How much do standard area diagrams improve accuracy of visual estimates of the percentage area diseased? A systematic review and meta-analysis

• Published in: Tropical plant pathology 2022-02, Vol.47 (1), p.43-57
• Main Authors: Del Ponte, Emerson M., Cazón, Luis Ignacio, Alves, Kaique S., Pethybridge, Sarah J., Bock, Clive H.
• Format: Article
• Language: English
• Subjects: Accuracy; Bias; Biomedical and Life Sciences; Correlation coefficient; Correlation coefficients; Estimates; Lesions; Life Sciences; Meta-analysis; Original Article; Plant diseases; Plant Pathology; Reduction; Reviews; Statistical analysis; Systematic review
• ISSN: 1983-2052; 1982-5676; 1983-2052
• DOI: 10.1007/s40858-021-00479-5

Plant disease severity, when expressed as percentage area diseased, is commonly estimated visually without or with the aid of standard area diagram sets (SADs). It is generally thought that the use of SADs leads to 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 from using SADs. Overall, there was a reduction of 2.65 points in the intercept (from 3.41 to 0.76) indicating a reduction in the constant bias. Slope was less influenced and was reduced slightly (from 1.09 to 0.966), indicating a marginal reduction in 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 severity of 50% is seldom reached. In contrast, estimates of severity for diseases that cause only a few lesions and those diseases where the lesions coalesce and occupy more than 50% of the organ surface had greater accuracy, which 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 utility as an assessment aid.