Quantitative analysis of quercetin using Raman spectroscopy

Raman spectroscopy was used for the quantitative analysis of quercetin. Raman spectra were measured with an Ar ion laser at 488 nm. A 20× objective lens was used for focusing the laser beam on the sample. The back scattering light was passed into the monochrometer and detected with a CCD detector. The Raman band of a solvent (ethanol and methanol) was used as the internal standard to remove the effect of factors such as laser power and other instrumental effect. The band ratio between the Raman intensity of the sample and that of the solvent had good linearity with the analyte concentration. The equations of the calibration curve were y = 9.005x with an R² of 0.9998 and y = 11.50x with R² of 0.9999 in ethanol and methanol, respectively. The limit of detection (LOD) was 5 × 10⁻⁵ mol/L. The quantity of quercetin extracted from onion peels was determined by Raman spectroscopy. Masses in quercetins of 73 mg/100 g and 70 mg/100 g were extracted from dried onion peels by using hot ethanol and hot methanol for three hours. These values are in good agreement with results obtained by HPLC and UV–vis spectroscopy.     

Improving the determination of moisture in edible oils by FTIR spectroscopy using acetonitrile extraction

A Fourier transform infrared (FTIR) method developed for the analysis of moisture in edible oils using dry acetonitrile as the extraction solvent was re-examined with the objective of improving its overall sensitivity and reproducibility. Quantitation was based on the H-O-H bending absorption at ～1630 cm(-1) instead of the bands in the OH stretching region, fewer interferences being an issue in the former as opposed to the latter region. In addition, a spectroscopic dilution correction procedure was developed to compensate for any miscibility of oil samples with acetonitrile, and gap-segment 2nd derivative spectra were employed to minimise the associated possibility of spectral interferences from absorptions of the oils. In comprehensive standard addition experiments using a variety of edible oils, the FTIR method was shown to recover the amounts of water quantitatively added to dry oil with an accuracy of ±20 ppm when the spectra of the acetonitrile extracts of the water-spiked oils were ratioed against the spectra of the acetonitrile extracts of the corresponding dry oils. The accuracy deteriorated substantially when the spectra of the acetonitrile extracts of the water-spiked oils were ratioed against the spectrum of the acetonitrile extraction solvent only. However, the primary variable affecting the apparent difference in the accuracy of the two approaches was determined to be the variability in the residual moisture content of the dried oils used in the standard addition experiments, as confirmed by an FTIR procedure based on H-D exchange with D(2)O. The FTIR method as structured is amenable to automation (>120 samples/h) and provides a very competitive means by which to routinely measure moisture present in a variety of hydrophobic materials that are normally the domain of Karl Fischer titration, such as edible oils, mineral oils, biodiesel and fuels.     

Infrared spectroscopy in the study of edible oils and fats

The use of infrared spectroscopy in the study of fats and oils is reviewed. The importance of the mid-infrared region in the study of lipids is shown. Differences between dispersive and Fourier-transform infrared techniques are commented on and the experimental methods used in the handling of oil and fat samples are reported. The assignment of oil and fat bands of mid-infrared spectra is made, and the usefulness of this technique to characterise oils and fats and to detect adulterations is reviewed. The application of spectroscopic data to determine the degree of unsaturation or iodine value, trans- double bonds content, free fatty acid content, average chain length or saponification number, solid fat content, as well as peroxide and anisidine values, is commented on. Also, the importance of this technique for monitoring oxidation processes is shown. © 1997 SCI.     

Application of Fourier transform infrared spectroscopy for the quality and safety analysis of fats and oils: A review

Abstract

Fats and oils are essential food components. Their quality and safety pose major concerns for consumers and food producers because of factors such as oxidation and rancidity, excessive levels of trans fatty acid (TFA), and widespread adulteration. Thus, a rapid and easy-to-use technique must be exploited for quality parameter evaluation and monitoring to ensure the edibility, safety, and quality of fats and oils. In the last decades, Fourier transform infrared (FTIR) spectroscopy has shown great potential in analyzing fats and oils given its speed and simplicity. FTIR-based analytical techniques for common intrinsic quality parameters, including peroxide value, free fatty acid, moisture, TFA, iodine value, as well as oxidation stability, adulteration, and classification of various fats and oils, are summarized in this review. The advantages and disadvantages of selected infrared spectral accessories and sample preparation and spectral processing methods are highlighted. The prospects and reformative aspects for future application of the FTIR technique in the field of fats and oils are also discussed. This review may serve as a basis for applying FTIR not only in future research but also in the fat and oil industries.     

