998 resultados para tree training
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Over the last 60 years, planting densities for apple have increased as improved management systems have been developed. Dwarfing rootstocks have been the key to the dramatic changes in tree size, spacing and early production. The Malling series of dwarfing rootstocks (M.9 and M.26) have been the most important dwarfing rootstocks in the world but are poorly adapted in some areas of the world and they are susceptible to the bacterial disease fire blight and the soil disease complex, apple replant disease which limits their uses in some areas. Rootstock breeding programs in several parts of the world are developing improved rootstocks with resistance to fire blight, and replant disease, and improved cold hardiness and yield efficiency. A second important trend has been the increasing importance of new cultivars. New cultivars have provided opportunities for higher prices until they are over-produced. A new trend is the "variety club" in which variety owners manage the production and marketing of a new unique cultivar to bring higher prices to the growers and variety owners. This has led to many fruit growers being unable to plant or grow some new cultivars. Important rootstock and cultivar genes have been mapped and can be used in marker assisted selection of future rootstock and cultivar selections. Other important improvements in apple culture include the development of pre-formed trees, the development of minimal pruning strategies and limb angle bending which have also contributed to the dramatic changes in early production in the 2nd-5th years after planting. Studies on light interception and distribution have led to improved tree forms with better fruit quality. Simple pruning strategies and labor positioning platform machines have resulted in partial mechanization of pruning which has reduced management costs. Improved plant growth regulators for thinning and the development of a thinning prediction model based on tree carbohydrate balance have improved the ability to produce the optimum fruit size and crop load. Other new plant growth regulators have also allowed control of shoot growth, control of preharvest fruit drop and control of fruit softening in storage after harvest. As we look to the future, there will be continued incremental improvement in our understanding of plant physiology that will lead to continued incremental improvements in orchard management but there is likely to be dramatic changes in orchard production systems through genomics research and genetic engineering. A greater understanding of the genetic control of dwarfing, precocity, rooting, vegetative growth, flowering, fruit growth and disease resistance which will lead to new varieties and rootstocks which are less expensive to grow and manage.
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Starch is the main form in which plants store carbohydrates reserves, both in terms of amounts and distribution among different plant species. Carbohydrates are direct products of photosynthetic activity, and it is well know that yield efficiency and production are directly correlated to the amount of carbohydrates synthesized and how these are distributed among vegetative and reproductive organs. Nowadays, in pear trees, due to the modernization of orchards, through the introduction of new rootstocks and the development of new training systems, the understanding and the development of new approaches regarding the distribution and storage of carbohydrates, are required. The objective of this research work was to study the behavior of carbohydrate reserves, mainly starch, in different pear tree organs and tissues: i.e., fruits, leaves, woody organs, roots and flower buds, at different physiological stages during the season. Starch in fruit is accumulated at early stages, and reached a maximum concentration during the middle phase of fruit development; after that, its degradation begins with a rise in soluble carbohydrates. Moreover, relationships between fruit starch degradation and different fruit traits, soluble sugars and organic acids were established. In woody organs and roots, an interconversion between starch and soluble carbohydrates was observed during the dormancy period that confirms its main function in supporting the growth and development of new tissues during the following spring. Factors as training systems, rootstocks, types of bearing wood, and their position on the canopy, influenced the concentrations of starch and soluble carbohydrates at different sampling dates. Also, environmental conditions and cultural practices must be considered to better explain these results. Thus, a deeper understanding of the dynamics of carbohydrates reserves within the plant could provide relevant information to improve several management practices to increase crop yield efficiency.
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We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS-DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of 884,126 SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: 14 <= r <= 21 (85.2%) and r >= 19 (82.1%). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT, and Ball et al. We find that our FT classifier is comparable to or better in completeness over the full magnitude range 15 <= r <= 21, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes (r > 19), our classifier is the only one that maintains high completeness (> 80%) while simultaneously achieving low contamination (similar to 2.5%). We also examine the SDSS parametric classifier (psfMag - modelMag) to see if the dividing line between stars and galaxies can be adjusted to improve the classifier. We find that currently stars in close pairs are often misclassified as galaxies, and suggest a new cut to improve the classifier. Finally, we apply our FT classifier to separate stars from galaxies in the full set of 69,545,326 SDSS photometric objects in the magnitude range 14 <= r <= 21.
