Study on genetic variation of 14 soybean cultivars using cluster and factor analysis under water stress and non-stress conditions

Paper Details

Research Paper 01/03/2015
Views (522)
current_issue_feature_image
publication_file

Study on genetic variation of 14 soybean cultivars using cluster and factor analysis under water stress and non-stress conditions

Seyyed Mohammad Ali Kargar, Ali Mostafaie, Eslam Majidi Hervan, Seyyed Said Pourdad
J. Biodiv. & Environ. Sci. 6(3), 100-112, March 2015.
Copyright Statement: Copyright 2015; The Author(s).
License: CC BY-NC 4.0

Abstract

This experiment was conducted in Mahidasht Agricultural Research Station in the west part of Iran in RCBD with three replications under normal and drought stress conditions. The cluster analysis based on ward method showed the cultivars were grouped by four clusters under non-stress condition. The cultivars of clusters were including; (I: Baj-maj); (II: M9, Hy-1 and LD9); (III: The fertile cultivars as L17, Union, Bonus, Williams, Steel, Elgine, Clark) and (IV: The infertile cultivars as Hack, Flanklin and Halcor) respectively; While they were grouped by three clusters under stress condition. These cultivars of clusters were including (I: The infertile cultivars as Baj-maj, Steel, Williams, Bonus, Hack, Halcor and Flanklin); (II: The cultivars as Hy-1, Elgine and M9); (III: The fertile cultivars as Clark, LD9, L17, Clark and Union); respectively. The evaluation of discriminate function on 14 soybean cultivars under non-stress condition showed 3 functions with eigenvalues more than 1 explained totally 100% of cultivar variations. The evaluation of discriminate function on 14 soybean cultivars under stress condition showed 2 functions with eigenvalues more than 1 explained totally 100% of cultivar variations. In factor analysis on 9 traits under non-stress condition, there were three components with 73.86% of traits variation with varimax rotation method. The contribution of first, second and third components were 38.08%, 20.56% and 15.21%, respectively. On the other hand three components explained 74.79% of traits variation with varimax rotation method under stress condition. The contribution of first, second and third components were 32.57%, 27.20 and 15.02 respectively. The cluster analysis based on wards method showed four clusters of traits in both stress and non-stress conditions.

Brown-Guedira GL, Thompson JA, Nelson RL, Warburton ML. 2000. Evaluation of genetic diversity of soybean introductions and north American ancestors using RAPD and SSR markers. Crop Science 40, 815-823.

Dong YS, Zhao LM, Liu B, Wang ZW, Jin ZQ, Sun H. 2004. The genetic diversity of cultivated soybean grown in China. Theoretical and Applied Genetics 108, 931-936.

Ghafoor A, Sharif A, Ahmad Z, Zahid MA, Rabbani MA. 2001. Genetic diversity in black gram (Vigna mungo L. Hepper). Field Crops Research., 69:183-190

Guan R, Chang R, Li Y, Wang L, Liu Z, Qiu L. 2010. Genetic diversity comparison between Chinese and Japanese soybeans (Glycine max (L.) Merr.) Revealed by nuclear SSRs. Genetic Resources and Crop Evolution 57, 229-242.

Liu M, Zhang M, Jiang W, Sun G, Zhao H, Hu S. 2011.Genetic diversity of Shaanxi soybean landraces based on agronomic traits and SSR markers. African Journal of Biotechnology. 10 (24), 4823-4837.

Mannan MA, Karim MA, Khaliq QA, Haque MM, Mian MAK, Ahmed JU. 2010. Assessment of Genetic Divergence in Salt Tolerance of Soybean (Glycine max L.) Genotypes. Journal of Crop Science of Biotechnology. 13 (1), 33- 38.

Masoudi B, Bihamta MR, Babaei HR, Peyghambari SA. 2008. Evaluation of genetic diversity for agronomic, morphological and phonological traits in soybean. Seed and plant. 24(3), 413-427.

Narjesi V, Khaneghah HZ. Zali EE. 2007. Assessment of genetic relationship in few important agronomic characters with grain yield in soybean by multivariate statistical analysis. Agriculture and Natural Research Science. 41(11), 227-234.

Panndy RK. 1987. A farmer on growing soybean on Richland. International rice research institute. IRRI.216 pages.

Rabbani MA, Iwabuchi A, Murakami Y, Suzuki T, Takayanagi K. 1998. Phenotypic variation and the relationship among mustard (Brassica juncea L.) germplasm from Pakistan. Euphytica, 101, 357-366.

