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This work deals with different aspects related to biomass combustion in a medium-size commercial pellet boiler. Firstly, there were evaluated the heating requirements of a bioclimatic building to select an adequate device. Once started up, it was developed a complete monitorization of gaseous emissions and solid wastes aiming to optimize its performance by manually modifying the fuel feeding and air inlet. Thanks to this, fuel consumption decreased a 20% and oxidizing air inlet was lessened to a 21% excess, what led to a reduction of CO, NOx and SO2 emissions to values respectively below 200 ppm and 80 and 30 mg/Nm3. Thermal yield was enhanced from 78.6 to 94.9%. Chamber and fumes temperatures and thermal rise increased to respectively 160 °C and 20 °C, accomplishing values recommended by boiler’s manufacturer. All measures taken, and the results they provided, entailed meaningful environmental and economical improvements.

Short Rotation Coppice Willow (SRCW) is one of the newest sources of renewable energy. Torrefaction enhances the initial poorest characteristics of SRCW, such as hygroscopicity or low heating value compared to traditional fuels, to use it as a fuel. Non-oxidative and oxidative torrefaction of SRCW were compared. Torrefaction were conducted within the range 200–240 °C and torrefied SRCW and released gases were characterized (proximate, ultimate, compositional and heating value analysis as well as hydrophobicity assessment, Py-GC/MS and chemical-kinetics parameters). At optimal torrefaction temperature, mass and energy yields were around 88% and 93%, respectively, moisture was reduced up to 1.22–1.28% and H/C and O/C atomic ratios up to 1.4 and 0.6, respectively. Biomass turns hydrophobic since contact angle increase and the amount of water absorb decrease in contact angle and liquid penetration studies, respectively. The global reaction order was 2 and kinetic constant values were in the range 4.6 10−5 s−1–3.6 10−5 s−1.

Compositional analysis of non-woody biomass is quite important to determine its possible applications. However, current standard methods developed for woody biomass compositional analysis have been revealed to be unsuitable when applied to non-woody biomass. Therefore, a novel and less-time consuming modified method which enables for a proper isolation of holocellulose in non-woody biomass samples while increasing lignin degradation has been developed. The novel method mainly consists in a treatment with sodium chlorite and glacial acetic acid at boiling point, which precludes changes in the holocellulose crystallinity degree or losses of carbohydrates, as shown by DSC, XRPD, and HPLC analysis. It was successfully applied to the determination of the structural components of 10 different non-woody biomass samples. Also, its use revealed that non-woody biomass belongs to LHC and LCH groups in the biomass structural composition ternary diagram, which are completely different than the ones the woody biomass belongs to, Ministerio de Economía, Industria y Competitividad (MINECO-13-CTQ2013-45155-R; Consejería de Economía y Empleo del Principado de Asturias (FC-15-GRUPIN14-095); Programa Severo Ochoa de ayudas predoctorales (PA-13-PF-BP13058)

The constant increase in the use of biomass fuels has raised prices of the most common commercial products and consequently seeking for new alternative biomass resources for thermal conversion, like some industrial and agricultural wastes, becomes an interesting issue. To this aim, thirteen alternative raw biomass samples were analyzed and compared with briquette, wood pellets, and charcoal. Their proximate, ultimate and calorimetric analysis and physical properties data have been considered. In the same way gaseous emissions, ash composition, deposition and corrosion tendencies were evaluated. In addition to these intrinsic and environmental parameters, a general economic study, based on our previously obtained data, has been developed. Some of the selected samples, like almond shell and especially olive stone, seem to be optimum biomass resources to use instead of wood pellets, charcoal or briquettes in grate boilers, while some others require pretreatment to improve their characteristics and make them suitable alternatives to be considered in a short term future.

Disturbances in lipid composition and lipoproteins metabolism can play a crucial role in the pathogenesis of Parkinson's disease (PD) and other neurodegenerative diseases. The lipidomic strategy proposed here involves lipoprotein profiling using NMR spectroscopy and multivariate data pre-processing and analysis tools on 94 plasma samples (belonging to 38 early-stage PD patients, 10 PD-related dementia patients, 23 persons with Alzheimer's dementia, and 23 healthy control subjects) to firstly differentiate PD patients (irrespective of the stage of the disease) from persons with Alzheimer's disease (AD) as well as from controls, and then to discriminate among PD patients according to disease severity. The whole data set was subdivided into 86 training and 8 external test samples for validation purposes. A two-step classification scheme, based on linear discriminant analysis with variable selection accomplished by a stepwise orthogonalisation procedure, was proposed to optimise classification performance. Careful pre-processing of NMR signals was crucial to ensure data set quality. A total of 30 chemical shift buckets enabled differentiation between PD patients (regardless of disease severity), AD and control subjects, providing classification, cross-validation and external prediction rates of 100% in all cases. Only 15 variables were required to further discriminate between early-stage PD and PD-related dementia, again with 100% correct classifications, and internal/external predictions. The simplicity and effectiveness of the classification methodology proposed support the use of NMR spectroscopy, in combination with chemometrics, as a viable alternative diagnostic tool to conventional PD clinical diagnosis.

