992 resultados para cherry leaf spot


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The central aim for the research undertaken in this PhD thesis is the development of a model for simulating water droplet movement on a leaf surface and to compare the model behavior with experimental observations. A series of five papers has been presented to explain systematically the way in which this droplet modelling work has been realised. Knowing the path of the droplet on the leaf surface is important for understanding how a droplet of water, pesticide, or nutrient will be absorbed through the leaf surface. An important aspect of the research is the generation of a leaf surface representation that acts as the foundation of the droplet model. Initially a laser scanner is used to capture the surface characteristics for two types of leaves in the form of a large scattered data set. After the identification of the leaf surface boundary, a set of internal points is chosen over which a triangulation of the surface is constructed. We present a novel hybrid approach for leaf surface fitting on this triangulation that combines Clough-Tocher (CT) and radial basis function (RBF) methods to achieve a surface with a continuously turning normal. The accuracy of the hybrid technique is assessed using numerical experimentation. The hybrid CT-RBF method is shown to give good representations of Frangipani and Anthurium leaves. Such leaf models facilitate an understanding of plant development and permit the modelling of the interaction of plants with their environment. The motion of a droplet traversing this virtual leaf surface is affected by various forces including gravity, friction and resistance between the surface and the droplet. The innovation of our model is the use of thin-film theory in the context of droplet movement to determine the thickness of the droplet as it moves on the surface. Experimental verification shows that the droplet model captures reality quite well and produces realistic droplet motion on the leaf surface. Most importantly, we observed that the simulated droplet motion follows the contours of the surface and spreads as a thin film. In the future, the model may be applied to determine the path of a droplet of pesticide along a leaf surface before it falls from or comes to a standstill on the surface. It will also be used to study the paths of many droplets of water or pesticide moving and colliding on the surface.

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Modelling droplet movement on leaf surfaces is an important component in understanding how water, pesticide or nutrient is absorbed through the leaf surface. A simple mathematical model is proposed in this paper for generating a realistic, or natural looking trajectory of a water droplet traversing a virtual leaf surface. The virtual surface is comprised of a triangular mesh structure over which a hybrid Clough-Tocher seamed element interpolant is constructed from real-life scattered data captured by a laser scanner. The motion of the droplet is assumed to be affected by gravitational, frictional and surface resistance forces and the innovation of our approach is the use of thin-film theory to develop a stopping criterion for the droplet as it moves on the surface. The droplet model is verified and calibrated using experimental measurement; the results are promising and appear to capture reality quite well.

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Banana leaf streak disease, caused by several species of Banana streak virus (BSV), is widespread in East Africa. We surveyed for this disease in Uganda and Kenya, and used rolling-circle amplification (RCA) to detect the presence of BSV in banana. Six distinct badnavirus sequences, three from Uganda and three from Kenya, were amplified for which only partial sequences were previously available. The complete genomes were sequenced and characterised. The size and organisation of all six sequences was characteristic of other badnaviruses, including conserved functional domains present in the putative polyprotein encoded by open reading frame (ORF) 3. Based on nucleotide sequence analysis within the reverse transcriptase/ribonuclease H-coding region of open reading frame 3, we propose that these sequences be recognised as six new species and be designated as Banana streak UA virus, Banana streak UI virus, Banana streak UL virus, Banana streak UM virus, Banana streak CA virus and Banana streak IM virus. Using PCR and species-specific primers to test for the presence of integrated sequences, we demonstrated that sequences with high similarity to BSIMV only were present in several banana cultivars which had tested negative for episomal BSV sequences.

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A brief travel article about Chile

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The great male Aussie cossie is growing spots. The ‘dick’ tog, as it is colloquially referred to, is linked to Australia’s national identify with overtly masculine bronzed Aussie bodies clothed in this iconic apparel. Yet the reality is our hunger for worshiping the sun and the addiction to a beach lifestyle is tempered by the pragmatic need for neck-to-knee, or more apt head-to-toe, swimwear. Spotty Dick is an irreverent play on male swimwear – it experiments with alternate modes to sheath the body with Lyrca in order to protect it from searing UV’s and at the same time light-heartedly fools around with texture and pattern; to be specific, black Scharovsky crystals, jewelled in spot patterns - jewelled clothing is not characteristically aligned to menswear and even less so to the great Aussie cossie. The crystals form a matrix of spots that attempt to provoke a sense of mischievousness aligned to the Aussie beach larrikin. Ironically, spot patterns are in itself a form of a parody, as prolonged sun exposure ages the skin and sun spots can occur if appropriate sun protection is not used. ‘Spotty Dick’ – a research experiment to test design suitability for the use of jewelled spot matrix patterns for UV aware men’s swimwear. The creative work was paraded at 56 shows, over a 2 week period, and an estimated 50,000 people viewed the work.

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The use of mobile devices such as smart phones and tablets in classrooms has been met with mixed sentiments. Some instructors and teachers see them as a distraction and regularly ban their usage. Others who see their potential to enhance learning have started to explore ways to integrate them into their teaching in an attempt to improve student engagement. In this paper we report on a pilot study that forms part of a university-wide project reconceptualising its approach to the student evaluation of learning and teaching. In a progressive decision to embrace mobile technology, the university decided to trial a smart phone app designed for students to check-in to class and leave feedback on the spot. Our preliminary findings from trialling the app indicate that the application establishes a more immediate feedback loop between students and teachers. However, the app’s impact depends on how feedback is shared with students and how the teaching team responds.

