<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Yu R</submitter><funding>Guangdong Provincial Introduction of Innovative Research and Development Team</funding><funding>National Key R&amp;D Program of China</funding><funding>Key Technologies Research and Development Program of Anhui Province</funding><pagination>75</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12690036</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>5(1)</volume><pubmed_abstract>Repeated occurrences of extreme weather events, such as low temperatures, due to global warming present a serious risk to the safety of wheat production. Quantitative assessment of frost damage can facilitate the analysis of key genetic factors related to wheat tolerance to abiotic stress. We collected 491 wheat accessions and selected four image-based descriptors (BLUE band, RED band, NDVI, and GNDVI) to quantitatively assess their frost damage. Image descriptors can complement the visual estimation of frost damage. Combined with genome-wide association study (GWAS), a total of 107 quantitative trait loci (QTL) (r&lt;sup>2&lt;/sup> ranging from 0.75% to 9.48%) were identified, including the well-known frost-resistant locus Frost Resistance (FR)-A1/ Vernalization (VRN)-A1. Additionally, through </pubmed_abstract><journal>Stress biology</journal><pubmed_title>Genome-wide association mapping and candidate genes analysis of high-throughput image descriptors for wheat frost tolerance.</pubmed_title><pmcid>PMC12690036</pmcid><funding_grant_id>grant no. Ylzy-xm-01</funding_grant_id><funding_grant_id>2022-NK-125</funding_grant_id><funding_grant_id>No.2022YFE0116200</funding_grant_id><pubmed_authors>Wu J</pubmed_authors><pubmed_authors>Zeng Q</pubmed_authors><pubmed_authors>Su B</pubmed_authors><pubmed_authors>Yu R</pubmed_authors><pubmed_authors>Yuan M</pubmed_authors><pubmed_authors>Liu S</pubmed_authors><pubmed_authors>Kang Z</pubmed_authors><pubmed_authors>Zhao Y</pubmed_authors><pubmed_authors>Jiang P</pubmed_authors><pubmed_authors>Liu Y</pubmed_authors><pubmed_authors>Wang Q</pubmed_authors><pubmed_authors>Ou J</pubmed_authors><pubmed_authors>Dong H</pubmed_authors><pubmed_authors>Luo Y</pubmed_authors><pubmed_authors>Zhang C</pubmed_authors><pubmed_authors>Xu X</pubmed_authors><pubmed_authors>Wang Y</pubmed_authors><pubmed_authors>Zhao J</pubmed_authors><pubmed_authors>Han D</pubmed_authors><pubmed_authors>Chen T</pubmed_authors></additional><is_claimable>false</is_claimable><name>Genome-wide association mapping and candidate genes analysis of high-throughput image descriptors for wheat frost tolerance.</name><description>Repeated occurrences of extreme weather events, such as low temperatures, due to global warming present a serious risk to the safety of wheat production. Quantitative assessment of frost damage can facilitate the analysis of key genetic factors related to wheat tolerance to abiotic stress. We collected 491 wheat accessions and selected four image-based descriptors (BLUE band, RED band, NDVI, and GNDVI) to quantitatively assess their frost damage. Image descriptors can complement the visual estimation of frost damage. Combined with genome-wide association study (GWAS), a total of 107 quantitative trait loci (QTL) (r&lt;sup>2&lt;/sup> ranging from 0.75% to 9.48%) were identified, including the well-known frost-resistant locus Frost Resistance (FR)-A1/ Vernalization (VRN)-A1. Additionally, through </description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Dec</publication><modification>2026-07-15T11:46:59.704Z</modification><creation>2026-07-05T03:08:24.469Z</creation></dates><accession>S-EPMC12690036</accession><cross_references><pubmed>41366184</pubmed><doi>10.1007/s44154-025-00257-2</doi></cross_references></HashMap>