Classification of Guizhou Aspidistra Plants by Near-infrared Diffuse Reflectance Spectroscopy

[Objective] This study was conducted to establish a near-infrared diffuse reflectance spectroscopy of Guizhou Aspidistra plants. [Method] Twenty three batch- es of Guizhou Aspidistra plants including A. chishuiensis, A. spinula, A. Caespitosa, A. sichuanensis, A. ebianensis, A. retusa, A. guizhouensis and A. liboensis were subjected to drying, pulverization and sieving and then directly determined for near- infrared reflectance spectrums; and the plants in this genus were classified by clus- ter analysis and principal component analysis （PCA）. [Result] The near-infrared re- flectance spectrums of the 23 batches of Guizhou Aspidistra plants showed very high similarity. The spectrums were processed by first derivative method, and the spectral range of 4 000-7 500 cm-1 was selected as the analytical range. Cluster analysis and PCA were employed to mass spectrum variables of plants in Aspidis- tra, fewer new variables became the linear combination of primary variables, and small differences between different varieties were enlarged, thereby facilitating intu- itive classification of plants in this genus. [Conclusion] Near-infrared diffuse re- flectance spectroscopy is nondestructive and rapid for determination of solid sam- pies, and provides a new method for the classification of Guizhou Aspidistra plants combined by information processing techniques.

The Study of Using Near-infrared Diffuse Reflectance Spectroscopy Rapid Identify Wheat Drought Resistance-Ⅱ

[Objective] The aim was to build an evaluation method rapidly identifying wheat drought tolerance with near infrared diffuse reflectance spectroscopy. [Method] In the research, 36 wheat varieties in 2007-2009 were chosen and drought-tolerance degrees of wheat were graded and identified according to Winter-wheat Drought Tol- erance Evaluation Technical Standards （GB/T 21127-2007）, and harvest wheat grains underwent spectrum collection, with a full-spectrum analyzer, to establish a database. [Result] Based on qualitative analysis and full-spectrum correlation research, the coef- ficient of determination （RSQ） and cross-validation coefficient of determination （1-VR） were concluded at 0.697 5 and 0.600 2, showing near-infrared diffuse reflectance spectroscopy is of significant differences among wheat varieties and of significant or extremely significant correlation with drought-tolerance indices. [Conclusion] The re- search indicates that to evaluate drought-tolerance of wheat with near-infrared diffuse reflectance spectroscopy is a rapid and feasible way, which is simple, convenient without damages on grains, and of practical values for construction wheat drought-tol- erance evaluation index system and identification of breeding materials.

Supercritical water syntheses of transition metal-doped CeO_2 nano-catalysts for selective catalytic reduction of NO by CO:An in situ diffuse reflectance Fourier transform infrared spectroscopy study

In the present study,we synthesized CeO2 catalysts doped with various transition metals(M=Co,Fe,or Cu)using a supercritical water hydrothermal route,which led to the incorporation of the metal ions in the CeO2 lattice,forming solid solutions.The catalysts were then used for the selective catalytic reduction(SCR)of NO by CO.The Cu‐doped catalyst exhibited the highest SCR activity;it had a T50(i.e.,50%NO conversion)of only 83°C and a T90(i.e.,90%NO conversion)of 126°C.Such an activity was also higher than in many state‐of‐the‐art catalysts.In situ diffuse reflectance Fourier transform infrared spectroscopy suggested that the MOx‐CeO2 catalysts(M=Co and Fe)mainly followed an Eley‐Rideal reaction mechanism for CO‐SCR.In contrast,a Langmuir‐Hinshelwood SCR reaction mechanism occurred in CuO‐CeO2 owing to the presence of Cu+species,which ensured effective adsorption of CO.This explains why CuO‐CeO2 exhibited the highest activity with regard to the SCR of NO by CO.

