Genetic variability, character association and path analysis of yield and yield attributes of rice genotypes at Lalitpur, Nepal
https://doi.org/10.26832/24566632.2025.1001016
Abstract
Rice is a staple for over half the world’s population. Location-specific varietal trials help identify suitable genotypes with desirable traits. A study in Lalitpur, Nepal, evaluated 12 rice genotypes in a randomized complete block design (RCBD) with three replications to assess genotypic variability, character association, and path analysis for yield-related traits. Observations from five randomly selected plants per plot were analyzed statistically. Analysis of variance revealed significant differences among genotypes for most traits, indicating ample genetic variability. Grain yield (20.26) showed the highest genotypic coefficient of variation (GCV), while effective tillers (24.26%) had the highest phenotypic coefficient of variation (PCV), followed by grain yield, straw yield, and tiller number. High heritability and high genetic advance as percent of mean were noted for days to flowering (35.15), total grain per panicle (34.84), tiller number (33.39), and panicle weight (31.55), suggesting additive gene control and selection potential. Grain yield was positively correlated with panicle length (r = 0.47**), total grain per panicle (r = 0.40*), panicle weight (r = 0.43**), tiller number (r = 0.34*), and straw yield (r = 0.62*). Path analysis showed total grain per panicle (2.55) had the highest positive direct effect on yield, alongside days to flowering, plant height, effective tillers, unfilled grains per panicle, and straw yield. Khumal-4, Khumal-8, and Taichung-176 emerged as superior genotypes. Hence, it is strongly advised that these traits be chosen in rice breeding programs to further enhance production. Khumal-4, Khumal-8, and Taichung-176 were the most promising genotypes.
Keywords:
Character association, Heritability, Path analysis, Rice, VariabilityDownloads
References
Abbas, S. H. (2024). Path Coefficient Analysis and Selection Index in Different Rice (Oryza sativa L.) Genotypes. Kufa Journal for Agricultural Sciences, 16(1), 131–146. https://doi.org/10.36077/kjas/2024/v16i1.10965
Abebe, T., Alamerew, S., & Tulu, L. (2017). Genetic variability, heritability and genetic advance for yield and its related traits in rainfed lowland rice (Oryza sativa L.) Genotypes at Fogera and Pawe, Ethiopia. Advances in Crop Science and Technology, 05(02). https://doi.org/10.4172/2329-8863.1000272
Adhikari, B., Joshi, B. prasad, Shrestha, J., & Bhatta, N. (2018). Genetic variability, heritability, genetic advance and correlation among yield and yield components of rice (Oryza sativa L.). Journal of Agriculture and Natural Resources, 1(1), 149–160. https://doi.org/10.3126/janr.v1i1.22230
Adhikari, B., Pokherel, B., & Shrestha, J. (2018). Evaluation and development of finger millet (Eleusine coracana L.) genotypes for cultivation in high hills of Nepal. Farming & Management, 3(1). https://doi.org/10.31830/2456-8724.2018.0001.7
Akinwale, M., Gregorio, G., Akinyele, B. O., Nwilene, F., Ogunbayo, S. A., & Odiyi, A. C. (2011). Heritability and correlation coefficient analysis for yield and its components in rice (Oryza sativa L.). African Journal of Plant Science, 5(3). https://www.researchgate.net/publication/284283001
Asilo, S., Nelson, A., de Bie, K., Skidmore, A., Laborte, A., Maunahan, A., & Quilang, E. J. P. (2019). Relating X-band SAR backscattering to leaf area index of rice in different phenological phases. Remote Sensing, 11(12), 1462. https://doi.org/10.3390/rs11121462
Azhar, T., Odhano, I. A., & Bughio, H. U. R. (2024). Ameliorating the quantitative traits in rice through physical mutagenesis. Pakistan Journal of Botany, 56(1), 161–165. http://dx.doi.org/10.30848/PJB2024-1(3)
Bandumula (2018). Rice Production in Asia: Key to Global Food Security. Proceedings of the National Academy of Sciences, India Section B: Biological Sciences, 88(4), 1323–1328. https://doi.org/10.1007/s40011-017-0867-7
