## Growing Degree Days

### Using weather and climate information to predict pests and diseases

Excerpt from Fruit Crop Ecology and Management. Chapter 2: Managing the Community of Pests and Beneficials by Larry Gut, Annemiek Schilder, Rufus Isaacs and Patricia McManus.

We can forecast pest development using mathematical models because pest development is closely linked to weather conditions. Because of the close relationship between temperature and insect growth, crop managers can predict when many insects will be active by recording temperature data. Sometimes more than one environmental variable is needed to create an effective model. When predicting fungal infection periods, temperature, humidity, and leaf wetness need to be considered. Models are designed to be simple to use but accurate at predicting pest events under most environmental conditions.

### Growing degree day models for insect information

Because insects are cold-blooded, the growth of adults, larvae, and eggs is driven by temperature. As the temperature fluctuates within these limits, development speed changes, with faster growth typically occurring at warmer temperatures. For all insect pests, diseases, and their natural enemies, there are also low and high temperature thresholds for development.

Since temperatures may vary widely from year to year, pest management strategies may not be effective if control measures are based on calendar dates rather than on insect development. Often the stage of insect development can be tied to the growth stage of the crop because plant growth is also driven by temperature. A widely used tool for predicting insect growth is the growing degree day (GDD) model. These models calculate the number of GDDs or heat units that are accumulated between the minimum (base) temperature threshold and the upper threshold. At the end of every day the GDD total for that day is added to the previous total to create a cumulative number of GDDs. Pest managers can use the GDD total to predict emergence, egg laying, and other important events based on the amount of heat accumulated in the vineyard, field, bed, or orchard.

Models have been developed that link GDDs to the stage of development of some key pests and, to a lesser extent, beneficial insects. Using a maximum-minimum thermometer, preferably placed in or near the crop, growers can track the development of insects on their farm. One degree day is accumulated when the average temperature for a day is one degree over the lower limit (base temperature) needed for development. A base temperature for each organism is used in the calculation because very little growth occurs below the base temperature. Growth rates also are reduced when temperatures exceed the upper threshold, and so the maximum is set to this value if temperatures become hotter.

There are many sophisticated methods for estimating GDDs based on more than maximum and minimum temperatures. For example, computer programs can be used to keep track of GDD accumulation based on hourly temperature data. However, for most uses, the method below provides sufficient ability to predict major events in insect development.

### How to calculate growing degree days

To calculate the number of GDDs accumulated per day, you need to know: 1) the upper threshold temperature (T high) and lower threshold (T low) for development of the organism you are interested in, 2) the minimum daily temperature, and 3) the maximum daily temperature. The method below enables easy tracking of GDDs with a simple max-min thermometer. The following examples are for an insect with a lower threshold of 42 and an upper threshold of 86. When this method is used for other insects, their threshold values should be used in the equations.

Growing degree days (GDD) = (T max + T min) / 2 -T low

Where T max is maximum daily temperature and is set to the upper threshold when temperatures exceed it. T min is the minimum daily temperature and is set to T low when temperatures fall below this value. T low is the base temperature for the insect.

1. Temperatures within insect’s development thresholds.
A day with a low of 50° and a high of 78°: (78 +50) / 2 - 42 = 22 GDD
2. Temperature drops below insect’s lower threshold.
A day with a low of 30° and a high of 70°: (70 + 42) / 2 - 42 = 14 GDD
3. Temperature goes outside both the higher and lower thresholds.
A day with a low of 28° and a high of 88°: (88 + 42) / 2 - 42 = 22 GDD

The start point for accumulating GDDs can be decided in two different ways. Either GDDs are counted from a set date, such as March 1, or they are counted from a specific biological event, called a biofix—the date when the first adult is captured in a pheromone or other trap, provided additional adults are captured on two successive trapping dates. This may be called the first sustained capture. Using a biofix is usually more accurate and means that the GDDs have to be counted for a shorter period. Often optimal timing for an insecticide application is during egg hatch, because this is when the insect is most vulnerable. At a set number of GDDs after biofix, sprays aimed at the pest can be applied to target the appropriate stage of the insect. For many of the apple and cherry pest insects, the number of GDDs from first sustained catch to egg-hatch is well known. By keeping track of the number of GDDs after biofix, the optimal timing for control measures can be determined. It is therefore important to check traps often near the start of adult emergence.

Above all, remember that degree day accumulations should be used only as a guide for making management decisions. Ultimate decisions should also be based heavily on frequent scouting of the crop for the presence of insects or insect damage.

### Disease prediction models

Disease prediction models usually predict one or more critical phases in epidemic development such as the presence of primary or secondary inoculum or an infection period. Infection periods are times when the minimum environmental conditions have been met for infection to take place. Environmental data such as temperature, relative humidity, and leaf wetness are typically needed to run disease prediction models. Research in Michigan indicates that leaf wetness can vary significantly over short distances and heights in a crop, especially late in the growing season when the canopy is most dense. The use of models such as for apple scab that predict disease severity based on leaf wetness may be complicated by the variations in microclimate. For models that predict infection periods, fungicides are generally applied “after the fact,” which means that growers have to use curative, systemic fungicides. Models and curative fungicides are not available for all diseases. Most models are based on current or past weather data, but can also be run using predicted weather data, however, those based on predictions are less accurate.