Victor Bloch, Taru Palosuo, Hanna Huitu, Ari Ronkainen, Juha Backman, Katariina Pussi, Antti Suokannas, Matti Pastel. Towards a digital twin for optimal field management.. 2022. agriXiv.2022.00165
DOI：10.31220/agriRxiv.2022.00165
声明：预印本系统所发表的论文仅用于最新科研成果的交流与共享，未经同行评议，因此不建议直接应用于指导生产实验。
Towards a digital twin for optimal field management.
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Abstract: Abstract Software for a real-time digital twin of crop production system was developed for supporting farming decisions. Software couples the APSIM crop simulation model with data from precision farming equipment, real-time on-field and remote sensing. A field managed according to precision farming practices and equipped with underground soil temperature and moisture sensors and local weather station was used as a test case. The software automatically initialized the simulation model based on ISOBUS time log data from sowing. The field was divided into unique zones with averaged parameters implemented in the simulation. Sensor data was continuously copied to Mongo database and the model was run daily to monitor the crop status. Yield maps obtained from combine harvester and leaf area index predicted from earth observation data were used to calibrate the simulation. Further development and fitting the system to the researchers and farmers needs will be done in the future study. The digital twin will offer researchers opportunities for real time management of crops and a tool for studying spatial variability of growing conditions within fields.
Key words: software; time; precision; researchers; digital twin; rea提交时间：2022-01-01
版权声明：作者本人独立拥有该论文的版权，预印本系统仅拥有论文的永久保存权利。任何人未经允许不得重复使用。 -
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