Pure, white-kernel colored (Triticum aestivum L.) cultivars are needed for new end-use markets, and selection tools are necessary to help wheat breeders differentiate and efficiently separate white and red colored kernels within segregating populations to develop new white-kernel colored wheat cultivars. This study evaluated the effectiveness of an automated optical kernel color sorter to select between white and red kernel colored genotypes and enrich segregating populations for white-kernel genotypes. The sorter was applied to six populations, each of which originated from a cross of different hard white and red winter wheat parents. Prior to initial planting to the field and starting with F3 kernels, each population was sorted into red-sort and white-sort categories, and these categories were maintained throughout the study as well as the population parents and the unsorted category. All categories and population parents were grown at three South Dakota locations; Brookings and Dakota Lakes in 2010, 2011, and 2012, and Winner in 2011 and 2012. Plants in sorted categories in 2010, 2011, and 2012 represented plants in the F4, F5, and F6 generations, respectively. Both parents and sorted categories for each population were grown in three replications of a split-plot design, with populations as main plots and sorted categories as sub-plots. The frequency of white kernels in each sort category was determined after staining harvested kernel samples and visually classifying for kernel color. By the final F6 sort generation, the percent white kernels in the white sort had resulted in significantly more white colored kernels within each population and at each environment, and generally, this increase was significant from the original population to the F4 generation, from the F4 to F5 generation, and from the F5 to F6 kernel generation. Based on the white-sort category, the smallest total mean increase in white colored kernels from the initial F3 kernels to the final harvested F6 kernels was 43% for population 4 (P-4) at the Brookings environment. The largest total mean increase in white colored kernels from the initial population to the final harvested F6 kernels was 88.4% and 89.8% for population 6 (P-6) at the Dakota Lakes and Winner environments, respectively. The optical sorter was effective in separating for kernel color within all six segregating populations, and it is expected to be useful to breeders in helping them select among segregating populations for white-kernel color genotypes. Considering the environments in which these populations were grown, the sorter appeared to be more effective in separating within samples derived from western environments of South Dakota, which were generally drier. Perhaps the lack of weathering in western environments allows for expression of greater contrast between red and white kernels and for the optical sorter to more effectively distinguish between kernel color differences.
","abstract_html":"<p>Pure, white-kernel colored (Triticum aestivum L.) cultivars are needed for new end-use markets, and selection tools are necessary to help wheat breeders differentiate and efficiently separate white and red colored kernels within segregating populations to develop new white-kernel colored wheat cultivars. This study evaluated the effectiveness of an automated optical kernel color sorter to select between white and red kernel colored genotypes and enrich segregating populations for white-kernel genotypes. The sorter was applied to six populations, each of which originated from a cross of different hard white and red winter wheat parents. Prior to initial planting to the field and starting with F3 kernels, each population was sorted into red-sort and white-sort categories, and these categories were maintained throughout the study as well as the population parents and the unsorted category. All categories and population parents were grown at three South Dakota locations; Brookings and Dakota Lakes in 2010, 2011, and 2012, and Winner in 2011 and 2012. Plants in sorted categories in 2010, 2011, and 2012 represented plants in the F<sub>4</sub>, F<sub>5</sub>, and F<sub>6</sub> generations, respectively. Both parents and sorted categories for each population were grown in three replications of a split-plot design, with populations as main plots and sorted categories as sub-plots. The frequency of white kernels in each sort category was determined after staining harvested kernel samples and visually classifying for kernel color. By the final F<sub>6</sub> sort generation, the percent white kernels in the white sort had resulted in significantly more white colored kernels within each population and at each environment, and generally, this increase was significant from the original population to the F<sub>4</sub> generation, from the F<sub>4</sub> to F<sub>5</sub> generation, and from the F<sub>5</sub> to F<sub>6</sub> kernel generation. Based on the white-sort category, the smallest total mean increase in white colored kernels from the initial F<sub>3</sub> kernels to the final harvested F<sub>6</sub> kernels was 43% for population 4 (P-4) at the Brookings environment. The largest total mean increase in white colored kernels from the initial population to the final harvested F6 kernels was 88.4% and 89.8% for population 6 (P-6) at the Dakota Lakes and Winner environments, respectively. The optical sorter was effective in separating for kernel color within all six segregating populations, and it is expected to be useful to breeders in helping them select among segregating populations for white-kernel color genotypes. Considering the environments in which these populations were grown, the sorter appeared to be more effective in separating within samples derived from western environments of South Dakota, which were generally drier. Perhaps the lack of weathering in western environments allows for expression of greater contrast between red and white kernels and for the optical sorter to more effectively distinguish between kernel color differences.</p>","abstract_has_math":false,"creators":["Carsrud, Bradley K."],"institution":null,"degree_name":"Master of Science (MS)","degree_level":"Thesis - University Access Only","degree_discipline":"Plant Science","degree_department":null,"school":null,"contributors":["William A. Bersonsky"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2013,"date_issued":"2013-01-01T08:00:00Z","date_published":"2013-01-01T08:00:00Z","updated_at":"2026-07-24T04:29:08Z","subjects":["Agronomy and Crop Sciences"],"languages":["en"],"rights":["In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/
