scholarly journals Spatiotemporal Characterization of Sclerotinia Crown Rot Epidemics in Pyrethrum

Plant Disease ◽  
2014 ◽  
Vol 98 (2) ◽  
pp. 267-274 ◽  
Author(s):  
Jason B. Scott ◽  
David H. Gent ◽  
Sarah J. Pethybridge ◽  
Frank S. Hay
Keyword(s):  
Plant Density ◽  
Disease Incidence ◽  
Severe Disease ◽  
Disease Outbreaks ◽  
Spatial Aggregation ◽  
Crown Rot ◽  
Sampling Unit ◽  
Small Scale ◽  
Unit Scale ◽  
Substantial Decline

Sclerotinia crown rot, caused by Sclerotinia minor and S. sclerotiorum, is a disease of pyrethrum in Australia that may cause substantial decline in plant density. The spatiotemporal characteristics of the disease were quantified in 14 fields during three growing seasons. Fitting the binary power law to disease incidence provided slope (b = 1.063) and intercept (ln(Ap) = 0.669) estimates significantly (P ≤ 0.0001) greater than 1 and 0, respectively, indicating spatial aggregation at the sampling unit scale that was dependent upon disease incidence. Covariate analyses indicated that application of fungicides did not significantly influence these estimates. Spatial autocorrelation and spatial analysis by distance indices indicated that spatial aggregation above the sampling unit scale was limited to 20 and 17% of transects analyzed, respectively. The range of significant aggregation was limited primarily to neighboring sampling units only. Simple temporal disease models failed to adequately describe disease progress, due to a decline in disease incidence in spring. The relationships between disease incidence at the scales of individual plants within quadrats and quadrats within a field was modeled using four predictors of sample size. The choice of the specific incidence–incidence relationship influenced the classification of disease incidence as greater than or less than 2% of plants, a provisional commercial threshold for fungicide application. Together, these studies indicated that epidemics of Sclerotinia crown rot were dominated by small-scale aggregation of disease. Larger scale patterns of diseased plants, when present, were associated with severe disease outbreaks. The spatial and temporal analyses were suggestive of disease epidemics being associated with localized primary inoculum and other factors that favor disease development at a small scale.

scholarly journals Spatial Pattern Analysis of Hop Powdery Mildew in the Pacific Northwest: Implications for Sampling

2004 ◽  
Vol 94 (10) ◽  
pp. 1116-1128 ◽  
Author(s):  
William W. Turechek ◽  
Walter F. Mahaffee
Keyword(s):  
Powdery Mildew ◽  
Spatial Pattern ◽  
Pacific Northwest ◽  
Disease Incidence ◽  
Sampling Unit ◽  
Small Scale ◽  
Effective Sample Size ◽  
Ratio Test ◽  
The Pacific ◽  
Unit Scale

The spatial pattern of hop powdery mildew was characterized using 3 years of disease incidence data collected in commercial hop yards in the Pacific Northwest. Yards were selected randomly from yards with a history of powdery mildew, and two to five rows were selected for sampling within each yard. The proportion of symptomatic leaves out of 10 was determined from each of N sampling units in a row. The binomial and the beta-binomial frequency distributions were fit to the N sampling units observed in each row and to ΣN sampling units observed in each yard. Distributional analyses indicated that disease incidence was better characterized by the beta-binomial than the binomial distribution in 25 and 47% of the data sets at the row and yard scales, respectively, according to a log-likelihood ratio test. Median values of the beta-binomial parameter θ, a measure of small-scale aggregation, were near 0 at both sampling scales, indicating that disease incidence was close to being randomly distributed. The variability in disease incidence among rows sampled in the same yard generally increased with mean incidence at the yard scale. Spatial autocorrelation analysis, used to measure large-scale patterns of aggregation, indicated that disease incidence was not correlated between sampling units over several lag distances. Results of a covariance analysis showed that heterogeneity of disease incidence was not dependent upon cultivar, region, or time of year when sampling was conducted. A hierarchical analysis showed that disease incidence at the sampling unit scale (proportion of sampling units with one or more diseased leaves) increased as a saturation-type curve with respect to incidence at the leaf level and could be described by a binomial function modified to account for the effects of heterogeneity through an effective sample size. Use of these models permits sampling at the sampling unit scale while allowing inferences to be made at the leaf scale. Taken together, hop powdery mildew was nearly randomly distributed with no discernable foci, suggesting epidemics are initiated from a well-distributed or readily dispersible overwintering population. Implications for sampling are discussed.

scholarly journals Crop Damage from Sclerotinia Crown Rot and Risk Factors in Pyrethrum

