红外光谱测定羧甲基纤维素钠的羧基含量

将羧甲基纤维素钠(CMC)经浓硝酸处理得到CMC-H,选取CMC-H的红外光谱吸收峰1735cm-1为特征吸收峰,以1918.9cm-1-1529.3cm-1为基线,避免了水分含量对1735cm-1峰高的影响;硫氰化钾(KSCN)作为内标物,得到了线性关系较好的标准曲线(R2=0.980)。实验结果表明,可用傅立叶变换红外光谱法(FT-IR)测定羧甲基纤维素钠中的羧基含量。     

基于红外光谱的木棉与棉定量分析

为了进行红外光谱定量分析纤维含量的研究,测试了不同比例木棉/棉混合物的红外光谱图,探讨了红外光谱定量分析木棉/棉混纺比的方法。研究表明,1732cm-1和1242cm-1处特征吸收峰面积与木棉含量的线性关系明显,1732cm-1处最佳。以1732cm-1处的特征吸收峰面积对木棉/棉混纺试样的木棉含量作了定量分析,得出了线性关系较好的标准曲线。用本法对未知样品的木棉含量进行测定,得到了较好的结果。     

FTIR技术结合区间偏最小二乘法快速测定油脂中反式脂肪酸

研究了傅里叶红外光谱技术结合区间偏最小二乘法(iPLS)快速分析食用油中低含量(0.1%~5%)反式脂肪酸的分析方法。通过系统地比较衰减全反射红外光谱法(ATR-FTIF)及衰减透射红外光谱法(TR-FTIR)光谱的模型效果,优化建模区间。研究结果表明,ATR-FTIR、TR-FTIR-PLS回归模型均能有效测定油脂中低浓度反式脂肪酸的含量,但TR-FTIR法灵敏度优于ATR-FTIR法。iPLS区间选择结果显示,以1 000~940 cm~(-1)波段透射光谱建模,相关系数R~2为0.998 8,标准集的RMSEC 0.016 6,验证集RMSEP为0.008 75,预测相对标准偏差2.92%,预测值与实际值高度相关,Y_(预测)=1.00X_(实际)-0.003 44,R~2=0.998 7。12组外部验证试验相对标准偏差为4.80%,说明预测精确度较高、模型稳定性好,有潜力替代传统气相色谱法用于油脂中低含量反式脂肪酸快速定量测定。     

原料不同配比合成的枸橼酸苹果酸钙钙溶解性及红外光谱

观察不同原料配比对合成的枸橼酸苹果酸钙钙含量、钙溶解性及红外光谱影响.4种用不同原料配比合成枸橼酸苹果酸钙,分别按中国药典方法测定钙含量、钙溶解性,用红外光谱仪测定4000 cm-1～400 cm-1吸收峰波数和强度.结果:4种不同原料配比合成枸橼酸苹果酸钙钙溶解性100mL钙元素分别为160.2、123.4、124.7、122.7mg,红外光谱测定图谱出现的吸收峰波数基本一致,特征峰更接近苹果酸钙,但4组样品红外光谱特征峰在相同波数下,强度有所不同.结论:不同原料配比对合成的枸橼酸苹果酸钙钙溶解性影响较大.     

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.     

硅氢加成反应中活泼氢质量分数的测定

根据Si—H键在2 166 cm-1的特征吸收峰,采用衰减全反射傅里叶变换红外光谱法(ATR-FTIR)来测定硅氢加成体系中的活泼氢质量分数。该方法的活泼氢质量分数在0.071%~0.628%范围内与其红外光谱的吸光度具有良好的线性关系,相关系数为0.999,相对标准偏差为0.785%。该方法操作简单,检测结果可靠,适用于硅氢加成反应体系中大量样品的快速检测。     

