Genetic Variability And Principal Component Analysis Of The Safflower Germplasm Mapping Panel (Sgmp)
DOI:
https://doi.org/10.48165/Keywords:
Genetic diversity, principal component analysis, safflower, variabilityAbstract
Worldwide there is focus on the development of safflower (Carthamus tinctorius L.) varieties having high seed yield coupled with high oil content. The present study was aimed to evaluate the safflower germplasm mapping panel (SGMP) for major seed yield traits and oil content to improve oil productivity of varieties. SGMP consisting of 200 safflower germplasm accessions and four checks (A-1, PBNS-12, NARI-6, NARI-57) were evaluated for 9 quantitative characters during 2016-17. The distribution of data for phenological characters and seed yield was normal, with the exception for seed size and 100-seed weight. The oil content was positively skewed toward higher values, thus indicating panel homogeneity. The studied traits showed significant variation in the germplasm panel. Seed yield and its related characters had high genotypic and phenotypic coefficients of variation, while oil content showed moderate coefficient of variation. Broad sense heritability and genetic advance over percent mean were high for most traits. The principal component analysis revealed that four components explained 75.3% of total variation. There was a strong correlation between seed yield, capitula plant-1, and number of branches plant-1. Superior accessions for each character were identified over the best check. The safflower germplasm mapping panel had wide range variability for the traits studies, and the best accessions can be used in safflower improvement programme. In terms of seed yield, genotypes A1, EC736504, and GMU6663 performed better. Genotype EC736504 gave higher seed yield and oil content. In terms of seed yield, genotypes A1, EC736504, and GMU6663 performed better; however, genotype EC736504 gave higher seed yield coupled with high oil content. For oil improvement, 26 germplasm lines performed better than the checks.
Downloads
References
Aravind, J., Mukesh, S., Wankhede, D. and Kaur, V. 2022. Augmented RCBD: Analysis of Augmented Randomized Complete Block Designs. R Package Version 0.1.2020, Volume 2. [https://aravind j.github.io/augmentedRCBD/].
Arif, M., Hussain, I., Rabbani, M.A., Ali, S., Ali, N., Khan, S.M., Tanoli, M.T.Z. and Raza1, H. 2016. Assessment of genetic diversity among safflower germplasm through agro-morphological traits. International Journal of Biological Science, 9(4): 1-11.
Bahmankar, M., Nabati, D.A. and Dehdari, M. 2017. Genetic relationships among Iranian and exotic safflower using microsatellite markers. Journal of Crop Science and Biotechnology, 20: 159-165. Bisne, R., Sarawgi, A. and Verulkar, S. 2010. Study of heritability, genetic advance and variability for yield contributing characters in rice. Bangladesh Journal of Agricultural Research, 34(2): 175-179.
Burton, G.W. 1952. Quantitative inheritance in grasses. pp. 277-283. In: 6th International Grassland Congress Proceedings, Pennsylvania State College, Pennsylvania, USA.
Dambal, G.I. and Patil, R.S. 2016. Character association and path analysis in safflower germplasm (Carthamus tinctorius L.). Research Journal of Agricultural Sciences, 7(1): 155-157. Dhruw, P., Chandrakar, P. and Shrivastava, R. 2022. Assessment of genetic variability, heritability and genetic advance for seed yield and its contributing traits in elite germplasm accessions of safflower (Carthamus tinctorius L.). Journal of Pharma Innovation, 11: 311-313. Dhutmal, R.R., Choulwar, S.B., Bhoyar, S.S., Kadam, G.L. and Pawar, K.M. 2006. Genetic variability for yield and yield related traits in F2 generation of safflower. Annals of Plant Physiology, 20: 102-105.
FAOSTAT. 2021. https://www.fao.org/faostat/en/#data/QCL
Gana, A.S., Shaba, S.Z. and Tsado, E.K. 2013. Principal component analysis of morphological traits in thirty-nine accessions of rice (Oryza sativa L.) grown in a rainfed lowland ecology of Nigeria. Journal of Plant Breeding and Crop Science, 5: 120-126.
Golkar, P., Arzani, A., Rezaei, A.M., Yarali, Z. and Yousefi, M. 2009. Genetic variation of leaf antioxidants and chlorophyll content in safflower. African Journal of Agriculture Research, 4(12): 1475-1482.
Usha Kiran Betha et al.
