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Development of a Core Set from a Large Rice Collection using a Modified Heuristic Algorithm to Retain Maximum Diversity
Author(s) -
Chung HunKi,
Kim KyuWon,
Chung JongWook,
Lee JungRo,
Lee SokYoung,
Dixit Anupam,
Kang HeeKyoung,
Zhao Weiguo,
McNally Kenneth L.,
Hamilton Ruraidh S.,
Gwag JaeGyun,
Park YongJin
Publication year - 2009
Publication title -
journal of integrative plant biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.734
H-Index - 83
eISSN - 1744-7909
pISSN - 1672-9072
DOI - 10.1111/j.1744-7909.2009.00882.x
Subject(s) - heuristic , core (optical fiber) , set (abstract data type) , redundancy (engineering) , computer science , algorithm , diversity (politics) , trait , data mining , artificial intelligence , telecommunications , programming language , operating system , sociology , anthropology
A new heuristic approach was undertaken for the establishment of a core set for the diversity research of rice. As a result, 107 entries were selected from the 10 368 characterized accessions. The core set derived using this new approach provided a good representation of the characterized accessions present in the entire collection. No significant differences for the mean, range, standard deviation and coefficient of variation of each trait were observed between the core and existing collections. We also compared the diversity of core sets established using this Heuristic Core Collection (HCC) approach with those of core sets established using the conventional clustering methods. This modified heuristic algorithm can also be used to select genotype data with allelic richness and reduced redundancy, and to facilitate management and use of large collections of plant genetic resources in a more efficient way.