低温氧漂活化剂TAED的结构表征及其应用

对市售的几种低温氧漂活化剂四乙酰乙二胺(TAED)采用广角X-射线衍射、红外光谱、紫外吸收光谱进行结构表征,测定了高纯度粉状TAED产品的溶解度,并对不同织物进行了双氧水/TAED活化漂白试验。结果表明,高纯度TAED产品在红外光谱中的1706cm-1和1680cm-1处存在酰胺I(C=O)伸缩振动的强吸收峰,1270cm-1和1193cm-1处存在酰胺III(C—N)伸缩振动的强吸收峰。各种TAED产品的水溶液在紫外吸收光谱215nm处均存在强吸收峰,可利用其吸收强度与浓度的线性关系检测各产品的浓度。高纯粉状TAED产品的溶解度随温度升高而增加,在70℃时的溶解度为17g/L。TAED产品剂型对漂白效果无影响,采用双氧水/高纯TAED产品对不同织物进行漂白,均能获得满意的漂白效果,且高效节能。     

羧甲基大蒜多糖的制备与鉴定

为拓宽大蒜多糖的应用范围,以自制的大蒜多糖为原料,与一氯乙酸在碱性条件下反应,经分离纯化获得羧甲基大蒜多糖.通过红外光谱(IR)和13C核磁共振谱(13C-NMR)鉴定所获产品.IR测定结果表明:所获产品在1603.20cm-1处有羧基上羰基的伸缩振动烽13C-NMR测定结果表明:在化学位移178处显示羰基吸收峰;羧甲基反应的取代位置主要为C3,其次是在C6.上述结果表明,用一氯乙酸羧甲基化大蒜多糖是成功的.     

近红外光谱法对茶叶中的咖啡碱含量的快速测定

以贵州省各地茶叶为研究对象,以近红外光谱分析技术快速检测茶叶中的咖啡碱含量为目的,将茶叶制成粉末进行光谱扫描并用化学法测定其咖啡碱含量,将偏最小二乘法与傅立叶变换近红外光谱法相结合,建立茶叶中咖啡碱含量的模型.通过多元散射校正(MSC)处理光谱,光谱范围选择4493.33cm-1～4354.48cm-1,5800.83cm-1～5696.69cm-1,主因子数为10,得到模型的内部交互验证相关系数(P)为0.991,交互验证均方差(RMSECV)为0.205;模型的预测值与化学测定值的相关系数为0.999,预测标准偏差(RMSEP)为0.242.通过稳定性试验得到的RSD都在0.30％以下.结果表明,模型的预测效果很好,具有较高的精密度和较好的稳定性,且方法简捷,能满足茶叶中咖啡碱的快速检测要求.     

ATR-FTIR在小麦及其制品呕吐毒素污染水平快速测定中的应用

为快速测定小麦及其制品呕吐毒素（deoxynivalenol,DON）污染情况,搜集小麦、面粉及面粉制品共98?份,利用衰减全反射-傅里叶变换红外光谱（attenuated total reflectance-Fourier transform infrared spectroscopy,ATR-FTIR）获取样品在4 000～600 cm－1的光谱信息,对样品中的DON含量建立了基于偏最小二乘回归（partial least squares regression,PLSR）分析和逐步多元性回归（stepwise multiple linear regression,SMLR）分析方法的定量分析模型。结果显示,不同DON含量样品在1?740、1?648、1?549?cm－1和1?300～900?cm－1等波段处的吸收值存在显著差异。PLSR和SMLR均能较好预测样品中的DON含量,其中PLSR模型的预测集决定系数RP2、预测均方根误差（root mean squared error of prediction,RMSEP）和相对分析偏差（residual predictive deviation,RPD）值分别为0.86、0.438?mg/kg和2.6。SMLR结合9?个波长所建模型的RP2、RMSEP和RPD值分别为0.86、0.426?mg/kg和2.6。结果表明,ATR-FTIR用于小麦及其制品DON污染快速分析具有可行性。     

基于太赫兹—衰减全反射光谱的甘氨酸溶液定量研究

采用太赫兹衰减全反射光谱,研究20～450cm-1范围内不同浓度甘氨酸水溶液的光谱信息,将光谱进行二阶导数预处理后,选择不同波数进行随机组合,确定最适三波数组合模型,并建立最适拟合三元线性回归方程。结果表明,分别在65.56,127.28,173.56,308.55cm-1处出现清晰的吸收峰;回归方程R2Adj为0.990 3,均方根误差为0.005 7,预测均方根误差为1.658 9。     

