Daily reference evapotranspiration prediction of Tieguanyin tea plants based on mathematical morphology clustering and improved generalized regression neural network-Reference-Cited by-同舟云学术

Daily reference evapotranspiration prediction of Tieguanyin tea plants based on mathematical morphology clustering and improved generalized regression neural network

Published:2020-06 Issue: Volume:236 Page:106177
ISSN:0378-3774
Container-title:Agricultural Water Management
language:en
Short-container-title:Agricultural Water Management

Author:

Ruiming Fang,Shijie Song

Funder

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province China

Publisher

Elsevier BV

Subject

Earth-Surface Processes,Soil Science,Water Science and Technology,Agronomy and Crop Science

Reference37 articles.

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2. Daily reference evapotranspiration estimates by artificial neural networks technique and empirical equations using limited input climate variables;Antonopoulos;Comput. Electron. Agric.,2017

3. Mathematical Morphology;Bloch,2007

4. Field water management to save water and increase its productivity in irrigated lowland rice;Bouman;Agric. Water Manage.,2001

5. Photosynthesis, yield, and chemical composition of Tieguanyin tea plants (camellia sinensis (l.) o. kuntze) in response to irrigation treatments;Chen;Agric. Water Manage.,2010

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