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Genetic variability analysis for yield and important agronomic traits in association panel of pearl millet [Pennisetum glaucum (L.) R. Br.]

International Journal of Advanced Biochemistry Research · 2024 · Vol. 8(9S) · pp. 843–848

Abstract

Pearl millet (Pennisetum glaucum (L.) R. Br.) is a quick growing kharif cereal crop which forms the staple food in arid and semi-arid regions of Indian subcontinent and Africa. The present experiment was conducted to know the variability parameters and association among the yield component traits in Pearl Millet Inbred Germplasm Association Panel (PMiGAP) with five checks. The material was evaluated in three locations (environments- ICRISAT, ARS, Vizianagaram and Srikakulam) during kharif, 2021. Analysis of variance revealed significant differences for all the traits indicating ample scope for improvement of yield and various yield attributing characters. All the accessions showed considerable amount of variation in their mean performance for all the studied yield component traits. High phenotypic coefficient of variation (PCV) and genotypic coefficient of variation (GCV) were observed for plant height, panicle weight, GYLD and harvest index in all the environments. High heritability coupled with high genetic advance was observed for all the characters in all the environments except for PHI in location 3. GYLD was positively and significantly correlated with harvest index and panicle harvest index in three locations and with all the traits in location 3. Hence, these characters have to be given importance during the selection programme to improve the grain yield potential of pearl millet.

Genetics and Plant BreedingCrop Yield and Soil FertilityLeaf Properties and Growth MeasurementPennisetumPearlAgronomyYield (engineering)BiologyGeographyPhysics
Citations
1
FWCI
0.60
field-weighted impact
References
0
Percentile
78%
vs. same field & year
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Genetic variability analysis for yield and important agronomic traits in association panel of pearl millet [Pennisetum glaucum (L.) R. Br.] · Scinovex