Requirements and challenges of process-based modeling for intermediate wheatgrass, a perennial cereal

Intermediate wheatgrass (IWG) is a perennial cereal suitable for climate-resilient cropping systems. Given the brief selection history, however, process-based models for IWG, and for perennial cereals generally, remain scarce. This scarcity currently prevents the projection of the crop’s performance across diverse environments and management regimes. To support the development of robust IWG models, this semi-systematic review evaluates 43 peer-reviewed articles. The analysis identifies the state of the art and critical knowledge gaps across four simulation blocks: (i) phenology, (ii) resource acquisition, (iii) biomass allocation, and (iv) management impacts. These identified gaps are categorized as either structure-limited or calibration-limited, which dictates distinct future research priorities: structure-limited gaps require the updates of existing model subroutines in annual crop, even perennial forage models, whereas calibration-limited gaps require mostly the re-evaluation and a better assessment of uncertainties of existing model parameters. Among these gaps, this review emphasizes in particular the improvement of biomass allocation modules for simulating IWG. Consequently, the review proposes a conceptual sink-source dynamic profile. This profile describes the demand and supply activities of both aboveground vegetative and reproductive organs, alongside storage organs and roots, as they evolve across five recurring phases in the perennial cycle. By highlighting the sink-source dynamics subject to high or extreme uncertainty, this conceptual framework directs future research toward resolving these specific uncertain biological processes. Finally, the review outlines how state-updating data assimilation can advance model development by mitigating over-parameterization. To resolve empirical bottlenecks unique to perennial systems, a high-frequency, non-destructive digital twinning framework was proposed, ultimately accelerating the model-improvement cycle not only for IWG, but also for other emerging perennial cereals.