Application of Near Infrared Diffuse Reflectance Spectroscopy with Radial Basis Function Neural Network to Determination of Rifampincin Isoniazid and Pyrazinamide Tablets

Partial least squares（PLS）,back-propagation neural network（BPNN）and radial basis function neural network（RBFNN）were respectively used for estalishing quantative analysis models with near infrared（NIR）diffuse reflectance spectra for determining the contents of rifampincin（RMP）,isoniazid（INH）and pyrazinamide（PZA）in rifampicin isoniazid and pyrazinamide tablets.Savitzky-Golay smoothing,first derivative,second derivative,fast Fourier transform（FFT）and standard normal variate（SNV）transformation methods were applied to pretreating raw NIR diffuse reflectance spectra.The raw and pretreated spectra were divided into several regions,depending on the average spectrum and RSD spectrum.Principal component analysis（PCA）method was used for analyzing the raw and pretreated spectra in different regions in order to reduce the dimensions of input data.The optimum spectral regions and the models＇ parameters were chosen by comparing the root mean square error of cross-validation（RMSECV）values which were obtained by leave-one-out cross-validation method.The RMSECV values of the RBFNN models for determining the contents of RMP,INH and PZA were 0.00288,0.00226 and 0.00341,respectively.Using these models for predicting the contents of INH,RMP and PZA in prediction set,the RMSEP values were 0.00266,0.00227 and 0.00411,respectively.These results are better than those obtained from PLS models and BPNN models.With additional advantages of fast calculation speed and less dependence on the initial conditions,RBFNN is a suitable tool to model complex systems.

Rapid Identification for Drought Resistance of Wheat Using Near-infrared Diffuse Reflectance Spectroscopy

[Objective] This study aimed to establish an identification system for drought-resistance in wheat by using near-infrared diffuse reflectance spectroscopy. [Method] In 2006-2007, 36 wheat varieties with different drought resistance were selected and were classified according to their drought resistance grades determined by the Technical Specification of Identification and Evaluation for Drought Resistance in Wheat （GB/T 21127-2007）. In addition, the harvested wheat seed samples were spectrally analyzed with FOSS NIRSystems5000 near-infrared spectrum analyzer for grain quality （full spectrum analyzer） and then the forecasted regression equations were established. [Result] After the establishment of a database and validation, dis- criminated functions were obtained. The determination coefficient （RSQ） and coeffi- cients of determination for cross validation （1-VR） in the discriminant function built with seed samples from water stress area were 0.846 0 and 0.781 8, respectively, which indicated that the consistency between drought resistance and spectral charac- teristics in wheat varieties was good, and there was high correlation between the near-infrared diffuse reflectance spectra of seeds and the drought resistance in wheat. [Conclusiou] Under water stress condition, it is feasible to establish a conve- nient, rapid and no-damage identification system for the drought resistance in wheat by using the near-infrared diffuse reflectance spectrum technique to scan wheat seeds.

Monitoring real time polymorphic transformation of sulfanilamide by diffuse reflectance visible spectroscopy

This study investigated the development of a novel approach to surface characterization of drug poly- morphism and the extension of the capabilities of this method to perform ＇real time＇ in situ measure- ments. This was achieved using diffuse reflectance visible （DRV） spectroscopy and dye deposition, using the pH sensitive dye, thymol blue （TB）. Two polymorphs, SFN-β and SFN-γ, of the drug substance sulfanilamide （SFN） were examined. The interaction of adsorbed dye with polymorphs showed different behavior, and thus reported different DRV spectra. Consideration of the acid/base properties of the morphological forms of the drug molecule provided a rationalization of the mechanism of differential coloration by indicator dyes. The kinetics of the polymorphic transformation of SFN polymorphs was monitored using treatment with TB dye and DRV spectroscopy. The thermally-induced transformation fitted a first-order solid-state kinetic model （R2=0.992）, giving a rate constant of 2.43 × 10^- 2 s 1.

