scholarly journals Peach Rusty Spot Epidemics: Management with Fungicide, Effect on Fruit Growth, and the Incidence-Lesion Density Relationship

Plant Disease ◽  
2003 ◽  
Vol 87 (12) ◽  
pp. 1477-1486 ◽  
Author(s):  
Laura A. Furman ◽  
Norman Lalancette ◽  
James F. White
Keyword(s):  
Disease Incidence ◽  
Exponential Model ◽  
Rapid Decline ◽  
Model Parameters ◽  
Data Sets ◽  
Progress Curve ◽  
Significant Seasonal Variation ◽  
Density Relationship ◽  
Parameter Values ◽  
The Relationship

Different numbers of consecutive fungicide applications, beginning at petal fall and continuing into the summer, were examined for their effect on rusty spot epidemics. Disease progressions for each fungicide level were quantified by fitting either the logistic or monomolecular model. When the weighted absolute infection rate (ρ) and maximum disease level (Kmax) parameters were expressed as functions of the number of applications, the logistic decline model provided the best fit for five of six data sets. This model described a gradual decrease in ρ and Kmax in response to the initial fungicide application, a rapid decline in parameter values with the addition of one or two applications, and a diminished parameter response as fungicide applications continued toward the end of the epidemic. Based on examination of model behavior across all 3 years of the study, adequate management was achieved with a total of three to five fungicide applications. Additional analyses of area under the disease progress curve and final disease intensity at harvest supported these results and indicated that further reduction in fungicide usage may be possible. Unlike earlier findings, rusty spot did not significantly decrease fruit volume or weight at midseason or at harvest; as lesion density increased, fruit volume remained constant. The relationship between disease incidence and lesion density within any given year was best explained by the zero-intercept version of the exponential model. However, comparison of model parameters across years revealed significant seasonal variation. Nevertheless, the incidence-lesion density relationships were fairly uniform across years at incidence values below 0.5, where lesion density increased gradually and in a near-linear fashion.

scholarly journals Cotton resistance to ramulose and variability of Colletotrichum gossypii f. sp. cephalosporioides

2006 ◽  
Vol 32 (1) ◽  
pp. 9-15 ◽  
Author(s):  
Jefferson Fernandes do Nascimento ◽  
Laércio Zambolim ◽  
Francisco Xavier Ribeiro do Vale ◽  
Paulo Geraldo Berger ◽  
Paulo Roberto Cecon
Keyword(s):  
Disease Severity ◽  
Disease Incidence ◽  
Disease Index ◽  
Mato Grosso ◽  
Progress Curve ◽  
Commercial Cultivars ◽  
Resistant Group ◽  
The Relationship ◽  
Highly Virulent ◽  
Susceptible Group

Four cultivars and 21 lines of cotton were evaluated for resistance to ramulose (Colletotrichum gossypii f. sp. cephalosporioides) in a field where the disease is endemic. The seeds of each genotype were planted in 5 x 5 m plots with three replications. The lines CNPA 94-101 and 'CNPA Precoce 2'were used as standard susceptible and resistant references, respectively. The disease incidence (DI) was calculated from the proportion of diseased plants in the plot. The disease index (DIn) was calculated from the disease severity using a 1 to 9 scale, and was evaluated at weekly intervals starting 107 days after emergence. The data collected was used to calculate the area under disease progress curve (AUDPC). In general, the DIn increased linearly with time and varied from 20.0 to 57.1 and AUDPC from 567 to 1627 among the genotypes which could be clustered in to two distinct groups. The susceptible group contained two cultivars and nine lines and the resistant group contained one cultivar and 12 lines. The relationship between disease index and evaluation times was linear for the 25 genotypes tested. The line CNPA 94-101, used as susceptible standard, was the most susceptible with an average DI = 83.4, DIn = 57.1 and AUDPC = 1627.7. The line CNPA 96-08 with DI = 37.8, DIn = 20.0 and AUDPC = 567.7 was the most resistant one. Among the commercial cultivars 'IAC 22' was the most susceptible and 'CNPA Precoce 2', used as resistant standard was the most resistant. The variability in virulence of the pathogen was studied by spray inoculating nine genotypes with conidial suspensions (10(5)/mL) of either of the 10 isolates. The disease severity was evaluated 30 days later using a scale of 1 to 5. The virulence of the isolate was expressed by DIn. All the isolates were highly virulent but their virulence avaried for several genotypes and could be clustered in two distinct groups of less and more virulent isolates. The isolate MTRM 14 from Mato Grosso was the least virulent while Minas Gerais was the most virulent, with DIn of 6.36 and 46.47, respectively. In this experiment the line HR 102 and the cultivar 'Antares' were the most resistant ones with DIns of 18.32 and 19.14, respectively.

