655-3 RiceCAP: Mapping Rice Milling Yield QTL In A U.S. Long Grain Cross.

See more from this Division: C07 Genomics, Molecular Genetics & Biotechnology
See more from this Session: Genetic Mechanisms for Enhancing Yield and Quality

Tuesday, 7 October 2008: 10:00 AM
George R. Brown Convention Center, 370A

Anna Mcclung1, Robert Fjellstrom1, James Oard2, Steve Linscombe2, Karen Ann Kuenzel Moldenhauer3, Farman Jodari4, Xavier Lacaze5, Sally Leong6, Henry Nguyen7, Guo-liang Wang8 and Clare Nelson5, (1)USDA-ARS, Stuttgart, AR
(2)School of Plant, Environmental, and Soil Sciences, Louisiana State University, Baton Rouge, LA
(3)2900 Highway 130E, Univ. of Arkansas, Stuttgart, AR
(4)California Rice Research Bd., Biggs, CA
(5)Plant Sciences, Kansas State University, Manhattan, KS
(6)Plant Pathology Univ. Wisconsin, USDA ARS, Madison, WI
(7)Univ. of Missouri, Columbia, MO
(8)Ohio State University, Columbus, OH
Abstract:
Whole grain milling yield is a major determinant of rice crop value. Because this trait is under quantitative inheritance and is sensitive to variation due to the production environment and post-harvest handling, it is difficult to improve. This study was conducted as part of the USDA NRI RiceCAP program to identify QTL associated with rice milling quality. A mapping population of 300 recombinant inbred lines was derived from a cross between two rice cultivars, Cypress (high milling yield) and LaGrue (low milling yield). The lines were genotyped with 106 SSR markers and evaluated for milling yield, grain fissuring, and grain dimension traits under field conditions in Stuttgart, AR and Crowley, LA in 2006 and 2007. QTL for milling yield identified on chromosomes 1, 2 and 10 accounted for 18 and 10% of genotype and genotype x environment variation in whole milling yield, respectively. The QTL on chromosome 10 showed a pleiotropic effect on fissuring susceptibility. All milling QTL were subject to strong interactions with the environment. Environmental characterization based on daily weather records was carried out for each year–location combination. Based on factorial regression, environmental covariates incorporating humidity variation during the grain filling period explain a large part of the QTL x E interaction for individual QTLs.

 

See more from this Division: C07 Genomics, Molecular Genetics & Biotechnology
See more from this Session: Genetic Mechanisms for Enhancing Yield and Quality