Improving the Performance of Vegetable Leaf Wetness Duration Models in Greenhouses Using Decision Tree Learning

Improving the Performance of Vegetable Leaf Wetness Duration Models in Greenhouses Using Decision Tree Learning

Leaf wetness duration (LWD) is a key driving variable for peat and disease control in greenhouse management, and depends upon irrigation, rainfall, and dewfall. However, LWD measurement is often replaced by its estimation from other meteorological variables, with associated uncertainty due to the mo...

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Detaylı Bibliyografya
Asıl Yazarlar: Wang, Hui, Sánchez Molina, Jorge Antonio, Li, Ming, Rodríguez Díaz, Francisco
Materyal Türü: info:eu-repo/semantics/article
Dil:English
Baskı/Yayın Bilgisi: MDPI 2020
Konular:
leaf wetness threshold
data classification
data mining technology
dew temperature
Online Erişim:http://hdl.handle.net/10835/7543

Internet

http://hdl.handle.net/10835/7543

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