Fourier transform infrared spectroscopy for the study of food biopolymers

The technique of Fourier transform infrared (FTIR) spectroscopy, in conjunction with new methods of sample presentation, has been used to study biopolymer functionality in aqueous systems. Changes in the spectra of κ-carrageenan gels have been observed with both counter—ion and temperature. Most of these differences arise from conformational changes of the polysaccharide backbone, but there is also evidence of direct ion—sulphate interaction in certain ion forms, consistent with previous NMR results. An assignment of the region 1400–800 cm⁻¹ has been made for the carrageenan gels. In waxy maize and wheat starch gels, changes in the IR spectra are observed during storage. Some of these can be related to the development of crystallinity in the material. The time course of the observed FTIR measurements during retrogradation of waxy maize starch is very similar to those produced from other techniques, such as shear modulus. This process can also be in wheat starch gels and the possibility that it can be measured in real foodstuffs is demonstrated by the fact that the same techniques could be used to acquire a high-quality spectrum of bread.     

Automatic baseline correction by wavelet transform for quantitative open-path Fourier transform infrared spectroscopy

A technique for automatically correcting the baseline of open-path Fourier transform infrared spectra is described in which the spectra are decomposed into high-frequency (details) and low-frequency (discrete approximations) information using a wavelet transform. After an appropriate number of iterations, n, the discrete approximation simulates the baseline of the spectrum. By setting the nth approximation to zero and reversing this process, the reconstructed signal contains only the high-frequency components in the original signal on a baseline that is approximately flat and at zero absorbance. When small molecules such as NH3 and CH4 are quantified by partial least-squares (PLS) regression, this process decreases the number of eigenvectors required for the analysis by two or three, increasing the ruggedness of the prediction. The baseline that is calculated is approximately the same for spectra measured at resolutions of 1, 2, 4, 8, and 16 cm(-1). Surprisingly, the baseline that is calculated is not totally smooth, with artifacts that are caused by the analyte. The amplitude of the artifacts is directly proportional to the concentration of the analyte, so the accuracy of PLS regression is not degraded.     

Prediction of pregnancy viability in bovine in vitro-produced embryos and recipient plasma with Fourier transform infrared spectroscopy

We analyzed embryo culture medium (CM) and recipient blood plasma using Fourier transform infrared (FTIR) metabolomics to predict pregnancy outcome. Individually cultured, in vitro-produced (IVP) blastocysts were transferred to recipients as fresh and vitrified-warmed. Spent CM and plasma samples were evaluated using FTIR. The discrimination capability of the classifiers was assessed for accuracy, sensitivity (pregnancy), specificity (nonpregnancy), and area under the receiver operator characteristic curve (AUC). Within all IVP fresh embryos (birth rate = 52%), high AUC were obtained at birth, especially with expanded blastocysts (CM: 0.80 ± 0.053; plasma: 0.89 ± 0.034). The AUC of vitrified IVP embryos (birth rate = 31%) were 0.607 ± 0.038 (CM, expanded blastocysts) and 0.672 ± 0.023 (plasma, all stages). Recipient plasma generally predicted pregnancy outcome better than did embryo CM. Embryos and recipients with improved pregnancy viability were identified, which could increase the economic benefit to the breeding industry.     

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。     

Discrimination of Salmonella enterica serotypes by Fourier transform infrared spectroscopy

