Comparison between monopolar and bipolar microsecond range pulsed electric fields in enhancement of apple juice extraction

The effect of monopolar and bipolar shaped pulses in additional yield of apple juice extraction is evaluated. The applied electric field strength, pulsewidth, and number of pulses are assessed for both pulse types, and divergences are analyzed. Variation of electric field strength is ranged from 100 to 1300 V/cm, pulsewidth from 20 to 300 mu s, and the number of pulses from 10 to 200, at a frequency of 200 Hz. Two pulse trains separated by 1 s are applied to apple cubes. Results are plotted against reference untreated samples for all assays. Specific energy consumption is calculated for each experiment as well as qualitative indicators for apple juice of total soluble dry matter and absorbance at 390-nm wavelength. Bipolar pulses demonstrated higher efficiency, and specific energetic consumption has a threshold where higher inputs of energy do not result in higher juice extraction when electric field variation is applied. Total soluble dry matter and absorbance results do not illustrate significant differences between application of monopolar and bipolar pulses, but all values are inside the limits proposed for apple juice intended for human consumption.

Pulsed electric field pre-treatment for apple juice extraction: Evaluation of monopolar and bipolar pulses effects

Additional apple juice extraction with pulsed electric field pretreated apple cubes towards control samples is evaluated. Monopolar and bipolar shaped pulses are compared and their effect is studied with variation of electric field, pulse width and number of pulses. Variation of electric field strength is ranged from 100 V/cm to 1300 V/cm, pulse width from 20 mu s to 300 mu s and number of pulses from 10 to 200, at frequency of 200Hz. Two pulse trains separated by 1 second are applied to all samples. Bipolar pulses showed higher apple juice yields with all studied parameters. Calculation of specific energies consumed was assessed and a threshold where higher energy inputs do not increase juice yield is found for a number of used parameters. Qualitative parameters of total soluble matter (Brix) and absorbance at 390 nm wavelength were determined for each sample and results show that no substantial differences are found for PEF pre-treated and control samples.

Part I : Comparing derivatization methods for amino acids – one and two-step procedures using gas chromatography – flame ion detector (GC-FID) Part II: Story of an icon from its execution until its conservation

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do grau de Mestre em Conservação e Restauro

Optimization of HS-SPME analytical conditions using factorial design for trihalomethanes determination in swimming pool water samples

Trihalomethanes (THMs) are widely referred and studied as disinfection by-products (DBPs). The THMs that are most commonly detected are chloroform (TCM), bromodichloromethane (BDCM), chlorodibromomethane (CDBM), and bromoform (TBM). Several studies regarding the determination of THMs in swimming pool water and air samples have been published. This paper reviews the most recent work in this field, with a special focus on water and air sampling, sample preparation and analytical determination methods. An experimental study has been developed in order to optimize the headspace solid-phasemicroextraction (HS-SPME) conditions of TCM, BDCM, CDBM and TBM from water samples using a 23 factorial design. An extraction temperature of 45 °C, for 25min, and a desorption time of 5 min were found to be the best conditions. Analysis was performed by gas chromatography with an electron capture detector (GC-ECD). The method was successfully applied to a set of 27 swimming pool water samples collected in the Oporto area (Portugal). TCM was the only THM detected with levels between 4.5 and 406.5 μg L−1. Four of the samples exceeded the guideline value for total THMs in swimming pool water (100 μgL−1) indicated by the Portuguese Health Authority.

SPE-LC-FD Determination of Polycyclic Aromatic Hydrocarbon Monohydroxy Derivatives in Cephalopods

A new analytical methodology, based on liquid chromatography with fluorescence detection (LC-FD), after extraction, enzymatic hydrolysis, and solid-phase extraction (SPE) through Oasis HLB cartridges, was developed and validated for the simultaneous determination of three monohydroxy derivatives of polycyclic aromatic hydrocarbons (PAHs). The optimized analytical method is sensitive, accurate, and precise, with recoveries between 62 and 110% and limits of detection of 227, 9, and 45 ng/g for 1-hydroxynaphthalene, 2-hydroxyfluorene, and 1-hydroxypyrene, respectively. Their levels were estimated in different cephalopod matrices (edible tissues and hemolymph). The methodology was applied to samples of the major cephalopod species consumed worldwide. Of the 18 samples analyzed, 39% were contaminated with 1-hydroxynaphthalene, which was the only PAH metabolite detected. Its concentration ranged from 786 to 1145 ng/g. This highly sensitive and specific method allows the identification and quantitation of PAH metabolites in forthcoming food safety and environmental monitoring programs.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Optimization of antioxidants extraction from coffee silverskin, aroasting by-product, having in view a sustainable process

Coffee silverskin is a major roasting by-product that could be valued as a source of antioxidant compounds. The effect of the major variables (solvent polarity, temperature and extraction time) affecting the extraction yields of bioactive compounds and antioxidant activity of silverskin extracts was evaluated. The extracts composition varied significantly with the extraction conditions used. A factorial experimental design showed that the use of a hydroalcoholic solvent (50%:50%) at 40 °C for 60 min is a sustainable option to maximize the extraction yield of bioactive compounds and the antioxidant capacity of extracts. Using this set of conditions it was possible to obtain extracts containing total phenolics (302.5 ± 7.1 mg GAE/L), tannins (0.43 ± 0.06 mg TAE/L), and flavonoids (83.0 ± 1.4 mg ECE/L), exhibiting DPPHradical dot scavenging activity (326.0 ± 5.7 mg TE/L) and ferric reducing antioxidant power (1791.9 ± 126.3 mg SFE/L). These conditions allowed, in comparison with other “more effective” for some individual parameters, a cost reduction, saving time and energy.

