Evaluation of Cu, Mn, and Se in Vegetables Using Ultrasonic Extraction and GFAAS Quantification

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of different extraction methods on the yield and linalool content of the extracts of Eugenia uniflora L.

This work has been developed using a sylvestral fruit tree, native to the Brazilian forest, the Eugenia uniflora L., one of the Mirtaceae family. The main goal of the analytical study was focused on extraction methods themselves. The method development pointed to the Clevenger extraction as the best yield in relation to SFE and Soxhlet. The SFE method presented a good yield but showed a big amount of components in the final extract, demonstrating low selectivity. The essential oil extracted was analyzed by GC/FID showing a large range of polarity and boiling point compounds, where linalool, a widely used compound, was identified. Furthermore, an analytical solid phase extraction method was used to clean it up and obtain separated classes of compounds that were fractionated and studied by GC/FlD and GUMS. (c) 2006 Elsevier B.V. All rights reserved.

Determination of rice herbicides, their transformation products and clofibric acid using on-line solid-phase extraction followed by liquid chromatography with diode array and atmospheric pressure chemical ionization mass spectrometric detection

A simultaneous method for the trace determination of acidic, neutral herbicides and their transformation products in estuarine waters has been developed through an on-line solid-phase extraction method followed by liquid chromatography with diode array and mass spectrometric detection. An atmospheric pressure chemical ionization (APCI) interface was used in the negative ionization mode after optimization of the main APCI parameters. Limits of detection ranged from 0.1 to 0.02 ng/ml for 50 mi of acidified estuarine waters preconcentrated into polymeric precolumns and using time-scheduled selected ion monitoring mode. Two degradation products of the acidic herbicides (4-chloro-2-methylphenol and 2,4-dichlorophenol) did not show good signal response using APCI-MS at the concentration studied due to the higher fragmentor voltage needed for their determination For molinate and the major degradation product of propanil, 3,4-dichloroaniline, positive ion mode was needed for APCI-MS detection. The proposed method was applied to the determination of herbicides in drainage waters from rice fields of the Delta del Ebro (Spain). During the S-month monitoring of the herbicides, 8-hydroxybentazone and 4-chloro-2-methylphenoxyacetic acid were successively found in those samples. (C) 2000 Elsevier B.V. B.V. All rights reserved.

Iron determination by FAAS in fish feed and feces after ultrasound-assisted extraction

This paper proposes a method to determine iron in samples of fish feed and feces using ultrasound in the extraction of the analyte and in subsequent quantification by flame atomic absorption spectrometry. Using HCl 0.10 mol L -1 as the extraction solution, the optimal conditions of extraction were found to be: granulometry of the sample <60 μm; a sonication time of five cycles of 10 s and sonication power of 136 W. The method was applied in studies of the availability of iron in four food sources used in the diet of Nile Tilapia. The results obtained with the proposed extraction method allowed us to calculate the coefficients of apparent digestibility of iron in the food sources, which was not possible when using results obtained from samples mineralized by acid digestion. © Springer Science+Business Media, LLC 2008.

Ultrasound-assisted extraction of Na and K from swine feed and its application in a digestibility assay: A green analytical procedure

The study is aimed to evaluate the efficiency of ultrasound-assisted extraction (UAE) as a simple strategy focused on sample preparation for metal determination in biological samples. The extraction of sodium and potassium extraction was carried out from swine feed followed by determination of the concentration of these metals by flame atomic emission spectrometry (FAES). The experiment was performed to cover the study of the variables influencing the extraction process and its optimal conditions (sample mass, particle size, acid concentration, sonication time and ultrasound power); the determination of these analytical characteristics and method validation using certified reference material; and the analysis of pre-starter diets. The optimal conditions established conditions were as follows: mass: 100 mg, particle size:<60 μm, acid concentration: 0.10 mol L-1 HCl, sonication time: 50 s and ultrasound power: 102 W. The proposed method (UAE) was applied in digestibility assays of those nutrients present in different piglet pre-starter feeds and their results proved to be compatible with those obtained from mineralized samples (P < 0.05). The ultrasound extraction method was demonstrated to be an excellent alternative for handless sampling and operational costs and the method also has the advantage of does not generating toxic residues that may negatively affect human health and contaminate the environment. © 2013 Elsevier B.V. All rights reserved.