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There is general agreement in the scientific community that entrepreneurship plays a central role in the growth and development of an economy in rapidly changing environments (Acs & Virgill 2010). In particular, when business activities are regarded as a vehicle for sustainable growth at large, that goes beyond mere economic returns of singular entities, encompassing also social problems and heavily relying on collaborative actions, then we more precisely fall into the domain of ‘social entrepreneurship’(Robinson et al. 2009). In the entrepreneurship literature, prior studies demonstrated the role of intentionality as the best predictor of planned behavior (Ajzen 1991), and assumed that the intention to start a business derives from the perception of desirability and feasibility and from a propensity to act upon an opportunity (Fishbein & Ajzen 1975). Recognizing that starting a business is an intentional act (Krueger et al. 2000) and entrepreneurship is a planned behaviour (Katz & Gartner 1988), models of entrepreneurial intentions have substantial implications for intentionality research in entrepreneurship. The purpose of this paper is to explore the emerging practice of social entrepreneurship by comparing the determinants of entrepreneurial intention in general versus those leading to startups with a social mission. Social entrepreneurial intentions clearly merit to be investigated given that the opportunity identification process is an intentional process not only typical of for profit start-ups, and yet there is a lack of research examining opportunity recognition in social entrepreneurship (Haugh 2005). The key argument is that intentionality in both traditional and social entrepreneurs during the decision-making process of new venture creation is influenced by an individual's perceptions toward opportunities (Fishbein & Ajzen 1975). Besides opportunity recognition, at least two other aspects can substantially influence intentionality: human and social capital (Davidsson, 2003). This paper is set to establish if and to what extent the social intentions of potential entrepreneurs, at the cognitive level, are influenced by opportunities recognition, human capital, and social capital. By applying established theoretical constructs, the paper draws comparisons between ‘for-profit’ and ‘social’ intentionality using two samples of students enrolled in Economy and Business Administration at the University G. d’Annunzio in Pescara, Italy. A questionnaire was submitted to 310 potential entrepreneurs to test the robustness of the model. The collected data were used to measure the theoretical constructs of the paper. Reliability of the multi-item scale for each dimension was measured using Cronbach alpha, and for all the dimensions measures of reliability are above 0.70. We empirically tested the model using structural equation modeling with AMOS. The results allow us to empirically contribute to the argument regarding the influence of human and social cognitive capital on social and non-social entrepreneurial intentions. Moreover, we highlight the importance for further researchers to look deeper into the determinants of traditional and social entrepreneurial intention so that governments can one day define better polices and regulations that promote sustainable businesses with a social imprint, rather than inhibit their formation and growth.

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Geminiviruses of the genera Begomovirus and Curtovirus utilize three replication modes: complementary-strand replication (CSR), rolling-circle replication (RCR) and recombinationdependent replication (RDR). Using two-dimensional gel electrophoresis, we now show for the first time that maize streak virus (MSV), the type member of the most divergent geminivirus genus, Mastrevirus, does the same. Although mastreviruses have fewer regulatory genes than other geminiviruses and uniquely express their replication-associated protein (Rep) from a spliced transcript, the replicative intermediates of CSR, RCR and RDR could be detected unequivocally within infected maize tissues. All replicative intermediates accumulated early and, to varying degrees, were already present in the shoot apex and leaves at different maturation stages. Relative to other replicative intermediates, those associated with RCR increased in prevalence during leaf maturation. Interestingly, in addition to RCR-associated DNA forms seen in other geminiviruses, MSV also apparently uses dimeric open circular DNA as a template for RCR. © 2010 SGM.

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The Beauty Leaf tree (Calophyllum inophyllum) is a potential source of non-edible vegetable oil for producing future generation biodiesel because of its ability to grow in a wide range of climate conditions, easy cultivation, high fruit production rate, and the high oil content in the seed. This plant naturally occurs in the coastal areas of Queensland and the Northern Territory in Australia, and is also widespread in south-east Asia, India and Sri Lanka. Although Beauty Leaf is traditionally used as a source of timber and orientation plant, its potential as a source of second generation biodiesel is yet to be exploited. In this study, the extraction process from the Beauty Leaf oil seed has been optimised in terms of seed preparation, moisture content and oil extraction methods. The two methods that have been considered to extract oil from the seed kernel are mechanical oil extraction using an electric powered screw press, and chemical oil extraction using n-hexane as an oil solvent. The study found that seed preparation has a significant impact on oil yields, especially in the screw press extraction method. Kernels prepared to 15% moisture content provided the highest oil yields for both extraction methods. Mechanical extraction using the screw press can produce oil from correctly prepared product at a low cost, however overall this method is ineffective with relatively low oil yields. Chemical extraction was found to be a very effective method for oil extraction for its consistence performance and high oil yield, but cost of production was relatively higher due to the high cost of solvent. However, a solvent recycle system can be implemented to reduce the production cost of Beauty Leaf biodiesel. The findings of this study are expected to serve as the basis from which industrial scale biodiesel production from Beauty Leaf can be made.