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Cultural fibrous material includes both important categories, i. e. textile and paper, consisting of precious cultural materials in museum, such as costume, painting, and manuscript. In recent years more and more connoisseur and conservator's concerns are, through nondestructive method, the authenticity and the ageing identification of these cultural relics especially made from fragile materials. In this research, we used attenuated total reflection infrared spectroscopy to identify five traditional textile fibers, alongside cotton, linen, wool, mulberry silk and tussah silk, and another five paper fibers alongside straw, wheat straw, long qisong, Chinese alpine rush and mulberry bar, which are commonly used for making Chinese traditional xuan paper. The research result showed that the animal fiber (wool, mulberry silk and tussah silk) and plant fiber (cotton and linen) were easier to be distinguished by comparing the peaks at 3 280 cm-1 belonging to NH stretching vibration and a serious peaks related to amide I to amide III. In the spectrum of wool, the peak at 1 076 cm-1 was assigned to the S-O stretching vibration absorption of cystine in wool structure and can be used to tell wool from silk. The spectrum of mulberry silk and tussah silk seems somewhat difficult to be identified, as well as the spectrum of cotton and linen. Five rural paper fibers all have obvious characteristic peaks at 3 330, 2 900 cm-1 which are related to OH and CH stretching vibration. In the fingerprint wavenumber range of 1 600 - 800 cm, the similar peaks also appeared at 1 370, 1 320 cm-1 and 1 162, 1 050 cm-1, both group peaks respectively are related to CH and CO vibration in the structure of cellulose and hemicellulose in paper fibers. Although there is more similarity of the infrared spectroscopy of these 5 paper fibers, some tiny difference in absorbance also can be found at 3 300 cm-1 and in the fingerprint range at 1 332, 1 203, and 1 050 cm-1 which are related to C-O-C vibration in cellulose. Moreover, in order to explore direct and simple method to identify different materials with similar spectrum,. the principal component analysis (PCA) was applied to separate cotton and linen, mulberry silk and tussah silk, as well as five paper fibers. To eliminate and reduce the spectral scattering caused by sample uneven surface roughness, the multiplicative scatter correction (MSC) has been applied based on total spectral data. The result showed that the score plot using the first two principal components can effectively categorize both group textiles of cotton and linen, as well as mulberry silk and tussah silk, and they have similar chemical structure. For five paper fibers, the PCA was applied in different spectral range (918-550, 1 280-918, 1 700-1 280 and 3 800-2 800 cm-1), and the best result appeared in the range from 3 800 to 2 800 cm-1, in which the five paper fibers can be well categorized. This research showed that infrared spectroscopy combined with principal component analysis has great potential advantage on identifying fibrous materials with similar structure.

The gas chromatograph (GC)-infrared spectroscopy (IR) technique combines the particular separating capacity of GC and the faultlessly with distinguishing capacity of molecular structure of IR, its detective sensitivity is very high and itis used to separate and identify many kinds of complicated compounds from element speciation analysis, natural products, and gasoline. This paper introduces the principle of GC-IR. Three types of interface techniques, light pipe technique, matrix isolation technique and direct deposition technique are compared. Connection type with other detections and factors influencing sensitivity in interface are also introduced. The improvement and achievement in coupling GC system, interface, data processing techniques and its application is reviewed in the present paper.

A real-time infrared (IR) spectroscopy measurement is an effective means to obtain enzymatic information either in vitro or in living cells, as it can provide direct, continue test of biomacromolecule reactions. The principles of measurements are performed basing on the fact that the absorption bands in spectra of reactants and products are usually separated to each other and changed independently with time. Therefore, it is possible to measure the enzymatic efficiency at any reaction time according to the changes of characteristic band, from either reactant or product. That is, IR spectroscopy can be used to obtain intracellular structural information during the cells metabolic processes, as which can provide detailed and reliable scientific evidences. In this paper, we summarized the new developments of IR spectra in the in vitro enzymatic assay for several representative enzymes, as well the screening of enzyme inhibitors, which was further extended to the identical aspect by using living cells as detection model. Such important enzymatic examination closes to the physiological conditions without labeling, supplying structural information of the related biomolecules. The developing trends of IR spectra are discussed and the perspectives of it in the research area are also provided in this review.

Infrared spectroscopy (IR), the normal Raman spectroscopy (NRS) and the surface enhanced Raman spectroscopy (SERS) in new Ag/Cu nanomaterial of Rotundine were studied in the present paper. The IR and the NRS of Rotundine were calculated by the density functional theory (DFT) using B3LYP/6-311+G(d, p), then the spectral intensity graph of Rotundine were given. The vibrational peaks were assigned comprehensively by the visualization software of Gauss view 5. 0. Rotundine has obvious infrared and Raman vibrational peak in the wave number range of 3 300-2500 and 1 800-600 cm(-1). SnCl2 and PVP was used as capping agent for the silver nanoparticles in SERS of Rotundine. Finally, by using the method of cyclic immersion well dispersed silver nanoparticles was obtained and achieved good enhancement effect. This molecule acquired strong selective enhancement vibration peak, In the wave number ranges of 1 500-1 400 and 1 000-700 cm(-1) the enhancement effect is most obvious. After analyzed, the methylene of this molecule is adsorbed on the silver nanoparticles surface and the angle between the benzene ring and the silver substrate is close to 90 degrees. The theoretically calculated spectra of Rotundine are consistent with the obtained experimental spectra. There are some differences may be due to the interaction forces between molecules and so on. The visualization software displayed the structure characteristics and molecular group vibration of this molecular visually and provided important basis for assigning the vibrational peaks. Rotundine is an important traditional Chinese medicine agent contained in many kinds of sedative drugs. The study provides a strong basis for the rapid, feature and trace identification of Rotundine and also supplies important reference for the biological role of central inhibition of analgesic drugs.

