L. V. Madden

Nonparametric Analysis of Ordinal Data in Designed Factorial Experiments

ABSTRACT Plant disease severity often is assessed using an ordinal rating scale rather than a continuous scale of measurement. Although such data usually should be analyzed with nonparametric methods, and not with the typical parametric techniques (such as analysis of variance), limitations in the statistical methodology available had meant that experimental designs generally could not be more complicated than a one-way layout. Very recent advancements in the theoretical formulation of hypotheses and associated test statistics within a nonparametric framework, together with development of software for implementing the methods, have made it possible for plant pathologists to analyze properly ordinal data from more complicated designs using nonparametric techniques. In this paper, we illustrate the nonparametric analysis of ordinal data obtained from two-way factorial designs, including a repeated measures design, and show how to quantify the effects of experimental factors on ratings through estimated relative marginal effects.

Risk assessment models for wheat fusarium head blight epidemics based on within-season weather data.

ABSTRACT Logistic regression models for wheat Fusarium head blight were developed using information collected at 50 location-years, including four states, representing three different U.S. wheat-production regions. Non-parametric correlation analysis and stepwise logistic regression analysis identified combinations of temperature, relative humidity, and rainfall or durations of specified weather conditions, for 7 days prior to anthesis, and 10 days beginning at crop anthesis, as potential predictor variables. Prediction accuracy of developed logistic regression models ranged from 62 to 85%. Models suitable for application as a disease warning system were identified based on model prediction accuracy, sensitivity, specificity, and availability of weather variables at crop anthesis. Four of the identified models correctly classified 84% of the 50 location-years. A fifth model that used only pre-anthesis weather conditions correctly classified 70% of the location-years. The most useful predictor variables were the duration (h) of precipitation 7 days prior to anthesis, duration (h) that temperature was between 15 and 30 degrees C 7 days prior to anthesis, and the duration (h) that temperature was between 15 and 30 degrees C and relative humidity was greater than or equal to 90%. When model performance was evaluated with an independent validation set (n = 9), prediction accuracy was only 6% lower than the accuracy for the original data sets. These results indicate that narrow time periods around crop anthesis can be used to predict Fusarium head blight epidemics.

Systemic Modulation of Gene Expression in Tomato by Trichoderma hamatum 382

ABSTRACT A light sphagnum peat mix inoculated with Trichoderma hamatum 382 consistently provided a significant (P = 0.05) degree of protection against bacterial spot of tomato and its pathogen Xanthomonas euvesicatoria 110c compared with the control peat mix, even though this biocontrol agent did not colonize aboveground plant parts. To gain insight into the mechanism by which T. hamatum 382 induced resistance in tomato, high-density oligonucleotide microarrays were used to determine its effect on the expression pattern of 15,925 genes in leaves just before they were inoculated with the pathogen. T. hamatum 382 consistently modulated the expression of genes in tomato leaves. We identified 45 genes to be differentially expressed across the replicated treatments, and 41 of these genes could be assigned to at least one of seven functional categories. T. hamatum 382-induced genes have functions associated with biotic or abiotic stress, as well as RNA, DNA, and protein metabolism. Four extensin and extensin-like proteins were induced. However, besides pathogenesis-related protein 5, the main markers of systemic acquired resistance were not significantly induced. This work showed that T. hamatum 382 actively induces systemic changes in plant physiology and disease resistance through systemic modulation of the expression of stress and metabolism genes.

Efficacy of triazole-based fungicides for fusarium head blight and deoxynivalenol control in wheat: a multivariate meta-analysis.

