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United States Department of Agriculture

Agricultural Research Service

Title: Variation in plant and seed traits found in a diverse collection of rice accessions

Authors
item Eizenga, Georgia
item Mccouch, Susan - CORNELL UNIVERSITY
item McClung, Anna
item McClung, Anna

Submitted to: American Society of Agronomy Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: September 1, 2007
Publication Date: November 8, 2007
Citation: Eizenga, G.C., Mccouch, S.R., Mcclung, A.M. 2007. Variation in plant and seed traits found in a diverse collection of rice accessions. [abstract] American Society of Agronomy Abstracts, New Orleans, LA, November 4-8, 2007. p. 279-15.

Technical Abstract: Rice (Oryza sativa L.) has been divided into indica and japonica types (sub-species) since ancient times. Morphological, ecotypic and genetic differences distinguish these groups. Recently, five different sub-populations were identified using SSR markers. As part of this project, we aim to examine the genetics of quantitative trait variation for approximately 30 agronomically important traits in the different sub-populations of O. sativa and to trace the sub-population origin of discrete molecular variants that are associated with the QTLs. During summer 2006, phenotypic data was collected on a diverse collection of 400 O. sativa accessions grown in the field at Stuttgart, AR using a RCB design with two replications. Data for heading date, plant height, plant type, tiller number, flag leaf length and width, panicle length, branches per panicle, and seed per panicle will be presented. In addition, preliminary data on seed traits determined using the WinSeedle image analysis system including hull color, grain color, and seed length and width of paddy and brown rice will be summarized. Variation for these traits will be compared to that of 100 accessions of the rice ancestral species, O. rufipogon. Once the second year of phenotypic data is collected on the O. sativa and O. rufipogon accessions, and all 500 accessions have been genotyped with SSR and SNP markers, we will use an association mapping approach to identify the genetic basis of quantitative variation in these materials.

Last Modified: 7/25/2014
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