The document discusses using the area under the disease progress curve (AUDPC) to quantify disease resistance in crops. AUDPC is a useful quantitative measure of disease intensity over time that allows for comparison across locations, years, and management tactics. It is calculated by discretizing time points and calculating the average disease intensity between pairs of adjacent points. While easy to calculate, AUDPC cannot be used to compare results across different experiments. The document provides examples of using AUDPC to evaluate resistance to late blight in potatoes and pearl millet.

1. The use of Area under disease progress
curve (AUDPC) to assess quantitative
disease resistance in crop
Chandrappa
Guljar I Dambal
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2. Time
Diseaseintensity
Time
Yield
Loss
prediction
Why do we need (want) to assess yield loss?
or
What are the uses of yield loss records
•For identifying the time when
control is needed and assisting to
develope effective management
procedures.
•For making decision concerning
the need of disease management
(cost/effective calculations).
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3. Evaluation of diseases
 It is one of the most important tasks and usually more
difficult to perform
 A adequate evaluation method should give exact, accurate
and reproducible results
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4. Methods for evaluating disease
• Horsfall-Barrant Scale: assigned to the plant, a numeric value
according to the percentage of leaf area infected by the
disease
•
Direct Estimation: Estimated percentage of severity directly
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5. Area under the disease progress curve to quantify
disease progress.
The area under the disease progress curve (AUDPC) is a
useful quantitative summary of disease intensity over time,
for comparison across years, locations, or management
tactics.
The most commonly used method for estimating the AUDPC,
the trapezoidal method, is to discretize the time variable
(hours, days, weeks, months, or years) and calculate the
average disease intensity between each pair of adjacent time
points (Madden et al. 2007).
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6. AREAUNDER DISEASE PROGRESS CURVE
• The area under the disease progress curve (AUDPC)
value was calculated according to the formula used by
Shaner and Finney (1977).
• Xi is the disease index expressed as a proportion at the
ith observation; t is the time (days after planting) at the ith
observations; and n is the total number of observations.
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7. • The AUDPC is simple to assess because it uses multiple
evaluations and does not need data transformation.
• It is very useful to carry out comparative analysis among
varieties, genotypes or treatments in the same experiment
and in the same crop season.
• One disadvantage of using AUDPC is that it cannot be
used to compare results from different experiments; these
values are not comparable for different reasons. Another
inconvenience is that the difference between resistant and
susceptible materials can be underestimated when
evaluations are made after the susceptible cultivar has
been destroyed, or when evaluations start after the
disease has already severely affected susceptible
genotypes.
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8. How to measure resistance to LB
• AUDPC : has been used for a long time as a single measure to
quantify the amount of disease (LB), but can not compare the
AUDPCs of a clon in different years and locationes, so we seek
standardized measure and was called audpc relative (AUDPCr)
• AUDPCr : is calculated dividing the AUDPC of clone by AUDPC
maximum potential.
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9. The scale of susceptibility :
• In 2009 Dr. Forbes et al., established a scale of susceptibility
to LB using the numbers 1 to 9.
• This scale allows us to compare resistance of a clon in
different years and locations.
• This scale from 1 to 9 (resistant to suceptible) , gives numbers
that are easier to remember and interpreted
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10. How plant pathogens affect their hosts ?
Effects on host
physiology
Effects on host
development
Effects on yield
quantity
Effects on yield
quality
Leaf
infection
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11. Evaluation of late blight resistance
• Late blight is a polycyclic disease because the causal
agent is able to reproduce and re-infect other plants in
the same crop season.
• To evaluate resistance of particular genetic material to
the disease, it is advisable to use the parameter known
as area under disease progressive curve (audpc).
• The assessment of this parameter is based on the
percentage of leaf area affected by late blight, which is
determined visually and registered several times during
the occurrence of the epidemic.
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12. Assessment of AUDPC, a Microsoft Excel
example
1. Evaluations of the percentage of diseased foliar area corresponding to each
genotype according to the date of evaluation should be recorded. Number of days
after planting in which evaluation was per formed must also be recorded. In the
example, nine varieties (a, b, c, d, e, f, g, h, and i) were evaluated at 7, 14, 21, 28, 35,
42 and 49 days after planting.