Torrefaction improves some of the poorest characteristics of biomass such as hygroscopicity, low energy density, or poor grindability which may cause some problems during its handling, storage and combustion. The aim of this work is to apply the torrefaction process to a Short Rotation Coppice of Poplar (SRCP) and characterize the new fuel. Therefore, both non-oxidative and oxidative torrefaction of SRCP were conducted in a tube furnace reactor within the range 200–240 °C and the torrefied biomass was fully characterize, i.e., proximate, ultimate, compositional and heating value analysis as well as wettability studies. In addition, Pyrolysis-Gas Chromatography/Mass Spectrometry (Py-GC/MS) was performed at optimal torrefaction temperature. Torrefaction kinetics were obtained using a thermogravimetric analyzer at optimal torrefaction temperature. Minimum mass and energy yields were found to be respectively 85.0% and 87.4% for oxidative torrefaction and 87.5% and 94.1% for non-oxidative option. Moisture was reduced from 6.97% to 4.8% and 4.4% for oxidative and non-oxidative torrefaction, respectively. Wettability studies carried out show an increase in hydrophobic behavior. Lignin was affected by torrefaction since decomposition products from guaiacyl (G) and syringyl (S) units were released during Py-GC/MS experiments. The reaction orders were 1.92 and 1.82 for oxidative and non-oxidative torrefaction, respectively and kinetic constant values were 5.99·× 10−5 and 2.98·× 10−5 s−1.

Routine wine analysis are commonly employed to ensure the quality and safety standards, and to meet consumers demands and legal requirements. In the last decades, efforts have been done in order to replace the traditional analytical techniques by vibrational spectroscopic techniques such as near infrared (NIR) and mid infrared (MIR) spectroscopy. The potential of these techniques has already been proved by several studies that revealed their ability for the determination of several wine parameters with high levels of precision and accuracy. Raman spectroscopy, (which is also a vibrational technique), was much less explored in the wine industry. In this work, the ability of Raman spectroscopy for routine wine analysis was evaluated and compared to NIR and MIR spectroscopy. Several calibration models were developed aiming the quantitative assessment of alcoholic strength, density, total acidity, volatile acidity, total sugars and pH in white wines. For this purpose, partial least squares (PLS) regression was employed, enabling the correlation between reference results and spectral information obtained by NIR, MIR and Raman spectroscopy. Results revealed the better performance of MIR spectroscopy for the measurement of alcoholic strength (R2 P = 0.99, RMSEP=1.77%, and RER=56.41), and total acidity (R2 P = 0.98, RMSEP=2.02%, and RER=49.46). Raman spectroscopy was pointed out as the most suitable for the determination of total sugars (R2 P = 0.97, RMSEP=5.12%, RER=19.52), and pH (R2 P = 0.90, RMSEP=4.92%, RER=20.34). The three techniques presented similar results in what referred the assessment of density (R2 P = 0.96, 0.98, and 0.97, RMSEP=4.72%, 3.90%, and 3.80%, for Raman, MIR, and NIR respectively). None of the three techniques seemed to be suitable for the accurate determination of volatile acidity (R2 P 14.32%, and RER

Torrefaction upgrades the biomass as an energy source enhancing its poorest characteristics. Non-oxidative torrefaction of six biomass samples (pine, eucalyptus, chestnut, holm oak, olive tree pruning and vine shoot) was conducted in a tube furnace reactor within the range 200–300 °C and proximate, ultimate and heating value analysis as well as wettability studies were carried out to characterize the torrefied samples and find the optimal temperature of the process. In addition, Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) was performed and chemical-kinetics parameters of torrefaction were obtained at optimal temperature. At optimal torrefaction temperature, moisture was reduced up to 2.5% and H/C and O/C atomic ratios up to 1.3 and 0.6, respectively. Contact angle measurements show an increase in hydrophobic behaviour. Lignin was affected by torrefaction since decomposition products from guaiacyl (G) and syringyl (S) units were released during Py-GCMS experiments. The global reaction order was 2.2 and kinetic constant values were in the range 2.17·10−5 to 4.83·10−5 s−1.

Experimental self-diffusivities of gases, vapors, and liquids obtained by means of tracer techniques and nuclear magnetic resonance are reviewed. The considered substances range from noble gases and simple diatomics (nitrogen, oxygen, carbon monoxide, etc.) to complex organic molecules, such as phenolphthalein dimethyl ether and 2-(α-methylbenzylamino)-5-nitropyridine, although polymers have not been included. Some comments on the applicability of neutron scattering to the determination of self-diffusion coefficients are also made. All the experimental results of the investigated systems are given as Supporting Information, whereas the references, temperatures, and pressures of these data and the main features of the measurement methods are compiled and classified.

