The Horsfall-Barratt scale and severity estimates of citrus canker

Citrus canker assessment data were used to investigate effects of using the Horsfall-Barratt (H-B) scale to estimate disease compared to direct estimation to the nearest percent. Twenty-eight raters assessed each of two-hundred infected leaves (0–38% true diseased area). The data were converted to the H-B scale. Correlation (r) showed that direct estimates had higher inter-rater reliability compared to H-B scaled data (r = 0.75 and 0.71 for direct estimates and H-B scaled data, respectively). Lin’s concordance correlation (LCC, ρ _c ) analysis showed individual rater estimates by direct estimation had better agreement with true values compared to H-B scaled data. The direct estimates were more precise compared to H-B scaled data (r = 0.80–0.95 and 0.61–0.90, respectively), but measures of generalised bias or accuracy (C _b ) were similar for both methods (0.38–1.00). Cumulative mean disease and cumulative variance of the means were calculated for each rater on a leaf-by-leaf basis. Direct estimates were closer to the true severity 59.5% of the time, and to the cumulative true sample mean 53.7% of the time, and to the cumulative true sample mean variance 63.6% of the time. Estimates of mean severity for each leaf based on estimates by 3, 5, 10, 20 and 28 raters were compared to true disease severity. LCC showed that rater-means based on more raters had better agreement with true values compared to individual estimates, but H-B scale data were less precise, although with means based on ≥ 10 raters, agreement was the same for both assessment methods. Magnitude and dispersion of the variance of the means based on H-B scaled data was greater than that by direct estimates. H-B scaling did not improve reliability, accuracy or precision of the estimate of citrus canker severity compared to direct visual estimation.     

A comparison between visual estimates and image analysis measurements to determine septoria leaf blotch severity in winter wheat

Methods to estimate disease severity vary in accuracy, reliability, ease of use and cost. Severity of septoria leaf blotch (SLB, caused by Zymoseptoria tritici) was estimated by four raters and by image analysis (assumed actual values) on individual leaves of winter wheat in order to explore accuracy and reliability of estimates, and to ascertain whether there were any general characteristics of error. Specifically, the study determined: (i) the accuracy and reliability of visual assessments of SLB over the full range of severity from 0 to 100%; (ii) whether certain 10% ranges in actual disease severity between 0 and 100% were more prone to estimation error compared with others; and (iii) whether leaf position affected accuracy within those ranges. Lin's concordance correlation analysis of all severities (0–100%) demonstrated that all raters had estimates close to the actual values (agreement: ρ_c = 0·92–0·99). However, agreement between actual SLB severities and estimates by raters was less good when compared over short 10% subdivisions within the 0–100% range (ρ_c = ?0·12 to 0·99). Despite common rater imprecision at estimating low and high SLB severities, individual raters differed considerably in their accuracy over the short 10% subdivisions. There was no effect of leaf position on accuracy or precision of severity estimate on separate leaves (L1–L3). Pursuing efforts in understanding error in disease estimation should aid in improving the accuracy of assessments, making visual estimates of disease severity more useful for research and applied purposes.     

Analysis of the association between the incidence of two spatially aggregated foliar diseases of strawberry

ABSTRACT Association of the incidence of leaf blight (caused by Phomopsis obscurans) and leaf spot of strawberry (caused by Mycosphaerella fragariae) was assessed at multiple scales in perennial plantings at several commercial farms over 3 years (1996 to 1998). For each field, the presence or absence of each disease was recorded from n = 15 leaflets in each of N approximately 70 evenly spaced sampling units, and the proportion of leaflets with blight, spot, and total disease (blight or spot) was determined. Individual diseases and total disease incidence were all well described by the beta-binomial distribution but not by the binomial distribution, indicating overdispersion of disease. The Jaccard similarity index was used to measure disease co-occurrence at the leaflet, sampling-unit, and field scales. Standard errors of this index for the lower two scales were obtained using the jackknife (resampling) procedure, and data randomizations were used to determine the expected Jaccard index for an independent arrangement of the two diseases, conditioned on the incidence and spatial heterogeneity of the observed disease data. Results based on these statistics showed that only 4 of 52 data sets at the leaflet level and no data sets at the sampling-unit level had Jaccard index values significantly different from that expected under an independent rearrangement of the two diseases. Rank correlation and cross-correlation statistics were calculated to determine the degree of covariation in incidence between the two diseases. Additionally, covariation between diseases was tested using a new procedure in the Spatial Analysis by Distance IndicEs (SADIE) class of tests. Covariation was detected in 21% of the data sets using rank correlation methods and in 15% of the data sets using the SADIE-based approach. The discrepancy between these two methods may be due to the rank correlation procedure not taking into account the effects of spatial pattern of disease incidence. There was no relationship between mean disease incidence per field of spot and blight or between degree of heterogeneity of the two diseases (as measured by theta of the beta-binomial distribution), demonstrating lack of covariation at the field scale. Incidence of leaflets with either disease (total disease incidence) could be well predicted using a linear combination of the estimated probabilities of leaf blight and leaf spot incidence based on independence of the two diseases. Heterogeneity of total disease incidence, measured with the estimated theta parameter of the beta-binomial distribution, could also be well predicted using a linear combination of the weighted theta values for leaf blight and leaf spot, with weights proportional to incidence of the individual diseases.     

