Full TGIF Record # 333437
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Web URL(s):https://scisoc.confex.com/scisoc/2023am/meetingapp.cgi/Paper/152832
    Last checked: 12/01/2023
Publication Type:
Content Type:Abstract or Summary only
Author(s):Bushman, Shaun B.; Robbins, Matthew D.
Author Affiliation:Bushman: Presenting Author and USDA-ARS, Logan, UT; Robbins: Forage and Range Research Lab, USDA ARS, Logan, UT
Title:Genotyping improvements for turfgrasses
Section:Turfgrass physiology, molecular biology, breeding, genetic and microbiome poster (includes student competition)
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C05 turfgrass science
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Meeting Info.:St. Louis, Missouri: October 29-November 1, 2023
Source:ASA, CSSA, SSSA International Annual Meeting. 2023, p. 152832.
Publishing Information:[Madison, Wisconsin]: [American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America]
# of Pages:1
Abstract/Contents:"Since turfgrasses can be difficult to distinguish when not flowering, especially under varying management regimes, identification and characterization with molecular markers is increasingly useful. In particular, genotyping can identify unknown varieties, contaminates, top performers in blends under specific conditions, hybrids or offtypes for grasses with unique breeding systems, and uniform breeding lines. Genotyping methods previously relied on SSR or other marker systems that were laborious, costly, and time-consuming. High throughput genotyping has more recently developed into robust genotyping processes that are accompanied by various pipelines for downstream data analyses. In this study, we utilized an efficient high-throughput genotyping method for three research experiments: discerning among bermudagrass cultivars, identifying Kentucky bluegrass hybrids, and characterizing relationships of K31 sources of tall fescue. Our results show that stringency parameters for calling molecular marker locations and genotypes affect uniformity results much more than cultivar relationship results. Also, using PCA, clustering, or STRUCTURE methods to group cultivars provides different statistical confidences. Our results highlight the utility of next-generation genotyping, and provide information about which analysis methods are most appropriate for addressing cultivar identification."
Note:This item is an abstract only!
ASA/CSSA/SSSA Citation (Crop Science-Like - may be incomplete):
Bushman, S. B., and M. D. Robbins. 2023. Genotyping improvements for turfgrasses. Agron. Abr. p. 152832.
Fastlink to access this record outside TGIF: https://tic.msu.edu/tgif/flink?recno=333437
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    Last checked: 12/01/2023
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