Multi-Trait Selection of Promising Advanced Lines of Rapeseed Using Selection Index of Ideal Genotypes

Gholizadeh, Amir; Amiri Oghan, Hassan; Rameeh, Valiollah; Payghamzadeh, Kamal; Bakhshi, Behnam; Alizadeh, Bahram; Dalili, Seyed Alireza; Kia, Shahriar; Shariati, Farnaz

doi:10.52547/pgr.9.1.7

[Home ] [Archive]

[ فارسی ]

Main Menu

Home

Journal Information

Articles archive

For Authors

For Reviewers

Registration

Contact us

Site Facilities

Search in website

Receive site information

Volume 9, Issue 1 (2022)

pgr 2022, 9(1): 85-98

Back to browse issues page

Multi-Trait Selection of Promising Advanced Lines of Rapeseed Using Selection Index of Ideal Genotypes

Amir Gholizadeh

, Hassan Amiri Oghan ^*

, Seyed Alireza Dalili

, Shahriar Kia

, Farnaz Shariati

Oil Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran , amirioghan@spii.ir

Abstract: (4870 Views)

Genetic diversity is key to breeding programs and increasing selection efficiency. In this study, 19 promising advanced lines (F7 generation) along with two cultivars, Dalgan and, RGS003 were evaluated in a randomized complete block design with three replications in three experimental field stations (Gorgan, Sari and, Zabol) during the 2020–2021 growing season. The highest phenotypic and genotypic coefficient of variations was found for number of lateral branches and number of pods per plant, respectively. The highest broad sense heritability was estimated for days to end of flowering, and days to start of flowering and the lowest broad sense heritability was estimated for the plant height. The genotypes G16, G18, G15, G1, G2, G5, and G20 with a higher SIIG values as well as a higher seed yield above average were introduced as superior genotypes with respect to yield and other agronomic traits. Therefore, these genotypes can be used for further testing, including adaptation tests. Also, the results of factor analysis and genetic correlation coefficients indicated a positive relationship between number of lateral branches, number of pods per plant and number of seeds per pod with seed yield and seed yield. Generally, it can be concluded that number of lateral branches, number of pods per plant and number of seeds per pod traits could be used as the appropriate criteria to select for increasing seed yield in rapeseed breeding programs.

Keywords: Phenotypic and genotypic coefficient of variation, Genetic correlation, Seed yield, Rapeseed, Promising advanced line

Full-Text [PDF 570 kb] (1051 Downloads)

Type of Study: Research | Subject: Plant improvement

References

1. Abdollahi Hesar, A., Sofalian, O., Alizadeh, B., Asgharii, A. and Zali, M. (2020). Evaluation of some autumn rapeseed genotypes based on morphological traits and SIIG index. Journal of Crop Breeding, 12: 151-159 (In Persian). [DOI:10.29252/jcb.12.34.151]

2. Alizadeh, B., Rezaizad, A., Yazdandoost Hamedani, M., Shiresmaeili, G., Nasserghadimi, F. and Khademhamzeh, H.R. (2021). Investigation of genotype × environment interaction and seed yield stability of rapeseed genotypes in cold and mild cold regions of Iran Plant Genetic Researches, 7: 65-82 (In Persian).

3. Alizadeh, B., Yazdandust Hamedani, M., Rezaei Zad, A., Azizinia, S., Khiyavi, M., Shirani Rad, A. H., Javidfar, F., Pasban Eslam, B., Mostafavi Rad, M., Shariati, F., Rahmanpour Ozan, S., Alem Khumaram, M.H., Majd Nasiri, B., Amiri Oghan, A. and Zareei Siahbidi, A. (2019). Nima, new winter oilseed rape variety for cultivation in the cold and moderately cold regions of Iran Research Achievements for Field and Horticulture Crops, 8: 61-76 (In Persian).

4. Ghanbari, S., Nooshkam, A., Fakheri, B.A. and Mahdinezhad, N. (2019). Relationship between yield and its component in soybean genotypes (Glycine Max L.) using multivariate statistical methods. Journal of Crop Breeding, 11: 85-92 (In Persian). [DOI:10.29252/jcb.11.29.85]

5. Gholizadeh, A. and Dehghani, H. (2016). Graphic analysis of trait relations of Iranian bread wheat germplasm under non-saline and saline conditions using the biplot method. Genetika, 48: 473-486. [DOI:10.2298/GENSR1602473G]

6. Gholizadeh, A., Ghaffari, M. and Shariati, F. (2021a). Use of selection index of ideal genotype (SIIG) in order to select new high yielding sunflower hybrids with desirable agronomic characteristics. Journal of Crop Breeding, 13(38): 116-123 (In Persian).

7. Gholizadeh, A., Khodadadi, M. and Sharifi-Zagheh, A. (2021b) Modeling the final fruit yield of coriander (Coriandrum sativum L.) using multiple linear regression and artificial neural network models. Archives of Agronomy and Soil Science, 67: 1-15. [DOI:10.1080/03650340.2021.1894637]

8. Holland, J.B. (2006). Estimating genotypic correlations and their standard errors using multivariate restricted maximum likelihood estimation with SAS Proc MIXED. Crop Science, 46: 642-654. [DOI:10.2135/cropsci2005.0191]

9. Kanwal, N., Ali, F., Ali, Q. and Sadaqat, H.A. (2019). Phenotypic tendency of achene yield and oil contents in sunflower hybrids. Acta Agriculturae Scandinavica, Section B-Soil & Plant Science, 69: 690-705. [DOI:10.1080/09064710.2019.1641546]

10. Karimizadeh, R., Hosseinpour, T., Sharifi, P., Alt Jafarby, J., Shahbazi, K. and Keshavarzi, K. (2021). Evaluation of grain yield stability of durum wheat genotypes using parametric and non-parametric methods. Plant Genetic Researches, 8: 115-132 (In Persian).

