Systematic synthesis of process-based vegetable crop modeling frameworks and implementations

Vegetable crops are indispensable for global nutritional security, yet their production requires unique physiological complexities and intensive management requirements that necessitate robust predictive modeling. This systematic synthesis analyzes the development of 59 process-based models across 25 species from 1990 to 2023. A distinct structural divergence between cultivation systems characterizes the evolution from static empirical equations to dynamic mechanistic frameworks. Greenhouse models, such as TOMGRO, have advanced by coupling canopy photosynthesis with microclimate energy balances and employing source–sink dynamics to simulate indeterminate growth. Conversely, field-based approaches like AquaCrop typically utilize radiation use efficiency and capacity-based water modules to prioritize resource sustainability and yield gaps. Consequently, application patterns are: usage is heavily concentrated on optimizing environmental control for fruit vegetables (primarily tomato) in Europe and China, while focusing on water productivity for legumes in arid regions. Despite this progress, current models lack transferability due to narrow parameterization—often restricted to tomato—and a structural inability to simulate the synergistic effects of combined abiotic stresses effectively. Future research should address these limitations by linking physiological processes with quality trait formation and integrating models with remote sensing data for real-time precision management.