Resistan Exercises Answer Sheet for Instructors
The exercises presented in this lesson represent only a sampling of the ways in which Resistan can be used
to demonstrate the principles of the selection of fungicide resistance. It is expected that each instructor will adapt
them to his or her own class and teaching style, perhaps even creating a new parameter set for new fungicides or
a different fungus. These exercises are intended to illustrate some of the key concepts, not all of which are generally
agreed upon by practitioners in the field (for example, the use of a vulnerable fungicide as a "rescue treatment"
in Exercise 3). These contentious issues can serve as a good jumping off point for a class discussion.
Below are sample outputs for each of the exercises. Individual student responses may vary somewhat.
Exercise 1. Captan
If all is working correctly, the screen at the end of the first season should look like
this.
The following is the year-end summary at the bottom of the Log file, edited to remove the extraneous columns and
to line up the columns to improve the presentation.
End Year Active Lesions % Res to benomyl Profit
1 4438.62 0.0 951.22
2 11817.20 0.0 936.82
3 31438.58 0.0 899.73
4 83476.66 0.0 808.97
5 220508.70 0.0 611.86
6 574652.63 0.0 272.46
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The parameters in this data set correspond to rates of fungicide weathering and rates of infection that would occur
on a very susceptible cultivar in an unusually rainy season, and the initial inoculum (5000 ascospores/acre) corresponds
to a very high level of infection the previous season. Under these conditions captan does not adequately control apple
scab, and the quantity of ascospores to begin each successive season creeps upward slowly.
Exercise 2. Benomyl
The percent of the Venturia population resistant to benomyl rose quickly to nearly 100% during the second season.
(See the graphic output of the second season of the
benomyl simulation.)
In subsequent seasons, resistance to benomyl remained at 100%, making the benomyl sprays completely ineffective.
The carryover inoculum from one season to the next grew higher in each succeeding season, and by the fourth season
the level of disease had risen to the point where the crop was no longer profitable.
End Year Active Lesions % Res to benomyl Profit
1 71.36 0.44 1015.84
2 61.92 95.11 1015.88
3 11065.33 100.0 994.70
4 1927352.82 100.0 -185.16
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The interesting point is that even though the level of resistance had risen to 95% by the end of the second season,
the level of disease was still very low (62 lesions per acre is less than one lesion per tree--probably undetectable),
owing to the very effective control the previous season and the very low carryover of inoculum.
Even in the third season, with 100% resistance, the level of disease had not yet risen to an alarming level. (If you figure
100 trees per acre, it's only 110 lesions per tree.) A grower would certainly notice that the scab control was not
as good as it had been, but it was still on a par with the control one would get with captan. By observation of disease
control, a grower may or may not suspect benomyl resistance by the end of the third season. It would, however, be
detectable by resistance monitoring. It would not be until the fourth season that the lack of disease control would
make benomyl resistance obvious.
Exercise 3. Inoculum Level
Note that the percent resistance in the second season with the low inoculum level follows exactly the same pattern as we
got with 10 times the initial inoculum. The only difference is that there is a lower level of disease.
(See the graphic output of the second season of the
low inoculum simulation.)
End Year Active Lesions % Res to benomyl Profit
1 7.14 0.44 1015.98
2 6.19 95.11 1015.99
3 1106.95 100.0 1013.84
4 206471.55 100.0 692.47
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Looking at the year-end summary, it is clear that under the same benomyl spray schedule the rate of selection of resistance is
exactly the same, regardless of the level of initial inoculum.
The difference is in the level of disease. As we would expect, with
one-tenth the level of initial inoculum we see one-tenth the number of
lesions until the level of disease rises to the point where we begin to
see the effects of density-dependent feedback. Disease control with the
higher level of initial inoculum failed
much faster, not because it selected resistance faster but because it
started with a higher level of inoculum. The rate of selection of
resistance is a function of the spray program, not of the level of
disease when the spray program is started.
In other words, we do not
risk a higher rate of selection of resistance if we use benomyl as a
"rescue" treatment than if we simply use it to maintain disease
control. If we were only observing the numbers of lesions and not
monitoring resistance, it would appear as if the evolution of resistance were higher when we had a higher level of disease at the start.
