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Evaluation of wheat genotypes (Triticum aestivum L.) for assessment of character association, path coefficient and cluster analysis
Author(s) -
Anuj Kumar,
Shailendra Singh Gaurav,
Tejbir Singh,
Ravi Singh Thapa
Publication year - 2018
Publication title -
indian journal of agricultural research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.241
H-Index - 8
eISSN - 0976-058X
pISSN - 0367-8245
DOI - 10.18805/ijare.a-4983
Subject(s) - path coefficient , path analysis (statistics) , cluster (spacecraft) , correlation , correlation coefficient , horticulture , randomized block design , biology , veterinary medicine , mathematics , grain yield , quantitative trait locus , zoology , statistics , medicine , genetics , gene , geometry , computer science , programming language
Thirty wheat genotypes (Triticum aestivum L.) were evaluated for 11 morphological and yield trait for analysis of character association (phenotypic and genotypic correlation coefficient), path analysis and cluster analysis. The experiment was conducted during rabi seasons of 2014-2015 in a randomized block design with three replication. Days to 50% heading showed positive and significant correlation with flag leaf area and number of spiklet per ear; flag leaf area showed positive and significant correlation with 1000 grain weight; Plant height showed positive and significant correlation with spike length; spike length showed positive and significant correlation with 1000 grain weight. Phenotypic path analysis showed biological yield and number of grain per spike had highly positive and direct effect on grain yield. Direct and highly positive effect on grain yield was shown by number of productive tillers, plant height, spike length, number of spikelet per spike genotypic path coefficient. Biological yield and grains yield per plant show highly positive and direct effect on yield with number of productive tillers, plant height, number of spikelet per spike and spike length. In cluster analysis the intra cluster distance ranged from 1.61 (cluster II) to 2.37 (cluster III and VI ). Thus the member of cluster II were least divergent and similarly the member of cluster III and IV were most divergent The maximum inter cluster distance was between cluster II and III followed by cluster IV and V , cluster VI and III and cluster VI and V that order therefore the accessions grouped in the five pair of cluster may be considered as most divergent.

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