The feasibility of protein determination of shiitake mushroom (Lentinus edodes) using mid-infrared spectroscopy (MIR) was studied in the present paper. Wavenumbers 3 581-689 cm(-1) were used for quantitative analysis of protein content after removing of the part of obvious noises. Five points Savitzky-Golay smoothing was applied to pretreat the MIR spectra and partial least squares (PLS) model was built based on the pretreated spectra. The full spectra PLS model obtained poor performance with the ratio of prediction to deviation (RPD) of only 1.77. Successive projections algorithm (SPA) was applied to select 7 sensitive wavenumbers from the full spectra, and PLS model, multiple linear regression (MLR), back-propagation neural network (BPNN) and extreme learning machine (ELM) model were built using the selected sensitive wavenumbers. SPA-PLS model and SPA-MLR model obtained relatively worse results than SPA-BPNN model and SPA-ELM model. SPA-ELM obtained the best results with correlation coefficient of prediction (R(p)) of 0.899 5, root mean square error of prediction (RMSEP) of 1.431 3 and RPD of 2.18. The overall results indicated that MIR combined with chemometrics could be used for protein content determination of shiitake mushroom, and SPA could select sensitive wavenumbers to build more accurate models instead of the full spectra.

Glucose specificity is the premise of spectroscopic measurements of blood glucose concentration, and it is also paramount for feasibility study of a spectral measurement method. Two-dimensional correlation spectroscopy technology is widely used in many fields such as inter-/intra-molecular reaction, material phase transition and information extraction because of its high resolution and effective Noda's rule. In the present paper, the glucose specificity for noninvasive glucose measurements by mid-infrared spectra based on the 2D correlation spectroscopy was investigated. First, the feasibility of this method was validated by a series of in vitro experiments of glucose. Then the in vivo experiments of four volunteers were conducted and the characteristic information of glucose by mid-infrared spectra collected from human fingers was confirmed by 2D correlation spectroscopy analysis.

In noninvasive blood glucose measurement, it is difficult to keep the contact area between skin and internal reflectance element uniform while the mid-infrared spectra of human skin are taken, and this would lead to path-length variations. To study the effect of path-length variations on PLSR calibration model, in the present paper, according to the correlation coefficients between path-lengths and glucose concentrations, two PLSR models were achieved respectively and RMSECV were 31.3 and 4.52 mg x dL(-1), RMSEP were 30.3 and 98.7 mg x dL(-1) for the validation set. The results show that the chance correlations between path-lengths and glucose concentrations will lead to calibration models with different accuracy and robustness. This is useful to improving the reliability of noninvasive measurement of blood glucose by mid-infrared spectroscopy.

The skin temperature distribution of a healthy human body exhibits a contralateral symmetry. Some lesions of facial nerve function are associated with an alteration of the thermal distribution of the human body. Since the dissipation of heat through the skin occurs for the most part in the form of infrared radiation, infrared thermography is the method of choice to capture the alteration of the infrared thermal distribution. This paper presents a new method of analysis of the thermal asymmetry named effective thermal area ratio, which is a product of two variables. The first variable is mean temperature difference between the specific facial region and its contralateral region. The second variable is a ratio, which is equal to the area of the abnormal region divided by the total area. Using this new method, we performed a controlled trial to assess the facial nerve function of the healthy subjects and the patients with Bell's palsy respectively. The results show: that the mean specificity and sensitivity of this method are 0.90 and 0.87 respectively, improved by 7% and 26% compared with conventional methods. Spearman correlation coefficient between effective thermal area ratio and the degree of facial nerve function is an average of 0.664. Hence, concerning the diagnosis and assessment of facial nerve function, infrared thermography is a powerful tool; while the effective ther mal area ratio is an efficient clinical indicator.

The purpose was to achieve the identification of Muscat Hamburg wines produced in Tianjin region through scanning and analyzing dry white wine samples of different grape varieties and regions by infrared spectroscopy technology. A support vector machine (SVM) based method was introduced to analyze infrared spectra of dry white wines. The pretreatment processes of the IR spectra were also elaborated, including baseline adjustment, noise Elimination, standard normalization and eliminating the main component of abnormal sample points. The authors selected great quantity of dry white wine samples of different grape regions including 511 Muscat Hamburg wine samples, 438 Italian Riesling wine samples, 307 Chardonnay wine samples, 29 Ugni Blanc wine samples, 44 Rkatsiteli wine samples, 31 longan wine samples and 79 ZeHong wine samples. According to different classification problems, 80% of IR spectra of the wine samples were used to establish discrimination models with SVM-based method, and the remaining 20% of IR spectra were used for the validation of the discrimination models. Experimental results showed that the proposed method is effective, since high classification accuracy, identification rate and rejecting rate were achieved: over 97% for the white wine samples of different grape varieties, meanwhile over 98% for the Muscat Hamburg wine samples produced in different regions. So the method developed in this paper played a good role in the qualitative classification and discrimination of Muscat Hamburg wines produced in Tianjin region. This novel method has a considerable potential and a rosy application future due to the expeditiousness, stability and easy-operation of FTIR method, as well as the veracity and credibility of SVM method.

For the rapid detection of the ethanol, pH and rest sugar in red wine, infrared (IR) spectra of 44 wine samples were analyzed. The algorithm of fast independent component analysis (FastICA) was used to decompose the data of IR spectra, and their independent components and the mixing matrix were obtained. Then, the ICA-NNR calibration model with three-level artificial neural network (ANN) structure was built by using back-propagation (BP) algorithm. The models were used to estimate the contents of ethanol, pH and rest sugar in red wine samples for both in calibration set and predicted set. Correlation coefficient (r) of prediction and root mean square error of prediction (RMSEP) were used as the evaluation indexes. The results indicate that the r and RMSEP for the prediction of ethanol content, pH and rest sugar content are 0.953, 0.983 and 0.994, and 0.161, 0.017 and 0.181, respectively. The maximum relative deviations between the ICA-NNR method predicted value and referenced value of the 22 samples in predicted set are less than 4%. The results of this paper provide a foundation for the application and further development of IR on-line red wine analyzer.