Is there a relationship between the behaviour of beef cattle and emissions of methane and ammonia from feedlot systems?

2009 ◽  
Vol 2009 ◽  
pp. 101-101
Author(s):  
S Muir ◽  
M Bai ◽  
Z Loh ◽  
J Hill ◽  
D Chen ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Production Systems ◽  
Animal Behaviour ◽  
Rapid Decline ◽  
Data Sets ◽  
Northern Australia ◽  
Grazing Cattle ◽  
Early Afternoon ◽  
The Relationship ◽  
Animal Production Systems

Associations between animal behaviour and emissions of methane (CH4) and ammonia (NH3) have been noted in studies of grazing cattle (Lockyer, 1997) and feedlot confined cattle (Harper et al., 1999, Flesch et al., 2007). Methane emissions have been predicted as being greatest during bouts of rumination (Harper et al., 1999) whereas the emissions of the indirect greenhouse gas ammonia tends to be low early in the morning but increasing rapidly in the early afternoon after which a rapid decline until sunset (Flesch et al., 2007). With the exception of Harper et al., (1999) there are few complete data sets that examine the interaction between animal behaviour and greenhouse gas emissions from intensive animal production systems. The current study aimed to investigate the relationship between animal behaviour and emissions of CH4 and NH3 in a beef feedlot system in northern Australia.

scholarly journals Spatial Pattern of Strawberry Powdery Mildew (Podosphaera aphanis) and Airborne Inoculum

Plant Disease ◽  
2014 ◽  
Vol 98 (1) ◽  
pp. 43-54 ◽  
Author(s):  
H. Van der Heyden ◽  
M. Lefebvre ◽  
L. Roberge ◽  
L. Brodeur ◽  
O. Carisse
Keyword(s):  
Powdery Mildew ◽  
Power Law ◽  
Negative Binomial Distribution ◽  
Binomial Distribution ◽  
Negative Binomial ◽  
Disease Incidence ◽  
Data Sets ◽  
Incidence Data ◽  
Airborne Inoculum ◽  
The Relationship

