Comparison of sampling procedures for two rice diseases: leaf blast and tungro

The precision and accuracy of eight random and systemic sampling methods, along with various sample sizes, were compared by means of a sampling simulation program with actual field data for two rice diseases, leaf blast and tungro. Three severity levels of leaf blast and two incidence levels of tungro were used. Precision depended primarily on disease intensity, followed by the sample size and the sampling method. Relative accuracy did not prove to discriminate sampling methods adequately, but simulated absolute accuracy is able to identify biases of systematic sampling paths. The results emphasize the necessity of pilot sampling at various stages of epidemics. The usefulness of simulated sample sizes and sampling methods based on real data is also demonstrated. With this approach a more practical combination of sample size and method may be found for different levels of disease intensity using precision and absolute accuracy as criteria.     

In the eye of the beholder: the effect of rater variability and different rating scales on QTL mapping

The agronomic importance of developing durably resistant cultivars has led to substantial research in the field of quantitative disease resistance (QDR) and, in particular, mapping quantitative trait loci (QTL) for disease resistance. The assessment of QDR is typically conducted by visual estimation of disease severity, which raises concern over the accuracy and precision of visual estimates. Although previous studies have examined the factors affecting the accuracy and precision of visual disease assessment in relation to the true value of disease severity, the impact of this variability on the identification of disease resistance QTL has not been assessed. In this study, the effects of rater variability and rating scales on mapping QTL for northern leaf blight resistance in maize were evaluated in a recombinant inbred line population grown under field conditions. The population of 191 lines was evaluated by 22 different raters using a direct percentage estimate, a 0-to-9 ordinal rating scale, or both. It was found that more experienced raters had higher precision and that using a direct percentage estimation of diseased leaf area produced higher precision than using an ordinal scale. QTL mapping was then conducted using the disease estimates from each rater using stepwise general linear model selection (GLM) and inclusive composite interval mapping (ICIM). For GLM, the same QTL were largely found across raters, though some QTL were only identified by a subset of raters. The magnitudes of estimated allele effects at identified QTL varied drastically, sometimes by as much as threefold. ICIM produced highly consistent results across raters and for the different rating scales in identifying the location of QTL. We conclude that, despite variability between raters, the identification of QTL was largely consistent among raters, particularly when using ICIM. However, care should be taken in estimating QTL allele effects, because this was highly variable and rater dependent.     

A comparison of potato seed-tuber sampling strategies using visual and DNA analyses to estimate incidence of major seed tuber-borne pathogens

Potato seed certification is a disease management tool that minimises the risk of spreading seed tuber-borne inoculum of infectious diseases. Traditionally, certification sampling strategies have relied upon visual assessment of a seedlot from samples taken at one or two points within the load of seed tubers. However methodologies in selection of tuber samples have not been critically assessed for their precision in estimating disease load. This study presents an analysis of 37 potato seedlots over a 3 year period. Analysis of sample data using receiver operating curves (ROCs) indicates that point sampling taking two samples of 100 tubers at the beginning and end of a seedlot gives equivalent disease estimation as a continuous sampling strategy taking ten samples of 20 tubers randomly throughout the seedlot, although at lower statistical precision. This was confirmed both by visual assessment of tuber-borne disease and by analysis of pathogen DNA content from tuber peel. Across the 3 years of study, powdery scab and black scurf were the major seed tuber-borne diseases recognised and this corresponded with high levels of pathogen DNA from peel analysis for both Spongospora subterranea and Rhizoctonia solani AG3 respectively.     

A stochastic optimization method to estimate the spatial distribution of a pathogen from a sample

Information on the spatial distribution of plant disease can be utilized to implement efficient and spatially targeted disease management interventions. We present a pathogen-generic method to estimate the spatial distribution of a plant pathogen using a stochastic optimization process which is epidemiologically motivated. Based on an initial sample, the method simulates the individual spread processes of a pathogen between patches of host to generate optimized spatial distribution maps. The method was tested on data sets of Huanglongbing of citrus and was compared with a kriging method from the field of geostatistics using the well-established kappa statistic to quantify map accuracy. Our method produced accurate maps of disease distribution with kappa values as high as 0.46 and was able to outperform the kriging method across a range of sample sizes based on the kappa statistic. As expected, map accuracy improved with sample size but there was a high amount of variation between different random sample placements (i.e., the spatial distribution of samples). This highlights the importance of sample placement on the ability to estimate the spatial distribution of a plant pathogen and we thus conclude that further research into sampling design and its effect on the ability to estimate disease distribution is necessary.     