As one of new optical detection methods, near-infrared spectroscopy (NIRS) technique has been widely used in food industry in recent years. NIRS technique is also promising for quality evaluation of meat and meat products and is characterized by its quickness, online operation and nondestructive detection. The present paper reviews the main application and recent development of research on near-infrared spectroscopy in meat industry, including components analysis, sensory quality evaluation as well as discrimination of production. It's necessary to determine the content of main chemical components in a variety of meat such as protein, fat, water etc as they exert important influence on meat quality. Sensory quality including tenderness, water holding capacity, color, and freshness is commonly evaluated by human sensory system. Thus there is an obvious potential profit to achieve online determination industrialization for meat quality. Additionally the utilization of NIRS in quality detection of common meat products is particularized in this paper. Most study of near-infrared spectroscopy technique for meat quality evaluation lays emphasis on component analysis that especially has shown a progress in the determination of protein, fat, water and part of fatty acid, which has been investigated much recently. Not any kind of sensory quality can be well predicted by NIRS as it depends on the species of meat and the limitation of this optical technique. Therein beef is the mostly used object with many reports on the evaluation of tenderness compared to other types. There is a lot of investigation for sensory quality detection of pork on water holding capacity etc. Meanwhile this review also tries to come up with some perspectives on meat quality detection with near-infrared spectroscopy according to current development trend: on the basis of deeply improving the meat detection precision, near-infrared spectroscopy technique combined with other non-detection techniques like machine vision will be investigated in order to realize overall evaluation of meat quality.

In the present paper, NMR spectroscopy, an effective tool to detect the variation in, molecular structure and changes in chemical composition of metabolites in tissues, was used to study the differences between malignant and normal tissues from rectum. 1H and 31P spectra of seven malignant rectum tissue samples and five normal control tissues were investigated by using a 300 M NMR spectrometers and compared with the results of the infrared spectra of normal and malignant rectum organ tissues. The results indicate that the 1H and 31P spectra of rectum cancer tissues are significantly different from those of the normal controls and most differences present in the form of variation in relative intensities of the characteristic peaks of various metabolites. Systematic differences in the NMR spectra between malignant tissues and normal controls are as follows: in the 1H NMR spectra, differences lie in fatty acids with the concentration of fatty acid decreasing significantly in malignant tissues. In the 31P NMR spectra, differences lie in phospholipid, with the chemical shift of phospholipid decreasing significantly in malignant tissues. This phenomenon may reflect the fact that the activity of protein synthesis is enhanced in cancerous tissues. The difference in the chemical shift of phospholipid between normal rectal tissue and malignant tissue may be considered as a detection criterion. Therefore, the above spectral variations in 31P NMR spectra may be utilized as a potential tool to diagnose rectum cancer.

To improve the thermal stability of poly (lactic acid), poly (lactic acid-co-phenylalanine) was prepared by introducing the phenyl of phenylalanine to the side chain. 3-phenylmethyl-2,5-morpholinedione (PMD) and lactide (LA) were synthesized using phenylalanine and lactic acid as raw materials, respectively. Subsequently, poly (lactic acid-co-phenylalanine), homopolymer of PMD (PPMD) and homopolymer of LA (PLA) were obtained by ring-opening polymerization of PMD and LA as monomer. The amount of phenyl had an effect on the thermal stability, so a quantitative analysis by infrared spectroscopy was established in the present paper. Two homopolymers were determined by infrared spectroscopy to find out two characteristic peaks at 1 671.53 and 870.82 cm(-1), which were selected for PPMD and PLA, respectively. Choosing the characteristic peaks and according to the Lambert-Beer law, which is the linear relationship between absorbance and concentration of an absorbing species, a standard working curve was calculated: y = 0.055 67x + 0.109 1 (r = 0.999 3), where x was the reciprocal of PPMD monomer molar concentration and y was the absorbance ratio of PLA to PPMD at their characteristic peaks. Collecting the absorbance of poly (lactic acid-co-phenylalanine) at two characteristic peaks, the contents of copolymer were calculation by the working curve and the results were similar to that of 1H NMR by calculation from the ratio of proton area of PMD and PLA. It was noted that the relative error was below 2%. It was also confirmed that the content of copolymer could be determined by infrared spectroscopy conveniently and quickly. Meanwhile, this method could be adopted to determine the other poly (lactic acid-co-amino acid) practicably and widely.

A novel classifier was constructed in the present paper by combination of an improved canonical variates analysis (ICVA) with Fish linear discriminant analysis (LDA). The resulting discrimination model based on this proposed approach (ICVA-LDA) was divided into two parts: the inner part that estimated the robust weight vector of canonical variates by linear partial least square algorithm and the outer part that built the LDA discrimination model by making use of the extracted canonical variates. The method utilized partial least squares regression as an engine for solving an eigenvector problem involving singular covariance matrices and the canonical variates were more relevant for discriminative purposes. Thus, the weight vectors found in the modified CVA method not only possessed the same properties as weight vectors of the standard CVA method, but also forced the discriminative information into the first fewer of canonical variates. The improved discrimination model was more concise and efficient in dealing with the problem of the effect sensitivity and numerous predictor variables with serious multicollinearity in the spectra data. Furthermore, in ICVA-LDA the interpretation could be performed with respect to the original high-dimensional data space. Finally, application to a four-group problem with near-infrared transmittance spectroscopy data consisting of 310 samples and 404 variables of the proposed ICVA-LDA approach was presented with comparison to the LDA combined with principal component analysis (PCA-LDA) and standard CVA-LDA methods. All the three discrimination models were validated using fivefold segmented cross-validation. The result demonstrates that the limitations of LDA were overcome with PLS algorithm and then the classification performance of LDA was improved by ICVA. This proposed approach can also be widely used in other fields for classification and discrimination of small samples and collinear data.

