Using voice input for improving the efficiency of surveying plant disease severity

Plant disease severity is commonly estimated visually without or with the aid of standard area diagram sets (SADs). It is generally believed that the use of SADs leads to less biased (more accurate) and thus more precise estimates, but the degree of improvement has not been characterized in a systematic manner. We built on a previous review and screened 153 SAD studies published from 1990 to 2021. A systematic review resulted in a selection of 72 studies that reported three linear regression statistics for individual raters, which are indicative of the two components of bias (intercept = constant bias; slope = systematic bias) and precision (Pearson's correlation coefficient, r), to perform a meta-analysis of these accuracy components. The meta-analytic model determined an overall gain of 0.07 (r increased from 0.88 to 0.95) in precision. Globally, there was a reduction of 2.65 units in the intercept, from 3.41 to 0.76, indicating a reduction in the constant bias. Slope was least affected and was reduced slightly from 1.09 to 0.966, indicating marginally less systematic bias when using SADs. A multiple correspondence analysis suggested an association of less accurate, unaided estimates with diseases that produce numerous lesions and for which maximum severities of 50% are rarely attained. On the other hand, more accurate estimates were observed with diseases that cause only a few lesions and those diseases where the lesions coalesce and occupy more than 50% of the specimen surface. This was most pronounced for specimen types other than leaves. By quantitatively exploring how characteristics of the pathosystem and how SADs affect precision and constant and systematic biases, we affirm the value of SADs for reducing bias and imprecision of visual assessments. We have also identified situations where SADs have greater or lesser effects as an assessment aid.

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Systemic Acquired Resistance Delays Race Shifts to Major Resistance Genes in Bell Pepper

Phytopathology ◽

10.1094/phyto.2004.94.12.1376 ◽

2004 ◽

Vol 94 (12) ◽

pp. 1376-1382 ◽

Cited By ~ 8

Author(s):

A. M. Romero ◽

D. F. Ritchie

Keyword(s):

Disease Severity ◽

Plant Disease Resistance ◽

Plant Disease ◽

Systemic Acquired Resistance ◽

Field Experiments ◽

Specific Resistance ◽

Acquired Resistance ◽

R Genes ◽

Host Pathogen Interaction ◽

Major Resistance Genes

The lack of durability of host plant disease resistance is a major problem in disease control. Genotype-specific resistance that involves major resistance (R) genes is especially prone to failure. The compatible (i.e., disease) host-pathogen interaction with systemic acquired resistance (SAR) has been studied extensively, but the incompatible (i.e., resistant) interaction less so. Using the pepper-bacterial spot (causal agent, Xanthomonas axonopodis pv. vesicatoria) pathosystem, we examined the effect of SAR in reducing the occurrence of race-change mutants that defeat R genes in laboratory, greenhouse, and field experiments. Pepper plants carrying one or more R genes were sprayed with the plant defense activator acibenzolar-S-methyl (ASM) and challenged with incompatible strains of the pathogen. In the greenhouse, disease lesions first were observed 3 weeks after inoculation. ASM-treated plants carrying a major R gene had significantly fewer lesions caused by both the incompatible (i.e., hypersensitive) and compatible (i.e., disease) responses than occurred on nonsprayed plants. Bacteria isolated from the disease lesions were confirmed to be race-change mutants. In field experiments, there was a delay in the detection of race-change mutants and a reduction in disease severity. Decreased disease severity was associated with a reduction in the number of race-change mutants and the suppression of disease caused by the race-change mutants. This suggests a possible mechanism related to a decrease in the pathogen population size, which subsequently reduces the number of race-change mutants for the selection pressure of R genes. Thus, inducers of SAR are potentially useful for increasing the durability of genotype-specific resistance conferred by major R genes.

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A phytopathometry glossary for the twenty-first century: towards consistency and precision in intra- and inter-disciplinary dialogues

Tropical Plant Pathology ◽

10.1007/s40858-021-00454-0 ◽

2021 ◽

Author(s):

Clive H. Bock ◽

Sarah J. Pethybridge ◽

Jayme G. A. Barbedo ◽

Paul D. Esker ◽

Anne-Katrin Mahlein ◽

...

Keyword(s):

Plant Pathology ◽

Disease Severity ◽

Plant Disease ◽

Yield Loss ◽

First Century ◽

Control Methods ◽

Visual Estimation ◽

Disease Symptoms ◽

Disease Epidemiology ◽

Measurement Science

AbstractPhytopathometry can be defined as the branch of plant pathology (phytopathology) that is concerned with estimation or measurement of the amount of plant disease expressed by symptoms of disease or signs of a pathogen on a single or group of specimens. Phytopathometry is critical for many reasons, including analyzing yield loss due to disease, breeding for disease resistance, evaluating and comparing disease control methods, understanding coevolution, and studying disease epidemiology and pathogen ecology. Phytopathometry underpins all activities in plant pathology and extends into related disciplines, such as agronomy, horticulture, and plant breeding. Considering this central role, phytopathometry warrants status as a formally recognized branch of plant pathology. The glossary defines terms and concepts used in phytopathometry based on disease symptoms or visible pathogen structures and includes those terms commonly used in the visual estimation of disease severity and sensor-based methods of disease measurement. Relevant terms from the intersecting disciplines of measurement science, statistics, psychophysics, robotics, and artificial intelligence are also included. In particular, a new, broader definition is proposed for “disease severity,” and the terms “disease measurement” and “disease estimate” are specifically defined. It is hoped that the glossary contributes to a more unified cross-discipline approach to research in, and application of the tools available to phytopathometry.

