yield loss asessment

1. ASSESSMENT OF YIELD LOSS BY PLANT
PATHOGENS

2. ■ For making decision concerning the need of
disease management (cost/effective calculations
■ For identifying the time when control is needed
and assisting to develope effective management
procedures.
Why do we need to assess yield loss?
What are the uses of yield loss records

3. ■ For administrative decisions: making
priorities in research, breeding,
allocation of efforts, etc.
■ For insurance purposes

4. Loss assessments can be made on
several scales
■ Individual plants
■ Small plots (e.g., experimental plots)
■ Individual field
■ Regions
■ Nations
■ The entire world

5. How plant pathogens affect their hosts ?
Effects on host
physiology
Effects on host
development
Effects on yield
quantity
Effects on yield
quality
Leaf
infection

6. Effects on host physiology

7. Effects of plant pathogens on host physiology
•Effects of radiation
interception (RI)
•Effects of radiation use
efficiency (RIE)
reflected
radiation
intercepted
radiation
transmitted radiation

8. Effects of plant pathogens on host physiology
Effects of radiation interception
Stand reducers
Seedling diseases

9. Effects of plant pathogens on host physiology
Effects of radiation interception
Tissue consumers
Alternaria macrospora in cotton

10. Effects of plant pathogens on host physiology
Effects of radiation interception
Leaf senescence accelerators
Alternaria solani in tomatoes

11. Effects of plant pathogens on host physiology
Effects of radiation interception
Light “stealers”
Smutty mold (Aspergillus sp.) in
cotton

12. Disease severity (%)
Photosynthesis
rate
(%)
0 50 100
0
50
100
invaded area
infected area Necrotic area
Effects of plant pathogens on host physiology
Effects of radiation use efficiency
photosynthetic rate reducers

13. Effects of plant pathogens on host physiology
Effects of radiation use efficiency
Turgor reducers
Disease severity (%)
Transpiration
rate
(%)
0 50 100
0
50
100
stomata
stomata

14. Effects of radiation use efficiency
Turgor reducers
Disease severity (%)
Transpiration
rate
(%)
0 50 100
0
50
100
Powdery
mildew
stomata

15. Effects of radiation use efficiency
Turgor reducers
Disease severity (%)
Transpiration
rate
(%)
0 50 100
0
50
100
rusts
stomata
rust pustules

16. Effects of radiation use efficiency
assimilate suppers
Powdery mildews

17. Quantification of yield losses

18. Effects of Alternaria macrospora on cotton yield
(mean of 11 field experiments)
Treatment yield (t/ha) yield increment
t/ha %
Untreated
Maneb
4.26
5.03
-
0.78
-
15.4
Tebuconazole 5.70 1.44 25.2

19. Measurement of yield loss:
which reference to use?
Commercially
managed-plot yield
(t/ha)
Untreated-plot yield 3.0
5.0
Attainable yield 8.0
Potential yield 15.0
-40%
+66%
Healthy-plot yield 6.0
-50%
+100%

20. Measurement of yield loss:
what is the reference?
Differences between yield of a reference plot and
yield of a diseased plot
Loss = [yield of reference plot] - [yield of diseased plot]
Reference plots:
A non-infected (healthy) plot
The least infected plot in the experiment
Average yield of commercial plot in the area

21. Measurement of yield loss:
what is the reference?
Differences between estimated yield of a healthy plot
and yield of a diseased plot
Loss = [estimated yield of healthy plot] - [yield of diseased plot]
Disease severity (%)
Yield
(t/ha)
0 100

22. The damage function
The quantitative relationship between disease intensity
and yield (or yield loss)
Disease intensity ( %)
Yield
(t/ha)
Disease intensity ( %)
Yield
loss
(%)

23. The damage function
Disease intensity
Yield
Linear
Disease intensity
Yield
Logarithmic
Disease intensity
Yield
Compensation
Disease intensity
Yield
Optimum

24. The relationship between the time of
disease development and the
resultant yield loss

25. Yield components of cereals
Emergence
Tillering
Boot stage
Grain filling

26. Yield components of cereals
no. of spikelets
per ear
no. of spikelets
per unit area
no. of grains
per spikelet
no. of grains
per unit area
Yield per unit area
weight of
a grain
no. of plants
per unit area
no. of ears
per plant
no. of ears
per unit area

27. The yield components that are affected by
plant diseases are those that are created at, or
soon after, the time of disease onset
% difference
No. of ears/plant
No. spikelets/ear
Grain wt.
Yield
19.1*
7.6
4.2
28.5*
Growth stage
tillering
Disease
severity
(%)
untreated
sprayed
emergence
Effects of powdery mildew in barley on yield and its components

28. milk
Growth stage
tillering
Disease
severity
(%)
Effects of Septoria tritici
blotch in wheat on yield
and its components
untreated
sprayed
earing
% difference
No. of ears/plant
No. spikelets/ear
No.
grains/spikelet
Grain weight
Yield
2.5
0.8
8.1*
8.0*
18.1*

29. In Israel, Septoria tritici blotch in wheat
affects only the weight of individual
grains.
Thus, there is no need to control the
disease before the earing stage.
Similarly, the is no need
to control the disease
after most of the grain
weight was accumulated.

