physicochemical

ABSTRACTS
Genetic divergence in Sesame (Sesamum indicum L.)
Student: J. Swapna
Major Advisor: Dr. P. V. Rama Kumar
Department of Genetics and Plant Breeding
The present study was carried out with 60
sesame genotypes (Sesamum indicum L.) to evoke
information on nature and extent of genetic variability,
heritability, genetic advance, genetic divergence,
character association and path analysis. The experiment
was laid out at Agricultural College Farm, Bapatla in a
randomized block design with three replications during
Kharif 2007-08. Observations were recorded on 10
quantitative characters i.e., days 50% flowering, plant
height (cm), days to maturity, number of primaries, number
of secondaries, capsules per plant, seeds per plant,
seeds per capsules, 1000-seed weight (g), oil content
(%) and seed yield per plant (g).
All the characters studied showed less genotypic
coefficients of variation than the phenotypic coefficients
of variation, revealing the masking effect of the
environment. High genetic variability coupled with high
heritability and genetic advance as per cent of mean
was observed for seeds per capsule, 1000-seed weight
and seed yield per plant, indicating the role of additive
gene action governing the inheritance of these traits and
these traits can be improved by simple selection.
The correlation studies revealed that days to
50% flowering, days to maturity number of primaries,
numbers of secondaries, capsules per plant, seeds per
capsule, 1000-seed weight and oil content (%) were
found to have significant positive association with seed
yield and among themselves.
Path coefficient analysis showed high positive
direct effect of seeds per capsule, capsules per plant,
1000-seed weight and oil content on seed yield.
Therefore, simultaneous selection for these traits is
suggested for improvement of seed yield in sesame.
The result of multivariate analysis revealed the
presence of considerable genetic divergence among
the 60-sesame genotypes studies and were grouped
into 7 clusters as per D 2 analysis. Clustering pattern of
genotypes did not follow geographical origin, suggesting
that geographical isolation may not be the only factor
causing genetic diversity. Based on D 2 analysis, crosses
may be effective between the genotypes of cluster VI
(E8) and cluster VII (VZM-23) followed by cluster IV (VSP-
14 ) VI (E8).
Out of 10 characters studies, 1000-seed weight
(g) (48.02%) contributed maximum towards diversity
followed by plant height (19.27%), seed yield per plant
(12.82%), number of secondaries (9.32%), capsules per
plant (4.75%). The character number of primaries
(3.67%), oil content % (1.19%), seed per capsule
(0.57%), days to 50% flowering (0.28%) and days to
maturity (0.11%) contributed less towards genetic
diversity.
Principal component analysis recognized four principal
component (PCs) eigen values more than one
contributed 90.55 per cent cumulative variance. The
contribution by the first PC was maximum and is loaded
with maximum contributing variables viz., 1000-seed
weight, seed yield per plant, oil content (%), capsules
per plant, plant height, number of primaries and seed
per capsule. This analysis identifies that genotypes (JCS-
9426, TMV- 4, Swetha Til, EC-355653, AKT-132, TMV-
5, Vinayak and VRI-1 have maximum variance for the
above characters.
The clustering pattern is in accordance with the
principal component analysis. Hierarchical cluster
analysis revealed the sub groups in the major group of
genotypes through Ward’s minimum variance method.
M.Sc (Ag), 2008
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