Agriculture Reference
In-Depth Information
Local amplification depends on complex interactions between plants and soil-
borne pathogens, regulated by the physicochemical and microbial characteristics of
the soil. It is difficult to measure these interactions and characteristics due to soil
'opacity'. One way of relating the epidemiology of a soil-borne disease (take-all of
winter wheat) to cultural practices known or thought to have an impact on these
interactions and characteristics is described below.
The aim of this work was to propose cropping strategies limiting disease risk. In
order to evaluate these strategies based on their ability to decrease epidemics and to
increase yield, a dynamic approach to the relationship between the kinetics of the
disease and crop growth and development is also presented.
Inoculum dispersal has received less attention, especially that occurring between
the harvesting of one crop and the sowing of the subsequent crop. Cultivation leads
to the redistribution of inoculum. This may increase the likelihood of invasion, but it
may also dilute the inoculum to levels below the threshold required for symptom
development in the next crop (Truscott and Gilligan, 2001). The third part of the
next section, will illustrate how current or possible management of this
intercropping period can affect disease incidence in the next crop.
14.3 MODELLING SOIL-BORNE DISEASE EPIDEMIOLOGY
14.3.1 Relationship between cropping practices and disease dynamics
Much attention has been given to the use of non-linear models to describe the
temporal progress of disease (Madden, 1980; Gilligan, 1985). Brasset and Gilligan
(1989) compared the use of several non-linear models to describe the increase in the
absolute number of diseased roots infected with
G. graminis
var.
tritici
in first and
second wheat crops. They concluded that a model incorporating components of
primary and secondary infection, together with inoculum decay, described the data
in a manner consistent with biological constraints.
Colbach
et al.
(1997a) simplified one of these models and used it to assess the
impact of crop management on the primary and secondary infection cycles of take-
all epidemics. Origin of inoculum and infection rates are the central elements of this
model. Inocula may be found in soils, on plant debris or on the roots of the living
plant. Each inoculum is associated with an infection rate. Rate (
c
1
) corresponds to
the capacity of the soil reservoir inoculum to cause infection and disease. The rate of
secondary infection (
c
2
) is a measure of the capacity of infected roots to spread
disease to other roots (or from a diseased plant to other plants). The percentage of
diseased plants is given by the following equation, where time
t
is expressed as
cumulative degree days (basis 0°C) since sowing:
−+
(
cct
)
e
1
−
12
y
=
(14.1)
c
c
−+
(
cct
)
e
1
+
12
2
1
