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

The 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.

Evaluation of field pea germplasm against rust disease caused by Uromyces viciae fabae De Bary in glass house and field conditions

Seventy three germplasm of field pea were tested under glasshouse and field condition against rust disease caused by Uromyces viciae fabae (Pers.) de Bary. Among screened germplasms, 30 susceptible, 40 highly susceptible and 3 belonged to moderately resistance group. The susceptible germplasm showed leaf area with symptoms (LAS) ranged from 30 to 65% with area under disease progressive curve (AUDPC) values from 77.5 to 1290 and apparent infection rate from 0.0134 to 0.1698 and highly susceptible germplasm showed LAS ranged from 60 to 95% with AUDPC values ranged from 1075 to 2179. Apparent infection rate ranged from 0.0616 to 0.6950 while moderately resistance germplasm showed LAS ranged from 20 to 24% with AUDPC values ranged from 350 to 438 and apparent infection rate ranged from 0.1180 to 0.1198 in field as well as glasshouse conditions. The moderate resistance germplasm JPF 99025, KPMR 615 and KPMR 551showed lowest LAS, AUDPC value and apparent infection rate, hence, these germplasms could be used in breeding programme.

High rates of infection by blood parasites during the nestling phase in UK Columbids with notes on ecological associations

SUMMARYStudies of blood parasite infection in nestling birds rarely find a high prevalence of infection. This is likely due to a combination of short nestling periods (limiting the age at which nestlings can be sampled) and long parasite prepatent periods before gametocytes can be detected in peripheral blood. Here we examine rates of blood parasite infection in nestlings from three Columbid species in the UK. We use this system to address two key hypotheses in the epidemiology of avian haemoparasites: first, that nestlings in open nests have a higher prevalence of infection; and second, that nestlings sampled at 14 days old have a higher apparent infection rate than those sampled at 7 days old. Open-nesting individuals had a 54% infection rate compared with 25% for box-nesters, probably due to an increased exposure of open-nesting species to dipteran vectors. Nestlings sampled at 14 days had a 68% infection rate compared with 32% in nestlings sampled at 7 days, suggesting that rates of infection in the nest are high. Further work should examine nestlings post-fledging to identify rates of successful parasite infection (as opposed to abortive development within a dead-end host) as well as impacts on host post-fledging survival and behaviour.

Simulation of Apparent Infection Rate to Predict Severity of Soybean Rust Using a Fuzzy Logic System

Few biologically based models to assess the risk of soybean rust have been developed because of difficulty in estimating variables related to infection rate of the disease. A fuzzy logic system, however, can estimate apparent infection rate by combining meteorological variables and biological criteria pertinent to soybean rust severity. In this study, a fuzzy logic apparent infection rate (FLAIR) model was developed to simulate severity of soybean rust and validated using data from field experiments on two soybean cultivars, TK 5 and G 8587. The FLAIR model estimated daily apparent infection rate of soybean rust and simulated disease severity based on population dynamics. In weekly simulation, the FLAIR model explained >85% of variation in disease severity. In simulation of an entire epidemic period, the FLAIR model was able to predict disease severity accurately once initial values of disease severity were predicted accurately. Our results suggest that a model could be developed to determine apparent infection rate and an initial value of disease severity in advance using forecasted weather data, which would provide accurate prediction of severity of soybean rust before the start of a season.

Effect of nitrogen fertilization on the expression of slow-blasting resistance in rice

The development of rice blast disease in four slow-blasting (SB) genotypes was compared with that in the fast-blasting (FB) genotype Karuna, under natural field epidemics over a period of 3 years at five levels of nitrogen, in order to determine if the application of high doses of nitrogen influenced the expression of disease progress in the SB types. The treatment effects were compared through estimation of nine parameters viz. (i) lesion number (LN); (ii) area under disease progress curve (AUDPC); (iii) relative area under disease progress curve (RAUDPC); (iv) logistic apparent infection rate (r); (v) Gompertz apparent infection rate (k); (vi) logit line intercept (logit-a); (vii) gompit line intercept (gompit-a); (viii) time required for the disease to reach 0·25 severity in logistic (T25r); and (ix) Gompertz (T25k) models. There was a significant increase in LN, AUDPC, RAUDPC, r and k with increased levels of nitrogen application in all genotypes, but the rate of increase in disease severity was much lower in SB genotypes than the FB one and did not lead to breakdown of resistance in the SB genotypes, since severity level was much below the economic injury level. Among the nine derived parameters for evaluation of resistance LN, AUDPC, RAUDPC, r and k were best. The AUDPC and RAUDPC had lower degrees of error variance compared with the other parameters and hence were considered superior measures for characterization of disease progress curves.

Influence of Host Diversity on Development of Epidemics: An Evaluation and Elaboration of Mixture Theory

A spatiotemporal/integro-difference equation model was developed and utilized to study the progress of epidemics in spatially heterogeneous mixtures of susceptible and resistant host plants. The effects of different scales and patterns of host genotypes on the development of focal and general epidemics were investigated using potato late blight as a case study. Two different radial Laplace kernels and a two-dimensional Gaussian kernel were used for modeling the dispersal of spores. An analytical expression for the apparent infection rate, r, in general epidemics was tested by comparison with dynamic simulations. A genotype connectivity parameter, q, was introduced into the formula for r. This parameter quantifies the probability of pathogen inoculum produced on a certain host genotype unit reaching the same or another unit of the same genotype. The analytical expression for the apparent infection rate provided accurate predictions of realized r in the simulations of general epidemics. The relationship between r and the radial velocity of focus expansion, c, in focal epidemics, was linear in accordance with theory for homogeneous genotype mixtures. The findings suggest that genotype mixtures that are effective in reducing general epidemics of Phytophthora infestans will likewise curtail focal epidemics and vice versa.

A MODEL FOR OPTIMAL CHEMICAL CONTROL OF LEAF AREA DAMAGED BY FUNGI POPULATION — PARAMETER DEPENDENCE

We present a model to study a fungi population submitted to chemical control, incorporating the fungicide application directly into the model. From that, we obtain an optimal control strategy that minimizes both the fungicide application (cost) and leaf area damaged by fungi population during the interval between the moment when the disease is detected (t=0) and the time of harvest (t=tf). Initially, the parameters of the model are considered constant. Later, we consider the apparent infection rate depending on the time (and the temperature) and do some simulations to illustrate and to compare with the constant case.