Multivariate near infrared spectroscopy models for predicting the iodine value, CFPP, kinematic viscosity at 40 degrees C and density at 15 degrees C of biodiesel

Biodiesel is one of the main alternatives to fossil diesel. It is a non-toxic renewable resource, which leads to lower emissions of polluting gases. In fact, European governments are targeting the incorporation of 20% of biofuels in the fossil fuels until 2020.Chemically, biodiesel is a mixture of fatty acid methyl esters, derived from vegetable oils or animal fats, which is usually produced by a transesterification reaction, where the oils or fats react with an alcohol, in the presence of a catalyst. The European Standard (EN 14214) establishes 25 parameters that have to be analysed to certify biodiesel quality and the analytical methods that should be used to determine those properties.This work reports the use of near infrared (NIR) spectroscopy to determine some important biodiesel properties: the iodine value, the cold filter plugging point, the kinematic viscosity at 40 °C and the density at 15 °C. Principal component analysis was used to perform a qualitative analysis of the spectra and partial least squares regression to develop the calibration models between analytical and spectral data. The results support that NIR spectroscopy, in combination with multivariate calibration, is a promising technique applied to biodiesel quality control, in both laboratory and industrial-scale samples.     

Multivariate near infrared spectroscopy models for predicting methanol and water content in biodiesel

The transesterification of vegetable oils, animal fats or waste oils with an alcohol (such as methanol) in the presence of a homogeneous catalyst (sodium hydroxide or methoxyde) is commonly used to produce biodiesel. The quality control of the final product is an important issue and near infrared (NIR) spectroscopy recently appears as an appealing alternative to the conventional analytical methods. The use of NIR spectroscopy for this purpose first involves the development of calibration models to relate the near infrared spectrum of biodiesel with the analytical data. The type of pre-processing technique applied to the data prior to the development of calibration may greatly influence the performance of the model. This work analyses the effect of some commonly used pre-processing techniques applied prior to partial least squares (PLS) and principal components regressions (PCR) in the quality of the calibration models developed to relate the near infrared spectrum of biodiesel and its content of methanol and water. The results confirm the importance of testing various pre-processing techniques. For the water content, the smaller validation and prediction errors were obtained by a combination of a second order Savitsky-Golay derivative followed by mean centring prior to PLS and PCR, whereas for methanol calibration the best results were obtained with a first order Savitsky-Golay derivative plus mean centring followed by the orthogonal signal correction.     

Catalytic conversions in green aqueous media: Part 4. Selective hydrogenation of polyunsaturated methyl esters of vegetable oils for upgrading biodiesel

This study deals with the influence of operating parameters on the selective hydrogenation of crude polyunsaturated methyl esters of linseed, sunflower and soybean oils in order to achieve high selectivities up to 79.8 mol% of monounsaturated (C18:1) fatty acid methyl esters (FAME) which is 1st generation biodiesel of increased oxidative stability, energy and environmental performance at a low pour point employing water-soluble Rh/TPPTS catalytic complexes [TPPTS = P(C₆H₄-m-SO₃Na)₃] in green aqueous/organic two-phase systems. This study also discloses the great potential of biphasic selective catalytic hydrogenation to produce 2nd generation biodiesel from polyunsaturated FAME of alternative, non-food oil feedstocks which are originally not suitable for biodiesel production or give poor quality biodiesel but combine the advantage that they would not affect food production. Because the mixture of methyl esters of linseed oil mainly consists of C18:3 FAME it constitutes a good model to investigate the effects of parameters on the whole spectrum of the stepwise hydrogenation: C18:3 (linolenates) → C18:2 (linoleates) → C18:1 (oleates)  C18:0 (stearate) and to obtain first information on the selective hydrogenation of alternative, non-food oils with a high C18:3 FAME content to make them suitable for 2nd generation biodiesel formulations.     