Forage was the material basis of animal husbandry production, and its quality is directly related to the quality of animal products. It was very important to control the forage quality and detect the composition of forage raw materials in forage production. Predication of forage quality was often completed by the traditional and classical methods in the past, which were complex, time consuming and expensive, and could not acquire the nutritional value of forage timely. Near infrared reflectance spectroscopy was a highly efficient and rapid modern analysis technique developed in 1970's. It comprehensively applied the latest research results of computer technique, spectroscopy and chemometrics, and has been widely used in various fields owing to its unique advantages such as being timely, less expensive, non-destructive, and so on. Near infrared reflectance spectroscopy has gained more and more importance though its application to forage analysis was very late. Presently, not only conventional composition (such as moisture, dry matter, crude protein, crude fiber, crude fat, crude ash neutral detergent fiber, acid detergent fiber, etc.), but also non-conventional composition (including minerals, trace elements, enzyme and anti-nutritional factors etc. ) and anti-nutritional factors in forage were determined by means of near infrared reflectance spectroscopy. Testing and analyzing the conventional composition in forage was the traditional applied field of near infrared reflectance spectroscopy, a lot of studies of which were done and it has already been one of the standard methods of testing the conventional composition. Forage bioavaibility was also evaluated by near infrared reflectance spectroscopy, so as to assess the utilization rate and nutritional value of forage. Moreover, near infrared spectroscopy could be used successfully to predict the botanical composition in grassland and leaf/stem ratios. Near infrared spectroscopy technique and its application and prospect in forage analysis were reviewed in the present paper.

Spectroscopy technique is one of the qualitative and quantitative analytical techniques developed quickly in recent years. The spectral analysis is a fast and non-destructive method and has been used in many fields such as oil industry, food industry and so on. In the present paper, the spectral band sensitive to soil moisture content was found from the visible/near infrared spectra and a monadic linear regression model based on the data of sensitive spectral band was applied to develop a method for rapid detection of soil moisture content. The spectral data of 52 soil samples were collected by using FieldSpec HandHeld spectroradiometer made by ASD (Analytical Spectral Device) company in the US, and the data of soil moisture content were obtained by experiment. The spectral band sensitive to soil moisture content was achieved by correlation coefficient method. Then, the data of sensitive spectral band were used to build monadic linear regression model of soil moisture content. Finally, the model was employed for the prediction of soil moisture content. Correlation coefficient (r) of prediction and root mean square error of prediction (RMSEP) were used as the evaluation standards. The results indicated that the r and RMSEP for the prediction of soil moisture content were 0.966 5 and 0.012 1 respectively. Thus, it is concluded that the method used in this paper is an available method for the rapid detection of soil moisture content based on the visible/near-infrared spectra.

For modeling the nonlinear relationship existing between samples' near infrared (NIR) spectra and their chemical or physical properties, a novel modeling method was put forward in the present paper, which builds model by combining Isomap and partial least squares (PLS). Isomap is a newly proposed nonlinear dimension reduction algorithm, and belongs to the algorithm family of manifold learning, which is a new branch of machine learning. Isomap is based on multidimensional scaling (MDS) algorithm; however, it replaces the Euclidean distance in MDS with an approximated geodesic distance, so it can effectively find out the intrinsic low dimensional structure from high dimensional data. By combining Isomap and PLS, refered to as Isomap-PLS, a novel nonlinear modeling method for NIR spectra analysis was proposed. In this method, Isomap was used to extract nonlinear information from high dimensional NIR spectra while keeping the invariance of geometric property, and then PLS was adopted to remove linear information redundancy and build a calibration model. The parameters of the Isomap, i.e. the number of the nearest neighbor k and output dimension d, can affect the performance of the method. In this paper, a grid search approach was used for parameter optimization. The Isomap-PLS modeling method was applied to two public benchmark NIR datasets, and the modeling results were compared with that of PLS. The results demonstrated that in both datasets, each model built with Isomap-PLS had a smaller rooted mean square error of cross-validation (RMSECV) than the corresponding model built with PLS. Moreover, for some properties, the RMSECV of Isomap-PLS was significantly reduced by a factor of 2-5 compared with that of PLS. It can be concluded that by taking the virtue that Isomap can reflect the intrinsic nonlinear structure of NIR spectra, Isomap-PLS can effectively model the nonlinear correlations between spectra and physicochemical properties of the samples, and so it gains more power in calibration and prediction than PLS.

Near infrared reflectance spectroscopy is a new developed method able to analyse the content of specific compound in the detected sample quickly and efficiently, and has been wildly used in many fields such as evaluation of nutrition value of forage, cultivar discrimination and so on. In the present paper a new method was developed for the discrimination of salt tolerance of alfalfa cultivars by Fourier transform near infrared reflectance spectroscopy. Firstly absorbance spectrum generated by Fourier transform near infrared spectrometry was used to classify twenty alfalfa cultivars. These cultivars were obviously clustered into two groups: salt tolerant and salt sensitive, similar to the result, screened by the traditional methods. Based on these results, a discrimination model was built for identification of salt tolerant cultivars. And then, six other cultivars were used to verify the function of the discriminating model. Result showed that the distinguishing rate of 100% was achieved with the performance index of 85.7%. It is concluded that Fourier transform near infrared spectrum is useful for classification and discrimination of salt tolerance of alfalfa cultivars. The method can be applied to estimate salt tolerance of alfalfa cultivars, and works more quickly and efficiently than the traditional screening methods. Application of Fourier transform near infrared spectrum to discriminating salt tolerance of alfalfa cultivars is significant in both academic and technical areas.