Fourier Transform Infrared Spectroscopy Combined with Multivariate Calibrations for the Authentication of Avocado Oil

Avocado oil is one of the functional oils having high quality and high price in the market. This oil shows many benefits for the human health and is applied in many cosmetic products. The authentication of avocado oil becomes very important due to the possible adulteration of avocado oil with other lower priced oils, such as palm oil and canola oil. In this study, Fourier transform infrared spectroscopy using attenuated total reflectance in combination with chemometrics techniques of partial least squares and principal component regression is implemented to construct the quantification and classification models of palm oil and canola oil in avocado oil. Partial least squares at the wavenumbers region of 1260–900 cm^–1 revealed the best calibration models, having the highest coefficient of determination (R² = 0.999) and the lowest root mean square error of calibration, 0.80%, and comparatively low root mean square error of prediction, 0.79%, for analysis of avocado oil in the mixture with palm oil. Meanwhile, the highest R², root mean square error of calibration, and root mean square error of prediction values obtained for avocado oil in the mixture with canola oil at frequency region of 3025–2850 and 1260–900 cm^–1 were 0.9995, 0.83, and 0.64%, respectively.     

ATR-FTIR and Spectrometric Methods for the Assay of Crocin in Commercial Saffron Spices (Crocus savitus L.)

Attenuated total reflectance Fourier transform infrared spectrometric method for determination of crocin in commercial saffron samples was studied. Calibration models were built based on the peaks at spectral region of 1700–900 cm^?1 and spectral wavenumbers with correlation coefficient (r) greater than 0.99 were selected for quantification of crocin in the samples. The quantitative analysis of samples by attenuated total reflectance Fourier transform infrared was tested against reference UV-visible spectrophotometry method. Considerable correlation (r = 0.95) between both methods in prediction of crocin content among the saffron samples indicated that the proposed methodology has the potential application as a rapid screening tool.     

Authentication of sweetness of mango juice using Fourier transform infrared-attenuated total reflection spectroscopy

Fourier transform infrared spectrometer equipped with attenuated total reflection and chemometrics were used to determine added sugar content (ASC), total soluble solids (TSS) and real juice content (RJC) in fresh and commercial mango juice. Sucrose solutions (0-27%), fresh mango juice adulterated with 0-27% sucrose, and two commercial brands were evaluated in wavenumber range of 4000-650 cm⁻¹. Partial least squares (PLS) discrimination and principal component analysis (PCA) were used to classify the samples with or without ASC. PLS and multiple linear regression (MLR) were carried out with and without data treatments. The detection limit for ASC was 3% for samples with low natural TSS, 5% for samples with natural TSS more than 10% and 3.6% for commercial samples. ASC, TSS, and RJC were predicted in the wavenumber range of 1476-912 cm⁻¹ using PLS (multiple correlation coefficient, R = 0.99) and three wavenumbers (1088, 1050, 991 cm⁻¹) using MLR (R = 0.98).     

基于CWT和GRNN的可见-近红外漫反射光谱检测樱桃糖度的研究

联合使用连续小波变换(continuous wavelet transform,CWT)和广义回归神经网络(generalized regression neural networks,GRNN)建立用于测定樱桃中糖含量的CWT-GRNN 预测校正模型。利用CWT 提取樱桃样本数据中反映含糖量的关键光谱特征,在CWT 域中选择3 个具有代表性的尺度,并在每个尺度下根据樱桃样本的可见- 近红外光谱的特征将其划分为4 个特征区间,从而构造12 个特征输入到GRNN,GRNN 的光滑因子取为0.0001。CWTGRNN模型对20 个预测样本集中的樱桃含糖量的预测相对误差在2% 以内。结果表明,可见- 近红外光谱技术可以快速、准确和无损地测定樱桃中的含糖量,本研究提出的方法可以用于果蔬产业的品质管理与控制。     

Determination of Total Sugar Content in Soy-Based Drinks Using Infrared Spectroscopy and Chemometrics

