Due to the lack of a standardized visual method for assessing bacterial blight (Pseudomonas syringae pv. garcae) in coffee leaves, a diagrammatic scale was developed and validated to quantify the disease. Leaves were collected in crops and nursery with different intensity of symptoms, and the true severity was determined electronically. Based on the frequency distribution of severity values and according to the Weber-Fechner's law of visual stimulus, the minimum and maximum limits and the intermediate levels in the scale were determined. Validation was performed by ten evaluators who estimated the severity of 50 leaves with different intensity of symptoms. One evaluation was performed without diagrammatic scale and two evaluations with the scale at 7-day intervals. The accuracy, precision, repeatability and reproducibility of the estimates were evaluated. The scale had nine levels: 0 (0%), 1 (0.1-0.99%), 2 (1-2%), 3 (2.01-4%), 4 (4.01-8%), 5 (8.01-16%), 6 (16.01-25%), 7 (25.01-45%) and 8 (≥45.1%). Using the scale, the evaluators were able to improve accuracy, precision, reproducibility and repeatability of estimates, compared to evaluators without scale. The scale was appropriate to visual estimation of severity of bacterial blight in coffee leaves.

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Given the damage and losses caused by bacterial blight of coffee (Pseudomonas syringae pv. garcae) (PSG) in coffee (Coffea arabica) seedling nurseries and lack of knowledge of the origin of the initial inoculum, the goal of this study was to determine whether coffee seeds can contain viable inoculum and spread bacterial inoculum. Seeds from plants with symptoms of bacterial blight of coffee were immersed in sterilized saline solution, and the crude extract obtained was inoculated in leaves of coffee seedlings. Leaves of plants inoculated with seed extract from symptomatic plants had symptoms of bacterial blight similar to those on leaves inoculated with reference isolate PSG. Seedlings inoculated with seed extract from asymptomatic plants showed no symptoms. Symptomatic leaves were submitted to exudate tests, and the etiologic agent was isolated in culture medium. The isolates with colonies morphologically similar to reference isolate PSG were selected and tested for hypersensitive reaction (HR) and pathogenicity to coffee seedlings. The isolates positive for HR and pathogenic to coffee also showed biochemical and molecular patterns equal to those of reference isolate PSG by the rep-PCR technique using Box primer. Thus, coffee seeds from plants with symptoms of bacterial blight can contain viable inoculum of P. syringae pv. garcae.

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In nurseries of coffee tree seedlings (Coffea arabica), there are favorable conditions for bacterial blight epidemics (Pseudomonas syringae pv. garcae). Studying the spatial distribution of diseased plants can help in the adoption of management strategies. Likewise, geostatistics has been applied to shape the spatial distribution and study epidemiological aspects of plant diseases. Thus, this study was developed to characterize the spatial distribution pattern of bacterial blight in a nursery of coffee tree seedlings. The disease progress was monitored over time in 704 seedlings organized in lines and columns in a nursery. Considering the mean diameter of the pots used for producing seedlings, georeferencing was carried out in Cartesian coordinate system for the seedlings in the nursery. The disease incidence data were subjected to non-spatial exploratory analysis and geostatistical analysis. The spherical isotropic semivariogram model was adjusted to the data and data interpolation was performed by ordinary kriging to visualize the spatial distribution of symptomatic seedlings. Bacterial blight epidemic was detected in the nursery during the experimental period, and there was variability and spatial dependence in relation to the distribution of diseased seedlings. As the epidemic progressed, the population of diseased plants increased, as well as the number and the size of the foci and their coalescence. Besides, there was an increase in the range value, sill and nugget effect. The kriging maps showed the disease progress and its variance. The bacterial blight epidemic of coffee tree started with a random spatial distribution pattern, progressing to an aggregate pattern.