Research and IPM
Disease: Powdery Mildew
Model 1 of 1
Guzman-Plazola, R. A. 1997. Development of a spray forecast model for tomato powdery mildew (Leveillula taurica (Lev) Arn). Ph.D. Thesis. University of California, Davis.
R. Michael Davis and J .J. Marois. Development of a spray forecast model for powdery mildew of tomato. California Tomato Research Institute 1995 Final Report. p. 52-59. In conjunction with R. Guzman-Plazola.
(See the UC IPM Web version of this model.)
One or more sensors of temperature (T) and relative humidity (RH) are located inside the foliage and toward the top of the plants. A T sensor and its corresponding RH sensor must be kept together and protected with a shield to avoid direct exposure to the sun and water. The shield must allow good air flow around the sensors. One or more leaf wetness (LW) sensors must also be used and located on top of the canopy on fully developed leaves. All sensors must be relocated periodically according to the dynamics of plant growth and checked after periods of high speed winds. Each sensor should make several measurements during an hour.
Environmental: Hourly average, maximum, and minimum temperatures (T), hourly average, maximum, and minimum relative humidity (RH), hourly average leaf wetness (LW).
Calculated: Daily values of the following: average T and RH; average hourly range of T and RH; range of Tmax and RHmax; average of the amount by which T>27.4 C; number of hours where 27.5<=T<=32.4 C; number of hours 5<=LW<=10; number of hours 17.5<=T<=22.4 C and RH>=40%; number of hours T>=32.5C; average of the amount by which RH<40%; number of hours T<12.5 C. If two sets of sensors are used, the hourly values are averaged before these calculations are made.
Daily environmental conditions are classified according to their conduciveness for powdery mildew development, in California typically from June to September. Conditions are measured several times every hour and values are averaged over the hour. Twenty-four hourly values are transformed into additional variables which are fed into a linear discriminant function. Using "No disease," "Moderate," and "Severe" coefficients, the function is evaluated three times. For each disease severity class, values of the 15 calculated daily variables are multiplied by their respective coefficients, summed, then added to the appropriate constant. The disease severity class sum with the largest value indicates whether the weather that day was nonconducive, moderately conducive, or conducive for powdery mildew development.
After this, management decision rules (see Action Threshold below) are applied on the basis of prevailing conditions on a set of six consecutive days. No fungicide spray is recommended when the six-day period is composed only of nonconducive days, moderate days, or any combination of them. A spray is recommended when at least three conducive days accumulate within the six-day period and no period of more than one nonconducive day has occurred. Occurrence of a minimum of two consecutive nonconducive days can cause 70-75% reduction in the final number of powdery mildew lesions. In the cases where no spray was recommended, the new set of six days for evaluation is modified by the elimination of the oldest day(s) and inclusion of the most recent day(s).
The six-day evaluation period corresponds to approximately half a latent period of Leveillula taurica under favorable conditions for disease. In greenhouse trials, sulfur or myclobutanil have controlled the disease when sprayed one to six days after inoculation. Making decisions after evaluating the microclimate for a period of six days is a strategy to assess the risk of disease severity by assuming what would happen if conditions remain the same during the next few days. Since in the absence of fungicides powdery mildew lesions start becoming visible about 13 days after inoculation under conducive conditions, the six-day waiting period provides a reasonable time to allow weather changes to suppress disease development.
The model assumes the following:
(See the UC IPM Web version of this model.)
According to the model, daily conditions evaluated over a six-day period yield the disease assessments and recommended actions listed in Table 1.
Table 1. Decision rules, expected disease severity, and recommended actions based on evaluation of six-day period of daily conditions.
|Conditions*||Expected disease severity||Spray recommendation||Next evaluation of a six-day period will be:|
|All N days||none||Don't spray||6 days later|
|All C days||severe||Spray||16 days after the last spray (with the spray day as day 1 of 16)|
|All M days||moderate||Don't spray||3 days later|
|All M & N days, no 2 N days are consecutive||none to moderate||Don't spray||3 days later|
|At least one series of at least 2 consecutive N days||none to moderate||Don't spray||6 days after last N period|
|At least 3 C days, no 2 N days are consecutive||moderate to severe||Spray||16 days after the last spray (with the spray day as day 1 of 16)|
|Less than 3 C days, no 2 N days are consecutive||moderate||Don't spray||1 day later|
|* N=Nonconducive, M=Moderate, C=Conducive|
In 1997, model validation will continue in the northern San Joaquin Valley by UC Farm Advisor Kent Brittan.
In 1995 and 1996, the moded was validated in several locations in the southern Sacramento Valley and northern San Joaquin Valley, by R. M. Davis, R. A. Guzman-Plazola, G. Miyao, B. Mullen, J. Valencia. Results are reported in R. Michael Davis and J. J. Marois. Development of a spray forecast model for powdery mildew of tomato. California Tomato Research Institute 1995 Final Report. P. 52-59.
Daily output from the model will be available through the California Tomato Weather Network in the 1998 field season.
Characterization of environmental conditions was done from microclimate data collected in 1993 and 1994 from a total of five tomato fields in California's Central Valley. Validation of the model has been done during two years (1995 and 1996) only. Efficacy of the discriminant function to correctly classify weather patterns for conduciveness to powdery mildew under a wider range of conditions must still be tested.
Creation of a larger data set of high resolution microclimate data from tomato canopies, with corresponding data on disease progress on several cultivars, would allow additional tests of the robustness of the discriminant function and possible adjustment of the function's coefficients.
Linear Discriminant Function used to characterize weather data for conduciveness to powdery mildew of tomato on a daily basis. To classify the daily weather conditions, multiply the value of each variable by its respective coefficient in each of the three severity classes. Sum the resulting products in each column and add the constant at the top. Classify the day based on which column (severity class) has the highest value.
|Variable||Disease Severity Class|
|Average of the amount by which T is above 27.4 C||-127.39563||-127.0104||-126.51857|
|Number of hours T is between 27.5 and 32.4 C (inclusive)||-27.51843||-28.83397||-27.47595|
|Number of hours leaf wetness is 5-10 (scale 0-10)||-1.52602||-1.0775||-1.45506|
|Average of the hourly range of T||239.64311||239.8116||227.29673|
|Number of hours T is between 17.5 and 22.4 C (inclusive) and RH is 40% or higher||-11.79873||-11.1779||-11.56707|
|Average of the hourly range of RH||-7.21593||-6.88243||-5.84917|
|Number of hours T is above 32.5 C (inclusive)||-27.91955||-29.31146||-28.43123|
|Range of Tmax||-52.90772||-52.77535||-50.6479|
|Range of RHmax||0.84523||0.66204||0.91081|
|Average of the amount by which RH is below 40%||36.66102||35.42098||35.34618|
|Number of hours T is below 12.5 C||27.49011||27.52647||27.08354|