تجزیه الگوی اثر متقابل ژنوتیپ و محیط برای عملکرد ارقام چغندرقند با استفاده از روش چند متغیره AMMI

نوع مقاله : کامل علمی - پژوهشی

نویسندگان

1 دانشگاه آزاد اسلامی واحد کرج

2 موسسه تحقیقات اصلاح و تهیه بذر چغندرقند، سازمان تحقیقات، آموزش و ترویج کشاورزی، کرج، ایران

چکیده

جهت مطالعه پایداری عملکرد و سازگاری ارقام چغندرقند در شرایط آب ‌و هوایی مختلف، نه رقم چغندرقند در قالب طرح بلوک‌های کامل تصادفی با چهار تکرار و در شش منطقه شامل اصفهان، کرج، کرمانشاه، خوی، مشهد و مغان در سال زراعی 1394 مورد ارزیابی قرار گرفت. در این بررسی به منظور تجزیه الگوی اثر متقابل ژنوتیپ در محیط از مدل اثرات اصلی افزایشی و اثرات متقابل ضرب‌پذیر (امی) استفاده شد. نتایج تجزیه اثرات افزایشی جمع‌پذیر (تجزیه واریانس) و اثرات متقابل ضرب پذیر (تجزیه به مؤلفه­های اصلی) مؤید آن بود که اثر ژنوتیپ در سطح احتمال پنج درصد، و اثر محیط و اثر متقابل ژنوتیپ در محیط در سطح احتمال یک درصد معنی‌دار بود. نتایج نشان داد که دو مؤلفه اصلی اول اثر متقابل ژنوتیپ در محیط در مجموع بیش از 77 درصد از واریانس اثر متقابل را تبیین نمودند. نمودار بای‌پلات حاصل از اولین مؤلفه اصلی اثر متقابل و میانگین عملکرد ریشه برای ژنوتیپ‌ها و محیط‌ها نشان داد که رقم JAAM با عملکرد بیشتر از میانگین کل و کمترین مقدار برای اولین مؤلفه اصلی اثر متقابل به عنوان رقم پایدار شناخته شد. براساس نمودار دو بعدی مربوط به دو مؤلفه اصلی اول اثر متقابل ژنوتیپ در محیط، ژنوتیپ‌هایJAAM و (I13*A37.1)*SH-1-HSF.5 در محیط‌های اصفهان و مشهد، ژنوتیپ‌های 1571، (I13*KWS)*302-HSF.20، (I13*A37.1)*S1.88239، BR1 و ARAS 101 در کرمانشاه و مغان و ژنوتیپ‌های ICو 7233در کرج دارای سازگاری خصوصی بودند. همچنین ژنوتیپ‌های 7233، (I13*A37.1)*S1.88239، JAAM و ARAS 101 نسبت به سایر ژنوتیپ‌ها از سازگاری عمومی بیشتری برخوردار بودند. بطور کلی نتایج مشخص نمود که امکان گزینش ارقام مناسب برای هر منطقه وجود دارد.

کلیدواژه‌ها

عنوان مقاله [English]

Genotype - environment interaction pattern analysis for sugar beet (Beta vulgaris L.) cultivars yield using AMMI multivariate method

نویسنده [English]

  • Khodadad Mostafavi 1
1 Associated Professor, Department of Agronomy and Plant Breeding, Karaj Branch, Islamic Azad University, Karaj, Iran.
چکیده [English]

In order to study the stability and adaptability of sugar beet genotypes under different climatic conditions, nine genotypes were evaluated in Isfahan, Karaj, Kermanshah, Khoy, Mashhad and Moghan regions in a randomized complete block design with four replications in 2015.Genotype × environment interaction was studied by estimating additive main effects and multiplicative interactions (AMMI) method. Analysis of additive main effects (analysis of variance) and multiplicative interactions (principal component analysis) showed significant effect of genotype (P < 0.05), environment (P < 0.01), and genotype × environment interaction (P < 0.01). Cumulative of first two principal components explained about 77% of the interaction variance. The biplot of the first interaction principal component and mean yield showed that JAAM had higher yield than the overall mean identified as a stable genotype. Based on AMMI2 graph, JAAM and (I13*A37.1)*SH-1-HSF.5 genotypes in Isfahan and Meshhad, 1571, (I13*KWS)*302-HSF.20, (I13*A37.1)*S1.88239, BR1 and ARAS 101 genotypes in Kermanshah and Moghan and IC and 7233 genotypes in Karaj had specific adaptability. Among all genotypes, 7233, (I13*A37.1)*S1.88239, JAAM and ARAS 101 had the highest general adaptability. Results showed the possibility of genotype selection for each location.

