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

B B BANDYOPADHYAY; SUBHASH CHAND; P K PANDEY; D C BASKHETI; K RAHUL; SHIR PAL; KAILASH CHANDRA; BHARATH K ALAM; RAJAT CHOUDHARY; ANKIT MALIK

doi:10.56093/ijas.v93i6.132553

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.

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