Moin U. Salam

Blackleg sporacle: A model for predicting onset of pseudothecia maturity and seasonal ascospore showers in relation to blackleg of canola

ABSTRACT A simple model has been developed to predict the onset of pseudothecia maturity and seasonal ascospore showers in relation to blackleg disease in canola, caused by the fungus Leptosphaeria maculans. The model considers a combination of two weather factors, daily mean temperature and daily total rainfall, to drive progress of maturity of pseudothecia on the infested canola stubble left from past crops. Each day is categorized as suitable or not suitable for progress of the maturation process. The onset of pseudothecia maturity occurs when approximately 43 suitable days have occurred. Following the onset of maturity, ascospore showers are triggered when daily rainfall exceeds a threshold. The model satisfactorily predicted the timing of the onset of pseudothecia maturity when tested with 3 years of field observations at four locations in Western Australia, which characteristically has a Mediterranean climate. The model also agreed reasonably well with the daily pattern of ascospore release observed in two locations. Sensitivity analysis was performed to show the relative importance of the parameters that describe the onset of pseudothecia maturity.

Improved resistance management for durable disease control: A case study of phoma stem canker of oilseed rape (Brassica napus)

Specific resistance loci in plants are generally very efficient in controlling development of pathogen populations. However, because of the strong selection pressure exerted, these resistances are often not durable. The probability of a resistance breakdown in a pathosystem depends on the evolutionary potential of the pathogen which is affected by: (i) the type of resistance (monogenic and/or polygenic), (ii) the type of reproduction of the pathogen (sexual and/or asexual), (iii) the capacity of the pathogen for dispersal, (iv) the resistance deployment strategy (pyramiding of specific resistances, mixture of cultivars, spatio-temporal alternation), (v) the size of the pathogen population, which is affected by control methods and environmental conditions. We propose the concept of Integrated Avirulence Management (IAM) to enhance the durability of specific resistances. IAM involves a strategy to limit the selection pressure exerted on pathogen populations and, at the same time, reduce the size of pathogen populations by combining cultural, physical, biological or chemical methods of control. Several breakdowns of resistance specific to Leptosphaeria maculans, the causal agent of phoma stem canker have occurred in Europe and in Australia. This review paper examines control methods to limit the size of L. maculans populations and discusses how this limitation of population size can enhance the durability of specific resistances. It proposes pathways for the development of a spatially explicit model to define IAM strategies. Simulation results are presented to demonstrate the potential uses of such a model for the oilseed rape/L. maculans pathosystem.

Principles of Predicting Plant Virus Disease Epidemics

Predicting epidemics of plant virus disease constitutes a challenging undertaking due to the complexity of the three-cornered pathosystems (virus, vector, and host) involved and their interactions with the environment. A complicated nomenclature is used to describe virus epidemiological models. This review explains how the nomenclature evolved and provides a historical account of the development of such models. The process and steps involved in devising models that incorporate weather variables and data retrieval and are able to forecast plant virus epidemics effectively are explained. Their application to provide user-friendly, Internet-based decision support systems (DSSs) that determine when and where control measures are needed is described. Finally, case studies are provided of eight pathosystems representing different scenarios in which modeling approaches have been used with varying degrees of effectiveness to forecast virus epidemics in parts of the world with temperate, Mediterranean, subtropical, and tropical climates.

AnthracnoseTracer: A Spatiotemporal Model for Simulating the Spread of Anthracnose in a Lupin Field

ABSTRACT A spatiotemporal model has been developed to simulate the spread of anthracnose, initiated by infected seed, in a lupin field. The model quantifies the loss of healthy growing points of lupin in all 1-m(2) subunits of a field throughout a growing season. The development of growing points is modeled as a function of temperature using a 1-day time step, and disease-induced compensatory growth is accounted for. Dispersal of spores is simulated explicitly using Monte Carlo techniques. Spread of spores occurs during rainfall events on a 1-h time step. The distance traveled by spores is partially dependent on wind speed and is generated by adding the values selected from half-Cauchy distributions. The direction of travel of the spores is influenced by wind direction. The model has been employed to produce a theoretical assessment of damage from disease in two environments at five levels of seed infection. It was calculated that in a susceptible lupin cultivar with a 0.01% initial seed infection, anthracnose would cause approximately 15% loss of healthy growing points in a high rainfall environment in Western Australia. In a low rainfall environment, similar damage would be unlikely even with a much higher (1%) level of seed infection.

