181-4 Use of An Automated Sorter to Enrich for Kernel Color In Winter Wheat (Triticum aestivum L.) Populations.



Tuesday, October 18, 2011: 8:50 AM
Henry Gonzalez Convention Center, Room 213A, Concourse Level

William Berzonsky1, Dalitso Yabwalo1 and Thomas Pearson2, (1)Plant Science, South Dakota State University, Brookings, SD
(2)CGAHR - Engineering and Wind Erosion Research Unit, USDA-ARS, Manhattan, KS
Wheat breeders continue to develop white kernel varieties for end-use markets, and tools are needed to enrich for the white genotypes.  This study examined use of an automated kernel sorter to enrich populations for white kernel genotypes.  The sorter was applied to six F2 populations, each originating from a cross between different hard white and red winter wheat parents.  After sorting, samples were categorized as red-sorted (rs), and white-sorted (ws), and a colorimeter was used to record the L* brightness (0 = black to 100 = diffuse white) for each category.  Before planting in 2009, L* differences between the rs and ws categories ranged from an average of 1.34 for population 1, with the brightest kernels, to 3.23 for a population with the darkest kernels.  Within each category, 300 kernels were also stained with a solution to enhance kernel color differences and visually determine the percent white kernels in each category.  Percent white kernels in categories were; population 1 = 26% rs, 42% ws; population 2 = 3% rs, 14% ws; population 3 = 12% rs, 32% ws; population 4 = 17% rs, 32% ws; population 5 = 6% rs, 17% ws; and population 6 = 8% rs, 27% ws.  In year-1, samples representing each category were grown in replicated field plots grown at two South Dakota locations.  Upon harvest in 2010, population 1 had 41% and 50% white kernels in rs and ws categories, respectively at one location, and 37% and 44% at another location.  Sorting population 1 prior to planting again in 2011 enriched it to 33% and 74% white kernels in rs and ws categories, respectively.  The sorter worked to enrich all populations, and particularly the population with the greatest initial kernel brightness; however, its effectiveness also depended on the environment and its influence on the samples.
See more from this Division: ASA Section: Agronomic Production Systems
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