Determination of the Hydroxyl Value of Soybean Polyol by Attenuated Total Reflectance/Fourier Transform Infrared Spectroscopy

A rapid method for the quantitative determination of the hydroxyl value (OHV) of hydroxylated soybean oils by HATR/FTIR spectroscopy is described. Calibration standards were prepared by the formic acid/hydrogen peroxide method and OH values were determined by the official method of AOCS Tx 1a-66, covering an analytical range of 3.5–125 mg of KOH/g of sample. A partial least squares (PLS) calibration model for the prediction of the hydroxyl value (OHV) was developed based on eight different spectral subregions between 3,150 and 990 cm⁻¹ and combinations of them. On average, 36 samples were used for the modeling and 17 were used for external validation. The resulting calibration was linear over the analytical range and had a standard deviation of 2.334. Validation of the method was carried out by comparing the OHV of a series of hydroxylated soybean oils predicted by the PLS model to the values obtained by the AOCS standard method. A correlation coefficient of R ² = 0.9843 and RMSEC and RMSEP values of, respectively, 3.393 and 3.643 were obtained. After the calibration of the spectrometer, the OHV could be obtained in 2–3 min per sample, a major improvement over conventional wet chemical methods. The advantages of these methodologies are that they do not destroy the sample, have a lower cost, expedite the analysis and do not produce residues. Therefore, they may yield excellent results when used to quantify OHV of soybean polyols obtained by hydroxylation reaction.     

偏最小二乘-近红外光谱测定抚顺石油二厂汽油辛烷值

对来自抚顺石油二厂的汽油样品进行近红外光谱分析,使用偏最小二乘算法建立近红外谱图与辛烷值的关联模型.检测表明,用近红外光谱检测石油二厂汽油样品辛烷值的误差在标准方法规定的再现性要求之内,证明了用近红外光谱技术分析石油二厂汽油辛烷值的可行性.     

气相色谱法测定分子筛生产循环废水中的三乙胺及杂质含量

采用气相色谱-质谱仪对晶化母液处理回收工艺流程中的三乙胺及杂质含量进行了定性分析,确定了三乙胺的杂质种类,为建立气相色谱分析方法确立了目标组分。在筛选色谱柱和优化色谱条件的基础上,选用十六烷醇柱CP7448(0.32 mm×60 m×0.5μm),TCD检测器,测定回用三乙胺产品的纯度和杂质含量,实验结果表明,目标组分分离效果良好。以校正面积归一法对三乙胺及杂质的质量分数进行定量,各组分重复测定5次的相对标准偏差均小于1.8%,回收率在98.5%~103.0%之间,表明方法的精密度和准确度良好,并具有快速、可靠的特点。     

Raman and IR studies of surface metal oxide species on oxide supports: Supported metal oxide catalysts

Raman and infrared spectroscopy provide complementary information about the nature of the surface metal oxide species present in supported metal oxide catalysts. This paper reviews the type of fundamental information that is typically obtained in Raman and IR characterization studies of supported metal oxide catalysts. The molecular structures of the surface metal oxide species are reflected in the terminal M=O and bridging M-O-M vibrations. The location of the surface metal oxide species on the oxide supports is determined by directly monitoring the specific surface hydroxyls of the support that are being titrated. The surface coverage of the surface metal oxide species on the oxide supports can be quantitatively obtained since at monolayer coverage all the reactive surface hydroxyls are titrated and additional metal oxide results in the formation of crystalline metal oxide particles. The nature of surface Lewis and Brønsted acid sites present in supported metal oxide catalysts are determined by adsorbing basic probe molecules like pyridine. Information about the behavior of the surface metal oxide species during catalytic reactions are provided by in situ characterization studies. Such fundamental information is critical for the development of molecular structure-reactivity relationships for supported metal oxide catalysts. This paper will be limited to supported metal oxide catalysts containing group V-VII transition metal oxides (e.g., V, Nb, Cr, Mo, W and Re) on several different oxide supports (alumina, titania, zirconia, niobia and silica).     

