Utilization of the most recent GGE biplot to locate stable genotypes in turmeric using the well-liked Eberheart Russell stability model
Stability Analysis of Turmeric in Different Agro-Climatic Zones of Chhattisgarh
Downloads
Published
DOI:
https://doi.org/10.58993/ijh/2026.83.1.3Keywords:
Indigenous turmeric, AMMI and GGE biplots, genotype × environment interaction, rhizome yieldIssue
Section
License
Copyright (c) 2026 Shrikant L. Sawargaonkar, A.K. Singh, M.K. Sahu, S. Agrawal, B. Patel

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
GGE and AMMI biplot methods with Eberhart and Russell regression model were applied on the set of twelve indigenous turmeric genotypes grown in nine environments for quick and relevant method to delineate genotype by environment interaction, stable genotypes and environmental discrimination. The average rhizome yield over the locations was depicted as 12.01 ton/ha, which ranged from 7.87 ton/ha (Jagdalpur) to 20.02 ton/ha (Raigarh). The genotype CG Haldi 2 (16.61 ton/ha) exhibited the highest rhizome yield followed by IT 36 (15.00 ton/ha), over national checks Roma (13.53 ton/ha), Suranjana (11.73 ton/ha) and over local check CG Haldi -1 (10.57 ton/ha). As per Eberhart and Russell model, the genotypes CG Haldi 2 (IT 10), CG Raigarh Haldi-3 (IT 36), Roma, and Narendra Haldi -1 were best performing entries while the performance of BSR 2, IT 38, Suranjana, CG Haldi-1, IT 7, and IT 8 were varied with change in environments. In AMMI analysis, IPCA 1 (62.60 %), IPCA 2 (21.80 %), IPCA 3 (11.70 %), and IPCA 4 (2.60 %) were explained the interaction mean squares, respectively. While, in GGE biplot, PC 1 and PC 2 captured 47.28 % and 34.62 % interaction variation, respectively. The genotypes T-111 (CG Haldi-2), T-101 (IT 36), and national check T-106 (Roma) were high yielding and as well as found stable in GGE and AMMI-1 biplot. The test environments RG 17, RG 16 and RG 15 exhibited different niches, whereas, AM 17, AM 16, JD 16, JD 17, JD 15 and AM 15 were representative with better discriminating ability. Between biplot models applied, the GGE biplots were clear in visualization for polygon view, genotypic stability and environmental discrimination. The GGE method considered both G+GE for biplot generation and found most suitable for stability analysis.Abstract
How to Cite
Downloads
1. Anandaraj, M., Prasatha, D., Kandiannana, K., John T. Z., Srinivasana, V., Jha, A.K., Singh, B.K., Singh, A.K., Pandey, V.P., Singh, S.P., Shoba, N., Jana, J.C., Ravindra K. and Maheswari U. 2014. Genotype by environment interaction effects on yield and curcumin in turmeric (Curcuma longa L.). Ind. Crop Prod. 53:358-364. 2. Dehghani, H., Ebadi, A. and Yousefi, A. 2006. Biplot analysis of genotype by environment interaction for barley yield in Iran. Agron. J. 98:388-393. 3. Eberhart, S.A. and Russell, W.A. 1966. Stability parameters for comparing varieties. Crop Sci. 6:36-40. 4. Flores, F., Moreno, M.T. and Cubero, J.I. 1998. A comparison of univariate and multivariate methods to analyse G×E interaction. Field Crops Res. 56:271-286. 5. Gauch, H.G. 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Sci. 46:488- 500. 6. Gauch, H.G., Piepho, H.P. and Annicchiarico, P. 2008. Statistical analysis of yield trials by AMMI and GGE: Further considerations. Crop Sci. 48:866-889. 7. Kang, M.S., Ma B., Woods, S. and Cornelius, P.L. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 47:643-653. 8. Muthusamy, A. 2013. A study on export on performance on Indian Turmeric. Ind. J. Appl. Res. 3:54 9. Rad, M.R.N., Kadir, M.A., Rafii, M.Y., Jaafar, H.Z., Naghavi, M.R. and Ahmadi, F. 2013. Genotype× environment interaction by AMMI and GGE biplot analysis in three consecutive generations of wheat (Triticum aestivum) under normal and drought stress conditions. Aust. J. Crop Sci. 7:956–61. 10. Srikrishnah, S. and Sutharsan, S. 2015. Effect of different shade levels on growth and tuber yield of turmeric (Curcuma longa L.) in the Batticaloa district of Sri Lanka. Amer. J. Agril. Env. Sci. 15: 813-816. 11. Suresh, D., Manjunatha H. and Srinivasan, K. 2008. Effect of heat processing of spices on the concentrations of their bioactive principles: turmeric (Curcuma longa), red pepper (Capsicum annuum) and black pepper (Piper nigrum). J Food Compos Anal. 20:346- 351. 12. Weiss, E.A. 2002. Spice crops. CABI Publishing, Wallingfoard. 43. 13. Yan, W. and Tinker, N.A. 2006. Biplot analysis of multi-environment trial data: principles and applications. Cand. J. Plant Sci. 86:623-645. 14. Yan, W., Hunt, L.A., Sheng, Q. and Sulavnics, Z. 2000. Cultivar evaluation and mega-environment investigation based on the GGE biplot. Crop Sci. 40:597-605. 15. Yan, W., Kang, M.S., Ma, B., Woods, S. and Cornelius, P. L. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci., 47(2):643–653.
