Agriculture Reference
In-Depth Information
8.6 CONCLUDING REMARKS
Many new analytical and modelling tools have been applied to plant disease
epidemiology in order to understand the temporal development of diseases.
Generally speaking, there are two contrasting approaches in investigating temporal
dynamics of plant pathogens. On one hand, for evaluating practical disease
management strategies, the two most commonly used tools are comparing disease
progress curves or AUDPCs between treatments (Jeger, 2004). On the other hand,
the approach based on linked differential equations is often used to deal with more
theoretical questions related to epidemic development (e.g., Gilligan and Bailey,
1997; Jeger
et al.
, 2002; Jeger
et al.
, 2004a). This chapter focuses on application of
modelling tools to temporal epidemic data and hence does not attempt to include
other more theoretical-orientated research on spatio-temporal modelling of plant
disease epidemics (e.g., Bosch
et al.
, 1988a,b; Ferrandino, 1993; Scherm, 1996;
Jeger
et al.
, 1998; Filipe and Gibson, 2001; Jeger
et al.
, 2002).
REFERENCES
Bailey, D.J. and Gilligan, C.A. (2004) Modeling and analysis of disease-induced host growth in the
epidemiology of take-all.
Phytopathology,
94
, 535-540.
Bailey, D.J., Kleczkowski, A. and Gilligan, C.A. (2004) Epidemiological dynamics and the efficiency of
biological control of soil-borne disease during consecutive epidemics in a controlled environment.
New Phytologist,
161
, 569-575.
Bosch, Fvd., Zadoks, J.C. and Metz, J.A.J. (1988a) Focus expansion in plant disease. 1: The constant rate
of focus expansion.
Phytopathology,
78
, 54-58.
Bosch, Fvd., Zadoks, J.C. and Metz, J.A.J. (1988b) Focus expansion in plant disease. 2: Realistic
parameter-sparse models.
Phytopathology,
78
, 59-64.
Brasset, P.R. and Gilligan, C. (1989) Fitting of simple models for field disease progress data for the take-
all fungus.
Plant Pathology,
38
, 397-407.
Buwalda, J.G., Ross, G., Stribley, D.P. and Tinker, P.B. (1982) The development of endomycorrhizal root
systems: III. The mathematical representation of the spread of vesicular arbuscular mycorrhizal
infection in root systems.
New Phytologist,
91
, 669-682.
Campbell, C.L. and Madden, L.V. (1990)
Introduction to Plant Disease Epidemiology.
New York: John
Wiley & Sons.
Campbell, C.L., Pennypacker, S.P. and Madden, L.V. (1980a) Progression dynamics of hypocotyl rot on
snapbean.
Phytopathology,
70
, 152-155.
Campbell, C.L., Pennypacker, S.P. and Madden, L.V. (1980b) Structural characterization of bean root rot
epidemics.
Phytopathology,
70
, 152-155.
Chan, M.S. and Jeger, M.J. (1994) An analytical model of plant disease dynamics with roguing and
replanting.
Journal of Applied Ecology,
31
, 413-427.
Colbach, N., Lucas, P. and Meynard, J.M. (1997) Influence of crop management on take-all development
and disease cycles on winter wheat.
Phytopathology,
87
, 26-32.
Correll, J.C., Gordon, T.R. and Elliott, V.J. (1988) Powdery mildew on tomato: the effect of planting date
and triadimefon on disease onset, progress, incidence, and severity.
Phytopathology,
78
, 512-519.
Davis, H. and Fitt, B.D.L. (1994) Effects of temperature and leaf wetness on the latent period of
Rhynchosporium secalis
(leaf blotch) on leaves of winter barley.
Journal of Phytopathology,
140
,
269-279.
Everitt, B., Landau, S. and Leese, M. (2001)
Clustering analysis
. Arnold.
Fargette, D. and Vie, K. (1994) Modelling the temporal primary spread of african cassa mosaic virus into
plantings.
Phytopathology,
84
, 378-382.
Ferrandino, F.J. (1993) Dispersive epidemic waves: I. Focus expansion within a linear planting.
Phytopathology,
83
, 795- 802.