کلیدواژه‌ها [English]

  • Analysis of stability and adaptability
  • Root yield
  • sugar beet

مراجع

Aghaei M. Study of genotype×environment interaction in barely cultivars on Tabriz. Journal of Agricultural Science. 1993; 1(2), 28-40. (In Persian, abstract in English).
Albert MJA. A comparison of statistical methods to describe genotype × environment interaction and yield stability in multi-location maize trials. M. Sc. Thesis. Department of Plant Science, the University of Free State. 2004; Bloemfontein.
Anandan A, Eswaran R. Genotype by environment interaction of rice (Oryza sativa L.) hybrids in the east ciast saline region of Tamil Nadu. Proceeding of 2ⁿᵈ international Rice Congress. 2009; 226 pp.
Annicchiarico P. Wide- versus specific-adaptation strategy for Lucerne breeding in northern Italy. 2007; Theoretical and Applied Genetics. 114, 647–657.
Asenjo CA, Bezus R, Acciaresi HJ. Genotype by environment interaction of rice (Oryza sativa L.) in temperate region using the joint regression analysis and AMMI methods. Cereal Research. Communi. 2003; 31(1-2): 97-104.
Becker HB, Leon J. Stability analysis in plant breeding. Plant Breeding. 1988; 101: 1-23.
Cornelius PL, Crossa J. Prediction assessment of shrinkage estimators of multiplicative models for multi-environment cultivar trials. Crop Science. 1999; 39: 998-1009.
Crossa J, Cornelius PL, Yan W. Biplot of linear-bilinear models for studying crossover genotype × environment interaction. Crop Science. 2001; 41: 158-163.
Crossa J, Fox PN, Pfeiffer WH, Rajaram S, Gauch HG. AMMI adjustment for statistical analysis of an interaction wheat yield trial. Theor. Appl. Genet. 1991; 81: 27-37.
Crossa J, Gauch HG, Zobel RW. Additive main effects and multiplicative interaction analysis of two international maiz cultivar trials. Crop Science. 1990; 30: 493-500.
Delacy IH, Eisemann RL, Cooper M. The importance of genotype by environment interaction in regional variety trials. 1990; pp. 287-300.
Ebdon JS, Gauch HG. Additive main effect and multiplicative interaction analysis of national turf grass performance trials: Interpretation of genotype × environment interaction. Crop Science. 2002; 42: 489-496.
Eberhart, S.A., & Russell, G.N. (1966). Stability parameters for comparing varieties. Crop Science, 6, 36- 40.
Ebrahimian HR, Sadeghiyan SY, Jahadakbar MR, Abasi Z. Stability of adaptability and stability of suger beet monogerm cultivars in different locations of Iran. Journal of Sugar beet. 2001; 24 (2): 1-13. (In Persian, abstract in English).
Ehdaei B. Plant breeding. 1994. Barsava Press. 256 pp.
Erdal G, Esengun K, Erdal H, Gunduz O, Energy use and economic analysis of sugar beet production in Tokat province of Turkey. Energy. 2007; 32: 35-41.
Falconer DS.  Introduction to quantitative genetics. Longman. 1985; U.S.A.
Farshadfar E, Sutka J. Locating QTLS controlling adaptation in wheat using AMMI Model. Cereal Research Communication. 2003; 31: 3-4.
Fernandez GCJ. Analysis of genotype environment interaction by stability estimates. Horticultural Sciences. 1991; 27:947-950.
Gauch HG, Zobel RW. AMMI analysis of yield trials. In: Genotype-by-Environment interaction, Kang MS and HG Gauch (Eds.). Boca Raton CRE CRC, New York, USA. 1996; pp: 85- 122.
Gauch HG. Model selection and validation for yield trials with interaction. Biometrics. 1988; 44: 705-715.
Gower JC, Hand DJ. Biplots. Chapman and Hall. 1996; UK.
Hanamaratti NG, Salimth PM, Vijayakumar CHM, Ravikumar RL, Kajjidoni ST, Chetti MB. Genotype stability of superior near isogenic introgression lines for productivity in upland rice. Karnataka J. Agriculture Science. 2009; 22(4): 736-740.
