Beyond radiation use efficiency: A mechanistic biochemical photosynthesis model for crop growth simulation and agroecosystem modeling

Authors: HU, TONGXI - The Ohio State University; Zhang, Xuesong; KHANAI, SAMI - The Ohio State University; ZHAO, KAIGUANG - The Ohio State University

Submitted to: Computers and Electronics in Agriculture
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 2/24/2025
Publication Date: 3/5/2025
Citation: Hu, T., Zhang, X., Khanai, S., Zhao, K. 2025. Beyond radiation use efficiency: A mechanistic biochemical photosynthesis model for crop growth simulation and agroecosystem modeling. Computers and Electronics in Agriculture. 233. https://doi.org/10.1016/j.compag.2025.110199.
DOI: https://doi.org/10.1016/j.compag.2025.110199

Interpretive Summary: Agroecosystem models often use a simple relationship between radiation and biomass accumulation (or radiation use efficiency - RUE) to estimate crop productivity. The RUE method does not explicitly represent mechanisms underlying the impact of climate change (e.g., extreme temperatures and rises in CO2 concentrations), limiting its application to reliably project future crop yields. Here, we developed a mechanistic Radiative-transfer and Photosynthesis (RP) Model, which explicitly represents the radiation transfer and photosynthesis processes in the crop canopy as influenced by climate variables. Our comparison showed that the RP method outperformed the RUE method at multiple flux tower sites and achieved comparable results in two additional experimental sites. We also showed the RP method can more credibly estimate the CO2 fertilization effects on crop yields. We anticipate the RP method will be a more reliable tool to support sustainable agroecosystem development under climate change.

Technical Abstract: The radiation use efficiency (RUE) method is widely used for simulating crop growth in popular process-based agroecosystem models. However, the simplicity of the RUE method (i.e., based on empirical relationships between biomass accrue and absorbed radiation) facilitates its use in modeling crop growth, it also limits our understanding of how climate forcings affect crop growth. Here, we developed a mechanistic crop growth model (named RP hereafter) combining two key processes for crop growth -- radiative transfer and photosynthesis as an alternative to the RUE method for simulating crop growth. We compared the capabilities of these two methods in characterizing climatic impacts and predicting potential biomass. We found that the RP method (R2 =0.85, RMSE= 10.66) could better simulate crop biomass than the RUE method (R2=0.67, RMSE= 15.70) at flux tower sites. We also incorporated the RP module into the Environmental Policy Integrated Climate (EPIC) model and found that the RP and RUE methods are comparable in predicting long-term crop yields at two additional experimental sites. Furthermore, the RP method more reasonably predicted responses of biomass accumulation to changes in climate factors than the RUE method. In total, the open-source RP model is promising to help understand the responses of crop growth to future climate conditions, thereby supporting sustainable designs of future agricultural landscapes under climate change.