The relationship between strawberry powdery mildew and airborne conidium concentration (ACC) of Podosphaera aphanis was studied using data collected from 2006 to 2009 in 15 fields, and spatial pattern was described using 2 years of airborne inoculum and disease incidence data collected in fields planted with the June-bearing strawberry (Fragaria × ananassa) cultivar Jewel. Disease incidence, expressed as the proportion of diseased leaflets, and ACC were monitored in fields divided into 3 × 8 grids containing 24 100 m2 quadrats. Variance-to-mean ratio, index of dispersion, negative binomial distribution, Poisson distribution, and binomial and beta-binomial distributions were used to characterize the level of spatial heterogeneity. The relationship between percent leaf area diseased and daily ACC was linear, while the relationship between ACC and disease incidence followed an exponential growth curve. The V/M ratios were significantly greater than 1 for 100 and 96% of the sampling dates for ACC sampled at 0.35 m from the ground (ACC0.35m) and for ACC sampled at 1.0 m from the ground (ACC1.0m), respectively. For disease incidence, the index of dispersion D was significantly greater than 1 for 79% of the sampling dates. The negative binomial distribution fitted 86% of the data sets for both ACC1.0m and ACC0.35m. For disease incidence data, the beta-binomial distribution provided a good fit of 75% of the data sets. Taylor's power law indicated that, for ACC at both sampling heights, heterogeneity increased with increasing mean ACC, whereas the binary form of the power law suggested that heterogeneity was not dependent on the mean for disease incidence. When the spatial location of each sampling location was taken into account, Spatial Analysis by Distance Indices showed low aggregation indices for both ACCs and disease incidence, and weak association between ACC and disease incidence. Based on these analyses, it was found that the distribution of strawberry powdery mildew was weakly aggregated. Although a higher level of heterogeneity was observed for airborne inoculum, the heterogeneity was low with no distinct foci, suggesting that epidemics are induced by well-distributed inoculum. This low level of heterogeneity allows mean airborne inoculum concentration to be estimated using only one sampler per field with an overall accuracy of at least 0.841. The results obtained in this study could be used to develop a sampling scheme that will improve strawberry powdery mildew risk estimation.

scholarly journals GRS1915+105: a comparison of the plateau state to the canonical hard state

2010 ◽  
Vol 6 (S275) ◽  
pp. 294-298 ◽  
Author(s):  
Pieter van Oers ◽  
Sera Markoff
Keyword(s):  
Black Hole ◽  
Near Infrared ◽  
Model Parameters ◽  
Data Sets ◽  
X Ray ◽  
Black Hole Binaries ◽  
Hard State ◽  
Multi Wavelength ◽  
Plateau State ◽  
The Relationship

AbstractGRS 1915+105 is a very peculiar black hole binary that exhibits accretion-related states that are not observed in any other stellar-mass black hole system. One of these states, however – referred to as the plateau state – may be related to the canonical hard state of black hole X-ray binaries. Both the plateau and hard state are associated with steady, relatively lower X-ray emission and flat/inverted radio emission, that is sometimes resolved into compact, self-absorbed jets. To investigate the relationship between the plateau and the hard state, we fit two multi-wavelength observations using a steady-state outflow-dominated model, developed for hard state black hole binaries. The data sets consist of quasi-simultaneous observations in radio, near-infrared and X-ray bands. Interestingly, we find both significant differences between the two plateau states, as well as between the best-fit model parameters and those representative of the hard state. We discuss our interpretation of these results, and the possible implications for GRS 1915+105's relationship to canonical black hole candidates.

scholarly journals Modelling to Engineering Data Using a New Class of Continuous Models

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
I. Elbatal ◽  
Naif Alotaibi
Keyword(s):  
Real Data ◽  
Exponential Model ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Simple Type ◽  
Data Sets ◽  
New Class ◽  
Engineering Data ◽  
Continuous Models ◽  
Mathematical Characteristics

In this paper, a new flexible generator of continuous lifespan models referred to as the Topp-Leone Weibull G (TLWG) family is developed and studied. Several mathematical characteristics have been investigated. The new hazard rate of the new model can be “monotonically increasing,” “monotonically decreasing,” “bathtub,” and “J shape.” The Farlie Gumbel Morgenstern (FGM) and the modified FGM (MFGM) families and Clayton Copula (CCO) are used to describe and display simple type Copula. We discuss the estimation of the model parameters by the maximum likelihood (MLL) estimations. Simulations are carried out to show the consistency and efficiency of parameter estimates, and finally, real data sets are used to demonstrate the flexibility and potential usefulness of the proposed family of algorithms by using the TLW exponential model as example of the new suggested family.

scholarly journals Population Pharmacodynamic Modeling Using the Sigmoid Emax Model: Influence of Inter-individual Variability on the Steepness of the Concentration–Effect Relationship. a Simulation Study

