Application of chemometric methods in the evaluation of chemical and spectroscopic data on organic matter from Oxisols in sewage sludge applications

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

Avaliação de características de desempenho e de carcaça de codornas de corte por meio da análise de componentes principais

Foram utilizados dados de 288 codornas de corte (Coturnix coturnix coturnix) para avaliar a possibilidade de resumir a informação contida no complexo de variáveis originais, eliminando-se variáveis inexpressivas por meio da técnica de componentes principais. Foram registrados o peso vivo (PVIVO) e pesos do peito (PPEITO), das coxas (PCOXA), da gordura abdominal (GA), das vísceras comestíveis (fígado, moela e coração) (FIG, MOELA e CORA) e da carcaça eviscerada (PCEVIS). As carcaças foram secas e trituradas para a avaliação do teor matéria seca (MS), gordura (GORD) e proteína bruta (PB). Dos 11 componentes principais, sete (63,6%) apresentaram variância menor que 0,7 (autovalor inferior a 0,7), sendo sugeridas para descarte, respectivamente, em ordem de menor importância, para explicar a variação total das seguintes variáveis: PCEVIS, PPEITO, PCOXA, CORA, FIG MOELA e GORD. Com base nos resultados, recomenda-se manter as seguintes variáveis em experimentos futuros: PVIVO, MS, PB e GA.

Relação entre características morfológicas e produção de leite em vacas da raça Gir

O objetivo deste trabalho foi determinar parâmetros genéticos relacionados a características morfológicas e suas correlações genéticas com a produção de leite, em vacas da raça Gir. Utilizaram-se 3.805 registros provenientes de 2.142 vacas. O modelo utilizado na análise de características morfológicas continha os efeitos fixos de rebanho, ano e estação de classificação, estádio da lactação e idade da vaca à classificação, além da identificação do classificador. Quanto à produção de leite, foram incluídos no modelo os efeitos fixos de rebanho, ano e estação de parição e idade da vaca ao parto. Os parâmetros genéticos foram obtidos por meio do aplicativo REMLF90. As estimativas de herdabilidade variaram de 0,09 a 0,54. A variabilidade genética aditiva da maioria das características é suficiente para que ganhos genéticos anuais significativos possam ser alcançados com o processo de seleção. As correlações genéticas entre as características morfológicas variaram de baixas a altas e, entre elas e a produção de leite, de baixas a moderadas. Altas correlações genéticas entre algumas características morfológicas implicam a possibilidade de exclusão de algumas delas do programa de melhoramento genético da raça Gir, no Brasil. As correlações genéticas entre produção de leite e algumas características morfológicas indicam que estas podem ser utilizadas na formação de índices de seleção.

Wine classification by taste sensors made from ultra-thin films and using neural networks

This paper reports on a sensor array able to distinguish tastes and used to classify red wines. The array comprises sensing units made from Langmuir-Blodgett (LB) films of conducting polymers and lipids and layer-by-layer (LBL) films from chitosan deposited onto gold interdigitated electrodes. Using impedance spectroscopy as the principle of detection, we show that distinct clusters can be identified in principal component analysis (PCA) plots for six types of red wine. Distinction can be made with regard to vintage, vineyard and brands of the red wine. Furthermore, if the data are treated with artificial neural networks (ANNs), this artificial tongue can identify wine samples stored under different conditions. This is illustrated by considering 900 wine samples, obtained with 30 measurements for each of the five bottles of the six wines, which could be recognised with 100% accuracy using the algorithms Standard Backpropagation and Backpropagation momentum in the ANNs. (C) 2003 Elsevier B.V. All rights reserved.

Exploiting the versatility of taste sensors based on impedance spectroscopy

The versatility of sensor arrays made from nanostructured Langmuir-Blodgett (LB) and layer-by-layer (LBL) films is demonstrated in two ways. First, different combinations of sensing units are employed to distinguish the basic tastes, viz. sweet, sour, bitter, and salty tastes, produced, respectively, by small concentrations (down to 0.01 g/mol) of sucrose, HCl, quinine, and NaCl solutions. The sensing units are comprised of LB and/or LBL films from semiconducting polymers, a ruthenium complex, and sulfonated lignin. Then, sensor arrays were used to identify wines from different sources, with the high distinguishing ability being demonstrated in principal component analysis (PCA) plots. Particularly important was the fact that the sensing ability does not depend on specific interactions between analytes and the film materials, but a judicious choice of materials is, nevertheless, required for the materials to respond differently to a given sample. It is also shown that the interaction with the analyte may affect the morphology of the nanostructured films, as indicated with scanning electron microscopy. For instance, in wine analysis these changes are not irreversible and the original film morphology is retrieved if the sensing unit is washed with copious amounts of water, thus allowing the sensor unit to be reused.