Changes in diffuse reflectance spectroscopy properties of hematite in sediments from the North Pacific Ocean and implications for eolian dust evolution history

Eolian dust preserved in deep-sea sediments of the North Pacific Ocean(NPO) is an important recorder of paleoclimatic and paleoenvironmental changes in the Asian inland. To better understand changes in the dust provenances, in this study diffuse reflectance spectroscopy(DRS) was used to extract the eolian signal recorded in sediments of ODP Hole 885 A recovered from the NPO. First, we systematically investigated sieving effects on the DRS data; then band positions of hematite(obtained from the second order derivative curves of the K-M remission function spectrum derived from the DRS) were used to distinguish different provenances of the eolian dust preserved in the pelagic sediments of this hole. Our results show that the sieving(38 μm) process can suppress effectively the experimental errors. Eolian signatures from Chinese Loess Plateau(CLP) sources and non-CLP-sources have been identified in the pelagic sediments of ODP Hole 885 A from the late Pliocene to the early Pleistocene. The provenance differences account for the discrepancies in the eolian records recovered from the pelagic sediments in the NPO and profiles in the CLP. Temporal changes in dust provenances are caused by the latitudinal movement of the westerly jet mainstream. The hematite DRS band position is a useful tool to distinguish the provenance of eolian components preserved in pelagic sediments.

RAPID DETERMINATION OF PROTEIN IN MILLET BY FOURIER TRANSFORM NEAR-INFRARED(FTNIR)DIFFUSE REFLECTANCE SPECTROSCOPY

In this paper,the Fourier transform near-infrared(FTNIR)diffuse reflectance spectroscopy is applied for the rapid determination of protein in millet.The partial least-squares(PLS)regression is successfully used as an effective multivariate calibration technique.The calibration set is composed of 20 standard millet samples that the protein contents were determined by the traditional Kjeldahl method.The optimal model dimension is found to be 5 by cross-validation.22 millet samples were determined by the proposed FTNIR-PLS method.The correlation coefficient between the concentration values obtained by the FTNIR-PLS method and the traditional Kjeldahl method is 0.9805.The standard error of prediction(SEP)is 0.28% and the mean recovery is 100.2%.The proposed method has been successfully applied for the routine analysis of protein in about 10,000 grain samples.

Determination of the Deep Optical Properties of Healthy and Diseased Skin Using Diffuse Reflectance Spectroscopy

In this study, we focused on diffuse reflectance spectroscopy, a rapid and noninvasive spectroscopy technique that has considerable potential for medical diagnosis. In order to better understand and analyze the signals induced by this method, we performed a series of in vivo measurements on healthy and diseased skin. Measurement sites on a human hand and feet were chosen. Some preliminary results obtained on these sites show the feasibility of this technique in clinics.

Synthesis and Diffuse Reflectance Spectrum of Open－framework Cobalt Phosphate DAF－2 From Alcoholic System

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Rapid, Non-Destructive, Textile Classification Using SIMCA on Diffuse Near-Infrared Reflectance Spectra

Soft independent modeling of class analogy (SIMCA) was successful in classifying a large library of 758 commercially available, non-blended samples of acetate, cotton, polyester, rayon, silk and wool 89% - 98% of the time at the 95% confidence level (p = 0.05 significance level). In the present study, cotton and silk had a 62% and 24% chance, respectively, of being classified with their own group and also with rayon. SIMCA correctly identified a counterfeit “silk” sample as polyester. When coupled with diffuse NIR reflectance spectroscopy and a large sample library, SIMCA shows considerable promise as a quick, non-destructive, multivariate method for fiber identification. A major advantage is simplicity. No sample pretreatment of any kind was required, and no adjust-ments were made for fiber origin, manufacturing process residues, topical finishes, weave pattern, or dye content. Increasing the sample library should make the models more robust and improve identification rates over those reported in this paper.