Microcomputer-Based Quantification of Maize Streak Virus Symptoms in Zea mays

ABSTRACT We investigated the use of computer-assisted image analysis techniques for the objective quantification of maize streak virus (MSV) symptoms in Zea mays. We compared independent duplicate evaluations of chlorotic lesion areas occurring on MSV-infected leaves using visual assessment, a commercial image analysis system, and a custom image analysis system employing software developed in our laboratory. Relative to visual assessments of disease severity, computer-assisted image analysis employing both the commercial and custom systems provided significant enhancements in the accuracy and precision of chlorotic area estimations. The commercial image analysis system afforded no significant improvement in precision or accuracy over the custom system. An important advantage of examining images using the custom-written software was that the software permitted a high degree of analysis automation. Digitized images of maize leaves could be automatically analyzed by the custom software five times faster than, and with the same precision and accuracy as, when the same images were analyzed with the commercial software. Because of the flexibility of the image analysis techniques described, they should be applicable to the measurement of symptom severity in other plant host-pathogen combinations.     

Quantifying Aphanomyces euteiches in Alfalfa with a Fluorescent Polymerase Chain Reaction Assay

ABSTRACT A polymerase chain reaction (PCR) assay using a set of specific primers and a dual-labeled probe (TaqMan) was developed to quantify the amount of Aphanomyces euteiches DNA in alfalfa plants exhibiting varying levels of disease severity. The study included isolates of race 1 and race 2 of A. euteiches. The assay also discriminated between alfalfa populations for resistance based on analysis of DNA extracted from bulked plant samples. Analysis of individual plants and bulked plant samples of standard check populations with both pathogen isolates resulted in Spearman rank correlations between pathogen DNA content and disease severity index ratings that were greater than 0.75 and highly significant (P < 0.0005). In experiments with a race 1 isolate, the amount of pathogen DNA present in the resistant check WAPH-1 was significantly less than in the susceptible check Saranac. In experiments with a race 2 isolate, the amount of pathogen DNA in the resistant check WAPH-5 was significantly less than in either of the susceptible checks, Saranac and WAPH-1. Discrimination between commercial cultivars based on quantitative PCR analysis of bulked plant samples was similar to classification based on visual assessment of disease severity.     

Evaluation of diagnostic and quantitative PCR for the identification and severity assessment of eyespot and sharp eyespot in winter wheat

Diagnostic and quantitative polymerase chain reaction (PCR) provided clarification of the causes of symptoms and the extent of infection by eyespot ( Tapesia spp.) and sharp eyespot ( Rhizoctonia cerealis ) on winter wheat at early growth stages. Disease assessments made before stem extension, when decisions to apply fungicides are usually made, often did not agree with the pathogen diagnoses using PCR, suggesting that such early visual diagnoses may be unreliable. Visual and PCR diagnoses made on stems in summer generally supported each other, but there were often discrepancies in relating disease severity to amounts of pathogen present when determined by regression analyses of incidence or severity of symptoms on amount of pathogen DNA. Mixed symptoms caused by different pathogens may sometimes have been confounded. Relationships between symptoms and DNA of eyespot pathogens were less clear on some cultivars, often those with least disease. Sharp eyespot symptoms had a stronger relationship to DNA of its pathogen. Significant regressions often accounted for a small percentage of the variance, suggesting either that pathogens not assayed were contributing to symptoms or that lesions were in some cases persisting longer into the season than pathogen DNA. The frequency of pathogen detection before stem extension was a poor predictor of the amounts of pathogen DNA measured later in the season.     

The Role of Psychophysics in Phytopathology: The Weber–Fechner Law Revisited

The accuracy and precision of disease severity assessment data might be improved if there was a better understanding of how the laws of psychophysics actually relate to the theory and practice of phytopathometry. In this regard, we utilized a classical method developed in the field of psychophysics (the method of comparison stimuli) to test Horsfall and Barratt’s claim that raters cannot accurately discriminate disease severity levels between 25% and 50% because, according to the Weber–Fechner law, visual acuity is proportional to the logarithm of the intensity of the stimulus. We show for two pathosystems, wheat leaf rust and grapevine downy mildew, that raters can accurately discriminate disease severity levels between 25% and 50%, and that although Weber’s law appears to hold true, Fechner’s law does not. Furthermore, based upon our results, the relationship between actual (true) disease severity (X) and disease severity estimated by raters (Y) is linear, not logarithmic as proposed by Horsfall and Barratt.     

