scholarly journals Comparative Analysis of Flexible Two-Parameter Models of Plant Disease Epidemics

2007 ◽  
Vol 97 (10) ◽  
pp. 1231-1244 ◽  
Author(s):  
B. Hau ◽  
E. Kosman
Keyword(s):  
Differential Equations ◽  
Goodness Of Fit ◽  
Inflection Point ◽  
Plant Disease ◽  
Shape Parameter ◽  
Relative Rate ◽  
Data Sets ◽  
Temporal Position ◽  
Progress Curve ◽  
Disease Epidemics

Eleven previously published models of plant disease epidemics, given as differential equations with a rate and a shape parameter, are compared using general model characteristics as well as their usefulness in fitting observed data. Six out of the eleven models can be solved analytically resulting in epidemic growth functions, while the others can be solved only numerically. When all 11 differential equations were fitted to two data sets, all models showed a similar goodness of fit, although the shape parameter in some models could not be estimated very precisely. With respect to useful characteristics (exponential population growth at the beginning, ability to generate monomolecular disease progression, and flexibility of the inflection point), the models of Fleming, Kosman-Levy, Birch, Richards and Waggoner, and Rich are recommended. Formulas were established to calculate the point of inflection as well as the weighted absolute and relative rate, respectively, depending on the shape and rate parameter. These formulas allow transformation of the parameter values of one model into those of another model in many cases. If the two models are required to have the same temporal position of the disease progress curve, then the initial disease level at the start of the epidemic or the time when the inflection point is reached have to be transformed.

scholarly journals A General Model for the Effect of Crop Management on Plant Disease Epidemics at Different Scales of Complexity

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 462
Author(s):  
Elisa González-Domínguez ◽  
Giorgia Fedele ◽  
Francesca Salinari ◽  
Vittorio Rossi
Keyword(s):  
Plant Disease ◽  
Secondary Infection ◽  
Crop Management ◽  
Cropping System ◽  
Policy Makers ◽  
Plant Parts ◽  
Management Actions ◽  
Progress Curve ◽  
Epidemic Development ◽  
Disease Epidemics

A general and flexible model was developed to simulate progress over time of the epidemics caused by a generic polycyclic pathogen on aerial plant parts. The model includes all of the epidemiological parameters involved in the pathogen life cycle: between-season survival, production of primary inoculum, occurrence of primary infections, production and dispersal of secondary inoculum both inside and outside the crop, and concatenation of secondary infection cycles during the host’s growing season. The model was designed to include the effect of the main crop management actions that affect disease levels in the crop. Policy-oriented, strategic, and tactical actions were considered at the different levels of complexity (from the agro-ecosystem to the farming and cropping system). All effects due to disease management actions were translated into variations in the epidemiological components of the model, and the model quantitatively simulates the effect of these actions on epidemic development, expressed as changes in final disease and in the area under the disease progress curve. The model can help researchers, students and policy makers understand how management decisions (especially those commonly recommended as part of Integrated Pest Management programs) will affect plant disease epidemics at different scales of complexity.

scholarly journals Analysis of Summer Epidemic Progress of Apple Scab at Different Apple Production Systems in the Netherlands and Hungary

2005 ◽  
Vol 95 (9) ◽  
pp. 1001-1020 ◽  
Author(s):  
I. J. Holb ◽  
B. Heijne ◽  
J. C. M. Withagen ◽  
J. M. Gáll ◽  
M. J. Jeger
Keyword(s):  
Factor Analysis ◽  
The Netherlands ◽  
Inflection Point ◽  
Production Systems ◽  
Disease Incidence ◽  
Relative Rate ◽  
Apple Scab ◽  
Disease Progress ◽  
Progress Curve ◽  
Apple Production

