应用主成分和判别分析的红外光谱法快速鉴别酸败植物油

通过收集并分析40个合格植物油和44个酸败植物油的傅里叶变换红外光谱,选取25个合格植物油和39个酸败植物油组成训练集,利用主成分分析获得累积可信度95%的三个主成分及对应的1743¹710cm-1、1172¹130cm-1、2945²844cm-1、1728¹689cm-1、2987²840cm-1和1731¹660cm-1对植物油酸败最为敏感的光谱波数范围。在主成分分析的基础上,选取对植物油酸败敏感的波段,利用训练集建立鉴别植物油酸败判别分析模型。采用验证集20个样品验证判别分析模型,判别正确率达100%。主成分结合判别分析的红外光谱法能快速、准确、无损地区分合格植物油和酸败植物油。      

傅里叶变换红外光谱法鉴别纯核桃油并定量检测掺伪含量

应用傅里叶变换红外光谱(FT—IR)法测定纯核桃油和分别混合大豆油、普洱茶籽油和葵花籽油的掺伪核桃油的红外光谱,结合主成分分析法(PCA)以及马氏距离判别法对核桃油的纯度进行判别,3个判别模型的准确率均达到100%;同时对验证集样品的类归属进行判别,判别准确率达均为100%。结合偏最小二乘法(PLS)定量检测核桃油纯度,建立的PLS校正集模型中核桃油的真实含量与FT—IR预测含量的相关系数R2分别为0.990 8、0.994 4和0.995 5,校正集均方根误差分别为0.032 7、0.023 5和0.019 6。试验结果证明,该方法可以作为核桃油质量监控的快速检测方法。     

3种植物油傅里叶变换红外光谱信息的判别分析研究

针对花生油、大豆油和棕榈油样品,采用傅里叶变换红外光谱仪,采集红外吸收光谱,对光谱预处理后,提取红外特征信息,以1 746 cm-1和2 855 cm-1波数处吸收峰特征参数比值为X轴, 1 099 cm-1与1 119 cm-1波数处吸收峰特征参数的比值为Y轴,及3种油O-C-C对称伸缩振动各自所产生的吸收带所在波数(cm-1)值作为Z轴,绘制三维分布图,对这3种油样进行判别分析.结果显示这3种油样之间有明显区分.     

红外光谱法对霍山石斛的鉴别

傅里叶变换红外光谱能反映特定分子官能团的振动模式,具有较好的指纹特性,是一种常用鉴别方法。利用傅里叶变换红外光谱技术测定霍山产的3种石斛的红外图谱,应用主成分分析和正交偏最小二乘判别分析处理数据以鉴别霍山石斛。结果表明,不同石斛的红外图谱峰型相似,相比主成分分析,红外光谱应用正交偏最小二乘判别分析方法更能有效地鉴别出霍山石斛,模型正确率更高。因此,红外光谱应用正交偏最小二乘判别分析是实现霍山石斛快速鉴别的一种有效方法。     

利用傅里叶变换红外光谱法分析燕麦片的品质

为了建立一种快速、无损的鉴定市场所销售的燕麦片的品质鉴定分析方法,对宁波市超市所销售的品牌1～品牌8的燕麦片商品进行了抽样,采取傅里叶变换红外光谱法(FTIR)进行定性分析。结果表明,通过红外光谱图和特征峰之间的比较,可以分析出燕麦中含有的营养成分及其含量高低;结合二阶导数谱能把红外图谱中重叠的峰区分开来,增大谱图的分辨率,使分析更加精细准确;利用热微扰法测定燕麦红外光谱及其二维相关红外光谱可以判断燕麦的热稳定性。因此,傅里叶变换红外光谱法是一种快速、无损的鉴定燕麦片品质的分析方法。     

