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.

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)

Ferramentas quimiométricas aplicadas a classificação de amostras de leite em pó e quantificação de proteínas

In this work we used chemometric tools to classify and quantify the protein content in samples of milk powder. We applied the NIR diffuse reflectance spectroscopy combined with multivariate techniques. First, we carried out an exploratory method of samples by principal component analysis (PCA), then the classification of independent modeling of class analogy (SIMCA). Thus it became possible to classify the samples that were grouped by similarities in their composition. Finally, the techniques of partial least squares regression (PLS) and principal components regression (PCR) allowed the quantification of protein content in samples of milk powder, compared with the Kjeldahl reference method. A total of 53 samples of milk powder sold in the metropolitan areas of Natal, Salvador and Rio de Janeiro were acquired for analysis, in which after pre-treatment data, there were four models, which were employed for classification and quantification of samples. The methods employed after being assessed and validated showed good performance, good accuracy and reliability of the results, showing that the NIR technique can be a non invasive technique, since it produces no waste and saves time in analyzing the samples

Estudo da eficácia do tensoativo sorbitano tween 80 veiculado em nanoemulsão contendo óleo de soja, como inibidor de corrosão

Nowadays, the use of chemicals that satisfactorily meet the needs of different sectors of the chemical industry is linked to the consumption of biodegradable materials. In this context, this work contemplated biotechnological aspects with the objective of developing a more environmentally-friendly corrosion inhibitor. In order to achieve this goal, nanoemulsion-type systems (NE) were obtained by varying the amount of Tween 80 (9 to 85 ppm) a sortitan surfactant named polyoxyethylene (20) monooleate. This NE-system was analyzed using phase diagrams in which the percentage of the oil phase (commercial soybean oil, codenamed as OS) was kept constant. By changing the amount of Tween 80, several polar NE-OS derived systems (O/W-type nanoemulsion) were obtained and characterized through light scattering, conductivity and pH, and further subjected to electrochemical studies. The interfacial behavior of these NE-OS derived systems (codenamed NE-OS1, S2, S3, S4 and S5) as corrosion inhibitors on carbon steel AISI 1020 in saline media (NaCl 3.5%) were evaluated by measurement of Open Circuit Potential (OCP), Polarization Curves (Tafel extrapolation method) and Electrochemical Impedance Spectroscopy (EIS). The analyzed NE-OS1 and NE-OS2 systems were found to be mixed inhibitors with quantitative efficacy (98.6% - 99.7%) for concentrations of Tween 80 ranging between 9 and 85 ppm. According to the EIS technique, maximum corrosion efficiency was observed for some tested NE-OS samples. Additionaly to the electrochemical studies, Analysis of Variance (ANOVA) and Principal Component Analysis (PCA) were used, characterization of the nanoemulsion tested systems and adsorption studies, respectively, which confirmed the results observed in the experimental analyses using diluted NE-OS samples in lower concentrations of Tween 80 (0.5 1.75 ppm)

Uso da espectroscopia do infravermelho próximo e técnicas multivariadas para diferenciar escherichia coli e salmonella enteritidis inoculadas em polpa de fruta (abacaxi)

Aiming to consumer s safety the presence of pathogenic contaminants in foods must be monitored because they are responsible for foodborne outbreaks that depending on the level of contamination can ultimately cause the death of those who consume them. In industry is necessary that this identification be fast and profitable. This study shows the utility and application of near-infrared (NIR) transflectance spectroscopy as an alternative method for the identification and classification of Escherichia coli and Salmonella Enteritidis in commercial fruit pulp (pineapple). Principal Component Analysis (PCA), Independent Modeling of Class Analogy (SIMCA) and Discriminant Analysis Partial Least Squares (PLS-DA) were used in the analysis. It was not possible to obtain total separation between samples using PCA and SIMCA. The PLS-DA showed good performance in prediction capacity reaching 87.5% for E. coli and 88.3% for S. Enteritides, respectively. The best models were obtained for the PLS-DA with second derivative spectra treated with a sensitivity and specificity of 0.87 and 0.83, respectively. These results suggest that the NIR spectroscopy and PLS-DA can be used to discriminate and detect bacteria in the fruit pulp