Two, 4-year studies on summer epidemic progress of apple scab were conducted at Randwijk, the Netherlands, from 1998 until 2001 and at Eperjeske, Hungary, from 2000 until 2003. Disease assessments were made on scab-susceptible cv. Jonagold. A range of nonlinear growth functions were fitted to a total of 96 disease progress curves (3 treatment classes × 2 plant parts × 2 disease measures × 4 years × 2 locations) of apple scab incidence and severity. The three-parameter logistic model gave the most consistent fit across three treatment classes in the experiment (integrated, organic-sprayed, and organic-unsprayed). Parameters estimated or calculated from the three-parameter logistic function were used to analyze disease progress. These were disease incidence and severity on the day of the first assessment (Ys); final disease incidence or upper asymptote for incidence (Yif) or severity (Ysf); fruit incidence and severity on day 40, after which no new lesions on fruits appeared (Y40); leaf incidence and severity on day 75, at which shoot growth stopped (Y 75); relative (β) and “absolute” (θ) rates of disease progress; inflection point (M); and area under the disease progress curve (AUDPCS) standardized by the duration of the total epidemic. Comparisons among disease progress curves were made by correlation and factor analysis followed by Varimax rotation. There were large differences but high positive correlations among the parameters Ys, Yf, θ, and AUDPCS across the three treatment classes. In the factor analysis, two factors accounted for more than 85% of the total variance for both incidence and severity. Factor 1 gave an overall description of epidemic progress of both scab incidence and severity and included the parameters Yf, Y40, Y75, θ, and AUDPCS. Factor 2 identified a relationship between the relative rate parameter (β) and the inflection point (M) for severity and a relationship between disease incidence and severity. For an integrated or an organic orchard, θ, AUDPCS, and one of Yf or Y75 (because of the link with host phenology) can characterize apple scab epidemics during summer. Based on these findings, improved scab management approaches were provided for integrated and organic apple production systems.

scholarly journals Goodness-of-Fit Tests for Bivariate Time Series of Counts

Econometrics ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 10
Author(s):  
Šárka Hudecová ◽  
Marie Hušková ◽  
Simos G. Meintanis
Keyword(s):  
Goodness Of Fit ◽  
Probability Generating Function ◽  
Parametric Bootstrap ◽  
Real Data ◽  
Data Sets ◽  
Test Statistics ◽  
Finite Sample ◽  
Generalized Poisson ◽  
Goodness Of Fit Tests ◽  
Monte Carlo Experiments

This article considers goodness-of-fit tests for bivariate INAR and bivariate Poisson autoregression models. The test statistics are based on an L2-type distance between two estimators of the probability generating function of the observations: one being entirely nonparametric and the second one being semiparametric computed under the corresponding null hypothesis. The asymptotic distribution of the proposed tests statistics both under the null hypotheses as well as under alternatives is derived and consistency is proved. The case of testing bivariate generalized Poisson autoregression and extension of the methods to dimension higher than two are also discussed. The finite-sample performance of a parametric bootstrap version of the tests is illustrated via a series of Monte Carlo experiments. The article concludes with applications on real data sets and discussion.

scholarly journals A Hypothesis Test for the Goodness-of-Fit of the Marginal Distribution of a Time Series with Application to Stablecoin Data

2021 ◽  
Vol 5 (1) ◽  
pp. 10
Author(s):  
Mark Levene
Keyword(s):  
Time Series ◽  
Goodness Of Fit ◽  
Marginal Distribution ◽  
Hypothesis Test ◽  
Data Sets ◽  
Test Statistic ◽  
Sample Test ◽  
Kolmogorov Smirnov ◽  
Heavy Tailed ◽  
Jensen Shannon Divergence

A bootstrap-based hypothesis test of the goodness-of-fit for the marginal distribution of a time series is presented. Two metrics, the empirical survival Jensen–Shannon divergence (ESJS) and the Kolmogorov–Smirnov two-sample test statistic (KS2), are compared on four data sets—three stablecoin time series and a Bitcoin time series. We demonstrate that, after applying first-order differencing, all the data sets fit heavy-tailed α-stable distributions with 1<α<2 at the 95% confidence level. Moreover, ESJS is more powerful than KS2 on these data sets, since the widths of the derived confidence intervals for KS2 are, proportionately, much larger than those of ESJS.