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Summary: Amphibians are among the most vulnerable animals of the world. One third of all species are currently threatened with extinction. Habitat loss is the major menace to pond- and stream-breeding species in the old world. In highly urbanized landscape like the Swiss Plateau, most species suffer from habitat reduction and fragmentation. Among all indigenous species, the European tree frog (Hyla arborea L., 1758) is one of the most endangered. It experienced an alarming decline during the last century and its regional long-term persistence is not guaranteed. We developed a monitoring framework based on calling male counts which included multiple visits to each wetland during the reproduction period in order to precisely determine its distribution on the Lemanic coast. Our results indicate that visiting populations 3 limes under suitable climatic conditions (temperature >20°C) provides reliable presence/absence data. Based on our monitoring data, we analyzed the species requirements regarding its breeding habitat. It appeared that anthropogenic activities had paradoxical effects on the species. On one hand, urbanization, traffic and intensive agriculture had a strong detrimental effect on tree frog distribution. On the other hand, large tree frog populations were frequently associated with gravel pits and military training grounds. Our results allowed us to create a habitat suitability map taking into account detrimental landscape elements around ponds (>1100m away from urban areas and >500m away from first class roads). In parallel, we developed a metapopulation model of the European tree frog in order to identify the critical threats to the long term persistence of the species. Our results indicated that suitable pond density is at the low end of the species requirements. Pond creation must therefore be considered an essential complementary approach to pond conservation and restoration. Our model also provided a mapping solution permitting the location of the must suitable area for pond creation from a metapopulation perspective. As many other amphibians, the European tree frog is not only exposed to an aquatic habitat (breeding and larval period), but also to a terrestrial stage (summer and overwintering habitats). Unfortunately, animals in their terrestrial phase are less conspicuous and, as a consequence, their terrestrial needs are relatively unknown. Using a recent tracking method (the Harmonic Direction Finder), we followed post-breeding frogs and identified favored terrestrial habitats, thus providing another practical conservation tool. We conclude that only the combination of multiple spatially explicit approaches (landscape-scale habitat suitability, metapopulation dynamics and terrestrial needs) is likely to provide wildlife managers with effective tools for the conservation of highly endangered amphibians. Résumé: Les amphibiens font partie des animaux les plus vulnérables du monde. Un tiers des espèces est actuellement menacé d'extinction. Dans l'ancien monde, la disparition des habitats constitue la principale menace pour les grenouilles, crapauds, tritons et salamandres. Dans les paysages fortement urbanisés comme le Plateau Suisse, la plupart des espèces souffrent d'une réduction et d'une fragmentation de leurs habitats. Parmi toutes les espèces indigènes, la rainette verte (Hyla arborea L., 1758) est l'une des plus menacée. Sa distribution a régressé de manière alarmante durant le siècle passé et sa survie régionale à long terme n'est pas assurée. Nous avons développé une méthode de suivi des populations se basant sur le comptage des mâles chanteurs durant la période de reproduction. Cette méthode requiert plusieurs visites à chaque plan d'eau de manière à déterminer précisément la distribution de l'espèce. Nos résultats démontrent que 3 visites par population dans des conditions climatiques favorable (température >20°C) permettent d'obtenir des données de présence/ absence valables. Sur la base de nos comptages sur la Côte lémanique, nous avons analysé les exigences de l'espèce concernant ses sites de reproduction. Il est apparu que les activités humaines avaient un effet paradoxal sur l'espèce. D'une part, l'urbanisation, le trafic routier et l'intensification de l'agriculture ont un effet fortement préjudiciable, tandis que d'autre part les plus grandes populations sont souvent associées à des gravières et autres places d'armes. Nos résultats ont permis de créer une carte de qualité d'habitat prenant en compte les éléments paysagers préjudiciables à la rainette (situé à plus de 1100m de zones urbaines et à plus de 500m de routes de première classe). En parallèle, nous avons développé un modèle métapopulationnel (incluant l'ensemble des populations) de manière à identifier les menaces prépondérantes sur la survie à long terme de l'espèce. Nos résultats ont permis de déterminer que la densité actuelle de plans d'eau adéquats est à la limite inférieure des exigences de l'espèce. La création d'étangs doit donc être considérée comme une approche indispensable et complémentaire à la protection et à la restauration des sites existants. Notre modèle a également fourni des résultats cartographiables permettant l'identification des sites les plus appropriés dans une perspective métapopulationnelle. Comme de nombreux autres amphibiens, la rainette verte est exposée à un habitat aquatique (reproduction et développement larvaire) ainsi qu'à un habitat terrestre (été et hiver). Les animaux étant particulièrement cryptiques dans cette seconde phase, leurs besoins terrestres sont relativement mal connus. Nous avons donc développé une nouvelle méthode de télémétrie basée sur le goniomètre harmonique. Cette méthode nous a permis de suivre des rainettes dans leurs migrations jusqu'à leurs habitats d'été et d'établir ainsi des recommandations pratiques pour la conservation de la rainette. Nous concluons que la combinaison de multiples approches spatialement explicites (qualité d'habitat, dynamique de métapopulation et habitats terrestres) est seule à même de produire des outils efficaces pour la conservation des espèces menacées d'amphibiens.
