Geostatistical analysis of bacterial blight in coffee tree seedlings in the nursery

• Autor(a) principal: Belan, Leônidas Leoni
• Data de Publicação: 2018
• Outros Autores: Pozza, Edson Ampélio, Alves, Marcelo de Carvalho, Freitas, Marcelo Loran de Oliveira
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFLA
• Texto Completo: http://repositorio.ufla.br/jspui/handle/1/34536
• topic: Pseudomonas syringae pv. garcae; Spatial dependence; Plant disease management; Epidemiology; Dependencia espacial; Manejo de doenças de plantas; Epidemiologia

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.