scholarly journals Optimal Control of Plant Disease Epidemics with Clean Seed Usage

2021 ◽  
Vol 83 (5) ◽  
Author(s):  
F. M. Hamelin ◽  
B. Bowen ◽  
P. Bernhard ◽  
V. A. Bokil
Keyword(s):  
Optimal Control ◽  
Plant Disease ◽  
Clean Seed ◽  
Disease Epidemics

scholarly journals An Improved Approach for Reduction of Defect Density Using Optimal Module Sizes

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Dinesh Verma ◽  
Shishir Kumar
Keyword(s):  
Goodness Of Fit ◽  
Defect Density ◽  
Optimal Size ◽  
Data Sets ◽  
Density Parameter ◽  
Proposed Model ◽  
Module Size ◽  
Curve Fitting Method ◽  
Improved Model ◽  
Effective Distribution

Nowadays, software developers are facing challenges in minimizing the number of defects during the software development. Using defect density parameter, developers can identify the possibilities of improvements in the product. Since the total number of defects depends on module size, so there is need to calculate the optimal size of the module to minimize the defect density. In this paper, an improved model has been formulated that indicates the relationship between defect density and variable size of modules. This relationship could be used for optimization of overall defect density using an effective distribution of modules sizes. Three available data sets related to concern aspect have been examined with the proposed model by taking the distinct values of variables and parameter by putting some constraint on parameters. Curve fitting method has been used to obtain the size of module with minimum defect density. Goodness of fit measures has been performed to validate the proposed model for data sets. The defect density can be optimized by effective distribution of size of modules. The larger modules can be broken into smaller modules and smaller modules can be merged to minimize the overall defect density.

Quantifying paleogeography using biogeography: a test case for the Ordovician and Silurian of Avalonia based on brachiopods and trilobites

Paleobiology ◽  
2002 ◽  
Vol 28 (3) ◽  
pp. 343-363 ◽  
Author(s):  
David C. Lees ◽  
Richard A. Fortey ◽  
L. Robin M. Cocks
Keyword(s):  
Goodness Of Fit ◽  
Total Evidence ◽  
Pairwise Distance ◽  
Test Case ◽  
Data Sets ◽  
Plate Tectonic ◽  
Plate Model ◽  
Optimal Arrangement ◽  
Evidence Analysis ◽  
Better Than

Despite substantial advances in plate tectonic modeling in the last three decades, the postulated position of terranes in the Paleozoic has seldom been validated by faunal data. Fewer studies still have attempted a quantitative approach to distance based on explicit data sets. As a test case, we examine the position of Avalonia in the Ordovician (Arenig, Llanvirn, early Caradoc, and Ashgill) to mid-Silurian (Wenlock) with respect to Laurentia, Baltica, and West Gondwana. Using synoptic lists of 623 trilobite genera and 622 brachiopod genera for these four plates, summarized as Venn diagrams, we have devised proportional indices of mean endemism (ME, normalized by individual plate faunas to eliminate area biogeographic effects) and complementarity (C) for objective paleobiogeographic comparisons. These can discriminate the relative position of Avalonia by assessing the optimal arrangement of inter-centroid distances (measured as great circles) between relevant pairs of continental masses. The proportional indices are used to estimate the “goodness-of-fit” of the faunal data to two widely used dynamic plate tectonic models for these time slices, those of Smith and Rush (1998) and Ross and Scotese (1997). Our faunal data are more consistent with the latter model, which we use to suggest relationships between faunal indices for the five time slices and new rescaled inter-centroid distances between all six plate pairs. We have examined linear and exponential models in relation to continental separation for these indices. For our generic data, the linear model fits distinctly better overall. The fits of indices generated by using independent trilobite and brachiopod lists are mostly similar to each other at each time slice and for a given plate, reflecting a common biogeographic signal; however, the indices vary across the time slices. Combining groups into the same matrix in a “total evidence” analysis performs better still as a measure of distance for mean endemism in the “Scotese” plate model. Four-plate mean endemism performs much better than complementarity as an indicator of pairwise distance for either plate model in the test case.

