تجزیۀ الگوی اثر متقابل ژنوتیپ و سال برای عملکرد دانه در رگه‌های جهش‌یافتة برنج با استفاده از روش چند متغیره AMMI

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار، مؤسسۀ تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ‏ترویج کشاورزی، رشت، ایران

2 محقق، مؤسسۀ تحقیقات برنج کشور، سازمان تحقیقات، آموزش و ‏ترویج کشاورزی، رشت، ایران

3 استادیار، بخش تحقیقات چغندرقند، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان آذربایجان غربی، سازمان تحقیقات، آموزش و ترویج کشاورزی، ارومیه، ایران

چکیده

وجود اثر متقابل ژنوتیپ × محیط ایجاب می­کند که عملکرد ژنوتیپ­ها در دامنۀ گسترده‌ای از شرایط محیطی آزمایش شوند، تا اطلاعات به‌دست‌آمده بتواند کارایی مربوط به گزینش و معرفی آن­ها را افزایش دهد. در این بررسی به‌منظور تعیین پایداری عملکرد و تجزیۀ الگوی اثر متقابل ژنوتیپ × محیط، 66 رگۀ (لاین) جهش‌یافتة (موتانت) برنج همراه با پنج رقم شاهد به مدت سه سال زراعی (1393-1391)، در قالب طرح بلوک­های کامل تصادفی با سه تکرار ارزیابی شدند. تجزیۀ اثر اصلی جمع­پذیر و اثر متقابل ضرب­پذیر (AMMI) نشان داد که اثر ژنوتیپ، سال و اثر متقابل بین آن‌ها بسیار معنی­دار بود. مجموع مربعات اثر متقابل توسط روش  AMMIبه یک مؤلفۀ اصلی اثر متقابل (IPCA) معنی­دار در سطح احتمال 05/0 و باقیمانده (نویز) جداسازی شد. مؤلفۀ اصلی اول 57/57 درصد از کل مجموع مربعات اثر متقابل را توجیه کرد. نمودار دووجهی (بای­پلات) نخستین مؤلفۀ اصلی و میانگین عملکرد با روش AMMI برای ژنوتیپ­ها و محیط­های (سال­های) مورد بررسی مشخص کرد که ژنوتیپ­های G7، G41 و G69 با داشتن کمترین اثر متقابل ژنوتیپ در محیط (سال) و داشتن عملکرد بالا پایداری بیشتری دارند و ژنوتیپ­های G63، G20 و G33 با عملکرد پایین­تر از میانگین به‌عنوان ژنوتیپ‌های ناپایدار شناخته شدند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Pattern analysis of genotype and year interaction for grain yield in mutant lines of rice (Oryza sativa L.) using AMMI multivariate method

نویسندگان [English]

  • Ali Akbar Ebadi 1
  • Shapour Abdollahi 2
  • Heydar Azizi 3
1 Assistant Professor, Rice Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Rasht, Iran
2 Researcher, Rice Research Institute of Iran, Agricultural Research Education and Extension Organization (AREEO), Rasht, Iran
3 Assistant Professor, Sugar Beet Research Department, West Azarbaijan Agricultural and Natural Resources Research Center, AREEO, Urmia, Iran
چکیده [English]

The existence of genotype × environment interaction necessiate the assessment of genotypes yields in wide range of environmental conditions, so that obtained information could increase their selection and introduction efficiency. In this study to determine the yield stability and analysis of genotype × environment interaction pattern, 66 mutant lines of rice with 5 check cultivars were evaluated using a randomized block design with three replications for three years (2012-2014). Analysis of additive main effects (analysis of variance) and multiplicative interaction effects (principal components analysis) revealed that the effects of genotype, year, and interaction between of them were highly significant. Total interaction effect was divided into one significant interaction principal component at 5% probability level and residual (noise) via AMMI model. The first principal component explained 57.57% of the total variation. Biplot of the first principal component and mean yields (AMMI1 model) for evaluated genotypes and environments (years) revealed that high yielding genotypes of G7, G41 and G69 with the least genotype × environment interaction effect were more stable genotypes and G63, G20 and G33 with yield lower than average recognized as unstable genotypes.

کلیدواژه‌ها [English]

