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International Journal of Applied Agricultural & Horticultural Sciences
  • 29 March, 2024
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Language : English
DOI Prefix : 10.37322
P-ISSN : 0974-0775
E-ISSN : 2582-4198
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Vol. 7 (4) : July-August 2016 issue
Green Farming Vol. 7 (4) : 799-802 ; July-August, 2016
Genetic variability, correlation and path analysis for yield and its components in horsegram (Macrotyloma uniflorum [Lam.] Verdc.)
RAKESH ALLEa1*, V. HEMALATHAa2, K.B. ESWARIa3 and V. SWARNALATHAb4
aDept of Genetics and Plant Breeding, Prof. Jayashankar Telangana State Agric. University, Hyderabad (Telangana)
bMaize Research Centre, Agricultural Res. Institute, Rajendranagar - 500 030, Hyderabad (Telangana)
Designation :  
1P.G. Student *(rakeshalle.agrico@gmail.com), 2,3Assoc. Professor, 4Scientist
Subject : Crop Genetics and Plant Breeding
Paper No. : P-4082
Total Pages : 4
Received : 10 August 2015
Revised accepted : 13 May 2016
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Citation :

RAKESH ALLE, V. HEMALATHA, K.B. ESWARI and V. SWARNALATHA. 2016. Genetic variability, correlation and path analysis for yield and its components in horsegram (Macrotyloma uniflorum [Lam.] Verdc.). Green Farming Vol. 7 (4) : 799-802 ; July-August, 2016

ABSTRACT
Genetic variability, character association and their direct and indirect effects on yield are important for crop improvement. Twenty nine crosses that resulted from crossing 9 lines with 3 testers through L x T design along with a check were grown in late kharif season 2013 to study the character association (correlation analysis) and path analysis among eleven characters. The mean sum of squares due to genotypes (parents and crosses) was highly significant for all the traits studied in this investigation. It revealed the presence of significant variability in the material studied for all the characters. The phenotypic coefficient of variation (PCV) were higher than the genotypic coefficient of variation (GCV) for all the characters in the study. The highest magnitude of PCV and GCV were recorded by number of pods per plant followed by number of clusters per plant and seed yield per plant. Correlation analysis revealed that 100 seed weight, number of pods per plant, number of clusters per plant, number of primary branches, pod length, number of seeds per pod and plant height showed positive and significant association with seed yield per plant. Path analysis revealed that 100 seed weight, number of clusters per plant, plant height and number of pods per plant were exhibited high direct effect showing the importance of these characters to the yield to improve the seed yield through selection. The present findings could be useful for establishing the criteria for high seed yield in the breeding programme.
Key words :
Correlation, GCV & PCV, Genetic variability, Horsegram, Path coefficient, Yield components.