultivars in the first group were late-flowering types characterized by tall plants and high yield. The second group consisted of late-flowering cultivars with few capsules and low yield. The third group included early-flowering, early-maturing cultivars with long capsules, while the fourth group comprised cultivars with small capsules but a high number of seeds.
Conclusion
It was shown by cluster analysis that there was no connection between the classification of genotypes and their geographical placement and predominantly, the genotypes were classified by their physical distinctions and morphological differences. It can be concluded from the results that principal components analysis and cluster analysis exhibit similarities in their ability to segregate cultivars and genotypes. Their analysis outcomes give us a better understanding of the genetic structure and helps identifying specific genetic populations that have the potential to improved breeding programs.

Keywords

Main Subjects


Authors retain the copyright. This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)

  1. Adebisi, M. A. (2004). Variation, stability and correlation studies in seed quality and yield components of sesame (Sesamum indicum). Ph.D. Thesis, University of Agriculture, Abeokuta. 123 pp.
  2. Ahmed, J., Qadir, G., Ansar, M., Wattoo, F. M., Javed, T., Ali, B., & Rahimi, M. (2023). Shattering and yield expression of sesame (Sesamum indicum L) genotypes influenced by paclobutrazol concentration under rainfed conditions of Pothwar. BMC Plant Biology23(1), 137. https://doi.org/10.1186/s12870-023-04145-7
  3. Akbar, F., Rabbani, M. A., Shinwari, Z. K., & Khan, S. J. (2011). Genetic divergence in sesame (Sesamum indicum) landraces based on qualitative and quantitative traits. Pakistan Journal of Botany, 43(6), 2737-2744.‏
  4. Akinyode, E. T. (2023). Principal component and cluster analysis as a tool in assessment of genetic diversity of tomato genotypes (Lycopersicum esculentum). Nigerian Journal of Horticultural Science27(4), 74-80.
  5. Arulmozhi, N., Santha, S., & Mohammed, S. E. N. (2001). Correlation and path co-efficient analysis in sesame. Journal of Ecology, 13(3), 229-232.
  6. Ashfaq, M., Rani, K. J., Padmaja, D., Yadav, P., & Betha, U. K. (2023). Assessment of genetic diversity in sesame genotypes based on morphological characters. International Journal of Environment and Climate Change13(11), 1104-1111. https://doi.org/10.9734/ijecc/2023/v13i113260
  7. Ashri, A. (1998). Sesame breeding. Plant Breeding Reviews, 16, 179–228.
  8. Aye, K. M., Sreewongchai, T., Phumichai, C., Mathayatthaworn, W., Kumdee, O., Ratanapongsai, Y., & Kaedphol, R. (2024). Assessment of genetic diversity, correlation and path coefficients analysis in sesame (Sesamum indicum). Science & Technology Asia, 29(2), 225-236. https://ph02.tci-thaijo.org/index.php/SciTechAsia/article/view/252391
  9. Baraki, F., Gebregergis, Z., Belay, Y., Berhe, M., Teame, G., Hassen, M., Gebremedhin, Z., Abadi, A., Negash, W., Atsbeha, A., & Araya, G. (2020). Multivariate analysis for yield and yield-related traits of sesame (Sesamum indicum) genotypes. Heliyon6(10), 1-8. https://doi.org/10.1016/j.heliyon.2020.e05295
  10. Baydar, H. A. S. A. N. (2005). Breeding for the improvement of the ideal plant type of sesame. Plant Breeding, 124(3), 263-267.‏ https://doi.org/10.1111/j.1439-0523.2005.01080.x
  11. Bitaraf, N., Khodambashi, N., & Houshmand, S. (2010). Correlation and path analysis of grain yield and its components for lentil under Shahrekord climate. Iranian Journal of Pulses Research, 1(1), 51-56. https://doi.org/10.22067/ijpr.v1i1.6345
  12. Davoodi Zanjani, N., Ghasemi Afshar, P., & Adeli Milani, M. (2020). Evaluation of the composition and oxidative stability of cold-pressed sesame oils in the market of Zanjan province, Iran (2019). Journal of Human Environment and Health Promotion6(4), 159-166.
