45 resultados para Multivariate statistical methods


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This paper examines the results of spatial (microgeographical) water contact/schistosomiasis studies in two African (Egyptian and Kenyan) and one Brazilian communities. All three studies used traditional cartographic and statistical methods but one of them emploeyd also GIS (geographical information systems) tools. The advantage of GIS and their potential role in schistosomiasis control are briefly described. The three cases revealed considerable variation in the spatial distribution of water contact, transmission parameters and infection levels at the household and individual levels. All studies showed considerable variation in the prevalence and intensity of infection between households. They also show a variable influence of distance on water contact behavior associated with type of activity, age, sex, socioeconomic level, perception of water quality, season and availability of water in the home. Water contact behavior and schistosomiasis were evaluated in the Brazilian village of Nova União within the context of water sharing between household and age/sex groups. Recommendations are made for further spatial studies on the transmission and control of schistosomiasis.

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Social wasps are important for the study of social behavior evolution because their colonies present different degrees of caste differentiation, from morphologically similar to highly conspicuous, associated with the occasional presence of intermediate females, which bears developed ovaries but no insemination. In the Polistinae, depending on the taxon, such differentiation can be discreet or conspicuous. This work intended to study morphological and physiological differences between castes in Protopolybia chartergoides by using morphometric analyses associated with multivariate statistical analyses and physiological evaluations from females' ovarian development. Results evidence low morphological and physiological differences among the castes in P. chartergoides, indicating three groups of females: queens, workers and intermediates. In this way, it was possible to suggest that Protopolybia chartergoides presents post-imaginal caste differentiation (or a very subtle form of pre-imaginal determination).

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The spatial variability of strongly weathered soils under sugarcane and soybean/wheat rotation was quantitatively assessed on 33 fields in two regions in São Paulo State, Brazil: Araras (15 fields with sugarcane) and Assis (11 fields with sugarcane and seven fields with soybean/wheat rotation). Statistical methods used were: nested analysis of variance (for 11 fields), semivariance analysis and analysis of variance within and between fields. Spatial levels from 50 m to several km were analyzed. Results are discussed with reference to a previously published study carried out in the surroundings of Passo Fundo (RS). Similar variability patterns were found for clay content, organic C content and cation exchange capacity. The fields studied are quite homogeneous with respect to these relatively stable soil characteristics. Spatial variability of other characteristics (resin extractable P, pH, base- and Al-saturation and also soil colour), varies with region and, or land use management. Soil management for sugarcane seems to have induced modifications to greater depths than for soybean/wheat rotation. Surface layers of soils under soybean/wheat present relatively little variation, apparently as a result of very intensive soil management. The major part of within-field variation occurs at short distances (< 50 m) in all study areas. Hence, little extra information would be gained by increasing sampling density from, say, 1/km² to 1/50 m². For many purposes, the soils in the study regions can be mapped with the same observation density, but residual variance will not be the same in all areas. Bulk sampling may help to reveal spatial patterns between 50 and 1.000 m.

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Improvements in working conditions, sustainable production, and competitiveness have led to substantial changes in sugarcane harvesting systems. Such changes have altered a number of soil properties, including iron oxides and organic matter, as well as some chemical properties, such as the maximum P adsorption capacity of the soil. The aim of this study was to characterize the relationship between iron oxides and the quality of organic matter in sugarcane harvesting systems. For that purpose, two 1 ha plots in mechanically and manually harvested fields were used to obtain soil samples from the 0.00-0.25 m soil layer at 126 different points. The mineralogical, chemical, and physical results were subjected to descriptive statistical analyses, such as the mean comparison test, as well as to multivariate statistical and principal component analyses. Multivariate tests allowed soil properties to be classified in two different groups according to the harvesting method: manual harvest with the burning of residual cane, and mechanical harvest without burning. The mechanical harvesting system was found to enhance pedoenvironmental conditions, leading to changes in the crystallinity of iron oxides, an increase in the humification of organic matter, and a relative decrease in phosphorus adsorption in this area compared to the manual harvesting system.

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The objective of this study was to determine the minimum number of plants per plot that must be sampled in experiments with sugarcane (Saccharum officinarum) full-sib families in order to provide an effective estimation of genetic and phenotypic parameters of yield-related traits. The data were collected in a randomized complete block design with 18 sugarcane full-sib families and 6 replicates, with 20 plants per plot. The sample size was determined using resampling techniques with replacement, followed by an estimation of genetic and phenotypic parameters. Sample-size estimates varied according to the evaluated parameter and trait. The resampling method permits an efficient comparison of the sample-size effects on the estimation of genetic and phenotypic parameters. A sample of 16 plants per plot, or 96 individuals per family, was sufficient to obtain good estimates for all traits considered of all the characters evaluated. However, for Brix, if sample separation by trait were possible, ten plants per plot would give an efficient estimate for most of the characters evaluated.

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The modern technological ability to handle large amounts of information confronts the chemist with the necessity to re-evaluate the statistical tools he routinely uses. Multivariate statistics furnishes theoretical bases for analyzing systems involving large numbers of variables. The mathematical calculations required for these systems are no longer an obstacle due to the existence of statistical packages that furnish multivariate analysis options. Here basic concepts of two multivariate statistical techniques, principal component and hierarchical cluster analysis that have received broad acceptance for treating chemical data are discussed.

