**AWARDS ISSUED PRIOR TO JANUARY 20, 2025, WERE FUNDED UNDER PREVIOUS ADMINISTRATIONS AND MAY NOT REFLECT THE PRIORITIES AND POLICIES OF THE CURRENT ADMINISTRATION.** THE PROJECT WILL DEVELOP SYSTEMS FOR PATHOGEN CLASSIFICATION AND THE PREDICTION OF DISEASE RESISTANCE IN PLANT BREEDING POPULATIONS. A SEQUENCING BASED APPROACH WILL BE DEVELOPED FOR PATHOGEN CLASSIFICATION AND IDENTIFICATION. PROBES TARGETING GENES THAT HAVE TRADITIONALLY BEEN USED FOR DIAGNOSTICS, HIGHLY CONSERVED LOCI AND GENES ASSOCIATED WITH PATHOGENICITY WILL BE DESIGNED AND BIOINFORMATICALLY VALIDATED USING EXISTING GENOMES. THE ACCURACY AND UNIVERSALITY OF THE PATHOGEN CLASSIFICATION MODELS WILL THEN BE QUANTIFIED USING SAMPLES FROM THE USDA FUNGAL COLLECTION AND THE NATIONAL PLANT DIAGNOSTIC NETWORK (NPDN). THE SYSTEM WILL BE EVALUATED BY THE UF NPDN LABORATORY FOR IN-PLANTA PATHOGEN IDENTIFICATION. PRACTICAL LABORATORIES WILL BE DELIVERED FOR BACTERIAL, FUNGAL AND VIRAL IDENTIFICATION AND A COURSE ON MOLECULAR IDENTIFICATION OF PATHOGENS WILL BE DEVELOPED. GERMPLASM FROM PINE AND MAIZE BREEDING PROGRAMS WILL BE SCREENED FOR TOLERANCE TO INFECTION BY FUSARIUM PATHOGENS. CONTROLLED INOCULATION AND ASSESSMENT OF CLONALLY REPLICATED PINE POPULATIONS AND MAIZE VARIETIES WILL PROVIDE PHENOTYPE THAT WILL BE PAIRED WITH GENOTYPE DATA TO CREATE GENOMIC PREDICTION MODELS FOR FUSARIUM TOLERANCE. STANDARD GENOMIC PREDICTION MODELS WILL BE COMPARED WITH ALTERNATIVE MODELS TO EVALUATE THE ACCURACY OF PREDICTIONS.