30. Yield components of a board-leaf plant
Emergence
Vegetative
growth
Reproductive
growth
Yield
production

31. Yield components of a broad-leaf plant
weight of
individual fruit
Yield per unit area
no. of plants
per unit area
no. of fruits
per plant
no. of fruits
per unit area

32. Effects of Alternaria in cotton on yield and its components
Boll
weight
Boll
Number
untreated
sprayed
Yield

33. A. macrospora affect only the number of
bolls per plant.
Bolls are shed only at the initial stages of
their development.
Thus, disease management
is very important early in
the season when the bolls
are small, but not towards
the end of the season,
when the bolls had already
developed enough.

34. Yield loss
models

35. The critical point model
Disease severity at time G1 (%)
Yield
(t/ha)
Time
Disease
severity
(%)
G1
harvest
disease
assessment
Y = 0- 1X
Y = yield of a diseased plot
0 = estimated yield of a healthy plot
1 = reduction in yield for each percent increase in disease severity
X = disease severity of the diseased plot

36. The critical point model is used mainly in cereals.
In cereals have distinct growth stages and it is
possible to determine precisely which crop growth
stage is affected most by the disease.
This stage should be chosen to be the “critical”
stage - for assessment.
Critical point models are used mainly for “after-
season” loss assessment.
Uses of critical point models

37. The multiple point
model
Time
Disease
severity
(%)
T1 T2 T3 T4 T5 T6T7 T8
Y = 0- 1X1 - 2X2 - 3X3 - 4X4 - 5X5 - 6X6 -
7X7 - 8X8
Y = yield of a diseased plot
0 = estimated yield of a healthy plot
1-8 = reduction in yield in each sampling for each percent
increase in disease severity
X1-X8 = disease severity of the diseased plot in each date
harvest
disease
assessments

38. ■ The multiple point model is used mainly in broad-
leaf crops.
■ In broad-leaf crops yield is accumulated during a
long period and there are no distinct growth
stages.
■ In many cases, the disease affect yield during the
whole period of its accumulation.
Uses of multiple point models

39. Time
Disease
severity
(%)
T1 T2 T3 T4
Critical
severity
The critical time
model
Time for critical severity (days)
Yield
(t/ha)
Y = 0+ 1X
Y = yield of a diseased plot
0 = estimated yield of a plot infected at day 0
1 =increase in yield for each day of delay in time to critical severity
X = time for critical severity in diseased plot

40. Critical time models may be used in both cereals and
broad-leaf crops.
These models are applicable in situations where disease
onset vary markedly from year to year and from location to
location.
The critical time models may be used for decision making.
For that purpose, the critical severity level to be used
should be low enough, to enable proper disease
suppression.
Uses of critical time models

41. The Area Under the Disease Progress Curve
(AUDPC) model
Time
Disease
severity
(%)
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

42. 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

43. Measure Disease Progression
1 . Research rules and guidelines that apply to
measuring the specific disease and crop you
investigate. The required size of the plant
sample varies by crop and disease. Studying
late blight in tubers, for example, requires a
minimum sample of 40 plants.
2. Plant the appropriate number of plants
required for the study.

44. 3. Watch carefully for signs of the disease. Research
when signs are expected to occur so that you are
prepared. For example, signs of late blight occur
about 30 to 40 days after planting and 10 days
after the last application of fungicide.
4. Estimate visually the percentage of infected leaf
area in your sample as soon as you notice the
disease.

45. 5 . Record the percentage of infected leaf area at
regular time intervals. Researchers take reading
for late blight every seven days if the disease
progresses more quickly than expected. Readings
are taken every 14 days when disease progression
is slower.
6. Stop recording infection measurements when the
percentage of infection stops increasing, and the
disease progression levels.

46. 7. Add the first two infection percentages you
recorded.
8. Divide the addition result by two to find the
average or mid-value of the two readings.
9. Multiply the average or mid-value by the time
interval, which is the number of days from the first
reading to the second reading. If you took the first
reading on day 20 and the second reading on day
27, for example, then the number of days, or time
interval, is seven days.
10.Record the result in units of percentage days.
The value is an area of a trapezoid.

47. 11.Repeat Steps One through Four for the second
and third infection readings you took. Their result will
be the area of a second trapezoid. Repeat Steps One
through Four until you calculated trapezoid areas for
all readings.
12.Add all of the trapezoids to find the AUDPC.
Lower AUDPCs represent slower disease progression
and greater resistance to the disease. Higher AUDPCs
represent faster disease progression and higher
susceptibility to the disease.

48. Concluding remarks
•Losses may be predicted early in the season for management
decision making or after the season for general analyses.
• Plant pathogens may affect the physiology of the host and result in
yield losses directly or indirectly.
•Determination of the yield component to be affected by the disease
is an important component of an IPM strategy.
•Yield loss should be determined in relation to a reference plot.
•Yield loss may be quantified by several models: the critical point
model, the multiple point model, the critical time model and the
AUDPC model.

49. Important points
1. Critical times
tillering, stem elongation, flag leaf opening
2. Crop loss : kernel weight
3. Crop loss is a function of disease epidemic
L = 1230.91+1.37AUDPC