Improving sooty blotch and flyspeck severity estimation on apple fruit with the aid of standard area diagrams

Sooty blotch and flyspeck is caused by numerous species of fungi that colonize the surface of apple fruit and thereby lower its market value. Although this disease poses a substantial threat to apple growers’ profitability in some regions, reliable and cost-effective methods for epidemiological and disease control studies have not been validated, nor are they widely available. We modified a standard area diagram to aid sooty blotch and flyspeck severity assessments and quantified its impact on accuracy and precision of visual estimates. Samples of ‘Fuji’ and ‘Mutsu’ fruit were photographed both from the top and laterally. Severity was assessed from a sub-sample of 160 images using image analysis software. Validation of the diagram was performed by eight raters who independently assessed severity in two series of selected images representing the lateral view and the top view, initially unaided and subsequently with the aid of the scale. Severity estimates ranged from 0.4% to 98% (most fruit had <10% severity). Accuracy and precision of the estimates were significantly improved when using the diagrammatic scale; concordance correlation coefficient values increased from 0.81 to 0.95. A strong tendency to underestimate severity for the mid-range to high levels was minimized when using the aid, which also improved reproducibility of the estimates among raters. In addition to strengthening evidence that a standard area diagram can be used reliably in sooty blotch and flyspeck studies, we expanded its application to disease assessment in the peduncle region, which enhances the usefulness of the method for evaluating efficacy of management practices.     

Application of image analysis in studies of quantitative disease resistance, exemplified using common bacterial blight-common bean pathosystem

The effectiveness of image analysis (IA) compared with an ordinal visual scale, for quantitative measurement of disease severity, its application in quantitative genetic studies, and its effect on the estimates of genetic parameters were investigated. Studies were performed using eight backcross-derived families of common bean (Phaseolus vulgaris) (n = 172) segregating for the molecular marker SU91, known to be associated with a quantitative trait locus (QTL) for resistance to common bacterial blight (CBB), caused by Xanthomonas campestris pv. phaseoli and X. fuscans subsp. fuscans. Even though both IA and visual assessments were highly repeatable, IA was more sensitive in detecting quantitative differences between bean genotypes. The CBB phenotypic difference between the two SU91 genotypic groups was consistently more than fivefold for IA assessments but generally only two- to threefold for visual assessments. Results suggest that the visual assessment results in overestimation of the effect of QTL in genetic studies. This may have been caused by lack of additivity and uneven intervals of the visual scale. Although visual assessment of disease severity is a useful tool for general selection in breeding programs, assessments using IA may be more suitable for phenotypic evaluations in quantitative genetic studies involving CBB resistance as well as other foliar diseases.     

Reliability and accuracy of visual estimation of phomopsis leaf blight of strawberry

ABSTRACT Six different individuals (raters) assessed the severity of Phomopsis leaf blight on strawberry leaflets in five experimental repetitions over 2 years by making a direct visual estimation of the percentage of diseased area of each leaflet or by using the Horsfall-Barratt (H-B) disease scale. Intra-rater and inter-rater reliability and accuracy were determined, and then the relationship between visually estimated severity values and actual severity values was evaluated. Agreement in estimated disease severity values between assessment times by the same raters (i.e., intra-rater reliability), and agreement in disease severity values among raters at a single assessment time (i.e., inter-rater reliability), were both high, with most correlation coefficients being greater than 0.85. The intra-class correlation for overall agreement among raters ranged from 0.80 to 0.96 for the five repetitions. Based on the concordance coefficient calculated for each rater in each repetition, agreement between estimated and actual severity (i.e., accuracy) was somewhat lower than reliability. The relationship between estimated and actual severity was linear, and there was a slight trend to overestimate disease severity. The H-B scale was not more reliable or accurate than direct estimation of severity, and the linear relationship between estimated and actual severity did not support the principles underling the H-B scale. Both size of leaflets and number of lesions per leaflet slightly affected the error in estimate of disease severity.     

Development of a Real-Time Polymerase Chain Reaction Assay for Quantifying Verticillium albo-atrum DNA in Resistant and Susceptible Alfalfa