Seasonal and Diurnal Patterns of Spore Release Can Significantly Affect the Proportion of Spores Expected to Undergo Long-Distance Dispersal

Many of the fungal pathogens that threaten agricultural and natural systems undergo wind-assisted dispersal. During turbulent wind conditions, long-distance dispersal can occur, and airborne spores are carried over distances greater than the mean. The occurrence of long-distance dispersal is an important ecological process, as it can drastically increase the extent to which pathogen epidemics spread across a landscape, result in rapid transmission of disease to previously uninfected areas, and influence the spatial structure of pathogen populations in fragmented landscapes. Since the timing of spore release determines the wind conditions that prevail over a dispersal event, this timing is likely to affect the probability of long-distance dispersal occurring. Using a Lagrangian stochastic model, we test the effect of seasonal and diurnal variation in the release of spores on wind-assisted dispersal. Spores released during the hottest part of the day are shown to be more likely to undergo long-distance dispersal than those released at other times. Furthermore, interactions are shown to occur between seasonal and diurnal patterns of release. These results have important consequences for further modelling of wind-assisted dispersal and the use of models to predict the spread of fungal pathogens and resulting population and epidemic dynamics.

Epidemiology of Blackleg (Leptosphaeria maculans) of Canola (Brassica napus) in Relation to Maturation of Pseudothecia and Discharge of Ascospores in Western Australia

ABSTRACT The timing of maturation of pseudothecia and discharge of ascospores of the blackleg fungus (Leptosphaeria maculans) is critical in relation to infection early in the cropping season of canola. During 1998 to 2000, development of pseudothecia was investigated on residues of the previous years canola crop collected from four agroclimatically different locations: Mount Barker (southern high rainfall), Wongan Hills (central medium rainfall), Merredin (central low rainfall), and East Chapman (northern low rainfall) in Western Australia. The pseudothecia matured on residues at different times after harvest in various regions. In general, pseudothecia maturity occurred earlier in the high-rainfall areas than in medium- and low-rainfall areas. An ascospore discharge pattern was investigated from residues of crop from the previous year (6-month-old residues) at three locations-Mount Barker, Wongan Hills, and East Chapman in Western Australia-and from 18-month-old residues that were burnt and raked in the previous year at Mount Barker and East Chapman. Ascospore discharge commenced earlier in high-rainfall (>450 mm) areas (Mount Barker) and late in northern low-rainfall (<325 mm) areas (East Chapman). The major ascospore showers took place during May (late autumn) and June (early winter) at Mount Barker and during July and August (mid- to late winter) at East Chapman. The number of ascospores discharged was extremely low at East Chapman compared with Mount Barker. At both locations, the number of ascospores discharged from 18-month-old residues that were raked and burnt in the previous year were only approximately 10% of those discharged from previous years residues left undisturbed. The discharge of ascospores on any given day was negatively correlated with accumulated temperatures, maximum temperature, evaporation, minimum and maximum soil temperatures, and solar radiation and was positively correlated with the minimum temperature, rain, and minimum relative humidity. This is the first report describing how pseudothecia mature on residues in different rainfall areas in Western Australia, and it potentially can be used in developing a forecasting system to avoid the synchronization of major ascospore showers with the maximum susceptibility period of canola seedlings.

