scholarly journals Analysis and simulation of plant disease progress curves in R: introducing the epifitter package

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Kaique S. Alves ◽  
Emerson M. Del Ponte
Keyword(s):  
Plant Disease ◽  
Temporal Analysis ◽  
R Package ◽  
Desktop Computer ◽  
Disease Epidemiology ◽  
Disease Progress Curve ◽  
Disease Progress ◽  
Progress Curve ◽  
Data User ◽  
Population Dynamics Models

AbstractThe analysis of the disease progress curves (DPCs) is central to understanding plant disease epidemiology. The shape of DPCs can vary significantly and epidemics can be better understood and compared with an appropriate depiction and analysis. This paper introduces epifitter, an open-source tool developed in R for aiding in the simulation and analysis of DPC data. User-level functions were developed and their use is demonstrated to the reader using actual disease progress curve data for facilitating the conduction of several tasks, including (a) simulation of synthetic DPCs using four population dynamics models (exponential, monomolecular, logistic, and Gompertz); (b) calculation of the areas under disease progress curve and stairs; (c) fitting and ranking the four above-mentioned models to single or multiple DPCs; and (d) generation and customization of graphs. The package requires the installation of R in any desktop computer and the scripted analysis can be fully documented, reproduced, and shared. The epifitter R package provides a flexible suite for temporal analysis of epidemics that is useful for both research and teaching purposes.

scholarly journals Management of Daylily Rust With Different Fungicides and Fungicide Combinations

2017 ◽  
Vol 18 (3) ◽  
pp. 162-165 ◽  
Author(s):  
Robert S. Emmitt ◽  
James W. Buck
Keyword(s):  
United States ◽  
Disease Management ◽  
Disease Severity ◽  
Low Cost ◽  
Single Application ◽  
Southeast United States ◽  
Disease Progress Curve ◽  
Disease Progress ◽  
Progress Curve ◽  
Disease Pressure

Production nurseries and daylily hybridizers in the southeast United States rely on the use of fungicides to manage daylily rust, caused by the fungus Puccinia hemerocallidis. Foliar sprays of pyraclostrobin, flutolanil, tebuconazole, myclobutanil, chlorothalonil, mancozeb, pyraclostrobin + boscalid, flutolanil + tebuconazole, flutolanil + myclobutanil, flutolanil + chlorothalonil, and flutolanil + mancozeb applied on 14-day intervals, and a nontreated control, were evaluated under high disease pressure at three locations in Griffin, GA, in 2015. Tebuconazole or the tebuconazole + flutolanil treatment consistently had the lowest area under the disease progress curve (AUDPC) of the treatments. The addition of flutolanil to chlorothalonil or mancozeb did not improve rust control and no difference in disease severity was observed in any treatment containing contact fungicides on all assessment dates. Single application costs ranged from $10.21 to $95.96 with tebuconazole providing excellent disease management at a relatively low cost per application ($13.90).

scholarly journals Estimation of a Time-varying Apparent Infection Rate from Plant Disease Progress Curves: A Particle Filter Approach

2019 ◽  
Author(s):  
Kaique dos S Alves ◽  
Willian B Moraes ◽  
Wellington B da Silva ◽  
Emerson M Del Ponte
Keyword(s):  
Particle Filter ◽  
Infection Rate ◽  
Plant Disease ◽  
Host Susceptibility ◽  
Time Varying ◽  
Factors Affecting ◽  
Initial Inoculum ◽  
Disease Progress ◽  
Progress Curve ◽  
Apparent Infection Rate

AbstractThe parameters of the simplest (two-parameter) epidemiological models that best fit plant disease progress curve (DPC) data are the surrogate for initial inoculum (y0) and the (constant) apparent infection rate (r), both being useful for understanding, predicting and comparing epidemics. The assumption thatris constant is not reasonable and fluctuations are expected due to systematic changes in factors affecting infection (e.g. weather favorability, host susceptibility, etc.), thus leading to a time-varyingr, orr(t). An arrangement of these models (e.g. logistic, monomolecular, etc.) can be used to obtainrbetween two time points, given the disease (y) data are available. We evaluated a data assimilation technique, Particle Filter (PF), as an alternative method for estimatingr(t). Synthetic DPC data for a hypothetical polycyclic epidemics were simulated using the logistic differential equation for scenarios that combined five patterns ofr(t) (constant, increasing, decreasing, random or sinusoidal); five increasing time assessment interval (Δt= 1, 3, 5, 7 or 9 time units - t.u.); and two levels of noise (α = 0.1 or 0.25) assigned toy(t). The analyses of 50 simulated 60-t.u. DPCs showed that the errors of PF-derivedwere lower (RMSE < 0.05) for Δt< 5 t.u. and least affected by the presence of noise in the measure compared with the logit-derivedr(t). The ability to more accurately estimater(t) using the novel method may be useful to increase knowledge of field epidemics and identify within-season drivers that may explainr(t) behaviour.