Quantitative Monitoring of the Amidation Reaction Between Coconut Oil and Diethanolamine by Attenuated Total Reflectance Fourier Transform Infrared Spectrometry

An analytical procedure was developed to monitor the batch reaction of coconut oil and diethanolamine which also would determine the cocodiethanolamide (CDEA) content of the final product. The method was based on attenuated total reflectance Fourier transform infrared spectrometry utilizing partial least squares regression. The calibration was modeled in the 1,781–1,714 and 1,658–1,639 cm⁻¹ spectral regions for coconut oil and CDEA respectively. The models were then applied to predict the amidation process yield and to monitor the in situ kinetics of reactions between coconut oil and DEA. The root mean square error of prediction was 0.590 and 0.336 for coconut oil and CDEA respectively. The proposed method can also be successfully applied to the determination of purity in commercial grade CDEA samples and would give reliable results in comparison with the potentiometric titration reference method.

Rapid Determination of Free Fatty Acid in Extra Virgin Olive Oil by Raman Spectroscopy and Multivariate Analysis

We introduce a visible Raman spectroscopic method for determining the free fatty acid (FFA) content of extra virgin olive oil with the aid of multivariate analysis. Oleic acid was used to increase the FFA content in extra virgin olive oil up to 0.80% in order to extend the calibration span. For calibration purposes, titration was carried out to determine the concentration of FFA for the investigated oil samples. As calibration model for the FFA content (FFA%), a partial least squares (PLS) regression was applied. The accuracy of the Raman calibration model was estimated using the root mean square error (RMSE) of calibration and validation and the correlation coefficient (R ²) between actual and predicted values. The calibration curve of actual FFA% obtained by titration versus predicted values based on Raman spectra was established for different spectral regions. The spectral window (945–1600 cm⁻¹), which includes carotenoid bands, was found to be a useful fingerprint region being statistically significant for the prediction of the FFA%. High R ² and small RMSE values for calibration and validation could be obtained, respectively.     

A rapid method for the analysis of hydrogenated fats by GC with IR detection

A rapid method for analysis of trans and cis FA in hydrogenated fats has been developed. The method is based on a single anlaysis by CG with IR detection. Multivariate partial least squares regression is applied on the IR spectra to predict the number of cis and trans double bonds. For each chain length the method provides information about the amount of the saturated FA, the amount of trans monoenes, the amount of cis monoenes, the amount of PUFA, and the average number of cis and trans double bonds in PUFA. The method has been validated by summing the values to a total trans value and total unsaturation. These sum values were compared with total trans unsaturation, as determined by AOCS method Cd 14-95, and iodine value, as determined by AOCS Cd 1d-92.     

Development of a Measuring Method for the Determination of Bisulfite and Sulfite in Seawater

In conventional reverse osmosis processes for seawater desalination, a disinfection of the process stream with chlorine compounds is carried out for antifouling. After disinfection the reduction agent Na₂S₂O₅ is used for the removal of residual chlorine in a strongly overstoichiometric way in order to protect the membranes from oxidational damages. To save chemicals a controlled dosing of Na₂S₂O₅ based on a reliable concentration measurement is desirable. Therefore, a measuring method for the determination of the sulfur(IV) components bisulfite and sulfite in seawater is developed based on the combination of UV spectroscopy and a PLS regression method. Experimental results as well as the development of the regression model for sulfur species in ultrapure and seawater is described.     

近红外光谱结合化学计量学方法快速鉴别一种汞污染植物

结合红外光谱法和化学计量学,建立汞污染植物千里光和未受污染千里光的快速鉴别模型,并考察其作为筛查土壤汞污染替代指标的可行性。分别在铜仁市汞矿周边和远离汞矿地区对千里光进行代表性采样,以ICP-AES对千里光汞含量进行分析。根据千里光粉末的漫反射红外光谱数据,建立化学计量学分类模型,对不同汞含量的千里光进行快速鉴别。ICP-AES结果表明,汞矿周边和远离汞矿地区的千里光中汞元素的差别显著,分别为0~0.2和10.0~19.7 mg/kg。基于原始近红外光谱、二阶导数光谱和标准正态变换(SNV)光谱的偏最小二乘判别分析(PLSDA)模型对两组千里光样品的预测准确率分别为0.886、0.943和0.900。近红外二阶导数光谱结合化学计量学建模可快速准确识别千里光的汞含量水平。该方法快速经济,可为土壤汞污染快速筛查提供一种替代指标。     