11. Leilah, A. and Al-Khateeb, S. (2005). Statistical analysis of wheat yield under drought conditions. Journal of Arid Environments, 61: 483-496. [DOI:10.1016/j.jaridenv.2004.10.011]

12. Majidi, M.M., Jafarzadeh Ghahdarijani, M., Rashidi, F. and Mirlohi, A. (2016). Relationship of different traits in rapeseed (Brassica napus L.) cultivars under normal and drought conditions. Journal of Crop Breeding, 8(17): 55-65 (In Persian). [DOI:10.18869/acadpub.jcb.8.17.65]

13. Moradi, M. and Soltani Howyzeh, M. (2018). Evaluation of genetic diversity and heritability of the grain yield and yield components in spring rapeseed cultivars. Journal of Crop Breeding, 10: 207-214 (In Persian). [DOI:10.29252/jcb.10.26.207]

14. Moradi, M., Soltani Howyzeh, M. and Shahbazi, E. (2017). Study the relations between grain yield and related traits in canola by multivariate analysis. Journal of Crop Breeding, 9(23): 187-194 (In Persian). [DOI:10.29252/jcb.9.23.187]

15. Najafi Mirak, T., Dastfal, M., Andarzian, B., Farzadi, H., Bahari, M. and Zali, H. (2018). Assessment of non-parametric methods in selection of stable genotypes of durum wheat (Triticum turgidum L. var. durum). Iranian Journal of Crop Sciences, 20: 126-138 (In Persian).

16. Ramazani, S.H.R. (2016). Surveying the relations among traits affecting seed yield in sesame (Sesamum indicum L.). Journal of Crop Science and Biotechnology, 19: 303-309. [DOI:10.1007/s12892-016-0053-0]

17. Roostabaghi, B., Dehghan, H., Alizadeh, B. and Sabaghnia, N. (2013). Study of diversity and evaluation of relationships between yield and yield components of rapeseed via multivariate methods. Journal of Crop Production and Processing, 2(6): 53-63 (In Persian).

18. Roy, D. (2000). Plant breeding, Analysis and Exploitation of Variation. Alpha Science International, Oxford, UK.

19. Sabaghnia, N., Dehghani, H., Alizadeh, B. and Mohghaddam, M. (2010). Interrelationships between grain yield and 20 related traits of 49 canola (Brassica napus L.) genotypes in non-stressed and water-stressed environments. Spanish Journal of Agricultural Research, 8: 356-370. [DOI:10.5424/sjar/2010082-1195]

20. Safari, S. and Mehrabi, A.A. 2016. Genetic relationships of rapeseed cultivars revealed by RAPD markers. Journal of Crop Breeding, 8(19): 170-177 (In Persian).

21. SAS, Inc. (2011). Base SAS 9.1 Procedures Guide. SAS Institute Inc, Cary, North Carolina, USA.

22. Soltani Howyzeh, M., Moradi, M., Saki nezhad, T., Zakernezhad, S. and Etaa, A. (2018). Evaluation of the relationships among yield and related traits in spring canola cultivars using path analysis. Journal of Crop Breeding, 10(27): 125-134 (In Persian). [DOI:10.29252/jcb.10.27.125]

23. SPSS, Inc. (2010). SPSS 20. Users Guied. IBM Corp, Chicago, USA.

24. Tahmasebi, S., Dastfal, M., Zali, H. and Rajaie, M. (2018). Drought tolerance evaluation of bread wheat cultivars and promising lines in warm and dry climate of the south. Cereal Research, 8: 209-225 (In Persian).

25. Zali, H. and Barati, A. (2020). Evaluation of selection index of ideal genotype (SIIG) in other to selction of barley promising lines with high yield and desirable agronomy traits. Journal of Crop Breeding, 12: 93-104 (In Persian). [DOI:10.29252/jcb.12.34.93]

26. Zali, H., Hasanloo, T., Sofalian, O., Asghari, A. and Zeinalabedini, M. (2016). Appropriate strategies for selection of drought tolerant genotypes in canola. Journal of Crop Breeding, 8(20): 77-90 (In Persian). [DOI:10.29252/jcb.8.18.191]

27. Zali, H., Hasanloo, T., Sofalian, O., Asgharii, A. and Enayati Shariatpanahi, M. (2019). Identifying drought tolerant canola genotypes using selection index of ideal genotype. Journal of Crop Breeding, 11: 117-126 (In Persian). [DOI:10.29252/jcb.11.29.117]

28. Zali, H., Sofalian, O., Hasanloo, T., Asgharii, A. and Hoseini, S.M. (2015). Appraising of drought tolerance relying on stability analysis indices in canola genotypes simultaneously, using selection index of ideal genotype (SIIG) technique: Introduction of new method. Biological Forum-An International Journal, 7(2): 703-711.

Send email to the article author

‎ 10.52547/pgr.9.1.7

‎ 20.1001.1.23831367.1401.9.1.7.8

Mendeley

Zotero

RefWorks

Gholizadeh A, Amiri Oghan H, Rameeh V, Payghamzadeh K, Bakhshi B, Alizadeh B, et al . Multi-Trait Selection of Promising Advanced Lines of Rapeseed Using Selection Index of Ideal Genotypes. pgr 2022; 9 (1) :85-98
URL: http://pgr.lu.ac.ir/article-1-232-en.html

Rights and permissions
	This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Volume 9, Issue 1 (2022)

Back to browse issues page

Persian site map - English site map - Created in 0.06 seconds with 38 queries by YEKTAWEB 4657