26 research outputs found

    Climatic effects on sugarcane ripening under the influence of cultivars and crop age

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    The lack of information about the effects of cultivars, crop age and climate on the sugarcane (Saccharum ssp.) crop yield and quality has been the primary factor impacting the sugar-ethanol sector in Brazil. One of the processes about which we do not have a satisfactory understanding is sugarcane ripening and the effects of cultivars, crop age and climate on that. Sugarcane ripening is the process of sucrose accumulation in stalks, which is heavily influenced by several factors, mainly by climatic conditions such as air temperature and water deficits. Because it is a complex process, studies of the variables involved in sugarcane ripening can provide important information, resulting in a better use of commercial cultivars, bringing advantages to growers, processing units, breeding programs and scientific community. In this review, we discuss the available knowledge of the interaction between climate conditions and sugarcane ripening, under the influence of genotypic characteristics and crop age. In several studies, the main conclusion is that sugarcane ripening depends on a complex combination of climate variables, the genetic potential of cultivars and crop management. Soil moisture and air temperature are the primary variables involved in sugarcane ripening, and their combination stimulates the intensity of the process. In addition, the need for studies integrating the effects of climate on plant physiological processes and on the use of chemical agents to stimulate sugarcane ripening is highlighted

    Application of holography to panel flutter

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    Continualization and Discretization

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    A dynamic data driven wildland fire model

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    We present an overview of an ongoing project to build DDDAS to use all available data for a short term wildfire prediction. The project involves new data assimilation methods to inject data into a running simulation, a physics based model coupled with weather prediction, on-site data acquisition using sensors that can survive a passing fire, and on-line visualization using Google Earth
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