Leaf wetness is a variable especially designed for agricultural purposes like plant disease monitoring. For many plant infections the leaf wetness is a triggering factor and therefore the appearance of leaf wetness is crucial for the right timing and frequency of plant protection measures like spraying activities.
There is 5 different variables related to leaf wetness:
- Leaf wetness index (binary)
- Leaf wetness probability (%)
- Precipitation index
- Dew index
- Evaporation index
Binary leaf wetness:
leafwetnessindex - binary variable indicating whether leaves are wet (1) or dry (0)
The binary leaf wetness index variable is included in the agro data package.
For temporal aggregations like 3-hourly or daily values an average over the specified time range is calculated. Therefore all values between 0 and on are suitable.
Probabilistic leaf wetness:
The leaf wetness is highly dependent on local conditions like the surrounding land use or vegetation and the actual field crops monitored. To give the agricultural expert the opportunity to weigh the leaf wetness due to its local conditions, we offer probabilities and the single elements that contribute to the appearance of leaf wetness:
leafwetness_probability - probability of leaf wetness appearance in percent
leafwetness_rainindex - intensity of rain calibrated on leafwetness probability
leafwetness_dewindex - intensity of dew calibrated on leafwetness probability
leafwetness_evaporationindex - intensity of evaporation calibrated on leafwetness probability
The probabilistic leaf wetness variables index are included in the agromodelleafwetness data package.
For more information consult the case study on leaf wetness prediction (including validation results of 9 stations in Central Europe).