Jabbari, H., Fanaei, H.R., Shariati, F., Sadeghi Garmarodi, H., Abasali, M. and Omidi, A.H. 2022. Principal components analysis of some iranian and foreign safflower genotypes using morphological and agronomic traits. Journal of Crops Improvement, 24(1): 125-143.
Jagtap, P.K., Chavan, A.A., Joshi, B.N. and Misal, A.M. 2012. Nature of association and path analysis among different quantitative traits in early segregating generations of safflower. Journal of Oilseeds Research, 29: 57-59.
Jignesh, H.K., Mital, D.J., Ajay, B.C., Sandip, K.B. and John, J.G. 2020. Effect of selection response for yield related traits in early and later generations of groundnut (Arachis hypogaea L.). Crop Breeding and Applied Biotechnology, 20(2): e317320215. [https://doi.org/10.1590/1984- 70332020v20n2a31].
Jolliffe, I.T. and Cadima, J. 2016. Principal component analysis: a review and recent developments. Philosophical Transactions of the Royal Society A, 374: 20150202. [http://doi.org/10.1098/rsta.2015.0202].
Jombart, T., Devillard, S. and Balloux, F. 2010. Discriminant analysis of principal components: A new method for the analysis of genetically structured populations. BMC Genetics, 11: 94. [https://doi.org/10.1186/1471-2156-11-94].
Kavani, R.H., Shukla, P.T. and Madariya, R.B. 2000. Analysis of variability for seed yield and related characters in safflower (Carthamus. tinctorius L.). Madras Agricultural Journal, 87: 449-452. Mohammadi, S.A. 2002. Statistical methods in genetics. pp. 26-28. In: 6th International University of Tarbiat Modares, August, 26-28, Tarboat, Iran.
Neelima, S., Prabhakar, K. and Ramanamma, K.V. 2021. Genetic variability, heritability, association and divergence studies in safflower (Carthamus tinctorius L.) genotypes. Journal of Oilseeds Research, 38: 265-269.
Nimbkar, N. 2008. Issues in safflower production in India. Safflower: Unexploited potential and world adaptability. pp. 1-9. In: Proceedings of the Seventh International Safflower Conference. 3-6 November. 2008, Wagga, New South Wales, Australia,
Ojaq, S.M.M., Mozafari, H., Jabbari, H. and Sani, B. 2020. Evaluation of yield of safflower (Carthamustinctorius L.) genotypes under semi-arid conditions. Plant Genetic Resources, 18(4): 270-277.
Pushpavalli, S.N.C.V.L. and Kumar, G. 2017. Study of genetic variability, correlation and path analysis of safflower genotypes. Research Journal of Agricultural Sciences, 8(3): 706-709. Rathod, P.S., Ghuge, S.B. and Wankhade, M.P. 2021. Genetic variability, heritability and genetic
advance studies in safflower (Carthamus tinctorius L.). The Pharma Innovation Journal, 10: 765-767.
Reddy, M.V.S., Chand, P., Vidyadhar, B. and Devi, L.S. 2004. Nature of association among some quantitative traits in F4 generation of safflower (Carthamus tinctorius L.). Progressive Agriculture, 4:51-53.
Safavi, S.M., Pourdad, S.S. and Safavi, S.A. 2017. Analysis of genetic diversity of safflower (Carthamus tinctorius L.) genotypes using agro-morphological traits and molecular markers. Journal of Crop Science, 42(2): 48-60.
Sahoo, B.C., Shrivastava, R. and Hemlata, O. 2022. Determination of optimum plant characters in safflower (Carthamus tinctorius L.) under rice based late sown condition. Electronic Journal of Plant Breeding. 13(1): 225-229.
Shinwari, Z.K., Rehman, H. and Rabbani, M.A. 2014. Morphological traits based genetic diversity in safflower (Carthamus tinctorius L.). Pakistan Journal of Botany. 46: 1389-1395. Valli, S.P., Sudhakar, C., Rani, J. and Rajeswari, R.R. 2016. Correlation and path coefficient analysis for the yield components of safflower germplasm (Carthamus tinctorius L.). Electronic Journal of Plant Breeding, 7(2): 420-426.
Yadav, P. 2016. Calibration of NMR spectroscopy for accurate estimation of oil content in sunflower, safflower and castor seeds. Current Science, 110: 73-76.