Salmonella continues to be an important cause of foodborne infections in humans throughout the world. The precise nature of the infection depends on the specific combination of host and Salmonella serotypes, some of them being highly pathogenic. Fourier transform infrared (FT-IR) spectroscopy together with chemometric techniques were used in this study to discriminate closely related S. enterica serotypes. Intact cells of 26 different serotypes belonging to serogroups B, C1, C2–C3 and D1 (Enteritidis, Typhimurium, Bredeney, Goldcoast, Rissen, Hadar, Derby, Essen, Virchow, Mbandaka, Menden, Agona, Brikama, Saintpaul, Infantis, Braenderup, Mikawasima, Brandenburg, Heidelberg, Indiana, Norwich, Bardo, Bovismorbificans, Istanbul, Newport and Blockley) were examined by FT-IR spectroscopy in transmittance mode and classified based on the agglutination pattern reactions using the Kauffmann–White classification scheme. Using FT-IR spectra in the 1200–900 cm^? 1 range (outer membrane polysaccharides) allowed to correctly classify all isolates according to the four analysed serogroups. A discrimination analysis applied within each serogroup, demonstrated that it was also possible to differentiate between the different serotypes. Results demonstrate that application of FT-IR spectroscopy together with chemometric methods has considerable potential to effectively fulfil the current requirements for fast and straightforward differentiation of S. enterica serotypes.     

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。     

Application of Fourier transform infrared spectroscopy to legume seed flour analysis

The secondary structure of legume (Phaseolus vulgaris L. and Lens culinaris L.) proteins was investigated by studying the amide I infrared absorption band in whole seed flours, before and after dry heating and autoclaving thermal treatments. The analysis procedure, set up on 7S and different model proteins, shows that the content of β-sheet structures in lentil is higher than in common bean (47% vs. 32%). The dry heating does not appreciably affect secondary structures in lentil, while it causes a reduction of β-sheets (to 13%), an increase of aggregates, and the appearance of random coil structures in common bean. The autoclaving treatment produces high amounts of aggregates in both legumes. However, in lentil, random coil structures are lower than in common bean and some β-sheet structures are still detectable. These results indicate that multimeric heat-induced complexes of legume proteins have a high stability because of the high content in β-sheet structures, in particular in lentil, which may adversely affect protein utilization.     

Predicting bovine milk protein composition based on Fourier transform infrared spectra

Phenotypic information on individual protein composition of cows is important for many aspects of dairy processing with cheese production as the center of gravity. However, measuring individual protein composition is expensive and time consuming. In this study, we investigated whether protein composition can be predicted based on inexpensive and routinely measured milk Fourier transform infrared (FTIR) spectra. Based on 900 calibration and 900 validation samples that had both capillary zone electrophoresis (CZE)-determined protein composition and FTIR spectra available, low to moderate validation R² were reached (from 0.18 for α_S1-casein to 0.56 for β-lactoglobulin). The potential usefulness of this model on the phenotypic level was investigated by means of achieved selection differentials for 25% of the best animals. For α-lactalbumin (R² = 0.20), the selection differential amounted to 0.18 g/100 g and for casein index (R² = 0.50) to 1.24 g/100 g. We concluded that predictions of protein composition were not accurate enough to enable selection of individual animals. However, for specific purposes when, for example, groups of animals that meet a certain threshold are to be selected, the presented model could be useful in practice on the phenotypic level. The potential usefulness of this model on the genetic level was investigated by means of genetic correlations between CZE-determined and FTIR-predicted protein composition traits. The genetic correlations ranged from 0.62 (β-casein) to 0.97 (whey). Thus, predictions of protein composition, when used as input to estimate breeding values, provide an excellent means for genetic improvement of protein composition. In addition, estimated repeatabilities based on 3 repeated observations of predicted protein composition showed that a considerable amount of prediction error can be removed using repeated observations.     

Development and application of Fourier transform infrared spectroscopy for detection of milk adulteration in practice

Fourier transform infrared (FT‐IR) spectroscopy is widely applied for routine milk analysis. More recently, it has been used to detect a range of specific milk adulterants. Here, we show that the simultaneous use of targeted and untargeted models applied to FT‐IR spectra for detecting potential milk adulterants across relevant concentration ranges is an effective strategy. Using an appropriate validation strategy, limits of detection, sensitivity and specificity are determined for specific adulterants giving a useful guide to how these models would work in a practical situation. Finally, theoretical limits of detection of a range of potential adulterants are listed.     

