Investigation of genotype × environment interaction and seed yield stability of rapeseed genotypes in cold and mild cold regions of Iran

Alizadeh, Bahram; Rezaizad, Abbas; Yazdandoost Hamedani, Mohammad; Shiresmaeili, Gholamhossein; Nasserghadimi, Farshad; Khademhamzeh, Hamid Reza

doi:10.52547/pgr.7.2.6

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Volume 7, Issue 2 (2021)

pgr 2021, 7(2): 65-82

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Investigation of genotype × environment interaction and seed yield stability of rapeseed genotypes in cold and mild cold regions of Iran

Bahram Alizadeh ^*

, Abbas Rezaizad

, Mohammad Yazdandoost Hamedani

, Gholamhossein Shiresmaeili

, Farshad Nasserghadimi

, Hamid Reza Khademhamzeh

Oil Crops Research Department, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran , ba.alizadeh@areeo.ac.ir

Abstract: (7354 Views)

The genotype × environment interaction is a major challenge in the study of quantitative characters because it reduces yield stability in different environments and also it complicates the interpretation of genetic experiments and makes predictions difficult. In this regard to analysis of genotype × environment interaction and determine the yield stability of winter rapeseed genotypes in cold and mild cold regions of the country, 9 lines and 4 cultivars were evaluated in a randomized complete block design with three replications in six experimental field stations (Isfahan, Hamedan, Karaj, Kermanshah, Khoy and Zarghan) during 2015–2017 growing seasons. Results of combined analysis of variance indicated that the effects of environments, genotypes and genotype × environment interaction were significant, suggesting that the genotypes responded differently in the studied environment conditions. So, there was the possibility of stability analysis. The Nafis cultivar and BAL-92-1 line with seed yields 4086 and 3829 kg.h^-1, respectively, were better than overall mean and had lower ranks and rank variance than others. According to the results of stability analysis using Eberhart and Russel method, the BAL-92-1 line with higher seed yield than overall mean and regression coefficient equal one (bi=1) was identified as the genotype with high general stability for all regions. Based on the simultaneous selection method for yield and stability (YSi), the lines of HW-92-1, BAL-92-1, HW-92-1 and Nafis cultivar with the lowest values were stable, whereas lines BAL-92-4, HW-92-2, HW-92-3 and Ahmadi cultivar with highest values were unstable. Also, based on the SIIG index, the lines of HW-92-1, BAL-92-1, BAL-92-6, BAL-92-11 and Nafis cultivar with having high SIIG value as well as higher seed yield that total average were recognized as superior genotypes from the point of stability and seed yield. Finally, BAL-92-1 line with high yield and broad adaptability was selected as superior line for supplementary studies to introduce the new commercial cultivar in cold and mild cold regions of Iran.

Keywords: Broad adaptability, Eberhart and Russel method, SIIG index, Winter rapeseed

Full-Text [PDF 734 kb] (1145 Downloads)

Type of Study: Research | Subject: Population genetics
Accepted: 2021/04/6

References

1. Ahmadi, J., Vaezi, B. and Pour-Aboughadareh, A. (2016). Evaluation of forage yield stability of advanced lines of grass pea (Lathyrus sativa L.) by parametric and non-parametric methods. Journal of Crop Breeding, 8: 149-159 (In Persian).

2. Ahmadpour, S., Darvishzadeh, R., Sofalian, O. and Hatamzadeh, H. (2019). Evaluation of yield stability of sunflower inbred lines under salt stress conditions. Journal of Crop Breeding, 11: 1-10 (In Persian).

3. Akbarpour, O., Dehghani, H. and Sorkhi-Lalehloo, B. (2012). Study of grain yield stability of barley (Hordeum vulgare L.) promising lines in cold regions of Iran using regression methods. Iranian Journal of Crop Sciences, 14: 155-170 (In Persian).