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PURPOSE: The objective of this experiment is to establish a continuous postmortem circulation in the vascular system of porcine lungs and to evaluate the pulmonary distribution of the perfusate. This research is performed in the bigger scope of a revascularization project of Thiel embalmed specimens. This technique enables teaching anatomy, practicing surgical procedures and doing research under lifelike circumstances. METHODS: After cannulation of the pulmonary trunk and the left atrium, the vascular system was flushed with paraffinum perliquidum (PP) through a heart-lung machine. A continuous circulation was then established using red PP, during which perfusion parameters were measured. The distribution of contrast-containing PP in the pulmonary circulation was visualized on computed tomography. Finally, the amount of leak from the vascular system was calculated. RESULTS: A reperfusion of the vascular system was initiated for 37 min. The flow rate ranged between 80 and 130 ml/min throughout the experiment with acceptable perfusion pressures (range: 37-78 mm Hg). Computed tomography imaging and 3D reconstruction revealed a diffuse vascular distribution of PP and a decreasing vascularization ratio in cranial direction. A self-limiting leak (i.e. 66.8% of the circulating volume) towards the tracheobronchial tree due to vessel rupture was also measured. CONCLUSIONS: PP enables circulation in an isolated porcine lung model with an acceptable pressure-flow relationship resulting in an excellent recruitment of the vascular system. Despite these promising results, rupture of vessel walls may cause leaks. Further exploration of the perfusion capacities of PP in other organs is necessary. Eventually, this could lead to the development of reperfused Thiel embalmed human bodies, which have several applications.
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Continuous field mapping has to address two conflicting remote sensing requirements when collecting training data. On one hand, continuous field mapping trains fractional land cover and thus favours mixed training pixels. On the other hand, the spectral signature has to be preferably distinct and thus favours pure training pixels. The aim of this study was to evaluate the sensitivity of training data distribution along fractional and spectral gradients on the resulting mapping performance. We derived four continuous fields (tree, shrubherb, bare, water) from aerial photographs as response variables and processed corresponding spectral signatures from multitemporal Landsat 5 TM data as explanatory variables. Subsequent controlled experiments along fractional cover gradients were then based on generalised linear models. Resulting fractional and spectral distribution differed between single continuous fields, but could be satisfactorily trained and mapped. Pixels with fractional or without respective cover were much more critical than pure full cover pixels. Error distribution of continuous field models was non-uniform with respect to horizontal and vertical spatial distribution of target fields. We conclude that a sampling for continuous field training data should be based on extent and densities in the fractional and spectral, rather than the real spatial space. Consequently, adequate training plots are most probably not systematically distributed in the real spatial space, but cover the gradient and covariate structure of the fractional and spectral space well. (C) 2009 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS). Published by Elsevier B.V. All rights reserved.
