Characterisation and Classification of Indian mustard [(Brassica juncea (L.) Czern & Coss.)] genotypes using multivariate analysis
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Date
2013
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CCSHAU
Abstract
The present study was conducted on 60 Indian mustard genotypes which was grown during
rabi 2011-2012 to evaluate, categorize and classify them and for computation of principal components
to determine the relative importance of principal components and characters involved in them.
Observations were recorded on 16 quantitative and 9 qualitative traits involving seed yield, its
attributes and oil content. All the genotypes were characterized for 25 agro-morphological characters
ranging from seedling emergence to crop maturity. A considerable level of variability was noticed for a
number of agro-morphological traits. Results revealed that maximum variation was found among
genotypes on the basis of seed yield in which seven genotypes were grouped into low, thirty two
genotypes in medium and twenty one genotypes in high seed yield/ plant category whereas, oil content
varied from low (40 genotypes) and medium (20 genotypes) category. In case of 1000-seed weight,
twelve genotypes had very low, thirty eight genotypes had medium and remaining ten genotypes had
high 1000-seed weight. Thirty three genotypes were having few numbers of seeds/ siliqua whereas,
intermediate number of seeds/ siliqua was recorded in twenty seven genotypes. On the basis of siliqua
density on main shoot, fifty two genotypes were grouped into medium, six in high and two in low
siliqua density category. Classification of genotypes on the basis of DUS traits provided identification
of key characteristics of various genotypes. Hierarchical cluster analysis classified the genotypes into
ten clusters containing one to twenty three genotypes. The cluster III and IV showed superiority for
seed yield/ plant due to possessing of more number of siliquae/ plant. To know the relative importance
and usefulness of variables and genotypes, principal component analysis was done which explained
75.26% variability through eleven principal components having eigen value more than one. Data were
further analyzed using principal factor analysis to offset the limitations of principal component
analysis. All the variables exhibited high loadings on different factors in such a manner that they could
be designated as growth rate factor, leafiness factor, yield factor and color factor etc. depending upon
the type of variables loaded on a particular factor. Genotypes JMM-937, RC-199, RH-0401(YS), Pusa
bold, Pusa bahar and KM-888 were found to be better performers on the basis of principal factor scores
with regard to seed yield and its components when all the principal factors were considered
simultaneously.
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Keywords
Brassica, Indian mustard, cluster, principal factor, variability and multivariate analysis