Evaluation of yield and genetic variation of Non-Spiny safflower genotypes (Carthamus tinctorius L.) using multivariate analysis

Document Type : Complete scientific research article

Authors

1 Assistant Professor, Department of plant production and genetic engineering, Faculty of Agriculture, University of Saravan. Saravan, Sistan and Baluchestan, Iran.

2 Assistant Professor of Genetics and Plant Breeding, Research and Technology Institute of Plant Production, Afzalipour Research Institute, Shahid Bahonar University of Kerman, Kerman- Iran

3 Professor of Genetics and Plant Breeding, Research and Technology Institute of Plant Production, Afzalipour Research Institute and Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman- Iran

Abstract

Background and objectives: Iran is considered one of the primary centers of origin for safflower and is among the richest regions globally regarding its genetic diversity. Enhancing grain yield is a crucial factor in the development of safflower cultivation. Given the proliferation of multiple non-spiny safflower genotypes and the importance of this trait in advancing safflower cultivation, the use of non-spiny genotypes can be an effective step toward implementing breeding programs. The most important step in this direction is utilizing the diversity in both native and non-native germplasm. The objective of this research was to investigate the genetic diversity of native and non-native non-spiny safflower genotypes to identify superior genotypes for grain production and to determine the effective relationships among traits.
Materials and Methods: In this study, 36 non-spiny safflower genotypes were evaluated in a 4 × 9 alpha-lattice design during the 2023-2024 growing season at the research farm of the University of Saravan. During the growth period, the following traits were assessed: days to seedling, days to 5% flowering, days to physiological maturity, plant height, number of branches, number of fertile pods per plant, number of grains per pod, 100-grains weight, Pods weight per plant, individual plant yield, grain weight per pod, total grain yield, biological yield, and harvest index.
Results: The results indicated a high level of genetic diversity among the studied genotypes. A highly significant positive correlation was observed between total grain yield and grain weight per pod (0.79), individual plant yield (0.99), and number of grains per pod (0.73). Cluster analysis using the minimum variance method (wards method) grouped the studied genotypes into six main clusters. Based on the comparison of cluster means, the genotypes in the first and second clusters had low means for most of the studied traits. Genotypes clustered in group three exhibited significantly higher yield (8809.9 kg/ha) compared to the other clusters. These genotypes exhibited higher values for days to physiological maturity (183.9), individual plant yield (22.65 g) and grain weight per pod (2.18) compared to other clusters. The fourth cluster had an average performance for all the studied traits. Genotypes in the fifth and sixth clusters showed significant differences from other clusters in terms of traits related to grain yield. Using principal component analysis, the studied traits were reduced to four components with a cumulative variance of 99.77%. Accordingly, the first component was named “yield,” the second “yield components,” the third “plant architecture,” and the fourth “phenology.” Based on the results of the biplot, the genotypes were classified into four groups. Genotypes in the first group had a high average total grain yield. Genotypes in the second group, with distribution around the vectors of plant height, number of branches, number of fertile pods, biological yield, pods weight per plant, and 100-grain weight, had high grain yield potential. Genotypes in the third group were identified as late-maturing. The fourth group included genotypes that were considered intermediate to low for the studied traits.
Conclusion: Based on the results of the present study, it is possible to utilize crosses between genotypes in the third, fifth, and sixth clusters, which have the highest means for grain yield and yield-related components, with genotypes in the fourth cluster, using the biplot and based on the distance between clusters, to develop non-spiny safflower genotypes with high grain yield potential.

