漫反射红外光谱法结合PLS测定稻谷脂肪酸值研究

为了快速、简便、无污染地测定稻谷中脂肪酸含量,提出基于漫反射傅里叶变换红外光谱法(DRIFTS)和近红外漫反射光谱法(NIDRS)测定稻谷脂肪酸值快速检测方法。同时探讨了反向区间偏最小二乘法(BiPLS)对中红外光谱区域的优化效果。傅里叶变换原始光谱模型经7点平滑预处理及BiPLS优化,得到的最佳模型的R~2、RMSECV、RMSEP分别为0.998、3.65、3.69。近红外光谱经一阶导数和多元散射校正预处理后建立最佳模型,其R~2为0.97,RMSECV为3.43。在验证实验中,傅里叶变换红外光谱预测值与国标测定值的相对标准偏差为1.16%,近红外光谱预测值与国标测定值的相对标准偏差为1.70%。结果表明,DRIFTS能够更加准确检测脂肪酸值。     

衰减全反射傅里叶变换红外光谱(ATR-FTIR)技术测定油脂中反式脂肪酸

以反油酸甘油酯和棕榈酸甘油酯为标准,按试验设计要求,配制各种不同含量反式脂肪酸(0%～20%)的油脂用于分析.通过ATR-FTIR技术在三台不同的红外光谱仪上采集光谱,用负二阶导法(-2 D法)来分析光谱,在二阶导光谱图中,反式脂肪酸在966～963 cm-1峰高与反式脂肪的含量回归得到红外定标方程.用验证样品集对定标方程进行验证,获得验证相关系数为0.999 2,结果表明-2 D分析法在ATRFTIR技术测定油脂中反式脂肪酸是完全可行的,与传统的方法相比,无需相应的基准油脂作为参考,其在日常检测及在线检测反式脂肪酸含量应用前景十分广阔.     

基于负二阶导数红外光谱的反式脂肪酸的快速测定

建立了基于负二阶导数红外光谱的反式脂肪酸的快速测定方法。以三反油酸甘油酯和三油酸甘油酯混合标样系列为校正集,使用带有水平衰减全反射(HATR)附件的傅里叶变换红外光谱仪采集校正集样品在1 050～900 cm-1波段范围的吸收光谱,求二阶导数,乘以-10 000,得负二阶导数谱(-2D-HATR-FTIR)。以970～960 cm-1波段范围的最大峰高为X轴,以三反油酸甘油酯含量为Y轴,构建定标方程为Y=0.348 8X-0.918 5,相关系数0.999 5。在0.5%～60%范围,验证集样品反式脂肪酸含量预测值与实际指定值显著相关,验证相关系数0.999 0,相对残差的绝对值小于10%,表明方法定标模型预测性能良好。方法检测下限达0.5%,改善了现有红外光谱法的灵敏度,适用于较低含量反式脂肪酸的快速测定。     

基于水平衰减全反射傅里叶变换红外光谱的食品中反式脂肪酸的测定

目的:建立基于水平衰减全反射傅里叶变换红外光谱的食品中反式脂肪酸的快速测定方法.方法:负二阶导数水平衰减全反射傅里叶变换红外光谱法(-2D-HATR-FTIR).使用带有水平衰减全反射(HATR)附件的傅里叶变换红外光谱仪,采集三反油酸甘油酯标样在l 050～900 cm-1波段范围的吸收光谱,并求得负二阶导数谱.根据反式脂肪酸中孤立的反式双键在966 cm-1处的特征吸收与混合标样中反式脂肪酸的含量符合比尔定律的原理,构建定标方程.根据定标方程测定食品样品中反式脂肪酸含量.结果:在试验条件下,定标方程为Y=3 359.2X-0.6175,相关系数0.9997,检出限0.27％,回收率78.06％～112.65％.食品中反式脂肪酸含量最高接近50％.结论:建立一种新的快速测定食品中反式脂肪酸的方法,该法准确可靠,快速、简便,克服了现有红外光谱法灵敏度低的缺点,适用于食品中较低含量反式脂肪酸的快速测定.     