The present paper constructs a new approach named local straight-line screening (LSLS) to detect Chinese proprietary medicines (CPM) containing undeclared prescription drugs (UPD). Different from traditional methods used in analysis of multi-component spectrum, LSLS is proposed according to the characteristics of original infrared spectra of the UPD and suspected CPM, without any pattern recognition or concentration model establishment. Spectrum-subtraction leads to the variance in local straight line, which serves as a key in discrimination of whether suspected CPD is adulterated or not. Sibutramine hydrochloride, fenfluramine hydrochloride, sildenafil citrate and lovastatin were used as reference substances of UPD to analyze 16 suspected CPM samples. The results show that LSLS can obtain an accurate quantitative and qualitative analysis of suspected CPM. It is possible for the method to be potentially used in the preliminary screening of CPM containing possible UPD.

The root of scutellaria baicalensis georgi that contains a variety of flavonoids is a very old and well-known drug in traditional Chinese medicine, which is widely used for treatment of bronchitis, tumors and inflammatory diseases. The baicalein is the main active component from traditional Chinese medicine-scutellaria baicalensis georgi. It is a very significance research work that the baicalein was separated and purified, and its composition and molecular structure are analyzed and determined for the pharmacology study of Chinese medicine-scutellaria baicalensis georgi. The main works in this paper are as follows. Powdered roots (100 g) were extracted with methanol by three times, each time for 48 hours. The crude extracts were purified by polyamide column chromatography and CH3Cl-C2H5OH gradient desorption. A short yellow prismatic crystal was acquired by recrystallizing technique and its composition and molecular structure were characterized by color reactions and spectral analysis methods as FTIR, UV-Vis, MS and 1H NMR, 13C-NMR. The FTIR spectrum appears the absorption bands for hydroxyls, pyrone carbonyl, aromatic C=C bond and singly substituted phenyl. The characteristic absorption peaks and the vibration modes in FTIR spectrum were identified as corresponding groups. The UV-Vis spectrum in methanol solution and the mix solution of methanol with 5 diagnostic reagents, NaOMe, NaOAc, NaOAc/H3BO3, AlCl3, AlCl3/HCl, respectively indicate that the yellow prismatic crystal is flavone with 5-hydroxyl, 4-carbonyl and 5,6,7- or 5,7,8-trihydroxyls on ring A. The structure of the crystal was characterized by three different MS. The results of FAB-, ESI- and EI-MS show that it is not a flavone glocuside but the flavone with three phenyl hydroxyls on ring A, and no OH group and other substituted groups on ring B. The molecular ion and fragment ions are identified by MS, which include such as m/z 270 M+, m/z 242 [M-CO]+, m/z 168 A, m/z 140 [A1-CO]+, m/z 105 B, m/z 102 B, m/z 77 [B2-CO]+, respectively. 13C-NMR (DMSO-d6) exhibits the signals of the fifteen carbon atoms, nine oxygenous aromatic C, five non-oxygenous aromatic C and a carbonyl C. 1H-NMR(DMSO-d6 + D2O, DMSO-d6 )indicates the presence of C-5, C-6, C-7 hydroxyl protons, which is consistent with the results of UV spectrum. The signals for C-2',6' hydroxyls appear at delta = 8.055 as a doublet peak with spin-spin coupling constant 6.0 Hz. The other signals were ascribed to the corresponding H or C atoms in the compound. The results of FTIR, UV-Vis, MS, 1H NMR, 13C-NMR spectroscopy characterization show that crystal is the 5,6,7-trihydroxy-flavone, that is baicalein, and the molecular formula is C15H10O5.

For the non-invasive blood glucose concentration sensing by the near-infrared spectroscopy, the signal to noise ratio of the optical measurement system is very low. Both the content of glucose in body and the absorption coefficient of glucose in the near-infrared region are quite weak. More over, the structure of spectral noise is complicated and the variation of noise intensity is very large. The background correction is one of the most effective pre-processing methods to improve the signal to noise ratio of the near-infrared optical detection system. In this paper, the theory expression formula of traditional background correction method was induced firstly. Then in order to avoid the influence from the variation of optical characteristics in the sample and the drift in the optical system, the similar background correction method was proposed, that is, the background which has the similar optical characteristics with the sample was chosen as the reference. The in vitro experiments of pure absorption media and scattering media were conducted to validate the effect. The results showed that, for the glucose in the blood plasma solution and Intralipid-2% solution, after the correction of the background which has the similar optical characteristics with the sample, the prediction precision of multivariate model for glucose concentration has been improved by 25.9% and 40.1%, respectively.

Regarding raw drugs of the different habitat and the different cultivation condition, its treatment efficacy is different. This is because they contain different chemical composition and different ingredients content proportion, which causes the difference in their infrared spectra. But these differences are extremely slight, and purely differentiating their characteristics from the infrared spectra is extremely difficult. In the present paper, the samples of epimedium brevicornu from different fields of Jilin province were surveyed by Fourier transform infrared (IR) spectra, and the corresponding pretreatment to the spectra data was carried out. Before establishing model through the artificial neural networks, in order to enhance the training speed of the ANN, the spectra variables were compressed through the wavelet transformation, and the parameters of the ANN model were also discussed in detail. The model can distinguish the producing area of the 42 samples of epimedium brevicornum correctly, avoiding the separation and drawing of raw drugs with traditional spectroscopy analysis at the same time, thus offer an effectively and reliable basis for the quality controls and modernized management of Chinese medicine.

Infrared spectroscopy technique is a rapid for the discrimination of food samples, and is widely used to detect and discriminate various beverages. This paper presents the advantages and disadvantages of techniques that have been used to discriminate alcoholic beverages, and the discriminating procedure with infrared spectroscopy technique. Applications of infrared spectroscopy technique to wine, whiskey, Japanese sake and Chinese rice wine etc. is presented too. Finally, problems in applications are analyzed, and the application of infrared spectroscopy technique to the discrimination of our traditional alcoholic beverages is prospected.