4. Alishah, O., MahmoodJanloo, H., Hekmat, M.H., Naderi Arefi, A., Sidmasoomi, S.Y. and Talat, F. (2019). Investigation of genotype × environment interaction and yield stability of hopeful cotton (G. hirsutum L.) genotypes. Journal of Crop Breeding, 11: 226-236 (In Persian).

5. 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).

6. Becker, H. and Leon, J. (1988). Stability analysis in plant breeding. Plant Breeding, 101: 1-23. [DOI:10.1111/j.1439-0523.1988.tb00261.x]

7. Becker, H.C. (1981). Correlation among some statistical measures of phenotypic stability. Euphytica, 30: 835-884.

8. Dalló, S.C., Zdziarski, A.D., Woyann, L.G., Milioli, A.S., Zanella, R., Conte, J. and Benin, G. (2019). Across year and year-by-year GGE biplot analysis to evaluate soybean performance and stability in multi-environment trials. Euphytica, 215: 113.

9. Dehghani, M.R., Majidi, M.M., Mirlohi, A. and Saeidi, G. (2016). Integrating parametric and non-parametric measures to investigate genotype × environment interactions in tall fescue. Euphytica, 208: 583-596.

10. Dorrani-Nejad, M. and Mohammadi-Nejad, G. (2018). Stability analysis for seed yield in different fenugreek (Trigonella foenum-graecum L.) ecotypes using Eberhart-Russel regression and different univariate statistics methods. Journal of Crop Breeding, 10: 19-27 (In Persian).

11. Eagles, H. and Frey, K.J. (1977). Repeatability of the stability-variance parameter in oats 1. Crop Science, 17: 253-256 (In Persian).

12. Ebadi, A., Sabaghpour, S.H., Dehghani, H. and Kamrani, M. (2008). Non-parametric measures of phenotypic stability in chickpea genotypes (Cicer arietinum L.). Euphytica, 162: 221-229.

13. Eberhart, S.T. and Russell, W. (1966). Stability parameters for comparing varieties 1. Crop Science, 6: 36-40.

14. Esmaeilzadeh Moghaddam, M., Tahmasebi, S., Lotf Ali Ayeneh, G.A., Akbari Moghadam, H., Mahmoudi, M., Sayyahfar, M., Tabib Ghaffari, S.M. and Zali, H. (2018). Yield stability evaluation of bread wheat promising lines using multivariate methods. Cereal Research, 8: 333-344 (In Persian).

15. Esmaeilzadeh Moghaddam, M., Zakizadeh, M., Akbari, M.H., Abedini, E.M., Sayahfar, M., Nikzad, A., Tabib, G.S. and Lotfi, A.G. (2011). Genotype × environment interaction and stability of grain yield of bread wheat genotypes in dry and warm areas of Iran. Seed and Plant Improvement Journal, 27: 257-273 (In Persian).

16. Esmaeilzadeh Moghaddam, M., Zakizadeh, M., Akbari, M.H., Abedini, E.M., Sayahfar, M., Nikzad, A., Tabib, G.S. and Aeineh, A. (2010). Study of grain yield stability and genotype-environment interaction in 20 bread wheat lines in warm and dry areas of south of Iran. Electronic Journal of Crop Production, 3: 179-200 (In Persian).

17. Falconer, D.S. (1981). Introduction to quantitive genetics. 2nd Ed, Longman, London, UK.

18. Farshadfar, E. and Sutka, J. (2006). Biplot analysis of genotype-environment interaction in durum wheat using the AMMI model. Acta Agronomica Hungarica, 54: 459-467.

19. Gerrish, B.J., Ibrahim, A.M., Rudd, J.C., Neely, C. and Subramanian, N.K. (2019). Identifying mega-environments for hard red winter wheat (Triticum aestivum L.) production in Texas. Euphytica, 215: 129.

