UK-China Agritech Challenge: CropDoc - Precision Crop Disease Management for Farm Productivity and Food Security
UK-China Agritech Challenge: CropDoc - Precision Crop Disease Management for Farm Productivity and Food Security
批准号:
BB/S020969/1
负责人:
Liangxiu Han
金额:
$57.24万
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
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英文摘要
CropDoc seeks to exploit existing research on Potato disease identification and outbreak management in the domain of precision agriculture, agriculture digitisation & decision management support. It will harness cutting-edge technologies (i.e. IoT, mobile devices, crowd sourced data, big data analytics and cloud computing). It will build a decision support system that generates insight from multiple data collected from remote sensing above the fields and IoT ground sensing within the fields for monitoring & prediction of disease in real time. CropDoc will base its data service and analytics platform on open standards and will allow interoperability through open APIs. This will ensure an end-platform ecosystem can emerge that consumes the data & analytics service, allowing farmers to use their platform of choice, while allowing central authorities to identify and manage sector outbreaks. The initial focus will be on potato late blight disease, one of the most devastating crop diseases in China. In a typical blight pressure season crop protection chemicals cost the industry an estimated $10-20bn per annum. Late blight has been referred to as a 'community disease', due to its ability to spread rapidly from field to field under the right weather conditions. Asexual spores travel easily on the wind when the weather is cool and moist, and can rapidly infect neighbouring fields. As such, understanding the symptoms of the disease and what to do when it is detected are essential to preventing an outbreak from rapidly turning into an epidemic.
期刊论文(10)
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DOI:
10.1109/tgrs.2021.3058782
发表时间:
2021-02
期刊:
IEEE Transactions on Geoscience and Remote Sensing
影响因子:
8.2
作者:
[Yue Shi;Liangxiu Han;Wenjiang Huang;Sheng Chang;Yingying Dong;D. Dancey;Lianghao Han]
通讯作者:
Yue Shi;Liangxiu Han;Wenjiang Huang;Sheng Chang;Yingying Dong;D. Dancey;Lianghao Han
DOI:
10.3390/rs14020396
发表时间:
2022-01
期刊:
Remote. Sens.
影响因子:
--
作者:
[Yue Shi;Liangxiu Han;Anthony Kleerekoper;Sheng Chang;Tongle Hu]
通讯作者:
Yue Shi;Liangxiu Han;Anthony Kleerekoper;Sheng Chang;Tongle Hu
DOI:
10.3390/rs11131554
发表时间:
2019-06
期刊:
Remote. Sens.
影响因子:
--
作者:
[Xin Zhang;Liangxiu Han;Yingying Dong;Yue Shi;Wenjiang Huang;Lianghao Han;P. González-Moreno;]
通讯作者:
Xin Zhang;Liangxiu Han;Yingying Dong;Yue Shi;Wenjiang Huang;Lianghao Han;P. González-Moreno;
A Fast Fourier Convolutional Deep Neural Network For Accurate and Explainable Discrimination Of Wheat Yellow Rust And Nitrogen Deficiency From Sentinel-2 Time-Series Data
快速傅立叶卷积深度神经网络,用于根据 Sentinel-2 时间序列数据准确且可解释地判别小麦黄锈病和氮缺乏症
DOI:
10.48550/arxiv.2306.17207
发表时间:
2023
期刊:
影响因子:
--
作者:
[Shi Y]
通讯作者:
Shi Y
DOI:
10.1109/tgrs.2022.3193441
发表时间:
2022-01-01
期刊:
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
影响因子:
8.2
作者:
[Shi, Yue, Han, Liangxiu, Dancey, Darren]
通讯作者:
Dancey, Darren
共 6 条
Synergising Process-Based and Machine Learning Models for Accurate and Explainable Crop Yield Prediction along with Environmental Impact Assessment
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批准号:BB/Y513763/1
-
项目类别:Research Grant
-
资助金额:$31.02万
-
财政年份:2024
-
负责人:Liangxiu Han
-
依托单位:
EYE-SCREEN-4-DPN: Development of an innovative Intelligent EYE imaging solution for SCREENing of Diabetic Peripheral Neuropathy
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负责人:Liangxiu Han
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依托单位:
EPIC: An automated diagnostic tool for Potato Late Blight disease detection from images
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批准号:BB/R019983/1
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项目类别:Research Grant
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资助金额:$8.23万
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负责人:Liangxiu Han
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财政年份:2012
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负责人:Liangxiu Han
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依托单位:
国内基金
海外基金
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