Controlled environment phenotyping for process-based crop modeling and field performance prediction

Overview

This research addresses a critical gap in crop science: connecting high-throughput controlled environment plant trait measurements with real-world field performance. The approach hypothesizes that controlled environment measurements of moderate to high-heritability traits can parameterize process-based crop models capable of predicting how diverse genotypes perform under novel field conditions. By bridging laboratory phenomics with agronomic outcomes, this work enables more efficient crop breeding, genotype selection, and performance prediction across variable environments.

Technical specifications

Core methodology:

• Controlled environment phenotyping of diverse rice genotypes under multiple nitrogen treatments
• Collection of approximately 250 A-Ci curves measuring photosynthetic response to intercellular CO2 across three developmental timepoints
• Measurement of specific leaf nitrogen and high-throughput phenomics data from hyperspectral and RGB imagery captured three times per week
• Parameterization of process-based crop models using controlled environment trait data
• Simulation of field performance using weather and soil data from the Dale Bumpers National Rice Research Center in Stuttgart, Arkansas
• Genomic prediction methods for scaling model parameterization across genotypes

Key capabilities:

• Significant differentiation observed between rice subpopulations in preliminary data
• Integration of direct physiological measurements with indirect imaging-derived traits
• Modeling of genotype-by-environment interactions across controlled and field conditions

Technology readiness level

The research is at an advanced validation stage. Preliminary controlled environment experiments have been completed with 24 diverse rice genotypes, demonstrating significant differentiation between subpopulations. The next phase involves parameterizing process-based models for two important U.S. rice varieties using existing controlled environment data, then validating predictions through field trials measuring yield, biomass production, photosynthetic rates, leaf area index, and phenological traits at the Dale Bumpers National Rice Research Center. This work builds on prior validated approaches for genotype-specific process-based modeling of genotype-by-environment interactions.