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.     

A generalized linear modeling approach for characterizing disease incidence in a spatial hierarchy

ABSTRACT Several statistical models are introduced to quantify the effect of heterogeneity on disease incidence relationships in a three-scale spatial hierarchy: the sampling unit level (highest), the leaf scale (intermediate), and the leaflet scale (lowest). The models are an extension of the theory previously developed for a two-scale hierarchy and were tested using data collected from strawberry leaf blight epidemics. Disease incidence at the sampling-unit scale (proportion of sampling units with one or more diseased leaflets) increased as a saturation-type curve with increasing leaflet or leaf disease incidence (proportion of leaflets or leaves diseased) as predicted by the good fit of the beta-binomial distribution to the leaflet and leaf data. The relationship could be accurately described, without curve fitting, by several simple nonlinear models, in which the aggregation of disease was represented by a modified binomial function incorporating an effective sample size that was either constant or dependent on mean incidence. The relationship between incidence at the leaflet and leaf scales could be modeled based on the combined sampling-unit models for leaflets and leaves. By taking the complementary log-log (CLL) transformation of incidence, the equations could be expressed as generalized linear models, and curve fitting used to estimate the parameters. Generally, curve fitting gave slight to no improvement in the accuracy of the predictions of incidence. These models have broad applicability in sampling for disease incidence, and results can be used to interpret how diseased individuals at the lowest level in a hierarchy are arranged within sampling units.     

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.     

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.     

Assessing disease severity: accuracy and reliability of rater estimates in relation to number of diagrams in a standard area diagram set

Error in estimates of plant disease severity occur and standard area diagrams (SADs) help improve accuracy and reliability. The effects of diagram number in SADs are unknown. The objective of this study was to compare estimates of pecan scab severity made without SADs, and using three‐, five‐, seven‐ or 10‐diagram SADs. Disease severity was estimated to the nearest percent (NPE), or classified to the closest reference diagram value using a scale. Twelve raters assessed 20 images of scabbed pecan valves with and without the SADs using NPEs and the scale method (values were converted to midpoints prior to analysis). Increases in diagram number using NPEs did not necessarily result in more accurate or reliable estimates. Inter‐rater reliability was positively correlated with number of diagrams using NPEs (r = 0·3288 (P < 0·0001)) or a scale (r = 0·2803 (P < 0·0001)). The least accurate estimates improved the most using SADs with NPEs, but the gain did not relate to number of diagrams; as few as three diagrams reduced error of inaccurate estimates as much as five, seven or 10 diagrams. When used as a scale, only estimates made with 10‐diagram SADs had similar accuracy and inter‐rater reliability to estimates made using SADs with NPEs. Maximum disease severity and the disease severity range for the pathosystem and the SADs are important factors and will probably influence resulting accuracy and reliability. The ramifications of diagram numbers in SADs and assessment methods on accuracy and reliability of disease estimates are discussed.     

Development and validation of standard area diagrams to aid assessment of pecan scab symptoms on fruit

Pecan scab (Fusicladium effusum) causes losses of pecan nutmeat yield and quality in the southeastern United States. Disease assessment relies on visual rating, which can be inaccurate and imprecise, with poor inter‐rater reliability. A standard area diagram (SAD) set for pecan scab on fruit valves was developed. A set of 40 images of diseased fruit valves with known severity was assessed twice by 23 raters. The first assessment was conducted without SADs, and the second assessment was made using the SADs as an aid. SADs improved rater accuracy (correction factor, C_b = 0·86 and 0·97, without and with SADs, respectively) and agreement (Lin’s concordance correlation coefficient, ρ_c = 0·79 and 0·89 without and with SADs, respectively) with true values. SADs improved inter‐rater reliability (intra‐class correlation coefficient, ρ = 0·77 and 0·96 without and with SADs, respectively). The least accurate and precise raters without SADs improved more using SADs compared to the most accurate and precise raters. Experienced raters had significantly higher accuracy and precision compared to inexperienced raters, but only when unaided by the SAD set. There was no significant difference in time to assess images without SADs, but experienced raters using SADs were faster compared to inexperienced raters. There was a slight tendency for faster raters to assess more slowly, and slower raters to assess faster when using SADs. SADs improve rater estimates of pecan scab severity on fruit, and this SAD set should be useful for assessment where greater precision, accuracy and inter‐rater reliability are required.     

