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United States Department of Agriculture

Agricultural Research Service

Title: Correlative association between the UDSA rice gemrplasm collection and its core subset based on 14 descriptors

Authors
item Yan, Wengui
item Rutger, J
item Bryant, Rolfe
item Bockelman, Harold
item Fjellstrom, Robert
item Chen, Ming-Hsuan
item Tai, Thomas
item McClung, Anna
item McClung, Anna

Submitted to: ASA-CSSA-SSSA Proceedings
Publication Type: Abstract Only
Publication Acceptance Date: August 15, 2006
Publication Date: November 12, 2006
Citation: Yan, W., Rutger, J.N., Bryant, R.J., Bockelman, H.E., Fjellstrom, R.G., Chen, M.H., Tai, T., Mcclung, A.M. 2006. Correlative association between the UDSA rice gemrplasm collection and its core subset based on 14 descriptors [abstract]. Agronomy Abstracts. p. 142.

Technical Abstract: The USDA rice germplasm collection is managed by GRIN at www.ars-grin.gov. A core subset including about 10% of total accessions was assembled in 2002. Frequency distributions for 14 descriptors: days to flower, plant height, awn type, panicle type, plant type, kernel length, width, length/width, and weight, hull color, hull cover, bran color, amylose content and alkali spreading value (ASV) were used to analyze the association of the core to the whole collection. Eight descriptors or 57% had correlation coefficients greater than 0.9, or coefficient of determination greater than 0.8. Descriptor ASV, amylose, kernel length and ratio had correlations less than 0.8, relatively lower than others. This is probably due to the fact that the data available in the whole collection span a narrower period of time when accessions were introduced and a narrower geographic range (fewer countries) of origin than the core collection. The 14 descriptors proved a high correlation of r=0.94 (P<0.0001), which resulted in determination coefficient r2=0.88 between the whole and core collections for frequency distributions. The high correlation demonstrated that information drawn from the core subset containing 10% of accessions in the whole collection could be effectively used to assess the whole collection with 88% certainty.

Last Modified: 10/25/2014
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