Prediction of daily leaf wetness duration using multi-step machine learning
Accurately predicting leaf wetness duration (LWD) is vital for effective plant disease
management outbreaks and timely warnings. This study introduces an innovative approach …
management outbreaks and timely warnings. This study introduces an innovative approach …
Spatial variability of leaf wetness under different soil water conditions in rainfed jujube (Ziziphus jujuba Mill.) in the loess hilly region, China
Z Gao, X Wang - Journal of Arid Land, 2022 - Springer
Leaf wetness provides a wide range of benefits not only to leaves, but also to ecosystems
and communities. It regulates canopy eco-hydrological processes and drives spatial …
and communities. It regulates canopy eco-hydrological processes and drives spatial …
Machine Learning Based Soft Sensing Tool for the Prediction of Leaf Wetness Duration in Precision Agriculture
Leaf wetness often emerges as the result of the exchange of atmospheric water-soluble
gases between the Earth surface and the atmosphere. The importance of this feature resides …
gases between the Earth surface and the atmosphere. The importance of this feature resides …
Approaches for the Prediction of Leaf Wetness Duration with Machine Learning
M Solís, V Rojas-Herrera - Biomimetics, 2021 - mdpi.com
The prediction of leaf wetness duration (LWD) is an issue of interest for disease prevention
in coffee plantations, forests, and other crops. This study analyzed different LWD prediction …
in coffee plantations, forests, and other crops. This study analyzed different LWD prediction …
Estimation model of cucumber leaf wetness duration considering the spatial heterogeneity of solar greenhouse
LIU Jian, REN Aixin, LIU Ran, JI Tao, LIU Huiying… - Smart …, 2020 - smartag.net.cn
Leaf wetness duration (LWD) is one of the important input variables of plant disease model,
which is related to the infection of many leaf pathogens and affects the pathogen infection …
which is related to the infection of many leaf pathogens and affects the pathogen infection …
Development of a wireless communication system for monitoring crop condition with leaf wetness sensor
Wireless sensor networks play an essential role in smart agriculture, especially on the future
farms without farmers. Â This paper presents a new wireless communication system (WCS) …
farms without farmers. Â This paper presents a new wireless communication system (WCS) …
考虑日光温室空间异质性的黄瓜叶片湿润时间估算模型研究
刘鉴， 任爱新， 刘冉， 纪涛， 刘慧英， 李明 - 智慧农业, 2020 - smartag.net.cn
叶片湿润时间(LWD) 是植物病害模型的重要输入变量之一, 它与许多叶部病原菌的侵染有关,
影响病原侵染和发育速率. 为了准确地预测日光温室黄瓜病害的发生时间和方位, 本研究于2019 …
影响病原侵染和发育速率. 为了准确地预测日光温室黄瓜病害的发生时间和方位, 本研究于2019 …