Studies of the liposolubility and the ecotoxicity of MC-LR degradation by-products using computational molecular modeling and in-vivo tests with Chlorella vulgaris and Daphnia magna.

Computational molecular modelling, mass spectrometry and in-vivo tests with Chlorella vulgaris (C. vulgaris) and Daphnia magna (D. magna) were used to investigate the liposolubility and ecotoxicity of MC-LR degradation by-products generated after oxidation by OH radicals in Fenton process.

Feasibility study on quantification and authentication of the cassava starch content in wheat flour for bread-making using NIR spectroscopy and digital images.

This works proposed a feasibility study on NIR spectroscopy and chemometrics-assisted color histogram-based analytical systems (CACHAS) to determine and authenticate the cassava starch content in wheat flour. Prediction results of partial least squares (PLS) achieved coefficient of correlation (r) of 0.977 and root mean square error of prediction (RMSEP) of 1.

Non-destructive authentication of Gourmet ground roasted coffees using NIR spectroscopy and digital images.

The growing demand for excellent-quality coffees allied with their symbolic aestheticization that add value to the products favor the adulteration practices and consequently economic losses. So, this work proposes the suitability of NIR spectroscopy and Digital Images (from CACHAS) coupled with one-class classification methods for the non-destructive authentication of Gourmet ground roasted coffees. For this, Gourmet coffees (n = 44) were discriminated from Traditional (n = 36) and Superior (n = 10) by directly analyzing their powder without any sample preparation.

Simultaneous voltammetric determination of four organic acids in fruit juices using multiway calibration.

A sensitive, fast, and inexpensive square wave voltammetric method using a cobalt phthalocyanine modified carbon paste electrode was developed for simultaneous determination of citric, lactic, malic and tartaric acids in fruit juices. To overcome the strong overlap of voltammetric signals caused by calibrated and uncalibrated constituents, multivariate curve resolution with alternating least squares (MCR-ALS) was used. Data were previous treated for correction of baseline and potential shift.

Simultaneous identification of the wood types in aged cachaças and their adulterations with wood extracts using digital images and SPA-LDA.

Cachaça is a sugarcane-derived alcoholic spirit exclusively produced in Brazil. It can be aged in barrels made from different types of wood, similar to other distilled beverages. The choice of wood type promotes different effects on color, flavor, aroma and consequently the price of cachaça, favoring fraudulent activities.

Macroemulsion-based dispersive magnetic solid phase extraction for preconcentration and determination of copper(II) in gasoline.

A new method referred to as microemulsion-based Dispersive Magnetic Solid-Phase Extraction (MDM-SPE) is presented for use in the extraction and preconcentration of metal ions from complex organic matrices. MDM-SPE combines the features of magnetic nanoparticles (MNPs) and microemulsions. It was successfully applied to the extraction of copper(II) from gasoline prior to its determination by Graphite Furnace Atomic Absorption Spectrometry (GF-AAS).

Determination of fat content in chicken hamburgers using NIR spectroscopy and the Successive Projections Algorithm for interval selection in PLS regression (iSPA-PLS).

Determining fat content in hamburgers is very important to minimize or control the negative effects of fat on human health, effects such as cardiovascular diseases and obesity, which are caused by the high consumption of saturated fatty acids and cholesterol. This study proposed an alternative analytical method based on Near Infrared Spectroscopy (NIR) and Successive Projections Algorithm for interval selection in Partial Least Squares regression (iSPA-PLS) for fat content determination in commercial chicken hamburgers. For this, 70 hamburger samples with a fat content ranging from 14.

Fluorescent fingerprints of edible oils and biodiesel by means total synchronous fluorescence and Tucker3 modeling.

The present work proposes the use of total synchronous fluorescence spectroscopy (TSFS) as a discrimination methodology for fluorescent compounds in edible oils, which are preserved after the transesterification processes in the biodiesel production. In the same way, a similar study is presented to identify fluorophores that do not change in expired vegetal oils, to associate physicochemical parameters to fluorescent measures, as contribution to a fingerprint for increasing the chemical knowledge of these products. The fluorescent fingerprints were obtained by Tucker3 decomposition of a three-way array of the total synchronous fluorescence matrices.

Handling time misalignment and rank deficiency in liquid chromatography by multivariate curve resolution: Quantitation of five biogenic amines in fish.

Biogenic amines (BAs) are used for identifying spoilage in food. The most common are tryptamine (TRY), 2-phenylethylamine (PHE), putrescine (PUT), cadaverine (CAD) and histamine (HIS). Due to lack of chromophores, chemical derivatization with dansyl was employed to analyze these BAs using high performance liquid chromatography with a diode array detector (HPLC-DAD).

Using UV-Vis spectroscopy for simultaneous geographical and varietal classification of tea infusions simulating a home-made tea cup.

In this work we proposed a method to verify the differentiating characteristics of simple tea infusions prepared in boiling water alone (simulating a home-made tea cup), which represents the final product as ingested by the consumers. For this purpose we used UV-Vis spectroscopy and variable selection through the Successive Projections Algorithm associated with Linear Discriminant Analysis (SPA-LDA) for simultaneous classification of the teas according to their variety and geographic origin. For comparison, KNN, CART, SIMCA, PLS-DA and PCA-LDA were also used.

Unfolded partial least squares/residual bilinearization combined with the Successive Projections Algorithm for interval selection: enhanced excitation-emission fluorescence data modeling in the presence of the inner filter effect.