  13. Durge, B. D., Geethanjali, S., & Sasikala, R. (2022). Assessment of genetic variability for seed yield and its components in sesame (Sesamum indicum) based on multivariate analysis. Electronic Journal of Plant Breeding13(3), 974-982.
  14. Emamgholizadeh, S., Parsaeian, M., & Baradaran, M. (2015). Seed yield prediction of sesame using artificial neural network. European Journal of Agronomy68, 89-96. https://doi.org/10.1016/j.eja.2015.04.010
  15. Ezhilarasi, T., Mahalingam, A., & Manivannan, N. (2024). 1. Assessment of genetic diversity in Indian sesame (Sesamum indicum) germplasm. Ecology, Environment & Conservation, 30(4), 344-348. https://doi.org/10.53550/eec.2024.v30i03s.059
  16. Falconer, D. S., & Mackey, T. F. C. (1996). Introduction to quantitative genetics. Longman Group Ltd. Harlow, UK, p. 187-246.
  17. Fazal, A., Mustafa, H. S. B., Hasan, E., Anwar, M., Tahir, M. H. N., & Sadaqat, H. A. (2015). Interrelationship and path coefficient analysis among yield and yield related traits in sesame (Sesamum indicum). Nature and Science, 13(5), 27-32.
  18. Ferreira, E. I., Pereira, M. D., Macedo, A. R. D., & Soares, E. R. (2017). Effect of fertilization on the physiological maturation of sesame seeds1. Pesquisa Agropecuária Tropical47(2), 202-210. https://doi.org/10.1590/1983-40632016v4745715
  19. Gedifew, S. (2024). Multivariate analyses of shattering and seed yield related morphological traits reveal high yielding sesame genotypes exhibit low degree of shattering. Middle East Research Journal of Biological Sciences, 4(3), 58-71. https://doi.org/10.36348/merjbs.2024.v04i03.002
  20. Gharib-Eshghi, A. M. I. R., Mozafari, J. A. V. A. D., & Azizov, i. B. R. A. H. I. M. (2016). Genetic Diversity Among Sesame Genotypes under Drought Stress Condition by Drought Implementation. CABI Databases. 89-108.
  21. Goudappagoudra, R., Lokesha, R., & Ranganatha, A. R. G. (2011). Trait association and path coefficient analysis for yield and yield attributing traits in sesame (Sesamum indicum). Electronic Journal of Plant Breeding, 2(3), 448-452.
  22. Gupta, D., Muralia, S., Khandelwal, V., & Nehra, A. (2021). Assessing diversity of sesame genotypes using cluster analysis and principal component analysis. International Journal of Current Microbiology and Applied Sciences10(01), 304-312. https://doi.org/10.20546/ijcmas.2021.1001.038
  23. Hemanth, S., Patil, L. C., Manoj, S. H., Naveen, A., Bhargavi, H. A., & Kotegoudra, H. (2024). Unravelling the genetic variability of seed yield and its components in sesame (sesamum indicum) through multivariate analysis. Plant Archives, 24(1), 237-242. https://doi.org/10.51470/plantarchives.2024.v24.no.1.034
  24. Islam, M. N., Sultana, S., Rashid, M. U., & Rahim, M. A. (2024). Determination of the potentiality of different sesame (Sesamum indicum) genotypes: Potentiality of different sesame (Sesamum indicum L.) genotypes. Bangladesh Journal of Agriculture49(1), 52-67.
  25. Kalaiyarasi, R., Rajasekar, R., Lokeshkumar, K., Priyadharshini, A., & Mohanraj, M. (2019). Correlation and path analysis for yield and yield traits in sesame (Sesamum indicum) genotypes. International Journal of Current Microbiology and Applied Sciences8(11), 1251-1257. https://doi.org/10.20546/ijcmas.2019.811.147
  26. Kante, S., Wadikar, P. B., Sargar, P. R., & Patil, S. S. (2022). Correlation analysis for seed yield and its related attributes in genotypes of sesame (Sesame indicum). International Journal of Plant and Environment8(01), 87-90. https://doi.org/10.18811/ijpen.v8i01.11
  27. Kavitha, M., & Sethupathi-Ramalingam, R. (2000). Path analysis in segregating population of sesame. Madras agricultural Journal, 5(1-3), 158-159.
