PLP 6404 Epidemiology of Plant Diseases Spring...
Transcript of PLP 6404 Epidemiology of Plant Diseases Spring...
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PLP 6404
Epidemiology of Plant Diseases
Spring 2015
Ariena van Bruggen, modified from Katherine Stevenson
Lecture 26: Crop loss assessment
Yield levels and losses
Theoretical yield
The yield obtained under the best growing conditions according to calculations
based on the plant and crop physiology or the maximum theoretical yield as
determined by using crop growth simulation models
Attainable yield
The yield achieved when crops are grown using all available pest control
technologies to minimize biotic stress
Economic yield
The level of yield where the value of the yield just exceeds the cost of production
Actual yield
The yield obtained under current agronomic husbandry practices
Primitive yield
The yield obtained without pest control (e.g. subsistence agriculture)
Introduction to crop loss
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The prevention of crop losses is the main reason that we study plant pathology. Zadoks & Schein
(1979) considered crop losses at the end point of epidemiology; this is where the science merges
with crop physiology, economics, and sociology.
Definitions:
Crop damage -- injuries caused by harmful biotic or abiotic agents that collectively
result in a measurable loss of yield
Crop loss -- a reduction in value or financial return due to damage; often measured
as the difference between actual yield and attainable yield due to pests
and/or pathogens
The reduction in value may be the result of
1. lower quantity
2. lower quality
Reliable yield loss data are always in demand (and difficult to get) and are used to:
determine research priorities
serve as a base of information for governmental decisions (local, regional or international
levels)
Potential and actual losses
A loss that may occur in the absence of any management practice is a potential loss.
A loss that has occurred (or is still occurring) is an actual loss.
Actual losses can be direct or indirect:
Losses in quality and quantity of product sustained by the grower, including costs of
pest management are referred to as direct losses.
Losses beyond the farm gate that arise as a consequence of plant pathogens or pests
are considered indirect losses (to community, consumer, wholesaler etc.).
Direct losses can be primary or secondary:
Preharvest and postharvest losses of plant products due to plant disease and pests,
including direct costs of pest management are primary losses.
Losses caused by a reduction in the yielding capacity of future crops sustained at the
grower level are considered secondary losses.
The crop loss estimates can be used to:
1. establish priorities for research programs;
2. justify programs on certain crops or problems;
3. predict yield and provide crop information;
4. plan strategies for future seasons, and;
5. compare seasons, epidemics, pathogens, etc.
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Measuring disease and yield in the field
Four basic approaches have been employed in crop loss studies:
1. single plant or tiller method
disease is assessed on a large number of individual plants (50-2000), covering the entire
range of possible disease intensity values.
yield of the individual plants is then measured and related to disease
problems include high inter-plant variability and low R2 values
2. microplot experiments
used primarily for soilborne pathogens
allows containment of pathogens and creation of wide range of disease levels
very labor intensive
3. Survey method
Involves measurement of many variables concerning biological and physical properties of
the crop and field, including disease intensity, usually at multiple times during the
growing season
4. conventional field experiments with different levels of disease
most widely used technique
should repeat experiment at least 3 years
A range of disease levels can be created by:
Add or remove inoculum
Timing or amount of fungicides applied
If possible, use "typical" farming equipment and practices.
Drawbacks to this approach:
usually includes effects of only a single pathogen - not very realistic
Note: The # of levels of disease intensity is more important than # of replications.
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Models for relating disease intensity and yield loss
Four categories of empirical loss models (what is an empirical model?):
single-point models integral models
multiple-point models generalized or nonlinear models
Single-point models
Single-point models relate yield loss to disease intensity at one specific time during the
growing seasons or at a specific host growth stage.
Most commonly used models; need relatively little data.
May be either linear or non-linear
Can be written in the form: L = a + bX, where L=loss and X=disease intensity
Example: Linear models of yield loss in soybeans as a function of incidence of
Sclerotinia stem rot (Yang, X. B., et al. 1999. Plant Disease 83:456-461)
(3 different years and 3 different locations)
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Example: Linear models of yield loss of chickpea as a function of intensity of fusarium
wilt (Navas-Cortes, J. A., et al., 2000. Phytopathology 90:1269-1278)
Incidence (I): 0=healthy, 1=diseased
Severity (S): 0=healthy, 1=1-33%, 2=34-66%, 3=67-100%, 4=dead plant
Disease intensity index (DII):
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Multiple-point or multiple regression models
Multiple-point models relate yield loss to assessments of disease made at several times
during a growing season.
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More applicable in situations where yield accumulation occurs over a relatively longtime
or rate of disease progress is highly variable.
Example: potato late blight and tuber yield (James, 1972)
L = 1.87X1 + 0.45X2 + 1.44X3 + 0.63X4 + 0.19X5 + 0.18X6 + 0.34X8 + 0.83X9
where L = % tuber yield loss and Xi = weekly change in % defoliation.
Difference between estimated loss and actual loss was less than 5% in 9 of 10
data sets, and has an R2 value of .952
Integral models
Yield or loss as a function of AUDPC
First used by Vanderplank for stem rust of wheat, estimation of yield loss is a function of
the area under the disease progress curve.
Problems with this approach: AUDPC doesn’t take into account
when disease started
that early disease may be more important
that it may not be a good predictor of yield
Weighting factors can be applied to disease assessments at particular times or
growth stages to account for the effect of time of disease occurrence on yield.
Example: Yield of soybean as a function of relative AUDPC (RAUDPC) for soybean
rust epidemics (Yang, X. B., et al., 1991. Phytopathology 81:1420-1426)
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Yield or loss as a function of healthy leaf area duration (HAD):
Waggoner and Berger (1987): Crop yield is determined not by the area of diseased
tissue, but by the area of productive, healthy tissue which is not reflected in
measurements of disease severity.
Yield loss is proportional to 1 - (HAD)/(LAD), where LAD is leaf area duration of a
disease-free control crop. (much more difficult to measure)
Example: Yield of peanut as a function of HAD and absorbed insolation. (Waggoner
and Berger, 1987. Phytopathology 77:393-398)
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Nonlinear models
more powerful than strictly linear modeling
account for more variation in response curve
need larger data sets to fit nonlinear models
Example: Relative yield of
chickpeas as a function of the
standardized areaunder the disease
intensity indexprogress curve
(Navas-Cortes, J. A., et al., 2000.
Phytopathology 90:1269-1278)
Negative exponential model:
RY = e1−erdx
RY = relative yield
x = AUDPC
rd = rate of decrease
(rd estimated from nonlinear
regression)
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Example: Seinhorst model (1965) for quantifying effects of nematodes on yield
Assessing and modeling losses in quality of yield
Losses in quality due to disease may be as important as losses in quantity.
For many products, such as fresh market fruits, quality grades are established and
prices received are determined by the grade.
Whenever quality is an important determinant of crop value, quality losses should be
considered in any investigation of the relationship between disease and loss.
Y = m+ (1-m)N (Z-t)
where Y = yield
m = minimum yield
t = threshold or
tolerance parameter
N = shape parameter
Z = nematode density
Effect of Meloidogyne
incognita on yield of fresh
spinach
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Example: Effect of apple scab on value of harvested fresh market apple fruit