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.     

Analysis of lard in meatball broth using Fourier transform infrared spectroscopy and chemometrics

Meatball is one of the favorite foods in Indonesia. For the economic reason (due to the price difference), the substitution of beef meat with pork can occur. In this study, FTIR spectroscopy in combination with chemometrics of partial least square (PLS) and principal component analysis (PCA) was used for analysis of pork fat (lard) in meatball broth. Lard in meatball broth was quantitatively determined at wavenumber region of 1018–1284 cm^− 1. The coefficient of determination (R²) and root mean square error of calibration (RMSEC) values obtained were 0.9975 and 1.34% (v/v), respectively. Furthermore, the classification of lard and beef fat in meatball broth as well as in commercial samples was performed at wavenumber region of 1200–1000 cm^− 1. The results showed that FTIR spectroscopy coupled with chemometrics can be used for quantitative analysis and classification of lard in meatball broth for Halal verification studies. The developed method is simple in operation, rapid and not involving extensive sample preparation.     

傅立叶变换红外光谱技术对6种致病性大肠埃希氏菌快速分型的研究

目的建立肠致病性大肠埃希氏菌(Enteropathogenic E.coli,EPEC)、肠产毒性大肠埃希氏菌(Enterotoxigenic E.coli,ETEC)、肠侵袭性大肠埃希氏菌(Enteroinvasive E.coli,EIEC)、肠黏附性大肠埃希氏菌(Enteroadhesive E.coli,EAEC)、肠出血性大肠埃希氏菌(Enterohmorrhagic E.coli,EHEC)、弥散粘附性大肠埃希氏菌(Diffusely adherent E.coli,DAEC)6种致病性大肠埃希氏菌的傅立叶变换红外光谱(Fourier transform infrared spectroscopy,FT-IR)数据库及FT-IR分型方法。方法应用FT-IR技术对6种致病性大肠埃希氏菌进行指纹图谱数据采集并对其进行基线校正、归一化等处理,应用化学计量学方法对光谱数据进行分析。结果本研究建立了6种致病性大肠埃希氏菌的FT-IR光谱数据库,实现了对6种可疑目标大肠埃希氏菌鉴定;建立了主成分分析(principal component analysis,PCA)和分级聚类分析(hierarchical cluster analysis,HCA)2种模型,成功实现了对6种致病性大肠埃希氏菌的快速分型。结论 FT-IR分析方法快速、简便、易操作,结果重现性好,是一种鉴定6种致病性大肠埃希氏菌的有效方法。     

傅里叶变换红外光谱法鉴别不同产地带鱼

摘 要：目的 建立不同产地带鱼红外指纹图谱，为带鱼产地鉴定提供新方法。方法 采用傅里叶变换红外光谱法(Fourier Transform Infrared Spectroscopy, FTIR)，分别构建国内外5个主产地的带鱼样品指纹图谱，并通过主成分分析和聚类分析开展带鱼产地鉴别应用研究。结果 通过主成分分析可以实现5个产地带鱼的分类，计算各产地带鱼化学成分累积量综合得分，表明舟山渔场和印度洋产地带鱼化学成分含量相对更为丰富。聚类分析结果表明各产地带鱼分别聚类，且水文条件和地理环境较为接近的带鱼样品先聚为一类；两者试验结果可相互补充和印证。结论 应用FTIR建立带鱼产地指纹图谱，方法可靠、重复性较好，符合指纹图谱的要求，适合对带鱼进行整体信息分析和质量控制。本研究为我国带鱼产地鉴别提供了参考，对于地理标志产品的保护具有借鉴意义。     