ABSTRACT A precise real-time polymerase chain reaction (PCR) assay was developed for quantifying Verticillium albo-atrum DNA. The assay was used in a repeated experiment to examine the relationship between the quantity of pathogen DNA detected in infected leaves and shoots and the severity of Verticillium wilt symptoms in several alfalfa cultivars expressing a range of disease symptoms. Plants were visually inspected for symptoms and rated using a disease severity index ranging from 1 to 5, and the quantity of pathogen DNA present in leaves and stems was determined with real-time PCR. No significant differences in pathogen DNA quantity or disease severity index were observed for experiments or for cultivar-experiment interactions. Significant differences were observed between cultivars for the quantity of pathogen DNA detected with real-time PCR and also for disease severity index ratings. In both experiments, the highly resistant check cultivar Oneida VR had significantly less pathogen DNA, and significantly lower disease severity index ratings than the resistant cultivar Samauri, the moderately resistant cultivar Vernema, and the susceptible check cultivar Saranac. In both experiments, the Spearman rank correlation between the amount of V. albo-atrum DNA detected in leaves and stems with real-time PCR and disease severity index ratings based on visual examination of symptoms was positive (>0.52) and significant (P < 0.0001). These results suggest that resistance to Verticillium wilt in alfalfa is characterized by a reduced colonization of resistant genotypes by the fungus.     

Variation in pathogen aggressiveness within a metapopulation of the Cakile maritima–Alternaria brassicicola host–pathogen association

Variation in aggressiveness and its consequences for disease epidemiology were studied in the Cakile maritima–Alternaria brassicicola host–pathogen association. Variability in pathogen growth rates and spore production in vitro , as well as disease severity and lesion growth rate on C. maritima in glasshouse inoculation trials, were investigated . Substantial variation was found in growth rates among individual A. brassicicola isolates, as well as among pathogen populations. A significant trade-off also existed between growth and spore production, such that faster-growing isolates produced fewer spores per unit area. While there was little evidence for a link between growth in vitro and either disease severity or lesion development among fast- vs slow-growth isolate classes at the individual isolate level, the results suggest that variation in pathogen fitness components associated with aggressiveness may influence disease dynamics in nature. An analysis using an independent data set of disease prevalence in the associated host populations found a significant positive relationship between the average growth rate of pathogen populations in vitro and disease progress over the growing season in wild host populations. Trade-offs such as those demonstrated between growth rate and spore production may contribute to the maintenance of variation in quantitatively based host–pathogen interactions.     

Spatial sampling to detect an invasive pathogen outside of an eradication zone

Invasive pathogens are known to cause major damage to the environments they invade. Effective control of such invasive pathogens depends on early detection. In this paper we focus on sampling with the aim of detecting an invasive pathogen. To that end, we introduce the concept of optimized spatial sampling, using spatial simulated annealing, to plant pathology. It has been mathematically proven (15) that this optimization method converges to the optimum allocation of sampling points that give the largest detection probability. We show the benefits of the method to plant pathology by (i) first illustrating that optimized spatial sampling can easily be applied for disease detection, and then we show that (ii) combining it with a spatially explicit epidemic model, we can develop optimum sample schemes, i.e., optimum locations to sample that maximize the probability of detecting an invasive pathogen. This method is then used as baseline against which other sampling methods can be tested for their accuracy. For the specific example case of this paper, we test (i) random sampling, (ii) stratified sampling as well as (iii) sampling based on the output of the simulation model (using the most frequently infected hosts as sample points), and (iv) sampling the hosts closest to the outbreak point.     

Relationships between incidence and severity of fusarium head blight on winter wheat in ohio

ABSTRACT 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.     

Comparison of three diagrammatic keys for the quantification of late blight in tomato leaves

Three diagrammatic grading keys were designed for the assessment of the severity of late blight (caused by Phytophthora infestans ) in tomato leaves. Simplified and broad keys considered, respectively, six (3, 12, 22, 40, 60 and 77%) and eight (3, 6, 12, 22, 40, 60, 77 and 90%) levels of disease severity, whilst a modified key based on a previous proposal for potato late blight considered six levels (1, 5, 10, 16, 32 and 50%). The keys were validated by 24 evaluators who assessed digital images of tomato leaves exhibiting different areas with lesions. Evaluator errors were compared using a mixed model in which evaluators were considered as random effects and the keys and evaluations as fixed effects. The accuracy and precision of the evaluators were compared by simple linear regression between the estimated and actual values of disease severity. The repeatability of evaluators was assessed using Pearson's correlation coefficient. There was significant ( P  ≤   0·001) variability amongst the errors made by evaluators, although the precision of each of the three keys was high with a coefficient of determination (R²) of 0·96, 0·93 and 0·83 for the simplified, broad and modified key, respectively. Repeatability of estimations amongst the evaluators was adequate (correlation coefficients of 0·91, 0·91 and 0·90 for the three keys, respectively). The simplified and broad keys resulted in higher precision and accuracy for the estimation of severity than did the modified key. Since the simplified key considers a smaller number of disease severity levels, its use is recommended in the assessment of late blight in tomato leaves.     

