A new standard area diagram set for assessment of severity of soybean rust improves accuracy of estimates and optimizes resource use

Abstract

Soybean rust (SBR), caused by Phakopsora pachyrhizi, is the most important yield‐damaging fungal disease of soybean due to severe reduction in healthy leaf area and acceleration of leaf fall. In experimental research, SBR severity is estimated visually aided/trained by a standard area diagram (SAD) developed and validated during the mid‐2000s (Old SAD). In this study, we propose a new SAD set for SBR with six true‐colour diagrams following linear increments (c. 15% increments) amended with four additional diagrams at low (<10%) severities, totalling 10 diagrams (0.2%, 1%, 3%, 5%, 10%, 25%, 40%, 55%, 70%, and 84%). For evaluation, 37 raters were split into two groups. Each assessed severity in a 50‐image sample (0.25%–84%), first unaided and then using either the Old SAD or the New SAD. Accuracy, precision, and reliability of estimates improved significantly relative to unaided estimates only when aided by the New SAD (accuracy >0.95). Low precision (<0.78) and a trend of underestimation with an increase in severity were the main issues with the Old SAD, which did not differ from unaided estimates. Simulation to evaluate the impact of the errors by different methods on hypothesis tests, showed that the new SAD was more powerful for detecting the smallest difference in mean control (e.g., 70% vs. 65% disease reduction) than the Old SAD; the latter required a 2‐fold increase in sample size to achieve the same power. There is a need to improve some SADs, taking advantage of new knowledge and technology to increase accuracy of the estimates, and to optimize both resource use efficiency and management decisions.

Severity assessment in the Nicotiana tabacum-Xylella fastidiosa subsp. pauca pathosystem: design and interlaboratory validation of a standard area diagram set

“…It is expected that for raters whose estimates are innately very accurate, the SADs usually have little positive effect, if any. In some occasions, the use of the SADs can be detrimental as shown in regression plots between gain/loss from using the SADs and unaided estimates (González-Domínguez et al 2014;Franceschi et al 2020;Melo et al 2020). This kind of response is not understood or easy to explain as it may be due to random error or specific test conditions.…”

“…The standard area diagram set (SADs) is a visual aid that generally, but not invariably, improves the accuracy of the visual estimates according to results by over a hundred validation studies (Bock et al 2016;Del Ponte et al 2017). Most commonly, a SADs is designed and validated for a specific disease and, occasionally, compared with existing ones (Del Ponte et al 2017;Franceschi et al 2020). In fact, a large and dynamic variation in the morphological features (number, size, shape, and color) of lesions exist among diseases given the infinite number of interactions from the combination of groups of pathogens, plants, and environment, which shape the symptomatic patterns (Lucas 2020).…”

A standard area diagram set for assessing severity of eucalyptus bacterial blight caused by Erwinia psidii

“…2). In most of the studies involving the validation of scales, raters tend to overestimate the disease severity levels (CAPUCHO et al, 2010;RIOS et al, 2013;FRANCESCHI et al, 2020), which also happened in this scale validation. However, this tendency decreased when the scale was used (Fig.…”

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

“…Although Kranz (1970) presented results which showed that error is not symmetrical (and logits were a suitable transformation), estimates did not follow the so-called Weber-Fechner law, because the standard deviation of rater estimates was similar and greatest between ≈18 and Fig. 3 The means and ranges of unaided estimates of disease severity A of stylized disease on 25 model leaves by 200 raters (Kranz 1970), B of symptoms of citrus canker on 200 leaves by 28 raters (Bock et al 2009a), and C of symptoms of soybean rust on 50 leaves by 37 raters Franceschi et al (2020). The standard deviations of the means are indicated in D, E, and F, respectively 52% compared to other severities (Fig.…”

“…Interestingly it was not a stated basis for defining incremental interval and number of diagrams in the pioneering work of James (1971). The basis for SADs design should probably be a linear scale, but with additional diagrams at low severity (Bock et al 2010a;Schwanck and Del Ponte 2014;Franceschi et al 2020).…”