傅里叶变换衰减全反射红外光谱测定米粉中硒代胱氨酸的硒含量

利用傅里叶变换衰减全反射红外光谱(ATR-FTIR)法测定米粉中硒代胱氨酸的硒含量,以期探寻一种快捷、绿色环保且准确的硒含量测定方法。采用添加法制备样本,衰减全反射中红外光谱仪采集红外光谱,TQ Analyst分析软件作偏最小二乘法建模并验证,选择1 600～650 cm~(-1)作为样品的红外光谱分析波段,用导数对原始红外光谱处理,结果表明二阶导数处理后的模型,噪音小、失真少且预测效果更好,模型的决定系数(R■)都大于0.995、因子数为5～8、校正均方差(RMSEC)为1.17～2.68,验证均方差(RMSEP)为4.053 0～6.234 6验证集预测值相对偏差在20%以内的占87.95%,含量在18μg/100 g以上更是占了96.75%,含量在50μg/100 g(不含)以上的样品93.33%偏差在10%以内,预测效果较准确。     

傅里叶红外光谱法油脂定量分析研究进展

论述了傅里叶红外光谱法油脂定量分析基本原理、优越性以及在油脂过氧化值、游离脂肪酸、反式脂肪酸、碘值、皂化值、顺式和反式脂肪酸和固体脂肪含量等方面应用研究进展.同时,对傅里叶光谱法分析模型的稳定性和传递性及其在自动化分析中应用进行探讨,以期为傅里叶光谱法油脂自动分析检测提供参考.     

红外光谱结合偏最小二乘法快速检测油茶籽油脂肪酸组成的模型建立与评价北大核心CSCD

为建立快速检测油茶籽油中脂肪酸组成的方法,利用傅里叶红外光谱仪扫描86个油茶籽油样品,红外光谱数据分别通过Savitzky-Golay平滑(SG)、多元散射校正(MSC)、标准正态变换(SNV)、一阶导数(FD)和二阶导数(SD)等5种方法进行降噪处理,然后以气相色谱测定的脂肪酸组成作为标准值,采用全波长偏最小二乘法(PLS)、区间偏最小二乘法(iPLS)和联合区间偏最小二乘法(siPLS)分别构建油茶籽油中主要脂肪酸(油酸、棕榈酸、亚油酸)的定量回归模型。结果表明:油酸、棕榈酸、亚油酸的红外光谱数据预处理分别以SG、SNV、SD较好;siPLS通过有效波段的选择可去掉更多的噪声,比PLS和iPLS建立的模型精确度高,油酸、棕榈酸、亚油酸的校正集和预测集的相关系数(R)分别为0.9479和0.8539、0.9008和0.9101、0.9793和0.9505。红外光谱结合siPLS更适用于油茶籽油脂肪酸组成的快速测定。     

轻涂纸涂层中羧基丁苯胶乳含量的测定

采用衰减全反射傅里叶变换红外光谱(ATR-FTIR)对涂有不同羧基丁苯胶乳含量的轻涂纸表面进行测定,选取羧基丁苯胶乳在波数为2922 cm-1、1028 cm-1、756 cm-和699 cm-1 4处特征吸收峰并使用红外光谱软件计算其峰面积,由此得到不同胶乳含量与这4处吸收峰峰面积之间的关系;分别采用多项式曲线拟合(PCF)、偏最小二乘回归(PLS regression)和广义回归神经网络(GRNN)进行建模,并对3种模型的预测效果进行比较.结果表明,轻涂纸涂层中的ATR-FTIR信息可以用来测定轻涂纸涂层中的羧基丁苯胶乳含量,3种预测模型中,GRNN方法具有最佳的预测效果,偏差最小(最大偏差为-3.39％).     