  • AMMI analysis
  • genotype environment interaction
  • rice
Adugna, W. & Labuschagne, M. T. (2002). Genotype- environment interactions and phenotypic stability analysis of linseed in Ethiopia. Plant Breeding, 121, 66- 71.
Akcura, M., Kaya, Y. & Taner, S. (2005). Genotype-environment interaction and phenotypic stability analysis for grain yield of durum wheat in the central Anatolian region. Turkish Journal of Agriculture and Forestry, 29, 369-375.
Ali Hussein, M., Bjornstad, A. & Astveit, A. H. (2000). SAS G×E STAB: A SAS program for computing genotype×environment stability statistics. Agronomy journal, 92, 454-459.
Allard, R. W. & Bradshaw, A. D. (1964). Implications of genotype- environment interactions in applied plant breeding. Crop Science, 4, 503-508.
Bose, K. L., Jambhulkar, N. N. & Pande, K. (2014) Genotype by Environment interaction and stability analysis for rice genotypes under Boro condition. Genetika, 46(2), 521-528.
Damavandi Kamali, S., Babaian Jelodar, N. & Aalishah, E. (2012). The assessment of adaptability and stability of yield in cotton cultivars by using uniparametric, non-parametric and AMMI methods. Iranian Journal of Field Crop Science, 42(2), 397- 407. (in Farsi)
Ebdon, J. S. & Gauch, H. G. (2002). Additive main effect and multiplicative interaction analysis of national turf grass performance trials. II Cultivar recommendations. Crop Science, 42, 497-506.
Eberhart, S. A. & Russell, G. N. (1966). Stability parameters for comparing varieties. Crop Science, 6(1), 36-40.
Gallob, H. F. (1968). A statistical model which combine features of factor analysis and analysis os variance techniques. Psychometrika, 33, 73-115.
Gauch, H. G. & Zobel, R. W. (1988). Predictive success of statistical analysis of yield traits. Theoretical and Applied Genetics, 76, 1-10
Gauch, H.G. (1992). Statistical analysis of regional trials. AMMI analysis of factorial designs. Elsevier Pub. Amesterdam, Netherlands.
Grausgruber, H., Oberforster, M., Werteker, M., Ruckenbauer, P. & Vollmann, J. (2000). Stability of quality traits in Austrian-grown winter wheats. Field Crops Research, 66, 257-267.
Grist, D. H. (1986). The origin and history of rice. In: Grist, D. H. (Ed.), Rice. Longman, Singapore. pp.  1-9.
Guach, H.G. & Zobel, R.W. (1997). Identifying mega–environments and targeting genotypes. Crop Science, 37, 311-326.
Honarnejad, R., Dorosti, H., Mohammadsalehi, M. & Tarang, A. (2007). Assessment of stability and adaptability in rice varieties in different environmental conditions. Plant Seed Journal, 4(13), 32-42. (in Farsi)
Kanbar, A., Katsuhiko, K. & Shashidhar, H. E. (2011). Comparative efficiency of pedigree, modified bulk and single seed descent breeding methods of selection for developing high-yielding lines in rice (Oryza sativa L.) under aerobic condition. Electronic Journal of Plant Breeding, 2(2), 184-193.
Karimzadeh, R., Dehghani, H. & Dehghanpour, Z. (2008). Use of AMMI method for estimating genotype environment interaction in early maturing corn hybrids. Seed and Plant Improvement Journal, 23(4), 537-546. (in Farsi)
Kaya, Y., Palta, C. & Taner, S. (2002). Additive Main Effect and Multiplicative Interactions Analysis of Yield Performances in Bread Wheat Genotypes across Environments. Turkish Journal of Agriculture, 26, 275-279.
Khush. G. S. & Virk, P. S. (2000). Rice breeding: achievements and future strategies. Crop Improvement, 27, 115-144.
Koocheki, A. R., Sorkhi, B. & Eslamzadeh Hesari, M. R. (2013). Study on Stability of Elite Barley (Hordeum vulgare L.) Genotypes for Cold Regions of Iran Using AMMI Method. Cereal Research, 2(4), 249- 261.
Kulsum, M. U., Sarker, U., Karim, M. A. & Mian, M. A. K. (2012). Additive Main Effects and Multiplicative Interaction (AMMI) Analysis for Yield of Hybrid Rice in Bangladesh. Tropical Agriculture and Development, 56(2), 53-61.
Lin, C. S., Binns, M. R. & Lefcovitch, L. P. (1986). Stability analysis: where do we stand?. Crop Scince, 26, 894- 900.
Lin, C. S. & Binns, M. R. (1988). A superiority measure of cultivar performance for cultivar× location data. Canadian Journal of Plant Science, 68(1), 193-198.‏
Mahaboub, H. (2005). Dose rice research reduces poverty in Asia?. Rice Today, 5 (1), 37.
Mohammadi, R., Armion, M. & Ahmadi, M. M. (2011). Genotype × environment interactions for grain yield of durum wheat genotypes using AMMI model. Seed and Plant Improvement Journal, 27(2), 183-198. (in Farsi)
Mohammadi, R., Pourdad, S. S. & Amri, A. (2008). Grain yield stability of spring safflower (Carthamus tinctorius L.). Australian Journal of Agricultural Research, 59, 546-553.
Nahvi, M., Allahgholipour, M.  & Mohammadsalehi, M. (2000). Study of adaptability and stability in rice in different regions of Guilan. Plant Seed Journal, 1(18), 1-13. (in Farsi)
Nassir, A. L. & Ariyo, O. J. (2011). Genotype × environment interaction and yield- stability analysis of rice grown in tropical swamp. Notulae Botanicae Horti Agrobotanici Cluj-Napoca, 39(1), 220-225.
Shahmohammadi, M., Dehghani, H. & Yossefi, A. (2004). Additive main effect and multiplicative interaction analysis (AMMI) in barley (Hordeum voulgare L.) genotypes. Seed and Plant, 20 (4), 405-416. (in Farsi)
Tarakanovas, P. & Ruzgas, V. (2006). Additive main effect and multiplicative interaction analysis of grain yield of wheat varieties in Lithuania. Agronomy Research, 4, 91-98.
Vargas, W., Crossa, J., Van Eeuwijk, F. A., Sayre, K. & Reynolds, M. P. (2001). Interpreting treatment×environment interaction in agronomy trials. Agronomy Journal, 93, 949-960.
Yan, W. & Hunt, L.A. (2001). Interpretation of genotype×environment interaction for winter wheat yield in Ontario. Crop Science, 41, 19-25.
Yan, W., Kang, M. S., Ma, B., Woods, S. & Cornelius, P. L. (2007). GGE biplot vs. AMMI analysis of genotype-by- environment data. Crop Science, 47, 643-655.
Zali, H., Sabaghpour, S. H., Farshadfar, E., Pezeshkpour, P., Safikhani, M., Sarparast, R. & Hashembeygi, A. (2008). Stability analysis of yield in chickpea genotypes by additive main effects and multiplicative interaction (AMMI). Journal of Scientific and Technological Agriculture Resources, 42, 173-180. (in Farsi)