Machine learning reveals complex genetics of fungal resistance in sorghum grain mold.

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Bibliographic Details
Title: Machine learning reveals complex genetics of fungal resistance in sorghum grain mold.
Authors: Ahn E; Sustainable Perennial Crops Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA. ezekiel.ahn@usda.gov., Prom LK; Insect Control and Cotton Disease Research, Agricultural Research Service, Southern Plains Agricultural Research Center, United States Department of Agriculture, College Station, TX, USA., Park S; Sustainable Perennial Crops Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA., Lee D; Soybean Genomics & Improvement Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA., Bhatt J; Sustainable Perennial Crops Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA., Ellur V; Molecular Plant Sciences, Washington State University, Pullman, WA, USA., Lim S; Sustainable Perennial Crops Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA., Jang JH; Sustainable Perennial Crops Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA., Lakshman D; Molecular Plant Pathology Laboratory, Agricultural Research Service, United States Department of Agriculture, Beltsville, MD, USA., Magill C; Department of Plant Pathology and Microbiology, Texas A&M University, College Station, TX, USA.
Source: Heredity [Heredity (Edinb)] 2025 Aug; Vol. 134 (8), pp. 485-499. Date of Electronic Publication: 2025 Jul 19.
Publication Type: Journal Article; Research Support, U.S. Gov't, Non-P.H.S.
Journal Info: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 0373007 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-2540 (Electronic) Linking ISSN: 0018067X NLM ISO Abbreviation: Heredity (Edinb) Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1365-2540
DOI:10.1038/s41437-025-00783-9