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

Sachet, Marcos Robson; Citadin, Idémir; Danner, Moeses Andrigo; Guerrezi, Marieli Teresinha; Pertille, Rafael Henrique

doi:10.1590/0103-8478cr20160924

Cited by 8 publications

(6 citation statements)

References 2 publications

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“…However, training raters may result in a standardized evaluation, reducing the observed discrepancies and consequently increasing the reliability of the estimates among pairs of raters. Various studies have demonstrated the relevance of training to increase performance, especially for the less experienced raters (González-Dominguez et al, 2014;Bock et al, 2016;Sachet, Citadin, Danner, Guerrezi, & Pertille, 2017). Table 1.…”

Section: Resultsmentioning

confidence: 99%

Standard Area Diagram Set for Scab Evaluation in Fruits of sour Passion Fruit

Costa¹,

Peixoto²,

Blum³

et al. 2019

JAS

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Scab (Cladosporium spp.) significantly comprises the commercial acceptance of sour passion fruit (Passiflora edulis) because of the deformed and atrophied fruit appearance resulting from the development of the lesions. Therefore, the objective of this study was to elaborate and validate a standard area diagram set (SADs) for the severity evaluation of scab in fruits of sour passion fruit. The SADs comprised eight severity levels (0.6; 1; 2; 4; 8; 16; 37; and 46%) and was validated by 20 raters (G1 and G3, inexperienced; G2 and G4, experienced). Initially, all raters performed a non-aided SADs evaluation of the scab severity. Afterward, G1 and G2 completed the second evaluation without the proposed SADs, whereas G3 and G4 performed a SADs-aided assessment of the disease severity. The accuracy and precision of the evaluations were determined by simple linear regression and by the Lin’s concordance correlation coefficient. Constant and systematic errors decreased with the use of the SADs, demonstrating an approximation between the estimated and the actual values. Precision increased with an increase in the coefficient of determination. Also, the absolute error reduced by 66% (G3) and 47% (G4). Therefore, 94.4% (G3) and 98.8% (G4) of the estimates had up to ±10% of errors, which corresponds to a 20.4% (G3) and 5.6% (G4) increment in the estimates with errors within this variation range. As a result, accuracy and precision were higher in the SADs-aided groups. Inexperienced raters were the most benefited by the use of the SADs. The accuracy and precision of the non-aided groups had a slight or no increase when compared with the SADs-aided groups.

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Section: Resultsmentioning

confidence: 99%

Standard Area Diagram Set for Scab Evaluation in Fruits of sour Passion Fruit

Costa¹,

Peixoto²,

Blum³

et al. 2019

JAS

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“…OLS images (228 pictures), of known severity, were inserted into the Disease Plan spreadsheet, which performs the randomization of images, estimate recording and agreement statistics (SACHET et al, 2016). The precision, accuracy, deviations from the ideal projection, Lin`s concordant correlation coefficient as shown by NICOLI et al (2015) and the smallest difference detectable value based on the random effect of the one-way ANOVA corresponding to the least significant difference (DMS-t com P=0.05) were evaluated.…”

Section: Crop Protectionmentioning

confidence: 99%

Standard area diagram set for olive leaf spot assessment

et al. 2017

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The establishment of olive (Olea europaea) orchards in Brazil is increasing due to their economic potential and benefits to human health. However, a number of limiting factors need to be overcome, such as Olive Leaf Spot (OLS) occurrence, for olives to reach their full potential. OLS, which is caused by Fusicladium oleaginum, results in defoliation and a reduction in fruit production. This study aimed to develop a standard area diagram set (SAD) for the assessment of OLS severity under humid subtropical climate conditions. The SAD was developed with six levels of severity (1, 3, 6, 9, 12 and 15%) and OLS severity was validated by eight inexperienced raters. Using the SAD provided an increase in accuracy, precision and concordance, while also reducing the smallest difference detectable. The proposed SAD was adequate at estimating the OLS and could be a useful tool for use in epidemiological and phytopathometry studies, evaluation of control strategies and selection of resistant genotypes.

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“…Interestingly, the development of these computer programs in the 1980s and 1990s was not immediately followed by computerized systems with greater sophistication to draw more realistic symptomatic digital leaves, despite the advances in software engineering. Indeed, there have been very few training programs developed since (Aubertot et al 2004;Sachet et al 2017).…”

Section: Arrival Of Personal Computers and Programs To Aid In Assessment Trainingmentioning

confidence: 99%

“…The inexpensive availability of scanners and portable digital cameras in the early 2000s, and the development of plant disease-specific image analysis software facilitated development of SADs (Del Ponte et al 2017 (Sachet et al 2017).…”

Section: Establishment and Evolution Of Sads Researchmentioning

confidence: 99%

Plant disease severity estimated visually: a century of research, best practices, and opportunities for improving methods and practices to maximize accuracy

Bock

Chiang

Ponte

2021

Trop. plant pathol.

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Plant disease quantification, mainly the intensity of disease symptoms on individual units (severity), is the basis for a plethora of research and applied purposes in plant pathology and related disciplines. These include evaluating treatment effect, monitoring epidemics, understanding yield loss, and phenotyping for host resistance. Although sensor technology has been available to measure disease severity using the visible spectrum or other spectral range imaging, it is visual sensing and perception that still dominates, especially in field research. Awareness of the importance of accuracy of visual estimates of severity began in 1892, when Cobb developed a set of diagrams as an aid to guide estimates of rust severity in wheat. Since that time, various approaches, some of them based on principles of psychophysics, have provided a foundation to understand sources of error during the estimation process as well as to develop different disease scales and disease-specific illustrations indicating the diseased area on specimens, similar to that developed by Cobb, and known as standard area diagrams (SADs). Several rater-related (experience, inherent ability, training) and technology-related (instruction, scales, and SADs) characteristics have been shown to affect accuracy. This review provides a historical perspective of visual severity assessment, accounting for concepts, tools, changing paradigms, and methods to maximize accuracy of estimates. A list of best-operating practices in plant disease quantification and future research on the topic is presented based on the current knowledge.

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

Cited by 8 publications

References 2 publications

Standard Area Diagram Set for Scab Evaluation in Fruits of sour Passion Fruit

Standard Area Diagram Set for Scab Evaluation in Fruits of sour Passion Fruit

Standard area diagram set for olive leaf spot assessment

Plant disease severity estimated visually: a century of research, best practices, and opportunities for improving methods and practices to maximize accuracy

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