Prediction of Inverted Cane Sugar Adulteration of Honey by Fourier Transform Infrared Spectroscopy

Fourier transform infrared (FTIR) spectroscopy with an attenuated total reflection (ATR) sampling accessory has been used to determine the cane medium invert sugar in 3 different varieties of honey. Predictive models were developed to classify the cane sugar-adulterated honey samples, using discriminant analysis. Linear discriminant and canonical variate analysis were used to discriminate adulterated honey samples. The optimum classification of 88 to 96.4% was achieved in a validation set, using linear discriminant analysis with the partial least squares (PLS) data compression technique. Calibrations developed to predict the spiked inverted cane sugar concentration in honey with PLS-1st derivative method gave standard error of prediction (SEP) between 2.8 to 3.6 % w/w.     

基于涂膜法FTIR的食用油羰基值快速检测

为了建立食用油羰基值快速检测方法,以菜籽油为实验材料,茴香醛为羰基标准物配制系列羰基值（0～60 mmol/kg）油样。用涂膜法采集油样光谱,建立羰基值与特征吸收峰1 703/1 570 cm－1处（1 703 cm－1处峰高两点基线均为1 570 cm－1,下同）吸光度的关系。然而,不同种类零羰基值的食用油在特征吸收峰1 703 cm－1处的吸收不相同而引起基底效应。因此,利用二维相关振动光谱技术寻找特征吸收峰的相关吸收峰,以校正食用油间的基底效应。结果表明：油样在1 703 cm－1处的吸光度与羰基值高度线性相关,利用相关吸收峰3 472 cm－1校正后的模型为y=0.005 4x＋0.090 9;相关系数（R）为0.991 9,标准偏差（s）为0.013 mmol/kg。模型预测值与国标法测定值高度线性相关,所得方程的斜率接近于1,R值均在0.99以上,两种方法测定结果十分接近。表明涂膜法傅里叶变换红外光谱检测食用油羰基值是可行的。     

蜂蜜中还原糖组分的近红外光谱应用研究

为探索快速测定还原糖含量的方法,提出了用傅立叶变换近红外光谱技术结合偏最小二乘法(PLS)建立近红外光谱与蜂蜜还原糖含量的数学模型并进行预测。通过光谱扫描还原糖含量在61.3%～75.22%范围的蜂蜜样本,选择11992.1～7494.6cm-1波数范围、二阶导数、及10个因子数进行光谱预处理,偏最小二乘法(PLS)交叉验证。结果表明,模型的校正决定系数(Rcal)、校正均方差(RMSEE)、交叉验证决定系数(RCV)、交叉验证均方差(RMSECV)分别为99.71%、0.27%、98.44%、0.45%。用该模型对验证集样本进行预测并统计分析,表明预测值与测定值无显著差异。因此,用该方法快速准确定量分析大批蜂蜜中的还原糖含量具有重要意义。     

基于FTIR技术快速测定食用油中叔丁基对苯醌含量的研究

研究了傅里叶红外光谱技术（FTIR）快速测定食用油中叔丁基对苯醌（TBBQ）含量的分析方法,系统地比较了FTIR结合朗伯比尔定律法及FTIR结合偏最小二乘法（PLS）的建模效果。结果表明,原始波谱经差谱和二阶导数预处理后在1 656 cm-1处采用朗伯比尔定律法建模,所得的线性回归方程为TBBQ（μg/mL）=1 089.5Abs-11.35,相关系数R2为0.998 1,15组煎炸油和10组市售食用油的外部验证实验的平均相对偏差分别仅为4.89%和6.80%。采用FTIR结合PLS法对原始波谱建模,建模区间为1 675~1 645 cm-1,模型相关系数R2为0.995 6,校正均方差为0.57,预测均方差为3.32,15组煎炸油和10组市售食用油的外部验证实验的平均相对偏差分别为8.53%和8.40%,说明基于FTIR的朗伯比尔定律法和PLS法均能有效测定食用油中TBBQ含量,其中朗伯比尔定律法预测准确度较高、模型稳定性更好。     

Rapid determination of tetracycline in milk by FT-MIR and FT-NIR spectroscopy

The feasibility of measuring tetracycline at the ppb levels in milk was investigated by Fourier transform mid-infrared (FT-MIR) and Fourier transform near-infrared (FT-NIR) spectroscopic techniques. Milk samples spiked with different concentrations of tetracycline were scanned using FT-MIR and FT-NIR spectroscopy. Suitable spectral wave number regions were selected for principal least square (PLS) regression models development. Prediction errors were high when the calibration model was developed using the wide range of tetracycline concentrations (4 to 2000 ppb) in milk. Maximum correlation coefficient (R2) value of about 0.89 was obtained for the validation models developed using different concentration ranges. Prediction errors were high for FT-NIR method. Results indicated that FT-MIR spectroscopy could be used for rapid detection of tetracycline hydrochloride residues in milk.     