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法的红花药材质量分析

目的 建立傅里叶变换红外光谱法分析评价红花药材质量的分析方法。方法 采用傅立叶变换红外光谱法(Fourier transform infrared spectrometry, FTIR)对采集自新疆不同产地的20批红花药材进行测量, 建立指纹图谱; 运用聚类分析与主成分分析等统计学及化学模式识别技术, 对不同来源的红花药材进行红外光谱数据比较分析。结果 筛选出12个波数段, 形成了红花药材FTIR红外光谱指纹图谱共有模式; 精密度、稳定性和重复性实验结果表明, 共有峰波数的相对标准偏差(relative standard deviation, RSD)分别为0.00%~0.1%、0.00%~4.56%、0.32%~7.5%, 符合指纹图谱的要求; 20批样品相似度均大于95%, 大致可以分为3大类, 区域间差异较为明显。结论 本研究建立的方法简单、易行、快速, 不污染、样品耗量低, 为不同来源红花药材的鉴定、内在质量评价与质量控制提供了依据、奠定了基础。     

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.     

傅里叶变换红外光谱结合化学计量学用于山茶油中掺杂大豆油的鉴别

建立快速定性鉴别山茶油与大豆油、菜籽油和玉米油,以及定量检测山茶油中掺杂大豆油的傅里叶变换红外光谱(Fourier transform infrared spectroscopy,FTIR)检测方法。采用FTIR光谱技术,对比山茶油与大豆油、玉米油、菜籽油红外光谱中2个特征峰(1 122 cm~(-1)与1 096 cm~(-1))的峰高差异,可快速定性区分山茶油与其他3种食用油,并能鉴别掺入大豆油含量(质量分数)在30%及以上的山茶油;利用4种食用油的1 464～722 cm~(-1)范围内的指纹光谱,结合PCA算法,建立的定性判别模型可区分山茶油及其他3种食用油,并结合PLSR算法,构建了检测山茶油中掺入大豆油的定量模型,其中校正集的RMSECV值为0.032 0,验证集的RMSEP值为0.029 7,校正集和验证集的R~2值均能达到0.99,最低检测限达1%(质量分数)。结果表明,所建立的山茶油中掺杂大豆油的FTIR光谱检测方法简便、灵敏、准确,为市场筛查掺假山茶油的快速鉴别提供了技术参考。     

纤维素热解的实时快速逸气分析/傅里叶变换红外光谱法研究

1　引言一般认为 ,纤维素热解产生两类主要初级反应产物 :脱水形成的脱水纤维素和解聚形成的左旋葡聚糖。脱水和解聚反应相互竞争活化纤维素 :在低温 (低于30 0℃ )和慢的加热速度下有利于脱水 ,而在高温 (高于30 0℃ )和快的加热速度下 ,有利于解聚。在二级反应时 ,脱水纤维素和左旋葡聚糖会进一步分解 ,形成炭、永久气体和其它挥发性物质。纤维素热解研究用的技术有多种 ,其中有热重量分析法 (ＴＧＡ)、扫描差示量热法 (ＤＳＣ)、热解 -气相色谱法、热解气相色谱 /质谱法和逸气分析法 (ＥＧＡ)。本研究建立了一种快速加热逸气分析 /傅里叶…     

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.     

Differentiation of Peats Used in the Preparation of Malt for Scotch Whisky Production Using Fourier Transform Infrared Spectroscopy

It is not known if peats derived from different areas of Scotland have distinctive chemical constituents that could impact on malt whisky in discernible organoleptic ways. Fourier transform‐infrared (FT‐IR) spectroscopy was used as a high throughput screening method to investigate discrimination of a large number of peat samples from six different geographical origins around Scotland. The data were analysed statistically (using principal component‐discriminant function analysis) and the results showed a difference between peat samples from different geographical origins. Therefore, we have shown that FT‐IR spectroscopy provides a quick and simple method for differentiating peat types.     