Keywords

Main Subjects

References

  1. Weiss, E.A. (2000). Oil seed crops. 2nd ed. Black Well Science Oxford.
  2. Nikpour, B., Nazari, M., & Abbasi, A. (2023). Assessment of the genetic diversity in 160 safflower genotypes focusing on oil quality characteristics. Journal of Crop Breeding,15(48), 113-122. https://doi.org/61186/jcb.15.48.113
  3. Singh, V., & Nimbkar, N. (2007). Genetics Resources, Chromosome Engineering and Crop Improvement Series, R.J. Singh, CRC Press, London.
  4. Nazari, M., Shariati, F., Sadeghi Garmaroodi, H., & Jabbari, H. (2022). Evaluation of genetic diversity in 273 safflower genotypes collected from different regions of the world. Journal of Crop Breeding,14(44), 174-180. https://doi.org/52547/jcb.14.44.174. [In Persian]
  5. Bowers, J.E., Pearl, S.A., & Burke, J.M. (2016). Genetic mapping of millions of snps in safflower (Carthamus tinctorius ) via whole-genome resequencing. G3 (Bethesda, Md.), 6(7), 2203–2211. https://doi.org/10.1534/g3.115.026690
  6. Coşge, B., Gürbüz, B., & Kıralan, M. (2007). Oil content and fatty acid composition of some safflower (carthamus tinctorius ) varieties sown in spring and winter. International Journal of Natural and Engineering Sciences, 1, 11-16. Corpus ID: 131524244
  7. Janmohammadi, M., Mohamadi, N., Shekari, F., Abbasi, A., & Esmailpour, M. (2017). The effects of silicon and titanium on safflower (Carthamus tinctorius L.) growth under moisture deficit condition. Acta Agriculturae Slovenica, 109(2), 443–455. https://doi.org/10.14720/aas.2017.109.2.27
  8. Patil, H.S. (1998). Genetic variability, association and path analysis in safflower. Indian Journal of Agricultural Resources, 32, 46-50.
  9. Rahmati, F., Seifzade, S., Jabari, H., Valadabadi, A. & Hadidi masoule, A. (2020). Effect of drought stress and foliar spraying on some physiological and agronomic traits of safflower cultivars. Scientific Journal of Crop Physiology, 47, 27-43. [In Persian]
  10. Safavi, A., Pourdad, S., Taeb, M., & Khosroshahli, M. (2010). Assessment of genetic variation among safflower (Carthamus tinctorius L.) accessions using agro-morphological traits and molecular markers. Journal of Food, Agriculture & Environment, 8, 616-625.
  11. Shahvardi, M. S., mohsenzadeh, M., & Habibollah Samizadeh Lahiji, H. (2022). Investigating the relationship between morphological and molecular diversity in safflower genotypes. Crop Biotechnology, 11(4), 93-110. https://doi.org/10.30473/cb.2023.66492.1896. [In Persian]
  12. Falconer, D., & Mackay, F.C. (1996). Introduction to quantitative genetics. Longman Group Ltd,
  13. McPherson, M.A., Good, A.G., Topinka, A.K.C., & Hall, L.M. (2004). Theoretical hybridization potential of transgenic safflower (Carthamus tinctorius L.) weedy relatives in the New World. Canadian Journal of Plant Science, 84, 923-934.
  14. Ahmadzadeh, A.R., Majedi, E., Darbani, B., Hagegat, A.R., & Dadashe, M.R. (2008). Grain yield and morphological characters of spring safflower genotypes: Evaluation relationship using correlation and path analysis. Research Journal of Biological Sciences, 3, 181-185.
  15. Mahmood, T., Muhammad, S. & Shinwari, Z.K. (2010). Molecular and morphological characterization of Caralluma species. Pakistan Journal of Botany, 42, 1163-1171.
  16. Mosavi Ojagh, S.M., Mozafari, H., Jabbari, H., & Sani, B. (2019). Study of genetic variation in safflower germplasm for early maturity and grain yield using multivariate statistical methods. Journal of Crop Breeding, 11(30), 47-57. https://doi.org/29252/jcb.11.30.47. [In Persian]