Hoffmann C, M, Huijbregts T, Van Swaaij N, and Jansen R. 2009. Impact of different environments in Europe on yield and quality of sugar beet genotypes. Europ. J. Agronomy, 30: 17-26.
Kang MS. Using genotype by environment interaction for crop cultivar development. Adv. Agronomy. 1998; 62: 199-252.
Keshavarz S, Mesbah M, Ranji Z, Amiri R. Study on stability parameters for determining the adaptation of sugar beet commercial varieties in different areas of IRAN. Journal of sugar beet. 2001; 17(1): 15-36. (In Persian, abstract in English)
Lin CS, Binne MR, Lefcovitch LP. Stability analysis: where do we stand? Crop Science. 1986; 26: 894-900.
Moradi F, Safari H, and Jalilian A. Study of genotype × environment interaction for sugar beet monogerm cultivars using AMMI method. Journal of Sugar beet. 2014. 28(1): 55-66. (In Persian, abstract in English).
Mostafavi K, Hosseini Imeni SS, Firoozi M. Stability Analysis of Grain Yield in Lineas and Cultivars of Rice (Oriza sativa L.) Using AMMI (Additive Main effects and Multiplicative Interaction) Method. Iranian journal of Field Crop Science. 2014. 45 (3): 445-452 (In Persian, abstract in English).
Nikkhah HR, Yousefi A, Mortazavian SM, Arazmjoo M. Analysis of yield stability of barley (Hordeum vulgare L.) genotypes using additive main effects and multiplicative interaction (AMMI) model. Iranian Journal of Crop Sciences. 2007; 9, 1(33): 1-12. (In Persian, abstract in English).
Ouk M, Basnayake J, Tsubo M, Fukai S, Fischer KS, Kang S, Men S, Thun V, Cooper M. Genotype-by-environment interactions for grain yield associated with water availability at flowering in rainfed lowland rice. Field Crops Res. 2007. 101: 145-154.
Pidgeon JD, Ober ES, Qi A, Clark CJA. Using multi-environmental sugar beet variety trials to screen for drought tolerance. Field Crops Res. 2006. 95: 268-279.
Rahimiyan MH, Asadi H. Water stress effect on quantitative and qualitative yield of Sugar Beet and determination of production function and its plant coefficient. Journal of Soil and Water. 1999; 12, 57-63. (In Persian, abstract in English).
Ranji Z, Mesbah M, Amiri R, Vahedi S. Study on the efficiency of AMMI method and pattern analysis for determination of stability in sugar beet varieties. Iranian Journal of crop sciences. 2005; 7(1): 1-21. (In Persian, abstract in English)
Reynolds MP, Trethowan R, Crossa J, Vargas M, Sayre KD. Physiological factors associated with genotype by environment interaction in wheat. Field Crops Res. 2002. 75: 139-160.
Rharrabti Y, Garcia del moral LF, Villegas D, Royo C. Durum wheat quality in Mediterranean environments ill: Stability and Comparative methods in analyzing G×E interaction. Field Crop Research. 2003; 80:141-146.
Roy D. Plant breeding analysis and exploitation of variation. Alpha Science International Ltd. 2000; U. K.
Stanley O, Samante PB, Wilson T, Anna MM, Medley JC. Targeting cultivars onto rice growing environment using AMMI and SREG GGE Biplot analysis. Crop Science. 2005; 45: 2414-2424.
Tarakanovas P, Ruzgas V. Additive main effect and multiplicative interaction analysis of grain yield of wheat varieties in Lithuania. Agricultural Research. 2006; 4: 91-98.
Yan W, Hunt LA. Biplot analysis of multi-environment trial data, in M. S. Kang, ed. Quantitative genetics, genomics and plant breeding. CAB international, willingford. 2002.
چغندرقند
دوره 33، شماره 2
دی 1396
صفحه 135-147

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