Energy and sustainability (2019, Coimbra, Portugal), This article is greatly indebted to Ministerio de Economía, Industria y Competitividad MINECO (Spain) for the economic support given to the Normalized Vegetable Biomass for Efficient Energetic Trigeneration project (MINECO-13-CTQ2013-45155-R) and Consejería de Economía y Empleo del Principado de Asturias for the economic support given to the TRIBIONOR project (PCTI Asturias 2013–2017, Ref. FC-15-GRUPIN14-095), which makes the continuation of research in this field possible. A. Álvarez acknowledges receipt of a graduate fellowship from the Severo Ochoa Program (Principado de Asturias, Spain).

Human immunodeficiency virus (HIV) is a retrovirus that weakens the immune system and permits opportunistic diseases such as hepatitis C (HCV) to enter the body. These diseases induce metabolic disorders in the patients and it is therefore logical to approach them from a holistic, functional perspective, studying the metabolome comprehensively to identify metabolic signatures associated with certain disease states. The metabolomics strategy here proposed involves metabolic fingerprinting using Fourier transform infrared spectroscopy and chemometric tools on 72 plasma samples (subdivided into 63 training and 9 test samples) to differentiate between healthy subjects and patients with different disease stages. Several options, relating to the variable selection method used in linear discriminant analysis and the number of categories being considered, were explored to optimize discrimination ability. A total of 18 bands enabled differentiation between control subjects, HIV patients and the group that encompassed patients with acquired immune deficiency syndrome (AIDS), AIDS/HCV and HIV/HCV, providing overall classification and internal prediction rates of 97.67% and 93.65%, respectively. Only 9 bands were required to further discriminate between AIDS, AIDS/HCV and HIV/HCV, with 99.20% (training) and 89.66% (cross-validation) correct classifications. The simplicity and effectiveness of the classification methodology proposed was reinforced by the satisfactory results obtained in external prediction.

The ability of the extended corresponding states principle (ECSP) to predict the self-diffusion coefficients of several types of fluids has been studied. Two versions of the model were compared with the traditional two-parameter corresponding states principle (where the equilibrium shape factors are set to unity): one using the equilibrium shape factors and another one that additionally introduces a correction based on the modified Enskog theory (MET). Ethane was chosen as a reference fluid and the experimental database comprises 3163 points from 37 substances (polar, non-polar and hydrogen-bonding ones). Results show that a third complementary parameter, generated from diffusion data, is necessary to accurately correlate this transport property.

Due to the great variety of existing potential biomass fuels, measuring their heating value accurately is a previous design requirement, since this is one of the most important parameters regarding the evaluation of competitive energy generation from biomass combustion. In this work, the higher heating value (HHV) of 100 different biomass samples was experimentally determined. The list of biofuels tested includes different kinds of solid densified commercial fuels, forest and agricultural industry residues, woody and herbaceous residues, energetic crops and cereals. Ultimate analysis-based equations were used to develop a correlation between data, in order to quantify the detected dependence of HHV on mainly carbon and oxygen content. A comparative study was carried out between our results and those predicted from theoretical equations found in the bibliography. The wide experimental database enables us to propose new predictive correlations, with departures from experimental values below 6% in all cases, as a contribution to the characterization and normalization of solid biofuels.

The potential of stepwise orthogonalisation of predictors (SELECT) coupled with multivariate calibration methods and pre-processing tools was examined to develop reliable and parsimonious regression models based on Fourier-transform mid-infrared (FT-MIR) spectroscopy for the prediction of peroxide value in extra virgin olive oils. The comprehensive calibration methodology proposed also involved the study of the structure of noise present in data, the preliminary detection of anomalous objects, and the appropriate construction of calibration sets. The improvement achieved through the application of feature selection was particularly remarkable when SELECT-Ordinary Least Squares (OLS) was applied on first-derivative spectra. In this case, a high-quality OLS model was obtained, providing a predictive ability similar to that achieved by full spectrum approaches (after noise removal and signal pre-processing) and with no significant signs of over-fitting (4.9, 5.3 and 5.2% root-mean-square errors of the residuals obtained in calibration, cross-validation and external prediction, respectively), but considerably improved properties in terms of model parsimony and interpretability. In fact, it should be noted that only 12 relevant predictors from a total of 408 original wavenumbers were selected to model peroxide value, which meant a very notable compression rate. The quality of the results obtained encourages the feasibility of implementing a FT-MIR based calibration strategy similar to that proposed in routine analysis for the assessment of other critical quality parameters for olive oil.

The storage of CO2 in unused coal mines is a viable option for reducing emissions of CO2, whose accumulation in the atmosphere is one of the main contributors to global warming. Understanding CO2 behaviour and storage capacity of the coal is an important first step before injecting the CO2. We used experimental equipment to extract coal from a mine and to obtain a representative sample of both its internal structure (in terms of cleats, macropores, mesopores and micropores) and occluded gases. Storage capacity was studied in terms of variations in gas pressure. The adsorption isotherm was experimentally obtained applying a procedure specifically designed to avoid altering the coal. An unused coal bed was selected to determine how much CO2 it could adsorb and to study the feasibility of storing power plant CO2 in this kind of mine.