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
Johannes H. Proost ◽  
Douglas J. Eleveld ◽  
Michel M. R. F. Struys
Keyword(s):  
Binary Data ◽  
Drug Effect ◽  
Individual Variability ◽  
Concentration Effect ◽  
Pharmacodynamic Modeling ◽  
Model Parameters ◽  
Data Sets ◽  
Effect Relationship ◽  
Multiple Data Sets ◽  
The Relationship

AbstractThe relationship between the concentration of a drug and its pharmacological effect is often described by empirical mathematical models. We investigated the relationship between the steepness of the concentration–effect relationship and inter-individual variability (IIV) of the parameters of the sigmoid Emax model, using the similarity between the sigmoid Emax model and the cumulative log-normal distribution. In addition, it is investigated whether IIV in the model parameters can be estimated accurately by population modeling. Multiple data sets, consisting of 40 individuals with 4 binary observations in each individual, were simulated with varying values for the model parameters and their IIV. The data sets were analyzed using Excel Solver and NONMEM. An empirical equation (Eq. (11)) was derived describing the steepness of the population-predicted concentration–effect profile (γ*) as a function of γ and IIV in C50 and γ, and was validated for both binary and continuous data. The tested study design is not suited to estimate the IIV in C50 and γ with reasonable precision. Using a naive pooling procedure, the population estimates γ* are significantly lower than the value of γ used for simulation. The steepness of the population-predicted concentration–effect relationship (γ*) is less than that of the individuals (γ). Using γ*, the population-predicted drug effect represents the drug effect, for binary data the probability of drug effect, at a given concentration for an arbitrary individual.

scholarly journals Relationships Between Incidence and Severity of Fusarium Head Blight on Winter Wheat in Ohio

2005 ◽  
Vol 95 (9) ◽  
pp. 1049-1060 ◽  
Author(s):  
P. A. Paul ◽  
S. M. El-Allaf ◽  
P. E. Lipps ◽  
L. V. Madden
Keyword(s):  
Fusarium Head Blight ◽  
Prediction Interval ◽  
Disease Incidence ◽  
Disease Assessment ◽  
Data Sets ◽  
Head Blight ◽  
Incidence Data ◽  
Treatment Comparisons ◽  
Time Required ◽  
The Relationship

To determine the relationship between incidence (I; proportion of diseased spikes) and severity (S; mean proportion of diseased spikelets per spike) for Fusarium head blight of wheat and to determine if severity could be predicted reliably from incidence data, disease assessments were made visually at multiple sample sites in artificially and naturally inoculated research and production fields between 1999 and 2002. Ten distinct data sets were collected. Mean disease intensity ranged from 0.023 to 0.975 for incidence and from 0.0003 to 0.808 for severity. A model based on complementary log-log transformation of incidence and severity performed well for all data sets, based on calculated coefficients of determination and random residual plots. The I-S relationship was consistent among years and locations, with similar slopes for all data sets. For 7 of the 10 data sets and for the pooled data from all locations and years, the estimated slope from the fit of the model ranged from 1.03 to 1.26. Time of disease assessment affected the relationship between incidence and severity; however, the estimated slopes from each assessment time were also close to 1. Based on the width of the 95% prediction interval, severity was estimated more precisely at lower incidence values than at higher values. The number of sampling units and the index of dispersion of disease incidence had only minor effects on the precision with which S was predicted from I. The estimation of mean S from I would substantially reduce the time required to assess Fusarium head blight in field surveys and treatment comparisons, and the observed relationship between I and S could be used to identify genotypes with some types of disease resistance.