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Rising population, rapid urbanisation and growing industrialisation have severely stressed water quality and its availability in Malawi. In addition, financial and institutional problems and the expanding agro industry have aggravated this problem. The situation is worsened by depleting water resources and pollution from untreated sewage and industrial effluent. The increasing scarcity of clean water calls for the need for appropriate management of available water resources. There is also demand for a training system for conceptual design and evaluation for wastewater treatment in order to build the capacity for technical service providers and environmental practitioners in the country. It is predicted that Malawi will face a water stress situation by 2025. In the city of Blantyre, this situation is aggravated by the serious pollution threat from the grossly inadequate sewage treatment capacity. This capacity is only 23.5% of the wastewater being generated presently. In addition, limited or non-existent industrial effluent treatment has contributed to the severe water quality degradation. This situation poses a threat to the ecologically fragile and sensitive receiving water courses within the city. This water is used for domestic purposes further downstream. This manuscript outlines the legal and policy framework for wastewater treatment in Malawi. The manuscript also evaluates the existing wastewater treatment systems in Blantyre. This evaluation aims at determining if the effluent levels at the municipal plants conform to existing standards and guidelines and other associated policy and regulatory frameworks. The raw material at all the three municipal plants is sewage. The typical wastewater parameters are Biochemical Oxygen Demand (BOD5), Chemical Oxygen Demand (COD), and Total Suspended Solids (TSS). The treatment target is BOD5, COD, and TSS reduction. Typical wastewater parameters at the wastewater treatment plant at MDW&S textile and garments factory are BOD5 and COD. The treatment target is to reduce BOD5 and COD. The manuscript further evaluates a design approach of the three municipal wastewater treatment plants in the city and the wastewater treatment plant at Mapeto David Whitehead & Sons (MDW&S) textile and garments factory. This evaluation utilises case-based design and case-based reasoning principles in the ED-WAVE tool to determine if there is potential for the tool in Blantyre. The manuscript finally evaluates the technology selection process for appropriate wastewater treatment systems for the city of Blantyre. The criteria for selection of appropriate wastewater treatment systems are discussed. Decision support tools and the decision tree making process for technology selection are also discussed. Based on the treatment targets and design criteria at the eight cases evaluated in this manuscript in reference to similar cases in the ED-WAVE tool, this work confirms the practical use of case-based design and case-based reasoning principles in the ED-WAVE tool in the design and evaluation of wastewater treatment 6 systems in sub-Sahara Africa, using Blantyre, Malawi, as the case study area. After encountering a new situation, already collected decision scenarios (cases) are invoked and modified in order to arrive at a particular design alternative. What is necessary, however, is to appropriately modify the case arrived at through the Case Study Manager in order to come up with a design appropriate to the local situation taking into account technical, socio-economic and environmental aspects. This work provides a training system for conceptual design and evaluation for wastewater treatment.
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Background: Leptospirosis is an important zoonotic disease associated with poor areas of urban settings of developing countries and early diagnosis and prompt treatment may prevent disease. Although rodents are reportedly considered the main reservoirs of leptospirosis, dogs may develop the disease, may become asymptomatic carriers and may be used as sentinels for disease epidemiology. The use of Geographical Information Systems (GIS) combined with spatial analysis techniques allows the mapping of the disease and the identification and assessment of health risk factors. Besides the use of GIS and spatial analysis, the technique of data mining, decision tree, can provide a great potential to find a pattern in the behavior of the variables that determine the occurrence of leptospirosis. The objective of the present study was to apply Geographical Information Systems and data prospection (decision tree) to evaluate the risk factors for canine leptospirosis in an area of Curitiba, PR.Materials, Methods & Results: The present study was performed on the Vila Pantanal, a urban poor community in the city of Curitiba. A total of 287 dog blood samples were randomly obtained house-by-house in a two-day sampling on January 2010. In addition, a questionnaire was applied to owners at the time of sampling. Geographical coordinates related to each household of tested dog were obtained using a Global Positioning System (GPS) for mapping the spatial distribution of reagent and non-reagent dogs to leptospirosis. For the decision tree, risk factors included results of microagglutination test (MAT) from the serum of dogs, previous disease on the household, contact with rats or other dogs, dog breed, outdoors access, feeding, trash around house or backyard, open sewer proximity and flooding. A total of 189 samples (about 2/3 of overall samples) were randomly selected for the training file and consequent decision rules. The remained 98 samples were used for the testing file. The seroprevalence showed a pattern of spatial distribution that involved all the Pantanal area, without agglomeration of reagent animals. In relation to data mining, from 189 samples used in decision tree, a total of 165 (87.3%) animal samples were correctly classified, generating a Kappa index of 0.413. A total of 154 out of 159 (96.8%) samples were considered non-reagent and were correctly classified and only 5/159 (3.2%) were wrongly identified. on the other hand, only 11 (36.7%) reagent samples were correctly classified, with 19 (63.3%) samples failing diagnosis.Discussion: The spatial distribution that involved all the Pantanal area showed that all the animals in the area are at risk of contamination by Leptospira spp. Although most samples had been classified correctly by the decision tree, a degree of difficulty of separability related to seropositive animals was observed, with only 36.7% of the samples classified correctly. This can occur due to the fact of seronegative animals number is superior to the number of seropositive ones, taking the differences in the pattern of variable behavior. The data mining helped to evaluate the most important risk factors for leptospirosis in an urban poor community of Curitiba. The variables selected by decision tree reflected the important factors about the existence of the disease (default of sewer, presence of rats and rubbish and dogs with free access to street). The analyses showed the multifactorial character of the epidemiology of canine leptospirosis.
