کاربرد روش AMMI در تجزیه اثر متقابل ژنوتیپ × محیط و تعیین پایداری عملکرد لاین‌های خالص سویا (Glycine max L.)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار پژوهش موسسه تحقیقات اصلاح و تهیه نهال و بذر

2 کارشناس مرکز تحقیقات کشاورزی و منابع طبیعی لرستان

3 مربی پژوهش مرکز تحقیقات کشاورزی و منابع طبیعی اردبیل (پارس آباد مغان)

چکیده

این تحقیق با هدف بررسی سازگاری و پایداری عملکرد دانه 19 لاین خالص سویا به همراه رقم تجارتی کوثر در سه منطقه کرج، خرم‌آباد و مغان طی دو سال زراعی ( 1393- 1392) اجرا شد. بدین منظور پس از آماده سازی زمین و پیاده نمودن نقشه آزمایشی اقدام به کشت بذور ژنوتیپ‌ها در کرت‌های مربوطه گردید. در طول دوره رشد گیاه مراقبت‌های زراعی معمول به عمل آمد و پس از برداشت عملکرد هر ژنوتیپ برآورد گردید. تجزیه واریانس مرکب بر اساس مدل امی، آماره ASV، نمودار دو بعدی عملکرد ژنوتیپ‌ها (لاینهای خالص) و محیط‌ها برای مولفه اول IPCA1 و نیز نمودار دو بعدی دو مولفه IPCA1 و IPCA2 توسط نرم‌افزار Genstat 12 انجام شد. نتایج تجزیه واریانس مرکب امی بیانگر معنی‌دار بودن اثرات جمع‌پذیر ژنوتیپ و محیط و اثر ضرب‌پذیر ژنوتیپ × محیط در سطح 1 % بود. مجموع مربعات اثرات ژنوتیپ، محیط و ژنوتیپ × محیط به‌ترتیب 4% ، 46 % و 13 % از مجموع مربعات کل را تشکیل دادند. همچنین سه ژنوتیپ: (Spry × Nemaha/7) G10، ( Spry × Savoy/3) G16 و(Kousar) G20 بر اساس معیار ASV و نمودارهای بای‌پلات1 و3 از پایدارترین ژنوتیپ‌ها بودند که ژنوتیپ(Spry × Nemaha/7) G10 با توجه به عملکرد (Kg/ha 2764) و پایداری به عنوان بهترین ژنوتیپ انتخاب شد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Application of AMMI approuch in “Genotype x Environment” interaction analysis and determining yeild stability of soybean purelines [Glycine max (L.) Merril ]

نویسندگان [English]

  • HAMID REZA BABAEI 1
  • Hosein Sabzi 2
  • Nasrin Razmi 3
1 1- Research Assistant of Professor of Center of Agricultural Research and Natural Resources Khorasan Razavi Province. (Corresponding author: 30241hrbabaei@gmail.com)
2 2- Research Expert of Center of Agricultural Research and Natural Resources Lorestan Province.
3 3- Research tutor of Center of Agricultural Research and Natural Resources Ardabil Province (Parsabad Moghan)
چکیده [English]

This study conducted to evaluating adaptability and seed yeild stability of 19 soybean purelines and Kousar cultvar (check) in three regions: Karaj, Khoram abad and Moghan in during 1392 and 1393 years. For this purpose after preparing soil and planing experimental design, genotype seeds planted in the respective plots. The usual agronomic attentions carried out at growth stages and each genotype yeild estimated after harvest. Combined analysis of variance according to AMMI model, ASV parameter, Biplot Genotypes & Environments means versus IPCA1 and Biplot IPCA1 versus IPCA2 computed by Genstat Ver.12 . the results of ANOVA and AMMI analysis showed that genotye and environment additive effects and “Genotype x Environment” multiplicative effect are significant in % 1 level. Sum of squares of genotype, environment and Gen. × Env. factors founded % 4, % 46 and % 13 of total Sum of squares respectivily. Also according to ASV parameter and results of 1 and 3 biplots three genotypes: G10 (Spry × Nemaha/7) , G16 ( Spry x Savoy/3) and G20 (Kousar) were the most stable and genotype G10 (Spry × Nemaha/7) selected as the best genotype considering the yeild (2764 Kg/ha) and stability.