食品中反式脂肪酸的研究进展

综述了反式脂肪酸的定义、来源及对人体的危害,详细介绍了红外光谱法、色谱法、气相色谱-质谱法等反式脂肪酸含量的检测方法,并从氢化技术、油脂精炼技术、交酯化反应及基因改良技术等方面介绍了减少油脂加工中反式脂肪酸产生的措施。     

近红外光谱结合不同偏最小二乘法无损检测食醋中总酸含量

探讨了快速、无损检测食醋中总酸含量的建模方法,利用近红外光谱法分别结合间隔偏最小二乘法(iPLS)、反向区间偏最小二乘法(BiPLS)、联合间隔偏最小二乘算法(SiPLS)进行建模,对各算法在不同划分区间数及区间选择时对建立模型的影响进行比较.结果表明:BiPLS、SiPLS(2,3,4区间联合)建模效果较好于iPLS所建立的模型,其中BiPLS在选择43个子区间,5个子区间联合(3,4,6,7,16)最佳,其RMSECV和RMSEP分别为0.2876和0.2726,校正集和预测集相关系数分别为0.9343和0.938;SiPLS在选择3个区间联合,49个区间数(3、5、7区间联合)最佳,其RMSECV和RMSEP分别为0.2607和0.2802,校正集和预测集相关系数分别为0.9463和0.9371;iPLS在选择22个子区间,第三个子区间,主因子数为4时最佳,其RMSECV和RMSEP分别为0.2998和0.2977,校正集和预测集相关系数分别为0.928和0.9213.不同偏最小二乘算法所选取区域大多集中于5500～6000 cm-1范围内,证明该波数范围应该是总酸的相应特征区间.     

Evaluation of Fatty Acid Profile of Wagyu Beef by ATR-FTIR Spectroscopy

Japanese black Wagyu beef has its characteristics of fatty well-marbled texture, flavor, and tenderness which are affected by fatty acid composition. The aim of this study was to develop an analytical method for evaluating the fatty acid profile of Wagyu beef by Fourier transform infrared (FTIR) spectroscopy. In the current study, attenuated total reflection–FTIR (ATR-FTIR) spectroscopy and gas chromatography (GC) were applied to the fat tissues, and the solvent-extracted fats which were sampled from subcutaneous, inter- and intramuscular fat tissues. Results of GC analysis showed that monounsaturated fatty acids (MUFA) content became larger in the order of intramuscular, intermuscular, and subcutaneous fats, and saturated fatty acids (SFA) became smaller in the same order. Subcutaneous fat could be discriminated from inter- and intramuscular fats on the basis of fatty acid composition by principal component analysis. The ATR-FTIR analysis revealed that the shift of the peak positions of alkene C–H stretching vibration at around 3,006 cm⁻¹ occurred depending on the unsaturation degree of fatty acids in beef fat. Partial least squares (PLS) regression analysis with leave-one-out cross-validation was applied to the combined regions of 2,800–3,050 and 1,000–1,500 cm⁻¹ for the fat tissues and the extracted fats. The correlation coefficients of the PLS validation models predicting the content of the MUFA and SFA for solvent-extracted fats were higher than those for fat tissues, and the coefficients (R ²) of determination more than 0.873 were obtained for solvent-extracted fats and 0.522 for fat tissues.     

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。     

二阶导数傅里叶变换红外光谱鉴别植物油和地沟油

利用傅里叶变换红外光谱法测定了食用植物油、地沟油和模拟的复热油的光谱并进行二阶导数处理分析。结果表明:地沟油和模拟的复热油的饱和脂肪酸、反式脂肪酸的含量均明显高于正常食用油的;二阶导数光谱中3 009、1 737、966、723 cm~(-1)4处特征吸收峰的变化可作为判定是否为地沟油的参考。用此方法鉴别油品用量少且无需样品预处理,分析速度快,可为地沟油检测方法的建立提供依据。     