Development and validation of a standard area diagram set to aid assessment of severity of loquat scab on fruit

A standard area diagram set (SAD) to aid visual assessment of loquat scab (caused by Fusicladium eriobotryae) severity on fruit was developed and evaluated for improving accuracy, precision and reliability of visual estimates. The SAD set contains eight black and white diagrams of diseased fruit with severity values from 2 % to 98 %. To evaluate the SADs, a group of 20 raters (comprising 10 ‘experienced’ and 10 ‘inexperienced’ raters) assessed the same set of 50 images three times, the first without SADs and the second and third using the SADs as an aid. Only for the group of inexperienced raters did SADs significantly improve accuracy (bias correction factor, C _b?=?0.93 without SADs and 0.98 with SADs), precision (correlation coefficient, r?=?0.88 without SADs and r?=?0.96 with SADs) and overall agreement (Lin’s concordance correlation coefficient, ρ _c?=?0.82 without SADs and ρc with SADs = 0.95) of the estimates. Accuracy and precision of the estimates by inexperienced raters were significantly higher than those obtained by the experienced raters, especially for the second assessment with SADs. Inter-rater reliability was improved when SADs were used by inexperienced raters, whereas a high degree of intra-rater reliability was obtained by both experienced and inexperienced raters when using SADs. The SADs developed in this study were useful for obtaining more accurate, precise and reliable assessments of loquat scab for inexperienced raters, and should be used as an aid for assessing scab in epidemiological studies or monitoring for decision-making purposes.     

Development and validation of a standard area diagram set to assess blast severity on wheat leaves

This study aimed to develop and validate a standard area diagram set (SADS) to quantify the severity of blast, caused by Pyricularia oryzae, on wheat leaves. The SADs has ten levels: 0.1, 1, 5, 10, 22, 32, 42, 52, 62 and 72 % blast severity. To validate the SADs, 12 inexperienced raters estimated disease severity on 50 images of leaves from cultivars BR-18 (susceptible) and BRS-229 (partially resistant). Blast severity was first estimated without the use of the SADs on 50 leaves with a range of blast severity. The same raters evaluated the same 50 leaves using the SADs as an aid. The SADs improved accuracy (coefficient of bias, C _b ?=?0.88 and 0.99, without and with SADs, respectively) and agreement (Lin’s concordance correlation coefficient, ρ _c ?=?0.84 and 0.96 without and with SADs, respectively) of the estimates of severity. The absolute error was (-) 52 % without the SADs and (-) 24 % when using SADs as an aid. Severity estimates were more reliable when using SADs (R²?=?0.87 unaided and R²?=?0.92 with SAD). The SADs proposed in this study will improve accuracy and reliability of estimates of blast severity on wheat leaves.     

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.     

Development and validation of a set of standard area diagrams to aid in estimation of spot blotch severity on wheat leaves

This study aimed to develop and validate a standard area diagram (SAD) set to quantify the severity of spot blotch, caused by Bipolaris sorokiniana, on wheat leaves. The proposed SAD set includes images of leaves with 11 distinct disease severities (0·1, 1, 5, 10, 20, 30, 40, 50, 60, 70 and 83%). The SAD set was validated by 12 raters without experience in evaluating plant disease. Lin's concordance correlation analysis of estimated versus actual disease severity (based on image analysis) showed that precision and accuracy improved for all raters using the SAD set in contrast to assessments made without it. The SAD set improved accuracy (coefficient of bias, C_b = 0·88 and 0·99, without and with the SAD set, respectively) and agreement (Lin's concordance correlation coefficient, ρ_c = 0·81 and 0·96 without and with the SAD set, respectively) of the estimates of severity. The severity estimates were also more reliable when using the SAD set (coefficient of determination, R² = 0·76 unaided and R² = 0·92 with the SAD set, and intra‐class correlation ρ = 0·79 without the SAD set and ρ = 0·95 using the SAD set). The SAD set proposed in this study will improve the accuracy and reliability of estimates of spot blotch severity on wheat leaves.     

