Leafwetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates.Because LWDis notwidelymeasured, severalmethodshave beendeveloped to estimate it from weather data. Among the models used to estimate LWD, those that use physical principles ofdewformationand dewand/or rainevaporationhave showngoodportability and sufficiently accurate results, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empiricalmodels use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimateLWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained fromAmes, IA (USA), Elora,Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sa~o Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH 90% model performed best, presenting the highest general fraction of correct estimates (FC), between 0.87 and 0.92, and the lowest false alarm ratio (FAR), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, evenwhen independent datawere used;MAE ranged from1.23 to 1.89 h, which is very similar to errors obtainedwithpublished physicalmodels forLWDestimation. Based on these results, weconcluded that, if calibrated locally,LWDcan be estimated with acceptable accuracy byRH above a specific threshold, and that theEXT_RHmethodwas unsuitable for estimating LWDat the locations used in this study.

Suitability of relative humidity as an estimator of leaf wetness duration

ORLANDINI S;
2008

Abstract

Leafwetness duration (LWD) is a key parameter in agricultural meteorology since it is related to epidemiology of many important crops, controlling pathogen infection and development rates.Because LWDis notwidelymeasured, severalmethodshave beendeveloped to estimate it from weather data. Among the models used to estimate LWD, those that use physical principles ofdewformationand dewand/or rainevaporationhave showngoodportability and sufficiently accurate results, but their complexity is a disadvantage for operational use. Alternatively, empirical models have been used despite their limitations. The simplest empiricalmodels use only relative humidity data. The objective of this study was to evaluate the performance of three RH-based empirical models to estimateLWD in four regions around the world that have different climate conditions. Hourly LWD, air temperature, and relative humidity data were obtained fromAmes, IA (USA), Elora,Ontario (Canada), Florence, Toscany (Italy), and Piracicaba, Sa~o Paulo State (Brazil). These data were used to evaluate the performance of the following empirical LWD estimation models: constant RH threshold (RH 90%); dew point depression (DPD); and extended RH threshold (EXT_RH). Different performance of the models was observed in the four locations. In Ames, Elora and Piracicaba, the RH 90% and DPD models underestimated LWD, whereas in Florence these methods overestimated LWD, especially for shorter wet periods. When the EXT_RH model was used, LWD was overestimated for all locations, with a significant increase in the errors. In general, the RH 90% model performed best, presenting the highest general fraction of correct estimates (FC), between 0.87 and 0.92, and the lowest false alarm ratio (FAR), between 0.02 and 0.31. The use of specific thresholds for each location improved accuracy of the RH model substantially, evenwhen independent datawere used;MAE ranged from1.23 to 1.89 h, which is very similar to errors obtainedwithpublished physicalmodels forLWDestimation. Based on these results, weconcluded that, if calibrated locally,LWDcan be estimated with acceptable accuracy byRH above a specific threshold, and that theEXT_RHmethodwas unsuitable for estimating LWDat the locations used in this study.
2008
Dew
temperature
empirical models
epidemiological models
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/14687
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