Molecular-physiological model integration revolutionizes cereal flowering prediction

Bibliographische Detailangaben
Veröffentlicht in:	The New phytologist. - 1979. - (2025) vom: 18. Okt.
1. Verfasser:	Wang, Enli (VerfasserIn)
Weitere Verfasser:	Brown, Hamish, Zheng, Bangyou, Zhao, Zhigan, Huth, Neil, Hunt, James R, Hyles, Jessica, Bloomfield, Maxwell, Celestina, Corinne, Porker, Kenton, Harris, Felicity, Biddulph, Ben, Stefanova, Katia, Trevaskis, Ben
Format:	Online-Aufsatz
Sprache:	English
Veröffentlicht:	2025
Zugriff auf das übergeordnete Werk:	The New phytologist
Schlagworte:	Journal Article flowering time gene expression molecular–physiological model phenological development phenotyping photoperiod vernalization wheat

Beschreibung
Zusammenfassung:	© 2025 The Author(s). New Phytologist © 2025 New Phytologist Foundation. Rapid prediction and control of flowering time is essential for breeding crops resilient to changing climates. Current models often fail to predict flowering time in new cultivars because molecular models lack integration of environmental signals, while physiological models inadequately capture the interactions of vernalization, photoperiod and temperature. This leads to mischaracterized genotypes and inaccurate forecasts. A new Cereal Anthesis Molecular Phenology (CAMP) model was developed for wheat. It explicitly integrates the regulatory roles of three major 'virtual' flowering genes (Vrn1, Vrn2, and Vrn3) with environmental cues. A novel phenotyping strategy based on main stem leaf number was introduced to shorten the time required for data collection and model calibration. CAMP predicted flowering time within 4-7 d across 64 genetically diverse wheat cultivars grown under contrasting environments. The leaf-number phenotyping method reduced phenotyping time by more than 80%, offering a practical alternative to resource-intensive field trials. Together, these advances enable accurate cultivar characterization and scalable prediction of flowering behaviour. CAMP enables the ability to predict flowering time directly from genotypic data (e.g. SNPs), eliminating the need for costly controlled-environment experiments. This represents a step change in molecular-physiological modelling, supporting faster deployment of new cultivars and more effective design of wheat for future climates
Beschreibung:	Date Revised 18.10.2025 published: Print-Electronic Citation Status Publisher
ISSN:	1469-8137
DOI:	10.1111/nph.70651