Title: Automated Single-Kernel Sorting to Select for Quality Traits in Wheat Breeding Lines Authors
Submitted to: Cereal Chemistry
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: May 4, 2009
Publication Date: September 1, 2009
Repository URL: http://www.ars.usda.gov/SP2UserFiles/Place/54300520/409AutomatedSingel-Kernelsortingtoselectforquality.pdf
Citation: Dowell, F.E., Maghirang, E.B., Baenziger, P. 2009. Automated Single-Kernel Sorting to Select for Quality Traits in Wheat Breeding Lines. Cereal Chemistry. 86(5):527-533. doi: 10-1094/CCHEM-86-5-0527. Interpretive Summary: Wheat breeding programs continually strive to improve the quality of their lines to meet market demands. Plants may be selected based on the presence of genes that are presumed to result in beneficial characteristics, or based on the expression of desirable traits. Seeds likely to propagate these desirable traits can be selected using molecular techniques or by measuring the seed chemical composition or morphological characteristics. However, these methods are either tedious, time-consuming, applicable only to large samples, or destructive. We applied single kernel near-infrared (SKNIR) sorting technology to selecting kernels with specific traits. The SKNIR system was effective at sorting kernels to increase hardness, protein content, or grain color purity, and it was effective at enabling selection for permanent increases in the expression of these trains in progeny. One advantage of enriching a population for desirable traits is that a breeder can more easily select for desirable lines in the sorted populations that have those traits. The chance of identifying an improved line can be increased with sorting which will improve the efficiency of breeding programs, thus resulting in more rapid release of improved cultivars.
Technical Abstract: An automated single kernel near-infrared system was used to select kernels to enhance the end-use quality of hard red wheat breeder samples. Twenty breeding populations and advanced lines were sorted for hardness index, protein content, and kernel color. To determine if the phenotypic sorting was based upon genetic or environmental differences, the progeny of the unsorted control and sorted samples were planted at two locations two years later to determine if differences in the sorted samples were transmitted to the progeny (e.g. based on genetic differences). The average hardness index of the harvested wheat samples for segregating populations improved significantly by seven hardness units. For the advanced lines, hardness index was not affected by sorting indicating little genetic variation within these lines. When sorting by protein content, a significant increase from 12.1% to 12.6% was observed at one location. Purity of the red samples was improved from about 78% (unsorted control) to about 92% (sorted samples), while the purity of the white samples improved from 22% (control) to about 62% (sorted samples). Similar positive results were found for sorting red and blue kernel samples. Sorting for kernel hardness, color, and protein content is effective and based upon genetic variation.