ارزیابی پایداری عملکرد دانه ژنوتیپ‌های عدس با استفاده از تجزیه GGE بای‌پلات و AMMI

نوع مقاله : مقاله پژوهشی

نویسندگان

1 مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان کهگیلویه و بویراحمد، سازمان تحقیقات، آموزش و ترویج کشاورزی، گچساران، ایران.

2 مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرم‌آباد، ایران.

3 مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایلام، ایران.

4 گروه زراعت و اصلاح نباتات، دانشگاه آزاد اسلامی، واحد رشت، رشت، ایران.

چکیده

در این پژوهش 18 ژنوتیپ عدس در سه سال زراعی (95-1392) در شرایط دیم مناطق گچساران، ایلام و خرم‌آباد کشت ‌شدند. بر اساس تجزیه واریانس اثر اصلی افزایشی و ضرب پذیر (AMMI) اثر محیط، ژنوتیپ و برهمکنش ژنوتیپ × محیط و سه مؤلفه اصلی اول بر عملکرد دانه معنی‌دار بودند. بر اساس شاخص انتخاب همزمان (ASV)، ژنوتیپ‌های G12، G16، G8، G9 و G2؛ ssiSIPC، ژنوتیپ‌های G11، G12، G9، G2 و G7؛ ssiEV، ژنوتیپ‌های G9، G11، G2، G7 و G15؛ ssiZA، ژنوتیپ‌های G12، G9، G2، G16 و G7؛ ssiWAAS، ژنوتیپ‌های G12، G9، G16، G2 و G8 به‌عنوان برترین ژنوتیپ‌ها شناسایی شدند. نمای چندضلعی GGE بای‌پلات ژنوتیپ‌های G2 و G12 را با پایداری عملکرد بالا مشخص کرد. نمای محور تستر متوسط (ATC) نشان داد که ژنوتیپ‌های G1، G10، G18 و G12 علاوه بر پایداری عملکرد، دارای عملکرد بالاتر از میانگین کل نیز بودند. برپایه نمای بای‌پلات ژنوتیپ ایده‌آل، ژنوتیپ‌های G1، G16، G8، G18، G10، G15 و G12 ژنوتیپ‌های مطلوب‌ بودند. نمای برداریGGE بای‌پلات نشان ‌داد که محیط E1 (گچساران، 93-1392) با قدرت نمایندگی و جداکنندگی بالا می‌تواند ژنوتیپ‌های دارای عملکرد پایدار را متمایز کند. در مجموع، بر اساس نماهای مختلف بای‌پلات و شاخص‌های انتخاب همزمان بر پایه مدل AMMI، ژنوتیپ G12 برترین ژنوتیپ بود و می‌تواند نامزد نامگذاری و آزادسازی به عنوان یک رقم جدید عدس برای شرایط دیم باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Evaluation of Seed Yield Stability of Lentil Genotypes Using GGE Biplot and AMMI Analysis

نویسندگان [English]

  • R. Karimizadeh 1
  • P. Pezeshkpour 2
  • A. Mirzaei 3
  • P. Sharifi 4
1 Kohgiloyeh and Boyerahmad Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Gachsaran, Iran.
2 Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Khorramabad, Iran.
3 Ilam Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization, Ilam, Iran.
4 Plant Breeding and Agronomy Department, Rasht Branch, Islamic Azad University, Rasht, Iran.
چکیده [English]

In this study, 18 lentil genotypes were grown under rainfed conditions for three growing seasons (2013-2016) in Gachsaran, Ilam and Khorramabad field stations in Iran. Analysis of additive main effects and multiplicative interaction (AMMI) revealed that the effect of environment, genotype and genotype by environment interaction and the first three principal components were significant for seed yield. According to the simultaneous selection indices: ssiASV; G12, G16, G8, G9 genotypes and G2, ssiSIPC: G11, G12, G9, G2 and G7 genotypes, ssiEV; G9, G11, G2, G7 and G15 genotypes, ssiZA; G12, G9, G2, G16 and G7 genotypes, and ssiWAAS; G12, G9, G16, G2 and G8 genotypes were identified as genotypes with yield stability. Polygon view of biplot demonstrated that G2 and G12 genotypes with yield stability. The average tester coordinate (ATC) view of biplot illustrated that G1, G10, G18 and G12 genotypes, in addition to high grain yield, had seed yield stability. G1, G16, G8, G18, G10, G15 and G12 genotypes were desirable based on the ideal genotype view of biplot. The vector view of GGE biplot indicated that the first environment (Gachsaran in 2013-2014) was highly discriminating and representative, and could discriminate the genotypes with yield stability. In conclusion, based on different views of biplot and simultaneous selection indices using AMMI analysis, G12 genotype was identified as superior genotype and can be considered as a candidate for being released as new lentil cultivar for dryland conditions.

کلیدواژه‌ها [English]

  • lentil
  • discriminating
  • adaptability
  • simultaneous selection index
  • stability indices
Bagheri, A., Goldani, M., and Hassanzadeh, M. 1997. Agronomy and breeding lentils. Jihad-e-Daneshgahi of Mashhad Publication. 248 pp. (in Persian).
 