20. Hemmati, I., Pourdad, S.S. and Choukan, R. (2018). Studying the genotype × environment interaction under different conditions of moisture stress using graphical GGE biplot analysis in synthetic varieties of sunflower (Helianthus annuus L.). Environmental Stresses in Crop Scienses, 11: 471-480 (In Persian).

21. Hühn, M. and Léon, J. (1995). Nonparametric analysis of cultivar performance trials: experimental results and comparison of different procedures based on ranks. Agronomy Journal, 87: 627-632.

22. Hwang, C.L. and Yoon, K. (1981). Multiple Attributes Decision Making Methods and Applications. Springer, Berlin Heidelberg, DE.

23. Jafari, M., Asghari, Z.R., Alizadeh, B., Sofalian, O. and Zare, N. (2015). Study of seed yield stability in winter rapeseed (Brassica napus L.) genotypes using Eberhart and Russell's method. Iranian Journal of Field Crop Science, 45: 585-592 (In Persian).

24. Jafari, T. and Farshadfar, E. (2018). Stability analysis of bread wheat genotypes (Triticum aestivum L.) by GGE biplot. Cereal Research, 8: 199-208 (In Persian).

25. Jamshidmoghaddam, M. and Pourdad, S.S. (2013). Genotype× environment interactions for seed yield in rainfed winter safflower (Carthamus tinctorius L.) multi-environment trials in Iran. Euphytica, 190: 357-369.

26. Kang, M. (1988). A rank-sum method for selecting high-yielding, stable corn genotypes. Cereal Research Communication, 16: 113-115.

27. Khalili, M. and Pour‐Aboughadareh, A. (2016). Parametric and non-parametric measures for evaluating yield stability and adaptability in barley doubled haploid lines. Journal of Agricultural Science and Technology, 18: 789-803.

28. Mahdavi, A.M., Babaeian Jelodar, N., Farshadfar, E. and Bagheri, N. (2020). Evaluation of stability and adaption of bread wheat genotypes using univariate statistics parameters and AMMI. Plant Genetic Researches, 7(1): 19-32 (In Persian).

29. MINITAB, INC. (2005). Minitab User's Guide, Vers. 14. Minitab Inc, Harrisburg, Pennsylvania, USA

30. Moghaddaszadeh, M., Asghari Zakaria, R., Hassanpanah, D. and Zare, N. (2018). Non-parametric stability analysis of tuber yield in potato (Solanum tuberosum L.) genotype. Journal of Crop Breeding, 28: 50-63 (In Persian).

31. Mohammadi, M., Karimizadeh, R., Hosseinpour, T., Ghojogh, H., Shahbazi, K. and Sharifi, P. (2018). Use of parametric and non-parametric methods for genotype × environment interaction analysis in bread wheat genotypes. Plant Genetic Researches, 4: 75-88 (In Persian).

32. Mortazavian, S., Nikkhah, H., Hassani, F., Sharif, A.H.M., Taheri, M. and Mahlooji, M. (2014). GGE biplot and AMMI analysis of yield performance of barley genotypes across different environments in Iran. Journal of Agricultural Science and Technology, 16: 609-622.

33. Movahedi, Z., Dehghani, H. and Mofidian, M. (2010). A study of yield stability in cold region ecotypes of alfalfa (Medicago sativa L.) through non-parametric measures. Iranian Journal of Field Crop Science, 40: 103-111 (In Persian).

34. 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).

35. Nowosad, K., Liersch, A., Popławska, W. and Bocianowski, J. (2016). Genotype by environment interaction for seed yield in rapeseed (Brassica napus L.) using additive main effects and multiplicative interaction model. Euphytica, 208: 187-194.

36. Pourdad, S., Moghaddam, M., Faraji, A. and Naraki, H. (2014). Study on different non-parametric stability methods on seed yield of spring rapeseed varieties and hybrids. Iranian Journal of Field Crop Science, 44: 539-548 (In Persian).