Salimi S, Samiezade H, Lahiji G, Abadi M, Salimi S, Moradi S. 2012. Genetic Diversity in soybean genotypes under drought stress condition using factor analysis and cluster analysis. World Applied Science Journal. 16 (4), 474-478.

Smartt, J. 1990. Evolution of genetic resources. In: Grain legumes, (Ed.): J. Smartt. pp. 140-175.Cambridge University Press, Cambridge

Smith JSC, Smith OS. 1989. The description and assessment of distances between inbred lines of maize: The utility of morphological, biochemical and genetic descriptors and a scheme for the testing of distinctiveness between inbred lines. Maydica 34, 151-161.

Upadhyaya HD, Ortiz R, Bramel PJ, Singh S. 2002. Phenotypic diversity for morphological and agronomic characteristics in chickpea core collection. Euphytica 123(3), 333-342.

Upadhyaya HD. 2003. Phenotypic diversity in groundnut (Arachis hypogaea L.) core collection assessed by morphological and agronomical evaluations. Genetic Research Crop Evolution 50, 539-550.

Wang KJ, Li XH, Li FS. 2008. Phenotypic Diversity of the Big Seed Type Sub collection of wild soybean (Glycine soja Sieb.et Zucc.) in China,” Genetic. Resources and Crop Evolution, 55(8), 1335-1346. doi:10.1007/s10722-008-9332-z

Wang M, Li RZ, Yang WM, Du WJ. 2010. Assessing the genetic diversity of cultivars and wild soybeans using SSR markers. African Journal of Biotechnology 9, 4857-4866.

Zhao YY, Geng ZD, Bao LP, Wang TJ. 2007. Principal component analysis and cluster analysis of local soybean varieties of Yunnan. Journal of Hunan Agricultural University (Natural Sciences).

Related Articles

Agroforestry in woody-encroached Sub-Saharan savannas: Transforming ecological challenges into sustainable opportunities

Yao Anicet Gervais Kouamé, Pabo Quévin Oula, Kouamé Fulgence Koffi, Ollo Sib, Adama Bakayoko, Karidia Traoré, J. Biodiv. & Environ. Sci. 27(3), 10-22, September 2025.

Extreme rainfall variability and trends in the district of Ouedeme, municipality of Glazoue (Benin)

Koumassi Dègla Hervé, J. Biodiv. & Environ. Sci. 27(3), 1-9, September 2025.

Heterosis breeding, general and specific combining ability and stability studies in pearl millet: Current trends

Ram Avtar, Krishan Pal, Kavita Rani, Rohit Kumar Tiwari, Mahendra Kumar Yadav, J. Biodiv. & Environ. Sci. 27(2), 117-124, August 2025.

Combining ability, heterosis and stability for yield and fibre quality traits in cotton: Breeding approaches and future prospects

Rohit Kumar Tiwari, Krishan Pal, R. P. Saharan, Ram Avtar, Mahendra Kumar Yadav, J. Biodiv. & Environ. Sci. 27(2), 109-116, August 2025.

Bridging the COPD awareness gap in marginalized populations: Findings from a multicentre study in Khalilabad, Sant Kabir Nagar, Uttar Pradesh, India

Anupam Pati Tripathi, Jigyasa Pandey, Sakshi Singh, Smita Pathak, Dinesh Chaudhary, Alfiya Mashii, Farheen Fatima, J. Biodiv. & Environ. Sci. 27(2), 97-108, August 2025.

Antioxidant and anti-inflammatory activity of Pleurotus citrinopileatus Singer and Pleurotus sajor-caju (Fr.) Singer

P. Maheswari, P. Madhanraj, V. Ambikapathy, P. Prakash, A. Panneerselvam, J. Biodiv. & Environ. Sci. 27(2), 90-96, August 2025.

Mangrove abundance, diversity, and productivity in effluent-rich estuarine portion of Butuanon River, Mandaue City, Cebu

John Michael B. Genterolizo, Miguelito A. Ruelan, Laarlyn N. Abalos, Kathleen Kay M. Buendia, J. Biodiv. & Environ. Sci. 27(2), 77-89, August 2025.

Cytogenetic and pathological investigations in maize × teosinte hybrids: Chromosome behaviour, spore identification, and inheritance of maydis leaf blight resistance

Krishan Pal, Ravi Kishan Soni, Devraj, Rohit Kumar Tiwari, Ram Avtar, J. Biodiv. & Environ. Sci. 27(2), 70-76, August 2025.