scholarly journals Temporal progress of southern rust in maize under different environmental conditions

2003 ◽  
Vol 28 (3) ◽  
pp. 273-278 ◽  
Author(s):  
Cláudia V. Godoy ◽  
Lílian Amorim ◽  
Armando Bergamin Filho ◽  
Herbert P. Silva ◽  
Willian J. Silva ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Disease Severity ◽  
Logistic Model ◽  
Inflection Point ◽  
Gompertz Model ◽  
Disease Progress Curve ◽  
Disease Progress ◽  
Progress Curve ◽  
Puccinia Polysora ◽  
The Mean

The progress of the severity of southern rust in maize (Zea mays) caused by Puccinia polysora was quantified in staggered plantings in different geographical areas in Brazil, from October to May, over two years (1995-1996 and 1996-1997). The logistic model, fitted to the data, better described the disease progress curves than the Gompertz model. Four components of the disease progress curves (maximum disease severity; area under the disease progress curve, AUDPC; area under the disease progress curve around the inflection point, AUDPCi; and epidemic rate) were used to compare the epidemics in different areas and at different times of planting. The AUDPC, AUDPCi, and the epidemic rate were analyzed in relation to the weather (temperature, relative humidity, hours of relative humidity >90%, and rainfall) and recorded during the trials. Disease severity reached levels greater than 30% in Piracicaba and Guaíra in the plantings between December and January. Lower values of AUDPC occurred in later plantings at both locations. The epidemic rate was positively correlated (P < 0.05) with the mean daily temperatures and negatively correlated with hours of relative humidity >90%. The AUDPC was not correlated with any weather variable. The AUDPCi was negatively related to both variables connected to humidity, but not to rain. Long periods (mostly >13 h day-1) of relative humidity >90% (that corresponded to leaf wetness) occurred in Castro. Severity of southern rust in maize has always been low in Castro, thus the negative correlations between disease and the two humidity variables.

scholarly journals Fungicides for Control of Downy Mildew on Pickling Cucumber in Michigan

2019 ◽  
Vol 20 (3) ◽  
pp. 165-169 ◽  
Author(s):  
Katelyn E. Goldenhar ◽  
Mary K. Hausbeck
Keyword(s):  
Downy Mildew ◽  
Untreated Control ◽  
Field Studies ◽  
Pseudoperonospora Cubensis ◽  
Relative Area ◽  
Disease Progress Curve ◽  
Cucurbit Downy Mildew ◽  
Disease Progress ◽  
Pickling Cucumber ◽  
Progress Curve

Michigan growers rely on fungicides to limit cucurbit downy mildew (CDM), incited by Pseudoperonospora cubensis; resistance of the pathogen to fungicides is a concern. We evaluated fungicides against CDM in Michigan field studies from 2015 to 2017. According to the relative area under the disease progress curve (rAUDPC), in 2015, mandipropamid, propamocarb, fluxapyroxad/pyraclostrobin, copper octanoate, and dimethomorph resulted in disease levels similar to the control. These treatments, along with cymoxanil, were similar to the control in 2016. Fungicides that were ineffective during 2015 and 2016 did not limit CDM in 2017. Famoxadone/cymoxanil and fluopicolide did not limit CDM in 2017. Each year, the following treatments were similar for disease based on rAUDPC data: oxathiapiprolin applied alone or premixed with chlorothalonil or mandipropamid, ametoctradin/dimethomorph, fluazinam, mancozeb/zoxamide, cyazofamid, and ethaboxam. An exception occurred in 2017, when ethaboxam was less effective than fluazinam, oxathiapiprolin/chlorothalonil, and oxathiapiprolin/mandipropamid. Mancozeb and chlorothalonil treatments were similar in 2015 and 2017, according to rAUDPC data. In 2017, yields were increased for oxathiapiprolin/chlorothalonil, oxathiapiprolin/mandipropamid, mancozeb, ametoctradin/dimethomorph, mancozeb/zoxamide, ethaboxam, cyazofamid, chlorothalonil, and fluazinam compared with the untreated control.

scholarly journals Stability of Slow-Rusting Resistance to Puccinia asparagi and Managing Rust in Asparagus

Plant Disease ◽  
2012 ◽  
Vol 96 (7) ◽  
pp. 997-1000 ◽  
Author(s):  
Dennis A. Johnson
Keyword(s):  
Irrigation Management ◽  
Field Trials ◽  
Disease Progress Curve ◽  
Resistant Cultivars ◽  
Disease Progress ◽  
Slow Rusting ◽  
South Central ◽  
Progress Curve ◽  
The Stability