Olive oil or lard?: Distinguishing plant oils from animal fats in the archeological record of the eastern Mediterranean using gas chromatography/combustion/isotope ratio mass spectrometry

Distinguishing animal fats from plant oils in archaeological residues is not straightforward. Characteristic plant sterols, such as β-sitosterol, are often missing in archaeological samples and specific biomarkers do not exist for most plant fats. Identification is usually based on a range of characteristics such as fatty acid ratios, all of which indicate that a plant oil may be present, none of which uniquely distinguish plant oils from other fats. Degradation and dissolution during burial alter fatty acid ratios and remove short-chain fatty acids, resulting in degraded plant oils with similar fatty acid profiles to other degraded fats. Compound-specific stable isotope analysis of δ(13)C(18:0) and δ(13)C(16:0), carried out by gas chromatography/combustion/isotope ratio mass spectrometry (GC/C/IRMS), has provided a means of distinguishing fish oils, dairy fats, ruminant and non-ruminant adipose fats, but plant oils are rarely included in these analyses. For modern plant oils where C(18:1) is abundant, δ(13)C(18:1) and δ(13)C(16:0) are usually measured. These results cannot be compared with archaeological data or data from other modern reference fats where δ(13)C(18:0) and δ(13)C(16:0) are measured, as C(18:0) and C(18:1) are formed by different processes resulting in different isotopic values. Eight samples of six modern plant oils were saponified, releasing sufficient C(18:0) to measure the isotopic values, which were plotted against δ(13)C(16:0). The isotopic values for these oils, with one exception, formed a tight cluster between ruminant and non-ruminant animal fats. This result complicates the interpretation of mixed fatty residues in geographical areas where both animal fats and plant oils were in use.     

Determination of methyl ester contents in biodiesel blends by FTIR-ATR and FTNIR spectroscopies

Partial last square regression (PLS) and artificial neural network (ANN) combined to FTIR-ATR and FTNIR spectroscopies have been used to design calibration models for the determination of methyl ester content (%, w/w) in biodiesel blends (methyl ester + diesel). Methyl esters were obtained by the methanolysis of soybean, babassu, dende, and soybean fried oils. Two sets of samples have been used: Group I, binary mixtures (diesel + one kind of methyl ester), corresponding to 96 biodiesel blends (0–100%, w/w), and Group II, quaternary mixtures (diesel + three types of methyl esters), corresponding to 60 biodiesel blends (0–100%, w/w). The PLS results have shown that the FTNIR model for Group I is more precise and accurate (±0.02 and ±0.06%, w/w). In the case of Group II the PLS models (FTIR-ATR and FTNIR) have shown the same accuracies, while the ANN/FTNIR models has presented better performance than the ANN/FTIR-ATR models. The best accuracy was achieved by the ANN/FTNIR model for diesel determination (0.14%, w/w) while the worthiest was that of dende ANN/FTIR-ATR model (0.6%, w/w). Precisions in Group II analysis ranged from 0.06 to 0.53% (w/w) and coefficients of variation were better than 3% indicating that these models are suitable for the determination of diesel–biodiesel blends composed of methyl esters derived from different vegetable oils.     

Determination of biodiesel content when blended with mineral diesel fuel using infrared spectroscopy and multivariate calibration

In this work, multivariable calibration models based on middle- and near-infrared spectroscopy were developed in order to determine the content of biodiesel in diesel fuel blends, considering the presence of raw vegetable oil. Soybean, castor and used frying oils and their corresponding esters were used to prepare the blends with conventional diesel. Results indicated that partial least squares (PLS) models based on MID or NIR infrared spectra were proven suitable as practical analytical methods for predicting biodiesel content in conventional diesel blends in the volume fraction range from 0% to 5%. PLS models were validated by independent prediction set and the RMSEPs were estimated as 0.25 and 0.18 (%, v/v). Linear correlations were observed for predicted vs. observed values plots with correlation coefficient (R) of 0.986 and 0.994 for the MID and NIR models, respectively. Additionally, principal component analysis (PCA) in the MID region 1700 to 1800 cm^− 1 was suitable for identifying raw vegetable oil contaminations and illegal blends of petrodiesel containing the raw vegetable oil instead of ester.     