کلیدواژه‌ها [English]

  • : Soybean
  • Purelines
  • yeild Stability
  • “Genotype x Environment” interaction and AMMI Method
Basford, K.E. & Cooper, M. (1998). Genotype by environment interactions and some
considerations of their implication for wheat breeding in Australia. Australian Journal of
Agricultural Research, 49: 154-175.
Bhartiya, A., Aditya, J.P., Pushpendra, K. S., Purwar, J.P. & Agarwal, A. (2017) AMMI & GGE biplot analysis of multi environment yield trial of soybean in North Western Himalayan state Uttarakhand of India. Legume Research Journal, 40 (2) , 306-312.
Buitrago, I. C., Mc Intire, E. Q. & Mendoza, M. G. (2011). Identifying mega‑environments to enhance the use of superior rice genotypes in Panama. Pesquisa Agropecuária Brasileira., Brasília, (46) 9, 1061-1069.
Campbell, B.T. & Jones,  M. A. (2005). Assessment of genotype x environment  interactions for yield and fiber quality in cotton performance trials. Euphytica, 144:69-78.
Campton, R. A. (1963). The use of biplots in stability among oat lines. Crop Sci. 33: 423-426.
Chaudhary, K. J.& Wu, J. (2012). Stability analysis for yeild and seed quality of soybean [ Glycine max (L.) Merril] across different environment in eastern South Dakota. Annual Conference on Applied Statistics in Agriculture. Retrieved Aug. 4, 2017. .http://newprairiepress.org/agstatconference/2012/proceedings/11
Eberhart, S. A. & Russel, W. A. (1966). Stability parameters for comparing varieties. Crop Sci. 6: 36-40.
10. Ebdon, J. S. & Gauch, H. G. (2002a). Additive main effect and multiplicative interaction analysis of national turfgrass performance trials: Interpretation of genotype x environment interaction. Crop Sci. 42:489-496.
11. Gurmu, F., Mohammed, H. & Alemaw, G. (2009). Genotype x Environment interactions and stability of soybean for grain yield and nutrition quality. African Crop Science Journal. 17,  87-99.
12. Jha, S.K., Singh, N.K., Kumar, R.A., Agrawal, P.K., Bhatt, J.C., Guleria, S.K., Lone, A.A., Sudan, R.S., Singh, K.P. & Mahajan, V. (2013). Additive main effects and multiplicative interaction analysis for grain yield of short duration maize hybrids in North-Western Himalayas. Indian Journal of  Genetics & Plant Breeding. 73: 29-35.
13. Kaya, Y., Akçura, M. & Taner, S. (2006). GGE biplot analysis of multi environment yield trials in bread wheat. Turkish Journal of Agriculture and Forestry, 30:325-337.
14. Kempton, R.A. 1984. The use of biplot in interpreting variety by environment interaction. Journal of
15. Agriculture Science Cambridge. 122: 335-342.
16. Pacheco, R. M., Duarte, J. B., Souza, P. I. M., Silva, S. A. & Nunes, J. (2009). Key locations for soybean genotype assessment in Central Brazil. Pesquisa Agropecuária Brasileia.  44 ( 5), 478-486.
17. Payne, R.W., Harding, S. A., Murray, D. A. & Soutar, D. M. ( 2009). GenStat Release 12. Published by VSN International, 5 The Waterhouse, Waterhouse Street, Hemel Hempstead, Hertfordshire HP1 1ES, UK.
18. Perkinz, J.M. (1972). The principal component analysis of genotype environment interaction and physical measures of the environment. Hered. 29: 51-57.
19. Samonte, S. O. P. B., Wilson, L. T., McClung, A. &  Mand Medley, J. C. (2005) Targeting cultivars onto rice growing environments using AMMI and SREG GGE biplot analysis. Crop Science 45: 2414-2424.
20. Silveira, D. A., Pricinotto,L. F., Nardino, M., Bahry, C. A., Cavenaghi Prete, C.E. & Cruz, L. (2016). Determination of the adaptability and stability of soybean cultivars in different locations and at different sowing times in Parana state using the AMMI and Eberhart and Russel methods. Seminar: Ciências Agrárias, Londrina. 37( 6),  3973-3982.
21. Tarakanovas,  P.  & Sprainaitis,  A. (2005). Main additive effect and  multiplicative interaction analysis of white clover genetic resources. Biologija, 04:38-42.
22. Unknown . (2017). Agriculture statistics. Center of  information and communication technology. Deputy of planning and economic affairs . Ministry of Agriculture Jihad. Retrieved Dec. 25, 2017. http://www.amar.maj.ir
Yan, W., Hunt, L.A., Sheng, Q. & Szlavnics, Z. (2002). Cultivar evaluation and mega-environment
24. investigation based on the GGE biplot. Crop Sciences, 40: 597-605.
25. Yan, W. (2011). GGE Biplot vs. AMMI Graphs for Genotype by Environment Data Analysis. Journal of the India Society of Agricultural Statistics, 65:181-193.
26. Yates, F. & Cochran, W. G. (1956). The analysis of experiments. J. Agric. Sci. 14 : 742-754.
27. Finlay, K. W. And Wilkinson. G. N., (1963). The analysis of adaptation  in  plant breeding programe. Aust. J. Agric. Res. 14: 742- 754.
28. Zobel , R. W., Wright, M. J., and Gauch, H. G. (1988). Statistical analysis of a yield trial. Agron. J. 80: 388-39.