Analyzing Medicago spp. seed morphology using GWAS and machine learning.
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| Title: | Analyzing Medicago spp. seed morphology using GWAS and machine learning. |
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| Authors: | Botkin J; Department of Plant Pathology, University of Minnesota, St. Paul, MN, 55108, USA., Medina C; Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA., Park S; Sustainable Perennial Crops Laboratory, United States Department of Agriculture- Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, MD, 20705, USA., Poudel K; Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA., Cha M; Department of Biotechnology, Korea University, Seoul, 02841, Republic of Korea., Lee Y; Department of Plant Pathology, University of Minnesota, St. Paul, MN, 55108, USA., Prom LK; United States Department of Agriculture- Agricultural Research Service, Southern Plains Agricultural Research Center, 2765 F & B Road, College Station, TX, 77845, USA., Curtin SJ; Department of Agronomy and Plant Genetics, University of Minnesota, St. Paul, MN, 55108, USA.; Plant Science Research Unit, United States Department of Agriculture- Agricultural Research Service, St. Paul, MN, 55108, USA.; Center for Plant Precision Genomics, University of Minnesota, St. Paul, MN, 55108, USA.; Center for Genome Engineering, University of Minnesota, St. Paul, MN, 55108, USA., Xu Z; Plant Science Research Unit, United States Department of Agriculture- Agricultural Research Service, St. Paul, MN, 55108, USA. Zhanyou.Xu@usda.gov., Ahn E; Sustainable Perennial Crops Laboratory, United States Department of Agriculture- Agricultural Research Service, Beltsville Agricultural Research Center, Beltsville, MD, 20705, USA. Ezekiel.Ahn@usda.gov. |
| Source: | Scientific reports [Sci Rep] 2024 Jul 30; Vol. 14 (1), pp. 17588. Date of Electronic Publication: 2024 Jul 30. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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