A Nonparametric Control Chart for Dynamic Disease Risk Monitoring

Wetness duration measured by flat plate sensors inside and outside a grape canopy was recorded from DecemberMarch Sensors outside the canopy generally recorded longer wetness duration than sensors inside the canopy For days with rain short wetness durations detected by outside sensors were not detected by inside sensors because of sheltering by the canopy When wetness arose solely from dew duration inside was much shorter than outside for prolonged wet periods Wetness was used to calculate infection periods according to two botrytis bunch rot risk models Agreement between sensors was worse inside the canopy than outside although on occasions when rainfall exceeded 10 mm there was greater uniformity between sensors For regionwide disease risk monitoring wetness duration measured outside leaf canopies at standard meteorological sites would give a worstcase estimate of disease risk Regression equations are presented that allow estimation of inside wetness duration from outside wetness duration for rainy and nonrainy days

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Chronic disease risk monitoring based on an innovative predictive modelling framework

2017 IEEE Symposium Series on Computational Intelligence (SSCI) ◽

10.1109/ssci.2017.8285257 ◽

2017 ◽

Cited By ~ 2

Author(s):

Nitten S. Rajliwall ◽

Girija Chetty ◽

Rachel Davey

Keyword(s):

Chronic Disease ◽

Disease Risk ◽

Predictive Modelling ◽

Chronic Disease Risk ◽

Modelling Framework ◽

Risk Monitoring

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How to Avoid Common Problems with Leaf Wetness Sensor Installation and Maintenance

EDIS ◽

10.32473/edis-ae538-2020 ◽

2020 ◽

Vol 2020 (1) ◽

Author(s):

Thiago Borba Onofre ◽

Clyde W. Fraisse ◽

Natalia A. Peres ◽

Janise McNair

Keyword(s):

Plant Disease ◽

Prediction Models ◽

Disease Risk ◽

Leaf Wetness ◽

Disease Prediction ◽

Biological Engineering ◽

Risk Monitoring ◽

Essential Input ◽

Common Problems ◽

Negative Impacts

Leaf wetness duration is an essential input in disease prediction models and decision support systems in Florida and elsewhere. Incorrect installation or lack of regular maintenance of leaf wetness sensors may lead to errors in plant disease risk monitoring and negative impacts on yield. This 7-page publication provides detailed guidelines for the proper installation and maintenance of leaf wetness sensors and describes the most common problems found in field installations as well as potential solutions. Written by T. B. Onofre, C. W. Fraisse, N. A. Peres, and J. McNair, and published by the UF/IFAS Department of Agricultural and Biological Engineering, February 2020.

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