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Resistance of Hosta Cultivars to Petiole Rot Caused by Sclerotium rolfsii var. delphinii

HortTechnology ◽

10.21273/horttech.13.2.0302 ◽

2003 ◽

Vol 13 (2) ◽

pp. 302-305 ◽

Cited By ~ 2

Author(s):

Brooke A. Edmunds ◽

Mark L. Gleason ◽

Stephen N. Wegulo

Keyword(s):

Disease Severity ◽

Plant Disease ◽

Leaf Shape ◽

Sclerotium Rolfsii ◽

Disease Development ◽

Wide Range ◽

Bare Root

Eighteen cultivars of hosta (Hosta spp.), selected to represent a wide range of size, leaf shape and color, and genetics, were evaluated for reaction to Sclerotium rolfsii var. delphinii in a greenhouse in Ames, Iowa in 2000 and 2001. Bare-root, single-eye plants were planted in 15.2-cm (6-inch) pots in a soil-containing (2000) and soilless (2001) mix and grown in a greenhouse for 3 months. Plants were then inoculated by placing a carrot disk infested with mycelium of S. rolfsii at the base of the plant. Disease severity was assessed weekly for 6 weeks as percent symptomatic petioles. Disease development varied significantly (P < 0.05) among cultivars. Overall, `Lemon Lime', `Munchkin', `Nakaiana', `Platinum Tiara', and `Tardiflora' had the most severe symptoms and `Halcyon' showed the least disease.

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The Relationship Between Plant Disease Severity and Yield

Annual Review of Phytopathology ◽

10.1146/annurev.py.33.090195.001003 ◽

1995 ◽

Vol 33 (1) ◽

pp. 119-144 ◽

Cited By ~ 84

Author(s):

R E Gaunt

Keyword(s):

Disease Severity ◽

Plant Disease ◽

The Relationship

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Use of Multispectral Radiometry for Assessment of Rhizoctonia Blight in Creeping Bentgrass

Phytopathology ◽

10.1094/phyto.1998.88.5.446 ◽

1998 ◽

Vol 88 (5) ◽

pp. 446-449 ◽

Cited By ~ 30

Author(s):

C. Raikes ◽

L. L. Burpee

Keyword(s):

Disease Severity ◽

Regression Models ◽

Plant Disease ◽

Near Infrared ◽

Linear Regression Analysis ◽

Creeping Bentgrass ◽

Anastomosis Group ◽

Disease Assessment ◽

Canopy Reflectance ◽

Group 2

The ability to identify diseases early and quantify severity accurately is crucial in plant disease assessment and management. This study was conducted to assess changes in the spectral reflectance of sunlight from plots of creeping bentgrass during infection by Rhizoctonia solani, the cause of Rhizoctonia blight, and to evaluate multispectral radiometry as a tool to quantify Rhizoctonia blight severity. After inoculation of 6-year-old creeping bentgrass turf with R. solani anastomosis group 2-2, reflectance of sunlight from the foliar canopy was measured at light wavelengths of 460 nm (blue) to 810 nm (near infrared [NIR]), at 50-nm intervals. Visual estimates of disease severity and percentage of canopy reflectance were made daily throughout each of three epidemics of Rhizoctonia blight from the onset of visible symptoms until maximum disease severity was reached. In each experiment, linear regression analysis revealed a significant reduction in the percentage of NIR (760 and 810 nm) reflectance as disease severity increased. However, in the majority of analyses, regression models explained <50% of the variability between components. Multispectrum radiometry appears to function best when used to assess differences in disease severity at discrete points in time rather than over an entire epidemic.

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DiseasePlan - a spreadsheet application for training people to assess disease severity and to assist with standard area diagram development

Ciência Rural ◽

10.1590/0103-8478cr20160924 ◽

2017 ◽

Vol 47 (6) ◽

Cited By ~ 1

Author(s):

Marcos Robson Sachet ◽

Idemir Citadin ◽

Moeses Andrigo Danner ◽

Marieli Teresinha Guerrezi ◽

Rafael Henrique Pertille

Keyword(s):

Disease Severity ◽

Plant Disease ◽

Visual Assessment ◽

Computer Applications ◽

Performance Statistics ◽

To Receive ◽

Spreadsheet Application

ABSTRACT: Several computer applications have been proposed for the visual assessment of plant disease severity; however, they have some restrictions such as not permitting the user to make modifications. Therefore, the VBA-Excel application was developed as a means to train people to estimate disease severity and to validate standard area diagrams through images and disease severity values (percentage, rating or score) inserted into a database. The main performance statistics are screen displayed and spreadsheet recorded. Finally, the authors hope to receive evaluations and feedback regarding this application.

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