ارزیابی پایداری لاین‌ها‌ی پیشرفته سویا (Glycine max L.) در شرایط تنش خشکی با استفاده از روش GGE بای پلات و Ammi

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استاد، موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، آموزش و ترویج کشاورزی (AREEO)، کرج، ایران،

2 استادیار، موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، آموزش و ترویج کشاورزی (AREEO)، کرج، ایران،

3 استادیار، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی صفی آباد دزفول، سازمان تحقیقات آموزش و ترویج کشاورزی (AREEO) دزفول، ایران،

چکیده

سابقه و هدف: سویا (Glycine max L.) مهم‌ترین گیاه روغنی در جهان است. عملکرد سویا وتوزیع جغرافیایی آن در کشور می‌تواند به شدت توسط تنش‌های غیرزیستی همچون خشکسالی محدود شود.از این رو نیاز دایمی به اصلاح ارقام سویا با عملکرد بالا و پایدار در محیط‌های مختلف وجود دارد. در این تحقیق به بررسی پایداری و سازگاری لاین‌های پیشرفته سویا در شرایط تنش کم آبی پرداخته شده است.
مواد و روش‌ها: در این تحقیق 14 لاین برتر سویا که در آزمایشات مقدماتی ارزیابی عملکرد سویا در مناطق مختلف برتر بوده‌اند به همراه دو رقم صبا و کوثر در دو آزمایش جداگانه در قالب طرح بلوک‌های کامل تصادفی در سه تکرار در دو سال زراعی 95 - 1394 در کرج ارزیابی شدند. هر دو آزمایش تا زمان استقرار گیاهچه و ظهور مرحله V4-V5 که مصادف با توسعه کامل چهارمین تا پنجمین برگ سه برگچه‌ای بود، مشابه یکدیگر آبیاری گردیده و پس از آن، در آزمایش‌های اول و دوم به ترتیب هر هفته و یک هفته در میان ( به ترتیب 55-50 و 120-100 میلی‌متر تبخیر از تشتک تبخیر کلاس A) آبیاری شدند. در پایان دو سال، پایداری و سازگاری لاین‌ها، با روش GGE ‌بای‌پلات، AMMI و میانگین رتبه میانگین ‌عملکرد بررسی شد.
یافته‌ها: نتایج نشان داد اثرات ژنوتیپ، محیط و ژنوتیپ × محیط به ترتیب 20، 68 و 12 درصد از کل مجموع مربعات را توجیه نمودند. همچنین دو مؤلفه اصلی اول معنی‌دار بودند و هرکدام‌ به ترتیب 67 و 24 درصد از مجموع مربعات اثر متقابل را به خود اختصاص دادند. بیشترین عملکرد دانه در شرایط بدون تنش به ترتیب در لاین‌های G1، G3 وG2 مشاهده شد. همچنین در شرایط تنش خشکی بیشترین عملکرد در لاین‌های G3 وG2 بدست آمد. لاین G3 با داشتن عملکرد بالاتر از متوسط کل در هر دو شرایط بدون تنش و تنش، به عنوان ژنوتیپ متحمل به خشکی شناخته شد.
نتیجه گیری: بر اساس نمودار بای پلات، رتبه‌بندی میانگین و انحراف معیار رتبه عملکرد دانه لاین‌ها G3، G1، G2 و G7 کم‌ترین اثر متقابل را با محیط داشته و به عنوان لاین‌های پایدار شناسایی شدند. در نمودار بای پلات دو مولفه اصلی اول و آماره ارزش پایداری مدل AMMI با عملکرد، لاین‌هایG2 ، G6، G3، G1 و G7 به عنوان لاین‌هایی با پایداری بیشتر شناخته شدند. براساس نمودار چندضلعی GGE، نیز لاین‌هایG1 ،G6 ، G2، G7، G4 و G5 انتخاب شدند. لاین‌های G3 و G8 در کرج در شرایط بدون تنش و تنش، سازگاری خصوصی خوبی را نشان دادند. لاین‌هایG3 ، G1 و G2 با میانگین عملکرد بالاتر از میانگین کل و ارقام شاهد به عنوان لاین‌های مناسب جهت کشت در مناطق کم آب معرفی ‌می‌گردند و همچنین می‌توان از آن‌ها در برنامه‌های به‌نژادی آتی استفاده نمود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Stability evaluation of advanced soybean lines (Glycine max L.) in drought conditions using GGE-Biplot analysis and Ammi

