GGE biplot analysis of finger millet (Eleusine coracana) genotypes under diverse agro-climatic conditions of Uttarakhand


Abstract views: 258 / PDF downloads: 263 / PDF downloads: 25

Authors

  • B B BANDYOPADHYAY G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand
  • SUBHASH CHAND G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263 145, India https://orcid.org/0000-0001-6898-9861
  • P K PANDEY G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263 145, India
  • D C BASKHETI G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263 145, India
  • K RAHUL G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263 145, India
  • SHIR PAL G B Pant University of Agriculture and Technology, Pantnagar, Uttarakhand 263 145, India
  • KAILASH CHANDRA College of Agriculture (SKN Agriculture University, Jobner), Fatehpur-Shekhawati, Sikar, Rajasthan
  • BHARATH K ALAM ICAR-National Research Center for Orchids, Pakyong, Sikkim
  • RAJAT CHOUDHARY ICAR-Indian Agricultural Research Institute, New Delhi
  • ANKIT MALIK ICAR-Indian Agricultural Research Institute, New Delhi

https://doi.org/10.56093/ijas.v93i6.132553

Keywords:

Finger millet, Genotype-by-environment interaction, GGE biplot, Stability, Representativeness

Abstract

Finger millet [Eleusine coracana (L.) Gaertn] is mostly cultivated in the arid and semi-arid regions of India. In this study, 11 finger millet genotypes were evaluated for six traits in a randomized complete block design with three replications at Ranichauri (E1), Dehradun (E2) and Pantnagar (E3) of Uttarakhand during kharif 2018 and 2019. The analysis of variance revealed significant variation among genotypes due to genotypes (G), environments (E) and G×E interaction (GEI) effects. The environment contributed for 37.3%, 38.6%, 58.2%, 65.5%, 21.0% and 76.9% of the total variation for days to 50% flowering, plant height, number of tillers, number of heads, number of fingers and grain yield, respectively. Grain yield exhibited a crossover-type GEI effect with a high environmental and GEI variance proportion. The mean grain yield over the locations was ranged from 16.9 (E1) to 38.8 q/ha (E3), whereas the genotypic mean was stretched from 22.7 (PF5) to 34.3 q/ha (PF8). The GGE biplot graphical analysis identified three mega environments, and the best genotypes were PF5, PF6 and PF2 in E1; PF8 in E2; PF10 and PF11 in E3. Based on a hypothetical ideal genotype, PF8 was identified as the best genotype owing to the high mean grain yield and stability over the locations. The ranking of genotypes based on ideal genotype would be as follows: PF8>PF10>PF3>PF7>PF2>PF1>PF11>PF4>PF9>PF6>PF5. The location Dehradun had high discriminating ability and representativeness and considered as the best environment for selecting high-yielding and stable genotypes among the locations.

Downloads

Download data is not yet available.

References

Aarthi S, Suresh J, Leela N K and Prasath D. 2020. Multi environment testing reveals genotype-environment interaction for curcuminoids in turmeric (Curcuma longa L.). Industrial Crops and Products 145(January): 112090. DOI: https://doi.org/10.1016/j.indcrop.2020.112090

Bandyopadhyay B B. 2001. Temperature and precipitation effects on grain yield of finger millet (Eleusine coracana) genotypes at high hills of Garhwal Himalayas. Indian Journal of Agricultural Sciences 71(3): 205–8.

Chand S, Chandra K, Indu, and Khatik C L. 2021. Varietal release, notification and denotification system in India. Plant Breeding - Current and Future Views, pp. 1–12. Abdurakhmonov I Y (Eds), IntechOpen. DOI: https://doi.org/10.5772/intechopen.94212

Chandra D, Chandra S, Pallavi and Sharma A K. 2016. Review of finger millet (Eleusine coracana (L.) Gaertn): A power house of health benefiting nutrients. Food Science and Human Wellness 5(3): 149–55. DOI: https://doi.org/10.1016/j.fshw.2016.05.004

Ghaffari M, Gholizadeh A, Andarkhor S A, Siahbidi A Z, Ahmadi S A K, Shariati F and Rezaeizad A. 2021. Stability and genotype × environment analysis of oil yield of sunflower single cross hybrids in diverse environments of Iran. Euphytica 217(10): 1–11. DOI: https://doi.org/10.1007/s10681-021-02921-w

Hilu K W, Wet J M J D and Harlan J R. 1979. Archaeobotanical studies of Eleusine coracana ssp. coracana (Finger millet). American Journal of Botany 66(3): 330–33. DOI: https://doi.org/10.1002/j.1537-2197.1979.tb06231.x

Reddy Y A N, Gowda J and Gowda K T K. 2021. Approaches for enhancing grain yield of finger millet (Eleusine coracana). Plant Genetic Resources: Characterisation and Utilisation (May): 1–9. doi: 10.1017/S1479262121000265. DOI: https://doi.org/10.1017/S1479262121000265

PBTools, version 1.4. 2014. Biometrics and Breeding Informatics, PBGB Division, International Rice Research Institute, Los Baños, Laguna. http://bbi.irri.org/products

Sharma N, Bandyopadhyay B B, Chand S, Pandey P K, Baskheti D C and Alam B K. 2022a. Genetic diversity, trait association and cause effect analysis in selected genotypes of finger millet [Eleusine coracana (L.) Gaertn.]. Journal of Environmental Biology 43(July): 551–61. DOI: https://doi.org/10.22438/jeb/43/4/MRN-2052

Sharma N, Bandyopadhyay B B, Chand S, Pandey P K, Baskheti D, Malik A and Chaudhary R. 2022b. Determining selection criteria in finger millet (Eleusine coracana) genotypes using multivariate analysis. Indian Journal of Agricultural Sciences 92(6): 763–8. DOI: https://doi.org/10.56093/ijas.v92i6.118939

Suwarno W B, Sobir S, Aswidinnoor H and Syukur M. 2015. PBSTAT: A web-based statistical analysis software for participatory plant breeding. http://repository.ipb.ac.id/handle/123456789/73862

Yan W. 2015. Mega-environment analysis and test location evaluation based on unbalanced multiyear data. Crop Science 55(1): 113–22. DOI: https://doi.org/10.2135/cropsci2014.03.0203

Yan W and Kang M S. 2003. GGE Biplot Analysis A Graphical Tool for Breeders, Geneticists, and Agronomists, pp. 1–267. Yan W and Kang M S (Eds), CRC Press LLC. ISBN 0-8493- 1338-4 (alk. paper).

Yan W and Tinker N A. 2006. Biplot analysis of multi-environment trial data: Principles and applications. Canadian Journal of Plant Science 86(3): 623–45. DOI: https://doi.org/10.4141/P05-169

Submitted

2023-01-23

Published

2023-07-07

Issue

Section

Articles

How to Cite

BANDYOPADHYAY, B. B., CHAND, S., PANDEY, P. K., BASKHETI, D. C., RAHUL, K., PAL, S., CHANDRA, K., ALAM, B. K., CHOUDHARY, R., & MALIK, A. (2023). GGE biplot analysis of finger millet (Eleusine coracana) genotypes under diverse agro-climatic conditions of Uttarakhand. The Indian Journal of Agricultural Sciences, 93(6), 602–608. https://doi.org/10.56093/ijas.v93i6.132553
Citation