BIPLOT ANALYSIS OF LEAF RUST RESISTANCE IN PURE LINES SELECTED FROM EASTERN ANATOLIAN BREAD WHEAT LANDRACES OF TURKEY

Year 2017, Volume: 22 Issue: 2, 227 - 234, 15.12.2017

Mevlut Akcura Kadir Akan Onur Hocaoglu

https://doi.org/10.17557/tjfc.356231

Cited By: 4

Abstract

The present research was conducted to determine the reactions of 42 pure lines selected from bread wheat landraces of Eastern Anatolia, Turkey, against the leaf rust (Puccinia triticina) disease under field conditions across 7 environments. G (Genotype), GE (Genotype Environment) biplot analysis method was used to determine the reactions of landraces against leaf rust disease. GGE-biplot graph created to assess leaf rust disease was explained a 78.12% of total variation. While E3 and E2 constituted the first and second mega environments respectively, the other four environments constituted the third and fourth mega environments. The lowest PC1 values and PC2 values close to 0.0 explaining the resistance of pure lines to leaf rust at best in the biplot. Reactions of landraces varied based on their distance from the Average Environment Axis (AEA). While the pure lines with the same or similar reactions in 7 experimental environments fell close to the axis, ones with different reactions in one or more environments were relatively distant. The pure lines of EA15 and EA19 were identified as the most resistant and stable genotypes in all environments when EA42 and EA41 were the most susceptible/stable genotypes in all environments. Pure lines that were resistant or moderately resistant at all seven tested environments should be useful for breeding wheat cultivars with resistance to leaf rust in Turkey.