This work proposes a 25 min-last thermogravimetric method as a tool to determine biomass sample's proximate analysis data (moisture, ash, volatile matter and fixed carbon contents) just by direct measure of weight changes on each sample's TG chart. Compared with international standards commonly used to that aim, TG is a faster and easier to develop technique. Obtained results were satisfactory, with AEE under 6% for moisture and volatile matter, close to 10% for fixed carbon determination and AAD of 1.6 points for ash content.

Binary diffusion coefficients of isobutylbenzene, sec-butylbenzene, and 3-methylbutylbenzene (isopentylbenzene) in carbon dioxide were measured at supercritical conditions: temperatures of (313, 323, and 333) K and in a pressure range of (15.0 to 35.0) MPa using the Taylor–Aris technique. The dependency on temperature, pressure, carbon dioxide density, and carbon dioxide viscosity was examined. The experimental results were compared with the predictions of 14 semiempirical equations derived from the Stokes–Einstein equation (six equations) and from the model of the rough-hard-sphere (eight equations). Despite of the low errors of some of them, none reproduced the trend in which the isomers diffused.

The potential of visible fingerprints and physical-chemical parameters in combination with multivariate data analysis was examined to classify extra virgin olive oils (EVOOs) from different Spanish regions according to their geographical origin. Firstly, spectral and quality parameters matrices were processed separately and subsequently were joined to evaluate the effect of synergy on the information obtained from the different methodologies. Linear discriminant analysis (LDA) and partial least squares discriminant analysis (PLS-DA) were performed as classification methods. The results revealed a perfect discrimination between the defined categories after performing PLS-DA on the Fused matrix, reaching 100% of correct classifications and showed a clear improvement in the overall prediction rates (92.5%), so that the effect of synergy was confirmed. These accurate results emphasise the feasibility of the proposed strategy and encourage the development of similar approaches based on visible spectroscopy in olive oil quality and traceability determination.

Two young red wines from D.O. Navarra (Spain) were separately subjected to accelerated aging in tanks with oak chips added and micro-oxygenation. Wine samples were collected during each process and were analyzed by a sensory panel according to 17 descriptors. A two-fold monitoring approach, aimed at both checking panel performance and tracking the impact of chips/micro-oxygenation treatments on sensory properties, was proposed for process control and optimisation. In a first stage this approach focused on investigating panel performance by suitably combining uni- and multivariate methods. Significant product effects were found for 7 and 6 attributes in the first and second aging series, respectively. Although panel performance was acceptable in both cases, moderate differences between assessors were detected, stressing the need for adopting a consensus approach to properly handle them. Thus, the STATIS method was subsequently applied to find an optimal compromise solution for the significant attributes describing each process. The resulting compromise matrix provided the consensus sensory profiles of samples at different aging stages. The assignment of individual weights was consistent with previous findings on assessors’ agreement. The first principal component of the compromise matrix, which accounted for 86.5% and 90.9% of the variance in each trial data, revealed a sample trend directly related to the time-course evolution of each process, and contrasted the attributes fruit and herbaceous with the other significant descriptors (related to the wood–wine interaction). This is the first time that a multi-block methodology has been used for monitoring sensory changes during accelerated aging processes.

The declining reserves and fluctuating prices of fossil fuels led to intensive search for an alternative to replace or complement petroleum derivates as main fuel resource. In this context biomass appears as an attractive feedstock, because of that a comprehensive characterization is needed, focusing morphological study, using scanning electron microscope (SEM) and particle size distribution, composition with X-ray dispersive energy (EDX), thermal analyses, using thermogravimetry and combustion gas analysis, to select the best behavior as a fuel from six biomass samples (almond shell, rice husk, straw, vegetable coal, wine pomace and a randomly chosen commercial brand of wood pellets) trying to comb all the range of commercial fuels most commonly available in the Spanish solid biofuel market.

The aim of this work is to provide a wide database of kinetic data for the most common biomass by thermogravimetric analysis (TGA) and differential thermogravimetry (DTG). Due to the characteristic parameters of DTG curves, a two-stage reaction model is proposed and the kinetic parameters obtained from model-based methods with energy activation values for first and second stages in the range 1.75·10(4)-1.55·10(5)J/mol and 1.62·10(4)-2.37·10(5)J/mol, respectively. However, it has been found that Flynn-Wall-Ozawa and Kissinger-Akahira-Sunose model-free methods are not suitable to determine the kinetic parameters of biomass combustion since the assumptions of these two methods were not accomplished in the full range of the combustion process.

In this study, ultrasound-assisted emulsification microextraction combined with solidification of floating organic drop method (USAEME–SFOD) has been proposed as a novel approach for the sensitive determination of haloanisoles and volatile phenols in wines. For this purpose, the influence of the different parameters affecting the procedure (type and volume of extraction solvent, temperature, time and ionic strength) was evaluated in order to optimise the efficiency of the process. Subsequently, the linearity, detection and quantification limits, precision, recoveries and applicability to real samples were studied, obtaining excellent method performance results. Moreover, USAEME–SFOD was compared with other liquid–liquid microextraction methods such as dispersive liquid–liquid microextraction (DLLME) and ultrasound-assisted emulsification microextraction (USAEME). This comparison study proved the suitability of USAEME–SFOD as an alternative to previously reported methods for the simultaneous determination of cork taint and Brett character responsible compounds in wines.