نویسندگان [English]

  • Jahanfar Daneshian 1
  • Mehrzad Ahmadi 2
  • Seyed ahmad Kalantar ahmadi 3
1 Professor, Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
2 Assistant Prof., Seed and Plant Improvement Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
3 Assistant Professor, Safiabad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Dezful, Iran.
چکیده [English]

Introduction: Soja (Glycine max L.) is the most important oil crop in the world. Soybean yield and its geographical distribution in the country can be severely limited by abiotic practices such as drought. There is a constant need to improve soybean cultivars with stable yields in different environments. In this study, the stability and adaptability of advanced soybean lines under water stress conditions have been investigated.
Materials and methods: In this study, 14 top soybean lines that were superior in preliminary soybean yield evaluation experiments in different regions along with two cultivars, Saba and Kowsar, in two separate experiments. They were evaluated in a randomized complete block design with three replications in the two years of 2015-2016 in Karaj. Both experiments were similarly irrigated until seedling establishment and the emergence of the V4-V5 stage, which coincided with the complete development of the fourth to fifth of three-leaf. After that, the first experiment was irrigated weekly and the second one every other week (50-55 and 100-120 mm evaporation from Class A evaporation pan, respectively). At the end of two years, the stability and adaptability of the lines were evaluated by GGE biplot, AMMI, and the rank of the mean yield.
Results: The results showed that the effects of genotype, environment and genotype × environment explained 20, 68, and 12% of the total squares, respectively. Also, the first two main components were significant and each of them accounted for 67 and 24% of the total squares, respectively. The results of this study showed that the highest seed yield in non-stress conditions was observed in G1, G3 and G2 lines, respectively. Also in drought stress conditions, the highest seed yield was obtained from G3 and G2 lines. The G3 line was known as a drought tolerant genotype with higher than total average yield in both non-stress and stress conditions.
Conclusion: According to the mean rank and standard deviation of seed yield rank of lines biplot diagram, G3, G1, G2, G7 had the least interaction with the environment and were identified as stable lines. in the first two main components biplot diagram, and the AMMI stability value (ASV) with the lines seed yield biplot diagram, G2, G6, G3, G1, G7 were recognized as more stable lines. Based on the GGE polygon diagram, lines G1, G6, G2, G7, G4, and G5 were also selected. Also, G3, and G8 lines showed good private adaptability with Karaj in stress-non stress conditions. The results showed that line G3, G1, G2 with higher seed yield than the total mean and control cultivars can be introduced as a suitable line for cultivation in low water areas.and they can also be used in future breeding programs.

کلیدواژه‌ها [English]

  • Dehydration stress
  • Seed yield
  • advanced soybean line
  • Stability and adaptability