Partial least square (PLS) regression models were developed and compared in order to determine the total sugar content in soy-based drinks using an infrared spectroscopy technique known as attenuated total reflectance Fourier transform infrared (ATR-FTIR). On a spectrophotometer set for analyzing on the middle infrared region, spectral band of 1900 to 900 cm^?1, commercial samples of soy beverage were analyzed, as well as samples with crescent water additions of 5, 10, and 20% v/v. Reference data for total sugars were obtained using the Lane-Eynon method. To construct regression models, algorithms of interval partial least square (iPLS) and synergy of interval partial least square (siPLS) were applied using iToolbox package on Matlab 8.1 environment. Kennard-Stone algorithm was used to the selection of calibration and prediction sets. Two models have been the best obtained: the first was an iPLS with seven latent variables, which selected the spectral band of 1399–900 cm^?1 and presented root mean square error of cross-validation (RMSECV)?=?0.1678% (w/w). The second best model was siPLS with six latent variables, which selected spectral bands of 1025–1150 and 1151–1476 cm^?1 and presented RMSECV?=?0.1963% (w/w). The proposed method presents advantages such as a small-required amount of sample for spectrum achievement, no sample destruction, and a high analytical frequency.     

Mid-infrared spectroscopy as a tool for rapid determination of internal quality parameters in tomato

The objective of this study was to investigate the possibility of predicting the quality parameters of tomato by mid-infrared spectroscopy. For 2 years, tomato samples, representing a large variability in the chemical composition, were scanned using the attenuated total reflectance accessory of a Fourier transform spectrometer in the wavenumber region between 4000 and 400 cm⁻¹_. Calibration models were developed using partial least squares (PLS) regression method and were tested with internal validation sample set in the first year. Different spectral preprocessing techniques were investigated and different spectral regions were selected to optimise the calibration models. In addition, the models obtained in 2007 were used to predict the soluble solids, dry matter and total acidity in tomato harvested in 2008.     

Use of Fourier transform infrared spectroscopy for rapid comparative analysis of Bacillus and Micrococcus isolates

The identification of foodborne microorganisms and their endospores in food products are important for food safety. The present work compares Bacillus (Bacillus licheniformis, Bacillus circulans and Bacillus subtilis) and Micrococcus (Micrococcus luteus) species with Fourier transform infrared (FTIR) spectroscopy. Our results show that there are several characteristic peaks belonging to both the Micrococcus and Bacillus species which can be used for the identification of these foodborne bacteria and their endospores. For Micrococcus species, a new band was observed at 1338 cm⁻¹ which may be due to acetate oxidation via the carboxylic acid cycle. The bands at 1313 cm⁻¹ and 1256 cm⁻¹ can be explained by an exopolymer formation and the other bands at 1074 cm⁻¹ and 550 cm⁻¹, may be due to the glycogen-like storage material in Micrococcus spp. There are also characteristic peaks at 993 cm⁻¹ and 801 cm⁻¹ for these bacterial species. Different Bacillus species also showed characteristic peaks at 1000–500 cm⁻¹ region. Dipicolinic acid (DPA) bands at ∼728 cm⁻¹ and ∼703 cm⁻¹ seen only in B. circulans were the marker of an endospore formation.     

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.     

The determination of frying oil quality using Fourier transform infrared attenuated total reflectance

The possibility of using the whole spectra (wave numbers between 4000 and 850 cm⁻¹) from Fourier transform infrared attenuated total reflectance spectroscopy (FTIR-ATR) to differentiate between good, marginal and unacceptable oils with regard to various intensities of oil rancidity was investigated. Fresh, used, and discarded oils were collected from several fast food restaurants from each frying cycle for 4 weeks. Dielectric constant, peroxide value, free fatty acid content, and density of oil samples significantly (P<0.01) increased with frying time. The correlation (r) between FTIR absorbance at 3300 cm⁻¹ and free fatty acid content was from 0.84 to 0.94 for oils from the three restaurants. Similarly, the correlation between FTIR absorbance at 3471 cm⁻¹ and peroxide value was from 0.90 to 0.97. The results of principal component analysis using the whole spectra (4000-850 cm⁻¹) showed good discrimination and stability for identification between acceptable, marginal and unacceptable frying oils.