Detection of Extra Virgin Olive Oil Adulteration With Edible Oils Using Front‐Face Fluorescence and Visible Spectroscopies

Synchronous front‐face fluorescence and visible spectroscopies are utilized for the simple, rapid, and nondestructive quantification of extra virgin olive oil (EVOO) adulteration with corn, soybean, and sunflower oils. For each adulterant, 42 adulterated EVOO samples in the adulterant amount in the range 1.0–50 g/100 g were prepared. The partial‐least‐squares regression was executed for quantification. Both full (leave‐one‐out) cross‐validation and external validation were performed to evaluate the predictive ability. The plots of observed vs. predicted values exhibit high linearity. The coefficient of determination (R²) values are larger than 0.99. The root mean square errors of both cross‐validation and prediction are no more than 2%. The detection limits for the three seed oils using fluorescence and visible spectroscopies are in the range of 1.5–2.2% and 1.8–2.4%, respectively. The merit of this method is that both the front‐face fluorescence and visible spectroscopies are recorded toward neat oils, avoiding any sample pretreatment including dilution.     

A New Strategy for Quantitative Proportions in Complex Systems of Blended Oils by Triacyglycerols and Chemometrics Tools

Many oils sold in China and India are a blend of various oils to improve performance, stability, and nutritional characteristics, which are required in their respective markets. Quantitative analysis of the proportions of constitutive components is fundamental to the conformity and adulteration checking of edible blended oil products. A multi linear regression model with constrained linear least squares and exhaustion calculation was applied in this study. The source of the varieties in the model is a database (614 pure oils) of triacylglycerols (TAGs) collected by GC–FID and HPLC–RID. There were 20 groups of binary and ternary blended oils consisting of two or three oils out of five kinds, namely soybean, corn, peanut, rapeseed, and sunflower, which were analyzed and processed separately. Results showed that the method was able to predict the proportions of constitutive components in the edible blended oils, given that relative errors required less than 20%, the accuracy was 98.2% for the binary system if the proportion of each oil in blended oils was more than 20%, while the accuracy was 84.7% for the ternary system if the proportion of each oil in blended oils was more than 10%. The quantitative method is based on a simple analysis to determine the TAGs composition and thus it is useful for quick segregation and quality control of blended oils in routine analysis.     

The prediction of fatty acid structure from selected ions in electron impact mass spectra of fatty acid methyl esters

The possibility of fatty acid identification from ions in the mass region of 50–110 amu in electron impact mass spectra has been studied by application of various multivariate techniques. The focus has mainly been on the prediction of the number of double bonds in methylene‐interrupted polyunsaturated fatty acids isolated from marine lipids. The number of double bonds in these fatty acids could be predicted with high accuracy, both by partial least squares regression on all ions in this region, and by multiple linear regressions on selected subsets of 5–6 ions. The subsets with optimal predictive power have been found, and the ability to distinguish between methylene interrupted polyunsaturated fatty acids and other fatty acids have also been evaluated.     

Prediction of properties of diesel/biodiesel blends by infrared spectroscopy and multivariate calibration

Partial least squares models (PLS) using near and middle infrared spectrometry were developed to predict quality parameters of diesel/biodiesel blends (density, sulphur content and distillation temperatures). Practical aspects are discussed, such as calibration set composition; model efficiency using different infrared regions and spectrometers; and the calibration transfer problem. The root mean square errors of prediction, employing both regions and equipment, were comparable with the reproducibility of the corresponding standard method for the properties investigated. Calibration transfer between the two instruments, using direct standardization (DS), yielded prediction errors comparable to those obtained with complete recalibration of the secondary instrument.     

