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Approaches for enhancing grain yield of finger millet (Eleusine coracana)

Published online by Cambridge University Press:  03 May 2021

Y. A. Nanja Reddy
Department of Crop Physiology, Bengaluru 560065, India AICRP on Small Millets, University of Agricultural Sciences, GKVK, Bengaluru 560065, India
Jayarame Gowda
AICRP on Small Millets, University of Agricultural Sciences, GKVK, Bengaluru 560065, India
K. T. Krishne Gowda
AICRP on Small Millets, University of Agricultural Sciences, GKVK, Bengaluru 560065, India
E-mail address:


Finger millet is gaining importance as a food crop with the increasing emphasis on nutritional aspects and drought resilience. However, yield improvement has stagnated. Therefore, popular varieties have been examined for the purpose of whether direct selection for grain yield can be continued or an alternate trait-based approach using the germplasm is necessary. Direct selection for grain yield over the ruling variety, cv. GPU-28 (Germplasm Unit) has not been satisfactory. The path analysis has revealed a high direct effect of mean ear weight on grain yield followed by a moderate direct effect of photosynthetic rate and leaf area index. Furthermore, backward stepwise regression analysis revealed that among the independent traits, the mean ear weight made a significant contribution (60.8%) towards grain yield, followed by the photosynthetic rate (39.2%). The regression equation predicts the inclusion of mean ear weight by 1.0 g extra (as in GE-2672) to cv. GPU-28 will increase grain yield by 4.74%. The trait-specific genotypes are superior to the cv. GPU-28 were GPU-67 (photosynthetic rate) and GE-2672 (mean ear weight) and they could be used as donors for yield improvement. Future selection would aim for genotypes having 70–75 days for flowering with 4−5 productive tillers and mean ear weight of more than 8−9 g/ear. The possible approaches for enhancing grain yield are also discussed.

Research Article
Copyright © The Author(s), 2021. Published by Cambridge University Press on behalf of NIAB

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