2. Place the cursor over cell I4, which corresponds to clone “a” area, and calculate
the AUDPC by using the
following formula: = ((C4+B4)/2)*($C$3-$B$3)+((D4+C4)/2)*($D$3-$C$3)+((E4+D4)/
2)*($E$3-$D$3)+((F4+E4)/2)*($F$3 $E$3)+((G4+F4)/2)*($G$3
$F$3)+((H4+G4)/2)*($H$3-$G$3)
3. Press ENTER, and the AUDPC value “2765.00” will be displayed in cell 14
4. Copy cell I4 to the other cells (I5 to I12) and press Edit. Select PASTE SPECIAL,
select FORMULAS and click OK. Values of AUDPC will be displayed in every copied
cell
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14. Interpretation of results
• AUDPC estimates the area under the disease progress curve.
This value is expressed as % - days, that is, the sum of non
transformed daily percentage values of infection.
• Highest values will correspond to more susceptible varieties
and lowest values will correspond to more resistant varieties
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16. Results can be shown in graphics,
where standard deviation values can be added if several repetitions have been
made. It is recommended to have varieties with known resistance as indicators
of susceptibility or resistance to late blight
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17. Interpretation of results
• An evaluation of 100% of late blight-diseased foliar area for
all evaluation dates would have a value of 1.0.
• All values of rAUDPC are expressed as the ratio of this
value. Low values of rAUDPC will indicate low infection
levels during the evaluation period; therefore, they will
correspond to more resistant varieties.
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18. Considerations in evaluating resistance
• Evaluations of the percent of leaf area blighted must be initiated
at the beginning of the epidemic.
• Time intervals for registering the disease should not be long; it
is advisable for them to be shorter (1 week) if climate
conditions are favorable to disease development.
• Evaluations should stop when susceptible genotypes are near
total destruction. Since susceptible materials cannot get more
infected, the more resistant ones will tend to catch up.
• The date of each evaluation must be recorded to calculate the
AUDPC.
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19. • The relative AUDPC (rAUDPC) should be used to
compare data from different experiments. This value is
better than AUDPC but it may introduce bias when
comparing experiments.
• To calculate the rAUDPC divide the AUDPC by N,
where N’=(The total number of days between the first and
last evaluation) multiply by100.
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20. The Area Under the Disease Progress Curve
(AUDPC) model
Time
Diseaseseverity(%)
AUDPC (Disease*days)
Yield(t/ha)
Y = 0- 1X
Y = yield of a diseased plot
0 = estimated yield of a healthy plot
1 =decrease in yield for each increase in AUDPC unit
X = AUDPC units
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21. The AUDPC models are used in both broad-leaf and cereal
crops.
In most cases, a very good relationship exist between AUDPC
values and yield.
The AUDPC models are used mainly for “after-season” loss
assessment.
Uses of the AUDPC models
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22. Percent disease incidence and AUDPC of early blight in the
tomato under field conditions in 2011
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24. The maximum disease severities on Torlesse were higher on
the Nil and B3 treatments, although for both they were below 15%
during the growing season.
Little disease was found on treatments A1, A2 and A4, while
mean severities were below 8% for the B2 treatment and below 7%
for the B1 treatment.
Maximum disease severities on Claire were higher on the Nil,
B1, B2 and B3 treatments, reaching levels of 75, 34, 38 and 32%
respectively during the growing season.
Treatments A1 and A2 had the lowest mean maximum disease
severities and mean AUDPC for all leaves during the growing
season.
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25. Apparent rate of infection (r) at different intervals of crop growth
and area under disease progress curve ( AUDPC) for rust in pearl
millet genotypes
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26. Area under disease progress curve (AUDPC) in different
genotypes of pearl millet
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27. Statistical models have been used extensively for summarizing
and comparing plant disease epidemics.
In these exercises, the statistical package AUDPC was used
to illustrate models and to summarize disease progress over
time, both in terms of population growth models and disease
progress in a locations.
Understanding temporal disease progress lays the groundwork
for developing methods to manage plant disease, such as
developing forecasting models (e.g., determining the optimal
time to apply a fungicide spray) or selecting an optimal
planting date to reduce disease impacts.
Conclusion
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