Estudo da potencialidade da espectroscopia de infravermelho próximo na análise de cabelo utilizando ferramentas quimiométricas para diferenciar fumantes de não fumantes

This paper investigates the potential of near infrared spectroscopy (NIR) for forensic analysis of human hair samples in order to differentiate smokers from nonsmokers, using chemometric modeling as an analytical tool. We obtained a total of 19 hair samples, 9 smokers and 10 nonsmokers varying gender, hair color, age and duration of smoking, all collected directly from the head of the same great Natal-RN. From the NIR spectra obtained without any pretreatment of the samples was performed an exploratory multivariate chemical data by applying spectral pretreatments followed by principal component analysis (PCA). After chemometric modeling of the data was achieved without any experimental data beyond the NIR spectra, differentiate smokers from nonsmokers, by demonstrating the significant influence of tabacco on the chemical composition of hair as well as the potential of the methodology in forensic identification

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.

Using chemical and physical parameters to define the quality of Pardo River water (Botucatu-SP-Brazil)

This paper aims to study the ecological system of the Pardo River, at the source and lower-order passages, which are in the Botucatu area, São Paulo State, Brazil. This study was carried out to determine water quality with some chemical-physical indicators, coliforms, and chemical species of samples taken monthly, 1995/02-1996/01, from eight sampling stations sited along the Pardo River. The results in the river monitoring are discussed based on annual averages, analysis of variance, and compared to Tukey's Studentized Range-HSD, and principal component analysis (PCA) was applied to normalize data to assess association between variables. We can conclude that the variables used are very efficient for identifying and that the dry season shows the worst water quality. These were caused by organic matter, nutrients (originate) from anthropogenic sources (spatial sources) and mainly municipal wastewater, affecting the quality and hydrochemistry of the river water, which have been differentiated and assigned to polluting sources. Meanwhile, the degree of degradation of the Pardo River is low (sewage treatment carried out by the city of Pardinho is efficient), leaving the water of the river suitable for use by the population of Botucatu, after conventional treatment (Conama, Resolucao No. 20, CONAMA, Brazilia DF, 09-23, 1986-the water of the Pardo river is classified as level 03). (C) 2001 Elsevier B.V. Ltd. All rights reserved.

Toward a hierarchical concept of plant stress

A number of attempts have been made to obtain a clear definition of biological stress. However, in spite of the efforts, some controversies on the concept of plant stress remain. The current versions are centered either on the cause (stress factor) or on the effect (stress response) of environmental stress. The objective of this study was to contribute to the definition of stress, using a hierarchical approach. Thus, we have performed an analysis of the most usual stress concepts and tested the relevance of considering different observation scales in a study on plant response to water deficit. Seedlings of Eucalyptus grandis were grown in vitro at water potentials ranging from -0.16 to -0.6 MPa, and evaluated according to growth and biochemical parameters. Data were analyzed through principal component analysis (PCA), which pointed to a hierarchical organization in plant responses to environmental disturbances. Growth parameters (height and dry weight) are more sensitive to water deficit than biochemical ones (sugars, proline, and protein), suggesting that higher hierarchical levels were more sensitive to environmental constraints than lower hierarchical ones. We suggest that before considering an environmental fluctuation as stressful, it is necessary to take into account different levels of plant response, and that the evaluation of the effects of environmental disturbances on an organism depends on the observation scale being used. Hence, a more appropriate stress concept should consider the hierarchical organization of the biological systems, not only for a more adequate theoretical approach, but also for the improvement of practical studies on plants under stress.

Evidence of higher photosynthetic plasticity in the early successional Guazuma ulmifolia Lam. compared to the late successional Hymenaea courbaril L. grown in contrasting light environments

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

Performance of an Anaerobic Baffled Reactor (ABR) in treatment of cassava wastewater

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