不同严重度分级方法下小麦赤霉病病情指数的比较

本研究以小麦赤霉病为对象,进一步探讨在不同计算方法下7种分级标准所得病情指数的差异及误差。论证了现行病情指数计算方法的不合理性,并提出了新的计算公式。结果表明,病情指数与实际值的误差主要不在于分级方法,是传统的计算方法造成了这种误差。传统计算方法用不同分级标准所得病情指数之间及其与实际病情指数之间有极显著误差。而用改进算法时,不同分级方法所得病情相近,也与实际值相符。     

Standard area diagram set for assessment of severity and temporal progress of apple blotch

Apple blotch (Marssonina coronaria) is a foliar disease of increasing importance globally. Methods to quantify the disease and knowledge about epidemiology are required for new studies on the disease. The objectives of this study were to develop a standard area diagram set (SADs) to assess apple blotch severity and to describe the temporal progress of the disease under field conditions on older and younger leaves of two apple cultivars. For the development of SADs, symptomatic leaves were collected and scanned to obtain the actual severity. Based on the pattern of the disease, a SADs was elaborated and validated. Leaf severities were estimated without and with SADs by 12 raters to validate the tool. After validation, the SADs was used to assess apple blotch in older and younger leaves of selected shoots during the vegetative cycle of cvs. Eva and Gala. SADs severities ranged from 0.2 to 96%. Accuracy, precision, and reliability of the estimates were significantly improved when the SADs was used. In the field, the onset of apple blotch was in late spring and greater increases in severity occurred during summer. Rates of disease progress ranged from 0.09 to 0.13. Epidemics were different in older and younger leaves at the end of the apple vegetative cycle for both cultivars tested. Our work provided a tool for apple blotch quantification and described the disease progress curve under subtropical conditions, which can contribute as basis for future studies.

     

Influence of host resistance and phenology on South American leaf blight of the rubber tree with special consideration of temporal dynamics

South American leaf blight (SALB), the most dangerous disease of the rubber tree, is responsible for the lack of significant natural rubber production in South America and is a major threat to rubber tree plantations in Asia and Africa. Although the selection of resistant clones is the preferred disease control method, greater knowledge is required of the relationship between host and pathogen, in order to construct more durable resistance. Based on small-scale trials, this study set out to compare the dynamics of SALB on two highly susceptible and one moderately susceptible clone and to analyse the effect of host phenology on disease severity, at leaflet and flush scales. Clonal resistance was found to have a noticeable effect on disease severity, asexual sporulation and stromatal density at both leaflet and flush levels, and on disease dynamics at a leaflet level; time for symptom and sporulation appearance were longer on the moderately susceptible clone than on the susceptible clones. On the moderately susceptible clone, the stromatal density was largely dependent on disease severity. The phenology did not differ among the three clones and could not be considered as a factor in genetic resistance to SALB. However, for the three clones, the position of the leaflet in the flush affected the duration of the immature stages and the disease: the shorter the duration of leaflet development, the lower the disease severity, the sporulation intensity and the stromatal density.     

Genetic diversity of <Emphasis Type="Italic">Ralstonia solanacearum</Emphasis> strains from Mexico associated with Moko disease

The aim of this study was to develop and validate a standard area diagram set (SADs) to assess the severity of peach rust, caused by Tranzschelia discolor. The proposed SADs includes ten images of leaves with a range of severity (0.1, 0.5, 1.0, 2.0, 5.0, 10, 15, 20, 25 and 30%). The SADs was validated by 14 raters who had no experience in plant disease severity estimation. In the first step of the validation, the raters made severity estimates of 50 leaves with a range of rust severity without using SADs. In the second step, the same raters estimated severity of rust on the same 50 leaves using the SADs to aid estimation. Lin’s concordance correlation analysis showed that both precision and accuracy improved when the raters used the SADs compared to the assessments made without SADs. Accuracy, as measured by the coefficient of bias (C _b ) improved from 0.70 to 0.98, without and with SADs, respectively, and precision measured by the correlation coefficient (r) improved from 0.85 to 0.90, without and with SADs, respectively. Overall agreement, measured by Lin’s concordance correlation coefficient (ρ _c ), improved from 0.59 to 0.88 without and with SADs, respectively. Furthermore, estimates were more reliable when using SADs: the coefficient of determination (R²) was 0.60 without and 0.73 with SADs; and the intra-class correlation coefficient (ρ) was 0.72 without, and 0.86 with SADs. Thus, the use of SADs improved the precision, accuracy and reliability of visual estimates of severity of peach rust.     

