Abstract:
The national average yield of rice is low which is mainly attributed to shortage of improved
varieties. The present study consists of 36 rice genotypes that were evaluated at two locations,
namely Fogera and Pawe with the objectives of identifying high yielding and well adapted
varieties assessing genetic variability and character association for the 14 traits. The experiments
were conducted using simple lattice design across two locations during the 2015 cropping season.
Combined analysis of variance revealed statistically significant differences (p<0.05) indicating
the existence of genetic variability among the 36 genotypes for all the traits studied. Genotype x
location interactions were significant for days to maturity, plant height, panicle length, culm
length, flag leaf length, number of filled spikelets per panicle, number of total spikelets per
panicle, days to heading, biomass yield, paddy yield and harvest index. Significant differences
were observed for paddy yield that ranged from 6759.00 to 2886.00 kg ha-1 with overall mean
value of 5370.0 kg ha-1
. Higher PCV and GCV values were exhibited by plant height, culm length,
number of unfilled spikelets per panicle, biomass yield and paddy yield. The highest heritability
was recorded for culm length followed by plant height, biomass yield and panicle length. High to
medium heritability coupled with high GCV and high genetic advance as percentage of mean
were exhibited for plant height, biomass yield , paddy yield and number of unfilled spikelets
per panicle. High genetic advances as percent of means were recorded by plant height, culm
length, biomass yield, paddy yield and number of unfilled spikelets per panicle. Clustering of
genotypes were not associated with their geographical origin, instead of the genotypes were
mainly grouped based on morphological significances. The Mahalanobis D2 statistics revealed
that 36 genotypes were grouped into five distinct clusters, and the chi-square test for the five
clusters indicated the presence of highly significant difference (p<0.01) among the clusters,
confirming that the studied genotypes were divergent. Principal component (pc) showed that the
first four PCs having eigen values greater than one accounted about 79.23% of the total
variation. Grain yield exhibited significant (P<0.05) and positive genotypic correlation with days
to heading, days to maturity, number of filled spikelets per panicle, number of fertile tillers per
plant, harvest index, number of total spikelets per panicle and biomass yield. Path coefficient
analysis showed that biomass yield followed by harvest index, number of total spikelets per
panicle and plant height exhibited the highest direct effects on grain yield. These characters can
be considered for indirect selection for paddy yield. This study was carried out only for one
season at two locations. Hence, it is advisable to repeat the study at more number of locations
and seasons in major rice-growing areas by including additional genotypes to come up with
sound conclusion and in the future, molecular analysis techniques should be employed to confirm
the genotypic diversity in this study