WheatSM V5.0: A Python-Based Wheat Growth and Development Simulation Model with Cloud Services Integration to Enhance Agricultural Applications

• Published in: Agronomy (Basel) Vol. 13; no. 9; p. 2411
• Main Authors: Chen, Xianguan, Bai, Huiqing, Xue, Qingyu, Zhao, Jin, Zhao, Chuang, Feng, Liping
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.09.2023
• Subjects: Accuracy; Agricultural industry; Agricultural production; agronomy; Algorithms; Biomass; Climate change; Cloud computing; Computer simulation; computer software; Computer-generated environments; crop model; Crop production; Decision making; Design optimization; Environmental assessment; Experiments; Flexibility; Food security; Global temperature changes; Growth; growth and development; Growth models; Irrigation; Language; Luminous intensity; Management decisions; Modularity; Moisture content; nitrate nitrogen; Nitrogen; Operating systems; Optimization techniques; Parameter sensitivity; Personal computers; Photosynthesis; Production management; Redesign; Sensitivity analysis; Simulation; Simulation models; Software development; Software packages; Soil moisture; Soil water; Soil water storage; water and nitrogen dynamics; Water storage; Wheat; Winter wheat; yield formation; China
• ISSN: 2073-4395; 2073-4395
• DOI: 10.3390/agronomy13092411

This project aims to improve the wheat growth and development simulation model (WheatSM) V4.0, a renowned wheat model, by addressing limitations in its structure and modules. The WheatSM V4.0 excelled numerically but lacked modularity, hindering maintenance, improvement, and secondary development. Therefore, the project undertook a software framework redesign, adopting a modular approach and implementing WheatSM V5.0 entirely in Python. Furthermore, the project conducted a sensitivity analysis of model parameters. Additionally, WheatSM V5.0 was seamlessly integrated into AgroStudio, an agricultural model system integration platform, enabling the provision of online cloud services. The Morris analysis indicated that photoperiod parameters significantly impacted the jointing and mature stages. Furthermore, biomass was highly sensitive to pmax (the maximum photosynthetic intensity at light saturation point), while yield was influenced by tr1 (the transfer rate of photosynthate to grain before heading). The simulated results demonstrated favorable performance in soil water storage, soil nitrate nitrogen content, winter wheat nitrogen accumulation, the development period, biomass, and yield. The NRMSE ranged from 1.2% to 15.1% for calibration and 1.0% to 18.7% for validation. The project successfully transformed WheatSM into a cloud-based service on AgroStudio, migrating from a PC-based application. Generally, this enhanced model exhibits potential for climate change assessment, wheat production optimization, and digital design.