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

文献类型： 外文期刊

第一作者： Chen, Xianguan

作者： Chen, Xianguan;Chen, Xianguan;Zhao, Jin;Zhao, Chuang;Feng, Liping;Bai, Huiqing;Xue, Qingyu

作者机构：

关键词： crop model; sensitivity analysis; growth and development; yield formation; water and nitrogen dynamics

期刊名称：AGRONOMY-BASEL （ 影响因子：3.7； 五年影响因子：4.0 ）

ISSN：

年卷期： 2023 年 13 卷 9 期

页码：

收录情况： SCI

摘要： 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.

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