The use of multivariate modelling of near infra-red spectra to predict the butter fat content of spreads

In order to obtain a rapid method that can detect adulteration of butter fats with cheaper vegetable fats, the use of NIR spectroscopy and multivariate modelling was explored. For model building and validation, an extensive set of samples was collected, consisting of 152 butter samples, 42 oils and 200 blends thereof. Variations in butter fat composition are reflected in distinct NIR spectral regions. Principal components analysis and partial least square discriminant analysis was used to inspect the variation within the sample set. As reference values for training partial least squares models, butter fat levels as declared by suppliers were taken, as well as C4:0 fatty acid levels as measured directly by GC. All samples were used for training, except for 100 blends, which were used later for validation. Different pre-processing and PLS approaches were explored, resulting in models that had a RMSEPs for butter fat and C4:0 fatty acid level in the range of 4.3-8.2 and 0.33-0.38% (w/w), respectively. The performance of NIR in assessment of C4:0 fatty acid levels is lower as for GC, but this disadvantage is outweighed by shorter measurement times and the lower skill levels required. Furthermore NIR is able to assess overall levels of butter fat, in addition to the indirect indicator provided by the C4:0 fatty acid level.     

Analysis of thermal,oxidative and cold flow properties of methyl and ethyl esters prepared from soybean and mustard oils

Oilseed crop with high oil content and promising ecological adaptability are potential sources for competitive biodiesel production. This study investigates the scope of utilizing biodiesel development through the methyl and ethyl ester from soybean and mustard oil as an alternative fuel. Methyl and ethyl esters of oils having different fatty acids compositions such as soybean (SOME and SOEE) and mustard oil (MUME and MUEE) were prepared by transesterification with methanol and ethanol in the presence of an alkali-KOH catalyst. The gas chromatographic (GC) analysis of oil samples revealed that primary fatty acid composition in soybean oil was linoleic acid (C_18:2, 51.93%), followed by oleic acid (C_18:1, 22.82%), palmitic acid (C_16:0, 11.56%), linolenic acid (C_18:3, 5.95%) and stearic acid (C_18:0, 4.32%). Whereas, the main components in mustard oil were erucic acid (C_22:1, 32.81%), oleic acid (C_18:1, 24.98%), eicosenoic acid (C_20:1, 10.44%), linolenic acid (C_18:3, 8.61%) and palmitic acid (C_16:0, 2.80%). The physicochemical properties (acid value, iodine value, calorific value, flash point, pour point etc.) of methyl and ethyl ester samples were estimated and found to be within the acceptable range of ASTM D6751 standards specifications. The prepared esters and oil samples were examined for cold flow properties by differential scanning calorimetry (DSC). Results revealed better cold flow properties for MUME (−2.55 °C) and MUEE (−3.10 °C) than SOME (3.21 °C) and SOEE (1.83 °C) due to more unsaturated fatty acid content in MU. Thermal and oxidative stability of samples was determined by thermogravimetric analysis (TG) and differential thermal analysis (DTA). The thermal and oxidative stability ranking of the samples was in the order of oil > methyl esters > ethyl esters.

     

Critical review on analytical methods for biodiesel characterization

Biodiesel is an alternative fuel composed of mono-alkyl esters and obtained mainly from the base-catalyzed transesterification reaction of oils or fats. Its use (pure or blended) does not demand any modification in the diesel engine and in the existing fuel distribution and storage infrastructure. Moreover, biodiesel has a high energetic yield, fixes the solar energy and contains insignificant amounts of sulphur. Therefore, biodiesel is currently the best substitute for fossil diesel fuel.Besides mono-alkyl esters, glycerol (main co-product), alcohol, catalyst, free fatty acids, tri-, di- and monoglycerides compose the final mixture of biodiesel production process. These and other kinds of contaminants can lead to severe operational and environmental problems. Therefore, the quality control of biodiesel is greatly significant to the success of its commercialization and market acceptance. Some important issues on the biodiesel quality control involve the monitoring of transesterification reaction, the quantification of mono-alkyl esters and free- and bonded glycerol as well as determination of residual catalysts and alcohol. Moreover, the determination of blend levels is another key aspect of biodiesel analyses. Chromatography and spectroscopy are the analytical methods most used for the biodiesel characterization, but procedures based on physical properties are also available.Previously, a review on analytical methods used to evaluate biodiesel quality was written by Knothe. Due to the importance of this field, we made an update of Knothes’ review. Therefore, in this paper, we will describe new developments in biodiesel analyses and some references showed in Knothes’ paper. Specially, we will describe analytical methods used for quantification of glycerol, mono-, di-, triglycerides, methanol, water, Na, K, P, and steroids in biodiesel or along the transesterification reaction. Also, the determination of biodiesel content in blends and some physicochemical parameters are discussed. At the end, we will assess the available techniques and point out some improvements on analytical methods for biodiesel characterization.     

