Identification of stable drought tolerant landraces of chickpea (Cicer arietinum) under multiple environments
![](/public/icon/gor.png)
![](/public/icon/pdf.png)
Keywords:
AMMI, Chickpea, Drought, GGE, LandracesAbstract
Drought is a major constraint to chickpea production leading to maximum crop loss. Further the narrow genetic base of chickpea (Cicer arietinum L.) can be widened by crossing them to landraces and wild species of which landraces provide valuable sources for abiotic and biotic stresses. The present investigation identifies highly stable drought tolerant landraces using AMMI analysis and GGE biplot techniques. The 42 chickpea genotypes (38 chickpea landraces obtained from West Asia and North Africa (WANA) and 4 known varieties) were evaluated at two locations under randomized block design in irrigated and rainfed condition in two seasons. Additive main effects and multiplicative interaction (AMMI) and Genotype main effect and genotype × environment interaction (GGE) were employed in the evaluation of genotype. AMMI analyses decomposes SS for GEI in to 3 Interaction Principal Components(PC) of which PC1(79.6%) and PC2(17.8%) explains most of the variability. From AMMI Stability Value (ASV) the genotype G35 (IL184) and G23 (IG5895) were found most stable landraces while Yield Stability Value (YSI) ranking identified G8 (IG5856) as the best genotype, based on stability and mean yield. From GGE biplot analyses the PC1 explains 80.0% and PC2 explains 18.9% of variability. G8(IG5856) performs well under across all the environments with high mean yield. Drought Susceptible Index (DSI) indicated G8 (IG5856) and G2 (ICC4958) to have the lowest DSI at both the locations. From the above investigation the landrace IG 5856 from Jordan was found to be most drought tolerant.
Downloads
References
Bharadwaj C, Srivastava R, Chauhan S K, Satyavathi C T, Kumar J, Faruqui A, Yadav S, Rizvi A H and Kumar T. 2011. Molecular diversity and phylogeny in geographical collection of chickpea (Cicersp.) accessions. J. Genet. 90: 94–100. DOI: https://doi.org/10.1007/s12041-011-0114-6
Farshadfar E and Mohammadhi J. 2013.AMMI analysis of phenotypic stability in chickpea genotypes over stress and non-stress environments. International Journal of Agriculture and Crop Sciences 5(3): 253–260.
Gauch H G and Zobel R W. 1996. AMMI analysis of yield trials. (In) 'Genotype by- Environment Interaction’, pp 85-122. (Eds) Kang M S and Gauch H G. DOI: https://doi.org/10.1201/9781420049374.ch4
Gauch H G and Zobel R W. 1997. Identifying mega-environment and targeting genotypes. Crop Sci. 37: 311–326. DOI: https://doi.org/10.2135/cropsci1997.0011183X003700020002x
Gauch H G. 2013. A simple protocol for AMMI analysis of yield trials. Crop Science 53: 1860–69. DOI: https://doi.org/10.2135/cropsci2013.04.0241
Gauch H G.1992. ‘Statistical analysis of regional yield trials: AMMI analysis of factorial designs.
Gollob H F. 1968. A statistical model which combines features of factor analytic and analysis of variance techniques. Psychometrika 33: 73–115. DOI: https://doi.org/10.1007/BF02289676
Hongyu K and Garc M. 2014.Statistical analysis of yield trials by AMMI analysis of genotype × environment interaction. Biometrical Letters 51: 89–102. DOI: https://doi.org/10.2478/bile-2014-0007
Kanouni H, Farayedi Y, Saeid A and Sabaghpour S H. 2015. Stability analyses for seed yield of chickpea (Cicer arietinum L.) genotypes in the Western cold zone of Iran. Journal of Agricultural Science 7: 219–230. DOI: https://doi.org/10.5539/jas.v7n5p219
Kanouni. 2018. Stability of chickpea (Cicer arietinum L.) landraces in National Plant Gene Bank of Iran for drylands. J. Agr. Sci. Tech. 20: 387–400.
Krishnamurthy L, Kashiwagi J, Upadhyaya H D, Gowda C L L, Gaur P M, Singh S, Purushothaman R and Varshney R K. 2013.Partitioning coefficient – a trait that contributes to drought tolerance in chickpea. Field Crops Research 149: 354–365. DOI: https://doi.org/10.1016/j.fcr.2013.05.022
Kumar T, Bharadwaj C, Rizvi A H and Shailesh. 2015. Chickpea landraces: a valuable and divergent source for drought tolerance. International Journal of Tropical Agriculture 33(3): 1–7.
Mohammadi R, Abdulahi A, Haghparast R and Armion M. 2007. Interpreting genotype_ environment interactions for durum wheat grain yields using nonparametric methods. Euphytica 157: 239–51. DOI: https://doi.org/10.1007/s10681-007-9417-3
Neisse A C, Kirch J L and Hongyu K. 2018. AMMI and GGE Biplot for genotype × environment interaction: a medoid–based hierarchical cluster analysis approach for high–dimensional data. DOI: https://doi.org/10.2478/bile-2018-0008
Oliviera R L, Von Pinho G, Balestre M and Ferreira D V. 2010. Evaluation of maize hybrids and enviromental stratification by the methods AMMI and GGE-biplot. Crop Breed and Appl. Biotechnol 10: 274–83. DOI: https://doi.org/10.1590/S1984-70332010000300010
Osiru M O, Olanya O M, Adipala E, Kapinga R and Lemaga B. 2009. Yield stability analysis of Ipomoea batatus L. cultivars in diverse environments. Aust J Crop Sci. 3(4): 213–220.
Purchase J L. 1997.Parametric analysis to described G x E interaction and yield stability in winter yield. Ph D thesis, Department of Agronomy, Faculty of Agriculture, University of Orange Free State, Bloemfontein, South Africa.
Purchase J L, Hatting H and Van Deventer CS. 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: 101–107. DOI: https://doi.org/10.1080/02571862.2000.10634878
Sumathi P, Govindaraj M and Govintharaj P. 2017. Identifying promising pearl millet hybrids using AMMI and clustering models. International Journal of Current Microbiology and Applied Science 6: 1348–59. DOI: https://doi.org/10.20546/ijcmas.2017.602.153
Varshney R K, Thudi M, May G D and Jackson S A. 2010. Legume genomics and breeding. (In) Janick J. Plant Breeding Reviews 33: 257–04. DOI: https://doi.org/10.1002/9780470535486.ch6
Yan W and Kang M S. 2003. GGE biplot analysis:Agraphical tool for breeders, geneticists, and agronomists. DOI: https://doi.org/10.1201/9781420040371
Yan W and Tinker N A. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Can. J. Plant Sci 86: 623–45. DOI: https://doi.org/10.4141/P05-169
Yan W, Hunt L A, Sheng Q and Szlavnics Z. 2000.Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Science 40: 597–05. DOI: https://doi.org/10.2135/cropsci2000.403597x
Zobel R W, Wright M J and Gauch H G. 1988.Statistical analysis of a yield trial. Agronomy Journal 80: 388–93. DOI: https://doi.org/10.2134/agronj1988.00021962008000030002x
Downloads
Submitted
Published
Issue
Section
License
The copyright of the articles published in The Indian Journal of Agricultural Sciences is vested with the Indian Council of Agricultural Research, which reserves the right to enter into any agreement with any organization in India or abroad, for reprography, photocopying, storage and dissemination of information. The Council has no objection to using the material, provided the information is not being utilized for commercial purposes and wherever the information is being used, proper credit is given to ICAR.