DEVELOPMENT OF AN ALGORITHM TO ANALYZE CARTOGRAPHIC FEATURES EXTRACTION METHODS IN DIGITAL IMAGES

The algorithm creates a buffer area around the cartographic features of interest in one of the images and compare it with the other one. During the comparison, the algorithm calculates the number of equals and different points and uses it to calculate the statistical values of the analysis. One calculated statistical value is the correctness, which shows the user the percentage of points that were correctly extracted. Another one is the completeness that shows the percentage of points that really belong to the interest feature. And the third value shows the idea of quality obtained by the extraction method, since that in order to calculate the quality the algorithm uses the correctness and completeness previously calculated. All the performed tests using this algorithm were possible to use the statistical values calculated to represent quantitatively the quality obtained by the extraction method executed. So, it is possible to say that the developed algorithm can be used to analyze extraction methods of cartographic features of interest, since that the results obtained were promising.

Evaluation of solvent effect on the extraction of phenolic compounds and antioxidant capacities from the berries: application of principal component analysis

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Physical and chemical characterization of the pulp of different varieties of avocado targeting oil extraction potential

The aim of this study was to evaluate the physicochemical properties of avocado pulp of four different varieties (Avocado, Guatemala, Dickinson, and Butter pear) and to identify which has the greatest potential for oil extraction. Fresh avocado pulp was characterized by moisture, protein, fat, ash, carbohydrates and energy contents were determined. The carotenoids and chlorophyll contents were determined by the organic solvent extraction method. The results showed significant differences in the composition of the fruit when varieties are compared. However, the striking feature in all varieties is high lipid content; Avocado and Dickinson are the most suitable varieties for oil extraction, taking into account moisture content and the levels of lipids in the pulp. Moreover, it could be said that the variety Dickinson is the most affected by the parameters evaluated in terms of overall quality. Chlorophyll and carotenoids, fat-soluble pigments, showed a negative correlation with respect to lipids since it could be related to its function in the fruit. The varieties Avocado and Dickinson are an alternative to oil extraction having great commercial potential to be exploited thus avoiding waste and increasing farmers income.

Applying design of experiments (DOE) to flavonoid extraction from Passiflora alata and P. edulis

The Passifloraceae family is extensively used in native Brazilian folk medicine to treat a wide variety of diseases. The problem of flavonoid extraction from Passiflora was treated by application of design of experiments (DOE), as an experiment with mixture including one categorical process variable. The components of the binary mixture were: ethanol (component A) and water (component B); the categorical process variable: extraction method (factor C) was varied at two levels: (+1) maceration and (-1) percolation. ANOVA suggested a cubic model for P. edulis extraction and a quadratic model for P. alata.These results indicate that the proportion of components A and B in the mixture is the main factor involved in significantly increasing flavonoid extraction. In regard to the extraction methods, no important differences were observed, which indicates that these two traditional extraction methods could be effectively used to extract flavonoids from both medicinal plants. The evaluation of antioxidant activity of the extract by ORAC method showed that P. edulis displays twice as much antioxidant activity as P. alata. Considering that maceration is a simple, rapid and environmentally friendly extraction method, in this study, the optimized conditions for flavonoid extraction from these Passiflora species is maceration with 75% ethanol for P. edulis and 50% ethanol for P. alata.

Fingerprint Recognition: Enhancement, Feature Extraction and Automatic Evaluation of Algorithms

The identification of people by measuring some traits of individual anatomy or physiology has led to a specific research area called biometric recognition. This thesis is focused on improving fingerprint recognition systems considering three important problems: fingerprint enhancement, fingerprint orientation extraction and automatic evaluation of fingerprint algorithms. An effective extraction of salient fingerprint features depends on the quality of the input fingerprint. If the fingerprint is very noisy, we are not able to detect a reliable set of features. A new fingerprint enhancement method, which is both iterative and contextual, is proposed. This approach detects high-quality regions in fingerprints, selectively applies contextual filtering and iteratively expands like wildfire toward low-quality ones. A precise estimation of the orientation field would greatly simplify the estimation of other fingerprint features (singular points, minutiae) and improve the performance of a fingerprint recognition system. The fingerprint orientation extraction is improved following two directions. First, after the introduction of a new taxonomy of fingerprint orientation extraction methods, several variants of baseline methods are implemented and, pointing out the role of pre- and post- processing, we show how to improve the extraction. Second, the introduction of a new hybrid orientation extraction method, which follows an adaptive scheme, allows to improve significantly the orientation extraction in noisy fingerprints. Scientific papers typically propose recognition systems that integrate many modules and therefore an automatic evaluation of fingerprint algorithms is needed to isolate the contributions that determine an actual progress in the state-of-the-art. The lack of a publicly available framework to compare fingerprint orientation extraction algorithms, motivates the introduction of a new benchmark area called FOE (including fingerprints and manually-marked orientation ground-truth) along with fingerprint matching benchmarks in the FVC-onGoing framework. The success of such framework is discussed by providing relevant statistics: more than 1450 algorithms submitted and two international competitions.