The use of the successive projections algorithm (SPA) for elimination of uninformative variables in interval selection, and unfold partial least squares regression (U-PLS) modeling of excitation-emission matrices (EEM), when under the inner filter effect (IFE) is reported for first time. Post-calibration residual bilinearization (RBL) was employed against events of unknown components in the test samples. The inner filter effect can originate changes in both the shape and intensity of analyte spectra, leading to trilinearity losses in both modes, and thus invalidating most multiway calibration methods.

Modeling nonbilinear total synchronous fluorescence data matrices with a novel adapted partial least squares method.

A new residual modeling algorithm for nonbilinear data is presented, namely unfolded partial least squares with interference modeling of non bilinear data by multivariate curve resolution by alternating least squares (U-PLS/IMNB/MCR-ALS). Nonbilinearity represents a challenging data structure problem to achieve analyte quantitation from second-order data in the presence of uncalibrated components. Total synchronous fluorescence spectroscopy (TSFS) generates matrices which constitute a typical example of this kind of data.

Binary classification of chalcone derivatives with LDA or KNN based on their antileishmanial activity and molecular descriptors selected using the Successive Projections Algorithm feature-selection technique.

Chalcones are naturally occurring aromatic ketones, which consist of an α-, β-unsaturated carbonyl system joining two aryl rings. These compounds are reported to exhibit several pharmacological activities, including antiparasitic, antibacterial, antifungal, anticancer, immunomodulatory, nitric oxide inhibition and anti-inflammatory effects. In the present work, a Quantitative Structure-Activity Relationship (QSAR) study is carried out to classify chalcone derivatives with respect to their antileishmanial activity (active/inactive) on the basis of molecular descriptors.

Eco-friendly sonoluminescent determination of free glycerol in biodiesel samples.

This paper proposes a flow-batch methodology for the determination of free glycerol in biodiesel that is notably eco-friendly, since non-chemical reagents are used. Deionized water (the solvent) was used alone for glycerol (sample) extractions from the biodiesel. The same water was used to generate water-cavitation sonoluminescence signals, which were modulated by the quenching effect associated with the amount of extracted glycerol.

Electrochemical study of ricin at glassy carbon electrode.

Ricin, Ricinus communis agglutinin 60 - RCA 60, is a deadly phytotoxic protein which inhibits ribosomes (class II), and there is no known effective antidote in living organisms. Ricin is composed of two polypeptide chains, A and B, linked covalently by a single disulfide bond. The analytical methods for the detection of RCA 60 are commonly laborious, expensive, require skilled labor, and involve sophisticated equipment.

Automatized flow-batch method for fluorescent determination of free glycerol in biodiesel samples using on-line extraction.

An automatic method, based on flow-batch (FB), for determining glycerol in biodiesel was developed. The FB systems draw upon the useful features of flow, batch and multi-commutation approaches. The standards and samples preparation, as well as, derivatization and analysis were fully automated.

Flow injection photometric determination of NaCl, KCl and glucose in injectable drugs exploiting Schlieren signals.

A flow injection photometric system that exploits Schlieren signals for analytical measurement is described. The system was designed to be used as a new strategy for determining the contents of sodium chloride, potassium chloride and glucose, each respectively in injectable drugs. The proposed methodology was based on the difference between the refractive indices of the sample zone and of the carrier stream.

Flow-batch technique for the simultaneous enzymatic determination of levodopa and carbidopa in pharmaceuticals using PLS and successive projections algorithm.

An enzymatic flow-batch system with spectrophotometric detection was developed for simultaneous determination of levodopa [(S)-2 amino-3-(3,4-dihydroxyphenyl)propionic acid] and carbidopa [(S)-3-(3,4-dihydroxyphenyl)-2-hydrazino-2-methylpropionic acid] in pharmaceutical preparations. The data were analysed by univariate method, partial least squares (PLS) and a novel variable selection for multiple lineal regression (MLR), the successive projections algorithm (SPA). The enzyme polyphenol oxidase (PPO; EC 1.

An inexpensive, portable and microcontrolled near infrared LED-photometer for screening analysis of gasoline.

A microcontrolled, portable and inexpensive photometer is proposed. It uses a near infrared light emitting diode (NIR LED) as radiation source, a PbSe photoresistor as infrared detector and a programmable interrupt controller (PIC) microcontroller as control unit. The detector system presents a thermoresistor and a thermoelectric cooling to control the detector temperature and keep the noise at low levels.

A multiscale wavelet data treatment for reliable localization of inflection points for analytical purposes.

Instrumental analysis techniques that employ measurements based on inflection points may have their accuracy compromised due to the need for signal differentiation, which is very sensitive to instrumental noise. This paper presents a strategy for localizing inflection points that exploits the multiscale processing capability of the Wavelet Transform and avoids the need for explicit signal differentiation. The strategy is illustrated in simulated examples and also in a real analytical problem involving the determination of Pb and Cd by potentiometric stripping analysis.

A linear semi-infinite programming strategy for constructing optimal wavelet transforms in multivariate calibration problems.

A novel strategy for the optimization of wavelet transforms with respect to the statistics of the data set in multivariate calibration problems is proposed. The optimization follows a linear semi-infinite programming formulation, which does not display local maxima problems and can be reproducibly solved with modest computational effort. After the optimization, a variable selection algorithm is employed to choose a subset of wavelet coefficients with minimal collinearity.