The effects of propiconazole, prothioconazole, tebuconazole, metconazole, and prothioconazole+tebuconazole (as a tank mix or a formulated premix) on the control of Fusarium head blight index (IND; field or plot-level disease severity) and deoxynivalenol (DON) in wheat were determined. A multivariate random-effects meta-analytical model was fitted to the log-transformed treatment means from over 100 uniform fungicide studies across 11 years and 14 states, and the mean log ratio (relative to the untreated check or tebuconazole mean) was determined as the overall effect size for quantifying fungicide efficacy. Mean log ratios were then transformed to estimate mean percent reduction in IND and DON relative to the untreated check (percent control: C(IND) and C(DON)) and relative to tebuconazole. All fungicides led to a significant reduction in IND and DON (P < 0.001), although there was substantial between-study variability. Prothioconazole+tebuconazole was the most effective fungicide for IND, with a C(IND) of 52%, followed by metconazole (50%), prothioconazole (48%), tebuconazole (40%), and propiconazole (32%). For DON, metconazole was the most effective treatment, with a [Formula: see text](DON) of 45%; prothioconazole+tebuconazole and prothioconazole showed similar efficacy, with C(DON) values of 42 and 43%, respectively; tebuconazole and propiconazole were the least effective, with C(DON) values of 23 and 12%, respectively. All fungicides, with the exception of propiconazole, were significantly more effective than tebuconazole for control of both IND and DON (P < 0.001). Relative to tebuconazole, prothioconazole, metconazole, and tebuconzole+prothioconzole reduced disease index a further 14 to 20% and DON a further 25 to 29%. In general, fungicide efficacy was significantly higher for spring wheat than for soft winter wheat studies; depending on the fungicide, the difference in percent control between spring and soft winter wheat was 5 to 20% for C(IND) and 7 to 16% for C(DON). Based on the mean log ratios and between-study variances, the probability that IND or DON in a treated plot from a randomly selected study was lower than that in the check by a fixed margin was determined, which confirmed the superior efficacy of prothioconazole, metconazole, and tebuconzole+prothioconzole for Fusarium head blight disease and toxin control.

Epidemiology of insect-transmitted plant viruses: modelling disease dynamics and control interventions

Abstract.  Plant viruses are an important constraint to crop production world‐wide. Rarely have plant virologists, vector entomologists and crop specialists worked together in search of sustainable management practices for viral diseases. Historically, modelling approaches have been vector‐based dealing with empirical forecasting systems or simulation of vector population dynamics. More recently, epidemiological models, such as those used in human/animal epidemiology, have been introduced in an attempt to characterize and analyse the population ecology of viral diseases. The theoretical bases for these models and their use in evaluating control strategies in terms of the interactions between host, virus and vector are considered here. Vector activity and behaviour, especially in relation to virus transmission, are important determinants of the rate and extent of epidemic development. The applicability and flexibility of these models are illustrated by reference to specific case studies, including the increasing importance of whitefly‐transmitted viruses. Some outstanding research and methodological issues are considered.

Systemic Resistance Induced by Trichoderma hamatum 382 in Cucumber Against Phytophthora Crown Rot and Leaf Blight

Phytophthora root rot, crown rot, leaf and stem blight, and fruit rot of cucumber can cause serious losses, and are difficult to control. Although composts can be used successfully for control of Phytophthora root rots, little is known about their effects on Phytophthora diseases of aboveground plant parts. This research shows that the severity of Phytophthora root and crown rot of cucumber caused by Phytophthora capsici was suppressed significantly in cucumber transplants produced in a composted cow manure-amended mix compared with those in a dark sphagnum peat mix. In split root bioassays, Trichoderma hamatum 382 (T382) inoculated into the compost-amended potting mix significantly reduced the severity of Phytophthora root and crown rot on paired roots in the peat mix. This effect did not differ significantly from that provided by a drench with benzothiadiazole (BTH) or mefenoxam (Subdue MAXX). Based on area under disease progress curves, T382 also significantly reduced the severity of Phytophthora leaf blight in transplants produced in the compost mix compared with controls not inoculated with T382. Efficacy of T382 did not differ significantly from that provided by a drench with BTH. T382 re-mained spatially separated from the pathogen in plants in both the split root and leaf blight bioassays, suggesting that these effects were systemic in nature.

A Theoretical Assessment of the Effects of Vector-Virus Transmission Mechanism on Plant Virus Disease Epidemics

ABSTRACT A continuous-time and deterministic model was used to characterize plant virus disease epidemics in relation to virus transmission mechanism and population dynamics of the insect vectors. The model can be written as a set of linked differential equations for healthy (virus-free), latently infected, infectious, and removed (postinfectious) plant categories, and virus-free, latent, and infective insects, with parameters based on the transmission classes, vector population dynamics, immigration/emigration rates, and virus-plant interactions. The rate of change in diseased plants is a function of the density of infective insects, the number of plants visited per time, and the probability of transmitting the virus per plant visit. The rate of change in infective insects is a function of the density of infectious plants, the number of plants visited per time by an insect, and the probability of acquiring the virus per plant visit. Numerical solutions of the differential equations were used to determine transitional and steady-state levels of disease incidence (d*); d* was also determined directly from the model parameters. Clear differences were found in disease development among the four transmission classes: nonpersistently transmitted (stylet-borne [NP]); semipersistently transmitted (foregut-borne [SP]); circulative, persistently transmitted (CP); and propagative, persistently transmitted (PP), with the highest disease incidence (d) for the SP and CP classes relative to the others, especially at low insect density when there was no insect migration or when the vector status of emigrating insects was the same as that of immigrating ones. The PP and CP viruses were most affected by changes in vector longevity, rates of acquisition, and inoculation of the virus by vectors, whereas the PP viruses were least affected by changes in insect mobility. When vector migration was explicitly considered, results depended on the fraction of infective insects in the immigration pool and the fraction of dying and emigrating vectors replaced by immigrants. The PP and CP viruses were most sensitive to changes in these factors. Based on model parameters, the basic reproductive number (R(0))-number of new infected plants resulting, from an infected plant introduced into a susceptible plant population-was derived for some circumstances and used to determine the steady-state level of disease incidence and an approximate exponential rate of disease increase early in the epidemic. Results can be used to evaluate disease management strategies.