مراجع

  1. Chaudhary, K.R. and Wu, J. 2012. “Stability Analysis for Yield and Seed Quality of Soybean [Glycine Max (L.) Merril] Across Different Environments in Eastern South Dakota. Conference on Applied Statistics in Agriculture. 215-220.
  2. Wu, N., Guan, Y. and Shi, T. 2011. Effect of water stress on physiological traits and yield in rice backcross lines after anthesis. Energy Proced. 5: 5. 255-260.
  3. Ku, Y.S., Au-Yeung, W.K., Yung, Y.L., Li, M.W., Wen, C.Q., Liu, X. and Lam, H.M. 2013. Drought stress and tolerance in soybean. In a comprehensive survey of international soybean research - genetics, physiology, agronomy and nitrogen relationships (eds). J.E. Board (New York, NY: InTech). 12: 1. 209-237.
  4. Khalili, M., Naghavi, M., Pour-Aboughadareh, A. and Rad, N.H. 2013. Effects of drought stress on yield and yield components in maize cultivars (Zea mays). Int J. Agron Plant Prod. 4: 38-49.
  5. Santos, A., Amaral Júnior, A.T., Nascimento Ferreira Kurosawa, Ra., Schegoscheski Gerhardt, I.F. and Fritsche Neto, R. 2017. GGE Biplot projection in discriminating the efficiency of popcorn lines to use nitrogen. Cienc. Agrotecnol. 41: 1. 22-31.
  6. Kron, A.P., Souza, G.M. and Ribeiro, R.V. 2008. Water deficiency at different developmental stages of Glycine max can improve drought tolerance. Bragantia. 67: 1.43-49.
  7. Rolla, A.A.P., Carvalho, J.F.C, Fuganti-Pagliarini, R., Engels, C., Rio, A., Marin, S.R.R., Oliveira, M.C.N., Beneventi, M.A., Marcelino-Guimarães, F.C., Farias, J.R.B., Neumaier, N., Nakashima, K., Yamaguchi-Shinozaki, K. and Nepomuceno, A.L. 2014. Phenotyping soybean plants transformed with rd29A:AtDREB1A for drought tolerance in the greenhouse and field. Transgenic Res. 23: 1. 75-87.
  8. Daneshian, J. 2015. Evaluation of grain yield and agronomic traits of soybean cultivars and lines under water deficit condition. Final report. Seed and Plant improvment Institute. Agricultural Research, Education and Extention Organization (AREEO). 75p.
  9. Li, Y.C., Yu, D.Y., Xu, R. and Gai, J.Y. 2008. Effects of natural selection of several quantitative traits of soybean RIL populations derived from the combinations of Peking ×7605 and RN-9×7605 under two ecological sites. Sci. Agric. Sin. 41: 3. 1917-1926.
  10. Mcblain, B.A., Hesketh, J.D. and Bernard, R.L. 1987. Genetic effects on reproductive phenology in soybean isolines differing in maturity genes. Can. J. Plant Sci. 67: 1. 105-115.
  11. Becker, H.C. and Leon, J. 1988. Stability analysis in plant breeding. Plant Breed. 101: 1-23.
  12. Abay, F. and Bjornstad, A. 2009. Specific adaptation of barley varieties in different locations in Ethiopia. Euphytica. 167: 2. 181-195.
  13. Akcura, M., Taner, S. and Kaya, Y. 2011. Evaluation of bread wheat genotypes under irrigated multi-environment conditions using GGE biplot analyses. Turk J. Agric. 98: 1. 35-40.
  14. Miranda, G.V., Souza, L.V., Guimarães, L.J.M., Namorato, H.L., Oliveira, R. and Soares, M.O. 2009. Multivariate analyses of genotype × environment interaction of popcorn. Pesqui. Agropecu. Bras. 44: 1. 45-50.
  15. Mitrovic, B., Stanisavljevic, D., Treski, S., Stojakovic, M., Ivanovic, M., Bekavac, G. and Rajkovic, M. 2012. Evaluation of experimental maize hybrids tested in multi-location trials using AMMI and GGE biplot analysis. Turk J. Field Crop. 17: 1. 35-40.
  16. Karimzadeh, R., Dehghani, H., and Dehghanpour, Z. 2008. Use of Ammi method for estimsting genotype- environment interaction in early maturing corn hybrids. Seed Plant. 23: 4. 531-546.
  17. Tiwari, J.K. 2019. GGE biplot and AMMI model to evaluate spine gourd (Momordica dioica) for genotype× environment interaction and seasonal adaptation. Electron. J. Plant Breed. 10: 1. 264-271.
  18. Yan, W. and Tinker, N.A. 2006. Biplot analysis of multi-environment trial data: principles and applications. Can. J. Plant Sci. 86: 3. 626-645.
  19. Babaei, H.R., Sabzi, H. and Razmi, N. 2018.Application of AMMI approuch in “Genotype x Environment” interaction analysis and determining yield stability of soybean purelines [Glycine max (L.) Merril]. J. Field Crop Sci. 50: 1.129-137. (In Persian)
  20. Babaei, H.R., Nasrin, R., Hazarjaribi, E. and Hashemijazi, M. 2020. Study on adaptability and grain yield stability of soybean genotypes [Glycine Max (L.) Merril] through AMMI & GGE biplot analysis. Crop Breed.12:35. 238-250. (In Persian).