Fabrication, structural characterization, and applications of Langmuir and Langmuir-Blodgett films of a poly(azo)urethane

The synthesis of a poly(azo)urethane by fixing CO2 in bis-epoxide followed by a polymerization reaction with an azodiamine is presented. Since isocyanate is not used in the process, it is termed clean method and the polymers obtained are named NIPUs (non-isocyanate polyurethanes). Langmuir films were formed at the air-water interface and were characterized by surface pressure vs mean molecular area per met unit (Pi-A) isotherms. The Langmuir monolayers were further studied by running stability tests and cycles of compression/expansion (possible hysteresis) and by varying the compression speed of the monolayer formation, the subphase temperature, and the solvents used to prepare the spreading polymer solutions. The Langmuir-Blodgett (LB) technique was used to fabricate ultrathin films of a particular polymer (PAzoU). It is possible to grow homogeneous LB films of up to 15 layers as monitored using UV-vis absorption spectroscopy. Higher number of layers can be deposited when PAzoU is mixed with stearic acid, producing mixed LB films. Fourier transform infrared (FTIR) absorption spectroscopy and Raman scattering showed that the materials do not interact chemically in the mixed LB films. The atomic force microscopy (AFM) and micro-Raman technique (optical microscopy coupled to Raman spectrograph) revealed that mixed LB films present a phase separation distinguishable at micrometer or nanometer scale. Finally, mixed and neat LB films were successfully characterized using impedance spectroscopy at different temperatures, a property that may lead to future application as temperature sensors. Principal component analysis (PCA) was used to correlate the data.

Fabrication and characterization of chemical sensors made from nanostructured films of poly(o-ethoxyaniline) prepared with different doping acids

Chemical sensors made from nanostructured films of poly(o-ethoxyaniline) POEA and poly(sodium 4-styrene sulfonate) PSS are produced and used to detect and distinguish 4 chemicals in solution at 20 mM, including sucrose, NaCl, HCl, and caffeine. These substances are used in order to mimic the 4 basic tastes recognized by humans, namely sweet, salty, sour, and bitter, respectively. The sensors are produced by the deposition of POEA/PSS films at the top of interdigitated microelectrodes via the layer-by-layer technique, using POEA solutions containing different dopant acids. Besides the different characteristics of the POEA/PSS films investigated by UV-Vis and Raman spectroscopies, and by atomic force microscopy.. it is observed that their electrical response to the different chemicals in liquid media is very fast, in the order of seconds, systematical, reproducible, and extremely dependent on the type of acid used for film fabrication. The responses of the as-prepared sensors are reproducible and repetitive after many cycles of operation. Furthermore, the use of an "electronic tongue" composed by an array of these sensors and principal component analysis as pattern recognition tool allows one to reasonably distinguish test solutions according to their chemical composition. (c) 2007 Published by Elsevier B.V.

Layer-by-Layer Technique as a New Approach to Produce Nanostructured Films Containing Phospholipids as Transducers in Sensing Applications

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

Exploiting Distinct Molecular Architectures of Ultrathin Films Made with Iron Phthalocyanine for Sensing

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

Sensor array made with nanostructured films to detect a phenothiazine compound

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

ANÁLISE DESCRITIVA QUANTITATIVA da AGUARDENTE DE CANA DURANTE O ENVELHECIMENTO em TONEL DE CARVALHO (Quercus alba L.)

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

Structural damage detection by fuzzy clustering

The development of strategies for structural health monitoring (SHM) has become increasingly important because of the necessity of preventing undesirable damage. This paper describes an approach to this problem using vibration data. It involves a three-stage process: reduction of the time-series data using principle component analysis (PCA), the development of a data-based model using an auto-regressive moving average (ARMA) model using data from an undamaged structure, and the classification of whether or not the structure is damaged using a fuzzy clustering approach. The approach is applied to data from a benchmark structure from Los Alamos National Laboratory, USA. Two fuzzy clustering algorithms are compared: fuzzy c-means (FCM) and Gustafson-Kessel (GK) algorithms. It is shown that while both fuzzy clustering algorithms are effective, the GK algorithm marginally outperforms the FCM algorithm. (C) 2008 Elsevier Ltd. All rights reserved.

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Phosphatidylcholine and Sphingomyelin Profiles Vary in Bos taurus indicus and Bos taurus taurus In Vitro- and In Vivo-Produced Blastocysts

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