葛粉掺假的近红外漫反射光谱快速检测

研究葛粉中掺假红薯淀粉和马铃薯淀粉的近红外漫反射光谱快速检测方法。采集样品的近红外漫反射光 谱,采用主成分回归和偏最小二乘法建立校正模型,并对比光谱预处理方法和光谱建模区间对模型的影响。结果表 明,采用偏最小二乘法建模,光谱采用标准正态变量变换预处理,光谱区间选择在962～1 389 nm时,模型预测效 果最佳,外部验证预测相关系数（RP 2）达0.994 5,均方根误差2.298 7%,相对分析误差13.56,平均回收率99.89% （n=9,RSD=2.96%）,这表明近红外漫反射技术能对葛粉中掺假红薯淀粉和马铃薯淀粉进行有效检测。     

基于近中红外光谱分析的大黄鱼产地区分技术

为实现4种产地来源的大黄鱼(福建养殖大黄鱼、温州养殖大黄鱼、舟山养殖大黄鱼和舟山野生大黄鱼)的准确快速区分,本研究应用傅里叶变换红外光谱仪对4种大黄鱼样本在4000～650 cm-1^的红外吸收指纹图谱进行测定,基于特征波段下的光谱吸收差异并结合PCA、CA和LDA、SVM模型对大黄鱼样品进行产地区分。结果如下：采用测定波段4000～650 cm-1^的全光谱采集信息经过SG预处理后建立的SVM模型效果最优,对4种大黄鱼样本的测试集准确率为83.3%。进一步对福建养殖大黄鱼和野生大黄鱼的产地区分方法优化后,选取特征波段3690～2800 cm-1⁺¹⁸⁰⁰～650 cm-1^{的光谱信息}经过1st ^Der、2nd ^Der和SNV 3种方式预处理后建立LDA判别模型,光谱训练集与预测集的准确率均达到100%;3690～2800 cm-1⁺¹⁸⁰⁰～650 cm-1^{的光谱信息}经SNV、MSC预处理后的PCA效果最佳,2种大黄鱼样本间彼此间距远、无重叠,且前两个主成分累计贡献率均在90%以上;经SNV预处理后的CA分析中除21号野生大黄鱼被误聚到福建养殖大黄鱼类中,其余2种产地大黄鱼样本各自聚为一类。研究表明基于近中红外光谱测定并结合化学计量学处理的方法能够对大黄鱼产地进行较准确地快速区分,从而为大黄鱼溯源鉴别、维护消费者权益和保护区域大黄鱼产业等方面提供技术支撑。     

近红外光谱分析技术在花生原产地溯源中的应用

采用近红外光谱结合化学计量学方法对不同省份来源的花生样品进行溯源研究。首先花生近红外光谱通过标准正态变换加去趋势化预处理降噪、主成分分析降维和小波转换降噪降维两种处理,然后结合线性判别分析、贝叶斯判别分析和k最近邻分析3种判别模型对不同省份来源地花生进行判别。通过分析最优判别组合结果表明,小波转换结合k最近邻分析对花生产地分类效果最好,原始正确分类率为100.0%;交叉验证正确分类率为55.9%。初步实现了花生产地判别,但模型的性能仍有待提高。     

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.     

基于傅里叶变换红外光谱技术对木耳中镰刀菌的识别检测

该研究建立了一种基于傅里叶变换红外光谱的木耳中镰刀菌的定性定量检测方法：对经高压灭菌的木耳样品分别接种木耳中常见的五种镰刀菌（层出镰刀菌189975、串珠镰刀菌340687、尖孢镰刀菌120618、木贼镰刀菌124121、茄病镰刀菌121547）,并于28 ℃,相对湿度80%的条件下进行储存培养,同时采集不同储存阶段的木耳样品在1 800~900 cm-1的红外光谱信息。分别运用主成分分析（PCA）、线性判别分析（LDA）以及偏最小二乘回归分析（PLSR）建立木耳中镰刀菌的快速识别检测模型。结果表明：LDA模型对受不同镰刀菌侵染的木耳样品的平均判别正确率达到87.50%,对受单一镰刀菌侵染的木耳样品霉变状态的平均判别正确率达到82.50%;PLSR模型对木耳样品中菌落总数的预测实现了较好的定量结果（R2 p=0.842 8,RMSEP=0.292 log CFU/g,RPD=2.81）;通过实际样品验证分析表明傅里叶变换红外光谱方法可以实现木耳中镰刀菌的快速识别检测。     