The stability of slow-rusting resistance to Puccinia asparagi in several asparagus cultivars was evaluated in two replicated field trials. Rust epidemics were monitored in each trial for 8 years spanning a period of 13 years (1983–1990 and 1987–1995). Inoculum of P. asparagi, an autoecious macrocyclic rust, originated each year as teliospores. In the first trial, the cultivars Jersey Titan, Jersey Centennial, Jersey Giant, Delmonte-361, and UC-157 had consistently lower area under the disease progress curve (AUDPC) values than Wash T2 and WSU-1. Cultivar Mary Washington was intermediate between the two groups of resistant and susceptible cultivars in 6 of 8 years. Jersey Titan consistently ranked number 1 for resistance with the lowest AUDPC values all 8 years. In the second trial, Jersey Giant, Delmonte-361, and UC-157 had consistently lower AUDPC values than Larac, Gynlim, Cito, Largo 17-3, and Franklim in each of 8 years. Jersey Giant, Delmonte-361, and UC-157 always ranked low (1, 2, or 3) for AUDPC. A shift from rust-susceptible to rust-resistant asparagus cultivars began in central Washington around 1996. In 2011, resistant cultivars made up nearly 96% of the asparagus plantings. From 1996 to 2011, rust was not considered a problem in commercial fields with slow-rusting resistant cultivars. Use of durable, slow-rusting cultivars, along with sanitation practices that reduced levels of aecia in nonharvested nurseries and on volunteer asparagus plants and judicious irrigation management, has effectively managed asparagus rust in commercial fields for at least 29 years in south-central Washington.

scholarly journals SAMPLE SIZE FOR ASSESS THE LEAF BLAST SEVERITY IN EXPERIMENTS WITH IRRIGATED RICE

2016 ◽  
Vol 29 (4) ◽  
pp. 822-831 ◽  
Author(s):  
BRUNO GIACOMINI SARI ◽  
ALESSANDRO DAL'COL LÚCIO ◽  
IVAN FRANCISCO DRESSLER DA COSTA ◽  
ANA LÚCIA DE PAULA RIBEIRO
Keyword(s):  
Spatial Distribution ◽  
Sample Size ◽  
Negative Binomial ◽  
Leaf Blast ◽  
Disease Progress Curve ◽  
Disease Progress ◽  
Progress Curve ◽  
Morisita Index ◽  
Rice Leaf Blast ◽  
Severity Of The Disease

ABSTRACT The aim of this study was to determine the sample size needed to assess the severity of leaf blast in rice in experiments with different fungicide treatments. The severity and the area under the disease progress curve data of three chemical disease control treatments carried out in Rio Grande do Sul, were used in the study. Analysis of variance was performed to verify whether the severity of the disease differed between treatments. The spread of disease was was also found to be different between treatments and assessments, using the variance/mean ratio and Morisita index. The spatial distribution of the disease among the treatments and during the evaluations is important for the choice of the equation used to calculate the sample size. The spatial distribution of the disease was not the same across the experiments, and it varied between treatments and evaluations. Thus, we decided to use a formula that was not associated with distributions to indicate the spatial distribution (negative binomial or Poisson) of the disease in the field. The sample size to estimate the average of rice leaf blast severity varied between treatments and evaluations. The area under the disease progress curve is necessary to be determined to reduce the number of samples needed. Thus, it is recommended to assess 293 sheets to estimate severity, and 63 to estimate AUDPC at 20% error.

scholarly journals The Area Under the Disease Progress Stairs: Calculation, Advantage, and Application

2012 ◽  
Vol 102 (4) ◽  
pp. 381-389 ◽  
Author(s):  
Ivan Simko ◽  
Hans-Peter Piepho
Keyword(s):  
Real Data ◽  
Disease Progress Curve ◽  
Disease Progress ◽  
Multiple Observations ◽  
Progress Curve ◽  
New Formula

The area under the disease progress curve (AUDPC) is frequently used to combine multiple observations of disease progress into a single value. However, our analysis shows that this approach severely underestimates the effect of the first and last observation. To get a better estimate of disease progress, we have developed a new formula termed the area under the disease progress stairs (AUDPS). The AUDPS approach improves the estimation of disease progress by giving a weight closer to optimal to the first and last observations. Analysis of real data indicates that AUDPS outperforms AUDPC in most of the tested trials and may be less precise than AUDPC only when assessments in the first or last observations have a comparatively large variance. We propose using AUDPS and its standardized (sAUDPS) and relative (rAUDPS) forms when combining multiple observations from disease progress experiments into a single value.

Disease Progress Curve Parameters Help to Characterise the Types of Resistance to Late Blight Segregating in Cultivated Potato

2013 ◽  
Vol 56 (2) ◽  
pp. 99-114 ◽  
Author(s):  
Sylvie Marhadour ◽  
Roland Pellé ◽  
Jean-Marc Abiven ◽  
Frédérique Aurousseau ◽  
Hervé Dubreuil ◽  
...  
Keyword(s):  
Late Blight ◽  
Disease Progress Curve ◽  
Cultivated Potato ◽  
Disease Progress ◽  
Progress Curve
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