Plant Disease ◽  
2014 ◽  
Vol 98 (1) ◽  
pp. 103-111 ◽  
Author(s):  
Jason B. Scott ◽  
David H. Gent ◽  
Sarah J. Pethybridge ◽  
Tim Groom ◽  
Frank S. Hay
Keyword(s):  
Risk Factors ◽  
Disease Incidence ◽  
Negative Relationship ◽  
Disease Outbreaks ◽  
Early Spring ◽  
Crown Rot ◽  
Crop Damage ◽  
Current Season ◽  
Canopy Density ◽  
Flower Yield

Sclerotinia crown rot, caused by Sclerotinia sclerotiorum and S. minor, is a prevalent disease in pyrethrum fields in Australia. Management involves fungicide applications during the rosette stage of plant development from autumn to early spring in fields approaching first harvest. However, estimates of crop damage and the efficacy of these tactics are poorly understood; therefore, plots were established in 86 pyrethrum fields in Tasmania, Australia during 2010 to 2012 to quantify these and to identify risk factors for disease outbreaks. On average, commercial management for Sclerotinia crown rot reduced disease incidence 43 to 67% compared with nontreated plots. There was a weak but significant relationship between relative increase in flower yield when fungicides were applied and the incidence of crown rot (R2 = 0.09, P = 0.006), although the mean number of flowers produced was similar regardless of fungicide applications. Flower yield was positively associated with canopy density in spring (S = 0.39, P = 0.001). Moreover, canopy density in spring was linked by both direct and indirect effects to canopy density during autumn and winter which, in turn, were associated with planting date and previous rain events. Modeling canopy density and disease incidence in autumn correctly categorized disease incidence in spring relative to a threshold of 2% in 72% of fields. In a subset of 22 fields monitored over 2 years, canopy density in the autumn following the first harvest had a negative relationship with Sclerotinia crown rot incidence the preceding year (R2 = 0.23, P = 0.006). On average, however, current commercial management efforts provided only small increases in flower yield in the current season and appear best targeted to fields with well-developed plant canopies and Sclerotinia crown rot present during early autumn.

Sources of Alternaria carthami inoculum in safflower

1987 ◽  
Vol 27 (1) ◽  
pp. 149 ◽  
Author(s):  
KJ Jackson ◽  
JAG Irwin ◽  
JE Berthelsen
Keyword(s):  
Seed Germination ◽  
Disease Incidence ◽  
Severe Disease ◽  
Disease Outbreaks ◽  
Safflower Seed ◽  
Seed Infection ◽  
Inoculum Sources ◽  
Alternaria Leaf Blight ◽  
Seed Health ◽  
Healthy Seed

Spread of the disease Alternaria leaf blight (Alternaria carthami) from infected safflower seed and stubble was studied at Biloela in central Queensland to determine the importance ofthese inoculum sources in the initiation of epidemics. Seed infection levels of 20-55% resulted in 1.4-2.0% emerged diseased seedlings in the field. Levels of 1.0% seed infection have previously caused severe disease outbreaks in commercial crops. Visual appraisal of seed health correlated highly with laboratory, glasshouse and field assessments of diseased seedlings. Glasshouse assessment of emerged diseased seedlings gave the best indication of expected disease incidence in the field. Seed germination in the laboratory correlated poorly with emergence in the glasshouse and the field. Incidence of A. carthami on seedlings following soil incorporation of diseased stubble in November 1977 diminished from 28% in May 1978 to 0% in September 1980. Burning of diseased stubble in November 1977 failed to eliminate the disease, but reduced the number of emerged disease seedlings by 66% in May 1978. Dusting of healthy seed with a fungicide increased total emergence, but it did not control the spread of the fungus from the infected stubble as emergence of diseased seedlings was also increased.

scholarly journals A Generalized Linear Modeling Approach for Characterizing Disease Incidence in a Spatial Hierarchy

2003 ◽  
Vol 93 (4) ◽  
pp. 458-466 ◽  
Author(s):  
W. W. Turechek ◽  
L. V. Madden
Keyword(s):  
Curve Fitting ◽  
Linear Models ◽  
Nonlinear Models ◽  
Disease Incidence ◽  
Sampling Unit ◽  
Effective Sample Size ◽  
Linear Modeling ◽  
Unit Scale ◽  
Spatial Hierarchy ◽  
The Relationship

