Development and validation of a standard area diagram set to aid estimation of bacterial spot severity on tomato leaves

Duan, Junjie; Zhao, Bin; Wang, Yuqing; Yang, Wencai

doi:10.1007/s10658-015-0642-7

Cited by 16 publications

(10 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The increase in accuracy and precision of visual estimates, particularly those performed by inexperienced raters, has already been reported for different SADs developed for the evaluation of bacterial spot in several crops (Braido et al, 2015;Duan, Zhao, Wang, & Yang, 2015;Nuñez et al, 2017). These diagrams have been used directly in breeding programs, aiding in disease resistance and genotype selection evaluations (Berrueta, Gimenez, Galvan, & Borges, 2016;Varago, Citadin, Sachet, Penso, & Raseira, 2017).…”

Section: Introductionmentioning

confidence: 73%

“…The accuracy of estimates of each rater was determined by a t-test applied to the intercept of linear regression (a) to validate the hypothesis H o : a = 0, and to the slope coefficient of the line ( (Citadin et al, 2008;Duan et al, 2015), suggesting that this genus may cause severe damages when not adequately controlled. Severity values above 88% are rarely observed in sour passion fruit since they result in rapid leaf senescence.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Standard Area Diagram Set for Bacterial Spot Quantification in Entire-Margined Leaves of Sour Passion Fruit

Costa¹,

Peixoto²,

Blum³

et al. 2019

JAS

View full text Add to dashboard Cite

This study developed and validated a standard area diagram set (SADs) to aid in the estimation of bacterial spot (Xanthomonas axonopodis pv. passiflorae) severity in entire-margined leaves of sour passion fruit (Passiflora edulis Sims). The SADs consisted of eight severity levels (3; 6; 12; 25; 50; 77, and 88%). For its validation, 20 raters, who initially estimated the disease severity without the aid of the SADs, were divided into groups (G1 and G3, inexperienced; G2 and G4, experienced). Subsequently, G1 and G2 performed the second evaluation without the SADs, and G3 and G4 completed the second evaluation using the proposed SADs. The accuracy and precision of the assessments were determined by simple linear regression and by the Lin’s concordance correlation coefficient. The increase in accuracy was confirmed by the 80% constant error-free estimates (G3 and G4) and 100% (G3) and 80% (G4) systematic error-free estimates when the SADs was used. Precision increased with the increase in the coefficient of determination, the reduction in absolute errors, and the increase in the reproducibility of the estimates between pairs of raters. Inexperienced raters benefited the most from the use of the SADs. The increase in the accuracy and precision in the non-aided groups, when present, was less pronounced than those increments observed in the SADs-aided groups. The Lin’s concordance correlation coefficient confirmed the increased accuracy and precision detected by the linear regression analysis and indicated increased agreement between the estimated and actual values of disease severity in the SADs-aided groups.

show abstract

Section: Introductionmentioning

confidence: 73%

Section: Methodsmentioning

confidence: 99%

Standard Area Diagram Set for Bacterial Spot Quantification in Entire-Margined Leaves of Sour Passion Fruit

Costa¹,

Peixoto²,

Blum³

et al. 2019

JAS

View full text Add to dashboard Cite

show abstract

“…During the last 25 years, research on SAD development and validation has intensified, further demonstrating the value of SADs for improving accuracy (Del Ponte et al 2017). Gains using SADs are variable among raters and across pathosystems (Spolti et al 2011;Yadav et al 2013;Schwanck and Del Ponte 2014), and are generally greatest for those raters who are least accurate (Yadav et al 2013;Braido et al 2014;González-Domínguez et al 2014;Debona et al 2015;Duan et al 2015). Increase (Δ) in agreement (based on Lin's concordance correlation, ρ c ) may range from Δ > 0.4 for inexperienced raters, to Δ~0, or possibly a slight loss in agreement for innately accurate raters.…”

Section: Methods To Improve Accuracy Of Estimatesmentioning

confidence: 99%

From visual estimates to fully automated sensor-based measurements of plant disease severity: status and challenges for improving accuracy

et al. 2020

View full text Add to dashboard Cite

The severity of plant diseases, traditionally the proportion of the plant tissue exhibiting symptoms, is a key quantitative variable to know for many diseases and is prone to error. Good quality disease severity data should be accurate (close to the true value). Earliest quantification of disease severity was by visual estimates. Sensor-based image analysis including visible spectrum and hyperspectral and multispectral sensors are established technologies that promise to substitute, or complement visual ratings. Indeed, these technologies have measured disease severity accurately under controlled conditions but are yet to demonstrate their full potential for accurate measurement under field conditions. Sensor technology is advancing rapidly, and artificial intelligence may help overcome issues for automating severity measurement under hyper-variable field conditions. The adoption of appropriate scales, training, instruction and aids (standard area diagrams) has contributed to improved accuracy of visual estimates. The apogee of accuracy for visual estimation is likely being approached, and any remaining increases in accuracy are likely to be small. Due to automation and rapidity, sensor-based measurement offers potential advantages compared with visual estimates, but the latter will remain important for years to come. Mobile, automated sensor-based systems will become increasingly common in controlled conditions and, eventually, in the field for measuring plant disease severity for the purpose of research and decision making.

show abstract

“…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

View full text Add to dashboard Cite

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.

show abstract

Development and validation of a standard area diagram set to aid estimation of bacterial spot severity on tomato leaves

Cited by 16 publications

References 33 publications

Standard Area Diagram Set for Bacterial Spot Quantification in Entire-Margined Leaves of Sour Passion Fruit

Standard Area Diagram Set for Bacterial Spot Quantification in Entire-Margined Leaves of Sour Passion Fruit

From visual estimates to fully automated sensor-based measurements of plant disease severity: status and challenges for improving accuracy

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

Contact Info

Product

Resources

About