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Published in 2021 at "Agricultural and Forest Meteorology"
DOI: 10.1016/j.agrformet.2021.108548
Abstract: Abstract Estimating leaf wetness duration (LWD) is fundamentally important for crop disease monitoring and early warning. This study developed and evaluated a novel framework based on machine learning techniques with climate reanalysis data to estimate…
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Keywords:
machine;
model;
leaf wetness;
machine learning ... See more keywords
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Published in 2021 at "MethodsX"
DOI: 10.1016/j.mex.2021.101332
Abstract: Plant canopies are wet for substantial amounts of time and this influences physiological performance and fluxes of energy, carbon and water at the ecosystem level. Leaf wetness sensors enable us to quantify the duration of…
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Keywords:
wetness;
forest canopy;
profile;
leaf wetness ... See more keywords
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Published in 2021 at "IEEE Sensors Journal"
DOI: 10.1109/jsen.2021.3089722
Abstract: Early plant disease detection and providing the control measures have become highly desirable to improve crop yield. Leaf wetness duration (LWD) is one of the essential parameters related to the development of fungal disease on…
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Keywords:
plant disease;
leaf wetness;
lws;
sensor ... See more keywords
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Published in 2017 at "Summa Phytopathologica"
DOI: 10.1590/0100-5405/1890
Abstract: ABSTRACT Considering the lack of epidemiological studies on orange rust of sugarcane in Brazil and the importance of this crop in the Brazilian agribusiness, the aims of this study were to determine the influence of…
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Keywords:
wetness duration;
orange rust;
puccinia kuehnii;
leaf wetness ... See more keywords
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Published in 2020 at "International Journal of Agricultural and Biological Engineering"
DOI: 10.25165/ijabe.v13i3.4301
Abstract: Leaf wetness duration (LWD) is a critical parameter used to predict plant disease, but its determination under actual field conditions is a major challenge. In this study, a method for determining LWD using thermal infrared…
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Keywords:
wetness duration;
means clustering;
thermal infrared;
segmentation ... See more keywords