In the present paper a method for identifying and evaluating traditional Chinese medicine (TCM) Jinkuishenqi pill and Guifudihuang pill samples is proposed. Mathematical statistics was applied to analyze the dual index sequences of infrared fingerprint spectra of components extracted from Jinkuishenqi pill and Guifudihuang pill samples with water, then the grade sequences were determined and the first and second clusters were performed based on these grade sequences. As a results, the most similar sample groups of different samples were also obtained. The Jinkuishenqi pill and Guifudihuang pill samples can be distinguished accurately with the most similar sample groups. The method put forward is new and effective to identify and evaluate combinational TCM quantitatively.

In the present paper, citric acid, acetic anhydride, polyethyleneoxide nonyl phenyl ether and diethanolamine were used as raw materials. The raw materials were purified, and the intermediate products were synthesized. Finally, the citric acid mono polyethyleneoxide nonyl phenyl ether amber diehylene glycol dinitrate diglycollic amide was made. The acidamide of the product synthesized was determined by IR. There is a characteristic peak of C=O in acidamide at 1 642.39 cm(-1). Using potassium rhodanate as a internal standard, and according to Lambert-Beer law, a method to determine the citric acid mono polyethyleneoxide nonyl phenyl ether amber diehylene glycol dinitrate diglycollic amide was developed. The linear regression equation is A = 0.007 6m+0.325 6 with a correlation coefficient (r2) of 0.998 9. The experimental results of the precisions and recoveries are satisfied. The method is very necessary for confirming the reaction extent and controlling quality of citric acid mono polyethyleneoxide nonyl phenyl ether amber diehylene glycol dinitrate diglycollic amide. So, the synthesis process conditions were right according to the IR data.

The research on the technology of infrared absorption spectrum and its application plays an important role in the development of technology of optical measurement. The analysis technology of blood infrared absorption spectrum is presented in the present paper. By comparison between and analyzing the infrared absorption spectra of the normal blood sample and the high cholesterol blood sample, the differences were obtained. The infrared absorption spectra of normal blood serum and high cholesterol blood serum were detected, and the differences between the spectra are presented. The analysis results indicate that the differences of the absorptivity, the absorption peak position and the absorptivity ratio between the normal blood sample and the high cholesterol blood sample can be taken as a criterion to check the normal and abnormal blood sample. This work, valuable for application, provides an important reference for the diagnosis of diseases.

In the present paper, a hapten of methamidophos was synthesized and conjugated with KLH by active ester method, thus the first artificial antigen was obtained. By diazotization method methamidophos conjugated with BSA, and the second artificial antigen was obtained. The synthesized haptens were characterized by MS, IR and 1H NMR, and the two artificial antigens were determined by the method of IR spectrum. The result implied that both the artificial antigens have absorbance peaks of hapten and protein, indicating that they were prepared successfully. This could provide evidence that the method of IR spectrum can be used to determine whether the artificial antigens are synthesized successfully.

Infrared spectroscopy is well suited for the rapid and nondestructive identification and quantification of traditional Chinese medicine (TCM) for its high resolution, easy operation and strong specialization of absorbance bands. It is becoming an efficient methodology in the quality control of TCM. The present paper reviews the applications of infrared spectrometry in the qualitative and quantitative analysis of TCM, especially to the discrimination and effective content determination of traditional Chinese medicinal materials (including different parts of the same medicinal material, TCM from different geographical areas, easily confusing TCM, and true and false TCM) and Chinese patent medicine (such as TCM formula particles, injections, etc.). With the ceaseless rapid development and popularization of FTIR spectrometer and computer science, infrared spectrometry will greatly accelerate the process of TCM modernization and internationalization by all means.

The vibrational spectra of thymine were predicted by density functional theory (DFT). In the calculation B3LYP complex function, and diffuse function and polarization function were added to heavy atoms and light atoms. Taking the effects of H-bonds into consideration, the authors added two water molecules in our calculation and simulated the case of forming H-bonds in crystal thymine. Whilst the Raman and infrared spectra of thymine were recorded, and the spectra of thymine calculated from DFT agree with the experimental results. The calculation results in the present paper are more approximate to the experimental data than ever reported. The vibrational modes of thymine were assigned.

In this paper, the authors have reviewed their investigation on the clinical detection of tumor tissues by infrared spectroscopy in recent ten years. Based on the comparison of different IR spectroscopic methods such as IR transmission spectroscopy, micro-IR spectroscopy etc, the authors found the good consistency of the results of ATR (attenuated total reglection) IR spectroscopic method with those of pathological biopsy. The authors have directly measured the IR spectra of frozen tissues stored in liquid nitrogen and freshly resected tissues, and have realized the measurement of tumor tissues in vito during the operation process using a specially designed IR spectrometer connected with a mid-IR fiberoptic with an ATR probe. The authors have investigated the malignant and normal tissues including parotid, esophagus, stomach, colon, liver, gallbladder, breast, thyroid etc. and compared with the pathological results. The accuracy of this novel IR detection method is more than 90%.

Takagi-Sugeno fuzzy system is composed of several back-propagation neural networks (BP-NNs), and has some fuzzy logic properties. In this paper, the Takagi-Sugeno fuzzy logic system is applied to identifying official and unofficial rhubarb samples based on their infrared spectra. The effects of the number of hidden neurons and the momentum parameters on the prediction were investigated. The results obtained by using Takagi-Sugeno fuzzy system were better than those by commonly used BP-networks. With a proper network training parameter, 100% correctness can be obtained by using Takagi-Sugeno fuzzy system. This method is more accurate than the common methods, and is more scientific than traditional methods. So it is applied to identifying rhubarb easily and rapidly.

