Identification of a suitable clustering method and allocation strategy for core set development in salt stress tolerant rice (Oryza sativa) germplasm

SOUMYA RANJAN BARDHAN; A R RAO; PRABINA KUMAR MEHER; SUDEEP MARWAHA; S D WAHI

doi:10.56093/ijas.v85i12.54301

Authors

SOUMYA RANJAN BARDHAN Senior Research Fellow, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
A R RAO Principal Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
PRABINA KUMAR MEHER Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
SUDEEP MARWAHA Senior Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012
S D WAHI Principal Scientist, ICAR-Indian Agricultural Statistics Research Institute, New Delhi 110 012

https://doi.org/10.56093/ijas.v85i12.54301

Keywords:

Core set, Genetic diversity, Rice germplasm, Salinity stress, SNP genotyping

Abstract

Preserving genetic diversity in repository of germplasm is essential for crop breeding programs. However, maintenance and protection of all the germplasms in gene bank is difficult due to its voluminous size. Hence the development of core set with minimum number of germplasm representing maximum genetic diversity of the population has become an alternative. From the available clustering methods and allocation strategies, identifying a suitable combination is essential for the development of species-specific core set. In the present study, data on 219 salt stress tolerant rice (Oryza sativa L.) germplasm accessions with 14 phenotypic traits and 2915 genome wide Single Nucleotide Polymorphisms (SNPs) is considered to identify a suitable combination of clustering method and allocation strategy for core set development. Eight different combinations consisting of two clustering methods, viz. Wardâ€™s and UPGMA along with four different allocation strategies, viz. L, D, LD and NY allocation with three level of sampling intensities (20%, 25% and 30%) have been tried. Based on the study carried out during 2013-14 at Indian Agricultural Statistics Research Institute, New Delhi, it is concluded that the Wardâ€™s clustering method with NY allocation, irrespective of sampling intensity, is suitable for developing core set with maximum diversity.

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