In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/
Pure, white-kernel colored (Triticum aestivum L.) cultivars are needed for new end-use markets, and selection tools are necessary to help wheat breeders differentiate and efficiently separate white and red colored kernels within segregating populations to develop new white-kernel colored wheat cultivars. This study evaluated the effectiveness of an automated optical kernel color sorter to select between white and red kernel colored genotypes and enrich segregating populations for white-kernel genotypes. The sorter was applied to six populations, each of which originated from a cross of different hard white and red winter wheat parents. Prior to initial planting to the field and starting with F3 kernels, each population was sorted into red-sort and white-sort categories, and these categories were maintained throughout the study as well as the population parents and the unsorted category. All categories and population parents were grown at three South Dakota locations; Brookings and Dakota Lakes in 2010, 2011, and 2012, and Winner in 2011 and 2012. Plants in sorted categories in 2010, 2011, and 2012 represented plants in the F4, F5, and F6 generations, respectively. Both parents and sorted categories for each population were grown in three replications of a split-plot design, with populations as main plots and sorted categories as sub-plots. The frequency of white kernels in each sort category was determined after staining harvested kernel samples and visually classifying for kernel color. By the final F6 sort generation, the percent white kernels in the white sort had resulted in significantly more white colored kernels within each population and at each environment, and generally, this increase was significant from the original population to the F4 generation, from the F4 to F5 generation, and from the F5 to F6 kernel generation. Based on the white-sort category, the smallest total mean increase in white colored kernels from the initial F3 kernels to the final harvested F6 kernels was 43% for population 4 (P-4) at the Brookings environment. The largest total mean increase in white colored kernels from the initial population to the final harvested F6 kernels was 88.4% and 89.8% for population 6 (P-6) at the Dakota Lakes and Winner environments, respectively. The optical sorter was effective in separating for kernel color within all six segregating populations, and it is expected to be useful to breeders in helping them select among segregating populations for white-kernel color genotypes. Considering the environments in which these populations were grown, the sorter appeared to be more effective in separating within samples derived from western environments of South Dakota, which were generally drier. Perhaps the lack of weathering in western environments allows for expression of greater contrast between red and white kernels and for the optical sorter to more effectively distinguish between kernel color differences.
"]},{"key":"dc:title","label":"Title","values":["Use of an Optical Sorter to Select for Winter Wheat (Triticum aestivum L.) Kernel Color"]}]}],"canonical_facts":{"dc:contributor":["William A. Bersonsky"],"dc:creator":["Carsrud, Bradley K."],"dc:date.available":["2017-07-31T07:00:00Z"],"dc:description.abstract":["Pure, white-kernel colored (Triticum aestivum L.) cultivars are needed for new end-use markets, and selection tools are necessary to help wheat breeders differentiate and efficiently separate white and red colored kernels within segregating populations to develop new white-kernel colored wheat cultivars. This study evaluated the effectiveness of an automated optical kernel color sorter to select between white and red kernel colored genotypes and enrich segregating populations for white-kernel genotypes. The sorter was applied to six populations, each of which originated from a cross of different hard white and red winter wheat parents. Prior to initial planting to the field and starting with F3 kernels, each population was sorted into red-sort and white-sort categories, and these categories were maintained throughout the study as well as the population parents and the unsorted category. All categories and population parents were grown at three South Dakota locations; Brookings and Dakota Lakes in 2010, 2011, and 2012, and Winner in 2011 and 2012. Plants in sorted categories in 2010, 2011, and 2012 represented plants in the F4, F5, and F6 generations, respectively. Both parents and sorted categories for each population were grown in three replications of a split-plot design, with populations as main plots and sorted categories as sub-plots. The frequency of white kernels in each sort category was determined after staining harvested kernel samples and visually classifying for kernel color. By the final F6 sort generation, the percent white kernels in the white sort had resulted in significantly more white colored kernels within each population and at each environment, and generally, this increase was significant from the original population to the F4 generation, from the F4 to F5 generation, and from the F5 to F6 kernel generation. Based on the white-sort category, the smallest total mean increase in white colored kernels from the initial F3 kernels to the final harvested F6 kernels was 43% for population 4 (P-4) at the Brookings environment. The largest total mean increase in white colored kernels from the initial population to the final harvested F6 kernels was 88.4% and 89.8% for population 6 (P-6) at the Dakota Lakes and Winner environments, respectively. The optical sorter was effective in separating for kernel color within all six segregating populations, and it is expected to be useful to breeders in helping them select among segregating populations for white-kernel color genotypes. Considering the environments in which these populations were grown, the sorter appeared to be more effective in separating within samples derived from western environments of South Dakota, which were generally drier. Perhaps the lack of weathering in western environments allows for expression of greater contrast between red and white kernels and for the optical sorter to more effectively distinguish between kernel color differences.
"],"dc:identifier":["https://openprairie.sdstate.edu/etd/1395"],"dc:language":["en"],"dc:rights":["In Copyright - Educational Use Permitted
http://rightsstatements.org/vocab/InC-EDU/1.0/