Repeatability and pattern recognition of bacterial fatty acid profiles generated by direct mass spectrometric analysis of in situ thermal hydrolysis/methylation of whole cells

Direct CI mass spectrometry profiling of fatty acid methyl esters (FAMEs) from in situ thermal hydrolysis/methylation (THM) of whole bacterial cells with tetramethylammonium hydroxide (TMAH) has been demonstrated as a potential method for real time and fieldable detection/identification of microorganisms. Bacillus anthracis (Ames), Yersinia pestis (Nair. Kenya), Vibrio cholerae (E1 Tor), Brucella melitensis (Abortus wild) and Francisella tularensis (LVS vaccine) were profiled by this method during a 10-month period. Repeatability of the in situ FAME data was calculated using one-way analysis of variance (ANOVA) and a t-test. Artificial neural network (ANN) and multivariate statistics of the FAME profiles were also compared for bacterial identification/classification. Equivalent results were obtained with a multivariate rule building expert system (MuRES) and the ANN. However, the ANN analysis required much less computer time and was deemed the best choice for this application. In situ THM FAME profiles of the bacterial samples provided comparable results with those obtained from the Microbial Identification System (MIDI) (Newark, DE) wet chemistry-gas chromatographic based system.     

Integrated multidimensional and comprehensive 2D GC analysis of fatty acid methyl esters

Fatty acid methyl ester (FAME) profiling in complex fish oil and milk fat samples was studied using integrated comprehensive 2D GC (GC × GC) and multidimensional GC (MDGC). Using GC × GC, FAME compounds – cis‐ and trans‐isomers, and essential fatty acid isomers – ranging from C18 to C22 in fish oil and C18 in milk fat were clearly displayed in contour plot format according to structural properties and patterns, further identified based on authentic standards. Incompletely resolved regions were subjected to MDGC, with Cn (n = 18, 20) zones transferred to a ²D column. Elution behavior of C18 FAME on various ²D column phases (ionic liquids IL111, IL100, IL76, and modified PEG) was evaluated. Individual isolated Cn zones demonstrated about four‐fold increased peak capacities. The IL100 provided superior separation, good peak shape, and utilization of elution space. For milk fat‐derived FAME, the ²D chromatogram revealed at least three peaks corresponding to C18:1, more than six peaks for cis/trans‐C18:2 isomers, and two peaks for C18:3. More than 17 peaks were obtained for the C20 region of fish oil‐derived FAMEs using MDGC, compared with ten peaks using GC × GC. The MDGC strategy is useful for improved FAME isomer separation and confirmation.     

Biofuels–Renewable Energy Sources: A Review

Biodiesel is biodegradable and nontoxic, and it significantly reduces toxic and other emissions when burned as a fuel. The advantages of biodiesel as diesel fuel are its portability, ready availability, renewability, higher combustion efficiency, non-toxicity, higher flash point, and lower sulfur and aromatic content, higher cetane number, and higher biodegradability. The major disadvantages of biodiesel are its higher viscosity, lower energy content, higher cloud point and pour point, higher nitrogen oxide (NO_x) emissions, lower engine speed and power, injector coking, engine compatibility, high price, and greater engine wear. The technical disadvantages of biodiesel/fossil diesel blends include problems with fuel freezing in cold weather, reduced energy density, and degradation of fuel under storage for prolonged periods. The sources of biodiesel are vegetable oils and fats. The direct use of vegetable oils and/or oil blends is generally considered to be unsatisfactory and impractical for both direct injection and indirect type diesel engines because of their high viscosities and low volatilities injector coking and trumpet formation on the injectors, higher level of carbon deposits, oil ring sticking, and thickening and gelling of the engine lubricant oil, acid composition. Biodiesel is obtained by transesterifying triglycerides with methanol. A popular variation of the batch transesterification process which needs high alcohol/acid ratio (several separation problems and high corrosivity and toxicity) is the use of continuous stirred tank reactors in series. This continuous process is heterogeneous and is based on reactive distillation. The key factor is the selection of the right and effective solid catalyst which leads to reduction of energy consumption and investments at all.     

Optimization of heterogeneous Catalyst-assisted fatty acid methyl esters biodiesel production from Soybean oil with different Machine learning methods

There is a growing attention to the bio and renewable energies due to fast depletion of fossil fuels as well as the global warming problem. Here, we developed a modeling and simulation method by means of artificial intelligence (AI) for prediction of the bioenergy production from vegetable bean oil. AI methods are well known for prediction of complex and nonlinear process. Three distinct Adaptive Boosted models including Huber regression, LASSO, and Support Vector Regression (SVR) as well as artificial neural network (ANN) were applied in this study to predict actual yield of Fatty acid methyl esters (FAME) production. All boosted utilizing the Adaptive boosting algorithm. The important influencing parameters on the biodiesel production such as the catalyst loading (CAO/Ag, wt%) and methanol to oil (Soybean oil) molar ratio were selected as the input variables of models while the yield of FAME production was selected as output. Model hyper-parameters were tuned to maintain generality while improving prediction accuracy. The models were evaluated using three distinct metrics Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R². Error rates of 8.16780E-01, 4.43895E-01, 2.06692E + 00, and 3.92713 E-01 were obtained with the MAE metric for boosted Huber, SVR, LASSO and ANN models. On the other hand, the RMSE error of these models were about 1.092E-02, 1.015E-02, 2.669E-02, and 1.01174E-02, respectively. Finally, the R-square score were calculated for boosted Huber, boosted SVR, and boosted LASSO as 0.976, 0.990, 0.872, and 0.99702, respectively. Therefore, it can be concluded that although the boosted SVR and ANN models were better models for prediction of process efficiency in terms of error, but all algorithms had high accuracy. The optimum yield of 83.77% and 81.60% for biodiesel production were observed at optimum operating values from boosted SVR and ANN models, respectively.     