Construction of universal quantitative models for the determination of cefoperazone sodium/sulbactam sodium for injection from different manufacturers using near-infrared reflectance spectroscopy

To develop near-infrared （NIR） reflectance spectroscopic methods for the quantitative analysis of cefoperazone sodium/ sulbactam sodium from different manufacturers for injection powder medicaments. Various powders of cefoperazone sodium/ sulbactam sodium were directly analyzed by non-destructive NIR reflectance spectroscopy using the spectrometer EQUINOX55. Two quantitative methods via integrating sphere （IS） and fiberoptic probe （FOP） models were explored from 6 batches of commercial samples and 42 batches of laboratory samples at a content ranging from 30% to 70% for cefoperazone and 60% to 20% for sulbactam. The root mean square errors of cross validation （RMSECV） and the root mean square errors of prediction （RMSEP） of IS were 1.79% and 2.85%, respectively, for cefoperazone sodium, and were 1.86% and 3.08%, respectively, for sulbactam sodium; and those of FOP were 2.93% and 2.92%, respectively, for cefoperazone sodium, and were 2.23% and 3.01%, respectively, for sulbactam sodium. Based on the ICH guidelines and Ref. 12, the quantitative models were then evaluated in terms of specificity, linearity, accuracy, precision, robustness and model transferability. The non-destructive quantitative NIR methods used in this study are applicable for rapid analysis of injectable powdered drugs from different manufacturers.

Reflectance spectra analysis for mucous assessment

This review report represents an overview of research and development on medical hyperspectral imaging technology and its applications.Spectral imaging technology is attracting attention as a new imaging modality for medical applications,especially in disease diagnosis and image-guided surgery.Considering the recent advances in imaging,this technology provides an opportunity for twodimensional mapping of oxygen saturation(SatO2)of blood with high accuracy,spatial spectral imaging,and its analysis and provides detection and diagnostic information about the tissue physiology and morphology.Multispectral imaging also provides information about tissue oxygenation,perfusion,and potential function during surgery.Analytical algorithm has been examined,and indication of accurate map of relative hemoglobin concentration and SatO2 can be indicated with preferable resolution and frame rate.This technology is expected to provide promising biomedical information in practical use.Several studies suggested that blood flow and SatO2 are associated with gastrointestinal disorders,particularly malignant tumor conditions.The use and analysis of spectroscopic images are expected to potentially play a role in the detection and diagnosis of these diseases.

Titanium dioxide as an adsorbent to enhance the detection ability of near-infrared diffuse reflectance spectroscopy

A method for quantitative determination of fish sperm deoxyribonucleic acid(fsDNA)was developed by using titanium dioxide(TiO2)as an adsorbent and near-infrared diffuse reflectance spectroscopy(NIRDRS).The selective enrichment of fsDNA was proved by comparing the adsorption efficiency of bovine serum albumin,tyrosine and tryptophan,and the low adsorption background of TiO2 was illustrated by comparing the spectra of four commonly-used inorganic adsorbents(alkaline aluminium oxide,neutral aluminium oxide,nano-hydroxyapatite and silica).The spectral feature of fsDNA can be clearly observed in the spectrum of the sample.Partial least squares(PLS)model was built for quantitative determination of fsDNA using 28 solutions,and 13 solutions with interferences were used for validation of the model.The results showed that the correlation coefficient(R)between the predicted and the reference concentration is 0.9727 and the recoveries of the validation samples are in the range of 98.2%-100.7%.

Application of transcutaneous diffuse reflectance spectroscopy in the measurement of blood glucose concentration

In this paper, the propagation characteristics of near-infrared (NIR) light in the palm tissue are analyzed, and the principle and feasibility of using transcutaneous diffuse reflectance spectroscopy for non-invasive blood glucose detection are presented. An optical probe suitable for measuring the diffuse reflectance spectrum of human palm and a non-invasive blood glucose detection system using NIR spectroscopy are designed. Based on this system, oral glucose tolerance tests are performed to measure the blood glucose concentrations of two young healthy volunteers. The partial least square calibration model is then constructed by all individual experimental data. The final result shows that correlation coefficients of the two experiments between the predicted blood glucose concentrations and the reference blood glucose concentrations are 0.9870 and 0.9854, respectively. The root mean square errors of prediction of full cross validation are 0.54 and 0.52 mmol/1, respectively.