Feature Extraction for Classification in the Data Mining Process

Dimensionality reduction is a very important step in the data mining process. In this paper, we consider feature extraction for classification tasks as a technique to overcome problems occurring because of “the curse of dimensionality”. Three different eigenvector-based feature extraction approaches are discussed and three different kinds of applications with respect to classification tasks are considered. The summary of obtained results concerning the accuracy of classification schemes is presented with the conclusion about the search for the most appropriate feature extraction method. The problem how to discover knowledge needed to integrate the feature extraction and classification processes is stated. A decision support system to aid in the integration of the feature extraction and classification processes is proposed. The goals and requirements set for the decision support system and its basic structure are defined. The means of knowledge acquisition needed to build up the proposed system are considered.

Jointly event extraction and visualization on Twitter via probabilistic modelling

Event extraction from texts aims to detect structured information such as what has happened, to whom, where and when. Event extraction and visualization are typically considered as two different tasks. In this paper, we propose a novel approach based on probabilistic modelling to jointly extract and visualize events from tweets where both tasks benefit from each other. We model each event as a joint distribution over named entities, a date, a location and event-related keywords. Moreover, both tweets and event instances are associated with coordinates in the visualization space. The manifold assumption that the intrinsic geometry of tweets is a low-rank, non-linear manifold within the high-dimensional space is incorporated into the learning framework using a regularization. Experimental results show that the proposed approach can effectively deal with both event extraction and visualization and performs remarkably better than both the state-of-the-art event extraction method and a pipeline approach for event extraction and visualization.

Evaluation of five commercial methods for the extraction and purification of DNA from human faecal samples for downstream molecular detection of the enteric protozoan parasites Cryptosporidium spp., Giardia duodenalis, and Entamoeba spp

High quality, pure DNA is required for ensuring reliable and reproducible results in molecular diagnosis applications. A number of in-house and commercial methods are available for the extraction and purification of genomic DNA from faecal material, each one offering a specific combination of performance, cost-effectiveness, and easiness of use that should be conveniently evaluated in function of the pathogen of interest. In this comparative study the marketed kits QIAamp DNA stool mini (Qiagen), SpeedTools DNA extraction (Biotools), DNAExtract-VK (Vacunek), PowerFecal DNA isolation (MoBio), and Wizard magnetic DNA purification system (Promega Corporation) were assessed for their efficacy in obtaining DNA of the most relevant enteric protozoan parasites associated to gastrointestinal disease globally. A panel of 113 stool specimens of clinically confirmed patients with cryptosporidiosis (n = 29), giardiasis (n = 47) and amoebiasis by Entamoeba histolytica (n = 3) or E. dispar (n = 10) and apparently healthy subjects (n = 24) were used for this purpose. Stool samples were aliquoted in five sub-samples and individually processed by each extraction method evaluated. Purified DNA samples were subsequently tested in PCR-based assays routinely used in our laboratory. The five compared methods yielded amplifiable amounts of DNA of the pathogens tested, although performance differences were observed among them depending on the parasite and the infection burden. Methods combining chemical, enzymatic and/or mechanical lysis procedures at temperatures of at least 56 °C were proven more efficient for the release of DNA from Cryptosporidium oocysts.

Fixing, storage time and DNA extraction applied to dT-RFLP for ecological and molecular studies of marine nematodes assemblages

The application of molecular methods offers an alternative faster than traditional methods based on morphology It is nearly impossible to process all the samples in short period using traditional methods, and the deterioration of marine sediments rapidly occurs The dT-RFLP (directed Terminal-Restriction Fragment Length Polymorphism) allows a rapid assessment of biodiversity changes of nematodes assemblages The use of a not suitable fixing, storage time and DNA extraction could be a limitation in molecular analysis like dT-RFLP and real time PCR.Objetives: the best fixative •the level of DNA degradation over the time •the best DNA extraction method for marine nematodes and suitable for dT-RFLP analysis

An application of fractal image-set coding in facial recognition

Faces are complex patterns that often differ in only subtle ways. Face recognition algorithms have difficulty in coping with differences in lighting, cameras, pose, expression, etc. We propose a novel approach for facial recognition based on a new feature extraction method called fractal image-set encoding. This feature extraction method is a specialized fractal image coding technique that makes fractal codes more suitable for object and face recognition. A fractal code of a gray-scale image can be divided in two parts – geometrical parameters and luminance parameters. We show that fractal codes for an image are not unique and that we can change the set of fractal parameters without significant change in the quality of the reconstructed image. Fractal image-set coding keeps geometrical parameters the same for all images in the database. Differences between images are captured in the non-geometrical or luminance parameters – which are faster to compute. Results on a subset of the XM2VTS database are presented.