Several statistical models are introduced to quantify the effect of heterogeneity on disease incidence relationships in a three-scale spatial hierarchy: the sampling unit level (highest), the leaf scale (intermediate), and the leaflet scale (lowest). The models are an extension of the theory previously developed for a two-scale hierarchy and were tested using data collected from strawberry leaf blight epidemics. Disease incidence at the sampling-unit scale (proportion of sampling units with one or more diseased leaflets) increased as a saturation-type curve with increasing leaflet or leaf disease incidence (proportion of leaflets or leaves diseased) as predicted by the good fit of the beta-binomial distribution to the leaflet and leaf data. The relationship could be accurately described, without curve fitting, by several simple nonlinear models, in which the aggregation of disease was represented by a modified binomial function incorporating an effective sample size that was either constant or dependent on mean incidence. The relationship between incidence at the leaflet and leaf scales could be modeled based on the combined sampling-unit models for leaflets and leaves. By taking the complementary log-log (CLL) transformation of incidence, the equations could be expressed as generalized linear models, and curve fitting used to estimate the parameters. Generally, curve fitting gave slight to no improvement in the accuracy of the predictions of incidence. These models have broad applicability in sampling for disease incidence, and results can be used to interpret how diseased individuals at the lowest level in a hierarchy are arranged within sampling units.

scholarly journals Twenty-Five Years of the Binary Power Law for Characterizing Heterogeneity of Disease Incidence

2018 ◽  
Vol 108 (6) ◽  
pp. 656-680 ◽  
Author(s):  
L. V. Madden ◽  
G. Hughes ◽  
W. Bucker Moraes ◽  
X.-M. Xu ◽  
W. W. Turechek
Keyword(s):  
Spatial Heterogeneity ◽  
Power Law ◽  
Disease Incidence ◽  
Plant Diseases ◽  
Stochastic Simulations ◽  
Sampling Unit ◽  
Small Scale ◽  
Parameter Estimates ◽  
Quarter Century ◽  
Wide Range

Spatial pattern, an important epidemiological property of plant diseases, can be quantified at different scales using a range of methods. The spatial heterogeneity (or overdispersion) of disease incidence among sampling units is an especially important measure of small-scale pattern. As an alternative to Taylor’s power law for the heterogeneity of counts with no upper bound, the binary power law (BPL) was proposed in 1992 as a model to represent the heterogeneity of disease incidence (number of plant units diseased out of n observed in each sampling unit, or the proportion diseased in each sampling unit). With the BPL, the log of the observed variance is a linear function of the log of the variance for a binomial (i.e., random) distribution. Over the last quarter century, the BPL has contributed to both theory and multiple applications in the study of heterogeneity of disease incidence. In this article, we discuss properties of the BPL and use it to develop a general conceptualization of the dynamics of spatial heterogeneity in epidemics; review the use of the BPL in empirical and theoretical studies; present a synthesis of parameter estimates from over 200 published BPL analyses from a wide range of diseases and crops; discuss model fitting methods, and applications in sampling, data analysis, and prediction; and make recommendations on reporting results to improve interpretation. In a review of the literature, the BPL provided a very good fit to heterogeneity data in most publications. Eighty percent of estimated slope (b) values from field studies were between 1.06 and 1.51, with b positively correlated with the BPL intercept parameter. Stochastic simulations show that the BPL is generally consistent with spatiotemporal epidemiological processes and holds whenever there is a positive correlation of disease status of individuals composing sampling units.

scholarly journals Cultivar and Spacing Effects on Transmission of Phytophthora parasitica in an Ebb-and-Flow Subirrigation System

Plant Disease ◽  
1997 ◽  
Vol 81 (1) ◽  
pp. 89-95 ◽  
Author(s):  
Stephen S. Strong ◽  
Bridget K. Behe ◽  
C. Fred Deneke ◽  
Kira L. Bowen ◽  
Gary J. Keever
Keyword(s):  
Catharanthus Roseus ◽  
Disease Incidence ◽  
Severe Disease ◽  
Disease Development ◽  
Phytophthora Parasitica ◽  
Spacing Effects ◽  
Ebb And Flow

Phytophthora parasitica was transmitted within 6 weeks from vinca (Catharanthus roseus) plants growing in infested potting mix, on the drain end of ebb-and-flow benches, to plants in noninfested potting mix. Transmission of Phytophthora was very low when potting mix was not pasteurized. When potting mix was steam pasteurized, infection of plants, disease incidence, and severity increased with time and decreased with distance from plants in infested pots. The cultivar Pretty in Pink was more susceptible to infection by P. parasitica than cv. Peppermint Cooler, allowing more rapid and severe disease development as well as pathogen dissemination and transmission. Pot spacing did not significantly affect transmission of P. parasitica on an ebb-and-flow bench.

scholarly journals The Role of Traditional Livelihood Practices and Local Ethnobotanical Knowledge in Mitigating Chestnut Disease and Pest Severity in Turkey

Forests ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 571 ◽  
Author(s):  
Jeffrey Wall ◽  
Coşkun Köse ◽  
Nesibe Köse ◽  
Taner Okan ◽  
Elif Başak Aksoy ◽  
...  
Keyword(s):  
Biological Diversity ◽  
Multiple Correspondence Analysis ◽  
Disease Outbreaks ◽  
Agroforestry Systems ◽  
Anthropogenic Factors ◽  
Small Scale ◽  
Multiple Factor Analysis ◽  
Tree Health ◽  
Chestnut Tree ◽  
Maintenance Of Diversity