In this paper, a method based on microwave assisted extraction (MAE) in combination with dispersive liquid–liquid microextraction (DLLME) has been proposed as a new approach for the sensitive determination of cork taint responsible compounds in cork stoppers and oak barrel sawdust. For this purpose, haloanisoles and halophenols were extracted from the solid samples using a MAE method. Subsequently, a DLLME-derivatisation procedure was applied on the MAE extracts and the analytes were determined by gas chromatography–electron capture detection (GC–ECD). Parameters affecting the DLLME-derivatisation method were exhaustively investigated by means of experimental design methodology. Once optimised, the proposed method showed satisfactory linearity (correlation coefficients over 0.991), repeatability (below 10.4%) and inter-day precision (below 11.2%). Detection limits obtained were similar or even lower than previously reported. The results obtained proved the suitability of the combination of MAE with DLLME as a sensitive sample preparation methodology for the analysis of haloanisoles and halophenols in solid enological matrices.

In this study, an ultrasound-assisted emulsification-microextraction (USAEME) has been optimised for the sensitive determination of haloanisoles (2,4,6-trichloroanisole (TCA), 2,3,4,6-tetrachloroanisole (TeCA), 2,4,6-tribromoanisole (TBA) and pentachloroanisole (PCA)) and volatile phenols (4-ethylphenol (4-EP), 4-ethylguaiacol (4-EG), 4-vinylphenol (4-VP) and 4-vinylguaiacol (4-VG)) in wine using gas chromatography coupled to tandem mass spectrometry (GC-MS/MS). Optimisation of USAEME method was performed by evaluating the different parameters that influence the recovery of the analytes in the extract. Firstly, extraction solvent was selected. Subsequently its volume, the ionic strength and the time and temperature at which the extraction must be performed were simultaneously evaluated by means of experimental design methodology. After optimisation step, the analytical characteristics of the method were evaluated. Satisfactory linearity (with correlation coefficients over 0.989), repeatability (below 11.5%) and inter-day precision (below 11.7%) were obtained for all target analytes. For all the studied compounds, detection limits obtained were similar or even lower than previously reported. In addition, the developed method was successfully applied to the analysis of wine samples. To the best of our knowledge, this is the first time that USAEME has been applied to simultaneously determine the compounds responsible for cork taint and Brett character in wine.

In this work, an ultrasound-assisted emulsification–microextraction method has been optimised for the determination in wine of haloanisoles (2,4,6-trichloranisole (TCA), 2,3,4,6-tetrachloroanisole (TeCA), 2,4,6-tribromoanisole (TBA) and pentachloranisole (PCA)) responsible for the so-called cork taint. Their halophenolic precursors (2,4,6-trichlorophenol (TCP), 2,3,4,6-tetrachlorophenol (TeCP), 2,4,6-tribromophenol (TBP) and pentachlorophenol (PCP)) have also been simultaneously determined. For this purpose, parameters affecting the USAEME–derivatisation procedure were exhaustively investigated. Firstly, extraction solvent, basic conditions and extraction time were selected to, subsequently, employ experimental design methodology for the simultaneous optimisation of the volumes of acetic anhydride and extraction solvent, temperature and ionic strength conditions. Once optimised, the evaluation of the analytical performance of the method confirmed its suitability for the determination of the studied compounds in wines. The proposed method showed satisfactory linearity (correlation coefficients over 0.981), repeatability (below 10.9%) and inter-day precision (below 11.0%). Detection limits obtained were similar or even lower than previously reported. In addition, the proposed method was successfully applied to the analysis of real samples. To our knowledge, this is the first time that USAME method has been optimised for the simultaneous determination of haloanisoles and halophenols in wine.

Energy plays an important role in the world's present and future. The best way to absorb the huge increase in energy demands is through diversification. In this context biomass appears as an attractive source for a number of environmental, economical, political and social reasons. There are several techniques used to obtain energy from biomass. Among these techniques, the most commonly used throughout the world is a thermo-chemical process to obtain heat. To optimize the combustion process in adequate reactors, a comprehensive study of the characterization of biomass fuel properties is needed, which includes proximate analysis (determination of moisture, ash, volatile and fixed carbon content), ultimate analysis (C, H, N, S and O composition) and calorimetry, focusing on biomass fuels obtained in Spain.

