A process-based mechanistic modeling framework for soil–plant zinc dynamics and rice zinc biofortification

Zinc (Zn) deficiency remains a major challenge for both crop productivity and human nutrition, and rice is a key target for Zn biofortification. To support mechanism-based Zn management, this study developed a coupled Rice Zinc Dynamics Model (RZDM) by integrating WOFOST, HYDRUS-1D, and a Zn translocation-remobilization module, with field experiments used for model calibration and evaluation. Field data were collected from 17 plots representing unique variety-fertilizer-method combinations rather than independent experimental replicates, testing three rice varieties (Huanghuazhan, 99-25, and Nanjing-9108) and three zinc fertilizers (ZnSO 4 ⋅ H 2 O, Zn-EDTA, and zinc sugar alcohol chelate (Zn-SA)) under two application methods (soil and foliar). Field evidence indicated that foliar Zn application outperformed soil application for grain Zn enrichment, with Zn-SA and ZnSO 4 ⋅ H 2 O generally showing higher effectiveness than Zn-EDTA. RZDM achieved satisfactory performance for crop growth indicators ( R 2 = 0.45–0.96) and crop Zn content ( R 2 = 0.57–0.96), though soil Zn concentrations showed limited predictive accuracy( R 2 = −0.87), indicating its utility for quantifying Zn transport and allocation across the soil–plant–grain continuum. Under the conditions of this study, scenario simulations suggested that weekly foliar ZnSO 4 ⋅ H 2 O or Zn-SA application starting one week after flowering showed potential to improve grain Zn concentration, while requiring further validation across broader environments. This work provides a process-based modeling framework for hypothesis-driven design of rice Zn biofortification strategies.