Fast unsupervised technique for extraction of endmembers spectra from hyperspectral data

One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.

Fast unsupervised extraction of endmembers spectra from hyperspectral data

Linear unmixing decomposes an hyperspectral image into a collection of re ectance spectra, called endmember signatures, and a set corresponding abundance fractions from the respective spatial coverage. This paper introduces vertex component analysis, an unsupervised algorithm to unmix linear mixtures of hyperpsectral data. VCA exploits the fact that endmembers occupy vertices of a simplex, and assumes the presence of pure pixels in data. VCA performance is illustrated using simulated and real data. VCA competes with state-of-the-art methods with much lower computational complexity.

Comparison of Disposable Pipette Extraction and Dispersive Solid-Phase Extraction in the QuEChERS Method for Analysis of Pesticides in Strawberries

In this study, we sought to assess the applicability of GC–MS/MS for the identification and quantification of 36 pesticides in strawberry from integrated pest management (IPM) and organic farming (OF). Citrate versions of QuEChERS (quick, easy, cheap, effective, rugged and safe) using dispersive solid-phase extraction (d-SPE) and disposable pipette extraction (DPX) for cleanup were compared for pesticide extraction. For cleanup, a combination of MgSO4, primary secondary amine and C18 was used for both the versions. Significant differences were observed in recovery results between the two sample preparation versions (DPX and d-SPE). Overall, 86% of the pesticides achieved recoveries (three spiking levels 10, 50 and 200 µg/kg) in the range of 70–120%, with <13% RSD. The matrix effects were also evaluated in both the versions and in strawberries from different crop types. Although not evidencing significant differences between the two methodologies were observed, however, the DPX cleanup proved to be a faster technique and easy to execute. The results indicate that QuEChERS with d-SPE and DPX and GC–MS/MS analysis achieved reliable quantification and identification of 36 pesticide residues in strawberries from OF and IPM.

Desenvolvimento de Métodos de Extração de Resíduos de Antimicrobianos e Quantificação em Amostras Alimentares

O leite é um alimento complexo, pela sua composição rico em água, proteínas, lípidos, vitaminas e minerais. Devido ao seu alto valor nutricional é fundamental para a amamentação de crianças e animais em crescimento, pois fornece componentes fundamentais para o desenvolvimento e manutenção da saúde. Os antimicrobianos são amplamente utilizados como uma medida terapêutica no tratamento de infeções bacterianas, profilaxia e como promotores de crescimento (aditivos). A presença de resíduos de antimicrobianos no leite pode representar riscos para a saúde humana, como reações alérgicas em indivíduos hipersensíveis e resistências. Os objetivos deste estudo são o desenvolvimento de novos métodos de limpeza e de pré-concentração para amostras de leite, por meio de extração em fase sólida (SPE), com a finalidade de realizar uma melhor identificação e quantificação de antimicrobiana por Cromatografia Líquida de Alta Performance (HPLC). Todos os métodos desenvolvidos são de fácil execução, com taxas de recuperação dos agentes antimicrobianos viáveis, com uma percentagem de recuperação a partir de 85%. O método cromatográfico utilizado para a deteção e quantificação (HPLC-DAD) têm os limites de deteção (LD) entre 2.43ng / mL e 1.62ng / mL e os limites de quantificação (LQ) entre 7,36 ng / mL e 4.92 ng / mL, o que significa este método vai de encontro às diretrizes estipuladas pela União Europeia para os agentes antimicrobianos estudados. A combinação dos métodos propostos de limpeza e pré-concentração por SPE e multirresíduo por HPLC-DAD permite, por conseguinte, a deteção e quantificação de resíduos de antibióticos no leite, tornando esta uma alternativa importante e útil no processo de controlo de qualidade para a indústria de alimentos e outras área.

Data Extraction Tool to Analyse, Transform and Store Real Data from Electricity Markets

The study of electricity markets operation has been gaining an increasing importance in the last years, as result of the new challenges that the restructuring process produced. Currently, lots of information concerning electricity markets is available, as market operators provide, after a period of confidentiality, data regarding market proposals and transactions. These data can be used as source of knowledge to define realistic scenarios, which are essential for understanding and forecast electricity markets behavior. The development of tools able to extract, transform, store and dynamically update data, is of great importance to go a step further into the comprehension of electricity markets and of the behaviour of the involved entities. In this paper an adaptable tool capable of downloading, parsing and storing data from market operators’ websites is presented, assuring constant updating and reliability of the stored data.

Automatic Electricity Markets Data Extraction for Realistic Multi-agent Simulations

Electricity markets worldwide suffered profound transformations. The privatization of previously nationally owned systems; the deregulation of privately owned systems that were regulated; and the strong interconnection of national systems, are some examples of such transformations [1, 2]. In general, competitive environments, as is the case of electricity markets, require good decision-support tools to assist players in their decisions. Relevant research is being undertaken in this field, namely concerning player modeling and simulation, strategic bidding and decision-support.

Analysis of early synthetic dyes with HPLC-DAD-MS: an important database for analysis of colorants used in cultural heritage

Presented thesis at Faculdade de Ciências e Tecnologias, Universidade de Lisboa, to obtain the Master Degree in Conservation and Restoration of Textiles

Cochineal, a precious source of red: cochineal dyes characterization by high performance liquid chromatography with diode array detection and principal component analysis

Presented at Faculdade de Ciências e Tecnologias, Universidade de Lisboa, to obtain the Master Degree in Conservation and Restoration of Textiles