Raman spectra of high‐density,low‐density,and linear low‐density polyethylene pellets and prediction of their physical properties by multivariate data analysis

Raman spectra have been measured for pellets of five samples of high‐density polyethylene (HDPE), seven samples of low‐density polyethylene (LDPE), and six samples of linear low‐density polyethylene (LLDPE). The obtained Raman spectra have been compared to find out characteristic Raman bands of HDPE, LDPE, and LLDPE. Principal component analysis (PCA) was applied to the Raman spectra in the 1600–650 cm^?1 region after multiplicative scatter correction (MSC) to discriminate the Raman spectra of the three different PE species. They are classified into three groups by a score plot of PCA factor 1 vs. 2. HDPE with high density and high crystallinity gives high scores on the factor 1 axis, while LDPE with low density and low crystallinity yields negative scores on the same axis. It seems that factor 1 reflects the density or crystallinity. A PC weight loadings plot for factor 1 shows six upward peaks corresponding to the bands arising from the crystalline parts or all‐trans ? (CH₂)_n? groups and seven downward peaks ascribed to the bands of the amorphous or anisotropic regions and those arising from the short branches. Partial least‐squares (PLS‐1) regression was applied to the Raman spectra after MSC to propose calibration models that predict the density, crystallinity, and melting points of the polyethylenes. The correlation coefficient was calculated to be 0.9941, 0.9800, and 0.9709 for the density, crystallinity, and melting point, respectively, and their root‐mean‐square error of cross validation (RMSECV) was found to be 0.0015, 3.3707, and 2.3745, respectively. The loadings plot of factor 2 for the prediction of melting point is largely different from those for the prediction of density and crystallinity. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 443–448, 2002     

便携式拉曼光谱仪内标法快速测定乙酸浓度

利用激光拉曼散射原理,研究得到乙酸的特征峰(892cm(-1)附近),以硝酸的特征峰为内标,建立了一种醋酸浓度测定的新方法.在醋酸浓度为1%～60%范围内,线性关系良好,线性方程为I=4.4886x+0.34312,相关系数r=0.9997.该方法加标回收率为96%～107%.对样品进行了测试,相对标准偏差分别为0.5...     

Rapid,Label-Free Prediction of Antibiotic Resistance in Salmonella typhimurium by Surface-Enhanced Raman Spectroscopy

The rapid identification of bacterial antibiotic susceptibility is pivotal to the rational administration of antibacterial drugs. In this study, cefotaxime (CTX)-derived resistance in Salmonella typhimurium (abbr. CTX^r-S. typhimurium) during 3 months of exposure was rapidly recorded using a portable Raman spectrometer. The molecular changes that occurred in the drug-resistant strains were sensitively monitored in whole cells by label-free surface-enhanced Raman scattering (SERS). Various degrees of resistant strains could be accurately discriminated by applying multivariate statistical analyses to bacterial SERS profiles. Minimum inhibitory concentration (MIC) values showed a positive linear correlation with the relative Raman intensities of I₉₉₀/I₁₃₄₈, and the R² reached 0.9962. The SERS results were consistent with the data obtained by MIC assays, mutant prevention concentration (MPC) determinations, and Kirby-Bauer antibiotic susceptibility tests (K-B tests). This preliminary proof-of-concept study indicates the high potential of the SERS method to supplement the time-consuming conventional method and help alleviate the challenges of antibiotic resistance in clinical therapy.     

Measurement of Disodium 5'‐Inosinate and Disodium 5'‐Guanylate in Aqueous Ethanol by Attenuated Total Reflection Ultraviolet Method

An online concentration monitoring method was established by using attenuated total reflection ultraviolet (ATR‐UV) coupled with a suitable partial least squares regression for a multi‐solute crystallization system, namely, disodium 5'‐inosinate (IMP) and disodium 5'‐guanylate (GMP) in aqueous ethanol. The results indicated that the established method accurately predicted the concentration of IMP and GMP in the solution. The solubility data was measured at various temperatures and ethanol/water mass ratios, and the experimental data was well correlated by applying the modified Apelblat equation and modified Jouyban‐Acree model. The implementation of cooling crystallization demonstrates that the developed calibration model is suitable for online concentration monitoring with reasonable accuracy and precision.     

近红外光谱法快速测定高含量精制甘油中的甘油含量

采用偏最小二乘法(PLS)建立了快速测定高含量精制甘油中甘油含量的近红外光谱校正模型,该模型主因子数为4,相关系数(R2)为99.12%,校正标准偏差(RMSECV)为0.027;以预测集对模型进行验证,结果表明,R2为99.17%,预测标准偏差(RMSEP)为0.023,对同一样品预测值的相对标准偏差(RSD)为0.04%。