  21. Anggoro Susanto, G.W., Haksiwi Putri, P., Maulana, H., Wijaya, A.A. and Karuniawan, Agung. 2021. Mega-environment analysis and identify stable and high-yielding of new promising black soybean lines in Indonesia. Res. Sq. 3: 2.1-17.
  22. Emuohwo Edugbo, R., Emeka Nwofia, G. and Fayeun, L.S. 2015. An assessment of soybean (Glycine max, L. Merrill) grain yield in different environments using AMMI and GGE biplot models in humidorest fringes of Southeast Nigeria. Trop. Et. Subtrop. 48: 3.82-90.
  23. Dadras, A.R., Samizadeh, H. and Sabouri, H. 2017. Evaluation of soybean varieties and advanced lines yield under drought stress. Conditions using GGE biplot analysis. J. Crop Breed. 9: 23. 18-26.
  24. Purchase, J.L., Hatting, H. and Vandeventer, C.S. 2000. Genotype × environment interaction of winter wheat (Triticum aestivum) in South Africa: Π. Stability analysis of yield performance. South Afric. J. Plant Soil. 17: 3. 101-107.
  25. Asghari, Q., Azizi, S. R. and Mirzaei, S. 2016. Statistical yearbook of Alborz province 1394. Alborz. Prov. 1-560. (In Persian)
  26. President, Country Management and Planning Organization. 2016. Yearbook of National Statistics. SCI, Frost 4968. 912p. https://www.amar.org.ir. (In Persian)
  27. Liu, Z., Fan, X., Huang, W., Yang, J., Zheng, Y., Wang, S. and Qiu, L. 2017. Stability analysis of seven agronomic traits for soybean [(Glycine max (L.) Merr.] Tokachi nagaha and its derived cultivars using the AMMI model. Plant Prod. Sci. 20: 4.499-506.
  28. Farshadfar, E., Mahmodi, N. and Yaghotipoor, A. 2011. AMMI stability value and simultaneous estimation of yield and yield stability in bread wheat (Triticum aestivum). Aust. J. Crop Sci. 5: 13.1837-1844.
  29. Zahrabi, E., Atminan, A., Safari, H. and Ashraf Jafari, A. 2011. Evaluation of forage yield stability in extensions of Elymus hispidus species with AMMI model and other methods of stability analysis in both stress and non-stress environments. 5: 2. 209-218.
  30. Hailemariam, M. and Tesfaye, A. 2019. Genotype x environment interaction by ammi and gge-biplot stability analysis in grain yield for soybean [(glycine max ) Merrill] in Ethiopia. Int. j. for. hortic. 5: 4. 10-21.
  31. Yan, W.K. and Kang, M.S. 2003. GGE biplot analysis: a graphical tool for breeders, geneticists, and agronomists (Boca Raton: FL: CRC press). 288p.
  32. Najafi Mirak, T., Dastfal, M., Farzadi, H., Sayahfar, M. and Andarzian, B. 2020. Study of durum wheat yield stability in warm zone of Iran under normal and drought stress. J. Crop. 12: 35. 80- 90.
  33. Latifi, ,  Najaphy, A. and Zarei, L. 2020 .Study of grain yield stability of barley (Hurdem vulgare L.) genotypes by AMMI model. Env. Stresses Crop Sci. 13: 2. 319-329.
  34. Sadeghzadeh, B., Mohammadi, R ., Ahmadi, , Abedias, G.R., Ahmadi, M. M.,  Mohammadfam, M., Bahrami, N.,  Sharif Khaledian, M. and  Naserian, A.A. 2018. GGE biplot and AMMI application in the study of adaptability and grain yield stability of durum lines under dryland conditions. Env. Stresses Crop Sci.11: 2. 241-260. (In Persian)
  35. Sharifi, , Erfani, A., Mohaddesi, A., Abbasian, A., Aminpanah, H., Yousefi, M.M. and Saeedi, M. 2020. Stability analysis of grain yield of some of rice genotypes by parametric and nonparametric uni-variate methods. J. Crop Prod. 13: 3. 85-106. (In Persian)
  36. Frutuoso Silva, K.E., DoVale, J.C., Fritsche-Neto, R. and Newton Marques, J. 2021. GGE biplot projection in adaptability and stability inference of soybean in an agricultural center Paraná, Brazil. Scientific Article. Rev. Ciênc. Agron. 52: 1.1-9. 
  37. Krisnawati, A. and Muchlish Adie, M. 2018. GGE biplot analysis of multi-environment yield trials in soybean promising lines. J. Ilmu Pertanian (Agric Sci. J.) 3: 2. 72-81.
  38. Masoudi, , Abbasali, M., Aien, A. and Saif Amiri. S. 2021. Evaluation of sesame yield stability using statistical parameters and GGE biplot graphical methods. J. Crop Prod. 3: 1.71-84. (In Persian)
  39. Santos, A., Amaral Júnior, A.T., Nascimento Ferreira Kurosawa, Ra., Schegoscheski Gerhardt, I.F. and Fritsche Neto, R. 2017. GGE Biplot projection in discriminating the efficiency of popcorn lines to use nitrogen. Cienc. Agrotecnol. 41: 1. 22-31.
مجله تولید گیاهان زراعی
دوره 15، شماره 4
دی 1401
صفحه 119-138

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