Development and validation of a set of standard area diagrams to estimate severity of potato early blight

Standard area diagrams (SADs) to assess the severity of potato early blight (Alternaria grandis) on leaves of potato (Solanum tuberosum L.) were developed and validated. The proposed SADs include images of leaves with 10 distinct disease severities (0.1, 1, 3, 5, 10, 20, 40, 60, 80 and 100 %). The SADs were validated by 12 raters who had no previous experience in evaluating plant disease. Lin’s concordance correlation analysis of estimated vs. actual disease severity (based on image analysis) showed that precision and accuracy improved for most raters using the SADs, compared to assessments made without the SADs. The SADs improved accuracy (coefficient of bias, C _b ?=?0.97 and 0.99, without and with SADs, respectively) and agreement (Lin’s concordance correlation coefficient, ρ _c ?=?0.91 and 0.98 without and with SADs, respectively) of the estimates of severity. Severity estimates were more reliable when using SADs (coefficient of determination, R ² ?=?0.80 unaided and R ² ?=?0.95 with SADs, and the intra-class correlation ρ?=?0.86 without SADs and ρ?=?0.97 using the SADs). The SADs improved raters’ ability to accurately, precisely and reliably estimate potato early blight severity, and as such can be used to assess severity for several purposes, including breeding for resistance, fungicide screening, and pathotype characterization.     

Spatial pattern analysis of strawberry leaf blight in perennial production systems

ABSTRACT Spatial pattern of the incidence of strawberry leaf blight, caused by Phomopsis obscurans, was quantified in commercial strawberry fields in Ohio using statistics for heterogeneity and spatial correlation. For each strawberry planting, two transects were randomly chosen and the proportion of leaflets (out of 15) and leaves (out of five) with leaf blight symptoms was determined from N = 49 to 106 (typically 75) evenly spaced sampling units, thus establishing a natural spatial hierarchy to compare patterns of disease. The beta-binomial distribution fitted the data better than the binomial in 92 and 26% of the 121 data sets over 2 years at the leaflet and leaf levels, respectively, based on a likelihood ratio test. Heterogeneity in individual data sets was measured with the index of dispersion (variance ratio), C(alpha) test, a standard normal-based test statistic, and estimated theta parameter of the beta-binomial. Using these indices, overdispersion was detected in approximately 94 and 36% of the data sets at the leaflet and leaf levels, respectively. Estimates of the slope from the binary power law were significantly (P < 0.01) greater than 1 and estimates of the intercept were significantly greater than 0 (P < 0.01) at both the leaflet and leaf levels for both years, indicating that degree of heterogeneity was a function of incidence. A covariance analysis indicated that cultivar, time, and commercial farm location of sampling had little influence on the degree of heterogeneity. The measures of heterogeneity indicated that there was a positive correlation of disease status of leaflets (or leaves) within sampling units. Measures of spatial association in disease incidence among sampling units were determined based on autocorrelation coefficients, runs analysis, and a new class of tests known as spatial analysis by distance indices (SADIE). In general, from 9 to 22% of the data sets had a significant nonrandom spatial arrangement of disease incidence among sampling units, depending on which test was used. When significant associations existed, the magnitude of the association was small but was about the same for leaflets and leaves. Comparing test results, SADIE analysis was found to be a viable alternative to spatial autocorrelation analysis and has the advantage of being an extension of heterogeneity analysis rather than a separate approach. Collectively, results showed that incidence of Phomopsis leaf blight was primarily characterized by small, loosely aggregated clusters of diseased leaflets, typically confined within the borders of the sampling units.     

Effects of rater bias and assessment method on disease severity estimation with regard to hypothesis testing

The effects of bias (over‐ and underestimates) in estimates of disease severity on hypothesis testing using different assessment methods was explored. Nearest percentage estimates (NPE), the Horsfall–Barratt (H‐B) scale, and two linear category scales (10% increments, with and without additional grades at low severity) were compared using simulation modelling to assess effects of bias. Type I and type II error rates were used to compare two treatment differences. The power of the H‐B scale and the 10% scale were least for correctly testing a hypothesis compared with the other methods, and the effects of rater bias on type II errors were greater over specific severity ranges. Apart from NPEs, the amended 10% category scale was most often superior to other methods at all severities tested for reducing the risk of type II errors. It should thus be a preferred method for raters who must use a category scale for disease assessments. Rater bias and assessment method had little effect on type I error rates. The power of the hypothesis test using unbiased estimates was most often greater compared with biased estimates, regardless of assessment method. An unanticipated observation was the greater impact of rater bias compared with assessment method on type II errors. Knowledge of the effects of rater bias and scale type on hypothesis testing can be used to improve accuracy and reliability of disease severity estimates, and can provide a logical framework for improving aids to estimate severity visually, including standard area diagrams and rater training software.