Characteristics of the Perception of Different Severity Measures of Citrus Canker and the Relationships Between the Various Symptom Types

Abstract

Citrus canker is a disease of citrus and is caused by the bacterial pathogen Xanthomonas citri subsp. citri. Ways of managing the disease are being sought, and accurate, precise, reproducible disease assessment is needed for monitoring epidemics. The objective of this study was to investigate the characteristics of visual assessment of citrus canker symptoms compared with actual disease measured using image analysis (IA). Images of 210 citrus leaves with a range of incidence and severity of citrus canker were assessed by three plant pathologists (VR1-3) and by IA. The number of lesions (L), % area necrotic (%AN), and % area necrotic+chlorotic (%ANC) were assessed. The best relationships were found between %AN and %ANC (r2 = 0.41 to 0.87), and the worst between L and %AN (r2 = 0.27 to 0.66). Bland-Altman plots showed various sources of rater error in assessments, including under- and over-estimation, proportional error, and heterogeneity of variation dependent on actual disease magnitude. There was a tendency to overestimate area diseased, but not lesion counts, and this tendency was pronounced at lower disease severity, with a leaf having more lesions tending to be assessed as having greater area infected compared with a leaf with fewer lesions but equal actual area infected. The rater estimations of disease were less accurate or precise with increasing actual disease severity as indicated by the fit of a normal probability density function—the incidence of extreme values increases with increasing actual disease. For example, for %ANC the kurtosis of the distribution ranged from 17.92 to 1.18, 0.51, and 0.22 in actual disease category ranges of 0 to 10, 11 to 20, 21 to 30, and 31 to 40% area infected, respectively. The log variance of the estimates plotted against log actual disease for all three raters over two assessment occasions gave a linear relationship for L, %AN, and %ANC (r2 = 0.74, 0.65, and 0.74, respectively). Training should improve the accuracy, precision, and reproducibility of raters, and knowledge of the characteristics of disease assessment should help develop and target the training more appropriately and address specific causes and sources of error.