傅立叶近红外光谱法测定桃果中果胶含量

目的 基于傅里叶近红外光谱(Fourier transform near infrared)检测桃果中果胶含量的研究。方法 近红外光谱采集样品利用两个品种的桃,探究光谱预处理对建模的影响,建模采用偏最小二乘法(PLS)以及主成分回归(PCR)方法,模型的评价标准采用建模相关系数(R_C)、建模均方偏差(RMSE_C)、预测相关系数(R_P)、预测均方偏差(RMSE_P)。结果 两个品种的近红外光谱图和果胶含量无明显差异(P＞0.05),采用标准正态变量变换(SNV)和多元散射校正(MSC)对原始光谱的光程进行选择,所得建模结果影响基本一致,合适光谱数据格式以及平滑处理,能提高PLS和PCR模型的预测精度和稳定性。综合得出模型最佳是利用PLS方法建模并采用MSC/SNV结合一阶导数和 Savitzky-Golay (S-G)平滑对近红外光谱图进行预处理,评价参数分别为R_C=0.7795、R_P=0.7545、RMSE_C=0.0933、RMSE_P=0.0534和R_C=0.7800、R_P=0.7530、RMSE_C=0.0932、RMSE_P=0.0534。结论 该方法为利用近红外建模快速检测桃果中果胶含量提供重要依据。     

The use of Fourier transform mid infrared (FT-MIR) spectroscopy for detection and quantification of adulteration in virgin coconut oil

Currently, the authentication of virgin coconut oil (VCO) has become very important due to the possible adulteration of VCO with cheaper plant oils such as corn (CO) and sunflower (SFO) oils. Methods involving Fourier transform mid infrared (FT-MIR) spectroscopy combined with chemometrics techniques (partial least square (PLS) and discriminant analysis (DA)) were developed for quantification and classification of CO and SFO in VCO. MIR spectra of oil samples were recorded at frequency regions of 4000–650 cm⁻¹ on horizontal attenuated total reflectance (HATR) attachment of FTIR. DA can successfully classify VCO and that adulterated with CO and SFO using 10 principal components. Furthermore, PLS model correlates the actual and FTIR estimated values of oil adulterants (CO and SFO) with coefficient of determination (R²) of 0.999.     

Fourier transform infrared spectroscopy and multivariate analysis for the detection and quantification of different milk species

The authenticity of milk and milk products is important and has extended health, cultural, and financial implications. Current analytical methods for the detection of milk adulteration are slow, laborious, and therefore impractical for use in routine milk screening by the dairy industry. Fourier transform infrared (FT-IR) spectroscopy is a rapid biochemical fingerprinting technique that could be used to reduce this sample analysis period significantly. To test this hypothesis we investigated 3 types of milk: cow, goat, and sheep milk. From these, 4 mixtures were prepared. The first 3 were binary mixtures of sheep and cow milk, goat and cow milk, or sheep and goat milk; in all mixtures the mixtures contained between 0 and 100% of each milk in increments of 5%. The fourth combination was a tertiary mixture containing sheep, cow, and goat milk also in increments of 5%. Analysis by FT-IR spectroscopy in combination with multivariate statistical methods, including partial least squares (PLS) regression and nonlinear kernel partial least squares (KPLS) regression, were used for multivariate calibration to quantify the different levels of adulterated milk. The FT-IR spectra showed a reasonably good predictive value for the binary mixtures, with an error level of 6.5 to 8% when analyzed using PLS. The results improved and excellent predictions were achieved (only 4-6% error) when KPLS was employed. Excellent predictions were achieved by both PLS and KPLS with errors of 3.4 to 4.9% and 3.9 to 6.4%, respectively, when the tertiary mixtures were analyzed. We believe that these results show that FT-IR spectroscopy has excellent potential for use in the dairy industry as a rapid method of detection and quantification in milk adulteration.     