FTIR spectroscopic characterization of soy proteins obtained through AOT reverse micelles

Fourier transform infrared (FTIR) method was used to study the conformations of soy protein obtained through aqueous solution and bis(2-ethylhexyl) sodium sulfosuccinate (AOT) reverse micelle extraction. The results showed that there were changes in signal intensity and/or position of IR bands at 4000–400 cm⁻¹ when the soy proteins were separated by two extraction methods. The FTIR spectral changes were subsequently assessed using the second derivative spectroscopy in the amide I region (1700–1600 cm⁻¹). The contents of α-helix, β-sheet, turn and irregular conformations for soy proteins using aqueous solution extraction were 11.6%, 32.8%, 44.3% and 11.3%, respectively; while using AOT reverse micelle extraction 13.1%, 41.6%, 32.5% and 12.9%, respectively. The amount change of these structures might affect functional properties of soy proteins.     

基于傅里叶变换红外光谱的食用油质量安全检测技术研究进展

为了进一步拓展傅里叶变换红外（Fourier transform infrared,FTIR）光谱技术在食用油分析和检测中的应 用范围,本文综述了近年来FTIR光谱技术在食用油品质分析和安全检测方面的研究进展。其中品质分析包括理化 指标（过氧化值、反式脂肪酸含量、游离脂肪酸含量、水分体积分数、碘值、羰基值及多指标分析和检测）和氧化 稳定性;安全检测即食用油真伪鉴别。通过对光谱采集、光谱范围选择、数据处理及基底效应消除等方面进行分析 和探讨,以期为FTIR光谱技术在食用油质量安全检测方面的进一步应用提供参考。     

Rapid Determination of Bitterness in Beer Using Fluorescence Spectroscopy and Chemometrics

Two fluorescence spectroscopic methods with the aim to develop a fast quantitative determination of bitterness in beer were tested. The first method was based on autofluorescence of the diluted and degassed beer samples without any further processing. A total of 21 dark and light beer samples were analyzed and multivariate Partial Least Squares (PLS) regression models to bitterness in form of international bitter units (IBU) were performed. A prediction error in the form of Root Mean Square Error of Cross‐Validation (RMSECV) of 2.77 IBU was obtained using six PLS components. Focusing only on the light beer samples the RMSECV was reduced to 1.81 IBU. The second method developed was based on addition of europium to induce delayed fluorescence signals in the beer samples. PLS models yielded an RMSECV of 2.65 IBU for all beers, while a model on the light beer samples gave an RMSECV of 1.75 IBU. The obtained prediction errors were compared to the errors given in the literature for the traditional extraction method of determining IBU.     

应用红外光谱结合化学计量学方法检测阿拉伯胶产地和蛋白质含量

研究利用傅里叶红外光谱结合化学计量学方法来实现对苏丹阿拉伯胶的产地和蛋白质含量的快速无损检测的可行性。采集自6?个不同的产地,每个产地12?个,总计72?个阿拉伯胶样本,作为研究对象,运用线性判别分析（linear discriminant analysis,LDA）和反向区间偏最小二乘（backward interval partial least squares,Bi-PLS）法分别实现对苏丹阿拉伯胶的产地区分和蛋白质含量检测。结果表明,当主成分数为6时,LDA对样本的训练集（48?个样本）和预测集（24?个样本）的识别率都为100%。Bi-PLS法回归联合20?个光谱子区间中的4?个子区间得到最佳的蛋白质预测模型,其预测集相关系数为0.937?3,均方根误差为0.173%。因此,利用傅里叶红外光谱结合化学计量学方法可实现对苏丹阿拉伯胶的产地以及蛋白质的含量的快速无损检测。     

近红外光谱协同BP神经网络的泰国茉莉香米掺伪含量快速鉴定

利用近红外光谱协同BP神经网络算法,对泰国茉莉香米及其掺伪样品的近红外光谱进行多元散射校正预处理,挑选出48个特征波长;以特征波长的吸光度为BP神经网络输入层神经元,以样品中泰国茉莉香米的含量为输出层神经元,获得BP神经网络算法的最优结构模型,即为单层隐含层、隐含层神经元数7、隐含层传递函数logsig、输出层传递函数...     