Quantitative detection of <Emphasis Type="Italic">Monosporascus cannonballus</Emphasis> in infected melon roots using real-time PCR

A method was developed for the specific detection, identification and quantification of Monosporascus cannonballus in infected melon roots based on real-time PCR (SYBR® Green chemistry) targeting the ITS1 region of the rDNA conserved between different strains of the pathogen. The specificity of the reaction was assessed using a number of fungi taxonomically and ecologically related to M. cannonballus. The method was highly sensitive and M. cannonballus was first detected in the roots of a susceptible Piel de Sapo cultivar 2 days after inoculation, before symptom appearance. Although conventional PCR methods could also provide such a specific and sensitive detection, real-time PCR was also able to produce reliable quantitative data over a range of 4 orders of magnitude (from 5 ng to 0.3 pg). The method allowed the quantitative monitoring of fungal growth from the very first stages of infection, and was successfully employed in the early screening of resistance. The assessment of disease progress and severity obtained with real-time PCR was more accurate than that obtained with the visual scoring of root lesions or root biomass losses. Therefore, there exists a great potential for its implementation in those steps of breeding programmes where high accuracy is required.     

Measurement of healthy and diseased haulm area for assessing late blight epidemics in potatoes

The advantages of assessing disease severity by visual grading and by measuring healthy and diseased plant area were compared in four mild to moderate late blight epidemics during spring and in two severe epidemics during autumn in Israel. Disease progress curves obtained through visual grading showed a continuous increase, but the area of lesions tended to fluctuate during the cropping season and often reached a maximum in plots in which the total amount of foliage was also largest. The healthy haulm area differed with disease intensity and undefined seasonal and cultural influences. The decrease in healthy haulm area was not related to expansion of the blighted area only, but also to the breaking of plants at stem lesions. This phenomenon was especially evident in the warm spring season and was not determined by visual grading of disease severity. Each kind of assessment revealed different features of the epidemics and suited different applications. Visual grading enabled the easiest comparison of epidemic patterns. Lesion areas reflected patterns of inoculum potential, while healthy haulm areas reflected the integrated influences of factors affecting the crop and disease and thus provided useful data for simulating epidemics and for estimating yield losses.     

Framework Development in Plant Disease Risk Assessment and its Application

This article reviews recent developments in plant disease risk assessment. The role of risk assessment as an application area in macrophytopathology and its contribution to the development of macroscale disease study are discussed. This article also discusses the concepts and components of risk assessment for different end points and the assessment framework of different potential ranges of a new pathogen: establishment range, suitability range, damage range, and dispersal range. Different end points generate risk information suitable for decision makers at different levels. New insights gained from selected major diseases, especially from risk assessment due to the recent global movement of soybean rust, are presented. The role of pathologists in presenting risk information has extended beyond the professional research domain and has become critical in influencing decision-making, evident by soybean rust in both South and North America. The bias components of risk communication are defined, and different levels of receivers for risk information are identified based on their interpretation capability of risk information, bias potential, and utilization of risk information. Lack of predictability of dispersal potential contributes to uncertainty of risk assessment for airborne diseases. Potential research areas in disease risk assessment are discussed.     

Reliability and accuracy of visual methods to quantify severity of foliar bacterial spot symptoms on peach and nectarine

The objectives of this study were to assess the reliability and accuracy of visual methods used to quantify the severity of bacterial spot (Xanthomonas arboricola pv. pruni) symptoms and evaluate the effects of rater experience on the quality of disease estimates. Three cohorts of raters differing in experience with disease assessment rated three sets of peach or nectarine leaves (n ≥ 103; disease severity levels from 0% to 100%) by direct estimation of percentage leaf area with symptoms. Four of the experienced raters also rated the leaves using a 1–7 interval scale. Actual disease severity on the leaves was obtained with the APS assess image analysis software. Equivalence tests based on a bootstrap analysis were used to compare the rating scale and direct estimation methods, and to evaluate the effects of rater experience, computer training and human instruction on accuracy and reliability of disease estimates. In concordance analysis of continuous variables, with data from scale converted to percentage, the direct estimation method resulted in more accurate and reliable estimates than the interval scale. Analysing the scale data without conversion to percentage improved the concordance statistics for the scale but not sufficiently to match the direct estimation method. Accuracy was affected more by rater experience and intrinsic ability than reliability. Instruction on disease symptoms resulted in the largest improvement in estimates from inexperienced raters. Accurate and reliable direct estimation of bacterial spot severity on peach and nectarine can be made by raters with varying levels of experience provided they receive sufficient instruction.