Barhate, K. K., Jadhav, M. S., & Bhavsar, V. V. (2021). Correlation and path analysis in aromatic lines of rice (Oryza sativa L.). Journal of Pharmacognosy and Phytochemistry, 10(3), 363–366. https://www.phytojournal.com/archives/2021/vol10issue3/PartE/10-1-132-972
Bhandari, K., Poudel, A., Sharma, S., Kandel, B. P., & Upadhyay, K. (2019). Genetic variability, correlation and path analysis of rice genotypes in rainfed condition at Lamjung, Nepal. Russian Journal of Agricultural and Socio-Economic Sciences, 92(8), 274–280. https://doi.org/10.18551/rjoas.2019-08.30
Bhargava, K., Shivani, D., Pushpavalli, S., Sundaram, R. M., Beulah, P., & Senguttuvel, P. (2021). Genetic variability, correlation and path coefficient analysis in segregating population of rice. Electronic Journal of Plant Breeding, 12(2), 549–555. https://ejplantbreeding.org/index.php/EJPB/article/view/3713
Burton, G. W., & Devane, E. H. (1953). Estimating heritability in tall fescue (Festuca arundinacea) from replicated clonal material. Agronomy Journal, 45, 478–481. https://doi.org/10.5555/19541601156
Chavan, B. R., Dalvi, V. V., Kunkerkar, R. L., Mane, A. V., & Gokhale, N. B. (2022). Study of correlation and path analysis in aromatic rice genotypes (Oryza sativa L.). The Pharma Innovation Journal, 11(2), 1704–1707. https://www.thepharmajournal.com/archives/2022/vol11issue2/PartX/11-2-277-946
Dhurai, S. Y., Reddy, D. M., & Ravi, S. (2016). Correlation and path analysis for yield and quality characters in rice (Oryza sativa L.). Rice Genomics and Genetics. https://doi.org/10.5376/rgg.2016.07.0004
Falconer, D. S. (1996). Introduction to Quantitative Genetics. Pearson Education India.
Fentie, D. B., Abera, B. B., & Ali, H. M. (2021). Association of agronomic traits with grain yield of lowland rice (Oryza sativa L.) genotypes. International Journal of Agricultural Sciences, 8, 161–175. https://www.researchgate.net/publication/365991076
Hossain, S., & Haque Md, M. (2016). Genetic Variability, Correlation and Path Coefficient Analysis of Morphological Traits in some Extinct Local Aman Rice (Oryza sativa L.). Rice Research: Open Access, 4(1). https://doi.org/10.4172/2375-4338.1000158
IRRI. (2018) Annual report. International Rice Research Institute. Philippines. https://www.loc.gov/item/lcwaN0032499/
Islam, S. S., Nualsri, C., & Hasan, A. K. (2021). Character association and path analysis studies in upland rice (Oryza sativa) genotypes. Research on Crops, 22(2), 239–245. http://dx.doi.org/10.31830/2348-7542.2021.063
Johnson, H. W., Robinson, H. F., & Comstock, R. E. (1955). Estimates of genetic and environmental variability in soybeans. 47, 314–318. https://doi.org/10.5555/19561600791
Kavya, G., Senguttuvel, P., Shivani, D., & Barbadikar, K. M. (2023). Estimation of variability, correlation coefficient and path analysis in improved restorer lines of rice (Oryza sativa L.). International Journal of Environment and Climate Change, 13(11), 2853–2862. https://doi.org/10.9734/ijecc/2023/v13i113455
Kiran, A. K., Sharma, D. J., Subbarao, L. V., Gireesh, C., & Agrawal, A. P. (2023). Correlation coefficient and path coefficient analysis for yield, yield attributing traits and nutritional traits in rice genotypes. The Pharma Innovation Journal, 12(2), 1978–1983. https://www.thepharmajournal.com/archives/2023/vol12issue2/PartX/12-2-61-259
Kiranmayee, B., Raju, C. D., Raju, K. K., & Balaram, M. (2018). A study on correlation and path coefficient analysis for yield and yield contributing traits in maintainer (B lines) lines of hybrid rice (Oryza sativa L.). https://krishi.icar.gov.in/jspui/handle/123456789/31757
Kulsum, U., Sarker, U., & Rasul, Md. (2022). Genetic variability, heritability and interrelationship in salt-tolerant lines of T. Aman rice. Genetika, 54(2), 761–776. https://doi.org/10.2298/GENSR2202761K
MoALD. (2023). Annual Statistical Information on Nepalese Agriculture. Ministry of Agriculture and Livestock Development. https://moald.gov.np
MoALD. (2023). Krishi Diary. Agriculture Information and Communication Centre. Ministry of Agriculture and Livestock Development.