Characterization of biodiesel and biodiesel blends using comprehensive two-dimensional gas chromatography

In this work the development of a comprehensive 2-D GC flame ionization detection (GC x GC FID) method for biodiesel fuels is reported. This method is used for the analysis of fatty acid methyl esters (FAMEs) in both biodiesel (B100) and biodiesel blend (B5) samples. The separation of FAME was based on component boiling point in the first dimension and polarity in the second dimension by using a BPX5/BP20 column set to provide a measure of 'orthogonality' in the 2-D space. Here the columns are coupled with a cryogenic modulator operating in a novel temperature programmed mode (T(M)) whereby the cryotrap is progressively incremented in temperature as the oven temperature is increased. The final method employs eight cryotrap temperature settings. The developed GC x GC method is able to successfully characterize and identify both B100 and B5 FAME components, which are produced from a variety of vegetable oils, animal fats and waste cooking oils, with high precision. The method is capable of analysing FAME with carbon numbers C4-C24, and is particularly suitable to characterize various types of biodiesel, making it possible to differentiate the origin and type of FAME used in the biodiesel samples.     

超高效液相色谱法测定生物柴油中的11种脂肪酸及脂肪酸甲酯

建立了采用超高效液相色谱(UPLC)-蒸发光散射检测器(ELSD)测定生物柴油中11种常见的脂肪酸及脂肪酸甲酯含量的方法。这11种常见的脂肪酸及脂肪酸甲酯为豆蔻酸、亚油酸、棕榈酸、油酸、亚麻酸甲酯、硬脂酸、亚油酸甲酯、棕榈酸甲酯、油酸甲酯、芥酸和硬脂酸甲酯。样品经提取后用甲醇溶解,采用Acquity UPLC BEH Phenyl C18柱(100 mm×2.1 mm,1.7 μm)分离,乙腈-水（体积比为3∶1)混合液为流动相进行等度洗脱,采用的ELSD条件为增益80,漂移管温度为45 ℃,载气压力为172 kPa,雾化器为冷却模式,并用外标法进行定量分析。结果表明,在一定的质量浓度范围内,峰面积的对数和质量浓度的对数线性关系良好。与其他检测生物柴油成分的方法相比,该方法简单,分离效果好,速度快,特别是此方法可以同时实现脂肪酸及脂肪酸甲酯的分离,并进行定量分析,能有效测定反应的进行程度,从而满足生物柴油工艺研究的需要。     

Quality control of pharmaceuticals with NIR: From lab to process line

This work describes a general framework for assessing the active pharmaceutical ingredient (API) and excipient concentrations simultaneously in pharmaceutical dosage forms based on laboratory-scale measurements. The work explores the comprehensive development of a near infrared (NIR) analytical protocol for the quantification of the API and excipients of a pharmaceutical formulation. The samples were based on a paracetamol (API) formulation with three excipients: microcrystalline cellulose, talc, and magnesium stearate. The developed method was based on laboratory-scale samples as calibration samples and pilot-scale samples (powders and tablets) as model test samples. Both types of samples were produced according to an experimental design. The samples were measured in reflectance mode in a Fourier-transform NIR spectrometer. Additionally, a new method for determining the minimum number of calibration samples was proposed. It was concluded that the use of laboratory-scale samples to construct the calibration set is an effective way to ensure the concentration variability in the development of calibration models for industrial applications. With this method, both API and excipients can be determined in high-throughput applications in the pharmaceutical industry.     