Lipid profiling is a promising tool for the discovery and subsequent identification of biomarkers associated with various diseases. However, data quality is quite dependent on the pre-analytical methods employed. To date, potential confounding factors that may affect lipid metabolite levels after the thawing of plasma for biomarker exploration studies have not been thoroughly evaluated. In this study, by means of experimental design methodology, we performed the first in-depth examination of the ways in which thawing conditions affect lipid metabolite levels. After the optimization stage, we concluded that temperature, sample volume and the thawing method were the determining factors that had to be exhaustively controlled in the thawing process to ensure the quality of biomarker discovery. Best thawing conditions were found to be: 4 °C, with 0.25 mL of human plasma and ultrasound (US) thawing. The new US proposed thawing method was quicker than the other methods we studied, allowed more features to be identified and increased the signal of the lipids. In view of its speed, efficiency and detectability, the US thawing method appears to be a simple, economical method for the thawing of plasma samples, which could easily be applied in clinical laboratories before lipid profiling studies.

In this study, a method based on ultrasound-assisted emulsification–microextraction (USAEME) was optimised for the determination of Brett character responsible compounds (4-ethylguaiacol (EG), 4-ethylphenol (EP), 4-vinylguaiacol (VG) and 4-vinylphenol (VP)) in wines. For this purpose, once the extraction solvent had been selected, the influence on the extraction efficiency of ratio between extraction solvent and sample volumes, temperature, ionic strength and time was studied using experimental design methodology. The optimum conditions found for USAEME of 5 mL of wine were 160 μL of chlorobenzene at 60 °C during 5 min without salt addition. Then, the analytical performance of the optimised USAEME procedure was evaluated. For all the studied compounds, the proposed method showed correlation coefficients over 0.984. Satisfactory repeatability (below 10%) and inter-day repeatability (below 11%) were obtained at different concentration levels and the method achieved detection limits similar or even lower than previously reported for these compounds in wines. Moreover, the applicability of the method was evaluated by the analysis of real samples. To our knowledge, this is the first time that USAEME has been applied to the determination of Brett character responsible compounds in wine.

The present study shows how multivariate analysis and variable selection techniques can be used in archaeological provenances studies to improve classification performances. Neutron activation analysis (NAA), in combination with stepwise linear discrimination analysis (SLDA) (capable of simultaneously performing variable selection and classification), was applied to differentiate among limestone samples from different quarries across the north of France based on their compositional fingerprint. A hierarchical classification approach was followed, aimed at progressively assigning limestone samples to more specific sources of origin, from the broadest classification units (French regions) to the narrowest ones (individual quarries). The application of the stepwise variable selection procedure to extract the most discriminating compositional variables prior to each classification development allowed us to obtain a perfect separation between the limestone categories considered at every classification stage (all samples were correctly classified and predicted in all cases). The high-quality results obtained were even more remarkable considering the relatively small number of significant variables selected in each case using the SLDA method. An illustrative example was provided in order to demonstrate that the classification strategy proposed can actually allocate an unknown sculpture to a particular quarry of origin. © University of Oxford, 2011.

A novel dispersive liquid-liquid microextraction (DLLME) method, coupled to gas chromatography-tandem mass spectrometry (GC-MS/MS), was developed for simultaneously determining the main compounds responsible for cork taint (2,4,6-trichloranisole (TCA), 2,3,4,6-tetrachloroanisole (TeCA), 2,4,6-tribromoanisole (TBA) and pentachloranisole (PCA)) and Brett character (4-ethylguaiacol (EG), 4-ethylphenol (EP), 4-vinylguaiacol (VG) and 4-vinylphenol (VP)) in wines. Optimisation of DLLME procedure was performed by evaluating the type of disperser and extraction solvents and the temperature and salt addition effects. The volumes of disperser and extraction solvents were also optimised by means of a central composite design combined with desirability functions. Under optimum conditions, 5 mL of wine were extracted with an extraction mixture consisting of 1.43 mL of acetone, and 173 μL of chloroform at room temperature. The analytical characteristics of the method were evaluated. Satisfactory linearity (with correlation coefficients over 0.992), repeatability (below 11.6%) and between-days precision (below 11.0%) were obtained for all target analytes. Detection limits attained were at similar levels or even lower than the olfactory threshold of the studied compounds. Finally, the developed method was successfully applied to the analysis of wine samples. To our knowledge, this is the first time that DLLME has been applied to simultaneously determine the compounds responsible for cork taint and Brett character in wine.

Fourier-transform mid-infrared (FT-MIR) spectroscopy, combined with partial least-squares (PLS) regression and IPW as feature selection method, was used to develop reduced-spectrum calibration models based on a few IR bands to provide near-real-time predictions of two key parameters for the characterization of finished red wines, which are essential from a quality assurance standpoint: total and volatile acidity. Separate PLS calibration models, correlating IR data (only considering those regions showing a high signal to noise ratio) with each response studied, were developed. Wavenumber selection was also performed applying IPW-PLS to take into account only significant predictors, in an attempt to improve the quality of the final models constructed. Using both PLS and IPW-PLS regression, prediction of the two responses modelled was performed with very high reliability, with RMSECV and RMSEP values on the order of 1% (comparable in terms of accuracy to the results provided by the respective reference analysis methods). An important advantage derived from the application of the IPW-PLS method had to do with the low number of original variables needed for modelling both total acidity (22 significant wavenumbers) and volatile acidity (only 11 selected predictor variables), in such a way that variable selection contributed to enhance the stability and parsimony properties of the final calibration models. The high quality of the calibration models proposed encourages the feasibility of implementing them as a fast and reliable tool in routine analysis for the determination of critical parameters for wine quality.

