Early Spray Calculator Explanation

The severity of virus disease symptoms depends upon the timing of inoculation. Plants infected soon after emergence are more severely affected than plants infected later on. We have measured this effect for PEMV and BLRV in pea. In summary, if pea plants remain free of infection until 24 days after emergence, injury will be negligible. Injury before 10 days is expected to be severe. See the data from this study. The effects of PEMV and BLRV are similar. With this information we developed a calculator to help producers decide on insecticidal sprays for aphids early in the growing season.

How the Calculator Works

Inputs

The benefits for treatment were estimated using 6 sources of information:

1. Two years of field data from Eigenbrode and coworkers (University of Idaho) in which untreated control plots were compared with insecticide treated plots of peas (var. Aragorn) where plants infected with viruses (Pea enation mosaic virus [PEMV] or Bean leaf roll virus, [BLRV]) had been inserted as a source of infection;
2. Two years of field data from Stokes and coworkers (University of Idaho) that statistically predict crop seed yield in untreated fields as a function of the time (plant growth stage stated as nodes) when pea plants first are colonized by pea aphids positive for either PEMV or BLRV;
3. Estimates of the efficacy of insecticidal seed treatments of Gaucho and Cruiser at labeled rates based on their effects on yield as compared with a triple spray of dimethoate designed to eliminate all aphids and virus.
4. Two years of field data from Eigenbrode & Ding (University of Idaho) during 2005 and 2004 and four years of field data from Bragg and Burns (Washington State University) between 1996 and 2003 to determine the effectiveness of various foliar-applied commercial insecticides for pea aphids in dry peas; based on these studies, efficacy values used for all dimethoate products and for Warrior with Zeon Technology are 0.9 (with 1.0 equivalent to complete control).
5. A current-season prediction (designated "global risk") of virus and aphid pressure across the Palouse that integrates 27 years of historical data about aphid and virus pressure with current year weather data observed during February, March and April in the Columbia Basin; global risk values can range from 0.0 [= few aphids per plant and no fields with virus] to 1.0 [>100 aphids per plant and 75% or more fields with virus] and is a standardized re-expression of the 1-to-4 Clement Index (Clement et al. 2010).
6. A site-dependent risk (designated "polygon risk") of local virus incidence based on 5 years of historical data from Husebye and coworkers (University of Idaho) on the observed occurrence of virus at sites sampled throughout the Palouse region; polygon risk is assigned values from 0.0 [no risk of virus] to 1.0 [maximum risk of virus] that are fixed to map locations and that do not change from year-to-year.

 

Field studies 1-3 above were conducted at the Plant Science Farm in Moscow, ID from 2009-2011; field studies #4 above were conducted in Moscow, ID at the Plant Science Farm and in Washington at Albion, Farmington, Pullman and Steptoe.

Estimates for Inputs #4 and #5 were based on our published and ongoing studies of pea aphid and virus incidence and abundance in the region. For more information see Clement S.L., Husebye D.S. & Eigenbrode S.D. (2010), "Ecological factors influencing pea aphid outbreaks in the US Pacific Northwest" in Aphid biodiversity under environmental change: patterns and processes, (eds. Kindlmann P, Dixon AFG & Houdková K). Springer Dordrecht, pp. 108-128, and the Legume Virus Project Interim Report (PDF, 26MB).

The costs for treatment include both current retail purchase price + application cost. The default values in the calculator were provided by local commercial sources or from the Idaho Crop Input Price Summary report annually compiled by the Department of Agricultural Economics & Rural Sociology, University of Idaho. Alternatively, users can enter their own estimates of cost into the calculator.

Calculations

Computations begin with the user entering to the calculator values for six parameters:

1. Crop Yield Potential (cwt/acre)
2. Crop Growth Stage (stated as nodes) when aphids first arrive in field
3. Percentage Aphid-infested Plants
4. Expected Crop Market Value ($/cwt)
5. Foliar insecticide (i.e., product name, rate, product cost [$/gallon] and application expense [$/acre]) to be applied
6. Insecticidal seed treatment applied (i.e., product name and rate);

 

Parameters #2 and #3 require actual field scouting data while parameters #1 and #4 are based on the practical experience of the user. Names and rates of insecticide for Parameters #5 and #6 are limited in the calculator to predetermined lists; users can select default cost estimates in Parameter #5 or they can enter their own estimates. Note that seed treatment costs do not enter into the decision to subsequently apply foliar insecticide.

The calculator computes expected relative yield (RY, %) caused by viruliferous aphids in the absence of any insecticidal seed treatment or foliar insecticide as:

RY = (0.0416*# nodes)+0.4195

This value then is used to compute the amount (cwt/acre) of total potentially preventable yield loss weighted for the observed % plants with aphids and for the risk those aphids transmit virus:

preventable yield loss (cwt/acre) = (user Parameter #1)*(1-RY)*(user Parameter #3)*(Global risk) *(Polygon risk)

Efficacy of insecticidal seed treatments and foliar insecticides determines how much of total preventable yield loss actually can be avoided (saved) by either or both control actions.

The efficacy of the insecticidal seed treatments (designated K_SeedTrt) was estimated from field data #3 as the proportion of the preventable yield loss (the difference between untreated plots and those receiving the 3x dimethoate spray) that was achieved by each seed treatment.