  28. Khairnar, S. S., & Monpara, B. A. (2013). Identification of potential traits and selection criteria for yield improvement in sesame (Sesamum indicum) genotypes under rainfed conditions. Iranian Journal of Genetics and Plant Breeding2(2), 1-8. (in Persian with English abstract)
  29. Kumar, V., Sinha, S., Sinha, S., Singh, R. S., & Singh, S. N. (2022). Assessment of genetic variability, correlation and path analysis in sesame (Sesamum indicum). Electronic Journal of Plant Breeding13(1), 208-215.
  30. Kumaresan, D., & Nadarajan, N. (2003). Genetic divergence analysis in sesame (sesamun indicum L). Sesame and Office Newsletter, 18, 15-19.
  31. Langham, D. R., Riney, J., Smith, G., & Wiemers, T. (2008). Sesame grower guide. Sesaco Corp30(331), 3.
  32. Manly, B. F. J. (2004). Multivariate statistical methods, A primer. Chapman and Hall, London. Third edition, 224 p. https://doi.org/10.1201/b16974
  33. Masoudi, B., & Ahmadi, M. (2019). Evaluation of genetic diversity of agronomic and morphological traits of sesame genotypes. Journal of Crop Breeding11(31), 78-91. https://doi.org/10.29252/jcb.11.31.78
  34. Mei, H., Cui, C., Liu, Y., Du, Z., Wu, K., Jiang, X., Zheng, Y., & Zhang, H. (2023). QTL analysis of traits related to seed size and shape in sesame (Sesamum indicum). Plos One18(11), e0293155. https://doi.org/10.1371/journal.pone.0293155
  35. Menzir, A. (2012). Phenotypic variability, divergence analysis and heritability of characters in sesame (Sesamum indicum) genotypes. Nature and Science, 10(10), 117-126.‏
  36. Mohammadi, S. A., Prasanna, B. M., & Singh, N. N. (2003). Sequential path model for determining interrelationships among grain yield and related characters in maize. Crop Science, 43(5), 1690-1697.‏ https://doi.org/10.2135/cropsci2003.1690
  37. Mukhthambica, K., Bisen, R., & Ramya, K. T. (2023). Principal component analysis for yield and yield related traits in sesame (Sesamum indicum). Biological Forum – An International Journal, 15(3), 227-232.
  38. Nadeem, A., Kashani, S., Ahmed, N., Buriro, M., Saeed, Z., Mohammad, F., & Ahmed, S. (2015). Growth and yield of sesame (Sesamum indicum) under the influence of planting geometry and irrigation regimes. American Journal of Plant Sciences6(07), 980. https://doi.org/10.4236/ajps.2015.67104
  39. Navaneetha, J. S., Murugan, E., & Parameswari, C. (2019). Correlation and path analysis for seed yield and its components in sesame (Sesamum indicum). Electronic Journal of Plant Breeding10(3), 1262-1268. https://doi.org/10.5958/0975-928x.2019.00161.3
  40. Nikfekr, R., Kazemitabar, S. K., Ranjbar, G., Hashemi-Petroudi, S. H., & Mehraban Joubani, P. (2023). Study of genetic diversity and evaluation of some sesame genotypes under salinity stress. Environmental Stresses in Crop Sciences16(3), 575-586. https://doi.org/10.22077/escs.2022.4516.2037
  41. Ramazani, S. H. R. (2016). Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum). Journal of Crop Science and Biotechnology19, 303-309. https://doi.org/10.1007/s12892-016-0053-0
  42. Ranganatha, A. R. G., Jyotishi, A., Deshmukh, M. R., Bisen, R., Panday, A. K., & Gupta, K. N. (2010). Improved technology for maximizing production of sesame. Indian Council of Agricultural Research, Jabalpur, IND.1-17.