A simple, accurate and sensitive method based on headspace solid-phase microextraction (HS-SPME) coupled to gas chromatography-tandem mass spectrometry (GC-MS/MS) was developed for the analysis of 4-ethylguaiacol, 4-ethylphenol, 4-vinylguaiacol and 4-vinylphenol in beer. The effect of the presence of CO2 in the sample on the extraction of analytes was examined. The influence on extraction efficiency of different fibre coatings, of salt addition and stirring was also evaluated. Divinylbenzene/carboxen/polydimethylsiloxane was selected as extraction fibre and was used to evaluate the influence of exposure time, extraction temperature and sample volume/total volume ratio (Vs/Vt) by means of a central composite design (CCD). The optimal conditions identified were 80 degrees C for extraction temperature, 55 min for extraction time and 6 mL of beer (Vs/Vt 0.30). Under optimal conditions, the proposed method showed satisfactory linearity (correlation coefficients between 0.993 and 0.999), precision (between 6.3% and 9.7%) and detection limits (lower than those previously reported for volatile phenols in beers). The method was applied successfully to the analysis of beer samples. To our knowledge, this is the first time that a HS-SPME based method has been developed to determine simultaneously these four volatile phenols in beers.

Three types of forest stands (chestnut coppice, maritime pine stands, and poplar and willow short-rotation woody crops (SRWC)) were evaluated to determine their potential for energy production. The properties of the main aboveground biomass fractions (wood, bark and crown) and also the whole tree were analysed, thus providing data that could be used for management purposes and for evaluating potential forest, biomass energy yields and atmospheric emissions. Proximate, elemental and energetic analyses of the biomass provided important information for evaluating the fuel potential. The energetic value of the biomass derived from the maritime pine stands was higher than that of the poplar and willow clonal stands and chestnut coppice stands. The high ash content of the chestnut bark, relative to that of the wood and crown material, is also an important consideration in relation to energy production. The proportion of carbon concentration accumulated per tree was very similar in all types of material studied, although the N and S contents were higher in the maritime pine stands than in the other stands. For this reason, selection of species and fractions can help to improve fuel quality and the efficiency of the combustion processes, and to minimize atmospheric emissions., This work was funded by the TRIBIONOR Project (Reference CTQ2013-45155-R) and the coal mining company HUNOSA GROUP supported by the HUNOSA CHAIR at the University of Oviedo (Project Reference SV-17-HUNOSA-1). The authors acknowledge the helpful co-operation of Hunosa staff in this study. The TRIBIONOR Project (CTQ2013-45155-R) is funded by the National Program for Research, Development and Innovation in Society Challenges, within the framework of the National Plan for Scientific and Technical Research and Innovation 2013–2016 from the State Research Agency (Ministry of Economy, Industry and Competitiveness), co-financed with FEDER Funds. The authors gratefully acknowledge the Government of the Principality of Asturias for supporting Ana Álvarez with a fellowship within the Severo Ochoa Program

A headspace solid-phase microextraction coupled to gas chromatography-tandem mass spectrometry (GC-MS/MS) method was optimised and validated for the determination of 4-ethylguaiacol, 4-ethylphenol, 4-vinylguaiacol and 4-vinylphenol, involved in the presence of Brett character, in ciders. The influence of different parameters on extraction efficiency (fibre coating, salt addition, exposure time, extraction temperature and sample volume/total volume ratio) was evaluated. Divinylbenzene/carboxen/PDMS was selected as extraction fibre and the other optimised parameters were as follows: 10 mL of cider, temperature 70 degrees C, extraction time 60 min and addition of 0.4 g/mL of NaCl. The proposed method showed satisfactory linearity. The detection limits obtained were 0.01 microg/L for 4-ethylguaiacol, 0.02 microg/L for 4-ethylphenol, 0.08 microg/L for 4-vinylguaiacol and 0.03 microg/L for 4-vinylphenol. These detection limits were lower than those obtained in previous studies on the determination of volatile phenols in other alcoholic beverages. Good recoveries of over 95% were observed for all compounds, and the repeatability obtained was considered acceptable, ranging between 4 and 10%. To demonstrate the feasibility of the procedure, the method was applied to the analysis of commercial ciders. To our knowledge, this is the first time that the headspace solid-phase microextraction procedure has been optimised to determine specifically the Brett character responsible compounds in cider.