近红外与表面增强拉曼光谱融合技术快速检测花生油中黄曲霉毒素B1

目的 在近红外光谱(near infrared spectroscopy, NIR)与表面增强拉曼光谱(surface-enhanced Raman spectroscopy, SERS)特征层数据融合的基础上构建偏最小二乘回归模型(partial least squares regression, PLSR)实现花生油中黄曲霉毒素B1 (aflatoxin B1, AFB1)含量的快速检测。方法 首先,分别采集待测样本的NIR与SERS光谱。其次,将采集的NIR与SERS光谱分别进行光谱预处理。然后,采用基于希尔伯特-施密特独立准则的变量空间迭代优化算法(Hilbert-Schmidt independence criterion based variable space iterative optimization, HSIC-VSIO)分别筛选NIR与SERS光谱的特征变量。最后,将筛选的特征变量进行融合并构建PLSR模型用于定量检测花生油中AFB1含量。结果 与NIR光谱数据、SERS光谱数据以及NIR与SERS光谱直接融合数据构建的PLSR模型相比,NIR与SERS光谱特征层融合数据构建的PLSR模型具有最佳的预测性能：校正集均方根误差(root mean squared error of calibration set, RMSEC)为0.1569,校正集决定系数(coefficient of determination of calibration set, )为0.9908,预测集均方根误差(root mean squared error of prediction set, RMSEP)为0.1827,预测集决定系数(coefficient of determination of prediction set, )为0.9854,性能偏差比(ratio of performance to deviation, RPD)为8.2761。将本方法与标准方法分别检测真实含有AFB1的花生油样本,结果表明两者的检测性能无显著性差异(P=0.84>0.05)。结论 本方法可实现花生油中AFB1含量的快速、高精度定量检测,也验证了NIR与SERS光谱融合的可行性与有效性。     

近红外光谱结合偏最小二乘法快速检测米糠油过氧化值和酸价

研究旨在建立近红外光谱法快速测定米糠油中过氧化值和酸价的方法。以化学滴定法测定米糠油中过氧化值和酸价为参比方法,采用近红外分析技术结合偏最小二乘法,建立了米糠油中过氧化值和酸价的近红外定量分析模型。过氧化值和酸价定量分析模型的决定系数分别为99.11%和99.72%,预测标准差分别为0.436 7%和0.044 78%,交叉验证标准差分别为0.452 2%和0.046 69%。利用78个验证集样品对定标模型进行外部独立验证,过氧化值及酸价的绝对误差分别在–0.78%～0.82%和–0.142%～0.139%之间,相对误差分别在–13.21%～14.44%和–14.85%～12.46%之间。表明所建立的定量分析模型及方法可对米糠油中过氧化值和酸价进行简便、快速测定。     

Investigation of the susceptibility of acid-deamidated wheat gluten to in vitro enzymatic hydrolysis using Raman spectra and free amino acid analysis

BACKGROUND: The number and surface nature of amino acids (AAs) in substrate proteins available to hydrolytic enzymes are critical. Among them, the micro‐environmental properties of specific AAs in substrates before hydrolysis would probably dominate the susceptibility of substrates to enzymatic hydrolysis. Fundamental knowledge concerning this regard is lacking. The objective of this work was to investigate the relationship between the exposure level of AAs in acid‐deamidated wheat gluten and their susceptibilities to in vitro enzymatic hydrolysis by pancreatin through both high‐performance liquid chromatography and Raman spectra. Wheat gluten deamidated with HCl (HDWG), citric acid (CDWG), succinic acid (SDWG) and acetic acid (ADWG) at the same degree of deamidation under the same heat treatment were chosen as the substrates. Substrate characterisations including degree of hydrolysis, surface hydrophobicity and structural characteristics before hydrolysis, together with analysis of free AAs of the corresponding hydrolysates during hydrolysis, were investigated. RESULTS: Hydrolysates from SDWG had the highest value for the degree of hydrolysis. The susceptibility of CDWG to pancreatin hydrolysis was the lowest, lower than native wheat gluten (CK) after the initial 36 h. Compared with free AAs, the mole increase profiles of CK, Arg production levelled off in HDWG after 12 h whereas it was inhibited in ADWG. For SDWG, Arg release was dramatically inhibited after 12 h and was replaced by Trp. Investigations using Raman spectra of the micro‐environment of Cys, Trp, Tyr and His and the mole increase trend of them indicated that the exposure level of these amino acids in substrates was positively related to their susceptibilities to pancreatin hydrolysis especially after 24 h of hydrolysis. CONCLUSION: Deamidation by four acids has a distinct influence on the structural characteristics of wheat gluten substrates. Although the substrates were selected at the same level of deamidation by the same heat treatment, their resultant conformational differences significantly influenced the exposure level of amino acids for binding to enzymes and the susceptibility of substrates to in vitro enzymatic hydrolysis. Therefore, it had an influence on changing enzyme cutting sites of pancreatin. This information will provide a better understanding of specific behaviour of AAs in wheat gluten during enzymatic hydrolysis from a new perspective. Copyright © 2012 Society of Chemical Industry     

基于检测概率模型的表面增强拉曼光谱法快速筛查果蔬中多菌灵残留

目的 建立一种水果蔬菜中多菌灵残留的表面增强拉曼光谱(SERS)快速筛查方法。方法 样品经乙醇提取、二氯甲烷净化、氮吹浓缩和乙醇溶液复溶四步获取待测液,通过单因素实验,优化金纳米粒子、提取液、萃取试剂及促凝剂的加入量,确定拉曼光谱仪的仪器测试条件。结果 多菌灵的拉曼特征位移为 630±5 cm^-1、728±5 cm^-1、1 002±5 cm^-1、1 224±5 cm^-1、1 264±5 cm^-1、1 316±5 cm^-1,根据其拉曼光谱特征峰及其强度,对多菌灵进行定性快速测定。结合检出概率模型(POD),确定出多菌灵在苹果、柑橘等水果中的检出限为 0. 5 mg/kg,在辣椒等蔬菜中的检出限为 1. 0 mg/kg。结论 本方法操作简单、快速准确,从样品前处理到结果显示仅需 40 min,结合使用 POD 模型,验证了该方法的有效性,可应用于水果蔬菜中多菌灵的现场快速检测。