  17. Shinwari, Z.K., Rehman, H., & Ashiq Rabbani, M. (2014). Morphological traits based genetic diversity in safflower (Carthamus tinctorius ). Pakistan Journal of Botany, 46(4), 1389-1395. Corpus ID: 4999358
  18. Yazdi Samadi, B. (1978). Evaluation of drought resistance in Iranian and foreign safflower cultivars. Iranian Journal of Agriculture Science, 2(3): 6-10. [In Persian]
  19. Yasari, T., Shahsavari, M., Barzegar, A. & Omidi, A.H. (1995). Study of developmental stages and relationship between of them and seed yield in ten advanced safflower genotypes. Pajouhesh and Sazandegi, 68(3), 75- 83. [In Persian]
  20. Biradar, S.S., Patil, M.K., Naik, V.R., Mukta, N., Nayidu, N.K., & Desai, S.A. (2022). Safflower improvement: conventional breeding and biotechnological approach. In: Gosal, S.S., Wani, S.H. (eds) Accelerated Plant Breeding, Volume 4. Springer, Cham. https://doi.org/10.1007/978-3-030-81107-5_9
  21. Arzu, K.O.S.E., Onder, O., Bilir, O., & Kosar, F. (2018). Application of multivariate statistical analysisfor breeding strategies of spring safflower (Carthamus tinctorius L.). Turkish Journal of Field Crops, 23(1), 12-19. https://doi.org/10.17557/tjfc.413818
  22. Ziaei, S.M., Salimi, K., Amiri, S.R., & Rigi, M.R. (2023). Effect of end-of-season drought and foliar application of Zinc and Manganese sulfate on yield and yield components of safflower (Carthamus tinctorius) in Saravan climatic conditions. Environmental Stresses in Crop Sciences, 16(3), 803-815. https://doi.org/10.22077/escs.2023.5002.2101
  23. SAS Institute Inc. 2019. SAS 9.4 Programmer’s Guide: Essentials. Cary, NC: SAS Institute Inc.
  24. Maechler, M., Rousseeuw, P., Struyf, A., Hubert, M., & Hornik, K., et al (2024). R package ‘cluster’ Ver. 2.1.2. Cluster analysis basics and extensions.
    https://doi.org/10.32614/CRAN.package.cluster
  25. Arzangh, S., Darvishzadeh, R., & Alipour, H. (2021). Evaluation of genetic diversity of maize lines (Zea mays L.) under normal and salinity stress conditions. Cereal Research, 11(3), 243-268. https://doi.org/10.22124/cr.2022.21075.1699. [In Persian]
  26. Sasaki, A. (2023). R Core Team. R: A Language and Environment for Statistical Computing_. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org
  27. Shiravand, R., & Majidi, M. (2014). Drought tolerance of wild and cultivated species of safflower and assessment of morphological variation. Iranian Journal of Field Crops Research, 12(4), 738-750. https://doi.org/10.22067/gsc.v12i4.24687. [In Persian]
  28. Vafaei, S., Tobeh, A., Hokmalipour, S., & Ashrafi, Reza. (2012). Investigate the correlation between components of grain filling and grain yield of different cultivars of rain-fed safflower. World Applied Sciences Journal, 18, 1257-1263. https://doi.org/10.5829/idosi.wasj.2012.18.09.896.
  29. Soares, R.S., Silva, H.W.da., Candido, W.dos.S., & Vale, L.S.R. (2018). Correlations and path analysis for fruit yield in pepper lines (Capsicum chinense ). Comunicata Scientiae, 8(2), 247–255. https://doi.org/10.14295/cs.v8i2.1839
  30. Salehian, M., Darvishzadeh, R., Rezazadeh Bari, M., Jabbari, M., & Jannatdoust, M. (2022). Evaluation of genetic variability of agro-morphological traits in Iranian pepper population (Capsicum annuum ). Plant Productions, 45(2),157-168. https://doi.org/10.22055/PPD.2022.37868.1988. [In Persian]
