Modeling riceleaf area index and canopy height in the US Mid-South region

Authors: KUHN, ELLIE - University Of Arkansas; MORENO-GARCIA, BEATRIZ - University Of Arkansas; Reba, Michele; NAITHANI, KUSUM - University Of Arkansas; RUNKLE, BENJAMIN - University Of Arkansas

Submitted to: Agrosystems, Geosciences & Environment
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 4/23/2025
Publication Date: 5/26/2025
Citation: Kuhn, E., Moreno-Garcia, B., Reba, M.L., Naithani, K., Runkle, B. 2025. Modeling riceleaf area index and canopy height in the US Mid-South region. Agrosystems, Geosciences & Environment. 8(2). https://doi.org/10.1002/agg2.70139.
DOI: https://doi.org/10.1002/agg2.70139

Interpretive Summary: There has been limited research for crop growth models for rice cultivars in the US Mid-South, which is the region that produces the most rice within the United States. We created and assessed empirical models using 30 field-seasons of observational data to predict key model inputs of leaf area index (LAI) and canopy height (Hcan) for numerous rice cultivars grown under different conditions in east-central Arkansas. Our results determined that a peaked response to accumulated growing degree day (GDD) is a better functional form than one utilizing days after planting and that cultivar-agnostic models perform equivalently to cultivar-specific models. These models will assist farmers, crop scientists, and policymakers improve crop predictions and farming decisions in the US Mid-South using simple, temperature-based models.

Technical Abstract: Crop growth modeling plays a critical role in addressing global challenges of food scarcity, carbon cycling, and water management. By simulating crop development and environmental factors, these models inform policy and investment decisions. However, for the US Mid-South, there is a lack of comprehensive datasets specific to rice cultivars and growing conditions of the area. Here, we develop and evaluate empirical models using 30 field-seasons of observational data to predict key model inputs of leaf area index (LAI) and canopy height (Hcan) for numerous rice cultivars grown under different conditions in east-central Arkansas. Our results show that a peaked response to accumulated growing degree day (GDD) (LAI: R2 = 0.83, RMSE = 0.97 m2m-2; Hcan: R2 = 0.90, RMSE = 10.9 cm) is a better functional form than one utilizing days after planting (LAI: R2 = 0.73, RMSE = 1.22 m2m-2; Hcan: R2 = 0.83, RMSE = 14.5 cm). Additionally, predictions from a cultivar-agnostic model are comparable to the predictions from cultivar-specific models, suggesting that the broader cultivar-agnostic model is sufficient and can be widely applied to rice production systems in this region.