Evaluation of App-Embedded Disease Scales for Aiding Visual Severity Estimation of Cercospora Leaf Spot of Table Beet.

Two diagrammatic ordinal scales are available in the Estimate app (2017 version) for Cercospora leaf spot (CLS) severity on table beet: 10% linear (linear-based diagrammatic scale [LIN]) and logarithmic based (Horsfall-Barratt [HB]). These allow for estimating severity data of four types depending on the system used. A group of 30 raters assigned percentage severity on 30 photographs of diseased table beet leaves during five rounds first without an aid and then using each of the four rating systems in Estimate. In two, the perceived ordinal score of the HB or LIN scale was assigned where severity of the subject fit best. HB2 and LIN2 involved a second choice of unitary severity within the perceived score interval. There was large variation in unaided ability of raters to estimate severity: 13% were accurate (Lin's concordance correlation [LCC] > 0.9), 23% were inaccurate (LCC < 0.7), and the remaining had moderate accuracy. Larger disparities between assigned and actual ordinal scores (mostly overestimates) occurred using the LIN compared with the HB. The LIN2 produced the most accurate estimates (Lin's concordance correlation coefficient, ρc = 0.96; generalized bias parameter, Cb = 0.99; Pearson's correlation coefficient r = 0.95) and the greatest interrater reliability (overall concordance correlation coefficient and intraclass correlation coefficient > 0.93). The two-step process using the 10% linear scale is recommended for severity estimates of CLS in table beet.

Genetic Diversity and Structure in Regional Cercospora beticola Populations from Beta vulgaris subsp. vulgaris Suggest Two Clusters of Separate Origin.

Cercospora leaf spot, caused by Cercospora beticola, is a highly destructive disease of Beta vulgaris subsp. vulgaris worldwide. C. beticola populations are usually characterized by high genetic diversity, but little is known of the relationships among populations from different production regions around the world. This information would be informative of population origin and potential pathways for pathogen movement. For the current study, the genetic diversity, differentiation, and relationships among 948 C. beticola isolates in 28 populations across eight geographic regions were investigated using 12 microsatellite markers. Genotypic diversity, as measured by Simpson's complement index, ranged from 0.18 to 1.00, while pairwise index of differentiation values ranged from 0.02 to 0.42, with the greatest differentiation detected between two New York populations. In these populations, evidence for recent expansion was detected. Assessment of population structure identified two major clusters: the first associated with New York, and the second with Canada, Chile, Eurasia, Hawaii, Michigan, North Dakota, and one population from New York. Inferences of gene flow among these regions suggested that the source for one cluster likely is Eurasia, whereas the source for the other cluster is not known. These results suggest a shared origin of C. beticola populations across regions, except for part of New York, where population divergence has occurred. These findings support the hypothesis that dispersal of C. beticola occurs over long distances.