FTIR spectroscopic characterization of irradiated hazelnut (Corylus avellana L.)

Radiation induced molecular changes in macromolecular components of hazelnut tissues were investigated by mid-Fourier transform infrared (FTIR) spectroscopy. Irradiation dose of 1.5 kGy (low) and 10 kGy (high) were applied. The changes in frequency, signal intensity and intensity ratio of IR bands revealed that the unsaturated lipid concentration increased for low dose treated samples whereas it decreased and peroxidation appeared at high dose treatment. The low dose irradiation treatment, slightly increased the total lipid content whereas it dramatically decreased for high dose treatment. A slight increase in the lipid to protein ratio was observed for low dose treatment, whilst this ratio significantly decreased for high dose treatment. In addition, the high dose γ-irradiation caused alterations in the structure of hazelnut proteins, as cross-linking and aggregation occured in protein molecules. These results indicate that FTIR spectroscopy can be successfully used to monitor food irradiation.     

拉曼光谱技术快速检测专用煎炸油极性组分

为能够快速、无损检测专用煎炸油的极性组分含量,采集不同煎炸时间下煎炸油样本的拉曼光谱图.为建立稳定性高、误差小、精度高的模型,研究不同预处理方法对模型效果的影响,建立相应的偏最小二乘回归模型以选择最优的光谱预处理方法.结果 表明:标准正态变换处理后的偏最小二乘模型最优,预测均方根误差(root mean square ...     

近红外光谱技术快速测定鹅肉新鲜度

目的：应用近红外光谱技术快速检测鹅肉的新鲜度,评价指标包括总挥发性盐基氮和pH值。方法：采集完整冷鲜鹅肉的近红外光谱（950～1 650 nm）,光谱经多种校正预处理后,采用偏最小二乘法建立鹅肉新鲜度的定量预测数学模型。结果：对于这2 种指标均采用标准常态变量结合偏最小二乘法所建立模型的预测效果最好,总挥发性盐基氮和pH值定量校正数学模型的模型决定系数分别为0.727、0.991,内部交互验证均方根误差分别为3.666、0.028。用此模型对预测集20 个样品进行预测,预测值与实测值的相关系数分别达到0.976、0.705,预测值平均偏差分别为－0.240、－0.024,预测值和实测值之间没有显著性差异（P＞0.05）。结论：近红外光谱作为一种无损快速的检测方法,可用于评价鹅肉新鲜度。     

光谱预处理对太赫兹光谱预测猪肉K值的影响

采用太赫兹（terahertz,THz）光谱分析技术无损检测猪肉的新鲜度K值,但水会强烈吸收THz波,从而严重影响THz波对肉的检测。考察预处理方法对削弱水的干扰、提升THz光谱检测猪肉K值的模型性能的影响。分别采用多元散射校正、标准正态变量变换、一阶微分、二阶微分4?种预处理方法对衰减全反射光谱进行预处理,基于反向传播人工神经网络回归算法建立猪肉K值的THz光谱预测模型,比较研究4?种预处理方法后的模型预测精度。研究表明：一阶微分预处理方法效果最好,能够消除光谱基线漂移,提高光谱质量。与原始光谱相比,模型的预测集相关系数（Rp）从0.34提高到0.75,预测集均方根误差从20.24%降低到14.36%。因此,选择合适的光谱预处理技术对提高模型预测精度非常重要,采用一阶微分预处理后的THz光谱数据建立反向传播人工神经网络模型能够无损检测猪肉的新鲜度K值。     

Fast Discrimination of Apple Varieties Using Vis/NIR Spectroscopy

We evaluated the potential of visible/near-infrared (Vis/NIR) spectroscopy for its ability to nondestructively differentiate apple varieties. The apple varieties used in this research included, Fuji apples, Red Delicious apples, and Copefrut Royal Gala apples. The chemometrics procedures applied to the Vis/NIR data were principal component analysis (PCA), wavelet transform (WT), and artificial neural network (ANN). The apple varieties could be qualitatively discriminated in the PC1-PC2 space resulted from PCA. Wavelet transform was used as a tool for dimension reduction and noise removal, reducing spectral to wavelet components. Wavelet components were utilized as input for three-layer back propagation ANN model. WT-ANN model gave the highest level of correct classification (100%) of the apple varieties.     

