Dynamical climatic model for time to flowering in Vigna radiata

Area of Science:

• Plant science
• Agricultural science
• Computational biology

Background:

• Phenology data from ~300 mungbean (Vigna radiata) accessions offer insights into climate impacts on plant development.
• Understanding plant phenology is crucial for predicting crop responses to environmental changes.

Purpose of the Study:

• To develop a mathematical model predicting mungbean flowering time.
• To identify key climatic and genetic factors influencing mungbean phenology.
• To forecast flowering times under future climate scenarios.

Main Methods:

• Developed a dynamic mathematical model incorporating temperature, precipitation, day length, and solar radiation.
• Calibrated model parameters using experimental phenology data.
• Validated the model using cross-validation techniques.

Main Results:

• The model accurately describes the dynamic control of flowering time by environmental variables.
• Maximal temperature was identified as the most critical local environmental factor.
• Plant geographic origin and genotype significantly predict phenological traits like flowering time.

Conclusions:

• The developed model provides a robust tool for understanding and predicting mungbean phenology.
• Maximal temperature is a primary driver of flowering time in mungbean.
• Forecasts indicate potential shifts in flowering times for Taiwanese mungbean crops (2020-2030).