966 resultados para Climate Leaf Analysis Multivariate Program (CLAMP)
Resumo:
The generalization of simple (two-variable) correspondence analysis to more than two categorical variables, commonly referred to as multiple correspondence analysis, is neither obvious nor well-defined. We present two alternative ways of generalizing correspondence analysis, one based on the quantification of the variables and intercorrelation relationships, and the other based on the geometric ideas of simple correspondence analysis. We propose a version of multiple correspondence analysis, with adjusted principal inertias, as the method of choice for the geometric definition, since it contains simple correspondence analysis as an exact special case, which is not the situation of the standard generalizations. We also clarify the issue of supplementary point representation and the properties of joint correspondence analysis, a method that visualizes all two-way relationships between the variables. The methodology is illustrated using data on attitudes to science from the International Social Survey Program on Environment in 1993.
Resumo:
The spatial variability of soil and plant properties exerts great influence on the yeld of agricultural crops. This study analyzed the spatial variability of the fertility of a Humic Rhodic Hapludox with Arabic coffee, using principal component analysis, cluster analysis and geostatistics in combination. The experiment was carried out in an area under Coffea arabica L., variety Catucai 20/15 - 479. The soil was sampled at a depth 0.20 m, at 50 points of a sampling grid. The following chemical properties were determined: P, K+, Ca2+, Mg2+, Na+, S, Al3+, pH, H + Al, SB, t, T, V, m, OM, Na saturation index (SSI), remaining phosphorus (P-rem), and micronutrients (Zn, Fe, Mn, Cu and B). The data were analyzed with descriptive statistics, followed by principal component and cluster analyses. Geostatistics were used to check and quantify the degree of spatial dependence of properties, represented by principal components. The principal component analysis allowed a dimensional reduction of the problem, providing interpretable components, with little information loss. Despite the characteristic information loss of principal component analysis, the combination of this technique with geostatistical analysis was efficient for the quantification and determination of the structure of spatial dependence of soil fertility. In general, the availability of soil mineral nutrients was low and the levels of acidity and exchangeable Al were high.
Resumo:
Transportation Department, Office of University Research, Washington, D.C.
Resumo:
Fluoride (F) is an air pollutant that causes phytotoxicity. Besides the importance of this, losses of agricultural crops in the vicinity of F polluting industries in Brazil have been recently reported. Injuries caused to plant leaf cell structures by excess F are not well characterized. However, this may contribute to understanding the ways in which plant physiological and biochemical processes are altered. A study evaluated the effects of the atmospheric F on leaf characteristics and growth of young trees of sweet orange and coffee exposed to low (0.04 mol L(-1)) or high (0.16 mol L(-1)) doses of HF nebulized in closed chamber for 28 days plus a control treatment not exposed. Gladiolus and ryegrass were used as bioindicators in the experiment to monitor F exposure levels. Fluoride concentration and dry mass of leaves were evaluated. Leaf anatomy was observed under light and electron microscopy. High F concentrations (similar to 180 mg kg(-1)) were found in leaves of plants exposed at the highest dose of HF. Visual symptoms of F toxicity in leaves of citrus and coffee were observed. Analyses of plant tissue provided evidence that F caused degeneration of cell wall and cytoplasm and disorganization of bundle sheath, which were more evident in Gladiolus and coffee. Minor changes were observed for sweet orange and ryegrass. Increase on individual stomatal area was also marked for the Gladiolus and coffee, and which were characterized by occurrence of opened ostioles. The increased F absorption by leaves and changes at the structural and ultrastructural level of leaf tissues correlated with reduced plant growth.
Resumo:
The Agricultural Production Systems Simulator (APSIM) is a modular modelling framework that has been developed by the Agricultural Production Systems Research Unit in Australia. APSIM was developed to simulate biophysical process in farming systems, in particular where there is interest in the economic and ecological outcomes of management practice in the face of climatic risk. The paper outlines APSIM's structure and provides details of the concepts behind the different plant, soil and management modules. These modules include a diverse range of crops, pastures and trees, soil processes including water balance, N and P transformations, soil pH, erosion and a full range of management controls. Reports of APSIM testing in a diverse range of systems and environments are summarised. An example of model performance in a long-term cropping systems trial is provided. APSIM has been used in a broad range of applications, including support for on-farm decision making, farming systems design for production or resource management objectives, assessment of the value of seasonal climate forecasting, analysis of supply chain issues in agribusiness activities, development of waste management guidelines, risk assessment for government policy making and as a guide to research and education activity. An extensive citation list for these model testing and application studies is provided. Crown Copyright (C) 2002 Published by Elsevier Science B.V. All rights reserved.
Resumo:
This paper discusses a document discovery tool based on Conceptual Clustering by Formal Concept Analysis. The program allows users to navigate e-mail using a visual lattice metaphor rather than a tree. It implements a virtual. le structure over e-mail where files and entire directories can appear in multiple positions. The content and shape of the lattice formed by the conceptual ontology can assist in e-mail discovery. The system described provides more flexibility in retrieving stored e-mails than what is normally available in e-mail clients. The paper discusses how conceptual ontologies can leverage traditional document retrieval systems and aid knowledge discovery in document collections.