Differentiation of Crude Lipopolysaccharides from Escherichia coli Strains Using Fourier Transform Infrared Spectroscopy and Chemometrics

Crude phenol‐phase extracts containing bacterial lipopolysaccharides (LPS) from 5 strains of Escherichia coli were investigated to differentiate the strains using Fourier transform infrared (FTIR) spectroscopy and multivariate statistical analysis. The strains used were E. coli K12, E. coli DH5α, E. coli O157:H7, E. coli O157:H12, and E. coli O157:H19. LPS‐containing extracts were isolated from each E. coli strain using a hot phenol‐water extraction procedure. The extracts were 1st analyzed by deoxycholic acid‐polyacrylamide gel electrophoresis and visualized by silver‐staining. Analysis of the extracts from E. coli K12 and E. coli DH5α showed rough‐type LPS on the lower half of the gel, whereas E. coli O157:H7, E. coli O157:H12, and E. coli O157:H19 yielded abundant smooth LPS (high‐molecular‐weight LPS that include the O‐polysaccharides). Spectra (4000 cm^‐1 to 700 cm^‐1) of crude E. coli LPS extracts and intact cells were collected using a FTIR spectrometer. Spectral data were compressed by principle component analysis and analyzed using canonical variate analysis (CVA) of 4000 cm^‐1 to 700 cm^‐1 or 1200 cm^‐1 to 900 cm^‐1 spectral regions. CVA showed better separation between strains using LPS extracts than intact cells in the 1200 cm^‐1 to 900 cm^‐1 spectral region. The same separation trend was found using Mahalanobis distances that quantified spectral differences between the E. coli strains, providing 80% and >95% correct classifications of intact cells and LPS extracts, respectively. This article is the first to report the successful differentiation of E. coli strains at a serotype level using FTIR spectra of bacterial phenol‐phase extracts (crude LPS preparations).     

Approaches to Adulteration Detection in Instant Coffees using Infrared Spectroscopy and Chemometrics

Fourier transform infrared (FTIR) spectroscopy is examined as a rapid alternative to wet chemistry methods for the detection of adulteration of freeze-dried instant coffees. Spectra have been collected of pure coffees, and of samples adulterated with glucose, starch or chicory in the range 20–100 g kg⁻¹. Two different FTIR sampling methods have been employed: diffuse reflectance, and attenuated total reflectance. Three different statistical treatments of the spectra were carried out. Firstly, the spectra were compressed by principal component analysis and a linear discriminant analysis performed. With this approach, a 98% successful classification rate was achieved. Secondly, a simultaneous partial least square regression was carried out for the content of three added carbohydrates (xylose, glucose and fructose) in order to assess the potential of FTIR spectroscopy for determining the carbohydrate profile of instant coffee. Lastly, the discrimination of pure from adulterated coffee was performed using an artificial neural network (ANN). A perfect rate of assignment was obtained. The generalization ability of the ANN was tested on an independent validation data set; again, 100% correct classifications were achieved.     

葛根淀粉颗粒性质的研究

本文对葛根淀粉颗粒的性质进行了研究，包括淀粉颗粒的大小、形貌、X—射线衍射图谱、α—淀粉酶的酶水解作用方式等，并与玉米淀粉进行了比较。结果表明：葛根淀粉平均粒度为24．08μm，小于玉米淀粉的38．97μm；葛根淀粉和玉米淀粉颗粒的偏光十字接近颗粒中心，但葛根淀粉颗粒的偏光十字不明显；葛根淀粉的X—射线衍射图谱为C型，玉米淀粉为A型，而两者的结晶度分别为18％和37％；葛根淀粉和玉米淀粉对α—淀粉酶的作用极为敏感，但在酶解方式上，葛根淀粉是在淀粉粒表面形成许多微孔并经脐心进入淀粉粒内部，而玉米淀粉则是被层层水解，在淀粉粒表面形成很少的微孔。