{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Wang H"],"funding":["Cornell University School of Integrative Plant Science","USDA-NIFA Agriculture and Food Research Initiative","New York Wine and Grape Foundation"],"pagination":["baaf055"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12475903"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["2025"],"pubmed_abstract":["Cold hardiness is a crucial physiological parameter that determines the survival of grapevines during the dormant season. Accurate modelling and large-scale prediction of grapevine cold hardiness are essential for assessing the potential geographic distribution of grapevine cultivation, quantifying the impact of climate change on grapevine habitats, and ensuring the sustainability of the grape and wine industries worldwide in the regions characterized by cool or cold dormant seasons. However, until now, no comprehensive database has been available. In this research, we combined advanced automated machine learning techniques with extensive historical and current weather data to create an integrative database for grapevine cold hardiness: VineColD (https://cornell-tree-fruit-physiology.shiny"],"journal":["Database : the journal of biological databases and curation"],"pubmed_title":["VineColD: an integrative database for global historical tracing and real-time monitoring of grapevine cold hardiness."],"pmcid":["PMC12475903"],"funding_grant_id":["2023-68008-39274"],"pubmed_authors":["Londo JP","Wang H"],"additional_accession":[]},"is_claimable":false,"name":"VineColD: an integrative database for global historical tracing and real-time monitoring of grapevine cold hardiness.","description":"Cold hardiness is a crucial physiological parameter that determines the survival of grapevines during the dormant season. Accurate modelling and large-scale prediction of grapevine cold hardiness are essential for assessing the potential geographic distribution of grapevine cultivation, quantifying the impact of climate change on grapevine habitats, and ensuring the sustainability of the grape and wine industries worldwide in the regions characterized by cool or cold dormant seasons. However, until now, no comprehensive database has been available. In this research, we combined advanced automated machine learning techniques with extensive historical and current weather data to create an integrative database for grapevine cold hardiness: VineColD (https://cornell-tree-fruit-physiology.shiny","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jan","modification":"2026-06-03T23:17:51.552Z","creation":"2026-05-03T03:10:16.101Z"},"accession":"S-EPMC12475903","cross_references":{"pubmed":["41014096"],"doi":["10.1093/database/baaf055"]}}