G1 Blackspot Manager model predicts the maturity and release of ascospores in relation to ascochyta blight on field pea

A simple model, G1 Blackspot Manager, has been developed to predict the seasonal pattern of release of ascospores in relation to ascochyta blight in field pea. The model considers a combination of two weather factors, daily mean temperature and daily total rainfall, to drive progress of maturity of pseudothecia on infested field pea stubble from past crops. Each day is categorised as suitable or not suitable for continuation of the maturation process. The onset of pseudothecial maturity has been found to take place when approximately ten suitable days have occurred. Following the onset of maturity, ascospore release is triggered when daily rainfall exceeds a threshold. The model was satisfactorily calibrated using three datasets from Western Australia. The calibrated model performed well when independently tested with 21 datasets, 17 from Western Australia and 4 from South Australia. It is concluded that G1 Blackspot Manager model has the potential to be used to formulate sowing guides for field pea in southern Australia that minimise the risk of ascochyta blight.

Temporal Patterns of Ascospore Release in Leptosphaeria maculans Vary Depending on Geographic Region and Time of Observation

Diurnal patterns of spore release have been observed in a number of fungal pathogens that undergo wind-assisted dispersal. The mechanisms that drive these patterns, while not well understood, are thought to relate to the ability of dispersing spores to survive their journey and infect new hosts. In this paper, we characterise the diurnal pattern of ascospore release by a Western Australian population of Leptosphaeria maculans. Although L. maculans has been previously shown to exhibit diurnal patterns of ascospore release, these patterns appear to vary from region to region. In order to characterise the pattern of release in the Mediterranean climate of Western Australia, we analysed historical data describing the bi-hourly count of airborne ascospores at Mt Barker, Western Australia. Results of this analysis showed diurnal patterns that differ from those previously observed in other countries, with ascospore release in our study most likely to occur in the afternoon. Furthermore, we found that the time of peak release can shift from month to month within any one season, and from year to year. In explaining the hourly pattern of spore release over an entire season, time since rainfall, time since last release, temperature, hour and month were all shown to be significant variables.

Impact of climate change in relation to ascochyta blight on field pea in Western Australia

Using a weather-based model, the G2 Blackspot Manager, the impact of climate change was studied in relation to a major disease of field pea, ascochyta blight, in three different field pea growing locations of Western Australia: Esperance, Lake Grace and Merredin representing high, medium and low rainfall zones. The model was run with weather data for two 30-year periods: the period centering on 1990 (termed as “current climate”) and another centering on 2050 (termed as “future climate”). The model outputs were summarised as the epidemic-initiating ascospore-load that crops would be exposed to, disease severity, and yield loss in relation to nine times of sowing within the current sowing-window of field pea crops in Western Australia. Results show a decreased pressure of ascospore-load across the sowing-window in all three locations because of changed summer conditions (more rainy days in conjunction with higher temperatures) under future climate, which could be translated as lower disease severity compared to the current climate. The relationship between disease severity and time of sowing showed a significant decrease (P ≤ 0.05) in the intercept of the regression lines for future climate compared to current climate in all three locations, but there was no significant difference between the slopes of the regression lines. This indicated a decreased initial disease pressure for future climate compared to the current. When the impact was assessed in terms of yield loss, results in Lake Grace, in contrast to Esperance and Merredin, showed insignificant difference between current and future climates. This was a consequence of the projected dry-finishing conditions of cropping seasons, the number of which could increase two-fold in the projected future climate. It is concluded that any decrease in ascochyta blight severity as a result of climate change would most likely be location-specific.

G2 Blackspot Manager model to guide field pea sowing for southern Australia in relation to ascochyta blight disease

G2 Blackspot Manager, the second generation (G2) of Blackspot Manager model, predicts disease severity and yield loss in addition to quantified release of seasonal ascospores in relation to ascochyta blight on field pea. The model predicts the disease severity with respect to the expected exposure of field pea crop to ascospores of D. pinodes, with yield loss subsequently related to the disease severity. Both the relationships were developed using published and unpublished data under southern Australian conditions. The model has been used as a decision support tool for developing a field pea sowing guide considering weather-based disease risk and abiotic risk. This paper presents the field pea sowing guide for South Australia, Victoria and Western Australia for the 2010 season and compares it with 2009. The guide is dynamic as the disease severity changes with seasonal weather conditions and is updated weekly starting around mid-April, being delivered principally via the web (http://www.agric.wa.gov.au/cropdisease). The paper also discusses other means of communicating the guide to the stakeholders of southern Australia.