  31. Malleshappa, S.M., Hiremath, I., & Ravikumar, R.I. (2003). Negative associations between important quantitative traits in safflower (Carthamus tinctorius ). Sesame and Safflower Newsletter, 80-84.
  32. Omidi, A.H., Khazaei, H., & Hongbo, S. (2009). Variation for some important agronomic traits in spring Safflower (Carthamus tinctorius ) genotypes. American-Eurasian Journal of Agricultural & Environmental Sciences, 5(6):791-795.
  33. Pavithra, K.P., Rajesh, S., Patil Harijan, Y., & Nishanth, G.K. (2016). Correlation and path analysis studies in Safflower (Carthamus tinctorius L.) germplasm. Research Journal of Agricultural Sciences, 7(2), 428-432.
  34. Sabaghnia, N., Ebrahimi, H., & Janmohammdi, M. (2024). Genetic variation among diverse safflower genotypes for some agro-morphological traits. OCL, 31. 17. https://doi.org/10.1051/ocl/2024015
  35. Abd El-Lattief., E.A. (2012). Evaluation of 25 safflower genotypes for seed and oil yields under arid environment in upper egypt. Asian Journal of Crop Science, 4, 72-79.
    https://doi.org/3923/ajcs.2012.72.79. [In Persian]
  36. Bahmankar, M., Nabati, D.A., & Dehdari, M. (2017). Genetic relationships among Iranian and exotic safflower using microsatellite markers. Journal of Crop Science and Biotechnology, 20, 159-165. https://doi.org/10.1007/s12892-017-0001-0.
  37. Ebrahimi, H., Sabaghnia, N., Javanmard, A., & Abbasi, A. (2023). Genotype by trait biplot analysis of trait relations in safflower. Agrotechniques in Industrial Crops, 3(2), 67-73. https://doi.org/10.22126/atic.2023.8906.1086.
  38. Shojaei, S.H., Mostafavi, K., Khosroshahli, M., Reza Bihamta, M., & Ramshini, H. (2020). Assessment of genotype-trait interaction in maize (Zea mays) hybrids using GGT biplot analysis. Food science & nutrition, 8(10), 5340–5351. https://doi.org/10.1002/fsn3.1826
  39. Welderufael, S., Abay, F., Ayana, A., & Amede, T. (2023). Genotype by trait (GT) and genotype by yield traits (GYT) analysis of sorghum landraces in Tigray, Northern Ethiopia. Crop Breed Genet Genom, 5(2),e230002. https://doi.org/10.20900/cbgg20230002
  40. Bakhshi, B., Oghan, H.A., Rameeh, V., Fanaei, H.R., Askari, A., Faraji, A., et al. (2023). Analysis of genotype by environment interaction to identify high-yielding and stable oilseed rape genotypes using the GGE-biplot model. Ecological Genetics and Genomics, 28, 100187. https://doi.org/10.1016/j.egg.2023.100187
  41. Baljani, R., Shekari, F., & Sabaghnia, N. (2015). Biplot analysis of trait relations of some safflower (Carthamus tinctorius L.) genotypes in Iran. Crop Research, 50(1-3), 63-73. Corpus ID: 90958270
  42. La Bella, S., Tuttolomondo, T., Lazzeri, L., Matteo, R., Leto, C., & Licata, M. (2019). An agronomic evaluation of new safflower (Carthamus tinctorius) germplasm for seed and oil yields under mediterranean climate conditions. Agronomy, 9(8), 468-484. https://doi.org/10.3390/agronomy9080468
  43. Beyyavas, V., & Dogan, L. (2022). Yield, yield components and oil ratios of irrigated and rainfed safflower cultivars (Carthamus tinctorius L.) under semi-arid climate conditions. Appl Ecol Environ Res, 20(2), 1807–1820. https://doi.org/15666/aeer/2002_18071820
  44. Gholami, M., Sabaghnia, N., Nouraein, M., Shekari, F. & Janmohammadi, M. (2018). Cluster analysis of some safflower genotypes using a number of agronomic characteristics. Journal of Crop Breeding, 10(25), 159- 166. https://doi.org/29252/jcb.10.25.159 . [In Persian]
Journal of Crop Production
Volume 18, Issue 1
March 2025
Pages 67-90

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