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Sooty blotch and flyspeck control with fungicide applications based on calendar, local IPM, and warning system PAB
Spolti,Piérri; Valdebenito-Sanhueza,Rosa Maria; Gleason,Mark Lawrence; Del Ponte,Emerson Medeiros.
The objective of this work was to compare fungicide application timing for the control of sooty blotch and flyspeck (SBFS) of 'Fuji' apples in Rio Grande do Sul state, Brazil. The following treatments were evaluated in two growing seasons: two warning system-based (modified version of the Brown-Sutton-Hartmann system) spray of captan plus thiophanate methyl, with or without summer pruning; two calendar/rain-based spray of captan or a mixture of captan plus thiophanate methyl; fungicide spray timing based on a local integrated pest management (IPM) for the control of summer diseases; and a check without spraying. Sooty blotch and flyspeck incidence over time and their severity at harvest were evaluated. The highest number of spray was required by...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Malus domestica; Disease forecasting; Fungicide management; Integrated pest managemet.
Ano: 2011 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-204X2011000700004
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Obtaining weather data for input to crop disease-warning systems: leaf wetness duration as a case study Scientia Agricola
Gleason,Mark L.; Duttweiler,Katrina B.; Batzer,Jean C.; Taylor,S. Elwynn; Sentelhas,Paulo Cesar; Monteiro,José Eduardo Boffino Almeida; Gillespie,Terry J..
Disease-warning systems are decision support tools designed to help growers determine when to apply control measures to suppress crop diseases. Weather data are nearly ubiquitous inputs to warning systems. This contribution reviews ways in which weather data are gathered for use as inputs to disease-warning systems, and the associated logistical challenges. Grower-operated weather monitoring is contrasted with obtaining data from networks of weather stations, and the advantages and disadvantages of measuring vs. estimating weather data are discussed. Special emphasis is given to leaf wetness duration (LWD), not only because LWD data are inputs to many disease-warning systems but also because accurate data are uniquely challenging to obtain. It is concluded...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Integrated pest management; Site-specific weather data; Disease forecasting; Disease prediction; Sustainable agriculture.
Ano: 2008 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162008000700013
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Models and applications for risk assessment and prediction of Asian soybean rust epidemics Trop. Plant Pathol.
Del Ponte,Emerson M.; Godoy,Cláudia V.; Canteri,Marcelo G.; Reis,Erlei M.; Yang,X.B..
Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Phakopsora pachyrhizi; Disease forecasting; Disease simulation models; Fungal aerobiology.
Ano: 2006 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-41582006000600001
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