In this paper, a series of glucosamine-Zn(II) complexes were synthesized by the reaction of D-glucosamine hydrochloride with ZnSO4 at different pH values. The physical properties and the IR spectra of glucosamine-ZnSO4 complexes were investigated. The absorption at 3346 and 3292 cm(-1) shifted to 3300 cm(-1) due to O--H and N--H stretching, one at 1617 cm(-1) shifted to 1530 cm(-1) due to N-H stretching, and one at 1094 cm(-1) disappeared due to secondary alcohol --OH stretching. But 1033 cm(-1) with primary alcohol --OH did not shift, suggesting that both the amino and secondary hydroxyl groups of glucosamine are coordinated to Zn(II). The results showed that the coordination ability of Zn(II) to glucosamine was enhanced with the pH value increasing, however, the coordination ability weakened when pH value was more than 6.5. So pH 6.5 is an optimal coordination condition for glucosamine-ZnSO4 complexes. The complexes of D-glucosamine with different zinc salts (zinc sulfate, zinc nitrate, zinc acetate, and zinc chloride) were also synthesized at the same pH value, and zinc chloride had weaker coordination ability than other zinc salts. Their IR spectra indicated that glucosamine-Zn(II) complexes with different zinc salts had different coordination model, and only glucosamine-ZnSO4 complex had fixed ratio of coordination under the condition of pH 6.5. The structure of the complex seems to correspond to [Zn(glucosamine)]SO4 7H2O at pH 6.5.

In this paper, ZrO(OH)2 was prepared with sol-gel method, then a series of metal-ions-doped SO(2)4- /ZrO2 nanosolid superacids were prepared by impregnated ZrO(OH)2 using diluted H2SO4 and Ni2+ , Al3+, Sn4+, Ag+ , Sn2+ etc. salt solutions. The samples were characterized by IR, XRD, TEM and chemical analysis method. The result shows that the IR spectra of samples are the characteristic spectra of the solid superacids. The stretching frequencies of Zr--O and S==O in Ni2+ and Sn4+ doped samples are obviously increased, the v(Zr-o) values of Zr--O increase from 485 cm(-1) for SO(2)4- /ZrO2 to 500 cm(-1) for both Ni2+ and Sn4+ doped samples, the v(as) values of S==O increase from 1 390 cm(-1) for So(2)4- /ZrO2 to 1405 and 1400 cm(-1) for Ni2+ and Sn4+ doped samples respectively, but that in Sn2+ doped sample increases a little. It is indicated that the samples doped by Ni2+ and Sn4+ show higher super acidity than SO(2)4- /ZrO2 . The IR spectra of samples were determined at different calcination temperatures. It was found that the stretching frequencies of Zr--O and S==O in Ni2+ and Al3+ doped samples are obviously increased with the increase in calcination temperature, but that in Ag+ doped sample is not.

In this paper, the IR and UV-Vis spectroscopy of five novel alpha-isoxazoleazoxyl-beta-diketone derivatives with different structures have been studied, and their keto-enol and azo-hydrazone tautomeric phenomena have been discussed. It was found that all compounds, which are in the solid or in the solution, exist in the form of hydrazodiketo and azoenol isomers. The authors can also see that there are two absorption bands which are in the range 246-262 nm and 326-339 nm, respectively, for all compounds in the UV spectra, and the intensities of long wavelength absorption bands which are attributed to azoenol forms are stronger than short wavelength absorption bands which are attributed to hydrazodiketo forms. This shows that the quantities of azoenol forms in the compounds are more than hydrazodiketo forms, and it may be due to that the varieties of the azoenol isomers can easily form six-membered rings structure in the form of intramolecular hydrogen bonding, and make chemical structures more stable.

The detection of deterioration degree of ancient silk fabrics will be helpful to the selection and developing of conservation methods. This paper carried out some research on the deterioration extent and mechanism of silk fabrics by means of infrared spectrometry. The samples artificially aged and excavated from Hubei, Innermongolia and Qinghai province, were analyzed. The artificially aging was done by simulating three main natural aging factors: light, heat and hydrolysis. The infrared spectrometric analysis results show that although the infrared spectrometry is a half-quantitative analysis method, for the hydrolysis-aged silk fabrics, it can give good qualitative and better half-quantitative analysis results because of the increase of carboxyl. So the infrared spectrometric analysis is of practical value for the conservation state and aging mechanism studies of ancient silk.

In this paper, the mid-infrared Attenuated Total Reflection (ATR) spectra of two slathered pesticides dichlorvos and trichlorfon in vegetable juice solution have been investigated. It can be concluded that within characteristic absorption region of the two pesticides in the mid-infrared range, the pigments inside the vegetable have no effect on the pesticide' s absorbance; pesticides in standard solution and vegetable juice solution share almost the same absorbance characteristics. These results indicate that: the authors can use the model built by the absorbance data of pesticides in water solution to simulate their absorbance in vegetable solution, then based upon infrared spectroscopy, the direct detection of pesticide residue on the vegetable can be achieved; it also provides a possible way of rapid detection on vegetable in the future.

Standard BanXia (Pinellia temata (Thumb.) Breit) and false Shui BanXia (Typhonium flagelliforme (Lodd.) Blume) were identified fast and nondestructively by Fourier Transform Infrared Spectroscopy (FTIR) combined with two-dimensional correlation spectroscopy (2D) in this paper. The two kinds of BanXia wree similar to each other in one-dimensional IR spectra but quite different in 2D FTIR spectra. In the range between 1 220 cm(-1) and 1700 cm(-1), one strong autopeak was aroused by BanXia around 1410 cm(-1) in synchronous spectrum, whereas three autopeaks not only at 1460 cm(-1) but also at 1540 cm(-1) and 1680 cm(-1) aroused by Shui BanXia. Also in the range between 940 cm(-1) and 1220 cm(-1), three autopeaks were shown at 980, 1080 and 1150 cm(-1) in synchronous spectrum of BanXia, but only two autopeaks at 1080 and 1150 cm(-1) in synchronous spectrum of Shui BanXia. It is proved that the 2D FTIR could serve in distinguishing standard and false medicinal herbs due to its unique advantages such as enhanced resolution and increased identification ability. Therefore, the rapidity and accuracy of 2D FTIR spectroscopy make it a powerful and new approach to evaluating the medicinal herbs.