scholarly journals Radiation damage effects on protein conformation at room temperature and 100K

2014 ◽  
Vol 70 (a1) ◽  
pp. C344-C344
Author(s):  
Silvia Russi ◽  
Shawn Kann ◽  
Henry van den Bedem ◽  
Ana M. González
Keyword(s):  
Data Collection ◽  
Radiation Damage ◽  
Crystal Structures ◽  
Room Temperature ◽  
Relative Rate ◽  
Absorbed Dose ◽  
Conformational Ensemble ◽  
Data Sets ◽  
Cryogenic Temperatures ◽  
Full Data

Protein crystallography data collection at synchrotrons today is routinely carried out at cryogenic temperatures to mitigate radiation damage to the crystal. Although damage still takes place, at 100 K and below, the immobilization of free radicals increases the lifetime of the crystals by orders of magnitude. Increasingly, experiments are carried out at room temperature. The lack of adequate cryo-protectants, the induced lattice changes or internal disorders during the cooling process, and the convenience of collecting data directly from the crystallization plates, are some of the reasons. Moreover, recent studies have shown that flash-freezing affects the conformational ensemble of crystal structures [1], and can hide important functional mechanisms from observation [2]. While there has been a considerable amount of effort in studying radiation damage at cryo-temperatures, its effects at room temperature are still not well understood. We investigated the effects of data collection temperature on secondary local damage to the side chain and main chain from different proteins. Data were collected from crystals of thaumatin and lysozyme at 100 K and room temperature. To carefully control the total absorbed dose, full data sets at room temperature were assembled from a few diffraction images per crystal. Several data sets were collected at increasing levels of absorbed dose. Our analysis shows that while at cryogenic temperatures, radiation damage increases the conformational variability, _x0004_at room temperature it has the opposite effect_x0005_. We also observed that disulfide bonds appear to break up at a different relative rate at room temperature, perhaps because of a more active repair mechanism. Our analysis suggests that elevated conformational heterogeneity in crystal structures at room temperature is observed despite radiation damage, and not as a result thereof.

scholarly journals Banana Moko disease management with resistance inducers and chlorine dioxide

2015 ◽  
Vol 33 (2) ◽  
pp. 194-202
Author(s):  
Joaquín Guillermo Ramírez G. ◽  
Melissa Muñoz A. ◽  
Luis Fernando Patiño H. ◽  
Juan Gonzalo Morales O.
Keyword(s):  
Methyl Jasmonate ◽  
Chlorine Dioxide ◽  
Plant Disease ◽  
Sodium Salicylate ◽  
Bacterial Disease ◽  
Disease Development ◽  
Musa Sp ◽  
Progress Curve ◽  
Potassium Phosphite ◽  
Resistance Inducers

The plant disease Moko, caused by Ralstonia solanacearum, is the most important bacterial disease in banana and plantain crops worldwide. In the present study, chlorine dioxide and seven resistance inducers in banana plants (Musa sp.) infected with this bacterium were evaluated under greenhouse conditions. For the evaluation of chlorine dioxide, three doses were used (10, 30 and 50 mg L-1). The evaluation of the resistance inducers included the following: sodium salicylate 0.4 g L-1; hydrogen peroxide 1 mM; potassium phosphite 1.5 mL L-1; 3-aminobutanoic acid 1.0 g L-1; methyl jasmonate 0.2 g L-1; acibenzolar-s-methyl 0.3 mL L-1 and chitosan 3.0 mg mL-1. The results showed a significant reduction of 74% in the area under the disease progress curve (AUDPC) value, which was calculated for the disease development when the injected chlorine dioxide dose was 50 mg L-1. The AUDPC value for the resistance inducers was reduced by 45.4% for chitosan, 75.5% for methyl jasmonate and 65.5% for 3-aminobutanoic acid. Therefore, the results indicated that these molecules have the potential to be used for control of the Moko disease.

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