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Identification of Diverse Core Set of Germplasm for Abiotic Stress Tolerance in Rice

KrishiKosh

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Title Identification of Diverse Core Set of Germplasm for Abiotic Stress Tolerance in Rice
M.Sc.
 
Creator Bardhan, Soumya Ranjan
 
Contributor Rao, A. R.
 
Subject sets, tolerance, germplasm, selection, rice, sampling, planting, genetics, genes, food preservation
 
Description ABSTRACT
Knowledge of germplasm diversity among breeding material is an invaluable aid in
crop improvement programs. Genetic diversity refers to variation within the
individual gene locus/ among alleles of a gene, or gene combination, between
individual plants or between plant populations. With the availability of population of
rice germplasm, it will be interesting to identify a core set of germplasm accessions
representing the maximum diversity present in the population. These rice germplasm
exhibits tolerance to different degree of abiotic stresses like heat, cold, moisture,
salinity and submergence. With the advent of SNP genotyping technologies and
availability of phenotypic traits performance of germplasm, the amount of
information available an quantitative and qualitative traits is enormous and their
number is much larger than the number of germplasm accessions or observations.
Handling of such high dimensional mixture data remains a challenge for plant
breeders to identify diversified core sets of germplasm. Also, only a subset of SNPs is
associated with the phenotypic traits. Hence, an application of suitable variable
selection methods for screening of significant SNPs associated with traits is essential.
It is also necessary to identify suitable clustering procedure(s) and sampling strategies
to identify maximal diversified core set from a population of germplasm with mixture
data. Keeping this in view, the present study is taken up with the following objectives
(i) to select effective SNPs associated with the different phenotypic traits, (ii) to
identify core set of germplasm by employing suitable combination of clustering
method and sampling strategies and (iii) to compare the performance of diversity
indices obtained from different core sets to identify core set with maximum diversity.
The developed procedure is finally illustrated by using a data set with mixture data on
salinity stress tolerance in rice germplasm accessions. The results reveal that the
application of random forest and LASSO are useful to identify effective SNPs
associated with the phenotypic trait performance. Further, a combination of Ward’s
clustering method with Gower’s distance and NY allocation method with at least 25%
of sampling intensity is found suitable criterion to develop a maximal diversified core
set of rice germplasm for salinity stress tolerance.
 
Date 2016-03-09T17:49:33Z
2016-03-09T17:49:33Z
2013
 
Type Thesis
 
Identifier http://krishikosh.egranth.ac.in/handle/1/65025
 
Language en_US
 
Format application/pdf
 
Publisher IARI, Indian Agricultural Statistics Research Institute, New Delhi