37. Pourdad, S.S. and Jamshidmoghaddam, M. (2013). Study on genotype × environment interaction through GGE biplot for seed yield in spring rapeseed (Brassica Napus L.) in rain-fed condition. Journal of Crop Breeding, 5: 1-13 (In Persian).

38. Sabaghnia, N., Dehghani, H. and Sabaghpour, S.H. (2006). Nonparametric methods for interpreting genotype × environment interaction of lentil genotypes. Crop Science, 46: 1100-1106.

39. Safavi, S. and Bahraminejad, S. (2017). The evaluation of genotype × environment interactions for grain yield of oat genotypes using AMMI model. Journal of Crop Breeding, 922: 125-132 (In Persian).

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

41. Setimela, P., Vivek, B., Bänziger, M., Crossa, J. and Maideni, F. (2007). Evaluation of early to medium maturing open pollinated maize varieties in SADC region using GGE biplot based on the SREG model. Field Crops Research, 103: 161-169.

42. Shiri, M.R. and Bahrampour, T. (2015). Genotype× environment interaction analysis using GGE biplot in grain maize (Zea mays L.) hybrids under different irrigation conditions. Cereal Research, 5: 83-94 (In Persian).

43. Shukla, G. (1972). Some statistical aspects of partitioning genotype environmental components of variability. Heredity, 29: 237-245 (In Persian).

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

45. Sserumaga, J.P., Oikeh, S.O., Mugo, S., Asea, G., Otim, M., Beyene, Y., Abalo, G. and Kikafunda, J. (2016). Genotype by environment interactions and agronomic performance of doubled haploids testcross maize (Zea mays L.) hybrids. Euphytica, 207: 353-365.

46. Vaezi, B., Pour-Aboughadareh, A., Mohammadi, R., Armion, M., Mehraban, A., Hossein-Pour, T. and Dorii, M. (2017). GGE biplot and AMMI analysis of barley yield performance in Iran. Cereal Research Communications, 45: 500-511.

47. Vaezi, B., Pour-Aboughadareh, A., Mohammadi, R., Mehraban, A., Hossein-Pour, T., Koohkan, E., Ghasemi, S., Moradkhani, H. and Siddique, K.H. (2019). Integrating different stability models to investigate genotype × environment interactions and identify stable and high-yielding barley genotypes. Euphytica, 215: 63.

48. Wachira, F., Ng'etich, W., Omolo, J. and Mamati, G. (2002). Genotype × environment interactions for tea yields. Euphytica, 127: 289-297.

49. Yan, W. and Kang, M.S. (2003). GGE biplot analysis: A graphical tool for breeders, geneticists and agronomists. CRC Press, Boca Raton, FL, USA.

50. Yan, W., Cornelius, P.L., Crossa, J. and Hunt, L. (2001). Two types of GGE biplots for analyzing multi‐environment trial data. Crop Science, 41: 656-663.

51. Yan, W., Hunt, L., Sheng, Q. and Szlavnics, Z. (2000). Cultivar evaluation and mega‐environment investigation based on the GGE biplot. Crop Science, 40: 597-605.

52. Yan, W., Kang, M.S., Ma, B., Woods, S. and Cornelius, P.L. (2007). GGE biplot vs. AMMI analysis of genotype‐by‐environment data. Crop Science, 47: 643-653.

53. 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).

54. Zali, H., Sofalian, O., Hasanloo, T., Asgharii, A. and Hoseini, S.M.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.

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‎ 10.52547/pgr.7.2.6

‎ 20.1001.1.23831367.1399.7.2.9.8

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Alizadeh B, Rezaizad A, Yazdandoost Hamedani M, Shiresmaeili G, Nasserghadimi F, Khademhamzeh H R. Investigation of genotype × environment interaction and seed yield stability of rapeseed genotypes in cold and mild cold regions of Iran. pgr 2021; 7 (2) :65-82
URL: http://pgr.lu.ac.ir/article-1-198-en.html

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