Authentication of Olive Oil Adulterated with Vegetable Oils Using Fourier Transform Infrared Spectroscopy

Determination of the authenticity of extra virgin olive oils has become more important in recent years following some infamous adulteration and contamination scandals. The study focused on application of Fourier transform infrared spectroscopy to identify the adulteration of olive oils. Single-bounce attenuated total reflectance measurements were made on pure olive oil and olive oil samples adulterated with varying concentrations of sunflower oil (20-100 mL vegetable oil/L of olive oil). Discriminant analysis using 12 principal components was able to classify the samples as pure and adulterated olive oils based on their spectra. A partial least squares model was developed and used to verify the concentrations of the adulterant. Furthermore, the discriminant analysis method was used to classify olive oil samples as distinct from other vegetable oils based on their infrared spectra.     

近红外光谱法鉴别奶牛饲料中三聚氰胺甲醛树脂的可行性研究

收集国内常用的、具有代表性的奶牛精补料33个样品,制备99个三聚氰胺甲醛树脂(MF)掺假样品,在全光谱范围内进行近红外透反射光谱扫描,选择合适的前处理方法,采用BP神经网络方法和PLS-LDA方法分别建立判别模型。建立的BP神经网络判别分析模型的预测正确率为100%,建立的PLS-LDA判别分析模型的交互验证最低错误率为0.0778,模型错分率为0.0667,模型预测错误率为0.1429。说明利用近红外透反射光谱建立定性分析模型来检测奶牛饲料中是否掺有MF的研究是可行的。     

基于FTIR和~1H-NMR方法分析高压脉冲电场技术对抗氧化肽KWFH的结构影响

为了探究高压脉冲电场(pulsed electric field,PEF)提高抗氧化肽活性的机制,以抗氧化肽KWFH为实验材料,以1,1-二苯基-2-三硝基苯肼为衡量指标,通过双因素试验方案,考察电场强度和电场频率对其活性的影响。经过频率2 400 Hz、电场强度10 k V/cm的PEF处理,抗氧化肽KWFH活性提高了13.92%(P0.05)。借助傅里叶变换红外光谱(Fourier transform infrared spectroscopy,FTIR)、核磁共振氢谱(nuclear magnetic resonance,1H-NMR)、Zeta电位及圆二色谱技术,分析高压脉冲电场技术对其结构的影响。FTIR分析结果显示,经过PEF处理的样品羧酸羰基C=O和苯环吸收峰强度增强;经过1H-NMR分析,推测羧酸羰基C=O和苯环吸收强度变化引起官能团携带的氢质子变化。同时,经过PEF处理抗氧化肽KWFH的Zeta电位提高了8.70 m V(P0.05),进一步推测经过PEF处理,抗氧化肽KWFH结构更加无序,致使官能团暴露,吸收峰强度发生变化,引起肽活性改变。研究发现PEF处理对二级结构之间转化没有影响。这些研究为进一步探究PEF技术提高抗氧化肽活性机理提供了理论依据。     

Rapid Differentiation of Listeria monocytogenes Epidemic Clones III and IV and Their Intact Compared with Heat‐Killed Populations Using Fourier Transform Infrared Spectroscopy and Chemometrics

The objectives of this study were to determine if Fourier transform infrared (FT‐IR) spectroscopy and multivariate statistical analysis (chemometrics) could be used to rapidly differentiate epidemic clones (ECs) of Listeria monocytogenes, as well as their intact compared with heat‐killed populations. FT‐IR spectra were collected from dried thin smears on infrared slides prepared from aliquots of 10 μL of each L. monocytogenes ECs (ECIII: J1‐101 and R2‐499; ECIV: J1‐129 and J1‐220), and also from intact and heat‐killed cell populations of each EC strain using 250 scans at a resolution of 4 cm^?1 in the mid‐infrared region in a reflectance mode. Chemometric analysis of spectra involved the application of the multivariate discriminant method for canonical variate analysis (CVA) and linear discriminant analysis (LDA). CVA of the spectra in the wavelength region 4000 to 600 cm^?1 separated the EC strains while LDA resulted in a 100% accurate classification of all spectra in the data set. Further, CVA separated intact and heat‐killed cells of each EC strain and there was 100% accuracy in the classification of all spectra when LDA was applied. FT‐IR spectral wavenumbers 1650 to 1390 cm^?1 were used to separate heat‐killed and intact populations of L. monocytogenes. The FT‐IR spectroscopy method allowed discrimination between strains that belong to the same EC. FT‐IR is a highly discriminatory and reproducible method that can be used for the rapid subtyping of L. monocytogenes, as well as for the detection of live compared with dead populations of the organism.