Methods for extracting biochemical information from bacterial Raman spectra: focus on a group of structurally similar biomolecules--fatty acids

In this paper we explore the possibilities of Raman spectroscopy in order to deduce information on the fatty acid composition of bacterial cells. Therefore, representative strains of two bacterial taxa were each cultured in different conditions and in parallel analyzed by Raman spectroscopy and gaschromatographic FAME analysis. Raman spectra of pure fatty acids were recorded and used as reference spectra. The culturing conditions for each strain could be easily distinguished by the fatty acid information retrieved from bacterial Raman spectra. Chemometric techniques such as EMSC and PCA allowed to extract information about groups of fatty acids, that was consistent with the results from FAME analysis. Although the information retrieved from Raman spectroscopy is not as refined as that from FAME analysis, the presented methods could be useful to obtain basic information on the fatty acid present in bacteria when performing Raman spectroscopic analysis for fast whole cell profiling, which provides information for different types of cell components (fatty acids, amino acids, primary metabolites, etc.).     

Fatty Acid Methyl Esters as Biosolvents of Epoxy Resins: A Physicochemical Study

The C8 to C18 fatty acid methyl esters (FAME) have been compared as solvents for two epoxy resin pre-polymers, bisphenol A diglycidyl ether (DGEBA) and triglycidyl p-aminophenol ether (TGPA). It was found that the solubilization limits vary according to the ester and that methyl caprylate is the best solvent of both resins. To explain these solubility performances, physical and chemical properties of FAME were studied, such as the Hansen parameters, viscosity, binary diffusion coefficient and vaporization enthalpy. Determination of the physicochemical parameters of FAME was carried out by laboratory experimentations and by calculation from bibliographic data. The Hansen parameters of FAME and epoxy resins pre-polymers were theoretically and experimentally determined. The FAME chain length showed a long dependence on the binary diffusion parameters and kinematic viscosity, which are mass and momentum transport properties. Moreover, the vaporization enthalpy of these compounds was directly correlated with the solubilization limits.     

Densities of FAMEs or FAEEs with ethanol at temperatures from 283.15 to 318.15 K

Ethanol is usually considered as an additive to blend with biodiesels to improve its cold flow characteristics. The thermophysical properties of ethanol with biodiesels are therefore of interest in its applications. In the present work, the densities of ethanol with six components of biodiesel (including methyl caprate, methyl laurate, methyl myristate, ethyl caprylate, ethyl caprate and ethyl laurate) mixtures were measured from 283.15 to 318.15 K and at atmospheric pressure in the overall composition range. Redlich–Kister equation was used to correlate the excess molar volumes of the mixtures, which were calculated from the experimental densities. In addition, Apelblat’s equation was extended to correlate and predict the densities of the studied mixtures as a function of concentration and temperature.     

A review on enzyme and ultrasound: A controversial but fruitful relationship

A critical review on the effect of ultrasound (US) on enzymes and their biocatalytic action is presented here. Discussion on the information users of US acquire before utilizing the different devices, and the importance they give to US frequency is constant along the review. The authors have gone into the different areas in which the US–enzyme binomial has been applied. The lack of enough information on the US–enzyme-working conditions under which each piece of research has been developed, and the necessity to provide complete information on the data and metadata to give enough light on each piece of research (and thus on the potential comparison of results from different studies) are critically exposed. With this aim, the study has been divided into the positive effect of US on enzymes to favor the production of metabolites, polymers or proteins; and the degradation, inhibition or activation of the biocatalyst under US application. Also the effect of US on enzyme production and the main fields of application of the US–enzyme binomial are discussed.     

Comparative characterization of Jatropha,soybean and commercial biodiesel

Oil was extracted from seeds of Jatropha Curcas,in high yields(up to 40% by weight).The extracted Jatropha oil was converted in a laboratory reactor to biodiesel by transesterification.Analysis of Jatropha oil and Jatropha biodiesel by GC/MS and GC/SIMDIS showed that Jatropha oil could be readily converted to a biodiesel product through NaOH catalyzed transesterification.The resulting biodiesel has desirable properties such as high cetane number and low flash point,which are major improvements over the prop...     

A study of the low temperature autoignition of methyl esters

The autoignition of a series of C₄ to C₈ fatty acid methyl esters has been studied in a rapid compression machine in the low and intermediate temperature region (650-850 K) and at increasing pressures (4-20 bar). Methyl hexanoate was selected for a full investigation of the autoignition phenomenology, including the identification and determination of the intermediate products of low temperature oxidation. The oxidation scheme and overall reactivity of methyl hexanoate has been examined and compared to the reactivity of C₄ to C₇n-alkanes in the same experimental conditions to evaluate the impact of the ester function on the reactivity of the n-alkyl chain. The low temperature reactivity leading to the first stage of autoignition is similar to n-heptane. However, the negative temperature coefficient region is located at lower temperature than in the case of the n-alkanes of corresponding reactivity. An evaluation of the distribution of esteralkyl radicals R and esteralkylperoxy radicals ROO gives an insight into the main reaction pathways.