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USING MACHINE LEARNING-BASED SEED HARVEST MOISTURE PREDICTIONS TO IMPROVE A COMPUTER-ASSISTED AGRICULTURAL FARM OPERATION
专利权人:
THE CLIMATE CORPORATION
发明人:
Shilpa Sood,Matthew Sorge,Nikisha Shah,Timothy Reich,Herbert Ssegane,Jason Kendrick Bull,Tonya S. Ehlmann,Morrison Jacobs,Susan Andrea Macisaac,Bruce J. Schnicker,Yao Xie,Allan Trapp,Xiao Yang
申请号:
US16661860
公开号:
US20200134485A1
申请日:
2019.10.23
申请国别(地区):
US
年份:
2020
代理人:
摘要:
Embodiments generate digital plans for agricultural fields. In an embodiment, a model receives digital inputs including stress risk data, product maturity data, field location data, planting date data, and/or harvest date data. The model mathematically correlates sets of digital inputs with threshold data associated with the stress risk data. The model is used to generate stress risk prediction data for a set of product maturity and field location combinations. In a digital plan, product maturity data or planting date data or harvest date data or field location data can be adjusted based on the stress risk prediction data. A digital plan can be transmitted to a field manager computing device. An agricultural apparatus can be moved in response to a digital plan.
来源网站:
中国工程科技知识中心
来源网址:
http://www.ckcest.cn/home/

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