Evaluation of a rapid method for preparation of fatty acid methyl esters for analysis by gas-liquid chromatography

The major limitation to fatty acid analysis by gas-liquid chromatography is associated with preparation of fatty acid methyl esters (FAME). In the present study, FAME preparations were made from plant oils (corn, olive, sunflower), sunflower oil margarine, lard and various animal tissue fats by a rapid transesterification involving tetramethylammonium hydroxide in methanol, and also by a longer conventional saponification-esterification method. Fats from animal (beef, mutton, pork) adipose tissues were extracted by a simpler modified procedure and also by the Folch method prior to the rapid and the conventional FAME preparations, respectively. FAME analysis on a gas-liquid chromatograph equipped with a Silar 10C glass capillary column indicated similar fatty acid composition of a given fat or oil, whether FAME was prepared by the rapid or the longer conventional method. The data obtained by both methods were very highly correlated for all the fats (r = 0.9895 - 0.9999). However, the rapid method showed a tendency for enhanced recoveries of lower chain fatty acids (e.g. 14:0), and also of unsaturated C18 isomers. Possibly, losses of fatty acids that occurred during the lengthy fat extraction, fatty acid esterification or ether-evaporation FAME concentration steps (conventional method) were minimised by the single transesterification step (rapid method). This rapid transesterification method appears to be an attractive alternative to FAME preparation from a wide variety of different fats for gas-liquid chromatographic analysis.     

Enzymatic conversion of waste cooking oils into alternative fuel—Biodiesel

Production of biodiesel from pure oils through chemical conversion may not be applicable to waste oils/fats. Therefore, enzymatic conversion using immobilized lipase based on Rhizopus orzyae is considered in this article. This article studies this technological process, focusing on optimization of several process parameters, including the molar ratio of methanol to waste oils, biocatalyst load, and adding method, reaction temperature, and water content. The results indicate that methanol/oils ratio of 4, immobilized lipase/oils of 30 wt% and 40°C are suitable for waste oils under 1 atm. The irreversible inactivation of the lipase is presumed, and a stepwise addition of methanol to reduce inactivation of immobilized lipases is proposed. Under the optimum conditions the yield of methyl esters is around 88–90%.     

Response Factor Correction for Estimation of Ester Content in Biodiesel

EN 14103 is generally used for quantification of ester content in biodiesel free of heptadecanoate ester (C17:0) or methyl nonadecanoate (C19:0), which are employed as internal standards. It was observed that ester content obtained by EN 14103 method did not match with theoretical value of biodiesel, as the method did not take care of response factors of each component to compensate for changes in detector sensitivities. In this study, the whole range of fatty acid (C₆–C_24:1) methyl esters have been taken into consideration for the calculation of the ester content. Methyl nonadecanoate (C19:0) was used as an internal standard. The response factors of both the saturated and unsaturated methyl esters in the range C₆–C_24:1 were estimated and found in the range 0.97–1.16. The ester content was calculated after applying the response factors of each methyl ester. The results obtained by this method agreed well with the theoretical value as compared to estimated value using EN14103 method. The results obtained from this method also show good correlation (R ² = 0.98) with ¹H-NMR method. Further, this method does not depend on nature of biodiesel feed stock and is applicable to all methyl biodiesel samples obtained from different raw materials.     

Comparative study of oxidative stability of sunflower and cotton biodiesel through P-DSC

Biodiesel can contain unsaturated fatty acids, which are susceptible to oxidation, being able to change into polymerized compounds. Oxidative stability is very important in the quality control of oils and biodiesel. In this study, biodiesel samples were produced through the methyl route, using a homogeneous catalyst. The determination of methyl esters was performed by gas chromatography in order to confirm the conversion of the carboxylic acids present in the raw material for the methyl esters. Also proved the presence of methyl linoleate and methyl oleate to the major constituent of biodiesel. The thermal and oxidative stability of sunflower and cotton oils and their biodiesel, using TG and P-DSC techniques were investigated. The use of P-DSC to measure the oxidative induction time was very important. These measurements were used to evaluate the cotton and sunflower oils, and their respective biodiesel. It was found that the thermal-oxidative stability of vegetable oils and their biodiesel were similar, due to the fact that both presented chemical composition and percentages of fatty acids similar.     