Keywords

GGE-Biplot, Landraces, Leaf rust (Puccinia triticina), Pure line, Turkey

References

• Acorsi, C., T. Guedes, M. Coan, R. Pinto, C. Scapim, C. Pacheco, and Casela, C. 2017. Applying the generalized additive main effects and multiplicative interaction model to analysis of maize genotypes resistant to grey leaf spot. J. Agric. Sci 1-15.
• Akin, B., N. Zencirci, and I. Ozseven. 2008. Field resistance of wheat (Triticum aestivum L.) genotypes from different countries to leaf rust (Puccinia triticina). Turk J Agric For. 32: 479-486.
• Alam, A. K. M., M. P. Somta, C. Jompuk, P. Chatwachirawong, and P. Srinives, 2014. Evaluation of mungbean genotypes based on yield stability and reaction to mungbean yellow mosaic virus disease. Plant Pathol. J 30: 261-268. Egesi, C. N., T. J. Onyeka, and R. Asiedu, 2009. Environmental stability of resistance to anthracnose and virus diseases of water yam (Dioscorea alata). Afr. J. Agric. Res 4: 113-118.
• Frutos, E., M. P. Galindo, and V. Leiva, 2014. An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stoch Environ Res Risk Assess 28: 1629.
• Gabriel, K. R. 1971. The biplot graphic display of matrices with application to principal component analysis. Biometrika 58: 453-467. Gomez, K. A. and A. A. Gomez, 1984.Statistical Procedures for Agricultural Research. John Wiley & Sons, New York City, USA.
• Heitefuss, R. 2011. Wheat Diseases and Pests. J Phytopathol, 159: 324.
• Ilker E, F. Aykut Tonk, O. Caylak, M. Tosun, I. Ozmen, 2009. Assesment of Genotype X Environment Interactions for Grain Yield in Mazie Hybrids Using AMMI and GGE Biplot Analyses. Turkish J. of Field Crops 14(2): 123 – 135.
• Kadariya, M., K. D. Glover, M. Mergoum and L. E. Osborne, 2008. Biplot analysis of agronomic and Fusarium head blight resistance traits in spring wheat. J Crop Improv. 22: 147–170.
• Kaplan M., K. Kokten and M. Akcura, 2017. Assessment of Genotype x Trait x Environment interactions of silage maize genotypes through GGE Biplot. Chilean Journal of Agricultural Research 77, 212 – 217.
• Kempton, R. A. 1984. The use of biplots in interpreting variety by environment interactions. J Agric Sci. 103: 123-135.
• Kumar, S., D. K. Baranwal, A. Kumar, R. N. Gupta, and A. Kumar, 2017. G × E Interaction analysis for yield and major diseases in chickpea under rice fallow land of bihar. Environ Ecol. 35: 1238-1243.
• Lillemo, M., R. P. Singh, and M. V. Ginkel, 2010. Identification of stable resistance to powdery mildew in wheat based on parametric and non-parametric methods. Crop Sci. 50: 478–485.
• Madden, L.V., P. A. Paul, and P. E. Lipps 2007. Consideration of nonparametric approaches for assessing genotype-by-environment (G×E) interaction with disease severity data. Plant Dis. 91: 891-900.
• McCallum, B. D., C. W. Hiebert, S. Cloutier, G. Bakkeren, S. B. Rosa, D. G. Humphreys and B. J. Saville, 2016. A review of wheat leaf rust research and the development of resistant cultivars in Canada. Can. J. Plant Pathol. 38: 1-18. Mitrović, B., D. Stanisavljević, S. Treskić, M. Stojaković, M. Ivanović, G. Bekavac, M. Rajković, 2012. Evaluation of experimental maize hybrids tested in multi-location trials using AMMI and GGE biplot analyses. Turk. J. Field Crops 17(1): 35-40. Morgounov, A., M. Keser, M. Kan, M. Kucukcongar, F. Ozdemir, N. Gummadov, H. Muminjanov, E. Zuev and C. O. Qualset, 2016. Wheat landraces currently grown in Turkey: distribution, diversity, and use. Crop Sci. 56: 3112-3124.
• Pande, S., M. Sharma, P. M. Gaur, A. K. Basandrai, L. Kaur, K. S. Hooda, D. Basandrai, T. Kiran, S. Babu, K. Jain and A. Rathore, 2013. Biplot analysis of genotype × environment interactions and identification of stable sources of resistance to Ascochyta blight in chickpea (Cicer arietinum L.). Australas. Plant Pathol., 42: 561–571.
• Parihar, A. K., A. K. Basandrai, A. Sirari, D. Dinakaran, D. Singh, K. Kannan, P. S. Kushawaha, M. Adinarayan, M. Akram, T. K. S. Latha, V. Paranidharan, and S. Gupta, 2017. Assessment of mungbean genotypes for durable resistance to Yellow Mosaic Disease: Genotype × Environment interactions. Plant Breeding 136: 94 – 100.
• Peterson R. F., A. B. Campbell, and A. E. Hannah, 1948. A diagrammatic scale for estimating rust intensity on leaves and stems of cereals. Can J Res. 26: 496–500.
• Piepho, H. P. 1996. Analyzing genotype environment data by mixed models with multiplicative effects. Biometrics 53:242- 252. R Core Team, 2013. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Rubiales,
• D., C. M. Avila, J. C. Sillero, M. Hybl, L. Narits, O. Sass, and F. Flores, 2012. Identification and multi-environment validation of resistance to Ascochyta fabae in faba bean (Vicia faba). Field Crops Res. 126: 165–170.
• Sandhu, P. S., K. S. Brar, J. S. Chauhan, P. D. Meena, R. P. Awasthi, A. S. Rathi, A. Kumar, J. C. Gupta, S. J. Kolte, and S. S. Manhas, 2015. Host–pathogen interactions of Brassica genotypes for white rust (Albugo candida) disease severity under aided epiphytotic conditions in India. Phytoparasitica 43:197-207.
• Sharma, M., R. Ghosh, R. Telangre, A. Rathore, M. Saifulla, D. M. Mahalinga and Y. K. Jain, 2016. Environmental influences on pigeonpea-Fusarium udum interactions and stability of genotypes to Fusarium Wilt. Front Plant Sci. 7:1-10.
• Villegas-Fernández, A. M., J. C. Sillero, A. A. Emeran, J. Winkler, B. Raffiot, J. Tay, F. Flores, and D. Rubiales, 2009. Identification and multi-environment validation of resistance to Botrytis fabae in Vicia faba. Field Crops Res. 114: 84-90.
• Yan, W. 2014. Crop variety trials: Data management and analysis. John Wiley and Sons. pp. 349 New York, USA.
• Yan, W. and D.E. Falk, 2002. Biplot analysis of host-by-pathogen data. Plant Dis, 86: 1396-1401.
• Yan, W., L. A. Hunt, Q. Sheng, and Z. Szlavnics, 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sc.i 40: 597-605.
• Yan, W. and M. S. Kang, 2003. GGE Biplot Analysis: A Graphical Tool for Breeders, Geneticists, and Agronomists. CRC Press, Boca Raton, FL.
• Yildiz, S. 2011. Rotational and nematicidal effect of lupine (Lupinus albus L.: Leguminosae). Afr. J. Biotechnol. 10: 13252-13255. Zobel, R. W., M. J. Wright and H. G. Gauch, 1988. Statistical analysis of a yield trial. Agron J, 80: 388-393