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In general, pattern recognition techniques require a high computational burden for learning the discriminating functions that are responsible to separate samples from distinct classes. As such, there are several studies that make effort to employ machine learning algorithms in the context of big data classification problems. The research on this area ranges from Graphics Processing Units-based implementations to mathematical optimizations, being the main drawback of the former approaches to be dependent on the graphic video card. Here, we propose an architecture-independent optimization approach for the optimum-path forest (OPF) classifier, that is designed using a theoretical formulation that relates the minimum spanning tree with the minimum spanning forest generated by the OPF over the training dataset. The experiments have shown that the approach proposed can be faster than the traditional one in five public datasets, being also as accurate as the original OPF. (C) 2014 Elsevier B. V. All rights reserved.
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The introduction of dwarfed rootstocks in apple crop has led to a new concept of intensive planting systems with the aim of producing early high yield and with returns of the initial high investment. Although yield is an important aspect to the grower, the consumer has become demanding regards fruit quality and is generally attracted by appearance. To fulfil the consumer’s expectations the grower may need to choose a proper training system along with an ideal pruning technique, which ensure a good light distribution in different parts of the canopy and a marketable fruit quality in terms of size and skin colour. Although these aspects are important, these fruits might not reach the proper ripening stage within the canopy because they are often heterogeneous. To describe the variability present in a tree, a software (PlantToon®), was used to recreate the tree architecture in 3D in the two training systems. The ripening stage of each of the fruits was determined using a non-destructive device (DA-Meter), thus allowing to estimate the fruit ripening variability. This study deals with some of the main parameters that can influence fruit quality and ripening stage within the canopy and orchard management techniques that can ameliorate a ripening fruit homogeneity. Significant differences in fruit quality were found within the canopies due to their position, flowering time and bud wood age. Bi-axis appeared to be suitable for high density planting, even though the fruit quality traits resulted often similar to those obtained with a Slender Spindle, suggesting similar fruit light availability within the canopies. Crop load confirmed to be an important factor that influenced fruit quality as much as the interesting innovative pruning method “Click”, in intensive planting systems.
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The direct application of existing models for seed germination may often be inadequate in the context of ecology and forestry germination experiments. This is because basic model assumptions are violated and variables available to forest managers are rarely used. In this paper, we present a method which addresses the aforementioned shortcomings. The approach is illustrated through a case study of Pinus pinea L. Our findings will also shed light on the role of germination in the general failure of natural regeneration in managed forests of this species. The presented technique consists of a mixed regression model based on survival analysis. Climate and stand covariates were tested. Data for fitting the model were gathered from a 5-year germination experiment in a mature, managed P. pinea stand in the Northern Plateau of Spain in which two different stand densities can be found. The model predictions proved to be unbiased and highly accurate when compared with the training data. Germination in P. pinea was controlled through thermal variables at stand level. At microsite level, low densities negatively affected the probability of germination. A time-lag in the response was also detected. Overall, the proposed technique provides a reliable alternative to germination modelling in ecology/forestry studies by using accessible/ suitable variables. The P. pinea case study highlights the importance of producing unbiased predictions. In this species, the occurrence and timing of germination suggest a very different regeneration strategy from that understood by forest managers until now, which may explain the high failure rate of natural regeneration in managed stands. In addition, these findings provide valuable information for the management of P. pinea under climate-change conditions.
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Thesis (Master's)--University of Washington, 2016-06