Systemic Resistance Induced by Trichoderma spp.: Interactions Between the Host, the Pathogen, the Biocontrol Agent, and Soil Organic Matter Quality

ABSTRACT Several factors affect the ability of Trichoderma spp. to provide systemic disease control. This paper focuses on the role of the substrate in which plants are grown, resistance of the host to disease, and the ability of introduced Trichoderma inoculum to spread under commercial conditions. Several reports reveal that foliar disease control provided by Trichoderma spp. is more effective on plants grown in compost-amended media compared with in lower-in-microbial-carrying-capacity sphagnum peat media. In Rhododendron spp., host resistance affects control of Phytophthora dieback provided by Trichoderma spp. For example, T. hamatum 382 (T382) significantly (P = 0.05) suppressed the disease on susceptible cv. Roseum Elegans while plant vigor was increased. The disease was not suppressed, however, on highly susceptible cvs. Aglo and PJM Elite even though the vigor of these plants was increased. Using a strain-specific polymerase chain reaction assay under commercial conditions, it was demonstrated that introduced inoculum of T382 did not spread frequently from inoculated to control compost-amended media. Other Trichoderma isolates typically are abundant in control media within days after potting unless inoculated with a specific Trichoderma isolate. Thus, the low population of isolates that can induce systemic resistance in composting and potting mix environments may explain why most compost-amended substrates do not naturally suppress foliar diseases.

Effect of potting mix microbial carrying capacity on biological control of rhizoctonia damping-off of radish and rhizoctonia crown and root rot of poinsettia.

ABSTRACT Potting mixes prepared with dark, highly decomposed Sphagnum peat, with light, less decomposed Sphagnum peat, or with composted pine bark, all three of which were colonized by indigenous microorganisms, failed to consistently suppress Rhizoctonia damping-off of radish or Rhizoctonia crown and root rot of poinsettia. Inoculation of these mixes with Chryseobacterium gleum (C(299)R(2)) and Trichoderma hamatum 382 (T(382)) significantly reduced the severity of both diseases in the composted pine bark mix in which both biocontrol agents maintained high populations over 90 days. These microorganisms were less effective against damping-off in the light and dark peat mixes, respectively, in which populations of C(299)R(2) declined. In contrast, crown and root rot, a disease that is severe late in the crop, was suppressed in all three types of mixes. High populations of T(382) in all three mixes late during the cropping cycle may have contributed to control of this disease.

Sampling for Plant Disease Incidence

ABSTRACT Knowledge of the distribution of diseased plant units (such as leaves, plants, or roots) or of the relationship between the variance and mean incidence is essential to efficiently sample for diseased plant units. Cluster sampling, consisting of N sampling units of n individuals each, is needed to determine whether the binomial or beta-binomial distribution describes the data or to estimate parameters of the binary power law for disease incidence. The precision of estimated disease incidence can then be evaluated under a wide range of settings including the hierarchical sampling of groups of individuals, the various levels of spatial heterogeneity of disease, and the situation when all individuals are disease free. Precision, quantified with the standard error or the width of the confidence interval for incidence, is directly related to N and inversely related to the degree of heterogeneity (characterized by the intracluster correlation, rho). Based on direct estimates of rho (determined from the theta parameter of the beta-binomial distribution or from the observed variance) or a model predicting rho as a function of incidence (derived from the binary power law), one can calculate, before a sampling bout, the value of N needed to achieve a desired level of precision. The value of N can also be determined during a sampling bout using sequential sampling methods, either to estimate incidence with desired precision or to test a hypothesis about true disease incidence. In the latter case, the sequential probability ratio test is shown here to be useful for classifying incidence relative to a hypothesized threshold when the data follows the beta-binomial distribution with either a fixed rho or a rho that depends on incidence.