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Encompassing the distribution, incidence and management of a disease epidemic, epidemiology provides information on variances of disease intensity within a host population over a defined time period (Madden et al, 2007). A graphical representation of disease intensity against time is possible to generate if three or more measurements of disease incidence (or amount) are recorded over a given duration, and is referred to as the disease progress curve, (Campbell and Madden, 1990). Disease progress curves are considered uniquely descriptive of an epidemic, and are utilised to describe epidemics in addition to assist making informed decisions to achieve effective management (Madden et al, 2007).
A plant disease epidemic may develop from inoculum present infield, producing one cycle of infection per growing season (monocyclic), or achieve multiple infection cycles increasing inoculum levels within a growing season (polycyclic) (Madden et al, 2007). Numerous models may be fitted to disease progress curves to determine whether a plant disease epidemic is monocyclic or polycyclic in nature; including exponential, monomolecular, logistic, Gompertz, log-logistic, Richards or Weibull models (Madden et al, 2007).
The exponential, monomolecular and logistic models provided the foundations for some of the most thorough studies in epidemiology to date (Madden et al, 2007). The exponential model has been used to describe population growth for over two hundred years, and can be useful for representing polycyclic epidemics during their early stages. Chemical reactions, animal growth as well as plant disease epidemics have been described by the monomolecular model, also referred to as the restricted or negative exponential model and often suggestive of monocyclic plant disease epidemics (Campbell and Madden, 1990). The logistic model borrows aspects from both monomolecular and exponential models, and is recognised as a superior descriptor of polycyclic plant diseases throughout the course of an epidemic (Madden et al, 2007). The Gompertz model was originally devised for measuring animal growth, and is considered to be less constraining than the logistic model when describing polycyclic plant disease epidemics (Campbell and Madden, 1990; Madden et al, 2007). The Richards model represents another modification of the Logistic model, and has been used to draw objective comparisons between models (Madden et al, 2007).
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Model Absolute rate of disease Rate (r)
increase or decrease (dy/dt) or other parameter
exponential rEy rE
monomolecular rM(1-y) rM
logistic rLy(1-y) rL
Gompertz rGy[ln(1)-ln(y)] rG
Richards rRy(1-yη-1)/η-1 rR, η(unitless parameter)
Table 1.1 - Differential equations of selected models where y = measured disease incidence or severity, adapted from Madden et al (2007).
Presently, little information is available pertaining to epidemiology of B. cinerea in Tasmanian pyrethrum fields. In a recent study, development of S. sclerotiorum flower blight was best described as a monocyclic disease; with 92% of Tasmanian fields surveyed between 2007-2009 having epidemics most aptly being described by the monomolecular model (Pethybridge et al, 2010). Additionally, there has been no comprehensive study of mycoflora associated with pyrethrum flowers in Tasmania. Whether or not other pathogenic fungi potentially contribute to flower disease in pyrethrum in Tasmania is presently unknown (MacDonald, 1995). Determining if mycoflora other than B. cinerea and S. sclerotiorum are associated with diseased pyrethrum flowers and potentially contributing to flower disease epidemics in Tasmania would therefore be of great interest.
The objective of this experiment was therefore to assess the fungal incidence of flowers through the flowering period to:
Investigate and describe epidemiology of B. cinerea and S. sclerotiorum flower blights of pyrethrum in Tasmanian fields.
Provide more detailed information on approximate time of initial infections of B. cinerea and S. sclerotiorum in flowers in the field.
Determine periods when disease incidence is ascending rapidly late during the flowering period to enable more effective timing of control measures/fungicide applications.
To determine if fungal species other than known pathogens of pyrethrum flowers were regularly associated with diseased pyrethrum flowers, and potentially contributing to flower disease.
37 1.2 Materials and methods
Plots to receive no flowering fungicide applications (Nontreated plots) were established in ten commercial pyrethrum fields approaching first flower harvest across numerous cultivation districts during late October of 2007 (Table 1.2.1). Fields were located across the North West coast up to approximately 75km apart and up to 20km back from the coast. Plots measured between approximately 10m × 10m to 20 × 20m (depending on spray boom and spray run widths at field sites) and were centred across adjacent spray runs (Figure 1.2.1). Marker pegs tied with brightly coloured flagging tape clearly identified plots, with signs reading ‘no flowering fungicides’ affixed at each end of nontreated plots. Growers were requested not to apply flowering fungicides to these areas, while the remainder of each field received the industry standard applications of the flowering fungicide program. Site District 07-1 Barrington 07-2 Sassafras 07-3 Forth 07-4 Forth 07-5 Kindred 07-6 Penguin 07-7 Table Cape 07-8 Table Cape 07-9 Table Cape 07-10 Wesley Vale
Table 1.2.1 - Field sites and cultivation districts (2007-08 flower harvest).
38 Sampling flowers for pathogen incidence
Flowers were sampled from nontreated plots for assessment of fungal incidence on five occasions during the flowering period (Table 1.2.2). At each sampling time, 100 flowers were randomly chosen from within each of the nontreated plots at each trial site. Fifty flowers were collected from along two transects on each side of the spray run and at least 2m into the crop from the edge of the spray run. Flowers were chilled during transit, and stored at 5°C for no longer than two days prior to processing. Flowers were placed inside mesh bags and surface sterilised in a solution of 2% sodium hypochlorite (Bleach, White King TM) in distilled water for five minutes. Flowers were subsequently rinsed with sterile distilled water three times to remove residual bleach. Flowers were spread out on filter paper inside a laminar flow cabinet for at least three hours to dry. Flowers were then placed on fibreglass insect mesh cut to fit sealable plastic trays (Genfac Plastics, Melbourne, Australia) suspended over a damp, folded tissue with 5 mm Gutterguard TM (Boddingtons Australia Pty. Ltd., Melbourne) mesh. Five flowers were positioned separately in each tray (Plate 1.2.1 A). Trays were sealed and incubated at room temperature (18-22°C day/ 10-15°C night) for 15-25 days. After incubation and development of fungal growth (Plate 1.2.1 B) each flower was individually assessed under a Zeiss stereomicroscope (63×).
B. cinerea was identified by occurrence of distinctive conidiophores, conidia and sclerotia (Plate 1.2.1 C). Sclerotia of B. cinerea are described as very small or variable in size with diameters ranging between 1-18 mm and colour being black, grey or white (Clarkson and Whipps, 2002; Kulakiotu et al, 2004; Schumann and D’arcy, 2010). During this study, sclerotia of B. cinerea ranged from approximately 5-10 mm in size, and were generally smaller than those of S. sclerotiorum. Sclerotia of B. cinerea often had a distinctive pock marked ‘golf ball’ appearance on the upper surface; and were also distinctly concave in shape on the underside, as opposed to S. sclerotiorum in which sclerotia wereconvex in shape, with a smooth exterior. Sclerotia of S. sclerotiorum were black in colour once mature, while B. cinerea gave rise to grey, dark grey or black sclerotia. Sclerotia of B. cinerea often had conidiophores growing directly from surfaces, thus providing several means to distinguish between sclerotia of both genera. S. sclerotiorum was identified by typical white, floccose mycelium and distinctive sclerotia (Plate 1.2.1 D).
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Plate 1.2.1 - Pyrethrum flowers; before (A) and after (B) incubation, profusely covered with conidia