References
Similar Articles
- Ahmad Azeem, Qaiser Javed, Jianfan Sun, Ikram Ullah, Noman Ali Buttar, Effect of salt stress on seed germination and seedling vigour in okra , Indian Journal of Horticulture: Vol. 77 No. 03 (2020): Indian Journal of Horticulture
- P.P. Singh, Dhurendra Singh, Genetic variability studies for improvement in brinjal under hot arid agro-climate , Indian Journal of Horticulture: Vol. 73 No. 03 (2016): Indian Journal of Horticulture
- J.S. Chandel, Sarita Devi, Effect of CPPU, promalin and hydrogen cyanamide on flowering, yield and fruit quality of kiwifruit , Indian Journal of Horticulture: Vol. 67 No. Special Issue (2010): Indian Journal of Horticulture
- Vijay Bahadur, O.P. Meena, Genetic diversity analysis of indigenous turmeric genotypes using horticultural markers , Indian Journal of Horticulture: Vol. 73 No. 04 (2016): Indian Journal of Horticulture
- Vishwanath Bidaramali, T. L. Bhutia, A. K. Sureja, A. D. Munshi, Amrita Das, Boopalakrishnan, G, Gopalakrishnan, S, T. K. Behera, S. S. Dey, Genetics of downy mildew resistance in indigenous cucumber germplasm , Indian Journal of Horticulture: Vol. 80 No. 1 (2023): Indian Journal of Horticulture
- K. Ramachandrudu, M. Thangam, Performance of heliconia under coconut garden and open field conditions , Indian Journal of Horticulture: Vol. 69 No. 03 (2012): Indian Journal of Horticulture
- P. Muthukumar, Pritam Kalia, Munish Sharma, Sonia Vashisht, Study of β-carotene enhancing ‘Or’ gene effects on yield and contributing traits in mid-season Indian cauliflower (Brassica oleracea var. botrytis L.) , Indian Journal of Horticulture: Vol. 74 No. 04 (2017): Indian Journal of Horticulture
- Dinesh Kumar, Nazeer Ahmed, Effect of rain water harvesting and mulch material on soil moisture regimes, fertility status and yield of almond under rainfed conditions of north western Himalayas , Indian Journal of Horticulture: Vol. 72 No. 02 (2015): Indian Journal of Horticulture
- Nakul Gupta, Sudhir Kumar Jain, Bhoopal Singh Tomar, Anjali Anand, Jogendra Singh, Awani Kumar Singh, Influence of fruit load per vine on seed quality in cucumber (Cucumis sativus L) grown under open field and protected environments , Indian Journal of Horticulture: Vol. 78 No. 01 (2021): Indian Journal of Horticulture
- P.P. Singh, A.K. Verma, Dhurendra Singh, Evaluation of brinjal genotype under hot arid agro-climate , Indian Journal of Horticulture: Vol. 75 No. 03 (2018): Indian Journal of Horticulture
<< < 11 12 13 14 15 16 17 18 19 20 > >>
You may also start an advanced similarity search for this article.
