Sazonalidade de ocorrência de mofo cinzento, oídio e manchas bacterianas foliares em dois viveiros de produção de mudas clonais de eucalipto

• Ano de defesa: 2014
• Autor(a) principal: Gonçalves, Juliana de Lima [UNESP]
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual Paulista (Unesp)
• Palavras-chave em Português: Eucalipto; Patogeno de solo - Controle; Viveiros de mudas; Oídio; Nursey stock
• Link de acesso: http://hdl.handle.net/11449/108734

Occurrences of diseases can compromise the production of eucalyptus seedlings in any of its phases, as well as its establishment and forest productivity. Thus, their management is a major concern of the production process of eucalyptus seedlings and their quality control. In general, forest nurseries employ monitoring systems in order to support the decision of performing diseases control. However, there is still no standardized system nor a procedure fully integrated into the routine of seedling production professionals, which allows predicting the time of occurrence of the disease. Therefore, the aim of this study was to develop a system of data collection, by utilizing annual climatic parameters and simple variables, in order to have a study of seasonality to grey mold, bacterial leaf spots and powdery mildew, to support the decision making of chemical interventions and facilitate seedlings management. To do that, we monitored all production stages of two seedling production nurseries in the State of São Paulo: Capão Bonito and Jacareí. Such steps include the production of cuttings for clonal mini garden, rooting in the greenhouse, acclimation, growth and hardening of seedlings. To determine the seasonality of pathogens in the nurseries, it was necessary the standardization of the data collection and the preparation of a spreadsheet. To do so, it was set the following variables to be collected in each chemical intervention: name of the professional, date, time, pathogen, severity, location, product, dose, temperature and precipitation. The time series data were entered into Microsoft Excel® spreadsheets, processed by Pivot Tables and statistically analyzed by Minitab 16® statistical software, which generated the correlations between the influence of climatic factors on each of the mentioned diseases. The data collection worksheet proved to be very useful and the study of seasonality ...