Coupled maize model: A 4D maize growth model based on growing degree days

• Published in: Computers and electronics in agriculture Vol. 212; p. 108124
• Main Authors: Qian, Binxiang, Huang, Wenjiang, Xie, Donghui, Ye, Huichun, Guo, Anting, Pan, Yuhao, Jin, Yin, Xie, Qiaoyun, Jiao, Quanjun, Zhang, Biyao, Ruan, Chao, Xu, Tianjun, Zhang, Yong, Nie, Tiange
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2023
• Subjects: 4D maize growth model; Coupled maize model; Growing degree days (GDDs); Maize canopy parameters; Maize growth model; Remote sensing; Maize canopy parameters; 4D maize growth model; Growing degree days (GDDs); Maize growth model; Remote sensing; Coupled maize model
• ISSN: 0168-1699; 1872-7107
• DOI: 10.1016/j.compag.2023.108124

•Coupled maize model is a 4D maize growth model based on growing degree days.•Coupled maize model simulates and visualizes maize canopy on multiple levels.•Improved thermal-driven crop growth model and plant functional-structural algorithm.•Coupled maize model has high accuracy through multi-seasonal dataset validation. Crop canopy parameters are critical for environmental remote sensing, describing crop phenotypes, and ensuring food security. Evaluating the effect of temperature on crop growth is crucial for estimating crop canopy parameters. However, existing crop growth and plant functional-structural models cannot simultaneously model temperature responses, perform accurate dynamic simulations, and provide multi-scale computer visualizations. This limitation has hindered the application of structural models of maize plants for use in 3D radiative transfer models, crop structure evaluations, and crop phenotype descriptions. We improve the leaf/organ-level thermal-driven crop growth model (MAIZSIM) and the plant functional-structural algorithm. To address these limitations, we propose the coupled maize model, a four-dimensional (4D) growth model based on growing degree days. This model can simulate and visualize the structural parameters of the maize canopy at the organ, plant, seasonal, and population levels. The model outputs three-dimensional (3D) predictions of the maize structure (file format.obj), enabling editing and 3D visualizations. We use maize datasets from multiple phenological periods to test the proposed model’s accuracy and stability in simulating the canopy parameters at multiple levels. The results show that the normalized root mean square errors (NRMSEs) between the simulated and measured maize leaf size, area, leaf node height, and vein curve derived from the coupled maize model are below 0.1, demonstrating the model's high accuracy.