Fourier transform infrared spectroscopy (FTIR) combined with two-dimensional correlation spectroscopy was used to identify the different parts of Danggui in this paper. Guitou and Guiwei are two parts of the same officinal plant, and similar to each other in normal. FTIR spectra revealed the comparabilities of these two parts in herbal characters, organizing structure and alkaloid components. However, variance in amino acids and naphtha contents, which is aroused by the different parts of the angelica, could be identified easily and clearly in 2D FTIR spectra. Thus the fast and accurate property of 2D FTIR spectroscopy makes it a powerful and new approach to evaluating the medicinal herbs impersonally.

During the manufacture and debugging of the NIR instruments it is compulsory to make final calibration analysis to verify whether the instruments operate correctly. However, the conventional method of NIR calibration needs to make calibration analysis for the instruments with all the samples at hand. In fact in order to cover the samples that will be encountered in the future the amount of the samples set and the labor that the personnel need to offer are enormous. In this paper a new algorithm is presented which can be used to effectively eliminate the similar samples in the original sample set. By using this algorithm we have chosen 94 optimal samples in the original 178 sample set successfully. After performing calibration experiment we found that the sample set chosen by this algorithm are equally representative to the original sample set and obtained almost the same precision compared to the original sample set when the two sample sets were individually calibrated. This algorithm brings great relief to the labor of the workers, presents the possibility of performing more experiments and greatly improves the efficiency of performing calibration experiment. As a result, the amount of calibration sets and the labor of the personnel are reduced remarkably.

In the present paper, butyl acrylate and phenylethylene were used as monomers, benzoyl peroxide as evocator, n-butyl acetate and methylbenzene as solvent, a new type of solid-phase micro extraction adsorbent that is phenylethylene-butyl acrylate copolymer was synthesized by solution polymerization. The polymer has good behaviour for adsorbing arenas. According to Lambert-Beer law and some calculation process, the linear relation between the absorptance (y) of the two functional groups, which are benzene and ester, and the two monomers' mole ratio (x) was obtained. The absorptances were determined by IR. The standard curve was obtained by external standard method. The linear regression equation is y = 0.1362 + 0.0841x. The precisions and recoveries were investigated. RSD is 2.464%, and recoveries are 92.89%-103.94%. The results are satisfactory. This method is rapid and accurate.

Organic peroxides play an important role in chemistry of the atmosphere and in controlling urban air quality; however, accurate knowledge about their atmospheric reactions is lacking. In this paper, the experimental simulation was employed to study the atmospheric photo-oxidation of methyl hydroperoxide (CH3OOH, MHP), a key organic peroxide in the atmosphere. At the temperature of (292 +/- 2) K and pressure of 9.3 x 10(4) Pa (20% O2 + 80% N2), the MHP photo-oxidation was initiated by Cl-atom and the process of reaction was in-situ observed by long path Fourier transform infrared (Long Path FTIR) spectrometry. From FTIR spectra, the main products observed were formaldehyde (HCHO), formic acid (HCOOH), carbon monoxide (CO) and carbon dioxide (CO2), and minor methanol (CH3OH) was found as well. Within the reaction period of 60 min, yields were determined: 24% for HCOOH and 6% for CO; 50% for HCHO at its maximum concentration although its yield was varying with the reaction time. Finally, reaction mechanisms were discussed, which implied that MHP is a reservoir of odd-hydrogen radicals (HOx) and plays an important role in atmospheric photo-reactions.

In this paper, we employ correlation spectroscopy method to detect gases and gas mixtures which have multi-line absorption in near infrared. The theories of correlation spectroscopy are discussed and a new modulation measure is proposed, which inherits the excellence of the correlation spectroscopy and makes the modulation easy. Then we compare this method with the traditional correlation spectroscopy method. Experimental results for the selective detection of methane by this method are also presented. The change in signal from interference gas is only equal to 7.4% of that from methane absorption. It has been proven that the proposed method is practicable for both theory and experiment. This method can reach a high accuracy for mixed gas detection.

Based on the unique characteristic of spectral line center in the whole spectrum and noise threshold, a computer approach and program for the determination of spectral line position and relative intensity automatically are presented in this paper. Exploring this approach and computer program, we pre-analyzed the partially overlapped 16 line TuFIR experiment spectra of CHF3. The results of line positions and intensities for these TuFIR spectra are in excellent agreement with the results by least-square fit with heavily manual inference. The accuracy and efficiency of this method and program will ensure their wide application in complex high-resolution molecular spectrum.

In order to extract the quantitative features of the rare pollution components from noisy atmospheric infrared spectra and thus create calibration models, a wavelength selection method based on statistic theory is proposed in this paper. In this method, an objective function is defined based on the estimation of spectral noise level at every wavelength position. Because the size of the wavelength subset is also included in the function, the model size will not become too big during the minimization of the error of the calibration model. To test the performance of this method, the wavelength subsets of measured spectra with background noises were selected and the calibration models were then created using neural network technique for three pollution gases, respectively. The test showed that the sizes of the selected wavelength subsets accorded with the calculated results. The subset sizes were less than 2% of the total wavelength points. Meantime, the spectral noises were also restrained markedly in the calibration model because of the wavelength selection. The experimental results proved the validity of the wavelength selection method.

In this paper several kind of ion exchange fiber have be studies by micro infrared spectroscopy and the main absorption band are assigned.

As an important method to study the constitution and properties of macromolecular organic compounds, the infrared spectroscopy has been more and more widely taken in the researches of soil organic matters (SOM). Especially,the application of FTIR and the combined uses of FTIR with chromatogram etc. have made the researches of SOM get a great progress in many aspects. In this paper, the infrared spectroscopy applications were reviewed in SOM. It includes the following contents: the methods to study SOM by IR, studies on the constitution of soil humic substances (SHS), extraction of SOM and classification of SHS, decomposition, transformation and humification of organic matters, the differences of SOM in different situations, the interactions of SHS with metais, clay minerals and other organics in soil.