Muthuramu, S., & Thangaraj, K. (2023). Heritable variation and association of yield traits in advanced rice genotypes grown under dry direct seeded condition. https://www.thepharmajournal.com/archives/2023/vol12issue11/PartK/12-10-368-707
Noatia, P., Sao, A., Tiwari, A., Nair, S. K., & Gauraha, D. (2021). Genetic Dissection of Yield Determinants in Advance Breeding Lines (ABLs) of Rice (Oryza sativa L.) under Irrigated Condition of Chhattisgarh, India. International Journal of Plant & Soil Science, 119–131. https://doi.org/10.9734/ijpss/2021/v33i2030638
Priya, C. S., Suneetha, Y., Babu, D. R., & Rao, S. V. (2017). Inter-relationship and path analysis for yield and quality characters in rice (Oryza sativa L.). International Journal of Science, Environment and Technology, 6(1), 381–390. https://www.researchgate.net/publication/378774162
Rashid, M., Hassan, L., Begum, S. N., & Nuruzzaman, M. (2017). Genetic variability analysis for various yield attributing traits in rice genotypes. Journal of Bangladesh Agricultural University, 15(1), 15–19. https://www.academia.edu/download/103764073/22588.pdf
Robinson, H. F., Harvey, P. H., & Comstock, R. E. (1949). Estimates of heritability and the degree of dominance in corn. Agronomy Journal, 41, 353–359. https://doi.org/10.5555/19501600265
Shrestha, J., Subedi, S., Kushwaha, U.K.S., & Maharjan, B. (2021). Evaluation of Growth and Yield Traits in Rice Genotypes Using Multivariate Analysis. Heliyon 7 (9). https://doi.org/10.1016/j.heliyon.2021.e07940
Shrestha, Jiban, Naba Raj Subedi, Sudeep Subedi, Ujjwal Kumar Singh, Bidhya Maharjan, and Mahesh Subedi. 2021. “Assessment of Variability, Heritability and Correlation in Rice (oryza sativa l.) Genotypes.” Natural Resources and Sustainable Development 11(2), 181–92. https://doi.org/10.31924/nrsd.v11i2.077
Singh, B., Gauraha, D., Sao, A., & Gaur, S. (2021). Assessment of genetic variability, heritability and genetic advance for yield and quality traits in advanced breeding lines of rice (Oryza sativa L.). The Pharma Journal, 10(8), 1627–1630. https://doi.org/10.17557/tjfc.485605
Singh, S. K., Korada, M., Singh, P., Khaire, A. R., Singh, D. K., Habde, S. V., Majhi, P. K., & Naik, R. (2020). Character association and path-coefficient analysis for yield and yield-related traits in 112 genotypes of rice (Oryza sativa L.). Current Journal of Applied Science and Technology, 39(48), 545–556. https://doi.org/10.9734/cjast/2020/v39i4831275
Sivasubramanian, S., & Menon, P. M. (1973). Genotypic and phenotypic variability in rice. Madras Agricultural Journal, 60, 1093–1096. https://doi.org/10.5555/19741623213
Sudeepthi, K., Srinivas, T., Kumar, B. R., Jyothula, D. P. B., & Umar, S. N. (2020). Assessment of genetic variability, character association and path analysis for yield and yield component traits in rice (Oryza sativa L.). Electronic Journal of Plant Breeding, 11(01), 144–148. https://doi.org/10.37992/2020.1101.026
Takai, T., Lumanglas, P., Simon, E. V., Arai-Sanoh, Y., Asai, H., & Kobayashi, N. (2019). Identifying key traits in high-yielding rice cultivars for adaptability to both temperate and tropical environments. The Crop Journal, 7(5), 685–693. https://doi.org/10.1016/j.cj.2019.06.004
Tiwari, D. N., Tripathi, S. R., Tripathi, M. P., Khatri, N., & Bastola, B. R. (2019). Genetic Variability and Correlation Coefficients of Major Traits in Early Maturing Rice under Rainfed Lowland Environments of Nepal. Advances in Agriculture, 1–9. https://doi.org/10.1155/2019/5975901
Zhang, Y., Yu, C., Lin, J., Liu, J., Liu, B., Wang, J., Huang, A., Li, H., & Zhao, T. (2017). OsMPH1 regulates plant height and improves grain yield in rice. PloS One, 12(7), https://doi.org/10.1371/journal.pone.0180825
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