基于傅里叶变换红外光谱的大豆原油掺伪定量 分析模型研究

目的应用傅里叶变换红外光谱(FTIR)结合最小偏二乘法(PLS)建立大豆原油-棕榈油二元掺伪体系的定量分析模型。方法以42个大豆原油、21个精炼油、88个掺伪油的FIIR谱图为模型样本,预处理方法选用标准正态变量(SNV),在此基础上应用主成分分析(PCA)提取特征变量,随机选取60个掺伪油样组成校正集,28个掺伪油样组成验证集,以PLS方法建立大豆原油的掺伪定量模型。结果 PCA可将大豆原油及精炼油分成独立的2类。经PCA分析,大豆原油中掺入棕榈油的掺伪检测限为5%。PLS校正模型的判定系数R2为0.9926,校正误差均方根RMSEC为1.8121。预测模型的R2为0.9823,交叉验证误差均方根RMSECV为2.8189。同时得到的预测结果的偏差在1.3909%~3.1019%之间,差异不显著,说明此模型可行。结论 FTIR-PLS模型能够实现大豆原油的掺伪定量分析,分析速度快,能够满足大豆原油入库要求,是一种可行的大豆原油掺伪分析方法。     

Evaluation of the quality of deep frying oils with Fourier transform near-infrared and mid-infrared spectroscopy

Deep frying oils are subjected to high temperature and prolonged heating that may lead to a series of quality and safety problems for fried foods. This study evaluated the quality of deep frying oils collected from a local college canteen (n = 132) with Fourier transform mid-infrared (FT-IR) and Fourier transform near-infrared (FT-NIR) spectroscopy. Partial least squares (PLS) regression was used to correlate spectral data with free fatty acids (FFA) and peroxide (PO) values of frying oils. The coefficient of determination (R(2)), standard error of prediction (SEP), and the RPD (ratio of the standard deviation of data set to the SEP) were used as indicators for the predictability of the PLS models. The FT-IR and FT-NIR methods exhibited similar predictability for the FFA values (FT-IR: R(2) = 0.954, SEP = 0.14, RPD = 4.48; FT-NIR: R(2) = 0.948, SEP = 0.14, RPD = 4.38). Although the predictability of the FT-IR method for the PO values was not as satisfactory as that of the FT-NIR method (FT-IR: R(2) = 0.893, SEP = 6.17, RPD = 2.93; FT-NIR: R(2) = 0.953, SEP = 4.15, RPD = 4.36), both FT-IR and FT-NIR methods could be used as simple and rapid approaches to determining the quality of deep frying oils.     

Quantitative determination of fatty acid compositions in micro-encapsulated fish-oil supplements using Fourier transform infrared (FTIR) spectroscopy

The research describes a rapid method for the determination of fatty acid (FA) contents in a micro-encapsulated fish-oil (μEFO) supplement by using attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopic technique and partial least square regression (PLSR) analysis. Using the ATR-FTIR technique, the μEFO powder samples can be directly analysed without any pre-treatment required, and our developed PLSR strategic approach based on the acquired spectral data led to production of a good linear calibration with R(2)=0.99. In addition, the subsequent predictions acquired from an independent validation set for the target FA compositions (i.e., total oil, total omega-3 fatty acids, EPA and DHA) were highly accurate when compared to the actual values obtained from standard GC-based technique, with plots between predicted versus actual values resulting in excellent linear fitting (R(2)≥0.96) in all cases. The study therefore demonstrated not only the substantial advantage of the ATR-FTIR technique in terms of rapidness and cost effectiveness, but also its potential application as a rapid, potentially automated, online monitoring technique for the routine analysis of FA composition in industrial processes when used together with the multivariate data analysis modelling.     

红外光谱快速测定油茶籽油脂肪酸组成的模型建立北大核心CSCD

通过气相色谱和傅里叶红外光谱仪测定86个油茶籽油样本的脂肪酸组成和红外光谱图,采用支持向量机(SVM)和BP人工神经网络(ANN)的非线性建模方法,构建油茶籽油中主要脂肪酸的定量回归模型。结果表明:ANN建立的油酸和棕榈酸定量回归模型精确度比SVM高,校正集的相关系数(R)分别为0.9987和0.9451,预测集的相关系数分别为0.9557和0.9262,相对标准偏差分别小于1%和5%;SVM和ANN建立的亚油酸定量分析模型精确度都非常高,相对标准偏差均小于1%。说明红外光谱用于油茶籽油中主要脂肪酸的快速检测是完全可行的。