The European chestnut population is enduring multiple compounding exotic pest and disease outbreaks across Turkey. The deeply held value of the chestnut species for the Turkish public is reflected in substantial government conservation programming. Chestnut is predominantly found on state land managed by Turkey’s General Directorate of Forestry (GDF), which generally upholds restrictive policies for chestnut-related livelihood practices other than nut collection and beehive placement. Such policies are justified by a government position that human activities and presence is likely to worsen disease dynamics. Conversely, a growing body of research findings testify that small-scale livelihood practices maintain biological diversity and, furthermore, that this traditional maintenance of diversity has been correlated with decreased pathogen pressure within agroecosystems. However, few studies have investigated this phenomenon in the context of agroforestry systems. At a global ecological moment of increasingly pervasive and severe exotic forest pathogen impact, this paper investigates the influence of diverse small-scale livelihood practices and knowledge on chestnut tree health across the highly heterogenous geography of Turkey. We conducted ethnobotanical questionnaires with 96 chestnut-utilizing households, and chestnut tree health evaluations in georeferenced forest areas they identified, throughout Turkey’s Black Sea, Marmara, and Aegean regions. Using data from 1500 trees, we characterized the effects of subsequently recorded environmental, physiological, and anthropogenic factors on tree health using multiple correspondence analysis (MCA), multiple factor analysis (MFA), and mixed models. Our results show that the traditional human management of tree physiology and ecology has a significant positive effect on tree health, especially through the acts of grafting and culling as well as the maintenance of diversity. We argue that conceptualizing such livelihood systems as human niche construction and maintenance can help forest management agencies to better understand and conserve valuable landscapes, even in increasingly common periods of severe pathogenic pressure.

STUDIES OF CROWN ROT OF APPLE TREES

1942 ◽  
Vol 20c (9) ◽  
pp. 457-490 ◽  
Author(s):  
Maurice F. Welsh
Keyword(s):  
Soil Moisture ◽  
Apple Tree ◽  
Disease Incidence ◽  
Antagonistic Effect ◽  
Crown Rot ◽  
Phytophthora Cactorum ◽  
Additional Information ◽  
Two Factors ◽  
Below Ground ◽  
Old Trees

The form of apple tree crown rot that occurs in the irrigated orchards of British Columbia is confined to the below-ground bark tissues of the tree. It has been encountered in trees of all ages and of all the commercial varieties.Proof is given that this crown rot is caused by the fungus Phytophthora cactorum (L. & C.) Schroet. Typical symptoms of the disease have been reproduced in over 200 trees of various ages as a result of their inoculation with this fungus. Isolation has been possible only from the margins of active lesions, and has proved difficult even from these tissues. There is evidence that the activity of P. cactorum is inhibited in rotted tissues by the antagonistic effect of one or more secondary organisms.The influence of soil moisture and temperature on disease incidence has been studied by field observations and by the inoculation of two-year—old trees under controlled conditions in Wisconsin tank equipment in the greenhouse. The effects of these two factors seem to be interrelated, with the highest incidence of disease in an almost saturated soil at the highest temperature imposed, 32 °C. The influence of soil moisture is exerted particularly in the subsoil, rather than in the locus of crown rot attack.Certain varieties of apple have been found to vary in their resistance to crown rot. Deep wounds have proved necessary to allow entry of the fungus into bark tissues.The additional information now available is being utilized in a search for improved means of combating the disease.

scholarly journals Finite Symmetries in Agent-Based Epidemic Models

2019 ◽  
Vol 24 (2) ◽  
pp. 44 ◽  
Author(s):  
Gilberto M. Nakamura ◽  
Ana Carolina P. Monteiro ◽  
George C. Cardoso ◽  
Alexandre S. Martinez
Keyword(s):  
Population Size ◽  
Transition Matrix ◽  
Large Scale ◽  
Initial Conditions ◽  
Disease Outbreaks ◽  
Epidemic Models ◽  
Small Scale ◽  
Stochastic Effects ◽  
Agent Based ◽  
Computational Performance

Predictive analysis of epidemics often depends on the initial conditions of the outbreak, the structure of the afflicted population, and population size. However, disease outbreaks are subjected to fluctuations that may shape the spreading process. Agent-based epidemic models mitigate the issue by using a transition matrix which replicates stochastic effects observed in real epidemics. They have met considerable numerical success to simulate small scale epidemics. The problem grows exponentially with population size, reducing the usability of agent-based models for large scale epidemics. Here, we present an algorithm that explores permutation symmetries to enhance the computational performance of agent-based epidemic models. Our findings bound the stochastic process to a single eigenvalue sector, scaling down the dimension of the transition matrix to o ( N 2 ) .

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