Determination of triglycerides in human serum by near-infrared diffuse reflectance spectroscopy using silver mirror as a substrate

Near infrared diffuse reflectance spectroscopy(NIRDRS) has gained wide attention due to its convenience for rapid quantitative analysis of complex samples. A method for rapid analysis of triglycerides in human serum using NIRDRS with silver mirror as the substrate is developed. Due to the even and high reflectance of the silver mirror, the spectral response is enhanced and the background interference is reduced.Furthermore, both linear and nonlinear modeling strategies were investigated adopting the partial least squares(PLS) and least squares support vector regression(LS-SVR), continuous wavelet transform(CWT)was used for spectral preprocessing, and variable selection was tried using Monte Carlo uninformative variable elimination(MC-UVE), randomization test(RT) and competitive adaptive reweighted sampling(CARS) for optimization the models. The results show that the determination coefficient(R) between the predicted and reference concentration is 0.9624 and the root mean squared error of prediction(RMSEP) is 0.21. The maximum deviation of the prediction results is as low as 0.473 mmol/L. The proposed method may provide an alternative method for routine analysis of serum triglycerides in clinical applications.

Determination of Cysteine Using Near-infrared Diffuse Reflectance Spectroscopy with Enrichment via Thiol-maleimide Click Reaction

Enrichment technique has been proved to be an efficient way to make the near-infrared diffuse reflectancespectroscopy（NIRDRS） suitable for micro analysis. However, low selectivity presented by conventional enrichmentmethods makes the quantitative analysis easy to be affected by the coexisting components. In this study, a specificenrichment method with chemical bonding via thiol-maleimide click reaction was used to achieve the reduction of theinterferences. Taking cysteine as the analyzing target, maleimide-functionalized SiO2 nanoparticles were prepared forthe enrichment of cysteine. Then determination of cysteine in aqueous solution and human serum was studied usingthe partial least squares model built from the NIRDRS spectra of the adsorbate. The results show that the concentra-tion that can be quantitatively detected is as low as 2.0 μg/mL, and the correlation coefficient（R） between thereference and predicted concentration is 0.9871 for the validation samples. The recoveries are in the range of89.5%-113.8% for human serum samples in the concentration range of 0--16.2 μg/mL.

Determination of optimal source-detector separation in measuring chromophores in layered tissue with diffuse reflectance

Based on analysis of the relation between mean penetration depth and source-detector separation in a threelayer model with the method of Monte-Carlo simulation, an optimal source-detector separation is derived from the mean penetration depth referring to monitoring the change of chromophores concentration of the sandwiched layer. In order to verify the separation, we perform Monte-Carlo simulations with varied absorption coefficient of the sandwiched layer. All these diffuse reflectances are used to construct a calibration model with the method of partial least square （PLS）. High correlation coefficients and low root mean square error of prediction （RMSEP） at the optimal separation have confirmed correctness of the selection. This technique is expected to show light on noninvasive diagnosis of near-infrared spectroscopy.

Determination of Active Components in a Natural Herb with Near Infrared Spectroscopy Based on Artificial Neural Networks

The non-linear relationships between the contents of ginsenoside Rg 1, Rb 1, Rd and Panax notoginseng saponins(PNS) in Panax notoginseng root herb and the near infrared(NIR) diffuse reflectance spectra of the herb were established by means of artificial neural networks(ANNs). Four three-layered perception feed-forward networks were trained with an error back-propagation algorithm. The significant principal components of the NIR spectral data matrix were utilized as the input of the networks. The networks architecture and parameters were selected so as to offer less prediction errors. Relative prediction errors for Rg 1, Rb 1, Rd and PNS obtained with the optimum ANN models were 8.99%, 6.54%, 8.29%, and 5.17%, respectively, which were superior to those obtained with PLSR methods. It is verified that ANN is a suitable approach to model this complex non-linearity. The developed method is fast, non-destructive and accurate and it provides a new efficient approach for determining the active components in the complex system of natural herbs.