气相色谱法在生物柴油生产工艺研究中的应用

综述了气相色谱法在生物柴油生产工艺研究中的应用,包括反应产物和生物柴油产品中脂肪酸甲酯含量和分布的测定,单脂肪酸甘油酯、二脂肪酸甘油酯和三脂肪酸甘油酯含量的测定,游离脂肪酸含量的测定以及微量甲醇含量的测定等。讨论了进样方式、色谱柱类型、硅烷化等因素对反应产物组成测定的影响;提出了一种采用双柱压力反吹的方式测定生物柴油产品中微量甲醇含量的方法：采用正丙醇作内标,甲醇与内标通过预切柱进入分析柱后,通过压力变化,将其余组分通过分流出口反吹出色谱系统;采用极性聚乙二醇色谱柱测定了8种不同植物油中脂肪酸甲酯的含量和分布。     

Study of the GC-MS determination of the palmitic-stearic acid ratio for the characterisation of drying oil in painting: La Encarnación by Alonso Cano as a case study

The correct identification of drying oils plays an essential role in providing an understanding of the conservation and deterioration of artistic materials in works of art. To this end, this work proposes the use of peak area ratios from fatty acids after ensuring that the linear responses of the detector are tested. A GC-MS method, previously reported in the literature, was revisited to its developed and validated in order to identify and quantify of eight fatty acids that are widely used as markers for drying oils in paintings, namely myristic acid (C(14:0)), palmitic acid (C(16:0)), stearic acid (C(18:0)), oleic acid (C(18:1)), linoleic acid (C(18:2)), suberic acid (2C(8)), azelaic acid, (2C(9)) and sebacic acid (2C(10)). The quaternary ammonium reagent m-(trifluoromethyl)phenyltrimethylammonium hydroxide (TMTFAH) was used for derivatization prior to GC-MS analysis of the oils. MS spectra were obtained for each methyl ester derivative of the fatty acids and the characteristic fragments were identified. The method was validated in terms of calibration functions, detection and quantification limits and reproducibility using the signal recorded in SIR mode, since two of the methyl derivatives were not totally separated in the chromatographic run. The proposed method was successfully applied to identify and characterise the most widely used drying oils (linseed oil, poppy seed oil and walnut oil) in the painting La Encarnación. This 17th century easel painting is located in the main chapel of the cathedral in Granada (Spain) and was painted by the well-known artist of the Spanish Golden Age, Alonso Cano (1601-1667).     

Gas-liquid chromatographic determination of fatty acid composition of cholesteryl esters in human serum using silica Sep-Pak cartridges

A simple and fast analytical procedure for separation and purification of cholesteryl esters of human serum is described. A single lipid extract, together with spiked cholesteryl pentadecanoate, as an internal standard, was passed through a Silica Sep-Pak cartridge. 1.5% diethyl ester in light petroleum was used to elute cholesteryl esters from the column. The separation was verified with thin-layer chromatography on silica gel using light petroleum-diethyl ether-glacial acetic acid (80:20:1) as a solvent. A very clean thin-layer chromatogram of cholesteryl esters without any additional spots of other lipids was obtained. The cholesteryl esters were quantitated by analyzing their fatty acid composition as methyl esters by gas-liquid chromatography. The coefficients of variation were 0.8--4.9% for the major fatty acids (C16:0, C16:1, C18:1, C18:2, C20:4) and 6.7--30.8% for the minor fatty acids (C18:0 and C20:0). The recoveries for cholesteryl palmitate, cholesteryl oleate and cholesteryl linoleate were 90.7, 92.3 and 91.0%, respectively.     

Chemometric Techniques Applied for Classification and Quantification of Binary Biodiesel/Diesel Blends

In this paper, three different types of biodiesel, which were synthesized from peanut, corn, and canola oils, were characterized by positive-ion electrospray ionization (ESI) and Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Different biodiesel/diesel blends containing 2–90% (V/V) of each biodiesel type were prepared and analyzed by near infrared spectroscopy (NIR). In the next step, the chemometric methods of hierarchical clusters analysis (HCA), principal component analysis (PCA), and support vector machines (SVM) were used for exploratory analysis of the different biodiesel samples, and the SVM was able to give the best classification results (correct classification of 50 peanut and 50 corn samples, and only one misclassification out of 49 canola samples). Then, partial least squares (PLS) and multivariate adaptive regression splines (MARS) models were evaluated for biodiesel quantification. Both methods were considered equivalent for quantification purposes based on the values smaller than 5% for the root mean square error of calibration (RMSEC) and root mean square of validation (RMSEP), as well as Pearson correlation coefficients of at least 0.969. The combination of NIR to the chemometric techniques of SVM and PLS/MARS was proven to be appropriate to classify and quantify biodiesel from different origins.