Molecular-physiological model integration revolutionizes cereal flowering prediction.

Abstract

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.

Plant phenotyping relevance

主茎葉数に基づく新規フェノタイピング手法とCAMPモデルを開発し、多様なコムギ品種・環境で開花期予測を検証している。表現型取得の効率化が中心的貢献である。

Code and data availability

The paper's Data availability statement explicitly provides public repositories containing the CAMP model source code and analysis scripts used for the phenotyping data analysis and flowering-time prediction: the APSIM Next Generation framework repository, the standalone Python CAMP model and analysis scripts, and theC