Improving accuracy, precision and reliability of severity estimates of Glomerella leaf spot on apple leaves using a new standard area diagram set

Moreira, Rafaele Regina; Duarte, Henrique da Silva Silveira; Mio, Louise Larissa May De

doi:10.1007/s10658-018-01610-0

Cited by 8 publications

(2 citation statements)

References 16 publications

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“…In this context, SADs are useful tools to assess the severity of plant disease because raters are able to estimate it with high accuracy and reliability. Several studies demonstrated that the use of SADs increased the accuracy, precision and reliability of the assessments of several diseases, such as blast (Rios, Debona, Duarte, & Rodrigues, 2013) and spot blotch (Domiciano, Duarte, Moreira, & Rodrigues, 2014) in wheat, Glomerella leaf spot in apple (Moreira, Duarte, & May‐De Mio, 2019), target spot in cotton (Fantin, Braga, Canteri, Dias, & Borges, 2018), frogeye leaf spot (Debona et al., 2015) and rust in soybean (Godoy, Koga, & Canteri, 2006), bacterial spot in tomato (Duan, Zhao, Wang, & Yang, 2015), rust in coffee (Capucho et al., 2011), leaf blight in eggplant (Correia et al., 2017) and bacterial blight in passion fruit (Monzani et al., 2018).…”

Section: Discussionmentioning

confidence: 99%

Standard area diagrams to assess scab severity of entire‐margined leaves of sour passion fruit

Brás

Rios

Silva

et al. 2020

Journal of Phytopathology

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Scab caused by the Cladosporium cladosporioides complex is one of the most important diseases affecting passion fruit yield and fruit quality. Standard area diagrams are useful tools to improve the accuracy and reliability of the estimates of disease severity in many pathosystems. The interpretation of the accuracy of the resulting disease data may be the basis for providing better disease management. This study aimed to develop and validate standard area diagrams (SADs) to quantify scab severity of entire‐margined leaves of sour passion fruit plants. The SADs are composed of ten images of scab severity values (0.4%, 3.5%, 5.4%, 8.0%, 11.1%, 16.2%, 26.1%, 38.2%, 47.9% and 58.9%). Twenty raters (ten experienced and ten inexperienced ones) evaluated the SADs. The raters estimated the same set of fifty images twice. In the examination, the SADs were used, while in the second examination, they were not used. Accuracy was significantly improved by using the SADs. The coefficients of bias (Cb) were 0.96 and 0.98 for the experienced raters and 0.75 and 0.98 for the inexperienced raters without and with SADs, respectively. The correlation coefficient (r) values were 0.95 and 0.97 for the experienced raters and 0.89 and 0.97 for the inexperienced raters without and with the use of the SADs, respectively. Lin's concordance correlation coefficient (ρc) values were 0.91 and 0.95 for the experienced raters and 0.66 and 0.95 for the inexperienced raters without and with the use of the SADs, respectively. Moreover, the coefficient of determination (R2) significantly improved when the SADs were used. The SADs proposed in this study, if properly used, may improve both the accuracy and reliability during the evaluation of scab severity of entire‐margined leaves of sour passion fruit plants.

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Section: Discussionmentioning

confidence: 99%

Standard area diagrams to assess scab severity of entire‐margined leaves of sour passion fruit

Brás

Rios

Silva

et al. 2020

Journal of Phytopathology

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“…SADs aid workers of various experiential background in the field when assessing plant damage ranging from wholeplant to single leaf symptoms (Vereijssen et al, 2003). Properly designed SADs have been shown to produce accurate and precise measures of disease when compared to the true disease score (Franceschi et al, 2020, Moreira et al, 2019. Notably, a SAD does not currently exist in sugar beet for Fusarium-induced diseases, therefore the aims of this study were to (1) develop a practical, useful and uniform standard area diagram for Fusarium yellows rating on sugar beet using expert raters as "trued" values, and to (2) assess the possibility of applying quick imaging and naïve bayes pixel quantification and imaging as a high throughput, equally accurate method for rating Fusarium-induced diseases.…”

Section: Introductionmentioning

confidence: 99%

A standard area diagram for Fusarium yellows rating in sugar beet (Beta vulgaris L.)

Todd,

Hanson,

Dorn

2024

Preprint

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Members of the Fusarium oxysporum species complex are pathogens of sugar beet causing Fusarium yellows. Fusarium yellows can reduce plant stand, yield, and extractable sugar. Improving host plant resistance against Fusarium-induced diseases, like Fusarium yellows, represents an important long-term breeding target in sugar beet breeding programs. Current methods for rating Fusarium yellows disease severity rely on an ordinal scale, which limits precision for intermediate phenotypes. In this study, we aimed to improve the accuracy and precision of rating Fusarium yellows by developing a standard area diagram (SAD). Two SAD versions were created using images of sugar beets infected with Fusarium oxysporum strain F19. Each version was tested using inexperienced raters. Comparing both the pilot and improved version showed no statistical differences in Lin's Concordance Correlation Coefficient (LCC) values to assess accuracy and precision between the two versions (Cb = 0.99 for both versions, Pc = 0.97 and 0.96 for version 1 and 2, respectively). In addition, five naive Bayesian machine learning models which used pixel classification to determine disease score, were tested for congruency to human estimates in version 2. Root mean square error was lowest compared to the true values for the unweighted model and a model where necrotic tissue was given a 2x weight (12.4 and 12.6, respectively). The creation of this standard area diagram enables breeding programs to make consistent, accurate disease ratings regardless of personnel's previous experience with Fusarium yellows. Additionally, more iterations of pixel quantification equations may overcome accuracy issues for rating Fusarium yellows.

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Comparative epidemiology of three Colletotrichum species complex causing Glomerella leaf spot on apple

Moreira

Filho²,

Zeviani

et al. 2020

Eur J Plant Pathol

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Improving accuracy, precision and reliability of severity estimates of Glomerella leaf spot on apple leaves using a new standard area diagram set

Cited by 8 publications

References 16 publications

Standard area diagrams to assess scab severity of entire‐margined leaves of sour passion fruit

Standard area diagrams to assess scab severity of entire‐margined leaves of sour passion fruit

A standard area diagram for Fusarium yellows rating in sugar beet (Beta vulgaris L.)

Comparative epidemiology of three Colletotrichum species complex causing Glomerella leaf spot on apple

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