Measuring Leaf Wetness: Best Practices and Sample Use Case

  • By Arable Staff

Leaf wetness is an essential parameter in many agricultural applications. Timely detection and analysis of leaf wetness can increase crop protection, decrease disease risk, and improve pesticide and irrigation scheduling.

Below, we’ll outline how leaf wetness can be detected, present an everyday use case, and discuss best practices for data analysis.

What Is Leaf Wetness?

Leaf wetness is simply the presence of water on the surface of the crop. Although this sounds innocuous, it is precisely what some microorganisms need to go from harmless to crop-destroying pathogens. By monitoring leaf wetness, growers and their advisors can take proactive measures to protect their crops from diseases before they have a chance to take hold.

When Is a Microorganism a Pest?

Figure 1: The disease triangle illustrates the phenomenon of plant disease. Based on 21st Century Guidebook to Fungi, second edition, by David Moore, Geoffrey D. Robson, and Anthony P. J. Trinci, updated July 2019.

The severity of a pathogen depends on several factors: the environment, the plant (the pathogen’s host), and the time that these factors are present. Bacteria, viruses, fungi, oomycetes, and invertebrates only become pests when their population surpasses a certain threshold and begins to cause damage.

For pest populations to grow past that threshold, the required plant and environmental conditions must be met for the organism to do the two most essential things in life: eat and reproduce.

Leaf wetness is one of the most commonly used indicators that a field is a breeding and feeding ground for pests. This is because dew provides a favorable environment for spores germination, and the temperature during the wet period determines the infection rate—especially for bacterial, fungal, and oomycete species.

How Do We Detect Leaf Wetness?

At Arable, we monitor factors related to the presence of surface water buildup and report leaf wetness measurements. We report daily leaf wetness because the hours after midnight are when the environmental conditions are most suitable for moisture to settle on the surface of leaves. We know a leaf is wet when the leaf temperature is equal to or below the dew point temperature (the temperature at which air cools to reach saturation).

To figure detect leaf wetness,we run calculations based on four variables:

  1. Surface temperature (T)
  2. Relative humidity (RH)
  3. Vapor pressure (ea)
  4. Dew point temperature (Tdew)

First, we calculate the actual vapor pressure in the air, helping us understand the pressure differential between how saturated the air is with water and how saturated it could be.

ea = esatRH

Second, we calculate the dew point temperature to identify what temperature it needs to be for the air to become so saturated with water vapor that it condenses into liquid.

Tdew = 116.91 + 237.3 log(ea) / 16.78 – log(ea)

Finally, the output results from Arable’s unique model, which incorporates measurements of relative humidity, precipitation, dew temperature, and surface temperature to find out how long the leaf temperature is below or equal to the dew point temperature. This model translates to a metric of leaf wetness duration over a 24-hour window.

Figure 2: Leaf wetness and maximum temperature at two California locations, as seen in Arable Web.

With Arable, you can unlock the value of measuring leaf wetness. Explore the Arable Solution >

How Can You Use This Data?

Arable can help you predict the threat level for pest infestation by monitoring the field conditions that determine a pest’s ability to eat and reproduce.

In combination with the expected growth stage based on the number of growing degree days and the plant’s health status (i.e., Normalized Difference Vegetation Index and Chlorophyll Index), leaf wetness hours can serve as a warning system for when to monitor your fields closely or when to plan for pest prevention interventions.

To use this data effectively, you may need to know the basics about the pest under consideration, such as:

  • The season or plant growth stage during which the infection occurs in your region
  • The temperature range at which infection generally occurs
  • The leaf wetness duration typically required for infection

You can easily find or infer this information through various research and educational institutions, such as the University of California Agriculture and Natural Resources (UCANR) Integrated Pest Management (IPM) group.

Leaf wetness affects the virulence of many diseases, including:

  • Apple scab
  • Cedar apple rust
  • Potato blight
  • Tomato early blight
  • Strawberry fruit rot
  • Botrytis fruit rot (strawberry & grape)
  • Citrus brown spot
  • Pear brown spot
  • Scotty blotch and flyspeck (apple)
  • Grape powdery mildew

Example Use Case

Lettuce downy mildew (Bremia lactucae), for example, occurs during damp, cool conditions when the leaves of the lettuce are wet. Management choices such as using drip irrigation over spray irrigation can help reduce the likelihood that leaves are wet long enough for infection. Still, nothing beats the certainty of knowing how long your leaves are wet during uncontrollable weather conditions that are perfect for B. lactucae sporulation and infection.

The combined knowledge of your pest infection cycle and in-field monitoring with the Arable Mark can serve as a warning system for inoculation and symptom occurrences.

Figure 3: Schematic representation of the infection cycle of lettuce downy mildew. Weather variables were summarized separately for the periods of afternoon, night, and morning to match the biology of the pathogen. PST = Pacific standard time. Modified from Scherm, H., and van Bruggen, A.H.C. 1994. “Weather Variables associated with infection of lettuce by downy mildew (Bremia lactucae) in coastal California.” Phytopathology 84:860-865.

Drive Sustainability with Arable

Leaf wetness is a critical metric for predicting and preventing pest infestations. By understanding the basics of the infection cycle of the pest, in combination with data on leaf wetness duration, you can develop a warning system for when to take action to prevent crop damage.

Click here to learn more about how we can help you harness the power of data to drive sustainable and profitable outcomes.

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