Evaluating the utility of gravity gradient tensor components

Geophysics ◽  
2014 ◽  
Vol 79 (1) ◽  
pp. G1-G14 ◽  
Author(s):  
Mark Pilkington
Keyword(s):  
Gravity Gradient ◽  
Directional Sensitivity ◽  
Model Parameters ◽  
Data Sets ◽  
Model Errors ◽  
Gravity Response ◽  
Quantitative Rating ◽  
Text Ranking ◽  
Body Shapes ◽  
The Relationship

Gravity gradiometry allows individual components and combinations of components to be used in interpretation. Knowledge of the information content of different components and their combinations is therefore crucial to their effectiveness, and a quantitative rating of information level is needed to guide the choice. To this end, I use linear inverse theory to examine the relationship between the different tensor components and combinations thereof and the model parameters to be determined. The model used is a rectangular prism, characterized by seven parameters: the prism location [Formula: see text], [Formula: see text]; its width [Formula: see text] and breadth [Formula: see text]; the density [Formula: see text]; the depth to top [Formula: see text]; and thickness [Formula: see text]. Varying these values allows a variety of body shapes, e.g., blocks, plates, dykes, and rods, to be considered. The Jacobian matrix, which relates parameters and their associated gravity response, clarifies the importance and stability of model parameters in the presence of data errors. In general, for single tensor components and combinations, the progression from well to poorly determined parameters follows the trend of [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], to [Formula: see text]. Ranking the estimated model errors from a range of models showed that data sets consisting of concatenated components produced the smallest parameter errors. For data sets comprising combined tensor components, the invariants of the tensor produced the smallest parameter errors. Of the single tensor components, [Formula: see text] gave the best performance overall, but those single components with strong directional sensitivity can produce some individual parameters with smaller estimated errors (e.g., [Formula: see text] and [Formula: see text] estimated from [Formula: see text]).

scholarly journals On the exponent in the Von Bertalanffy growth model

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4205 ◽  
Author(s):  
Katharina Renner-Martin ◽  
Norbert Brunner ◽  
Manfred Kühleitner ◽  
Werner Georg Nowak ◽  
Klaus Scheicher
Keyword(s):  
Optimal Parameter ◽  
Growth Function ◽  
Model Parameters ◽  
Data Sets ◽  
Scaling Exponent ◽  
Von Bertalanffy ◽  
Large Variability ◽  
Metabolic Scaling ◽  
Main Observation ◽  
Parameter Values

Von Bertalanffy proposed the differential equation m′(t) = p × m(t)a − q × m(t) for the description of the mass growth of animals as a function m(t) of time t. He suggested that the solution using the metabolic scaling exponent a = 2/3 (Von Bertalanffy growth function VBGF) would be universal for vertebrates. Several authors questioned universality, as for certain species other models would provide a better fit. This paper reconsiders this question. Based on 60 data sets from literature (37 about fish and 23 about non-fish species) it optimizes the model parameters, in particular the exponent 0 ≤ a < 1, so that the model curve achieves the best fit to the data. The main observation of the paper is the large variability in the exponent, which can vary over a very large range without affecting the fit to the data significantly, when the other parameters are also optimized. The paper explains this by differences in the data quality: variability is low for data from highly controlled experiments and high for natural data. Other deficiencies were biologically meaningless optimal parameter values or optimal parameter values attained on the boundary of the parameter region (indicating the possible need for a different model). Only 11 of the 60 data sets were free of such deficiencies and for them no universal exponent could be discerned.

Generalized Flexible Weibull Extension Distribution

2017 ◽  
Vol 2 (4) ◽  
pp. 68-75
Author(s):  
Zubair Ahmad ◽  
Brikhna Iqbal
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Real Data ◽  
Likelihood Method ◽  
Model Parameters ◽  
Data Sets ◽  
Suggested Model ◽  
Proposed Model ◽  
Parameter Values ◽  
Family Of Distributions

In this article, a four parameter generalization of the flexible Weibull extension distribution so-called generalized flexible Weibull extension distribution is studied. The proposed model belongs to T-X family of distributions proposed by Alzaatreh et al. [5]. The suggested model is much flexible and accommodates increasing, unimodal and modified unimodal failure rates. A comprehensive expression of the numerical properties and the estimates of the model parameters are obtained using maximum likelihood method. By appropriate choice of parameter values the new model reduces to four sub models. The proposed model is illustrated by means of three real data sets.

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