Determination of fatty acid composition of pork fat by Fourier transform infrared spectroscopy

The fatty acid composition of pork fat determines its processing quality. FTIR spectroscopic methods were evaluated on pork back and breast fat, directly on fat slices and on the fat extracts. Near infrared transmission and middle infrared using an ATR method were developed to determine the fatty acid content in the fat extracts. The results obtained with 80 back and 80 breast samples showed the validity of infrared spectroscopy to estimate SFA (saturated fatty acids), MUFA (monounsaturated fatty acids), PUFA (polyunsaturated fatty acids), C16:0, C18:0, C18:1 and C18:2 contents in fat extracts. Correlation coefficients (R(2)) were around 0.91 and 0.98 for MIR (ATR) and around 0.85 and 0.96 for NIR (transmission). Direct measurements on fat slices by NIR predicted SFA, PUFA, C18:1 and C18:2, although the coefficient correlations were less good; 0.69-0.79. This method though, is easier and faster than other techniques and is accurate enough to discriminate fat samples separated by standard visual and texture classification. Measurements could be made in 1 min.     

Application of Fourier transform infrared spectroscopy for monitoring short-chain free fatty acids in Swiss cheese

Short-chain free fatty acids (FFA) are important sources of cheese flavor and have been reported to be indicators for assessing quality. The objective of this research was to develop a simple and rapid screening tool for monitoring the short-chain FFA contents in Swiss cheese by using Fourier transform infrared spectroscopy (FTIR). Forty-four Swiss cheese samples were evaluated by using a MIRacle three-reflection diamond attenuated total reflectance (ATR) accessory. Two different sampling techniques were used for FTIR/ATR measurement: direct measurement of Swiss cheese slices (∼0.5 g) and measurement of a water-soluble fraction of cheese. The amounts of FFA (propionic, acetic, and butyric acids) in the water-soluble fraction of samples were analyzed by gas chromatography-flame ion-ization detection as a reference method. Calibration models for both direct measurement and the water-soluble fraction of cheese were developed based on a cross-validated (leave-one-out approach) partial least squares regression by using the regions of 3,000 to 2,800, 1,775 to 1,680, and 1,500 to 900 cm⁻¹ for short-chain FFA in cheese. Promising performance statistics were obtained for the calibration models of both direct measurement and the water-soluble fraction, with improved performance statistics obtained from the water-soluble extract, particularly for propionic acid. Partial least squares models generated from FTIR/ATR spectra by direct measurement of cheeses gave standard errors of cross-validation of 9.7 mg/100 g of cheese for propionic acid, 9.3 mg/100 g of cheese for acetic acid, and 5.5 mg/100 g of cheese for butyric acid, and correlation coefficients >0.9. Standard error of cross-validation values for the water-soluble fraction were 4.4 mg/100 g of cheese for propionic acid, 9.2 mg/100 g of cheese for acetic acid, and 5.2 mg/100 g of cheese for butyric acid with correlation coefficients of 0.98, 0.95, and 0.92, respectively. Infrared spectroscopy and chemometrics accurately and precisely predicted the short-chain FFA content in Swiss cheeses and in the water-soluble fraction of the cheese.     

织物傅里叶变换衰减全反射红外光谱库的建立及应用

针对常规方法鉴别纯纺织物及预测混纺织物组分含量工序多、耗时长且污染环境的问题,采用傅里叶变换红外光谱仪,结合衰减全反射(ATR)附件测试各纯纺及二组分混纺织物的傅里叶变换衰减全反射红外光谱(ATR-IR)图,并从已测的753个样品中筛选出正反经纬组分一致的纯纺及混纺织物样品205个,建立了涤纶/棉、涤纶/羊毛、涤纶/锦纶、蚕丝/棉和涤纶/粘胶等纯纺及混纺织物的ATR-IR谱库。并利用自建谱库的检索功能,对20个未知纤维织物样品进行快速无损鉴别及含量预测。研究表明:对于纯纺织物,识别准确率为100%;对于混纺织物,当误差≤3% 时,通过T检验,其定量预测结果与国标法测定值无显著差异,方便了样品的快速检验与含量预测。