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GENETIC DIVERGENCE IN RICE (Oryza sativa L.)

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Title GENETIC DIVERGENCE IN RICE (Oryza sativa L.)
 
Creator SIVA PARVATHI, P
 
Contributor SATAYANARAYANA RAO, V
 
Subject genotypes, developmental stages, grain, phenotypes, planting, yields, rice, genetics, biological phenomena, packaging
RICE, (Oryza sativa L.)
 
Description The present investigation was carried out during kharif 2009-2010, at Agricultural
College Farm, Bapatla, with 84 genotypes of Rice (Oryza sativa L.) to elicit information
on the nature and extent of variability, heritability, genetic advance, character association,
the magnitude of direct and indirect effects of yield components on yield and genetic
divergence based on the characters viz., plant height, total number of tillers, ear bearing
tillers per plant (EBT/ plant), panicle length, days to 50% flowering, number of filled
grains per panicle, grain length, grain width, flag leaf length, test weight, grain yield per
plot, kernel length, kernel breadth, kernel length after cooking (KLAC), water uptake,
alkali spreading value, amylose content, protein percentage, gel consistency, hulling
percentage, milling percentage and head rice recovery percentage (HRR %).
The mean, variability, heritability, genetic advance as per cent of mean, genetic
divergence, character association and the magnitude of direct and indirect effects of yield
component traits with grain yield were studied for 22 characters.
The analysis of variance revealed significant differences among the genotypes for
all the characters studied indicating that the data generated from the above diverse
material shall represent wide variability. The genotypic coefficients of variation for all the
characters studied were lesser than the phenotypic coefficients of variation indicating the
modifying effect of the environment in association with the characters at genotypic level.
High PCV coupled with high GCV observed for filled grains per panicle, test weight, grain
yield per plot, alkali spreading value, and gel consistency. High heritability coupled with
high genetic advance as per cent of mean was observed for all the traits except for panicle
length, days to 50% flowering, grain length, grain width, kernel breadth, amylose content,
hulling percentage, milling percentage, head rice recovery percentage indicating the
operation of additive gene action in the inheritance of these traits and improvement of
these characters is possible through simple selection.
The correlation study indicated that plant height, total tillers per plant, ear bearing
tillers per plant, panicle length, days to 50% flowering, filled grains per panicle and grain
length showed significant positive association with grain yield at both phenotypic and
genotypic levels. So, improvement in grain yield is possible by giving emphasis on above
characters in selection scheme.
The path analysis revealed that total tillers per plant, ear bearing tillers per plant
and filled grains per panicle exerted direct positive significant association with grain yield
per plot at phenotypic and genotypic levels.
The results of D2 analysis indicated the presence considerable genetic divergence
among the 84 genotypes studied. The 84 genotypes were grouped into ten clusters. Out of
22 characters studied, alkali spreading value, gel consistency, kernel length after cooking,
kernel length contributed maximum towards divergence. Based upon the divergence
studies crosses may be made between the genotypes of cluster II (1111, 1124, 1504, 1546,
1110 and 1118) and X (1502, 1527, 1122, 1533 and 1127) having the distance 1051.145
followed by cluster V (1107) and X having the distance 978.842 to obtain transgressive
recombinants in rice for their yield and quality traits.
The principal component analysis identified nine principal components. Out of
which PC 1 contributed maximum to the variance. Characters viz., kernal length, grain
length, hulling percentage and test weight explained the maximum variance. Genotypes
like 1520, 1518, 1124 and 1538 scattered distantly in 2D and 3D plots showing their
maximum divergence and these genotypes can be utilized in breeding programmes for
exploitation of heterosis.
Hierarchical cluster analysis grouped the 84 genotypes into ten clusters.
Maximum divergence was observed between clusters V (1502, 1527, 1531 and 1122) and
X (1111, 1124, 1504, 1121, 1123, 1130 and 1145) (3646.751) followed by clusters V
(1502, 1527, 1531 and 1122) and IX (1511, 1139, 1107, 1118, 1110, 1546, 1303, 1128,
1134 and 1307) (2905.756).
 
Date 2016-06-06T10:33:43Z
2016-06-06T10:33:43Z
2010
 
Type Thesis
 
Identifier http://krishikosh.egranth.ac.in/handle/1/66809
 
Language en
 
Relation D9049;
 
Format application/pdf
 
Publisher ACHARYA N. G. RANGA AGRICULTURAL UNIVERSITY