Dehghani, H., Sabaghpour, S. H., and Sabaghnia, N. 2008. Genotype × environment interaction for grain yield of some lentil genotypes and relationship among univariate stability statistics. Spanish Journal of Agricultural Research 6 (3): 385-394.
 
Farshadfar, E., 2008. Incorporation of AMMI stability value and grain yield in a single non-parametric index (GSI) in bread wheat. Pakistan Journal of Biological Science 11: 1791–1796.
 
Jeberson, M. S., Shashidhar, K. S., Wani, S. H., Singh, A. K., and Dar, S. A. 2019. Identification of stable lentil (Lens culinaris Medik) genotypes through GGE biplot and AMMI analysis for north hill zone of India. Legume Research 42 (4): 467-472.
 
Kanouni, H., Talei, A., Bihamta, M. R., Shahab, M. R., Kamel, M., and Mostafaei, H. 2007. Stability of seed yield of lentil genotypes in rainfed areas of the west of the country through AMMI analysis. Iranian Journal of Agricultural Sciences 38 (2): 295-302 (in Persian).
 
Karimizadeh, R., and Mohammadi, M. 2010. AMMI adjustment for rainfed lentil yield trials in Iran. Bulgarian Journal of Agricultural Science 16: 66-73.
 
Karimizadeh, R., Pezeshkpour, P., Mohammadi, M., Sadeghzadeh Ahri, D., and Yousefi Azar, M. 2014. Evaluation of genotype × environment interaction by AMMI method in lentil lines. pp. 553-556. In Proceedings of the 5th Iranian Pulse Crops Conference. Karaj, Iran (in Persian).
 
Karimizadeh, R., M. Mohammadi, and N. Sabaghnia. 2013a. Site regression biplot analysis for matching new improved lentil genotypes into target environments. Journal of Plant Physiology and Breeding 3 (2): 51-65.
 
Karimizadeh, R., Mohammadi, M., Sabaghnia, N., Mahmoodi, A. A., Roustami, B., Seyyedi, F., Akbari, F. 2013b. GGE biplot analysis of yield stability in multi-environment trials of lentil genotypes under rainfed condition. Notulae Scientia Biologicae 5 (2): 256-262.
 
Karimizadeh, R., Safikhani., M., Mohammadi., M., Seyyedi, F., Mahmoodi, A. A., and Rostami, B. 2008. Determining rank and stability of lentil in rainfed condition by non-parametric statistics. Journal of Science and Technology in Agriculture and Natural Resources 43 (1): 93-103 (in Persian).
 
Kroonenberg, P. M. 1995. Introduction to biplots for G × E tables. Centre for Statistics. Research Report 51. The University of Queensland, Brisbane, Australia. 22 pp.
 
Olivoto, T., Lucio, A. D. C., da Silva, J. A. G., Marchioro, V. S., de Souza, V. Q., and Jost, E. 2019. Mean performance and stability in multi-environment trials I: Combining features of AMMI and BLUP techniques. Agronomy Journal 111: 2949-2960.
 
Purchase, J. L., Hatting, H., and Van Deventer C. S. 2000. Genotype × environment interaction of winter wheat (Triticum aestivum L.) in South Africa: II. Stability analysis of yield performance. South African Journal of Plant and Soil 17 (3): 101-107.
 
Sharifi P., Aminpanah, H., Erfani, R., Mohaddesi, and A., Abbasian, A. 2017. Evaluation of genotype × environment interaction in rice based on AMMI model in Iran. Rice Science 24 (3): 173−180.
 
Sharifi, P., and Aminpanah, H. 2016. Evaluation of genotype × environment interactions, stability and a number of genetic parameters in rice genotypes. Plant Genetic Research 3 (2): 25-42 (in Persian).
 
Sneller, C. H., Kilgore-Norquest, L., and Dombek, D. 1997. Repeatability of yield stability statistics in soybean. Crop Science 7: 383–390.
 
Turk, Z., and Kendal, E. 2017. The practice of AMMI and GGE biplot analysis of lentil genotypes assessment in multi-environment trials. Philippine Journal of Crop Science 42 (3): 39-48.
 
Yan, W., and Kang M. S. 2003. GGE biplot analysis: a graphical tool for breeders, geneticists and agronomists. 1st edition. CRC Press LLC. Boca Raton, Florida. 271 pp.
 
Yan, W., and Tinker, N. A. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Canadian Journal of Plant Science 86: 623–645.
 
Yan, W., Hunt, L. A., Sheny, Q., and Szlavnics, Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 40 (3): 597- 605.
 
Zali, H., Farshadfar, E., Sabaghpour, S. H., and Karimizadeh, R. 2012. Evaluation of genotype × environment interaction in chickpea using measures of stability from AMMI model. Annals of Biological Research 3: 3126–3136.
 
Zobel, R. W., Wright, A. J., and Gauch H. G. 1988. Statistical analysis of a yield trial. Agronomy Journal 80: 388-393.