  43. Sabag, I., Pnini, S., Morota, G., & Peleg, Z. (2024). Refining flowering date enhances sesame yield independently of day-length. BMC Plant Biology24(1), 711. https://doi.org/10.1186/s12870-024-05431-8
  44. Salehi, M., Esmailzadeh Hosseini, S. A., Salehi, E., & Bertaccini, A. (2017). Genetic diversity and vector transmission of phytoplasmas associated with sesame phyllody in Iran. Folia Microbiologica62, 99-109. https://doi.org/10.1007/s12223-016-0476-5
  45. Sankar, P. D., & Kumar, C. A. (2003). Character association and path coefficient analysis in sesame (Sesamum indicum). Agricultural Scientist Digestion, 23, 17-19.
  46. Sasipriya, S. (2018). Correlation and path analysis for seed yield and its components in sesame (Sesamum indicum). Electronic Journal of Plant Breeding9(4), 1594-1599.
  47. Sonaniya, R., Bisen, R., & Sonaniya, P. (2023). Assessment of Exotic Sesame (Sesamum indicum) Accessions through Principal Component Analysis. International Journal of Environment and Climate Change, 13(11), 282-290. https://doi.org/10.9734/ijecc/2023/v13i113170
  48. Sumathi, P., Muralidharan, V., & Manivannan, N. (2007). Trait association and path coefficient analysis for yield and yield attributing traits in sesame (Sesamum indicum L). Madras Agriculture Journal, 94, 174–178. https://doi.org/10.29321/maj.10.100660
  49. Tabatabaei, I., Pazouki, L., Bihamta, M. R., Mansoori, S., Javaran, M. J., & Niinemets, U. (2011). Genetic variation among iranian sesame (Sesamum indicum) accessions vis-a-vis exotic genotypes on the basis of morpho-physiological traits and rapd markers. Australian Journal of Crop Science5(11), 1396-1407.
  50. Teklu, D. H., Shimelis, H., & Abady, S. (2022). Genetic improvement in sesame (Sesamum indicum): Progress and outlook: A review. Agronomy12(9), 2144. https://doi.org/10.3390/agronomy12092144
  51. Wang, C., Niu, J., Miao, H., Li, C., Duan, Y., Ju, M., Cao, H., Wei, L., Wang, H., & Zhang, H. (2024). Genetic variation, correlation, and association mapping of seed yield and its component traits in sesame. Genetic Resources and Crop Evolution71(2), 603-619. https://doi.org/10.1007/s10722-023-01644-2
  52. Winstead, D. J., & Jacobson, M. G. (2024). Storable, neglected, and underutilized species of Southern Africa for greater agricultural resilience. Plant‐Environment Interactions5(4), e70004. https://doi.org/10.1002/pei3.70004
  53. Yadav, R., Kalia, S., Rangan, P., Pradheep, K., Rao, G. P., Kaur, V., & Siddique, K. H. (2022). Current research trends and prospects for yield and quality improvement in sesame, an important oilseed crop. Frontiers in Plant Science13, 863521. https://doi.org/10.3389/fpls.2022.863521
  54. Yingzhong, Z., & Yishou, W. (2002). Genotypic correlations and path coefficient analysis in sesame. Sesame and Sofflower Newsletter, 17, 10-12.
  55. Yol, E., Karaman, E., Furat, S., & Uzun, B. (2010). Assessment of selection criteria in sesame by using correlation coefficients, path and factor analyses. Australian Journal of Crop Science4(8), 598-602.
  56. Zewdu, D., Mekonnen, F., & Geleta, N. (2024). Cluster and principal component analysis for yield and yield related traits of bread wheat (Triticum aestivum) genotypes. AGBIR, 40(2) 962-967.
CAPTCHA Image
Volume 23, Issue 4 - Serial Number 80
December 2025
Pages 461-478
  • Receive Date: 25 December 2024
  • Revise Date: 22 February 2025
  • Accept Date: 01 March 2025
  • First Publish Date: 13 April 2025