A scale-up methodology was applied to the model previously developed for the industrial production of vinegar in an aerated-stirred pilot fermenter. The response surfaces generated by the model demonstrated that aerated mechanical power input, superficial air velocity, temperature, hydrostatic pressure and concentrations of compounds must be kept in the industrial-scale fermenters with the same geometry dimensions as the pilot fermenter. These variables maintain the values of kLa, C O 2 , L ∗ and OTRmax and asses the same effects of hydrodynamics and oxygen transfer, allowing the values of the process variables of the industrial-scale fermenters to be scaled down to the values of the pilot fermenter, which are required for applying the models. On these bases, a Simulation Environment for Acetification Processes (SEAP) was developed to design industrial processes on any scale and to predict the behaviour of fermentations and the costs of vinegar production. Finally, an example of the design and optimisation of a fermentation process with SEAP is reported, applying an optimisation methodology based on response surfaces and genetic algorithms using a desirability function as the response.

The binary diffusion coefficients of 2-ethyltoluene, 3-ethyltoluene, and 4-ethyltoluene in supercritical carbon dioxide were determined in a pressure range of (15.0 to 35.0) MPa at temperatures of (313, 323, and 333) K by means of the Taylor−Aris dispersion technique. The influence of pressure, temperature, density, and viscosity on the binary diffusion coefficients was examined, and some general trends were established. The experimental results were compared with the values estimated by several semiempirical equations based on the Stokes−Einstein formula and on the Rough−Hard−Sphere model.

The production of vinegar in an aerated-stirred reactor was modelled using a hybrid approach. The growth rate was modelled according to the total biomass specific growth rate, μ g ν , which represents the growth of an active biophase and the fraction of cells which are growing. A quadratic model based on the process variables, i.e. hydrostatic pressure, ethanol concentration, aeration, agitation and temperature, was developed for μ g ν and the substrate and product kinetics were related mechanistically to the growth rate, including the kinetics of acetoin and ethyl acetate production. This model was coupled with the models for oxygen transfer and gas–liquid transfer, reported in a previous study, and the prediction capacity of the system of equations was validated by simulating semi-continuous and continuous real processes developed in a pilot fermentor.

The measurement and correlation of the experimental binary diffusion coefficients of 2,3-dimethylaniline, 2,6-dimethylaniline, 2-methylanisole, 4-methylanisole and 3-nitrotoluene in supercritical carbon dioxide is reported. Results were obtained using the Taylor-Aris dispersion technique, at 313, 323, and 333 K, and in a pressure range from 15.0 to 35.0 MPa. The diffusivity experimental data were correlated with temperature, pressure and carbon dioxide density and viscosity. Moreover, the experimental results were compared with the values estimated by several semiempirical equations.

A robustness test of a solid-phase microextraction-based method optimised for the simultaneous determination of chloroanisoles and acetyl-chlorophenols implicated in the presence of corky taste in wine has been carried out using a hybrid experimental design. The influence of small changes around the nominal level of four factors (Vs/Vt ratio, extraction temperature, exposure time and sample incubation time) on the measured response were evaluated in order to indicate if the method is robust for the experimental range considered. Moreover, it was also necessary to identify the critical parameters in the validated model in order to keep them under strict control. Experimental design provides an effective approach for robustness testing as a part of the analytical method validation.

Binary diffusion coefficients at infinite dilution in supercritical carbon dioxide, DAB, were measured for five n-alkylbenzenes (n-butylbenzene, n-pentylbenzene, 1-phenylhexane, 1-phenyloctane, and 1-phenyldodecane) by means of the Taylor−Aris technique in a chromatographic apparatus from 313 to 333 K and from 15.0 to 35.0 MPa. The experimental results were correlated with temperature, pressure, solvent viscosity, and solvent density. In the case of temperature dependence, additional measurements were carried out for n-pentylbenzene from 308 to 398 K at 35.0 MPa. As the five solutes are similar molecules, the corresponding states principle of Teja was tested together with the results obtained from several predictive equations based on the Stokes−Einstein formula and on the rough-hard-sphere model.

A modification of an existing correlative equation for self-diffusion coefficients is presented. A free-volume theory for liquids has been corrected to reproduce diffusivities of hard-sphere and Lennard–Jones fluids from low-density limit to melting points, and has been applied to correlate a wide database of non-polar, polar, quantic and hydrogen-bonding substances, although it is unable to fit helium, water and hydrogen fluoride. The adjustable parameters are generalized with available fluid properties, and the three resulting predictive formulas present lower deviations than other correlative equations used in a predictive way for non-quantic and non-associated fluids.

The transfer of oxygen from aeration flow to the fermentation medium and the transfers of ethanol, ethyl acetate, acetoin, acetic acid and water from the fermentation medium to aeration flow were modelled for the industrial production of vinegar. The study was developed in a pilot fermentor, working with continuous processes and industrial fermentation mediums. The cores of the proposed models were the semi-empiric correlations for the volumetric transfer coefficients kLa for oxygen transfer and kA,Ga for the liquid–gas transfers. The main novelty was the introduction of the effect of pressure on the fermentation medium, together with the expression proposed for kA,Ga, with the same structure as the expression for kLa. A genetic algorithm was developed to calculate the parameters of the models, with a four composed desirability function as the evaluation function. The optimised sets of parameters provided models with good predictive ability. The models can be applied for any fermentor with the same agitation and aeration system design and the same geometry.