Research Assistant University of Illinois Urbana-Champaign Urbana, Illinois
Body of Abstract: Efficient allocation of photo-assimilated carbon resources to the reproductive organs is crucial for crop yield improvements. However, current crop models use partitioning models to prescribe how carbon is allocated across different development stages, relying primarily on empirical partitioning tables or harvest indices, while disregarding essential mechanisms such as utilization and translocation. This compromises their predictive capabilities under varying conditions that the models were not trained on. In this study, we incorporated Thornley's transport-resistance utilization model with the Soybean-BioCro crop model, extending the utilization model to encompass the entire lifespan of soybeans including the reproductive stages and senescence. We calibrated this new version of Soybean-BioCro following the same approach as the original Soybean-BioCro, which uses a carbon partitioning model, using biomass data collected from soybean grown at the ambient [CO2] levels at the SoyFACE facility in Urbana, IL in 2002 and 2005. We compared the two versions of Soybean-BioCro using biomass and yield data collected from plants grown in ambient and elevated [CO2] environments in 2002 and 2004-2006. We also compared the performance of the two models when predicting soybean biomass and yield for two additional soybean cultivars that were grown in 2021 and 2022. For these two new cultivars, the photosynthetic parameters were updated for both models based on experimental measurements, but the parameters relevant to the carbon allocation models were kept the same. Preliminary results demonstrate that incorporating a utilization-based carbon allocation model with the Soybean-BioCro crop model performed as well as or better than the original Soybean-BioCro. Future work will include a broader range of conditions to further evaluate model performance. We expect that by incorporating a more physiologically-based allocation model we will be able to improve our ability to identify and evaluate crop improvement strategies that improve yields and enhance adaptation to evolving climates.