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One of the major interests in soil analysis is the evaluation of its chemical, physical and biological parameters, which are indicators of soil quality (the most important is the organic matter). Besides there is a great interest in the study of humic substances and on the assessment of pollutants, such as pesticides and heavy metals, in soils. Chemometrics is a powerful tool to deal with these problems and can help soil researchers to extract much more information from their data. In spite of this, the presence of these kinds of strategies in the literature has obtained projection only recently. The utilization of chemometric methods in soil analysis is evaluated in this article. The applications will be divided in four parts (with emphasis in the first two): (i) descriptive and exploratory methods based on Principal Component Analysis (PCA); (ii) multivariate calibration methods (MLR, PCR and PLS); (iii) methods such as Evolving Factor Analysis and SIMPLISMA; and (iv) artificial intelligence methods, such as Artificial Neural Networks.

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Water quality was monitored at the upper course of the Rio das Velhas, a major tributary of the São Francisco basin located in the state of Minas Gerais, over an extension of 108 km from its source up to the limits with the Sabara district. Monitoring was done at 37 different sites over a period of 2 years (2003-2004) for 39 parameters. Multivariate statistical techniques were applied to interpret the large water-quality data set and to establish an optimal long-term monitoring network. Cluster analysis separated the sampling sites into groups of similarity, and also indicated the stations investigated for correlation and recommended to be removed from the monitoring network. Principal component analysis identified four components, which are responsible for the data structure explaining 80% of the total variance of the data. The principal parameters are characterized as due to mining activities and domestic sewage. Significant data reduction was achieved.

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In this work, the impact of fish farming activities on the Queixada, Macuco and Pari-Veado Rivers in the Paranapanema watershed was evaluated. Physical, chemical and microbiological parameters were quantified in these aquatic systems followed by application of multivariate statistical analysis (MSA) and water quality index (WQI) tools. Watersheds where fish farming activities are predominant presented WQI > 52 indicating good quality, whereas MSA demonstrated bad quality for these aquatic bodies. The results showed that the degradation in this watershed follows the fish farming activity. The MSA index is more restricted than the "National Foundation Sanitation" (NFS) index routinely used to infer water quality.

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The spatial and temporal retention of metals has been studied in water and sediments of the Gavião River, Anagé and Tremedal Reservoirs, located in the semi-arid region, Bahia - Brazil, in order to identify trends in the fluxes of metals from the sediments to the water column. The determination of metals was made by ICP OES and ET AAS. The application of statistical methods showed that this aquatic system presents suitable conditions to move Cd2+ and Pb2+ from the water column to the sediment.

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The application of one-dimensional proton high-resolution magic angle spinning (¹H HR-MAS) NMR combined with a typical advantages of solid and liquid-state NMR techniques was used as input variables for the multivariate statistical analysis. In this paper, different cultivars of beans (Phaseolus vulgaris) developed and in development by Embrapa - Arroz e Feijão were analyzed by ¹H HR-MAS, which have been demonstrated to be a valuable tool in its differentiation according chemical composition and avoid the manipulation of the samples as used in other techniques.

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The synthesis and characterization of crosslinked chitosan microbeads and their application in the removal of Cr(VI) are described. New kinetic and thermodynamic parameters of Cr(VI) adsorptions processes were found using continuous isothermal calorimetry. All adsorption processes are exothermic in nature. However, a multivariate statistical analysis have pointed out that adsorption enthalpies were affected by important binary interactions of the initial Cr(VI) in solution and temperature. The adsorption energetic data were well fitted to a kinetic exponential model, which have indicated fractionary adsorption kinetic orders.

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In this work, the organic compounds of cigar samples from different brands were analyzed. The compound extraction was made using the matrix solid-phase dispersion (MSPD) technique, followed by gas chromatography and identification by mass spectrometry (GC-MS) and standards, when available. Thirty eight organic compounds were found in seven different brands. Finally, with the objective of characterizing and discriminating the cigar samples, multivariate statistical analyses were applied to data, e.g.; principal component analysis (PCA) and hierarchical cluster analysis (HCA). With such analyses, it was possible to discriminate three main groups of three quality levels.

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This paper presents a multivariate statistical analysis as a valuable tool for educational management applied to public high school chemistry teacher formation. From 2003 to 2007, a decrease of 10% in the number of public high schools was seen, as well as a reduction of 7% in the number of teachers. Contrarily, there was an increase in the number of university graduate teachers. Principal Component Analyses reveal that in 2003, most chemistry teachers were not university graduates. In 2007, eight Regional Offices of Education reported teachers holding academic degrees, qualifying them as chemistry teacher in the school system

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Honey produced by three stingless bee species (Melipona flavolineata, M. fasciculata and Apis mellifera) from different regions of the Amazon was analyzed by separating phenolic acids and flavonoids using the HPLC technique. Data were subjected to multivariate statistical analysis (PCA, HCA and DA). Results showed the three species of honey samples could be distinguished by phenolic composition. Antioxidant activity of the honeys was determined by studying the capacity of inhibiting radicals using DPPH assay. Honeys with higher phenolic compound contents had greater antioxidant capacity and darker color.