Resumo:
ABSTRACT The analytical determination of nutrient levels in recently mature leaves in order to diagnose nutritional status is based on the fact that leaves are metabolically active and more sensitive to variation in nutrients of the soil. In most of cases, there is a direct well known between foliar content and the development and yield of the plant. However, for a more accurate interpretation, it is essential to establish the index leaf. There are few published studies about Jatropha with contrasting results. In order to establish the index leaf, in adult plants, the macronutrient levels were evaluated in samples collected in experimental plots, in which doses of nitrogen and phosphorus were applied, in two parts of the floral branches (in the top and in the middle thirds); and in three positions of leaves of the floral branch (between the 1st and 3rd, 6th and 8th, and 13th and 15th leaves below the inflorescence). The location of the leaf on the plant significantly affects nutrient contents. Nitrogen, phosphorus, potassium and sulfur tend to have higher concentration in young tissues. Calcium and magnesium showed higher levels in the basal leaves of floral branches. Samples collected in the top third of plants (between the 6th and 15th leaves of the floral branch) are more sensitive to variations of nitrogen and phosphorus fertilization. Therefore, we indicate the 6th to 15th leaves of the top third plants as index leaves estimate nutritional status of Jatropha.
Resumo:
Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.
Resumo:
The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.
Resumo:
Dissertação para obtenção do Grau de Doutor em Ambiente
Resumo:
Univariate statistical control charts, such as the Shewhart chart, do not satisfy the requirements for process monitoring on a high volume automated fuel cell manufacturing line. This is because of the number of variables that require monitoring. The risk of elevated false alarms, due to the nature of the process being high volume, can present problems if univariate methods are used. Multivariate statistical methods are discussed as an alternative for process monitoring and control. The research presented is conducted on a manufacturing line which evaluates the performance of a fuel cell. It has three stages of production assembly that contribute to the final end product performance. The product performance is assessed by power and energy measurements, taken at various time points throughout the discharge testing of the fuel cell. The literature review performed on these multivariate techniques are evaluated using individual and batch observations. Modern techniques using multivariate control charts on Hotellings T2 are compared to other multivariate methods, such as Principal Components Analysis (PCA). The latter, PCA, was identified as the most suitable method. Control charts such as, scores, T2 and DModX charts, are constructed from the PCA model. Diagnostic procedures, using Contribution plots, for out of control points that are detected using these control charts, are also discussed. These plots enable the investigator to perform root cause analysis. Multivariate batch techniques are compared to individual observations typically seen on continuous processes. Recommendations, for the introduction of multivariate techniques that would be appropriate for most high volume processes, are also covered.
Resumo:
The comparative analysis of air quality control policies provides an interesting field for studies of comparative policy analysis including program formulation and implementation processes. In European countries, the problem is comparable, whereas implementation structures, programs and policy impacts vary to a considerable extent. Analysis testing possibilities and constraints of air control policies under varying conditions are likely to contribute to a further development of a theory of policy analysis. This paper presents the analytical framework applied in a continuing empirical study explaining program formulation and implementation processes with respect to the different actors involved. Concrete emitter behavior can be explained by interaction processes at the very local level, by program elements of national legislation, and by structural constraints under which such programs are produced.
Resumo:
Leaf analysis is the chemical evaluation of the nutritional status where the nutrient concentrations found in the tissue reflect the nutritional status of the plants. Thus, a correct interpretation of the results of leaf analysis is fundamental for an effective use of this tool. The purpose of this study was to propose and compare the method of Fertilization Response Likelihood (FRL) for interpretation of leaf analysis with that of the Diagnosis and Recommendation Integrated System (DRIS). The database consisted of 157 analyses of the N, P, K, Ca, Mg, S, Cu, Fe, Mn, Zn, and B concentrations in coffee leaves, which were divided into two groups: low yield (< 30 bags ha-1) and high yield (> 30 bags ha-1). The DRIS indices were calculated using the method proposed by Jones (1981). The fertilization response likelihood was computed based on the approximation of normal distribution. It was found that the Fertilization Response Likelihood (FRL) allowed an evaluation of the nutritional status of coffee trees, coinciding with the DRIS-based diagnoses in 84.96 % of the crops.
Resumo:
This past winter the sieve analysis of combined aggregate was investigated. This study was given No. 26 by the Central Laboratory. The purpose of this work was to try and develop a sieve analysis procedure for combined aggregate which is less time consuming and has the same accuracy as the method described in I.M. 304. In an attempt to use a variety of aggregates for this investigation, a request was made to each District Materials Office to obtain at least 3 different combined aggregate samples in their respective districts. At the same time it was also requested that the field technician test these samples, prior to submitting them to the Central Laboratory. The field technician was instructed to test each sample as described in method I.M. 304 and also by a modified AASHTO T27 method which will be identified in the report as Method A. The modified AASHTO Method A was identical to T27 with the exception that a smaller sample is used for testing. The field technicians submitted the samples, test results and also comments regarding the modified AASHTO procedure. The general comments of the modified AASHTO procedure were: The method was much simpler to follow; however, it took about the same amount of time so there was no real advantage. After reviewing AASHTO T27, T164, I.M. 304 and Report No. FHWA-RD-77-53 another test method was purposed. Report No. FHWA-RD-77-53 is a report prepared by FHWA from data they gathered concerning control practices and shortcut or alternative test methods for aggregate gradation. A second test method was developed which also was very similar to AASHTO T27, The test procedure for this method is attached and is identified as Method B. The following is a summary of test results submitted by the Field Technicians and obtained by the aggregate section of the Central Laboratory.