Exercise 4. Reduced Dose of Benomyl
End Year Active Lesions % Res to benomyl Profit
1 1193.25 0.03 1013.57
2 922.79 7.48 1014.13
3 14637.39 95.83 987.90
4 2572315.89 99.98 -303.24
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Comparing the year-end summary
using a reduced dose of benomyl with that of the full dose in Exercise
2, we can see that the rate of selection of resistance is significantly
lower with the reduced dose compared that with the full dose. Of
course, the reduced dose is not as effective in controlling the
disease, so if one is only looking at the numbers of lesions the perception is that the low dose
fails faster.
For the reduced dose of benomyl
to be effective in controlling apple scab, it will have to be combined
with another fungicide or with other methods of disease suppression.
Exercise 5. Fungicide Combinations
End Year Active Lesions % Res to benomyl Profit
1 17.56 0.02 959.96
2 0.19 4.87 960.00
3 0.04 92.06 960.00
4 0.73 99.96 960.00
5 1.75 100.0 960.00
6 4.16 100.0 959.99
7 9.93 100.0 959.98
8 23.68 100.0 959.95
9 56.47 100.0 959.89
10 134.68 100.0 959.73
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If one were to look only at the
numbers of lesions, it would indeed appear as if the fungicide
combination prevented the evolution of resistance. However, by
monitoring resistance we can see that the combination of captan with
benomyl only reduces the rate of selection of resistance. (Compare the
resistance at the end of each year with those of benomyl alone in
Exercise 2.)
Clearly applying a full dose of
captan on top of a full dose of benomyl amounts to overkill and is too
expensive to be practical. To reduce the cost of the spray program, one
can play around with reducing either the dose of each fungicide in each
spray or reducing the number of sprays of each fungicide. One can gain
the effect of further reducing the rate of selection of resistance to
benomyl by reducing the dose or number of sprays of benomyl. This has
to be weighed against the cost of reducing the number of captan
applications to reduce the application cost.
Exercise 6. Reduced Spray Schedule
End Year Active Lesions % Res to benomyl Profit
1 650.46 0.01 986.71
2 254.51 0.27 987.49
3 112.81 12.19 987.78
4 316.51 87.79 987.37
5 5628.42 99.73 976.88
6 112953.88 99.99 789.94
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Reducing the numbers of benomyl sprays in the spray program and maintaining apple scab control with captan clearly
reduces the rate of selection of (but does not prevent) resistance. It is also clear that this program cannot be
maintained indefinitely.
If you look at the results with benomyl alone (Exercise 2), it probably would not be possible to detect resistance
by monitoring until the third season, by which time the Venturia population would already be 100% resistant
to benomyl. In the above program, benomyl resistance could probably be detected in the third season also, but the
level of resistance would only be 12%. This would allow the grower time to shift to another fungicide to prevent
incurring significant losses to resistance.
Exercise 7. Host Susceptibility
End Year Active Lesions % Res to benomyl Profit
1 22.75 0.19 1015.94
2 1.38 77.65 1016.00
3 27.27 99.98 1015.94
4 692.28 100.0 1014.47
5 17563.21 100.0 977.95
6 438592.95 100.0 386.95
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Using a variety of apple that is slightly less susceptible to apple scab substantially reduces rate of epidemic development
and slightly reduces the rate of selection of resistance. In fact, any factor that reduces the rate of
epidemic development will also reduce the rate of selection of fungicide resistance.
Exercise 8. Reduced Fitness of the Resistant Biotype
Looking first at the selection of resistance where there is
no fitness cost, we can see that In the absence of benomyl, the resistant population
survives as well as the sensitive one, and its proportion of the total population remains the same.
In the case where we gave the resistant fungus a small
fitness cost, we see that first of all, the rate of selection
of resistance is not quite as high as it was where the was no fitness cost. The most important effect, however,
we observe when the modified benomyl residues disappear. The resistant population is not as ecologically fit as the
sensitive wildtype, and in the absence of continued selection by the hypothetically modified benomyl, the resistant
population gradually declines and the total population slowly reverts to sensitive. (In the real world, there appears
to be no fitness cost to benomyl, and there is no such reversion to the sensitive wildtype.)
If you look at the characteristics of myclobutanil, there is a small fitness cost to resistance, so if we stopped applying
myclobutanil after selecting a resistant population, we would expect to see a gradual reversion to the sensitive wildtype.
Exercise 9.
This is a chance for the students to be creative and put together a spray program that both effectively controls
apple scab and avoids selecting high levels of reistance to any fungicide. You might offer a prize to the student
who has the highest net profit for the 10-year period. Remind them that they can change the spray program between seasons
using Select and Schedules options in the Fungicides menu.
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