The efficacy of each foliar treatment (designated K_foliar) was estimated from field data #4 as the difference in aphid counts sampled through approximately 14-days post-application between small plots sprayed with foliar insecticides and untreated control (check) plots (i.e., K_foliar = [aphids in untreated plot – aphids in sprayed lot]/aphids in untreated plot).

The calculator then computes the portion of preventable yield loss that accrues to foliar insecticide application under two contrasting situations:

Scenario #1    foliar spray applied to fields not planted with insecticide-treated seed
vs
Scenario #2    foliar spray applied to fields that were planted with insecticide-treated seed

For Scenario #1, the amount of preventable yield loss (cwt/acre) from foliar insecticide applied to fields that were not planted with insecticide-treated seed was assumed to be directly proportional to reduction in aphid counts and was computed as:

Foliar yield gain (cwt/acre) = preventable yield loss * K_foliar

For Scenario #2, the amount of preventable yield loss (cwt/acre) from foliar insecticides applied to fields that were planted with insecticide-treated seed was calculated in two steps:

step #1:  determine the portion of preventable loss (cwt/acre) that remains after accounting for the effect of seed treatment, computed as:

preventable yield loss * (1- K_SeedTrt)

step #2:  determine the portion of preventable loss remaining in step #1 that accrues to immediate application of foliar insecticide, computed as:

Foliar yield gain (cwt/acre) = step #1 * K_foliar

The net benefit of foliar treatment ($/acre) is estimated by subtracting the estimated cost from the benefit as follows:

net benefit ($/acre) = [(Foliar yield gain cwt/acre) * (user Parameter #4 Expected Crop Market Value $/cwt)] – (user Parameter #5 product purchase cost + application expense $/acre)

The resulting net benefit ($/acre) value can be negative (= predicted $ loss per acre) or positive (= predicted $ gain per acre).

Assumptions, Limitations and Disclaimers

• Our controlled field plot studies (Inputs 1-3) all used the variety Aragorn and were conducted near Moscow, Idaho in 2009-2011. Different agronomic conditions (especially crop varieties) and different seasonal weather conditions from those in our studies will likely produce different results than those produced by this calculator.
• The regression equation (Input #2) that predicts crop yield as a function of plant growth stage when viruliferous aphids first colonize fields assumes that (1) aphid colonization occurs during a single point in time, (2) aphids are detected by field scouting as soon as they arrive, and (3) control action eliminates aphid infestations within 3 days of first detection. Continuous arrival of viruliferous aphids, unknown timing of first infestation, or persistence of infestations beyond three days of first arrival will produce actual yield losses that differ from calculator predictions.
• The two regression models that estimate Input #2 and that calculate Input #5 Global Risk are statistically significant (p>F less than 0.05) but are of relative low accountability as measured by R² values (i.e., R² = "0.TBD" and 0.44 respectively). Hence, although the models represent our best interpretation, they leave unaccounted more half of the variability in predictions. Potential errors are further increased because we apply these predictions multiplicatively and so accumulate errors.
• Injury by viruses is estimated as the average of PEMV and BLRV from our field studies. This is because it is not possible at this time to readily distinguish the two viruses in the field and because combinations of PEMV and BLRV can also occur. This average of injury by the two viruses is therefore the best estimate of loss to virus and aphid possible at this time. In our studies, the injury by PEMV tends to be greater than that caused by BLRV, but PEMV also tends to be more prevalent in the Palouse region.
• Overall risk of virus infection was computed as the multiplicative product of global risk and polygon risk. This mathematical approach assumes that the impact of seasonal spring weather factors (on which global risk depends) and fixed geographic location of commercial pea fields (on which polygon risk depend) are co-equally important in predicting aphid density and virus intensity. That assumption may not be true; one of these two determinants might be more important than the other.
• Estimates of risk of virus infection on the landscape are based on surveys conducted each year of this project, with approximately 30 sites being surveyed in each year. Although this represents nearly 150 site – years, the resolution is somewhat course (9 mile square??). Individual fields close to one another may differ in likelihood of virus occurring, but our data cannot detect these differences.
• The project was designed specifically to forecast aphid and virus "outbreak" years, but no outbreak has occurred since the project began in 2008. It is possible that outbreak years differ substantially from patterns and impacts we have documented from our data during the five years of this study.
• Use this calculator as a general guide for decision-making rather than as an absolute never-failing prediction of economic returns. If your local conditions differ from our experimental and observational studies used to design this calculator, your outcomes will differ from those in this calculator.
• This calculator ONLY considers the direct immediate effects of insecticidal seed treatment and foliar sprays on pea aphids and the viruses they transmit. Other benefits (such as pea leaf weevil control) OR problems (such as kill of beneficial natural enemies that contribute to suppression of pea aphids or other pea pests) have not been considered. Consider these other potential benefits and costs when making insecticide-use decisions.

Reference cited

Clement S.L., Husebye D.S. & Eigenbrode S.D. (2010). Ecological factors influencing pea aphid outbreaks in the US Pacific Northwest. In: Aphid biodiversity under environmental change: patterns and processes. (eds. Kindlmann P, Dixon AFG & Houdková K). Springer Dordrecht, pp. 108-128.