Predicting crop productivity using biophysical modeling of water dynamics

Overview

This research offers a novel mechanistic framework for predicting crop productivity by modeling the relationship between plant water dynamics and photosynthesis at the molecular level. The approach bridges a critical gap in current plant productivity models by connecting micro-scale water behavior within photosystem II (PSII) to whole-plant photosynthesis. By integrating first principles of energy partitioning at the PSII level, this work enables more accurate prediction of crop performance, particularly under water-limited conditions such as drought.

The solution has demonstrated strong correlation between simulated molecular water dynamics and in vivo plant measurements, with over 94% correlation (p<0.01) between MCCE-simulated pressure values and pressure chamber measurements on Brassica rapa under progressive drought. This level of mechanistic accuracy represents a significant advancement over empirical crop models.

Technical specifications

Core methodology:

• Multi Conformational Continuum Electrostatic (MCCE) simulations calculate changes in water binding within proteins as a function of water chemical potential
• Simulated step-release curves quantify water molecule behavior from PSII under varying pressure conditions
• A minimum pressure of approximately -10 MPa is required to remove water from a single PSII
• Integration with in vivo pressure chamber measurements across multiple drought steps

Key scientific findings supporting the model:

• PSII core (PSBY), light-harvesting complex (LHCB2.2), and regulation (ELIP1/2) genes show increased expression at different times of day
• Water is an integral part of photosystem structure and directly influences fluorescence behavior and energy partitioning
• The model has been validated across morphologically diverse species from fully watered to desiccated states

Future validation activities:

• Greenhouse experiments sampling leaf tissue from 10 rapa genotypes
• Expression profiling of 24 protein-coding genes linked to PSII using Nanostring technology
• In silico mutation of PSII proteins to modify water channels and quantify structural changes
• Assessment of hydrogen bond connection persistency around PSII

Technology readiness level

The technology is currently at an early-to-mid stage of development. Initial validation has been completed with strong results showing over 94% correlation between simulated and measured values across six drought steps with 12 replicates each. The research team is now planning a one-year greenhouse validation study to bridge microscopic PSII function with cellular peptide expression. Further development and field-scale validation would be needed before commercial deployment in agricultural applications. The approach holds promise for breeding programs, precision agriculture, and climate-resilient crop development.